Understanding foraging practices in Lagos metropolis to redesign urban greenspaces in support of human-nature interactions
- Adeyemi, Opeyemi, Shackleton, Charlie M
- Authors: Adeyemi, Opeyemi , Shackleton, Charlie M
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/401353 , vital:69728 , xlink:href="https://doi.org/10.1016/j.ufug.2022.127805"
- Description: Enhancing knowledge of urban foraging across different urban landscapes is an urgent matter given that about two-thirds of the world’s population is projected to live in urban areas by 2050, whilst 50 % of Africa’s population is expected to live in cities by 2030. This study was conducted in Lagos metropolis which is the economic hub of Africa’s most populous country. Data was collected using an in-person, semi-structured questionnaire from 347 persons who were 18 years or older to identify foragers and non-foragers, their sociodemographic profiles, and their foraging practices. Results revealed that about two out of three persons sampled forage to some degree. The collection happened more in domestic gardens (34 %) and streets (27 %) than in other foraging sites (such as unused lands, institutional grounds and lakes and riparian fringes). A total of 35 species were reportedly foraged within the metropolis, mostly for food (71 %) and medicine (26 %). Mango (Mangifera indica), pawpaw (Carica papaya), tropical almond (Terminalia catappa), fish (various species), bitter leaf (Vernonia amygdalina) and spinach (Spinacia oleracea) were the most gathered species. The distance travelled to foraging wild species ranged from 5 m to 25 km. The primary motivation for foraging was the acquisition of fresh and natural materials. However, some felt that foraging was a stressful activity. The unavailability of foraging sites and species was the major constraint to foraging in this megacity. Hence, efforts to increase the edible components of public green spaces and to provide free access could potentially allow more people to forage and make current foraging more secure. We suggest that making provisions for foraging in urban planning goals could contribute to the sustainable development of cities in Africa and elsewhere.
- Full Text:
- Date Issued: 2023
- Authors: Adeyemi, Opeyemi , Shackleton, Charlie M
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/401353 , vital:69728 , xlink:href="https://doi.org/10.1016/j.ufug.2022.127805"
- Description: Enhancing knowledge of urban foraging across different urban landscapes is an urgent matter given that about two-thirds of the world’s population is projected to live in urban areas by 2050, whilst 50 % of Africa’s population is expected to live in cities by 2030. This study was conducted in Lagos metropolis which is the economic hub of Africa’s most populous country. Data was collected using an in-person, semi-structured questionnaire from 347 persons who were 18 years or older to identify foragers and non-foragers, their sociodemographic profiles, and their foraging practices. Results revealed that about two out of three persons sampled forage to some degree. The collection happened more in domestic gardens (34 %) and streets (27 %) than in other foraging sites (such as unused lands, institutional grounds and lakes and riparian fringes). A total of 35 species were reportedly foraged within the metropolis, mostly for food (71 %) and medicine (26 %). Mango (Mangifera indica), pawpaw (Carica papaya), tropical almond (Terminalia catappa), fish (various species), bitter leaf (Vernonia amygdalina) and spinach (Spinacia oleracea) were the most gathered species. The distance travelled to foraging wild species ranged from 5 m to 25 km. The primary motivation for foraging was the acquisition of fresh and natural materials. However, some felt that foraging was a stressful activity. The unavailability of foraging sites and species was the major constraint to foraging in this megacity. Hence, efforts to increase the edible components of public green spaces and to provide free access could potentially allow more people to forage and make current foraging more secure. We suggest that making provisions for foraging in urban planning goals could contribute to the sustainable development of cities in Africa and elsewhere.
- Full Text:
- Date Issued: 2023
Agricultural disturbance affects taxonomic and functional diversity of Afrotropical macroinvertebrate composition in a South African river system
- Akamagwuna, Frank C, Odume, Oghenekaro N, Richoux, Nicole B
- Authors: Akamagwuna, Frank C , Odume, Oghenekaro N , Richoux, Nicole B
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/454293 , vital:75333 , xlink:href="https://doi.org/10.1016/j.indic.2023.100251"
- Description: Developing species-level biomonitoring tools to monitor riverine systems threatened by anthropogenic pollution, including local agricultural activities in the Afrotropical region, remain a critical challenge. Here we explored the utility of taxonomic-based (diversity, richness, and composition) as well as functional-based (functional diversity) indices to examine the effects of agricultural disturbance on macroinvertebrate communities in the Kat River, Eastern Cape Province of South Africa. We collected physicochemical parameters and macroinvertebrates from eight sites delineated into four land-use categories (highly impacted, HIC; impacted category, IC; moderately impacted, MIC and least impacted, LIC) using agricultural land cover. We recorded 70 macroinvertebrate taxa belonging to 49 families and 48 genera in the Kat River. Redundancy analysis (RDA) and Pearson correlation analysis revealed that species of Lymnaeidae, Belostomatidae, Planorbidae and Libellulidae families and class Oligochaeta were tolerant to agricultural disturbance, as they were dominant in the highly impacted sites and were significantly associated with high salinity, temperature, total dissolved solids (TDS), flow velocity and nutrients. Conversely, species of Baetidae, Caenidae and Potamonautidae were negatively associated with the highly impacted sites and high salinity, temperature, and nutrients. On the other hand, taxonomic indices showed more sensitivity to indicators of agricultural pollution than functional indices, with taxon richness, Shannon index, Simpson's index and Margalef's index declining significantly in the highly disturbed sites (p less than 0.05). They were negatively associated with high electrical conductivity, large river width, and high nitrite and nitrate concentrations; hence they were identified as indicator metrics sensitive to agricultural pollution. Overall, our study revealed that agricultural disturbance could differentially affect the structure and function of macroinvertebrates, and indicator taxonomic and functional indices were identified for long-term monitoring of rivers that drain agricultural landscapes.
- Full Text:
- Date Issued: 2023
- Authors: Akamagwuna, Frank C , Odume, Oghenekaro N , Richoux, Nicole B
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/454293 , vital:75333 , xlink:href="https://doi.org/10.1016/j.indic.2023.100251"
- Description: Developing species-level biomonitoring tools to monitor riverine systems threatened by anthropogenic pollution, including local agricultural activities in the Afrotropical region, remain a critical challenge. Here we explored the utility of taxonomic-based (diversity, richness, and composition) as well as functional-based (functional diversity) indices to examine the effects of agricultural disturbance on macroinvertebrate communities in the Kat River, Eastern Cape Province of South Africa. We collected physicochemical parameters and macroinvertebrates from eight sites delineated into four land-use categories (highly impacted, HIC; impacted category, IC; moderately impacted, MIC and least impacted, LIC) using agricultural land cover. We recorded 70 macroinvertebrate taxa belonging to 49 families and 48 genera in the Kat River. Redundancy analysis (RDA) and Pearson correlation analysis revealed that species of Lymnaeidae, Belostomatidae, Planorbidae and Libellulidae families and class Oligochaeta were tolerant to agricultural disturbance, as they were dominant in the highly impacted sites and were significantly associated with high salinity, temperature, total dissolved solids (TDS), flow velocity and nutrients. Conversely, species of Baetidae, Caenidae and Potamonautidae were negatively associated with the highly impacted sites and high salinity, temperature, and nutrients. On the other hand, taxonomic indices showed more sensitivity to indicators of agricultural pollution than functional indices, with taxon richness, Shannon index, Simpson's index and Margalef's index declining significantly in the highly disturbed sites (p less than 0.05). They were negatively associated with high electrical conductivity, large river width, and high nitrite and nitrate concentrations; hence they were identified as indicator metrics sensitive to agricultural pollution. Overall, our study revealed that agricultural disturbance could differentially affect the structure and function of macroinvertebrates, and indicator taxonomic and functional indices were identified for long-term monitoring of rivers that drain agricultural landscapes.
- Full Text:
- Date Issued: 2023
Associations between contraceptive use, physical activity, depression, and quality of life among women of childbearing age in Akure South Local Government area of Ondo State, Nigeria
- Authors: Alimi, Olabisi Ganiyat
- Date: 2023-10-13
- Subjects: Exercise for women Nigeria Ondo State , Depression in women Nigeria Ondo State , Well-being Nigeria Ondo State , Quality of life Nigeria Ondo State , Contraception Side effects
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424210 , vital:72133
- Description: Background: Population experts and policymakers are concerned about Nigeria's rapid annual population growth due to the country's high birth rate which was 5.3 births per woman in 2018. Fear of the side effects of modern contraceptives among Nigerian women contributes to the low rate of contraceptive use, which was reported to be 17% and 37% among married and sexually active unmarried women, respectively. Which is a significant cause of the high birth rate. Although the side effects of modern contraceptives on women's clinical and physiological variables are well known, studies examining the associations between contraceptive use and physical and psychosocial variables such as physical activity (PA), depression, and quality of life (QoL) in non-athletic Nigerian women of reproductive age are scarce. This study aimed to examine the associations between contraceptive use, PA, depression, and QoL among non-athletic women of childbearing age in Akure South Local Government, Ondo State, Nigeria. Methods: In a descriptive cross-sectional study, 646 women of childbearing age were recruited using the multistage sampling technique. The data of 496 current contraceptive users and 146 non-users were analysed, as 4 respondents did not respond regarding current contraceptive use status. The Global PA Questionnaire (GPAQ), Beck’s Depression Inventory (BDI) and World Health QoL Organization Quality of Life Brief (WHOQoL BREF) were used to assess respondents’ scores/levels of PA, depression and health-related quality of life (HRQoL). The GPAQ, BDI, and WHOQOL scores were compared between contraceptive users and non-users using non-parametric Quade Analysis of Covariance while age, married status, tribe, religion, and occupation were included covariates. PA, sedentary behaviour (SB), and BDI scores were categorized using guidelines. Contraceptive use/practice was the outcome variable. Pearson's chi-square test bivariate analysis and a multivariate logistic model were used to identify factors associated with contraceptive use (users and non-users). Crude and adjusted odds ratios and their confidence intervals were calculated to determine the significance of the association. The regression model was adjusted for age, marital status, religion, tribe, highest education level, occupation, awareness of contraceptives, current use, lifetime use, type, class, and duration of current contraception. “Statistical significance was set at p < 0.05. Results: The mean age of the respondents was 29.73±6.10 years. The contraceptive users and non-users were not significantly different regarding their ages (p = 0.135), marital status (p = 0.245), highest education (p = 0.444), occupation (p = 0.238), and tribe (p = 0.192). The respondents’ lifetime and point prevalence of contraceptive uptake was 93.6% and 77.3%, respectively, while 72 (12.8%) reported experiencing contraception-related side effects. Of the 496 respondents who currently practice contraception, 146 (29.4%) were hormonal contraceptive users. The majority of the respondents had moderate and mild levels of PA (48.5%) and depression (51.4%), respectively, and a significantly higher proportion of contraceptive users had minimal and moderate depression levels than the non-users (p = 0.018). The contraceptive users demonstrated significantly higher median scores of BDI (p = 0.02), Physical health QoL (p < 0.001), environment QoL (p = 0.033) and overall QoL (0.004) than the non-users. Hormonal contraceptive users had significantly higher median PA walking/bicycling scores than non-hormonal users (p = 0.014). Respondents with mild and moderate depression levels had higher odds of being contraceptive users than those with minimal depression (AOR = 3.12, 95% CI = 1.43 – 6.80, p = 0.04 and 4.67, 95% CI = 1.92 – 11.36, p = 0.001 respectively). Conclusion: Contraceptive use is negatively associated with depression but positively related to Physical health, environment and overall domains of HRQoL. Healthcare professionals should consider women's mental and emotional condition while advising on family planning for optimal HRQoL. , Thesis (MSc) -- Faculty of Science, Human Kinetics and Ergonomics, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Alimi, Olabisi Ganiyat
- Date: 2023-10-13
- Subjects: Exercise for women Nigeria Ondo State , Depression in women Nigeria Ondo State , Well-being Nigeria Ondo State , Quality of life Nigeria Ondo State , Contraception Side effects
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424210 , vital:72133
- Description: Background: Population experts and policymakers are concerned about Nigeria's rapid annual population growth due to the country's high birth rate which was 5.3 births per woman in 2018. Fear of the side effects of modern contraceptives among Nigerian women contributes to the low rate of contraceptive use, which was reported to be 17% and 37% among married and sexually active unmarried women, respectively. Which is a significant cause of the high birth rate. Although the side effects of modern contraceptives on women's clinical and physiological variables are well known, studies examining the associations between contraceptive use and physical and psychosocial variables such as physical activity (PA), depression, and quality of life (QoL) in non-athletic Nigerian women of reproductive age are scarce. This study aimed to examine the associations between contraceptive use, PA, depression, and QoL among non-athletic women of childbearing age in Akure South Local Government, Ondo State, Nigeria. Methods: In a descriptive cross-sectional study, 646 women of childbearing age were recruited using the multistage sampling technique. The data of 496 current contraceptive users and 146 non-users were analysed, as 4 respondents did not respond regarding current contraceptive use status. The Global PA Questionnaire (GPAQ), Beck’s Depression Inventory (BDI) and World Health QoL Organization Quality of Life Brief (WHOQoL BREF) were used to assess respondents’ scores/levels of PA, depression and health-related quality of life (HRQoL). The GPAQ, BDI, and WHOQOL scores were compared between contraceptive users and non-users using non-parametric Quade Analysis of Covariance while age, married status, tribe, religion, and occupation were included covariates. PA, sedentary behaviour (SB), and BDI scores were categorized using guidelines. Contraceptive use/practice was the outcome variable. Pearson's chi-square test bivariate analysis and a multivariate logistic model were used to identify factors associated with contraceptive use (users and non-users). Crude and adjusted odds ratios and their confidence intervals were calculated to determine the significance of the association. The regression model was adjusted for age, marital status, religion, tribe, highest education level, occupation, awareness of contraceptives, current use, lifetime use, type, class, and duration of current contraception. “Statistical significance was set at p < 0.05. Results: The mean age of the respondents was 29.73±6.10 years. The contraceptive users and non-users were not significantly different regarding their ages (p = 0.135), marital status (p = 0.245), highest education (p = 0.444), occupation (p = 0.238), and tribe (p = 0.192). The respondents’ lifetime and point prevalence of contraceptive uptake was 93.6% and 77.3%, respectively, while 72 (12.8%) reported experiencing contraception-related side effects. Of the 496 respondents who currently practice contraception, 146 (29.4%) were hormonal contraceptive users. The majority of the respondents had moderate and mild levels of PA (48.5%) and depression (51.4%), respectively, and a significantly higher proportion of contraceptive users had minimal and moderate depression levels than the non-users (p = 0.018). The contraceptive users demonstrated significantly higher median scores of BDI (p = 0.02), Physical health QoL (p < 0.001), environment QoL (p = 0.033) and overall QoL (0.004) than the non-users. Hormonal contraceptive users had significantly higher median PA walking/bicycling scores than non-hormonal users (p = 0.014). Respondents with mild and moderate depression levels had higher odds of being contraceptive users than those with minimal depression (AOR = 3.12, 95% CI = 1.43 – 6.80, p = 0.04 and 4.67, 95% CI = 1.92 – 11.36, p = 0.001 respectively). Conclusion: Contraceptive use is negatively associated with depression but positively related to Physical health, environment and overall domains of HRQoL. Healthcare professionals should consider women's mental and emotional condition while advising on family planning for optimal HRQoL. , Thesis (MSc) -- Faculty of Science, Human Kinetics and Ergonomics, 2023
- Full Text:
- Date Issued: 2023-10-13
The morphogenesis of higher education leadership: a social realist exploratory journey
- Authors: Andrews, Ruth
- Date: 2023-10-13
- Subjects: Educational leadership South Africa , Education, Higher South Africa , Critical realism , Social realism , Educational change South Africa , Transformational leadership
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/442897 , vital:74051 , DOI 10.21504/10962/442897
- Description: The purpose of the study underpinning this thesis was to explore the tensions experienced by university leaders as they balance politics, power and the academic project whilst pursuing their ultimate concerns in the world. Universities are undergoing constant change, particularly in the present time of hypercomplexity, where the discourses of globalisation and neoliberalism condition higher education institutions and their leaders. This predisposes universities to operate as a market economy rather than as a public good. University leaders are under immense pressure as they seek to reposition themselves and exercise their agency in steering their institutions in a landscape fraught with complexity and contestation about the very nature of the modern university. The study was located in a traditional university in South Africa, which added another layer of complexity given the history of Apartheid and, the use of education as a means of discriminating against the black majority population, and the subsequent attempts by the government to transform the system following the first democratic election of 1994. Bhaskar’s (1989) critical realism and Archer’s (1998, 2000) social realism were used to frame the study theoretically. Bhaskar argues for the understanding of the world as an ‘open system’ in which experiences and events emerge from the tendential interplay of mechanisms at a layer of reality not directly accessible to empirical observation. Archer’s (2000) social realism draws on critical realism to provide a set of tools that allows an exploration of the social world in more detail. This study draws on the tools of analytical dualism, or the temporary separation of structure, culture and agency for analytical purposes, and Archer’s (1998) morphogenetic framework, which allows for the exploration of change, or non-change, over time. The overarching goal of the study was to explore how leaders at one South African university were enabled and constrained as they exercised their agency in the pursuit of projects they had identified to address their ultimate concerns about the world more generally and higher education in particular. However, the study also sought to explore the construct of leadership itself in a specific context by using Archer’s (2007, 2012) theoretical work on reflexivity. The study drew on in-depth interviews with senior leaders at the institution, including two vice-chancellors. The interviews were subjected to analysis, and the inferential tools of abduction and retroduction were used to identify the interplay of mechanisms located at the level of the Real, the deepest layer of reality posited by Bhaskar (1978), which led to the events and experiences reported by leaders. A literature review was used to identify additional theories that were used in the processes of abduction and retroduction. The study revealed that change, or rather non-change, is often concealed in cultural rhetoric veiled in leadership practices in acts assimilating past ideology and codified rules and practices with new codified rules and practices. Leaders often draw on powerful relational networks as they reflexively exercise their agency, and these networks can also work to constrain change. , Thesis (PhD) -- Faculty of Education, Education 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Andrews, Ruth
- Date: 2023-10-13
- Subjects: Educational leadership South Africa , Education, Higher South Africa , Critical realism , Social realism , Educational change South Africa , Transformational leadership
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/442897 , vital:74051 , DOI 10.21504/10962/442897
- Description: The purpose of the study underpinning this thesis was to explore the tensions experienced by university leaders as they balance politics, power and the academic project whilst pursuing their ultimate concerns in the world. Universities are undergoing constant change, particularly in the present time of hypercomplexity, where the discourses of globalisation and neoliberalism condition higher education institutions and their leaders. This predisposes universities to operate as a market economy rather than as a public good. University leaders are under immense pressure as they seek to reposition themselves and exercise their agency in steering their institutions in a landscape fraught with complexity and contestation about the very nature of the modern university. The study was located in a traditional university in South Africa, which added another layer of complexity given the history of Apartheid and, the use of education as a means of discriminating against the black majority population, and the subsequent attempts by the government to transform the system following the first democratic election of 1994. Bhaskar’s (1989) critical realism and Archer’s (1998, 2000) social realism were used to frame the study theoretically. Bhaskar argues for the understanding of the world as an ‘open system’ in which experiences and events emerge from the tendential interplay of mechanisms at a layer of reality not directly accessible to empirical observation. Archer’s (2000) social realism draws on critical realism to provide a set of tools that allows an exploration of the social world in more detail. This study draws on the tools of analytical dualism, or the temporary separation of structure, culture and agency for analytical purposes, and Archer’s (1998) morphogenetic framework, which allows for the exploration of change, or non-change, over time. The overarching goal of the study was to explore how leaders at one South African university were enabled and constrained as they exercised their agency in the pursuit of projects they had identified to address their ultimate concerns about the world more generally and higher education in particular. However, the study also sought to explore the construct of leadership itself in a specific context by using Archer’s (2007, 2012) theoretical work on reflexivity. The study drew on in-depth interviews with senior leaders at the institution, including two vice-chancellors. The interviews were subjected to analysis, and the inferential tools of abduction and retroduction were used to identify the interplay of mechanisms located at the level of the Real, the deepest layer of reality posited by Bhaskar (1978), which led to the events and experiences reported by leaders. A literature review was used to identify additional theories that were used in the processes of abduction and retroduction. The study revealed that change, or rather non-change, is often concealed in cultural rhetoric veiled in leadership practices in acts assimilating past ideology and codified rules and practices with new codified rules and practices. Leaders often draw on powerful relational networks as they reflexively exercise their agency, and these networks can also work to constrain change. , Thesis (PhD) -- Faculty of Education, Education 2023
- Full Text:
- Date Issued: 2023-10-13
Two new Poyntonophrynus species (Anura: Bufonidae) highlight the importance of Angolan centers of endemism
- Baptista, Ninda L, Pinto, Pedro V, Keates, Chad, Lobón-Rovira, Javier, Edwards, Shelley, Rödel, Mark-Oliver
- Authors: Baptista, Ninda L , Pinto, Pedro V , Keates, Chad , Lobón-Rovira, Javier , Edwards, Shelley , Rödel, Mark-Oliver
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/461572 , vital:76214 , xlink:href="https://zoobank.org/7B5494CC-F8F2-46EA-BB73-D28B13D31CB6"
- Description: The pygmy toad genus Poyntonophrynus is endemic to southern Africa. The morphology of these small toads is conserved. They are usually dully colored, and are predominately adapted to arid conditions. During recent surveys in Angola we found Poyntonophrynus specimens that were not assignable to known species. Using an integrative approach, based on mitochondrial and nuclear DNA, morphology, osteology, biogeography and ecology, we identified three new lineages, and describe two of them as new species. All three lineages are closely related to P. pachnodes, an Angolan endemic species, but they are geographically isolated from it. The new species are morphologically distinguishable, and are associated with two of the most important Angolan centers of endemism: the western escarpment and the central highlands. In order to get a more comprehensive understanding of the osteology of the genus, we also provide an osteological characterization of P. dombensis, which was not available to date. Our findings i) increase the number of earless species in the genus Poyntonophrynus, ii) emphasize southwestern Africa as the cradle of diversification in this genus, iii) report the occurrence of Poyntonophrynus in humid environments, thus showing that these toads are ecologically more variable than previously thought, and iv) underline the importance of further biodiversity studies in Angolan centers of endemism.
- Full Text:
- Date Issued: 2023
- Authors: Baptista, Ninda L , Pinto, Pedro V , Keates, Chad , Lobón-Rovira, Javier , Edwards, Shelley , Rödel, Mark-Oliver
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/461572 , vital:76214 , xlink:href="https://zoobank.org/7B5494CC-F8F2-46EA-BB73-D28B13D31CB6"
- Description: The pygmy toad genus Poyntonophrynus is endemic to southern Africa. The morphology of these small toads is conserved. They are usually dully colored, and are predominately adapted to arid conditions. During recent surveys in Angola we found Poyntonophrynus specimens that were not assignable to known species. Using an integrative approach, based on mitochondrial and nuclear DNA, morphology, osteology, biogeography and ecology, we identified three new lineages, and describe two of them as new species. All three lineages are closely related to P. pachnodes, an Angolan endemic species, but they are geographically isolated from it. The new species are morphologically distinguishable, and are associated with two of the most important Angolan centers of endemism: the western escarpment and the central highlands. In order to get a more comprehensive understanding of the osteology of the genus, we also provide an osteological characterization of P. dombensis, which was not available to date. Our findings i) increase the number of earless species in the genus Poyntonophrynus, ii) emphasize southwestern Africa as the cradle of diversification in this genus, iii) report the occurrence of Poyntonophrynus in humid environments, thus showing that these toads are ecologically more variable than previously thought, and iv) underline the importance of further biodiversity studies in Angolan centers of endemism.
- Full Text:
- Date Issued: 2023
In silico characterization of missense mutations in infectious diseases: case studies of tuberculosis and COVID-19
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Microbial mutation , COVID-19 (Disease) , Drug resistance in microorganisms , Antitubercular agents , Tuberculosis , Molecular dynamics , Single nucleotide polymorphisms
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431626 , vital:72791 , DOI 10.21504/10962/431626
- Description: One of the greatest challenges facing modern medicine and the global public health today is antimicrobial drug resistance (AMR). This “silent pandemic,” as coined by the world health organization (WHO), is steadily increasing with an estimated 4.95 million mortalities attributed to AMR in 2019, 1.27 million of which were directly linked to AMR. Some of the contributors to AMR include self-prescription, drug overuse, sub-optimal drug prescriptions by health workers, and inaccessibility to drugs, especially in remote areas, which leads to poor adherence. The situation is aggravated by the upsurge of new zoonotic infections like the coronavirus disease 2019, which present unique challenges and take the bulk of resources hence stunting the fight against AMR. Quite alarming still is our current antimicrobial arsenal, which hasn’t had any novel antimicrobial drug discovery/addition, of a new class, since the 1980s. This puts a burden on the existing broad-spectrum antimicrobial drugs which are already struggling against multi-drug resistant strains like multi-drug resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB). Besides the search for new antimicrobial agents, the other avenue for addressing AMR is studying drug resistance mechanisms, especially single nucleotide polymorphisms (SNPs), that change drug target characteristics. With the advancement of computational power and data storage resources, computational approaches can be applied in mutational studies to provide insight into the drug resistance mechanisms with an aim to inform future drug design and development. Therefore, in the first part of this thesis, we employ integrative in silico approaches, including 3D structure modeling, molecular dynamic (MD) simulations, comparative essential dynamics (ED), and protein network analysis approaches i.e., dynamic residue network (DRN) analysis to decipher drug resistance mechanisms in tuberculosis (TB). This involved an investigation of the drug resistance mutations in the catalase-peroxidase (KatG) and pyrazinamidase (MtPncA) enzymes which are responsible for activation of TB first-line drugs; Isoniazid (INH) and Pyrazinamide (PZA), respectively. In the case of KatG, eleven high confidence (HC) KatG mutations associated with a high prevalence of phenotypic INH resistance were identified and their 3D structures modeled before subjecting them to MD simulations. Global analysis showed an unstable KatG structure and active site environment in the mutants compared to the wildtype. Active site dynamics in the mutants compromised cofactor (heme) interactions resulting in less bonds/interactions compared to the wildtype. Given the importance of the heme, reduced interactions affect enzyme function. Trajectory analysis also showed asymmetric protomer behavior both in the wildtype and mutant systems. DRN analysis identified the KatG dimerization domain and C-terminal domain as functionally important and influential in the enzyme function as per betweenness centrality and eigenvector centrality distribution. In the case of the MtPncA enzyme, our main focus was on understanding the MtPncA binding ability of Nicotinamide (an analogue of PZA) in comparison to PZA, especially in the presence of 82 resistance conferring MtPncA mutations. Like in KatG, the mutant structures were modeled and subjected to MD simulations and analysis. Interestingly, more MtPncA mutants favored NAM interactions compared to PZA i.e., 34 MtPncA mutants steadily coordinated NAM compared to 21 in the case of PZA. Trajectory and ligand interaction analysis showed how increased active site lid loop dynamics affect the NAM binding, especially in the systems with the active site mutations i.e., H51Y, W68R, C72R, L82R, K96N, L159N, and L159R. This led to fewer protein-ligand interactions and eventually ligand ejection. Network analysis further identified the protein core, metal binding site (MBS), and substrate binding site as the most important regions of the enzyme. Furthermore, the degree of centrality analysis showed how specific MtPncA mutations i.e., C14H, F17D, and T412P, interrupt intra-protein communication from the MtPncA core to the MBS, affecting enzyme activity. The analysis of KatG and MtPncA enzyme mutations not only identified the effects of mutations on enzyme behaviour and communication, but also established a framework of computational approaches that can be used for mutational studies in any protein. Besides AMR, the continued encroachment of wildlife habitats due to population growth has exposed humans to wildlife pathogens leading to zoonotic diseases, a recent example being coronavirus disease 2019 (COVID-19). In the second part of the thesis, the established computational approaches in Part 1, were employed to investigate the changes in inter-protein interactions and communication patterns between the severe acute respiratory coronavirus 2 (SARS-CoV-2) with the human host receptor protein (ACE2: angiotensin-converting enzyme 2) consequent to mutations in the SARS-CoV-2 receptor binding domain (RBD). Here, the focus was on RBD mutations of the Omicron sub-lineages. We identified four Omicron-sub lineages with RBD mutations i.e., BA.1, BA.2, BA.3 and BA.4. Each sub-lineage mutations were modeled into RBD structure in complex with the hACE2. MD analysis of the RBD-hACE2 complex highlighted how the RBD mutations change the conformational flexibility of both the RBD and hACE2 compared to the wildtype (WT). Furthermore, DRN analysis identified novel allosteric paths composed of residues with high betweenness and eigenvector centralities linking the RBD to the hACE2 in both the wildtype and mutant systems. Interestingly, these paths were modified with the progression of Omicron sub-lineages, highlighting how the virus evolution affects protein interaction. Lastly, the effect of mutations on S RBD and hACE2 interaction was investigated from the hACE2 perspective by focusing on mutations in the hACE2 protein. Here, naturally occurring hACE2 polymorphisms in African populations i.e., S19P, K26R, M82I, K341R, N546D, and D597Q, were identified and their effects on RBD-hACE2 interactions investigated in presence of the Omicron BA.4/5 RBD mutations. The hACE2 polymorphisms subtly affected the complex dynamics; however, RBD-hACE2 interaction analysis showed that hACE2 mutations effect the complex formation and interaction. Here, the K26R mutation favored RBD-hACE2 interactions, whereas S19P resulted in fewer inter-protein interactions than the reference system. The M82I mutation resulted in a higher RBD-hACE2 binding energy compared to the wildtype meaning that the mutation might not favor RBD binding to the hACE2. On the other hand, K341R had the most RBD-hACE2 interactions suggesting that it probably favors RBD binding to the hACE2. N546D and D597Q had diminutive differences to the reference system. Interestingly, the network of high betweenness centrality residues linking the two proteins, as seen in the previous paragraph, were maintained/modified in presence of hACE2 mutations. HACE2 mutations also changed the enzyme network patterns resulting in a concentration of high eigenvector centrality residues around the zinc-binding and active site region, ultimately influencing the enzyme functionality. Altogether, the thesis highlights fundamental structural and network changes consequent to mutations both in TB and COVID-19 proteins of interest using in silico approaches. These approaches not only provide a new context on impact of mutations in TB and COVID target proteins, but also presents a framework that be implemented in other protein mutation studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Barozi, Victor
- Date: 2023-10-13
- Subjects: Microbial mutation , COVID-19 (Disease) , Drug resistance in microorganisms , Antitubercular agents , Tuberculosis , Molecular dynamics , Single nucleotide polymorphisms
- Language: English
- Type: Academic theses , Doctoral theses , text
- Identifier: http://hdl.handle.net/10962/431626 , vital:72791 , DOI 10.21504/10962/431626
- Description: One of the greatest challenges facing modern medicine and the global public health today is antimicrobial drug resistance (AMR). This “silent pandemic,” as coined by the world health organization (WHO), is steadily increasing with an estimated 4.95 million mortalities attributed to AMR in 2019, 1.27 million of which were directly linked to AMR. Some of the contributors to AMR include self-prescription, drug overuse, sub-optimal drug prescriptions by health workers, and inaccessibility to drugs, especially in remote areas, which leads to poor adherence. The situation is aggravated by the upsurge of new zoonotic infections like the coronavirus disease 2019, which present unique challenges and take the bulk of resources hence stunting the fight against AMR. Quite alarming still is our current antimicrobial arsenal, which hasn’t had any novel antimicrobial drug discovery/addition, of a new class, since the 1980s. This puts a burden on the existing broad-spectrum antimicrobial drugs which are already struggling against multi-drug resistant strains like multi-drug resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB). Besides the search for new antimicrobial agents, the other avenue for addressing AMR is studying drug resistance mechanisms, especially single nucleotide polymorphisms (SNPs), that change drug target characteristics. With the advancement of computational power and data storage resources, computational approaches can be applied in mutational studies to provide insight into the drug resistance mechanisms with an aim to inform future drug design and development. Therefore, in the first part of this thesis, we employ integrative in silico approaches, including 3D structure modeling, molecular dynamic (MD) simulations, comparative essential dynamics (ED), and protein network analysis approaches i.e., dynamic residue network (DRN) analysis to decipher drug resistance mechanisms in tuberculosis (TB). This involved an investigation of the drug resistance mutations in the catalase-peroxidase (KatG) and pyrazinamidase (MtPncA) enzymes which are responsible for activation of TB first-line drugs; Isoniazid (INH) and Pyrazinamide (PZA), respectively. In the case of KatG, eleven high confidence (HC) KatG mutations associated with a high prevalence of phenotypic INH resistance were identified and their 3D structures modeled before subjecting them to MD simulations. Global analysis showed an unstable KatG structure and active site environment in the mutants compared to the wildtype. Active site dynamics in the mutants compromised cofactor (heme) interactions resulting in less bonds/interactions compared to the wildtype. Given the importance of the heme, reduced interactions affect enzyme function. Trajectory analysis also showed asymmetric protomer behavior both in the wildtype and mutant systems. DRN analysis identified the KatG dimerization domain and C-terminal domain as functionally important and influential in the enzyme function as per betweenness centrality and eigenvector centrality distribution. In the case of the MtPncA enzyme, our main focus was on understanding the MtPncA binding ability of Nicotinamide (an analogue of PZA) in comparison to PZA, especially in the presence of 82 resistance conferring MtPncA mutations. Like in KatG, the mutant structures were modeled and subjected to MD simulations and analysis. Interestingly, more MtPncA mutants favored NAM interactions compared to PZA i.e., 34 MtPncA mutants steadily coordinated NAM compared to 21 in the case of PZA. Trajectory and ligand interaction analysis showed how increased active site lid loop dynamics affect the NAM binding, especially in the systems with the active site mutations i.e., H51Y, W68R, C72R, L82R, K96N, L159N, and L159R. This led to fewer protein-ligand interactions and eventually ligand ejection. Network analysis further identified the protein core, metal binding site (MBS), and substrate binding site as the most important regions of the enzyme. Furthermore, the degree of centrality analysis showed how specific MtPncA mutations i.e., C14H, F17D, and T412P, interrupt intra-protein communication from the MtPncA core to the MBS, affecting enzyme activity. The analysis of KatG and MtPncA enzyme mutations not only identified the effects of mutations on enzyme behaviour and communication, but also established a framework of computational approaches that can be used for mutational studies in any protein. Besides AMR, the continued encroachment of wildlife habitats due to population growth has exposed humans to wildlife pathogens leading to zoonotic diseases, a recent example being coronavirus disease 2019 (COVID-19). In the second part of the thesis, the established computational approaches in Part 1, were employed to investigate the changes in inter-protein interactions and communication patterns between the severe acute respiratory coronavirus 2 (SARS-CoV-2) with the human host receptor protein (ACE2: angiotensin-converting enzyme 2) consequent to mutations in the SARS-CoV-2 receptor binding domain (RBD). Here, the focus was on RBD mutations of the Omicron sub-lineages. We identified four Omicron-sub lineages with RBD mutations i.e., BA.1, BA.2, BA.3 and BA.4. Each sub-lineage mutations were modeled into RBD structure in complex with the hACE2. MD analysis of the RBD-hACE2 complex highlighted how the RBD mutations change the conformational flexibility of both the RBD and hACE2 compared to the wildtype (WT). Furthermore, DRN analysis identified novel allosteric paths composed of residues with high betweenness and eigenvector centralities linking the RBD to the hACE2 in both the wildtype and mutant systems. Interestingly, these paths were modified with the progression of Omicron sub-lineages, highlighting how the virus evolution affects protein interaction. Lastly, the effect of mutations on S RBD and hACE2 interaction was investigated from the hACE2 perspective by focusing on mutations in the hACE2 protein. Here, naturally occurring hACE2 polymorphisms in African populations i.e., S19P, K26R, M82I, K341R, N546D, and D597Q, were identified and their effects on RBD-hACE2 interactions investigated in presence of the Omicron BA.4/5 RBD mutations. The hACE2 polymorphisms subtly affected the complex dynamics; however, RBD-hACE2 interaction analysis showed that hACE2 mutations effect the complex formation and interaction. Here, the K26R mutation favored RBD-hACE2 interactions, whereas S19P resulted in fewer inter-protein interactions than the reference system. The M82I mutation resulted in a higher RBD-hACE2 binding energy compared to the wildtype meaning that the mutation might not favor RBD binding to the hACE2. On the other hand, K341R had the most RBD-hACE2 interactions suggesting that it probably favors RBD binding to the hACE2. N546D and D597Q had diminutive differences to the reference system. Interestingly, the network of high betweenness centrality residues linking the two proteins, as seen in the previous paragraph, were maintained/modified in presence of hACE2 mutations. HACE2 mutations also changed the enzyme network patterns resulting in a concentration of high eigenvector centrality residues around the zinc-binding and active site region, ultimately influencing the enzyme functionality. Altogether, the thesis highlights fundamental structural and network changes consequent to mutations both in TB and COVID-19 proteins of interest using in silico approaches. These approaches not only provide a new context on impact of mutations in TB and COVID target proteins, but also presents a framework that be implemented in other protein mutation studies. , Thesis (PhD) -- Faculty of Science, Biochemistry and Microbiology, 2023
- Full Text:
- Date Issued: 2023-10-13
The effects of different shift patterns on nurses’ sleep-wake behaviours in selected, private healthcare facilities
- Authors: Bell, Emma Catherine
- Date: 2023-10-13
- Subjects: Fatigue , Fatigue in the workplace , Sleep deprivation , Sleep-wake cycle , Shift systems , Nurses , Health facilities, Proprietary
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424219 , vital:72134
- Description: Nurses are required to work shifts to provide 24-hour care, in which they complete physically and mentally demanding tasks. The length and type of shifts, particularly night shifts interfere with the natural sleep-wake behaviours, leading to extended wakefulness and overall reduced sleep, and increase the likelihood of sleepiness during subsequent shifts. This can in turn affected various cognitive processes such attention, vigilance and alertness, which are necessary during the care process. Sleepiness as a result of working shifts has also been associated with an increased risk accidents and error during the delivery of care. Given the unique demands and ways in which workplaces are structured, each context arranges its shifts in unique ways and thus, in order to determine how to manage the effects of shift work, it is important to understand how it affects self-reported fatigue and sleep, of, in this case, nurses. While there has been extensive research on this in the global north, to date, there has been limited research aimed at examining the effects of shift work on nurses’ sleep-wake behaviours and fatigue in the South African context. Therefore, the aim of this study is to characterise shift arrangements in selected private facilities and explore its effects on private healthcare nurses. This study adopted a cross-sectional, survey design using an amended version of Standard Shiftwork Index. The questionnaire included demographic and shift details and explored the impact of the shift systems on nurse sleep-wake behaviours and disturbances and fatigue and workload. It was distributed among shift working nurses registered with the South African Nursing Council across three selected, private, healthcare facilities in the Eastern Cape, over a two-month period. The responses were analysed with descriptive and inferential statistics, with open-ended questions analysed using a thematic analysis. A total of 51 nurses completed the survey. Nurses worked 12-hour shifts which included night shifts and day shifts with fixed start and end times. Over time was commonly reported and generally, nurses reported having very little control over their shift arrangements. Overall, nurses slept less than what they reported they needed on duty days, with nurses working both day and night shifts reporting to sleep less than the globally recommended required sleep. This was compensated for by longer sleep durations during days off. The data collection revealed that three different shift arrangements were in use, including permanent day shifts, permanent night shifts and rotating shift work including nights, with permanent night nurses working significantly more consecutive shifts (seven) than the other two shift types and having significantly more days off (seven) as well. While there were no significant differences in self-reported sleep across the three shift types, permanent night nurses were found to have the shortest sleep. During days off, rotating nurse reported significantly longer sleep times compared to day shift workers which may point to the need to catch up from sleep debt. Rotating nurses experienced the greater total disturbances to their sleep than permanent day and permanent night shift nurses. While not statistically significant, it may point to the fact that rotating shift workers could not obtain regularly timed sleep (due to having to change their schedules) compared to permanent day and night nurses. Workload (physical, emotional, mental and time pressure) did not differ between the shifts (day or night) or the shift types, but did reflect a heavier workload, possibly due to the data collection occurring during the 5th wave of the COVID 19 pandemic. This study highlights that nurses in private healthcare facilities are working extended hours which were associated with reduced total sleep, irrespective of the nature of the shift, with rotating shift nurses experiencing some degree of greater disturbances to their sleep. The number, duration speed and direction of the shifts of rotating nurses needs to be explored further, whilst also exploring the influence of individual factors on sleep-wake behaviours of nurses. It may be beneficial for the healthcare facilities to implement fatigue management strategies to mitigate the negative impacts of shift work, given the impact that this may impact the delivery of care. , Thesis (MSc) -- Faculty of Science, Human Kinetics and Ergonomics, 2023
- Full Text:
- Date Issued: 2023-10-13
- Authors: Bell, Emma Catherine
- Date: 2023-10-13
- Subjects: Fatigue , Fatigue in the workplace , Sleep deprivation , Sleep-wake cycle , Shift systems , Nurses , Health facilities, Proprietary
- Language: English
- Type: Academic theses , Master's theses , text
- Identifier: http://hdl.handle.net/10962/424219 , vital:72134
- Description: Nurses are required to work shifts to provide 24-hour care, in which they complete physically and mentally demanding tasks. The length and type of shifts, particularly night shifts interfere with the natural sleep-wake behaviours, leading to extended wakefulness and overall reduced sleep, and increase the likelihood of sleepiness during subsequent shifts. This can in turn affected various cognitive processes such attention, vigilance and alertness, which are necessary during the care process. Sleepiness as a result of working shifts has also been associated with an increased risk accidents and error during the delivery of care. Given the unique demands and ways in which workplaces are structured, each context arranges its shifts in unique ways and thus, in order to determine how to manage the effects of shift work, it is important to understand how it affects self-reported fatigue and sleep, of, in this case, nurses. While there has been extensive research on this in the global north, to date, there has been limited research aimed at examining the effects of shift work on nurses’ sleep-wake behaviours and fatigue in the South African context. Therefore, the aim of this study is to characterise shift arrangements in selected private facilities and explore its effects on private healthcare nurses. This study adopted a cross-sectional, survey design using an amended version of Standard Shiftwork Index. The questionnaire included demographic and shift details and explored the impact of the shift systems on nurse sleep-wake behaviours and disturbances and fatigue and workload. It was distributed among shift working nurses registered with the South African Nursing Council across three selected, private, healthcare facilities in the Eastern Cape, over a two-month period. The responses were analysed with descriptive and inferential statistics, with open-ended questions analysed using a thematic analysis. A total of 51 nurses completed the survey. Nurses worked 12-hour shifts which included night shifts and day shifts with fixed start and end times. Over time was commonly reported and generally, nurses reported having very little control over their shift arrangements. Overall, nurses slept less than what they reported they needed on duty days, with nurses working both day and night shifts reporting to sleep less than the globally recommended required sleep. This was compensated for by longer sleep durations during days off. The data collection revealed that three different shift arrangements were in use, including permanent day shifts, permanent night shifts and rotating shift work including nights, with permanent night nurses working significantly more consecutive shifts (seven) than the other two shift types and having significantly more days off (seven) as well. While there were no significant differences in self-reported sleep across the three shift types, permanent night nurses were found to have the shortest sleep. During days off, rotating nurse reported significantly longer sleep times compared to day shift workers which may point to the need to catch up from sleep debt. Rotating nurses experienced the greater total disturbances to their sleep than permanent day and permanent night shift nurses. While not statistically significant, it may point to the fact that rotating shift workers could not obtain regularly timed sleep (due to having to change their schedules) compared to permanent day and night nurses. Workload (physical, emotional, mental and time pressure) did not differ between the shifts (day or night) or the shift types, but did reflect a heavier workload, possibly due to the data collection occurring during the 5th wave of the COVID 19 pandemic. This study highlights that nurses in private healthcare facilities are working extended hours which were associated with reduced total sleep, irrespective of the nature of the shift, with rotating shift nurses experiencing some degree of greater disturbances to their sleep. The number, duration speed and direction of the shifts of rotating nurses needs to be explored further, whilst also exploring the influence of individual factors on sleep-wake behaviours of nurses. It may be beneficial for the healthcare facilities to implement fatigue management strategies to mitigate the negative impacts of shift work, given the impact that this may impact the delivery of care. , Thesis (MSc) -- Faculty of Science, Human Kinetics and Ergonomics, 2023
- Full Text:
- Date Issued: 2023-10-13
Puma (Puma concolor) sex influences diet in southwest New Mexico
- Bernard, Kelly M T, Perry, Travis W, Mgqatsa, Nokubonga
- Authors: Bernard, Kelly M T , Perry, Travis W , Mgqatsa, Nokubonga
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/462647 , vital:76322 , xlink:href="https://doi.org/10.3398/064.083.0201"
- Description: Puma (Puma concolor) is a wide-ranging, large felid species, and site-specific research on its diet is important for local management. Like the diets of other large felids, puma diets may differ between sex due to size dimorphism and between seasons due to changes in prey vulnerability and availability. We investigated the influence of sex and season on puma diet in southwest New Mexico in terms of prey species and size categories. Pumas (10 males, 6 females) were tracked with GPS collars for an average of one year per individual between February 2008 and July 2020. Puma location was recorded every 2 hours between 19:00 and 7:00, and kill sites were identified by a minimum of 2 GPS fixes occurring within 100 m and 100 hours of the first fix. Pumas specialized on mule deer (Odocoileus hemionus) and elk (Cervus elaphus) but also preyed upon a range of other species of different sizes. The probability of making a medium-sized kill such as a mule deer was higher for females than for males, while the probability of making an extra-large kill, such as an elk, was considerably greater for males than for females. There was substantial variation in prey species and size categories killed by individual pumas, particularly of smaller-sized prey like collared peccary (Pecari tajacu) and skunks (e.g., Spilogale gracilis, Mephitis mephitis). Our findings concur with previous research on the importance of mule deer and elk in puma diet, demonstrate individual variation in prey killed, and may have management implications.
- Full Text:
- Date Issued: 2023
- Authors: Bernard, Kelly M T , Perry, Travis W , Mgqatsa, Nokubonga
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/462647 , vital:76322 , xlink:href="https://doi.org/10.3398/064.083.0201"
- Description: Puma (Puma concolor) is a wide-ranging, large felid species, and site-specific research on its diet is important for local management. Like the diets of other large felids, puma diets may differ between sex due to size dimorphism and between seasons due to changes in prey vulnerability and availability. We investigated the influence of sex and season on puma diet in southwest New Mexico in terms of prey species and size categories. Pumas (10 males, 6 females) were tracked with GPS collars for an average of one year per individual between February 2008 and July 2020. Puma location was recorded every 2 hours between 19:00 and 7:00, and kill sites were identified by a minimum of 2 GPS fixes occurring within 100 m and 100 hours of the first fix. Pumas specialized on mule deer (Odocoileus hemionus) and elk (Cervus elaphus) but also preyed upon a range of other species of different sizes. The probability of making a medium-sized kill such as a mule deer was higher for females than for males, while the probability of making an extra-large kill, such as an elk, was considerably greater for males than for females. There was substantial variation in prey species and size categories killed by individual pumas, particularly of smaller-sized prey like collared peccary (Pecari tajacu) and skunks (e.g., Spilogale gracilis, Mephitis mephitis). Our findings concur with previous research on the importance of mule deer and elk in puma diet, demonstrate individual variation in prey killed, and may have management implications.
- Full Text:
- Date Issued: 2023
The Southern African Program on Ecosystem Change and Society: an emergent community of practice
- Biggs, Reinette, Reyers, Belinda, Blanchard, Ryan, Clements, Hayley S, Cockburn, Jessica J, Cumming, Graeme S, Cundill, Georgina, de Vos, Alta, Dziba, Luthando E, Esler, Karen J, Fabricius, Christo, Hamann, Maike, Henriksson, Rebecka, Kotschy, Karen, Lindborg, Regina, Luvuno, Linda, Masterson, Vanessa A, Nel, Jeanne L, O'Farrell, Patrick, Palmer, Carolyn G, Pereira, Laura, Pollard, Sharon, Preiser, Rika, Roux, Dirk J, Scholes, Robert J, Selomane, Odirilwe, Shackleton, Charlie M, Shackleton, Sheona E, Sitas, Nadia, Slingsby, Jasper A, Spierenburg, Marja, Tengö, Maria
- Authors: Biggs, Reinette , Reyers, Belinda , Blanchard, Ryan , Clements, Hayley S , Cockburn, Jessica J , Cumming, Graeme S , Cundill, Georgina , de Vos, Alta , Dziba, Luthando E , Esler, Karen J , Fabricius, Christo , Hamann, Maike , Henriksson, Rebecka , Kotschy, Karen , Lindborg, Regina , Luvuno, Linda , Masterson, Vanessa A , Nel, Jeanne L , O'Farrell, Patrick , Palmer, Carolyn G , Pereira, Laura , Pollard, Sharon , Preiser, Rika , Roux, Dirk J , Scholes, Robert J , Selomane, Odirilwe , Shackleton, Charlie M , Shackleton, Sheona E , Sitas, Nadia , Slingsby, Jasper A , Spierenburg, Marja , Tengö, Maria
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/401330 , vital:69726 , xlink:href="https://doi.org/10.1080/26395916.2022.2150317"
- Description: Sustainability-focused research networks and communities of practice have emerged as a key response and strategy to build capacity and knowledge to support transformation towards more sustainable, just and equitable futures. This paper synthesises insights from the development of a community of practice on social-ecological systems (SES) research in southern Africa over the past decade, linked to the international Programme on Ecosystem Change and Society (PECS). This community consists of a network of researchers who carry out place-based SES research in the southern African region. They interact through various cross-cutting working groups and also host a variety of public colloquia and student and practitioner training events. Known as the Southern African Program on Ecosystem Change and Society (SAPECS), its core objectives are to: (1) derive new approaches and empirical insights on SES dynamics in the southern African context; (2) have a tangible impact by mainstreaming knowledge into policy and practice; and (3) grow the community of practice engaged in SES research and governance, including researchers, students and practitioners. This paper reflects on experiences in building the SAPECS community, with the aim of supporting the development of similar networks elsewhere in the world, particularly in the Global South.
- Full Text:
- Date Issued: 2023
- Authors: Biggs, Reinette , Reyers, Belinda , Blanchard, Ryan , Clements, Hayley S , Cockburn, Jessica J , Cumming, Graeme S , Cundill, Georgina , de Vos, Alta , Dziba, Luthando E , Esler, Karen J , Fabricius, Christo , Hamann, Maike , Henriksson, Rebecka , Kotschy, Karen , Lindborg, Regina , Luvuno, Linda , Masterson, Vanessa A , Nel, Jeanne L , O'Farrell, Patrick , Palmer, Carolyn G , Pereira, Laura , Pollard, Sharon , Preiser, Rika , Roux, Dirk J , Scholes, Robert J , Selomane, Odirilwe , Shackleton, Charlie M , Shackleton, Sheona E , Sitas, Nadia , Slingsby, Jasper A , Spierenburg, Marja , Tengö, Maria
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/401330 , vital:69726 , xlink:href="https://doi.org/10.1080/26395916.2022.2150317"
- Description: Sustainability-focused research networks and communities of practice have emerged as a key response and strategy to build capacity and knowledge to support transformation towards more sustainable, just and equitable futures. This paper synthesises insights from the development of a community of practice on social-ecological systems (SES) research in southern Africa over the past decade, linked to the international Programme on Ecosystem Change and Society (PECS). This community consists of a network of researchers who carry out place-based SES research in the southern African region. They interact through various cross-cutting working groups and also host a variety of public colloquia and student and practitioner training events. Known as the Southern African Program on Ecosystem Change and Society (SAPECS), its core objectives are to: (1) derive new approaches and empirical insights on SES dynamics in the southern African context; (2) have a tangible impact by mainstreaming knowledge into policy and practice; and (3) grow the community of practice engaged in SES research and governance, including researchers, students and practitioners. This paper reflects on experiences in building the SAPECS community, with the aim of supporting the development of similar networks elsewhere in the world, particularly in the Global South.
- Full Text:
- Date Issued: 2023
Enabling Vehicle Search Through Robust Licence Plate Detection
- Boby, Alden, Brown, Dane L, Connan, James, Marais, Marc, Kuhlane, Luxolo L
- Authors: Boby, Alden , Brown, Dane L , Connan, James , Marais, Marc , Kuhlane, Luxolo L
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/463372 , vital:76403 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10220508"
- Description: Licence plate recognition has many practical applications for security and surveillance. This paper presents a robust licence plate detection system that uses string-matching algorithms to identify a vehicle in data. Object detection models have had limited application in the character recognition domain. The system utilises the YOLO object detection model to perform character recognition to ensure more accurate character predictions. The model incorporates super-resolution techniques to enhance the quality of licence plate images to increase character recognition accuracy. The proposed system can accurately detect license plates in diverse conditions and can handle license plates with varying fonts and backgrounds. The system's effectiveness is demonstrated through experimentation on components of the system, showing promising license plate detection and character recognition accuracy. The overall system works with all the components to track vehicles by matching a target string with detected licence plates in a scene. The system has potential applications in law enforcement, traffic management, and parking systems and can significantly advance surveillance and security through automation.
- Full Text:
- Date Issued: 2023
- Authors: Boby, Alden , Brown, Dane L , Connan, James , Marais, Marc , Kuhlane, Luxolo L
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/463372 , vital:76403 , xlink:href="https://ieeexplore.ieee.org/abstract/document/10220508"
- Description: Licence plate recognition has many practical applications for security and surveillance. This paper presents a robust licence plate detection system that uses string-matching algorithms to identify a vehicle in data. Object detection models have had limited application in the character recognition domain. The system utilises the YOLO object detection model to perform character recognition to ensure more accurate character predictions. The model incorporates super-resolution techniques to enhance the quality of licence plate images to increase character recognition accuracy. The proposed system can accurately detect license plates in diverse conditions and can handle license plates with varying fonts and backgrounds. The system's effectiveness is demonstrated through experimentation on components of the system, showing promising license plate detection and character recognition accuracy. The overall system works with all the components to track vehicles by matching a target string with detected licence plates in a scene. The system has potential applications in law enforcement, traffic management, and parking systems and can significantly advance surveillance and security through automation.
- Full Text:
- Date Issued: 2023
A Practical Use for AI-Generated Images
- Boby, Alden, Brown, Dane L, Connan, James
- Authors: Boby, Alden , Brown, Dane L , Connan, James
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/463345 , vital:76401 , xlink:href="https://link.springer.com/chapter/10.1007/978-3-031-43838-7_12"
- Description: Collecting data for research can be costly and time-consuming, and available methods to speed up the process are limited. This research paper compares real data and AI-generated images for training an object detection model. The study aimed to assess how the utilisation of AI-generated images influences the performance of an object detection model. The study used a popular object detection model, YOLO, and trained it on a dataset with real car images as well as a synthetic dataset generated with a state-of-the-art diffusion model. The results showed that while the model trained on real data performed better on real-world images, the model trained on AI-generated images, in some cases, showed improved performance on certain images and was good enough to function as a licence plate detector on its own. The study highlights the potential of using AI-generated images for data augmentation in object detection models and sheds light on the trade-off between real and synthetic data in the training process. The findings of this study can inform future research in object detection and help practitioners make informed decisions when choosing between real and synthetic data for training object detection models.
- Full Text:
- Date Issued: 2023
- Authors: Boby, Alden , Brown, Dane L , Connan, James
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/463345 , vital:76401 , xlink:href="https://link.springer.com/chapter/10.1007/978-3-031-43838-7_12"
- Description: Collecting data for research can be costly and time-consuming, and available methods to speed up the process are limited. This research paper compares real data and AI-generated images for training an object detection model. The study aimed to assess how the utilisation of AI-generated images influences the performance of an object detection model. The study used a popular object detection model, YOLO, and trained it on a dataset with real car images as well as a synthetic dataset generated with a state-of-the-art diffusion model. The results showed that while the model trained on real data performed better on real-world images, the model trained on AI-generated images, in some cases, showed improved performance on certain images and was good enough to function as a licence plate detector on its own. The study highlights the potential of using AI-generated images for data augmentation in object detection models and sheds light on the trade-off between real and synthetic data in the training process. The findings of this study can inform future research in object detection and help practitioners make informed decisions when choosing between real and synthetic data for training object detection models.
- Full Text:
- Date Issued: 2023
Trauma survivors’ perceptions and experiences of prolonged exposure for PTSD at a psychology clinic
- Booysen, Duane D, Kagee, Ashraf
- Authors: Booysen, Duane D , Kagee, Ashraf
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/454177 , vital:75316 , xlink:href="https://hdl.handle.net/10520/ejc-m_sajp_v29_n1_a1869"
- Description: BACKGROUND Several trauma-focused treatments have been developed to treat post-traumatic stress disorder (PTSD). Yet there are limited studies on how trauma survivors perceive and experience trauma-focused treatments such as prolonged exposure therapy (PE) for PTSD, especially in low- and middle-income countries (LMIC). AIM The study aimed to explore the perceptions and experiences of trauma survivors receiving prolonged exposure therapy for PTSD and the general acceptability of PE for PTSD in a LMIC.
- Full Text:
- Date Issued: 2023
- Authors: Booysen, Duane D , Kagee, Ashraf
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/454177 , vital:75316 , xlink:href="https://hdl.handle.net/10520/ejc-m_sajp_v29_n1_a1869"
- Description: BACKGROUND Several trauma-focused treatments have been developed to treat post-traumatic stress disorder (PTSD). Yet there are limited studies on how trauma survivors perceive and experience trauma-focused treatments such as prolonged exposure therapy (PE) for PTSD, especially in low- and middle-income countries (LMIC). AIM The study aimed to explore the perceptions and experiences of trauma survivors receiving prolonged exposure therapy for PTSD and the general acceptability of PE for PTSD in a LMIC.
- Full Text:
- Date Issued: 2023
The use of a Subjective wellbeing scale as predictor of adherence to neuroleptic treatment to determine poor prognostic factor in African population with Schizophrenia
- Boshe, J J, Stein, Dan J, Campbell, Megan M
- Authors: Boshe, J J , Stein, Dan J , Campbell, Megan M
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/450766 , vital:74980 , xlink:href="10.1192/j.eurpsy.2023.384"
- Description: Objectives: To investigate and identify demographic and clinical predic-tors of subjective well-being in a sample of Xhosa people with schizo-phrenia on neuroleptic treatment. Methods: As a part of a large genetic study, 244 study participants with a confirmed diagnosis of schizophre-nia completed the translated SWN-K 20 scale. Internal consistency analysis was performed, and convergent analysis and exploratory analysis were conducted using Principal Component Analysis (PCA). Linear regression methods were used to determine predictors of SWBN in the sample population.
- Full Text:
- Date Issued: 2023
- Authors: Boshe, J J , Stein, Dan J , Campbell, Megan M
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/450766 , vital:74980 , xlink:href="10.1192/j.eurpsy.2023.384"
- Description: Objectives: To investigate and identify demographic and clinical predic-tors of subjective well-being in a sample of Xhosa people with schizo-phrenia on neuroleptic treatment. Methods: As a part of a large genetic study, 244 study participants with a confirmed diagnosis of schizophre-nia completed the translated SWN-K 20 scale. Internal consistency analysis was performed, and convergent analysis and exploratory analysis were conducted using Principal Component Analysis (PCA). Linear regression methods were used to determine predictors of SWBN in the sample population.
- Full Text:
- Date Issued: 2023
Count me in: Leopard population density in an area of mixed land‐use, Eastern Cape, South Africa
- Bouderka, Safia, Perry, Travis W, Parker, Daniel M, Beukes, Maya, Mgqatsa, Nokubonga
- Authors: Bouderka, Safia , Perry, Travis W , Parker, Daniel M , Beukes, Maya , Mgqatsa, Nokubonga
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/462591 , vital:76317 , xlink:href="https://doi.org/10.1111/aje.13078"
- Description: Although the leopard (Panthera pardus) has the widest range of any felid in the world is designated as a vulnerable species, mainly because of human-induced conflict (Jacobson et al., 2016). Our study focuses on a population of leopards on privately owned, mixed-use farmland (Baviaanskloof Hartland–BH hereafter) which is adjacent to the Baviaanskloof Mega Reserve (BMR) in the Baviaanskloof UNESCO World Heritage Site of the Eastern Cape, South Africa. Given the unique make-up of the region, with sometimes conflicting management objectives, the status of leopards in the broader Baviaanskloof is of particular interest to a range of stakeholders. However, despite the need for management decisions to be based on reliable and regular population monitoring efforts (Elliot et al., 2020), the last formal assessment of the leopard population in the Baviaanskloof was performed in 2011/2012 but published 9 years later (Devens et al., 2018). The only other assessment of the status of leopards in the region was an unpublished Master's project (McManus, 2009). Here, we use photographic captures of leopards and a Spatially Explicit Capture Recapture (SECR) analytical framework in the mixed-use BH region of the Baviaanskloof to generate an up-to-date leopard population density estimate that can inform conservation management of the species in this important World Heritage Site.
- Full Text:
- Date Issued: 2023
- Authors: Bouderka, Safia , Perry, Travis W , Parker, Daniel M , Beukes, Maya , Mgqatsa, Nokubonga
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/462591 , vital:76317 , xlink:href="https://doi.org/10.1111/aje.13078"
- Description: Although the leopard (Panthera pardus) has the widest range of any felid in the world is designated as a vulnerable species, mainly because of human-induced conflict (Jacobson et al., 2016). Our study focuses on a population of leopards on privately owned, mixed-use farmland (Baviaanskloof Hartland–BH hereafter) which is adjacent to the Baviaanskloof Mega Reserve (BMR) in the Baviaanskloof UNESCO World Heritage Site of the Eastern Cape, South Africa. Given the unique make-up of the region, with sometimes conflicting management objectives, the status of leopards in the broader Baviaanskloof is of particular interest to a range of stakeholders. However, despite the need for management decisions to be based on reliable and regular population monitoring efforts (Elliot et al., 2020), the last formal assessment of the leopard population in the Baviaanskloof was performed in 2011/2012 but published 9 years later (Devens et al., 2018). The only other assessment of the status of leopards in the region was an unpublished Master's project (McManus, 2009). Here, we use photographic captures of leopards and a Spatially Explicit Capture Recapture (SECR) analytical framework in the mixed-use BH region of the Baviaanskloof to generate an up-to-date leopard population density estimate that can inform conservation management of the species in this important World Heritage Site.
- Full Text:
- Date Issued: 2023
An Exploration of Flow Control Using Machine Learning and Computational Fluid Dynamics
- Bradshaw, Karen L, Cornfield Matthew
- Authors: Bradshaw, Karen L , Cornfield Matthew
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/440211 , vital:73757 , xlink:href="https://doi.org/10.59200/ICARTI.2023.017"
- Description: Although numerous studies relating to computational fluid dynamics and machine learning have been conducted in relation to automotive development, the majority focus on either early development using completed 3D models, or the final testing stages of development, or machine learning accelerated computational fluid dynamic simulations. While this approach is helpful in software development and simulation, it is not easily adaptable to automotive design where the final model is constantly changing and being modified. Consequently, the aim of this study is to propose a method for conducting computational fluid dynamics and machine learning concurrently to accelerate the development process. The proposed method is used to design and improve the aerodynamic efficiency of an object. The approach focuses on developing, implementing, and comparing machine learning models capable of generating optimised three-dimensional objects with the required geometry to direct airflow paths required in applications such as pressure generation, as needed for both active and passive flow control. The study concludes that both decision tree regression and long short-term memory (LSTM) autoencoder models could be used to optimise the aerodynamic efficiency of solid bodies, but that the LSTM autoencoder performs better overall. An undesirable effect of the shape optimisation is an overall reduction in shape size as optimization increases.
- Full Text:
- Date Issued: 2023
- Authors: Bradshaw, Karen L , Cornfield Matthew
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/440211 , vital:73757 , xlink:href="https://doi.org/10.59200/ICARTI.2023.017"
- Description: Although numerous studies relating to computational fluid dynamics and machine learning have been conducted in relation to automotive development, the majority focus on either early development using completed 3D models, or the final testing stages of development, or machine learning accelerated computational fluid dynamic simulations. While this approach is helpful in software development and simulation, it is not easily adaptable to automotive design where the final model is constantly changing and being modified. Consequently, the aim of this study is to propose a method for conducting computational fluid dynamics and machine learning concurrently to accelerate the development process. The proposed method is used to design and improve the aerodynamic efficiency of an object. The approach focuses on developing, implementing, and comparing machine learning models capable of generating optimised three-dimensional objects with the required geometry to direct airflow paths required in applications such as pressure generation, as needed for both active and passive flow control. The study concludes that both decision tree regression and long short-term memory (LSTM) autoencoder models could be used to optimise the aerodynamic efficiency of solid bodies, but that the LSTM autoencoder performs better overall. An undesirable effect of the shape optimisation is an overall reduction in shape size as optimization increases.
- Full Text:
- Date Issued: 2023
Darknet Traffic Detection Using Histogram-Based Gradient Boosting
- Brown, Dane L, Sepula, Chikondi
- Authors: Brown, Dane L , Sepula, Chikondi
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/464063 , vital:76472 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_59"
- Description: The network security sector has observed a rise in severe attacks emanating from the darknet or encrypted networks in recent years. Network intrusion detection systems (NIDS) capable of detecting darknet or encrypted traffic must be developed to increase system security. Machine learning algorithms can effectively detect darknet activities when trained on encrypted and conventional network data. However, the performance of the system may be influenced, among other things, by the choice of machine learning models, data preparation techniques, and feature selection methodologies. The histogram-based gradient boosting strategy known as categorical boosting (CatBoost) was tested to see how well it could find darknet traffic. The performance of the model was examined using feature selection strategies such as correlation coefficient, variance threshold, SelectKBest, and recursive feature removal (RFE). Following the categorization of traffic as “darknet” or “regular”, a multi-class classification was used to determine the software application associated with the traffic. Further study was carried out on well-known machine learning methods such as random forests (RF), decision trees (DT), linear support vector classifier (SVC Linear), and long-short term memory (LST) (LSTM). The proposed model achieved good results with 98.51% binary classification accuracy and 88% multi-class classification accuracy.
- Full Text:
- Date Issued: 2023
- Authors: Brown, Dane L , Sepula, Chikondi
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/464063 , vital:76472 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_59"
- Description: The network security sector has observed a rise in severe attacks emanating from the darknet or encrypted networks in recent years. Network intrusion detection systems (NIDS) capable of detecting darknet or encrypted traffic must be developed to increase system security. Machine learning algorithms can effectively detect darknet activities when trained on encrypted and conventional network data. However, the performance of the system may be influenced, among other things, by the choice of machine learning models, data preparation techniques, and feature selection methodologies. The histogram-based gradient boosting strategy known as categorical boosting (CatBoost) was tested to see how well it could find darknet traffic. The performance of the model was examined using feature selection strategies such as correlation coefficient, variance threshold, SelectKBest, and recursive feature removal (RFE). Following the categorization of traffic as “darknet” or “regular”, a multi-class classification was used to determine the software application associated with the traffic. Further study was carried out on well-known machine learning methods such as random forests (RF), decision trees (DT), linear support vector classifier (SVC Linear), and long-short term memory (LST) (LSTM). The proposed model achieved good results with 98.51% binary classification accuracy and 88% multi-class classification accuracy.
- Full Text:
- Date Issued: 2023
Efficient Plant Disease Detection and Classification for Android
- Brown, Dane L, Mazibuko, Sifisokuhle
- Authors: Brown, Dane L , Mazibuko, Sifisokuhle
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/464096 , vital:76475 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_39"
- Description: This paper investigates the feasibility of using a CNN model to diagnose plant diseases in the wild. Plant diseases are a major risk to ecosystems, human and animal health, and the quality of life overall. They may reduce farm productivity drastically, leaving farmers with financial losses and food insecurity. Small-scale farmers and producers cannot pay for an expert to look at their plants for plant diseases because it would cost too much. A mobile solution is thus built for the Android platform that utilises a unified deep learning model to diagnose plant diseases and provide farmers with treatment information. The literature-recommended CNN architectures were first analysed on the PlantVillage dataset, and the best-performing model was trained for integration into the application. While training on the tomato subset of the PlantVillage dataset, the VGG16 and InceptionV3 networks achieved a higher F1-score of 94.49% than the MobileNetsV3Large and EfficientNetB0 networks (without parameter tuning). The VGG model achieved 94.43% accuracy and 0.24 loss on the RGB PlantVillage dataset, outperforming the segmented and greyscaled datasets, and was therefore chosen for use in the application. When tested on complex data collected in the wild, the VGG16 model trained on the RGB dataset yielded an accuracy of 63.02%. Thus, this research revealed the discrepancy between simple and real-world data, as well as the viability of present methodologies for future research.
- Full Text:
- Date Issued: 2023
- Authors: Brown, Dane L , Mazibuko, Sifisokuhle
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/464096 , vital:76475 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_39"
- Description: This paper investigates the feasibility of using a CNN model to diagnose plant diseases in the wild. Plant diseases are a major risk to ecosystems, human and animal health, and the quality of life overall. They may reduce farm productivity drastically, leaving farmers with financial losses and food insecurity. Small-scale farmers and producers cannot pay for an expert to look at their plants for plant diseases because it would cost too much. A mobile solution is thus built for the Android platform that utilises a unified deep learning model to diagnose plant diseases and provide farmers with treatment information. The literature-recommended CNN architectures were first analysed on the PlantVillage dataset, and the best-performing model was trained for integration into the application. While training on the tomato subset of the PlantVillage dataset, the VGG16 and InceptionV3 networks achieved a higher F1-score of 94.49% than the MobileNetsV3Large and EfficientNetB0 networks (without parameter tuning). The VGG model achieved 94.43% accuracy and 0.24 loss on the RGB PlantVillage dataset, outperforming the segmented and greyscaled datasets, and was therefore chosen for use in the application. When tested on complex data collected in the wild, the VGG16 model trained on the RGB dataset yielded an accuracy of 63.02%. Thus, this research revealed the discrepancy between simple and real-world data, as well as the viability of present methodologies for future research.
- Full Text:
- Date Issued: 2023
Learning Movement Patterns for Improving the Skills of Beginner Level Players in Competitive MOBAs
- Brown, Dane L, Bischof, Jonah
- Authors: Brown, Dane L , Bischof, Jonah
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/464161 , vital:76482 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_45"
- Description: League of Legends is a massively multiplayer online battle arena (MOBA)—a form of online competitive game in which teams of five players battle to demolish the opponent’s base. Expert players are aware of when to target, how to maximise their gold, and how to make choices. These are some of the talents that distinguish them from novices. The Riot API enables the retrieval of current League of Legends game data. This data is used to construct machine learning models that can benefit amateur players. Kills and goals can assist seasoned players understand how to take advantage of micro- and macro-teams. By understanding how professional players differ from novices, we may build tools to assist novices’ decision-making. 19 of 20 games for training a random forest (RF) and decision tree (DT) regressor produced encouraging results. An unseen game was utilised to evaluate the impartiality of the findings. RF and DT correctly predicted the locations of all game events in Experiment 1 with MSEs of 9.5 and 10.6. The purpose of the previous experiment was to fine-tune when novice players deviate from professional player behaviour and establish a solid commencement for battles. Based on this discrepancy, the system provided the player with reliable recommendations on which quadrant they should be in and which event/objective they should complete. This has shown to be a beneficial method for modelling player behaviour in future research.
- Full Text:
- Date Issued: 2023
- Authors: Brown, Dane L , Bischof, Jonah
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/464161 , vital:76482 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-99-1624-5_45"
- Description: League of Legends is a massively multiplayer online battle arena (MOBA)—a form of online competitive game in which teams of five players battle to demolish the opponent’s base. Expert players are aware of when to target, how to maximise their gold, and how to make choices. These are some of the talents that distinguish them from novices. The Riot API enables the retrieval of current League of Legends game data. This data is used to construct machine learning models that can benefit amateur players. Kills and goals can assist seasoned players understand how to take advantage of micro- and macro-teams. By understanding how professional players differ from novices, we may build tools to assist novices’ decision-making. 19 of 20 games for training a random forest (RF) and decision tree (DT) regressor produced encouraging results. An unseen game was utilised to evaluate the impartiality of the findings. RF and DT correctly predicted the locations of all game events in Experiment 1 with MSEs of 9.5 and 10.6. The purpose of the previous experiment was to fine-tune when novice players deviate from professional player behaviour and establish a solid commencement for battles. Based on this discrepancy, the system provided the player with reliable recommendations on which quadrant they should be in and which event/objective they should complete. This has shown to be a beneficial method for modelling player behaviour in future research.
- Full Text:
- Date Issued: 2023
Enhanced plant species and early water stress detection using visible and near-infrared spectra
- Brown, Dane L, Poole, Louise C
- Authors: Brown, Dane L , Poole, Louise C
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/463384 , vital:76404 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-19-9819-5_55"
- Description: This paper reports on recent successful work aimed at preventing crop loss and failure before visible symptoms are present. Food security is critical, especially after the COVID-19 pandemic. Detecting early-stage plant stresses in agriculture is essential in minimizing crop damage and maximizing yield. Identification of both the stress type and cause is a non-trivial multitask classification problem. However, the application of spectroscopy to early plant diseases and stress detection has become viable with recent advancements in technology. Suitable frequencies of the electromagnetic spectrum and machine learning algorithms were thus first investigated. This guided data collection in two sessions by capturing standard visible images in contrast with images from multiple spectra (VIS-IR). These images consisted of six plant species that were carefully monitored from healthy to dehydrated stages. Promising results were achieved using VIS-IR compared to standard visible images on three deep learning architectures. Statistically, significant accuracy improvements were shown for VIS-IR for early dehydration detection, where ResNet-44 modelling of VIS-IR input yielded 92.5% accuracy compared to 77.5% on visible input on general plant species. Moreover, ResNet-44 achieved good species separation.
- Full Text:
- Date Issued: 2023
- Authors: Brown, Dane L , Poole, Louise C
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/463384 , vital:76404 , xlink:href="https://link.springer.com/chapter/10.1007/978-981-19-9819-5_55"
- Description: This paper reports on recent successful work aimed at preventing crop loss and failure before visible symptoms are present. Food security is critical, especially after the COVID-19 pandemic. Detecting early-stage plant stresses in agriculture is essential in minimizing crop damage and maximizing yield. Identification of both the stress type and cause is a non-trivial multitask classification problem. However, the application of spectroscopy to early plant diseases and stress detection has become viable with recent advancements in technology. Suitable frequencies of the electromagnetic spectrum and machine learning algorithms were thus first investigated. This guided data collection in two sessions by capturing standard visible images in contrast with images from multiple spectra (VIS-IR). These images consisted of six plant species that were carefully monitored from healthy to dehydrated stages. Promising results were achieved using VIS-IR compared to standard visible images on three deep learning architectures. Statistically, significant accuracy improvements were shown for VIS-IR for early dehydration detection, where ResNet-44 modelling of VIS-IR input yielded 92.5% accuracy compared to 77.5% on visible input on general plant species. Moreover, ResNet-44 achieved good species separation.
- Full Text:
- Date Issued: 2023
Social innovation that connects people to coasts in the Anthropocene
- Celliers, Louis, Costa, Maria M, Rölfer, Lena, Aswani, Shankar, Ferse, Sebastian C A
- Authors: Celliers, Louis , Costa, Maria M , Rölfer, Lena , Aswani, Shankar , Ferse, Sebastian C A
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/391410 , vital:68649 , xlink:href="https://doi.org/10.1017/cft.2023.12"
- Description: Post-industrial society is driving global environmental change, which is a challenge for all generations, current and future. The Anthropocene is the geological epoch in which humans dominate and it is rooted in the past, present, and future. Future sustainability is building on the momentum of the fundamental importance of studying human dynamics and governance of coupled social and ecological systems. In the Anthropocene, social innovation may play a critical role in achieving new pathways to sustainability. This conventional narrative review uses a qualitative analysis anchored in the Grounded Theory Method and a systematic collection and analysis of papers to identify broad types of social innovations. Scientific journal articles published since 2018 were prioritised for inclusion. The six types of social innovation proposed are (a) authentic engagement; (b) artful and engaging communication; (c) urging and compelling change; (d) governance for social-ecological systems; (e) anticipation in governance; and (f) lived experiences and values. The six innovations proposed in this paper can be embedded within, and form part of, social action using a science–society compact for the sustainable development of coasts in the Anthropocene.
- Full Text:
- Date Issued: 2023
- Authors: Celliers, Louis , Costa, Maria M , Rölfer, Lena , Aswani, Shankar , Ferse, Sebastian C A
- Date: 2023
- Subjects: To be catalogued
- Language: English
- Type: text , article
- Identifier: http://hdl.handle.net/10962/391410 , vital:68649 , xlink:href="https://doi.org/10.1017/cft.2023.12"
- Description: Post-industrial society is driving global environmental change, which is a challenge for all generations, current and future. The Anthropocene is the geological epoch in which humans dominate and it is rooted in the past, present, and future. Future sustainability is building on the momentum of the fundamental importance of studying human dynamics and governance of coupled social and ecological systems. In the Anthropocene, social innovation may play a critical role in achieving new pathways to sustainability. This conventional narrative review uses a qualitative analysis anchored in the Grounded Theory Method and a systematic collection and analysis of papers to identify broad types of social innovations. Scientific journal articles published since 2018 were prioritised for inclusion. The six types of social innovation proposed are (a) authentic engagement; (b) artful and engaging communication; (c) urging and compelling change; (d) governance for social-ecological systems; (e) anticipation in governance; and (f) lived experiences and values. The six innovations proposed in this paper can be embedded within, and form part of, social action using a science–society compact for the sustainable development of coasts in the Anthropocene.
- Full Text:
- Date Issued: 2023