title: Proteases from extreme thermophiles

authors: Coolbear, Tim

subjects: thermophile

abstract: Extremely thermophilic bacteria are those that grow optimally at 65 ℃ or higher. Comparative data are presented on extracellular proteases from two extremely thermophilic eubacteria and one extremely thermophilic archaebacterium. The eubacteria were a Bacillus isolate (protease unnamed) and a Thermus isolate (protease named caldolysin) with optimum growth temperatures of 65 ℃ and 75 ℃, respectively. The archaebacterium was a Desulfurococcus isolate (protease named archaelysin) with an optimum growth temperature of 88 ℃.

text: Proteases from extreme thermophiles Extremely thermophilic bacteria are those that grow optimally at 65 ℃ or higher. Comparative data are presented on extracellular proteases from two extremely thermophilic eubacteria and one extremely thermophilic archaebacterium. The eubacteria were a Bacillus isolate (protease unnamed) and a Thermus isolate (protease named caldolysin) with optimum growth temperatures of 65 ℃ and 75 ℃, respectively. The archaebacterium was a Desulfurococcus isolate (protease named archaelysin) with an optimum growth temperature of 88 ℃.

year: 1988

title: Building ensembles of adaptive nested dichotomies with random-pair selection

authors: Leathart, Tim

subjects: computer science

abstract: A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems. Such a system recursively applies binary splits to divide the set of classes into two subsets, and trains a binary classifier for each split. Although ensembles of nested dichotomies with random structure have been shown to perform well in practice, using a more sophisticated class subset selection method can be used to improve classification accuracy. We investigate an approach to this problem called random-pair selection, and evaluate its effectiveness compared to other published methods of subset selection. We show that our method outperforms other methods in many cases when forming ensembles of nested dichotomies, and is at least on par in all other cases. The software related to this paper is available at https://svn.cms.waikato.ac.nz/svn/weka/trunk/packages/ internal/ensemblesOfNestedDichotomies/.

text: Building ensembles of adaptive nested dichotomies with random-pair selection A system of nested dichotomies is a method of decomposing a multi-class problem into a collection of binary problems. Such a system recursively applies binary splits to divide the set of classes into two subsets, and trains a binary classifier for each split. Although ensembles of nested dichotomies with random structure have been shown to perform well in practice, using a more sophisticated class subset selection method can be used to improve classification accuracy. We investigate an approach to this problem called random-pair selection, and evaluate its effectiveness compared to other published methods of subset selection. We show that our method outperforms other methods in many cases when forming ensembles of nested dichotomies, and is at least on par in all other cases. The software related to this paper is available at https://svn.cms.waikato.ac.nz/svn/weka/trunk/packages/ internal/ensemblesOfNestedDichotomies/.

year: 2016

title: Implementation framework for chronic disease intervention effectiveness in Maori and other indigenous communities

authors: Oetzel, John G.

subjects: Science & Technology

abstract: Background: About 40% of all health burden in New Zealand is due to cancer, cardiovascular disease, and type 2 diabetes/obesity. Outcomes for Māori (indigenous people) are significantly worse than non-Maori; these inequities mirror those found in indigenous communities elsewhere. Evidence-based interventions with established efficacy may not be effective in indigenous communities without addressing specific implementation challenges. We present an implementation framework for interventions to prevent and treat chronic conditions for Māori and other indigenous communities.
Theoretical framework: The He Pikinga Waiora Implementation Framework has indigenous self-determination at its core and consists of four elements: cultural-centeredness, community engagement, systems thinking, and integrated knowledge translation. All elements have conceptual fit with Kaupapa Māori aspirations (i.e., indigenous knowledge creation, theorizing, and methodology) and all have demonstrated evidence of positive implementation outcomes.
Applying the framework: A coding scheme derived from the Framework was applied to 13 studies of diabetes prevention in indigenous communities in Australia, Canada, New Zealand, and the United States from a systematic review. Cross-tabulations demonstrated that culture-centeredness (p = .008) and community engagement (p = .009) explained differences in diabetes outcomes and community engagement (p = .098) explained difference in blood pressure outcomes.
Implications and conclusions: The He Pikinga Waiora Implementation Framework appears to be well suited to advance implementation science for indigenous communities in general and Māori in particular. The framework has promise as a policy and planning tool to evaluate and design effective interventions for chronic disease prevention in indigenous communities.

text: Implementation framework for chronic disease intervention effectiveness in Maori and other indigenous communities Background: About 40% of all health burden in New Zealand is due to cancer, cardiovascular disease, and type 2 diabetes/obesity. Outcomes for Māori (indigenous people) are significantly worse than non-Maori; these inequities mirror those found in indigenous communities elsewhere. Evidence-based interventions with established efficacy may not be effective in indigenous communities without addressing specific implementation challenges. We present an implementation framework for interventions to prevent and treat chronic conditions for Māori and other indigenous communities.
Theoretical framework: The He Pikinga Waiora Implementation Framework has indigenous self-determination at its core and consists of four elements: cultural-centeredness, community engagement, systems thinking, and integrated knowledge translation. All elements have conceptual fit with Kaupapa Māori aspirations (i.e., indigenous knowledge creation, theorizing, and methodology) and all have demonstrated evidence of positive implementation outcomes.
Applying the framework: A coding scheme derived from the Framework was applied to 13 studies of diabetes prevention in indigenous communities in Australia, Canada, New Zealand, and the United States from a systematic review. Cross-tabulations demonstrated that culture-centeredness (p = .008) and community engagement (p = .009) explained differences in diabetes outcomes and community engagement (p = .098) explained difference in blood pressure outcomes.
Implications and conclusions: The He Pikinga Waiora Implementation Framework appears to be well suited to advance implementation science for indigenous communities in general and Māori in particular. The framework has promise as a policy and planning tool to evaluate and design effective interventions for chronic disease prevention in indigenous communities.

year: 2017