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Patent
Science and Research GmbH | Date: 2016-11-11

Treatment of vaginal mycoses, bacterial vaginoses, and other forms of the vaginitis (inflammation of the vagina) by clinoptilolite having a particle size of between 0.2 and 10 m. Clinoptilolite, when used externally, is effective in the treatment of these vaginal disorders in mammals and humans, and also for restoring a healthy vaginal microbiota. The clinoptilolite may be used with one or more of the following adjuvants: pharmaceutically acceptable carrier materials, viable microorganisms and/or extracts thereof, nutrients for the healthy vaginal microbiota (e.g. lactose, etc.), and/or substances which favorably influence the vaginal environment for the healthy vaginal microbiota (e.g. estradiol, organic acids, etc.). The composition used may be applied locally, preferably in one of the following administration forms: foam, suppository, vaginal tablet, ovule, gel, aerosol, powder, rinse, douche, cream/ointment, or suspension.


News Article | May 26, 2017
Site: www.chromatographytechniques.com

With rain forests at risk the world over, a new collaboration is equipping conservationists with the tools to predict and plan for future forest loss. A new study by scientists from the Universities of Oxford, Montana and the U.S. Forest Service highlights novel approaches to tackling deforestation. The team focused their research on Borneo, an island that has lost a staggering 30 percent of its forest since the 1970s and is among the most biodiverse and threatened on the planet. The loss of Bornean forests threatens species such as the orangutan, Sumatran rhino, and the Sunda clouded leopard; as well as emitting significant amounts of carbon dioxide into the atmosphere. Although focused on Borneo, the study findings, published in Landscape Ecology, will be useful to all forest conservationists, and could help tropical forests around the world. The study took an innovative approach to conducting their data analysis, using existing maps of the area and the machine learning algorithm “Random Forests,” the team built a multi-scale model of deforestation on the island over time (from 2000- 2010). After calculating the historic links between landscape variables and deforestation, the team used this information to predict the future deforestation risk facing Borneo's remaining forests. The goal of this study was to provide national authorities with a tool that would support them to recognize potential deforestation threats in the future. The deforestation risk factors varied from nation to nation, within the island. In Brunei, deforestation was associated with a highly patchy landscape with multiple land uses within a 10km radius and a large amount of forest edge. By contrast, in the Malaysian provinces of Borneo, deforestation was associated with a high proportion of lowland mosaic landscape types within 20km and high proportions of existing plantations within 30km. This led to a diffuse pattern of risk across Malaysian forests. Finally, in the Indonesian provinces of Borneo, deforestation was associated with areas of low elevation and a highly patchy landscape, leading to strong frontiers of deforestation risk. “Our results provide the best insight to date of where the highest risks lie to Borneo's remaining forests. I hope this will help governments and conservation planners to develop effective strategies to combat these risks and to conserve these beautiful forests for future generations,” said Ewan Macdonald, joint first author and a researcher in Oxford's Wildlife Conservation Research Unit (WildCRU). “If we understand where risks lurk, we can plan action to counteract them. And these risks are real and imminent for many species, such as the beautiful and enigmatic Sunda clouded leopard, which are threatened by Borneo's forest loss. I hope our understanding of the patterns of deforestation risk will provide a vital tool in developing effective conservation strategies.” The research findings strongly suggest that this novel approach offer a powerful method for analyzing land use change. In addition, it highlights the immense and imminent deforestation risk to Borneo's forest biodiversity, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo. “It is well accepted that ecological processes interact across a range of scales both in time and space; despite this, very few studies have explicitly accounted for scale dependence in predictive modeling. This analysis highlights the power of multi scale approaches to land cover change modeling and we hope it will encourage other researchers to adopt this approach,” said Samuel Cushman, joint first author, director of the Center for Landscape Science and Research Landscape Ecologist at the U.S. Forest Service Rocky Mountain Research Station. “Borneo's majestic forests and glorious wildlife are beacons to the world and what's so exciting about this study is that the intelligence gained from studying patterns in Borneo, sheds a light to illuminate a way of helping tropical forests around the world. The innovation lies in a methodology that can be rolled out far beyond Borneo,” said David Macdonald, director of Oxford's Wildlife Conservation Research Unit.


HOUSTON--(BUSINESS WIRE)--PROS® (NYSE: PRO), a cloud software company powering the shift to modern commerce, today announced that Darius Walczak, Ph.D., a Principal Research Scientist on the company’s Science and Research team, will deliver a revenue management research presentation at the Third Workshop on Marketplace Innovation. Scheduled for June 1-2, the conference will be held at Stanford University in Stanford, Calif. The conference will examine a host of market variables such as pricing, visibility and terms of trade, and the complexities companies face in dealing with new modeling and theory to drive revenue. Walczak will deliver a poster presentation titled “Dynamic Pricing Game with a Loyal Demand Component.” He will analyze a market model where two carriers compete for price-sensitive customers and provide insights into how market equilibrium is affected when some of the customers are loyal to each carrier. “The move to modern commerce strategies is creating a dramatic shift in how companies do business,” said PROS Senior Vice President of Science and User Experience Jeff Robinson. “At PROS, our customers look to us for our decades of market experience, which we combine with advances in cognitive computing and machine learning. We help companies profitably price and sell their products and services with speed, precision and consistency, powered by next-generation dynamic pricing. We are honored that Darius Walczak will present next-generation revenue management research at this prestigious industry event.” To learn more about the conference, visit www.pros.com or follow PROS on Twitter at @PROS_Inc. PROS Holdings, Inc. (NYSE: PRO) is a cloud software company powering the shift to modern commerce by helping companies create personalized and frictionless buying experiences for their customers. Fueled by dynamic pricing science and machine learning, PROS solutions make it possible for companies to price, configure and sell their products and services in an omnichannel environment with speed, precision and consistency. Our customers, who are leaders in their markets, benefit from decades of data science expertise infused into our industry solutions. To learn more, visit pros.com. This press release contains forward-looking statements, including statements about the functionality and benefits of revenue and profit realization software to organizations generally as well as the functionality and benefits of PROS software products. The forward-looking statements contained in this press release are based upon PROS historical experience with revenue and profit realization software and its current expectations of the benefits of revenue and profit realization software for organizations that implement and utilize such software. Factors that could cause actual results to differ materially from those described herein include the addressability of an organization’s revenue and profit realization software needs, the risks associated with PROS developing and enhancing products with the functionality necessary to deliver the stated results and the risks associated with the complex implementation and maintenance of revenue and profit realization software such as PROS software products. Additional information relating to the uncertainty affecting the PROS business is contained in PROS filings with the Securities and Exchange Commission. These forward-looking statements represent PROS expectations as of the date of this press release. Subsequent events may cause these expectations to change, and PROS disclaims any obligations to update or alter these forward-looking statements in the future whether as a result of new information, future events or otherwise.


News Article | May 25, 2017
Site: www.sciencedaily.com

With rain forests at risk the world over, a new collaboration is equipping conservationists with the tools to predict and plan for future forest loss. A new study by scientists from the Universities of Oxford, Montana and the US Forest Service highlights novel approaches to tackling deforestation. The team focused their research on Borneo, an island that has lost a staggering 30 percent of its forest since the 1970s and is among the most biodiverse and threatened on the planet. The loss of Bornean forests threatens species such as the orangutan, Sumatran rhino, and the Sunda clouded leopard; as well as emitting significant amounts of carbon dioxide into the atmosphere. Although focussed on Borneo, the study findings, published in Landscape Ecology, will be useful to all forest conservationists, and could help tropical forests around the world. The study took an innovative approach to conducting their data analysis, using existing maps of the area and the machine learning algorithm 'Random Forests', the team built a multi-scale model of deforestation on the island over time (from 2000- 2010). After calculating the historic links between landscape variables and deforestation, the team used this information to predict the future deforestation risk facing Borneo's remaining forests. The goal of this study was to provide national authorities with a tool that would support them to recognise potential deforestation threats in the future. The deforestation risk factors varied from nation to nation, within the island. In Brunei, deforestation was associated with a highly patchy landscape with multiple land uses within a 10km radius and a large amount of forest edge. By contrast, in the Malaysian provinces of Borneo, deforestation was associated with a high proportion of lowland mosaic landscape types within 20km and high proportions of existing plantations within 30km. This led to a diffuse pattern of risk across Malaysian forests. Finally, in the Indonesian provinces of Borneo, deforestation was associated with areas of low elevation and a highly patchy landscape, leading to strong frontiers of deforestation risk. Ewan Macdonald, joint first author and a researcher in Oxford's Wildlife Conservation Research Unit (WildCRU) said: 'Our results provide the best insight to date of where the highest risks lie to Borneo's remaining forests. I hope this will help governments and conservation planners to develop effective strategies to combat these risks and to conserve these beautiful forests for future generations. 'If we understand where risks lurk, we can plan action to counteract them. And these risks are real and imminent for many species, such as the beautiful and enigmatic Sunda clouded leopard, which are threatened by Borneo's forest loss. I hope our understanding of the patterns of deforestation risk will provide a vital tool in developing effective conservation strategies.' The research findings strongly suggest that this novel approach offer a powerful method for analysing land use change. In addition, it highlights the immense and imminent deforestation risk to Borneo's forest biodiversity, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo. Samuel Cushman, joint first author, Director of the Center for Landscape Science and Research Landscape Ecologist at the U.S. Forest Service Rocky Mountain Research Station said: 'It is well accepted that ecological processes interact across a range of scales both in time and space; despite this, very few studies have explicitly accounted for scale dependence in predictive modelling. This analysis highlights the power of multi scale approaches to land cover change modelling and we hope it will encourage other researchers to adopt this approach.' Professor David Macdonald, Director of Oxford's Wildlife Conservation Research Unit said: 'Borneo's majestic forests and glorious wildlife are beacons to the world and what's so exciting about this study is that the intelligence gained from studying patterns in Borneo, sheds a light to illuminate a way of helping tropical forests around the world. The innovation lies in a methodology that can be rolled out far beyond Borneo.'


News Article | May 25, 2017
Site: www.rdmag.com

With rain forests at risk the world over, a new collaboration is equipping conservationists with the tools to predict and plan for future forest loss. A new study by scientists from the Universities of Oxford, Montana and the US Forest Service highlights novel approaches to tackling deforestation. The team focused their research on Borneo, an island that has lost a staggering 30 percent of its forest since the 1970s and is among the most biodiverse and threatened on the planet. The loss of Bornean forests threatens species such as the orangutan, Sumatran rhino, and the Sunda clouded leopard; as well as emitting significant amounts of carbon dioxide into the atmosphere. Although focussed on Borneo, the study findings, published in Landscape Ecology, will be useful to all forest conservationists, and could help tropical forests around the world. The study took an innovative approach to conducting their data analysis, using existing maps of the area and the machine learning algorithm 'Random Forests', the team built a multi-scale model of deforestation on the island over time (from 2000- 2010). After calculating the historic links between landscape variables and deforestation, the team used this information to predict the future deforestation risk facing Borneo's remaining forests. The goal of this study was to provide national authorities with a tool that would support them to recognise potential deforestation threats in the future. The deforestation risk factors varied from nation to nation, within the island. In Brunei, deforestation was associated with a highly patchy landscape with multiple land uses within a 10km radius and a large amount of forest edge. By contrast, in the Malaysian provinces of Borneo, deforestation was associated with a high proportion of lowland mosaic landscape types within 20km and high proportions of existing plantations within 30km. This led to a diffuse pattern of risk across Malaysian forests. Finally, in the Indonesian provinces of Borneo, deforestation was associated with areas of low elevation and a highly patchy landscape, leading to strong frontiers of deforestation risk. Ewan Macdonald, joint first author and a researcher in Oxford's Wildlife Conservation Research Unit (WildCRU) said: 'Our results provide the best insight to date of where the highest risks lie to Borneo's remaining forests. I hope this will help governments and conservation planners to develop effective strategies to combat these risks and to conserve these beautiful forests for future generations. 'If we understand where risks lurk, we can plan action to counteract them. And these risks are real and imminent for many species, such as the beautiful and enigmatic Sunda clouded leopard, which are threatened by Borneo's forest loss. I hope our understanding of the patterns of deforestation risk will provide a vital tool in developing effective conservation strategies.' The research findings strongly suggest that this novel approach offer a powerful method for analysing land use change. In addition, it highlights the immense and imminent deforestation risk to Borneo's forest biodiversity, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo. Samuel Cushman, joint first author, Director of the Center for Landscape Science and Research Landscape Ecologist at the U.S. Forest Service Rocky Mountain Research Station said: 'It is well accepted that ecological processes interact across a range of scales both in time and space; despite this, very few studies have explicitly accounted for scale dependence in predictive modelling. This analysis highlights the power of multi scale approaches to land cover change modelling and we hope it will encourage other researchers to adopt this approach.' Professor David Macdonald, Director of Oxford's Wildlife Conservation Research Unit said: 'Borneo's majestic forests and glorious wildlife are beacons to the world and what's so exciting about this study is that the intelligence gained from studying patterns in Borneo, sheds a light to illuminate a way of helping tropical forests around the world. The innovation lies in a methodology that can be rolled out far beyond Borneo.'


News Article | May 25, 2017
Site: phys.org

A new study by scientists from the Universities of Oxford, Montana and the US Forest Service highlights novel approaches to tackling deforestation. The team focused their research on Borneo, an island that has lost a staggering 30 percent of its forest since the 1970s and is among the most biodiverse and threatened on the planet. The loss of Bornean forests threatens species such as the orangutan, Sumatran rhino, and the Sunda clouded leopard; as well as emitting significant amounts of carbon dioxide into the atmosphere. Although focussed on Borneo, the study findings, published in Landscape Ecology, will be useful to all forest conservationists, and could help tropical forests around the world. The study took an innovative approach to conducting their data analysis, using existing maps of the area and the machine learning algorithm 'Random Forests', the team built a multi-scale model of deforestation on the island over time (from 2000- 2010). After calculating the historic links between landscape variables and deforestation, the team used this information to predict the future deforestation risk facing Borneo's remaining forests. The goal of this study was to provide national authorities with a tool that would support them to recognise potential deforestation threats in the future. The deforestation risk factors varied from nation to nation, within the island. In Brunei, deforestation was associated with a highly patchy landscape with multiple land uses within a 10km radius and a large amount of forest edge. By contrast, in the Malaysian provinces of Borneo, deforestation was associated with a high proportion of lowland mosaic landscape types within 20km and high proportions of existing plantations within 30km. This led to a diffuse pattern of risk across Malaysian forests. Finally, in the Indonesian provinces of Borneo, deforestation was associated with areas of low elevation and a highly patchy landscape, leading to strong frontiers of deforestation risk. Ewan Macdonald, joint first author and a researcher in Oxford's Wildlife Conservation Research Unit (WildCRU) said: 'Our results provide the best insight to date of where the highest risks lie to Borneo's remaining forests. I hope this will help governments and conservation planners to develop effective strategies to combat these risks and to conserve these beautiful forests for future generations. 'If we understand where risks lurk, we can plan action to counteract them. And these risks are real and imminent for many species, such as the beautiful and enigmatic Sunda clouded leopard, which are threatened by Borneo's forest loss. I hope our understanding of the patterns of deforestation risk will provide a vital tool in developing effective conservation strategies.' The research findings strongly suggest that this novel approach offer a powerful method for analysing land use change. In addition, it highlights the immense and imminent deforestation risk to Borneo's forest biodiversity, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo. Samuel Cushman, joint first author, Director of the Center for Landscape Science and Research Landscape Ecologist at the U.S. Forest Service Rocky Mountain Research Station said: 'It is well accepted that ecological processes interact across a range of scales both in time and space; despite this, very few studies have explicitly accounted for scale dependence in predictive modelling. This analysis highlights the power of multi scale approaches to land cover change modelling and we hope it will encourage other researchers to adopt this approach.' Professor David Macdonald, Director of Oxford's Wildlife Conservation Research Unit said: 'Borneo's majestic forests and glorious wildlife are beacons to the world and what's so exciting about this study is that the intelligence gained from studying patterns in Borneo, sheds a light to illuminate a way of helping tropical forests around the world. The innovation lies in a methodology that can be rolled out far beyond Borneo.' Explore further: New population of endangered cats found in Borneo More information: Samuel A. Cushman et al, Multiple-scale prediction of forest loss risk across Borneo, Landscape Ecology (2017). DOI: 10.1007/s10980-017-0520-0


News Article | May 25, 2017
Site: www.eurekalert.org

With rain forests at risk the world over, a new collaboration is equipping conservationists with the tools to predict and plan for future forest loss. A new study by scientists from the Universities of Oxford, Montana and the US Forest Service highlights novel approaches to tackling deforestation. The team focused their research on Borneo, an island that has lost a staggering 30 percent of its forest since the 1970s and is among the most biodiverse and threatened on the planet. The loss of Bornean forests threatens species such as the orangutan, Sumatran rhino, and the Sunda clouded leopard; as well as emitting significant amounts of carbon dioxide into the atmosphere. Although focussed on Borneo, the study findings, published in Landscape Ecology, will be useful to all forest conservationists, and could help tropical forests around the world. The study took an innovative approach to conducting their data analysis, using existing maps of the area and the machine learning algorithm 'Random Forests', the team built a multi-scale model of deforestation on the island over time (from 2000- 2010). After calculating the historic links between landscape variables and deforestation, the team used this information to predict the future deforestation risk facing Borneo's remaining forests. The goal of this study was to provide national authorities with a tool that would support them to recognise potential deforestation threats in the future. The deforestation risk factors varied from nation to nation, within the island. In Brunei, deforestation was associated with a highly patchy landscape with multiple land uses within a 10km radius and a large amount of forest edge. By contrast, in the Malaysian provinces of Borneo, deforestation was associated with a high proportion of lowland mosaic landscape types within 20km and high proportions of existing plantations within 30km. This led to a diffuse pattern of risk across Malaysian forests. Finally, in the Indonesian provinces of Borneo, deforestation was associated with areas of low elevation and a highly patchy landscape, leading to strong frontiers of deforestation risk. Ewan Macdonald, joint first author and a researcher in Oxford's Wildlife Conservation Research Unit (WildCRU) said: 'Our results provide the best insight to date of where the highest risks lie to Borneo's remaining forests. I hope this will help governments and conservation planners to develop effective strategies to combat these risks and to conserve these beautiful forests for future generations. 'If we understand where risks lurk, we can plan action to counteract them. And these risks are real and imminent for many species, such as the beautiful and enigmatic Sunda clouded leopard, which are threatened by Borneo's forest loss. I hope our understanding of the patterns of deforestation risk will provide a vital tool in developing effective conservation strategies.' The research findings strongly suggest that this novel approach offer a powerful method for analysing land use change. In addition, it highlights the immense and imminent deforestation risk to Borneo's forest biodiversity, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo. Samuel Cushman, joint first author, Director of the Center for Landscape Science and Research Landscape Ecologist at the U.S. Forest Service Rocky Mountain Research Station said: 'It is well accepted that ecological processes interact across a range of scales both in time and space; despite this, very few studies have explicitly accounted for scale dependence in predictive modelling. This analysis highlights the power of multi scale approaches to land cover change modelling and we hope it will encourage other researchers to adopt this approach.' Professor David Macdonald, Director of Oxford's Wildlife Conservation Research Unit said: 'Borneo's majestic forests and glorious wildlife are beacons to the world and what's so exciting about this study is that the intelligence gained from studying patterns in Borneo, sheds a light to illuminate a way of helping tropical forests around the world. The innovation lies in a methodology that can be rolled out far beyond Borneo.' The study is described in the paper "Multiple-scale prediction of forest loss risk across Borneo" published in the journal Landscape Ecology. https:/ Map from the study showing the predicted risk of deforestation across Borneo's remaining forests. Red areas represent areas of highest risk. Photo of a Sunda clouded leopard captured as part of a WildCRU study into their ecology in Malaysian Borneo. Deforestation is one of the biggest threats to clouded leopards. (Photo Credit: Andrew Hearn, WildCRU) For interviews or supporting images please contact: Lanisha Butterfield, Media Relations Manager on 01865 280531 or lanisha.butterfield@admin.ox.ac.uk David Macdonald founded the Wildlife Conservation Research Unit (WildCRU) in 1986 at the University of Oxford. Now the foremost University-based centre for biodiversity conservation, the mission of the WildCRU is to achieve practical solutions to conservation problems through original research. WildCRU is renowned for its specialisation in wild carnivores, especially wild cats, for its long-running studies on lion and clouded leopard, and for its training centre, where early-career conservationists, so far from 32 countries, are trained by experts to become leaders in conservation, resulting in a global community of highly skilled and collaborative conservationists. Visit wildcru.org About the U.S. Forest Service The mission of the Forest Service, part of the U.S. Department of Agriculture, is to sustain the health, diversity, and productivity of the Nation's forests and grasslands to meet the needs of present and future generations. The agency manages 193 million acres of public land, provides assistance to state and private landowners, and maintains the largest forestry research organization in the world. USDA is an equal opportunity provider, employer, and lender. The Mathematical, Physical and Life Sciences Division (MPLS) is one of four academic divisions at the University of Oxford, representing the non-medical sciences. Oxford is one of the world's leading universities for science, and MPLS is at the forefront of scientific research across a wide range of disciplines. Research in the mathematical, physical and life sciences at Oxford was rated the best in the UK in the 2014 Research Excellence Framework


News Article | May 26, 2017
Site: www.chromatographytechniques.com

With rain forests at risk the world over, a new collaboration is equipping conservationists with the tools to predict and plan for future forest loss. A new study by scientists from the Universities of Oxford, Montana and the U.S. Forest Service highlights novel approaches to tackling deforestation. The team focused their research on Borneo, an island that has lost a staggering 30 percent of its forest since the 1970s and is among the most biodiverse and threatened on the planet. The loss of Bornean forests threatens species such as the orangutan, Sumatran rhino, and the Sunda clouded leopard; as well as emitting significant amounts of carbon dioxide into the atmosphere. Although focused on Borneo, the study findings, published in Landscape Ecology, will be useful to all forest conservationists, and could help tropical forests around the world. The study took an innovative approach to conducting their data analysis, using existing maps of the area and the machine learning algorithm “Random Forests,” the team built a multi-scale model of deforestation on the island over time (from 2000- 2010). After calculating the historic links between landscape variables and deforestation, the team used this information to predict the future deforestation risk facing Borneo's remaining forests. The goal of this study was to provide national authorities with a tool that would support them to recognize potential deforestation threats in the future. The deforestation risk factors varied from nation to nation, within the island. In Brunei, deforestation was associated with a highly patchy landscape with multiple land uses within a 10km radius and a large amount of forest edge. By contrast, in the Malaysian provinces of Borneo, deforestation was associated with a high proportion of lowland mosaic landscape types within 20km and high proportions of existing plantations within 30km. This led to a diffuse pattern of risk across Malaysian forests. Finally, in the Indonesian provinces of Borneo, deforestation was associated with areas of low elevation and a highly patchy landscape, leading to strong frontiers of deforestation risk. “Our results provide the best insight to date of where the highest risks lie to Borneo's remaining forests. I hope this will help governments and conservation planners to develop effective strategies to combat these risks and to conserve these beautiful forests for future generations,” said Ewan Macdonald, joint first author and a researcher in Oxford's Wildlife Conservation Research Unit (WildCRU). “If we understand where risks lurk, we can plan action to counteract them. And these risks are real and imminent for many species, such as the beautiful and enigmatic Sunda clouded leopard, which are threatened by Borneo's forest loss. I hope our understanding of the patterns of deforestation risk will provide a vital tool in developing effective conservation strategies.” The research findings strongly suggest that this novel approach offer a powerful method for analyzing land use change. In addition, it highlights the immense and imminent deforestation risk to Borneo's forest biodiversity, with clear spatial patterns of risk related to topography and landscape structure that differ between the three nations that comprise Borneo. “It is well accepted that ecological processes interact across a range of scales both in time and space; despite this, very few studies have explicitly accounted for scale dependence in predictive modeling. This analysis highlights the power of multi scale approaches to land cover change modeling and we hope it will encourage other researchers to adopt this approach,” said Samuel Cushman, joint first author, director of the Center for Landscape Science and Research Landscape Ecologist at the U.S. Forest Service Rocky Mountain Research Station. “Borneo's majestic forests and glorious wildlife are beacons to the world and what's so exciting about this study is that the intelligence gained from studying patterns in Borneo, sheds a light to illuminate a way of helping tropical forests around the world. The innovation lies in a methodology that can be rolled out far beyond Borneo,” said David Macdonald, director of Oxford's Wildlife Conservation Research Unit.

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