217 research outputs found
The first novel in Xhosa
The first novel in the Xhosa language, USamson, written by the greatest figure in the history of Xhosa literature, S. E. K. Mqhayi (1875–1945), and published in 1907, is now lost. It was produced at a time when black people in South Africa were becoming bolder in their demand for human rights, forming independent black churches and political organizations. It appeared after a period of gestation for Xhosa literature in newspapers, at a time when missionaries were discussing the publication of books in Xhosa, but Mqhayi paid for its printing and organized its distribution. The novelette added details of setting and characterization to the biblical story to encourage the youth to gather behind black leaders who lacked support. Caught in the social tension between Xhosa and Mfengu, USamson was heavily criticized by I. W. Wauchope for departing from biblical narrative, but more generally defended by readers, who looked forward to the further publication of Xhosa literature in books
Predicting the status of sediment ecosystems around commercial fish farms from taxonomic and functional profiles
The sediments around commercial fish farms are regularly monitored regarding the
environmental condition. If the environmental condition is not sufficient, a quarantine period is
imposed on the fish farms. It is therefore important that the environmental state is mapped
quickly and with good precision. Currently, this is determined manually from inspection of
sediment samples by expert taxonomists, who determine an environmental index based on
macrofauna. The AQUAeD project (2021-2025) – On-site monitoring of aquaculture impact on
the environment by open-source nanopore eDNA analysis – aims to replace the current
environmental monitoring analyses with digital DNA based solutions, as well as moving the
analyses to the facilities to achieve fast and accurate results.
This thesis is a part of the AQUAeD project, and the data used was from 16S sequencing. From
the 16S data, taxonomic profiles can be made, and the essential aim of this thesis is to predict
the ecosystem status from this. However, the taxonomic diversity present in sediments is
significant, with numerous organisms being unidentified and lacking names within the existing
taxonomy. From the metagenome data, functional profiles can be derived. This entails coding
genes and categorizing them into functional groups such as EC functions, KO functions and
MetaCyc pathways. Then functional profiles can be constructed accordingly.
An indicator of the ecosystem status is the nEQR values, which is what has been predicted in
this thesis for both the taxonomic and functional profiles. The results from this shows that the
predictions are good for both taxonomic and functional profiles, but also that the functional
profiles do not give better predictions. Rather, they are very similar to each other.
In this thesis, AI (Artificial Intelligence) was used to assist with the coding, as well as finding
sources for the background information in the introduction of this thesis. The AI instruments
used in this thesis was ChatGPT and Perplexity.
Sedimentene rundt kommersielle fiskeoppdrettsanlegg blir jevnlig overvåket med tanke på
miljøtilstanden. Hvis miljøtilstanden ikke er tilstrekkelig, blir det pålagt karantenetid for
oppdrettsanleggene. Det er derfor viktig at miljøtilstanden kartlegges raskt og med god
presisjon. For øyeblikket blir dette bestemt gjennom inspeksjon av sedimentprøver utført av
eksperter på taksonomi, som fastsetter en miljøindeks basert på makrofauna. AQUAeDprosjektet (2021-2025) – Overvåkning av akvakulturens påvirkning på miljøet ved hjelp av
open source for nanopore eDNA analyse – har som mål å erstatte de nåværende
miljøovervåkningsanalysene med digitale DNA-baserte løsninger, samt å flytte analysene til
fiskeoppdrettsanleggene for å oppnå raske og nøyaktige resultater.
Denne avhandlingen er en del av AQUAeD-prosjekter, og dataene som ble brukt var fra 16S
sekvensering. Fra 16S dataene kan det lages taksonomiske profiler, og det essensielle målet
med denne avhandlingen er å forutsi økosystemets tilstand fra dette. Den taksonomiske
mangfoldigheten i sedimentene er derimot betydelig, med mange organismer som ikke er
identifisert og som mangler navn innenfor den eksisterende taksonomien. Fra metagenomdataene kan funksjonelle profiler utledes. Dette innebærer kodende gener og kategorisering av
dem i funksjonelle grupper som EC funksjoner, KO funksjoner og MetaCyc pathways. Videre
kan funksjonelle grupper konstrueres.
En indikator på økosystemets tilstand er nEQR-verdier, som er det som har blitt predikert i
denne avhandlingen for både de taksonomiske og funksjonelle profilene. Resultatene fra dette
viser at prediksjonene er gode for både taksonomiske og funksjonelle profiler, men de
funksjonelle profilene gir heller ikke bedre prediksjoner. Tvert imot er de veldig like hverandre.
I denne avhandlingen ble KI (Kunstig Intelligens) brukt til å hjelpe med kodingen, samt å finne
kilder til bakgrunnsinformasjonen i innledningen til denne avhandlingen. KI-instrumentene
som ble brukt i denne avhandlingen var ChatGPT og Perplexity
Lord of the Singers
Like three other authors in this issue, Jeff Opland has put his fieldwork, in this case principally among the Xhosa-speaking peoples of South Africa, to excellent use in his writings on oral tradition. As an Africanist and an Anglo-Saxonist, he has contributed important studies in both fields, particularly Anglo-Saxon Oral Poetry (1980) and Xhosa Oral Poetry (1983)
Opland, William. F. (Math) (8-24-45) [4 l.]
Teacher narrative of William F. Opland, math teacher at Tule Lake Relocation Center, entitled Personal Narrative Report, dated 8/24/1945https://scholarlycommons.pacific.edu/cook-nisei/1164/thumbnail.jp
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