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06 February 2025 | Story André Damons | Photo Supplied
Dr Jared McDonald
Prof Jared McDonald, Assistant Dean: Faculty of The Humanities at the University of the Free State, obtained his first National Research Foundation rating in the C2 category.

Obtaining his first National Research Foundation (NRF) rating has been the goal of Prof Jared McDonald, Assistant Dean: Faculty of The Humanities at the University of the Free State (UFS), since 2020 when he was selected for the UFS Transforming the Professoriate Mentoring Programme.

Prof McDonald obtained a C2 rating recently and credits the programme, under the leadership of Dr Henriëtte van den Berg, who provided invaluable support and mentorship, for this achievement. This rating recognises Prof McDonald as an established researcher and he may enjoy some international recognition for the quality and impact of his recent research outputs. 

“I am delighted to have received a C2 rating. I was hoping to obtain a C2, so when I received confirmation, it felt really good. Since being recruited to the Transforming the Professoriate Programme I have been focused on producing a series of quality journal articles, and importantly, my first monograph. At times it was a struggle to balance the demands of being Assistant Dean in the Faculty of Humanities along with my teaching responsibilities,” says Prof McDonald.

He says obtaining the rating would not have been possible without the interventions of the programme, which assisted him in securing funding for a sabbatical. The encouragement of colleagues and family was equally valuable in helping him to keep his eye on the goal.


Research 

As a nineteenth-century historian, Prof McDonald’s, who is an Associate Professor in the Department of History, research includes topics ranging from the London Missionary Society’s missions to the San as well as the role of controversial missionaries in influencing public discourse on the right to legal equality and social inclusion for indigenous subjects of the British Crown. Another topic is the ways in which evangelical-humanitarian discourse inadvertently provided the justification for the transfer of San children to Cape colonial society. 

“In my publications, the key actors, including Khoesan, are revealed to have been exercising agency in response to a social and political context that was not of their own choosing, but to which they had to respond. The contradictions of the period, coupled with the prospects for blurring the social boundaries of an otherwise strict hierarchical society, provided the means for social manoeuvre and options for resistance from within the confines of the colonial state. I am continuing to explore these ideas in a series of upcoming journal articles and book chapters,” he says. 

The pressure, says Prof McDonald, is already on to retain his rating, and hopefully improve it, when it comes up for review in five years’ time. He is currently working on his second monograph, which is a historical biography of a controversial, but fascinating, missionary who played a notable role in South African history in the early nineteenth century. “The worth of any historical biography lies in the biographer’s ability to shed light on the circumstances, contingencies, and contradictions that shaped the contours of the protagonist’s life, thus illuminating the historical context,” concludes Prof McDonald. 

He seeks to relate his research to his approach to teaching by exploring innovative ways of making the past relevant to students today. This is motivated by the conviction that the elucidation of possibilities of agency in the past raises the prospect for students to engage with the meanings and possibilities of agency in the present.

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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