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Globalization and the call for global citizenship education have enabled virtual exchange to prepare healthcare students as emerging healthcare professionals for working in an increasingly interconnected and diverse world. Integrating virtual exchange opportunities into undergraduate curricula in higher education equips students with the knowledge, skills, and attributes needed to be responsive to global healthcare challenges. This study reports on the perceptions of undergraduate healthcare students from geographically distant locations on how (if any) participating in an international virtual exchange project fostered their intercultural competence. Anchored in social constructivism and adopting a qualitative methodology, data was collected using an online, open-ended reflective questionnaire. Findings from the thematic analysis highlight that integrating virtual exchange into curriculum design can foster intercultural competence, preparing healthcare students as emerging professionals for the world of work that necessitates an appreciation for diverse ways of knowing, being, and doing to ensure optimal healthcare.

Corporate norms and values, characterised by an enterprise ethos, became the new parameters that defined the academic environment. Academics are increasingly becoming concerned about the commodification of higher education and its impact on academic quality and the standards of quality graduates. The voices of South African academics and their experiences within the neoliberal university governance remain underexplored in the current literature. This study aimed to enhance understanding and contribute to knowledge by exploring lecturers' experiences within a corporatised academic work environment. This study took place across public and private higher education institutions in South Africa. A cross-sectional, qualitative, interpretative phenomenological research design was employed. Data was collected by means of semi-structured interviews with a diverse sample of 20 lecturers. The data analysis followed the principles of interpretative phenomenological analysis. The findings of the study identified three key areas that triggered feelings of frustration with management: (1) participants experienced a lack of management's understanding of governing academic work environments, (2) an erosion of their collegial culture, and (3) a lack of transparent communication. Contribution: A key contribution of this study, which set it apart from other studies, was lecturers' perceptions that their professional identity, collegiality, autonomy, and academic freedom were in crisis.

Prolonged inoculation of soya bean (Glycine max L.) farms with exotic strains of Bradyrhizobium species starting in the 1960s resulted in the establishment of populations of Bradyrhizobium strains in the soils of several soya bean farms in South Africa. With the increasing number of new soya bean genotypes in the country, it is challenging to determine which genotypes are highly compatible with a given rhizobium strain. In this study, we investigated the symbiotic compatibility of native rhizobial isolates and the strains from the South African Rhizobium Culture Collection (SARCC) on ten selected locally available soya bean genotypes. A glasshouse soil trap experiment using soil samples collected from Lothair, Bothaville, and Standerton was performed on five cultivars. The trapped rhizobial strains were further screened in the glasshouse to authenticate their nodulation compatibility with the different soya bean cultivars. The rhizobial strains showed significant nodulation compatibility with the selected cultivars. These strains were also tested for beneficial traits in vitro and characterized using DNA sequencing methods to elucidate their taxonomic identity. Some of the most nodulation-compatible strains characterized as Bradyrhizobium and Sinorhizobium species exhibited significant symbiotic performance in terms of plant biomass, nodule number, and nodule dry weight. The study generated valuable data that provide information on the extent of symbiotic compatibility of some of the existing cultivars used in South Africa with native rhizobia and whether inoculation of soya bean with commercial products is vital on some soya bean farms.

Previous phases of the Coupled Model Intercomparison Project (CMIP) have primarily focused on simulations driven by atmospheric concentrations of greenhouse gases (GHGs), for both idealized model experiments and climate projections of different emissions scenarios. We argue that although this approach was practical to allow parallel development of Earth system model simulations and detailed socioeconomic futures, carbon cycle uncertainty as represented by diverse, process-resolving Earth system models (ESMs) is not manifested in the scenario outcomes, thus omitting a dominant source of uncertainty in meeting the Paris Agreement. Mitigation policy is defined in terms of human activity (including emissions), with strategies varying in their timing of net-zero emissions, the balance of mitigation effort between short-lived and long-lived climate forcers, their reliance on land use strategy, and the extent and timing of carbon removals. To explore the response to these drivers, ESMs need to explicitly represent complete cycles of major GHGs, including natural processes and anthropogenic influences. Carbon removal and sequestration strategies, which rely on proposed human management of natural systems, are currently calculated in integrated assessment models (IAMs) during scenario development with only the net carbon emissions passed to the ESM. However, proper accounting of the coupled system impacts of and feedback on such interventions requires explicit process representation in ESMs to build self-consistent physical representations of their potential effectiveness and risks under climate change. We propose that CMIP7 efforts prioritize simulations driven by CO2 emissions from fossil fuel use and projected deployment of carbon dioxide removal technologies, as well as land use and management, using the process resolution allowed by state-of-the-art ESMs to resolve carbon–climate feedbacks. Post-CMIP7 ambitions should aim to incorporate modeling of non-CO2 GHGs (in particular, sources and sinks of methane and nitrous oxide) and process-based representation of carbon removal options. These developments will allow three primary benefits: (1) resources to be allocated to policy-relevant climate projections and better real-time information related to the detectability and verification of emissions reductions and their relationship to expected near-term climate impacts, (2) scenario modeling of the range of possible future climate states including Earth system processes and feedbacks that are increasingly well-represented in ESMs, and (3) optimal utilization of the strengths of ESMs in the wider context of climate modeling infrastructure (which includes simple climate models, machine learning approaches and kilometer-scale climate models).

We review how the international modelling community, encompassing integrated assessment models, global and regional Earth system and climate models, and impact models, has worked together over the past few decades to advance understanding of Earth system change and its impacts on society and the environment and thereby support international climate policy. We go on to recommend a number of priority research areas for the coming decade, a timescale that encompasses a number of newly starting international modelling activities, as well as the IPCC Seventh Assessment Report (AR7) and the second UNFCCC Global Stocktake. Progress in these priority areas will significantly advance our understanding of Earth system change and its impacts, increasing the quality and utility of science support to climate policy. We emphasize the need for continued improvement in our understanding of, and ability to simulate, the coupled Earth system and the impacts of Earth system change. There is an urgent need to investigate plausible pathways and emission scenarios that realize the Paris climate targets – for example, pathways that overshoot 1.5 or 2 °C global warming, before returning to these levels at some later date. Earth system models need to be capable of thoroughly assessing such warming overshoots – in particular, the efficacy of mitigation measures, such as negative CO2 emissions, in reducing atmospheric CO2 and driving global cooling. An improved assessment of the long-term consequences of stabilizing climate at 1.5 or 2 °C above pre-industrial temperatures is also required. We recommend Earth system models run overshoot scenarios in CO2-emission mode to more fully represent coupled climate–carbon-cycle feedbacks and, wherever possible, interactively simulate other key Earth system phenomena at risk of rapid change during overshoot. Regional downscaling and impact models should use forcing data from these simulations, so impact and regional climate projections cover a more complete range of potential responses to a warming overshoot. An accurate simulation of the observed, historical record remains a fundamental requirement of models, as does accurate simulation of key metrics, such as the effective climate sensitivity and the transient climate response to cumulative carbon emissions. For adaptation, a key demand is improved guidance on potential changes in climate extremes and the modes of variability these extremes develop within. Such improvements will most likely be realized through a combination of increased model resolution, improvement of key model parameterizations, and enhanced representation of important Earth system processes, combined with targeted use of new artificial intelligence (AI) and machine learning (ML) techniques. We propose a deeper collaboration across such efforts over the coming decade. With respect to sampling future uncertainty, increased collaboration between approaches that emphasize large model ensembles and those focussed on statistical emulation is required. We recommend an increased focus on high-impact–low-likelihood (HILL) outcomes – in particular, the risk and consequences of exceeding critical tipping points during a warming overshoot and the potential impacts arising from this. For a comprehensive assessment of the impacts of Earth system change, including impacts arising directly as a result of climate mitigation actions, it is important that spatially detailed, disaggregated information used to generate future scenarios in integrated assessment models be available for use in impact models. Conversely, there is a need to develop methods that enable potential societal responses to projected Earth system change to be incorporated into scenario development. The new models, simulations, data, and scientific advances proposed in this article will not be possible without long-term development and maintenance of a robust, globally connected infrastructure ecosystem. This system must be easily accessible and useable by modelling communities across the world, allowing the global research community to be fully engaged in developing and delivering new scientific knowledge to support international climate policy.

Orientation: Leadership styles have a significant influence on institutional performance. Transactional, transformational and agile leadership styles demonstrate positive organisational outcomes. Research purpose: This study examines how transactional, transformational, and agile leadership styles influence and predict institutional performance within South African higher education. By identifying the most effective leadership approach, the research offers recommendations to enhance leadership strategies in the sector. Motivation for the study: These leadership styles were selected because of their relevance in navigating the structural, innovative and adaptive needs of higher education institutions. Understanding their impact will help shape more effective leadership interventions. Research approach/design and method: A quantitative, correlational design was used. The Multifactor Leadership Questionnaire (MLQ), Agile Leadership Questionnaire and Institutional Performance Questionnaire were administered to a convenience sample of 224 staff across five public institutions in South Africa. Main findings: All three leadership styles positively and significantly influenced institutional performance. Transformational and agile leadership showed the strongest ability to explain the variance in performance, with transformational leadership explaining the most variance. Practical/managerial implications: Effective leadership is critical for performance in South African higher education. Leadership training should develop transformational and agile leadership behaviours. Contribution/value-add: The findings highlight the importance of leadership style for institutional performance and the need for tailored leadership developmental programmes in academia.

Forestation can contribute to climate change mitigation. However, increasing frequency and intensity of climate extremes are posed to have profound impact on forests and consequently on the mitigation potential of forestation efforts. In this perspective, we critically assess forestation-reliant climate mitigation scenarios from five different integrated assessment models (IAMs) by showcasing the spatially explicit exposure of forests to fire weather and the simulated increase in global annual burned area. We provide a detailed description of the feedback from climate change to forest carbon uptake in IAMs. Few IAMs are currently accounting for feedback mechanisms like loss from fire disturbance. Consequently, many forestation areas proposed by IAM scenarios will be exposed to fire-promoting weather conditions and without costly prevention measures might be object to frequent burning. We conclude that the actual climate mitigation portfolio in IAM scenarios is subject to substantial uncertainty and that the risk of overly optimistic estimates of negative emission potential of forestation should be avoided. As a way forward we propose how to integrate more detailed climate information when modeling climate mitigation pathways heavily relying on forestation.

Empathy is an important competence for communication professionals. This article investigates two aspects of empathy in an educational setting: the validity of self versus other assessments and the manifestation of empathy in communicative behaviors. Communication students were given a mediating role in discussions with two clients and their empathy was measured using self-ratings and client assessments. Videos of highest- and lowest-rated students were analyzed to identify empathy-related behaviors. No correlation was found between self-rated empathy and clients' assessments. Several verbal and nonverbal behaviors corresponded to empathy: body language, an other-orientation in asking questions, paraphrasing, and a solution orientation.

Global demand for fossil fuels is projected to decline by up to 75 percent by 2050, requiring new economic strategies for fossil exporters to promote diversification. This study employs an inter-country input-output model to assess sector interdependence in Saudi Arabia and explore the macroeconomic impacts of investing in Power-to-X (PtX) plants. We analyze four configurations: pure solar and hybrid solar-wind systems, producing either green hydrogen or ammonia. Our comparative analysis shows that hybrid plants appear to have stronger domestic effects than pure solar configurations, while producing green ammonia instead of hydrogen generates stronger relative employment. These trends remain consistent across different sensitivities and domestic supply shares. However, the differences between configurations and sensitivities decrease with increasing domestic supply. Currently Saudi Arabia has limited developed manufacturing sectors and the economy is heavily dependent on exports of crude oil and related products-a situation often referred to as the “resource curse”. For all PtX configurations, the construction sector therefore emerges as the largest contributor to domestic employment and value added. At current import shares, foreign effects, particularly in China and the United States, account for about half of the total impact, especially in sectors such as electronics and machinery. Without embedding the hydrogen supply chain into their industrial landscape by starting to produce parts of clean technologies locally, exporters risk substantial value creation occurring predominantly abroad. Overall, our research highlights the need for targeted policy measures to capitalize on the „renewables pull effect“ when installing PtX plants for green energy exports.

The effective training of law students, which demystifies technology, and the creation of cost effective, fit for purpose technology solutions are crucial to democratising legal technology and levelling the playing fields between "Big Law" and the legal services available to the bulk of South African citizens. A public/private partnership between the Nelson Mandela Faculty of Law, the university's Information and Communication Technology department and a consortium of legal practitioners (including Cliffe Dekker Hofmeyr and various industry players) has piloted HiveLaw, a SharePoint-based practice management solution custom designed to fit university law clinics' dual purpose of legal service delivery and practical legal education. This pilot serves as a case study firstly to investigate how legal technology can contribute to transformative teaching and learning and transformative legal practice at university law clinics, as it exposes staff and students to the benefits of digital and online activities. Secondly, the pilot illustrates how proficiency in the use of technology such as HiveLaw aids the staff and students to adapt to digital processes while improving access to justice for indigent communities. In this way staff and students make a difference in the working world by implementing their knowledge in legal practice, which is widely known for slowly adapting to digital processes, while being exposed to experiential learning and getting in touch with the demands of modern legal practice.

This article delves into the transition of Afrikaans from a hegemonic language to a minority language post-1994. Afrikaans was one of the two official South African languages in the 20th century. Afrikaans films enjoyed privileges because the government manipulated racial and cultural identities through subsidies and audience segregation. However, in the post-apartheid era, Afrikaans filmmakers had to find new funding models, such as relying on the Afrikaans satellite channel, kykNET, to commission content for cinema distribution. The article briefly discusses the symbiosis between the Afrikaans language and its film industry and how Afrikaans film remains sustainable despite not being one of South Africa’s most spoken languages.

By offering clients attractive credit terms on sales, a company may increase its turnover, but granting credit also incurs the cost of money tied up in accounts receivable (AR), increased administration and a heightened probability of incurring bad debt. The management of credit sales, although eminently important to any business, is often performed manually, which may be time-consuming, expensive and inaccurate. Such an administrative workload becomes increasingly cumbersome as the number of credit sales increases. As a result, a new approach towards proactively identifying invoices from AR accounts that are likely to be paid late, or not at all, has recently been proposed in the literature, with the aim of employing intervention strategies more effectively. Several computational techniques from the credit scoring literature and particularly techniques from the realms of survival analysis or machine learning have been embedded in the aforementioned approach. This body of work is, however, lacking due to the limited guidance provided during the data preparation phase of the model development process and because survival analytic and machine learning techniques have not yet been ensembled. In this paper, we propose a generic framework for modelling invoice payment predictions with the aim of facilitating the process of preparing transaction data for analysis, generating relevant features from past customer behaviours, and selecting and ensembling suitable models for predicting the time to payment associated with invoices. We also introduce a new sequential ensembling approach, called the Survival Boost algorithm. The rationale behind this method is that features generated by a survival analytic model can enhance the efficacy of a machine learning classification algorithm.

Marizé Cuyler,1 Danielle Twilley,1 Velaphi C Thipe,2 Vusani Mandiwana,3 Michel L Kalombo,3 Suprakas S Ray,4 Rirhandzu Shamaine Rikhotso-Mbungela,4 Arno Janse van Vuuren,5 Will Coetsee,6 Kattesh V Katti,2,&ast; Namrita Lall1,7– 9,&ast; 1Department of Plant and Soil Sciences, University of Pretoria, Pretoria, Gauteng, 0002, South Africa; 2Department of Radiology, Institute of Green Nanotechnology, University of Missouri, Columbia, MO, 65212, USA; 3Chemical Cluster Centre for Nanostructures and Advanced Materials, Council for Scientific and Industrial Research, Pretoria, 0001, South Africa; 4DST/CSIR National Centre for Nanostructured Materials, Council for Scientific and Industrial Research, Pretoria, 0001, South Africa; 5Centre for High Transmission Electron Microscopy, Nelson Mandela University, Port Elizabeth, 6031, South Africa; 6Botanica Natural Products Pty (Ltd), Canterbury Farm MR 254, Alldays, Limpopo, 0909, South Africa; 7School of Natural Resources, University of Missouri, Columbia, MO, 65211, USA; 8College of Pharmacy, JSS Academy of Higher Education and Research, Mysuru, Karnataka, 570015, India; 9Bio-Tech Research and Development Institute, University of the West Indies 770, Kingston, Jamaica&ast;These authors contributed equally to this workCorrespondence: Kattesh V Katti, Department of Radiology, Institute of Green Nanotechnology, University of Missouri, Columbia, MO 65212, USA, Tel +1 (573) 882-5656, Fax +1 (573) 884-5679, Email kattik@health.missouri.edu Namrita Lall, Department of Plant and Soil Sciences, University of Pretoria, Pretoria, Gauteng, South Africa, Tel/Fax +27 (012) 420 2524, Email namrita.lall@up.ac.zaBackground: Atopic dermatitis (eczema) is an inflammatory skin condition with synthetic treatments that induce adverse effects and are ineffective. One of the proposed causes for the development of the condition is the outside-in hypothesis, which states that eczema is caused by a disruption in the skin barrier. These disruptions include developing dry cracked skin, which promotes the production of histamine. Bulbine frutescens (BF) is traditionally used to treat wounds and eczema; however, limited research has been conducted to scientifically validate this. Furthermore, gold nanoparticles (AuNPs) have been used to repair damaged skin; however, no research has been conducted on AuNPs synthesized using BF.Purpose: The study aimed to determine whether BF alleviated skin damage through wound healing, reducing the production of histamine and investigate whether AuNPs synthesized using BF would enhance biological activity.Methods: Four extracts and four synthesized AuNPs were prepared using BF and their antiproliferative and wound healing properties against human keratinocyte cells (HaCaT) were evaluated. Thereafter, the selected samples antiproliferative activity and antihistamine activity against phorbol 12-myristate 13-acetate (PMA) stimulated granulocytes were evaluated.Results: Of the eight samples, the freeze-dried leaf juice (BFE; p < 0.01) extract and its AuNPs (BFEAuNPs; p < 0.05) displayed significant wound closure at 100 μg/mL and were further evaluated. The selected samples displayed a fifty percent inhibitory concentration (IC50) of > 200 μg/mL against PMA stimulated granulocytes. Compared to the untreated (media with PMA) control (0.30 ± 0.02 ng/mL), BFEAuNPs significantly inhibited histamine production at a concentration of 100 (p < 0.01) and 50 μg/mL (p < 0.001).Conclusion: BFE and BFEAuNPs stimulated wound closure, while BFEAuNPs significantly inhibited histamine production. Further investigation into BFEAuNPs in vivo wound healing activity and whether it can target histamine-associated receptors on mast cells as a potential mechanism of action should be considered. Keywords: atopic dermatitis, histamine production, outside-in hypothesis, scratch assay