title: Salinity indicators in sediment through the fluvial-to-marine transition (Fraser River, Canada).

authors: Dashtgard, Shahin E.

subjects: Canada

abstract: Many sediment attributes have been proposed as proxies for determining salinity conditions under which sediment is deposited, and six attributes (Sr/Ba-HAc, Sr/Ba-NH4Ac, δ13Corg, C/N, and the relative abundances and concentrations of dinoflagellate cysts) are compared here. In this paper, sediment attributes from the Fraser River Delta, Canada and surrounding coastal areas are compared by depositional position along the fluvial-to-marine transition, by salinity, and by sedimentological characteristics. Along the fluvial-to-marine transition, most attributes exhibit distinct trends between parts of the river that experience sustained marine water (saltwater) influence over seasonal and tidal timeframes, and parts that experience only freshwater or periodic saltwater influence. No attributes are reliable indicators of depositional position where saltwater incursion is short lived or where water is fresh. Where marine influence is sustained, Sr/Ba-HAc and Sr/Ba-NH4Ac are the most reliable positional indicators along the fluvial-to-marine transition. When compared strictly to salinity, Sr/Ba-HAc, Sr/Ba-NH4Ac, and δ13Corg all correlate predictably except in delta front and prodelta settings. Our data show that all six sediment attributes are heavily impacted by river-derived sedimentation, and it is not appropriate to compare values from strongly river-influenced settings (e.g., deltas) with those from weakly river-influenced settings (e.g., bays and estuaries).

text: Salinity indicators in sediment through the fluvial-to-marine transition (Fraser River, Canada). Many sediment attributes have been proposed as proxies for determining salinity conditions under which sediment is deposited, and six attributes (Sr/Ba-HAc, Sr/Ba-NH4Ac, δ13Corg, C/N, and the relative abundances and concentrations of dinoflagellate cysts) are compared here. In this paper, sediment attributes from the Fraser River Delta, Canada and surrounding coastal areas are compared by depositional position along the fluvial-to-marine transition, by salinity, and by sedimentological characteristics. Along the fluvial-to-marine transition, most attributes exhibit distinct trends between parts of the river that experience sustained marine water (saltwater) influence over seasonal and tidal timeframes, and parts that experience only freshwater or periodic saltwater influence. No attributes are reliable indicators of depositional position where saltwater incursion is short lived or where water is fresh. Where marine influence is sustained, Sr/Ba-HAc and Sr/Ba-NH4Ac are the most reliable positional indicators along the fluvial-to-marine transition. When compared strictly to salinity, Sr/Ba-HAc, Sr/Ba-NH4Ac, and δ13Corg all correlate predictably except in delta front and prodelta settings. Our data show that all six sediment attributes are heavily impacted by river-derived sedimentation, and it is not appropriate to compare values from strongly river-influenced settings (e.g., deltas) with those from weakly river-influenced settings (e.g., bays and estuaries).

year: 2022

title: Concept-based Text Clustering

authors: Huang, Lan

subjects: clustering

abstract: Thematic organization of text is a natural practice of humans and a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of current texts, as well as organization of future ones. Automatic clustering is usually based on words. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The resulting bag-of-words model is semantically ambiguous and undesirably orthogonal|it ignores the connections between words. This thesis claims that using concepts as the basis of clustering can significantly improve effectiveness. Concepts are defined as units of knowledge. When organized according to the relations among them, they form a concept system. Two concept systems are used here: WordNet, which focuses on word knowledge, and Wikipedia, which encompasses world knowledge. We investigate a clustering procedure with three components: using concepts to represent text; taking the semantic relations among them into account during clustering; and learning a text similarity measure from concepts and their relations. First, we demonstrate that concepts provide a succinct and informative representation of the themes in text, exemplifying this with the two concept systems. Second, we define methods for utilizing concept relations to enhance clustering by making the representation models more discriminative and extending thematic similarity beyond surface overlap. Third, we present a similarity measure based on concepts and their relations that is learned from a small number of examples, and show that it both predicts similarity consistently with human judgement and improves clustering. The thesis provides strong support for the use of concept-based representations instead of the classic bag-of-words model.

text: Concept-based Text Clustering Thematic organization of text is a natural practice of humans and a crucial task for today's vast repositories. Clustering automates this by assessing the similarity between texts and organizing them accordingly, grouping like ones together and separating those with different topics. Clusters provide a comprehensive logical structure that facilitates exploration, search and interpretation of current texts, as well as organization of future ones. Automatic clustering is usually based on words. Text is represented by the words it mentions, and thematic similarity is based on the proportion of words that texts have in common. The resulting bag-of-words model is semantically ambiguous and undesirably orthogonal|it ignores the connections between words. This thesis claims that using concepts as the basis of clustering can significantly improve effectiveness. Concepts are defined as units of knowledge. When organized according to the relations among them, they form a concept system. Two concept systems are used here: WordNet, which focuses on word knowledge, and Wikipedia, which encompasses world knowledge. We investigate a clustering procedure with three components: using concepts to represent text; taking the semantic relations among them into account during clustering; and learning a text similarity measure from concepts and their relations. First, we demonstrate that concepts provide a succinct and informative representation of the themes in text, exemplifying this with the two concept systems. Second, we define methods for utilizing concept relations to enhance clustering by making the representation models more discriminative and extending thematic similarity beyond surface overlap. Third, we present a similarity measure based on concepts and their relations that is learned from a small number of examples, and show that it both predicts similarity consistently with human judgement and improves clustering. The thesis provides strong support for the use of concept-based representations instead of the classic bag-of-words model.

year: 2011

title: Student belonging: critical relationships and responsibilities

authors: Berryman, Mere

subjects: Belonging

abstract: In this paper, we consider New Zealand’s education system to understand what can happen when we focus only on excellence and students reaching their potential, without simultaneously investing in their sense of belonging and wellbeing. National statistics suggest we are alienating and shortchanging an increasing number of students and, for disproportionate numbers of Indigenous students, these statistics are part of a world trend. The literature, and the students themselves, highlight the need to overturn the underlying racism that persistently disadvantages clearly identifiable groups of students over others. Until we do, using equity and excellence as the most powerful drivers for reform, will continue to promote conditions where our students’ sense of belonging and wellbeing are undermined throughout their education and we will risk, failing to address the ensuing negative statistics. We conclude with a response that we have learned from working with these same students.

text: Student belonging: critical relationships and responsibilities In this paper, we consider New Zealand’s education system to understand what can happen when we focus only on excellence and students reaching their potential, without simultaneously investing in their sense of belonging and wellbeing. National statistics suggest we are alienating and shortchanging an increasing number of students and, for disproportionate numbers of Indigenous students, these statistics are part of a world trend. The literature, and the students themselves, highlight the need to overturn the underlying racism that persistently disadvantages clearly identifiable groups of students over others. Until we do, using equity and excellence as the most powerful drivers for reform, will continue to promote conditions where our students’ sense of belonging and wellbeing are undermined throughout their education and we will risk, failing to address the ensuing negative statistics. We conclude with a response that we have learned from working with these same students.

year: 2019