title: Synthetic, structural, electrochemical, and theoretical studies of heterometallic aggregates with a [Pt₂(μ-S)₂M] Core (M = Hg, Au)

authors: Xu, Xingling

subjects: heterometallic aggregates

abstract: Novel electroactive multimetallic compounds based on the {Pt₂(μ₂-S)₂M} core, viz. [Pt₂(PPh₃)₄(μ₃-S)₂HgFc]PF₆ (1) [Fc = (η⁵-C₅H₄)Fe(η⁵-C₅H₅)] and [Pt₂(PPh₃)₄(μ₃-S)₂Hg₂Fc⁶](PF₆)₂ (2) [Fc⁶ = Fe(η⁵-C₅H₄)₂], have been synthesized under the guide of electrospray mass spectrometry. The electrochemistry of these ferrocene funtionalized compounds together with the reported [Pt₂(PPh₃)₄(μ₃-S)₂HgPPh₃](PF₆)₂ (3), [Pt₂(PPh₃)₄(μ₂-S)(μ₃-S)HgPh]PF₆ (4), and [Pt₂(PPh₃)₄(μ₂-S)(μ₃-S)AuPPh₃]PF₆ (5) have been investigated using cyclic voltammetry and DFT calculations. These results point to a prominent ligand-based oxidation.

text: Synthetic, structural, electrochemical, and theoretical studies of heterometallic aggregates with a [Pt₂(μ-S)₂M] Core (M = Hg, Au) Novel electroactive multimetallic compounds based on the {Pt₂(μ₂-S)₂M} core, viz. [Pt₂(PPh₃)₄(μ₃-S)₂HgFc]PF₆ (1) [Fc = (η⁵-C₅H₄)Fe(η⁵-C₅H₅)] and [Pt₂(PPh₃)₄(μ₃-S)₂Hg₂Fc⁶](PF₆)₂ (2) [Fc⁶ = Fe(η⁵-C₅H₄)₂], have been synthesized under the guide of electrospray mass spectrometry. The electrochemistry of these ferrocene funtionalized compounds together with the reported [Pt₂(PPh₃)₄(μ₃-S)₂HgPPh₃](PF₆)₂ (3), [Pt₂(PPh₃)₄(μ₂-S)(μ₃-S)HgPh]PF₆ (4), and [Pt₂(PPh₃)₄(μ₂-S)(μ₃-S)AuPPh₃]PF₆ (5) have been investigated using cyclic voltammetry and DFT calculations. These results point to a prominent ligand-based oxidation.

year: 2002

title: Using weighted nearest neighbor to benefit from unlabeled data

authors: Driessens, Kurt

subjects: computer science

abstract: The development of data-mining applications such as textclassification and molecular profiling has shown the need for machine learning algorithms that can benefit from both labeled and unlabeled data, where often the unlabeled examples greatly outnumber the labeled examples. In this paper we present a two-stage classifier that improves its predictive accuracy by making use of the available unlabeled data. It uses a weighted nearest neighbor classification algorithm using the combined example-sets as a knowledge base. The examples from the unlabeled set are “pre-labeled” by an initial classifier that is build using the limited available training data. By choosing appropriate weights for this pre-labeled data, the nearest neighbor classifier consistently improves on the original classifier.

text: Using weighted nearest neighbor to benefit from unlabeled data The development of data-mining applications such as textclassification and molecular profiling has shown the need for machine learning algorithms that can benefit from both labeled and unlabeled data, where often the unlabeled examples greatly outnumber the labeled examples. In this paper we present a two-stage classifier that improves its predictive accuracy by making use of the available unlabeled data. It uses a weighted nearest neighbor classification algorithm using the combined example-sets as a knowledge base. The examples from the unlabeled set are “pre-labeled” by an initial classifier that is build using the limited available training data. By choosing appropriate weights for this pre-labeled data, the nearest neighbor classifier consistently improves on the original classifier.

year: 2006

title: Akoranga whakarei: Learning about inclusion from four kura rumaki

authors: Berryman, Mere

subjects: Special education

abstract: In 2004 the New Zealand Ministry of Education proposed two research projects to understand how learning, social and cultural outcomes were being promoted for tamariki and rangatahi Māori with special educational needs in both kura auraki (English-medium schools) and kura rumaki (Māori-medium schools). 1hey also wanted to understand how this played out for other whānau members. At the time, a description of the services being promoted for Māori with special education needs acknowledged the philosophy that "tamariki and rangatahi with special needs and their whānau learn effectively through the provision of culturally competent services, which will ensure mana and tikanga are upheld" (Ministry of Education, 2003, p. 56). 
This chapter will briefly describe how this research was undertaken in kura rumaki and then discuss the findings that emerged. Perhaps not surprisingly, it will show that the staff from the kura who participated in this study, as with all of their students and whānau, had a very holistic and inclusive view of educating all tamariki and rangatahi, especially those with identified special education needs. The conclusion will consider some of the implications of these findings for others and propose that these research outcomes maintain relevance in 2014, a decade later.

text: Akoranga whakarei: Learning about inclusion from four kura rumaki In 2004 the New Zealand Ministry of Education proposed two research projects to understand how learning, social and cultural outcomes were being promoted for tamariki and rangatahi Māori with special educational needs in both kura auraki (English-medium schools) and kura rumaki (Māori-medium schools). 1hey also wanted to understand how this played out for other whānau members. At the time, a description of the services being promoted for Māori with special education needs acknowledged the philosophy that "tamariki and rangatahi with special needs and their whānau learn effectively through the provision of culturally competent services, which will ensure mana and tikanga are upheld" (Ministry of Education, 2003, p. 56). 
This chapter will briefly describe how this research was undertaken in kura rumaki and then discuss the findings that emerged. Perhaps not surprisingly, it will show that the staff from the kura who participated in this study, as with all of their students and whānau, had a very holistic and inclusive view of educating all tamariki and rangatahi, especially those with identified special education needs. The conclusion will consider some of the implications of these findings for others and propose that these research outcomes maintain relevance in 2014, a decade later.

year: 2015