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Stress to stability: sense of coherence as a buffer against pandemic-related psychological distress
No full textBackground: Identifying protective factors in mental health-related outcomes is crucial, offering insights into the vulnerabilities and strengths individuals harness against psychological distress. There has been limited focus on exploring complex mediation and moderation models, which can uncover the relationships between stressors, protective factors and wellbeing. Aim: This study investigated the interrelationship between perceived stress, sense of coherence (SOC), and psychological distress. Setting: South African university students (N = 322) completed the Perceived Stress Scale, Sense of Coherence Scale-13, Beck Hopelessness Scale-9 and Center for Epidemiological Studies Depression Scale-10. Methods: Moderation analysis was conducted using the PROCESS macro to examine the role of SOC in moderating the relationship between perceived stress and psychological distress. Where moderation was not significant, mediation analysis was conducted. Results: Sense of coherence demonstrated multiple roles in mental health, exhibiting direct effects on indicators of psychological distress. Sense of coherence moderated the relationship between perceived stress and hopelessness. Under heightened stress conditions, individuals with low to medium SOC displayed more profound feelings of hopelessness compared to those with high SOC. Mediation analysis showed that SOC served as a bridge between perceived stress and both depression and anxiety. The identification of a potential SOC threshold offers a novel perspective on assessing risk levels, suggesting that individuals with low to moderate SOC are particularly vulnerable under high stress
Probabilistic cosmological inference on HI tomographic data
No full textWe explore the possibility of retrieving cosmological information along with its inherent uncertainty from 21-cm tomographic data at intermediate redshift. The first step in our approach consists of training an encoder, composed of several three dimensional convolutional layers, to cast the neutral hydrogen 3D data into a lower dimension latent space. Once pre-trained, the featurizer is able to generate 3D grid representations which, in turn, will be mapped onto cosmology (Ωm, σ8) via likelihood-free inference. For the latter, which is framed as a density estimation problem, we consider a Bayesian approximation method which exploits the capacity of Masked Autoregressive Flow to estimate the posterior. It is found that the representations learned by the deep encoder are separable in latent space. Results show that the neural density estimator, trained on the latent codes, is able to constrain cosmology with a precision of R2≥0.91 on all parameters and that most of the ground truth of the instances in the test set fall within 1σ uncertainty. It is established that the posterior uncertainty from the density estimator is reasonably calibrated. We also investigate the robustness of the feature extractor by using it to compress out-of-distribution dataset, that is either from a different simulation or from the same simulation but at different redshift. We find that, while trained on the latent codes corresponding to different types of out-of-distribution dataset, the probabilistic model is still reasonably capable of constraining cosmology, with R2≥0.80 in general. This highlights both the predictive power of the density estimator considered in this work and the meaningfulness of the latent codes retrieved by the encoder. We believe that the approach prescribed in this proof of concept will be of great use when analyzing 21-cm data from various surveys in the near future
A taxonomic revision of the twelve-scaled species of struthiola (thymelaeaceae: thymelaeoideae): the struthiolamundiig roup
No full textStruthiola L. (Thymelaeaceae: Thymelaeoideae) is a genus of approximately 40 species (Wright, 1915; manning and goldblatt, 2012) largely endemic to South Africa, but with four species in tropical Africa (Peterson, 1958, 1978, 2006). the Greater Cape Floristic Region (GCFR) is the centre of diversity for the genus, as well as for several other related southern African Thymelaeoideae, including Gnidial., Lachnaea l. and Passerina l. Almost all of the South African species of Struthiola are restricted to the GCFR (manning and goldblatt, 2012; Snijman, 2013), with only three of the South African species occurring beyond the region in the grasslands of KwaZulu-Natal (Wright, 1915; hilliard and burtt, 1986; Hilliard, 1993).
Struthiola l. was established by Linnaeus (1767) in his Systema Naturae ed. 12 for two species of Thymelaeaceae that were characterised by flowers with just four anthers and petaloid scales (incorrectly described as nectary glands) and subsequently conserved against the earlier name Belvala Adans. (1763) with the conserved type S. erecta l. The genus was last revised more than a century ago by Wright (1915), and as the taxonomy of the southern African species remains poorly understood it has been identified as one of the priority groups for taxonomic revision (Victor et al., 2015; Victor, 2020). Meisner (1857), in his global treatment of Thymelaeaceae, subdivided the genus into three morphological groups based on the number of petaloid scales in the mouth of the hypanthium, viz. four, eight or 12. All subsequent authors have retained these informal subdivisions.
The molecular analyses by Makhoba (2024) recovered the species with four scales (the Struthiola striata group) and those with 12 scales (the Struthiola mundii group) as two independent clades nested within the remaining species of the genus, all with eight scales. This confirms the value of the putatively derived scale-numbers of four and 12 in identifying relationships in the genus. The four-scaled S. striata group was recently revised (Makhoba et al., 2019) as a first step towards a comprehensive revision of the genus. As the next step we present a revision of the twelve-scaled species comprising the S. mundii group.
Twelve species and three varieties were recognized in the S. mundii group at the onset of this study. Characters such as habit, flower colour, presence or absence of hairs on the hypanthium, hypanthium length, shape of the petaloid scales and the colour of the associated hairs, bracteole length, and presence or absenc
Are first-year students linguistically ready for further studies: a needs analysis of english for academic purposes students at King Saud University
No full textThis study aimed to investigate the English for academic purposes (EAP) needs of the Common First Year (CFY), particularly first-year Engineering students at King Saud University (KSU), Riyadh, Kingdom of Saudi Arabia (KSA). Additionally, the study intended to examine whether intermediate or B-level students studying the Q: Skills for Success coursebook were linguistically or academically ready to continue their studies successfully at the university's Engineering College. The objectives of the study were to (i) assess the present EAP needs of prospective Engineering students in the CFY; (ii) analyse the target EAP needs of students and the demands of the field of study they have entered, i.e. the Engineering College of KSU; and (iii) evaluate the current EAP programme delivered by the English Language Skills Department (ELSD) at the CFY. The main research question was: Did the EAP programme for the CFY level students at KSU adequately prepare them for further studies in the field of Engineering – if not, why not? Three sub-questions guided the research. These were: (i) What were the key features of the academic needs of Engineering students at the CFY? (ii) What were the main traits of the target academic needs of second-year students at the College of Engineering (COE)? (iii) What should the EAP programme at the CFY ideally resemble and constitute to maximise its impact? The study’s theoretical framework was based on needs analysis. It used two of the four prominent needs analysis approaches: present situation needs analysis (PSA) and target situation needs analysis (TSA) (Basturkmen, 2010). The qualitative study employed a phenomenological research design, enabling the researcher to explore and identify problems, barriers, and potential solutions for improvement (Jeremic, 2019)
Solar variability in the mg ii h and k lines
No full textSolar irradiance and its variations in the ultraviolet (UV) control the photochemistry in Earth's atmosphere and influence Earth's climate. The variability in the Mg ii h and k core-to-wing ratio, also known as the Mg ii index, is highly correlated with the solar UV irradiance variability. Because of this, the Mg ii index is routinely used as a proxy for solar UV irradiance variability, which can help to get insights into the influence of solar UV irradiance variability on Earth's climate. Measurements of the Mg ii index, however, have only been carried out since 1978 and do not cover climate-relevant timescales longer than a few decades. Here we present a model to calculate the Mg ii index and its variability based on the well-established Spectral And Total Irradiance REconstruction (SATIRE) model. We demonstrate that our model calculations yield an excellent agreement with the observed Mg ii index variations, both on the solar activity cycle and on the solar rotation timescales. Using this model, we synthesize the Mg ii index time series on climate-relevant timescales of decades and longer. Here we present the time series of the Mg ii index spanning nearly three centuries
Sargassum incisifolium and Ulva spp metabolites activity and their molecular dynamics simulation against Fusarium oxysporum 14-alpha-demethylase
No full textFusarium oxysporum, a major agricultural pathogen, poses severe risks to crops worldwide. With increasing resistance to conventional antifungal agents, there is an urgent need for alternative treatments. Seaweeds such as Ulva spp. and Sargassum incisifolium are promising sources of bioactive compounds that may offer novel antifungal properties. This study investigates the antifungal activity of acetone extracts from Ulva spp. and Sargassum incisifolium against F. oxysporum, with the goal of identifying specific bioactive compounds responsible for this activity and evaluating their effectiveness quantitatively. We prepared acetone extracts from both seaweed species and assessed their antifungal activity using a series of in vitro assays. The total phenolic content (TPC) and antioxidant capacity were determined for each extract. LC-qTOF-MS/MS was employed for phytochemical profiling, while molecular docking and molecular dynamics simulations were used to predict interactions between identified compounds and the 14-alpha-demethylase enzyme of F. oxysporum. The TPC was 2.72±0.009 and 2.23±0.009 GAE/mg dry weight for Ulva spp and S. incisifolium. Additionally, significant antioxidant activity was observed, with IC50 values of 8.38±0.06 µg/mL for Ulva spp and 8.01±0.07 µg/mL for S. incisifolium, which are comparable to ascorbic acid (5.23±0.04 µg/mL). Phytochemical analysis revealed high levels of terpenoids, phenolics, and fatty acids. In molecular docking, compounds such as medicocarpin, corynanthine, and merulinic acid demonstrated strong binding affinities (binding energies ≤ -7.5 kcal/mol). Molecular dynamics simulations confirmed stable interactions over 100 ns, with medicocarpin exhibiting the most stable binding profile. The study demonstrates that acetone extracts of Ulva spp. and S. incisifolium possess significant antifungal activity against F. oxysporum. Medicocarpin, in particular, emerged as a promising candidate for further development as an antifungal agent. These findings underscore the potential of seaweed-derived compounds as antifungal agents against fungal pathogens and highlight the need for further investigation into their practical applications in plant disease management. Specifically, Medicocarpin emerged as a promising in silico candidate, warranting further experimental validation
Influencing return to work among women with acquired brain injury
No full textPurpose: Research indicates that women with brain injury have a higher risk of not resuming their work roles. This study investigates the influence of sociodemographic, impairment‐related and environmental factors on the return‐to‐work outcomes of women with acquired brain injury in Cape Metropolitan, South Africa. Methods: A cross‐sectional survey was conducted among 139 women aged 18–65 with acquired brain injury in Cape Metropolitan, South Africa. Participants were conveniently sampled, and the Work Rehabilitation Questionnaire was used for data collection. Data were analysed using IBM SPSS Statistics Version 26, focusing on sociodemographic, impairment‐related and environmental factors influencing return to work outcomes. Results: Women with acquired brain injury who participated in this study yielded a postinjury return to work rate of 61.2%. Older women were less likely to return to work (odds ratio: 0.905). Environmental support, particularly from workplace supervisors or managers, significantly enhanced RTW (odds ratio: 5.660). Marital status, impairment‐related restrictions, type of vocational intervention and family support were not significant predictors of return to work. Conclusion: These results highlight the necessity for multidimensional and integrative RTW programmes that address both personal and systemic barriers. Such programmes are essential to promoting sustained economic participation and improving the quality of life for women with ABI
Function‐oriented electrolyte additives: chemical strategy to enhance the performance of lithium‐sulfur batteries
No full textLithium‐sulfur (Li‐S) batteries have emerged as a promising candidate for next‐generation energy storage systems. However, the practical application of Li‐S batteries faces several significant technical challenges, such as the “shuttle effect,” sluggish polysulfide conversion kinetics, irreversible loss of active materials, and disordered growth of lithium dendrites on the anode. To overcome these issues, the strategic incorporation of functional electrolyte additives has emerged as a novel approach for enhancing Li‐S battery performance. This paper focuses on reviewing functional electrolyte additives with different properties and their action mechanisms. First, based on the structure and composition of additive molecules, they are classified into inorganic molecules, organic molecules, ionic liquids, and polymer‐based additives. Then, the effects of additives on sulfur cathodes are deeply expounded from aspects such as sulfur fixation, construction of interfacial CEI layers, alteration of sulfur redox pathways, and realization of 3D deposition of Li₂S. Furthermore, the construction of SEI layers on lithium metal anodes, lithium ion migration, and inhibition of lithium dendrites by additives are summarized and compared. Finally, the future development of electrolyte additives for Li‐S batteries is projected, offering theoretical insights and technological strategies for the development of a highly stable Li‐S battery
Assessing the spatial variability of neglected and underutilized crop species (NUS) leaf and canopy chlorophyll content in KwaZulu-Natal smallholder farms using unmanned aerial Vehicle (UAV)-based high-throughput phenotyping
No full textAssessing the variability of crop chlorophyll content as an indicator of productivity is essential for optimising the production of Neglected and Underutilized crop Species (NUS) crops like as sweet potato and taro as well as establishing them among mainstream food crops. These NUS present a viable solution to address food and nutritional deficiencies in marginalised communities. Recent advancements in precision agriculture, particularly the use of drones outfitted with high-resolution sensors, have been demonstrated to offer near real-time, spatially explicit data that are invaluable for accurately monitoring and assessing crop growth dynamics at both farm and plot scales. The combined use of UAV-borne remote sensing techniques offers a platform for comprehensively understanding NUS crop productivity characteristics, which can guide operational decisions related to crop health, enabling timely remedial actions and optimising productivity. Hence, the purpose of this research was to assess the usefulness of data obtained from drones and remotely sensed data in mapping the leaf and canopy chlorophyll content of taro and sweet potato crops as a proxy for productivity. The first objective systematically reviewed existing literature on the use of earth observation data in characterising NUS productivity elements on smallholder croplands. The second objectivesought to predict the leaf chlorophyll content (LCC) of taro and sweet potato crops using UAV- derived data while comparatively assessing the accuracy of Random Forest (RF), Linear Regression, and Neural Network regressions in estimating chlorophyll across these NUS crops. The third objective sought to estimate the canopy chlorophyll content (CCC) of taro and sweet potato crops using UAV remotely sensed data. It also compared the prediction accuracies of LCC and CCC of the NUS based on RF. The findings of the review showed that very few published studies have focused on estimating and assessing both foliar and canopy chlorophyll content variability as an indicator of plant growth in NUS, particularly within smallholder contexts. Relative to the second objective, the findings revealed that the best machine algorithm for predicting the Leaf Chlorophyll Content (LCC) is the RF regression ensemble. Specifically, LCC prediction for sweet potato in the late vegetative growth phase showed limited accuracy, with an R2 of 0.23, a RMSE of 13.6 μmol m-2 and a RRMSE of11% based on SR1, CIRE ,The https://uwcscholar.uwc.ac.za/homeII chlorophyll content of the sweet potato crop was noted to be relatively higher than that of taro throughout the phenotyping stages. Using the RF algorithm, results showed that CCC can be accurately predicted during the mid-vegetative growth stage for both sweet potato and taro. For sweet potato, the prediction achieved an RMSE of 9.2% and R2 = 0.91 μmol m-2 with the most important variables being Cirededge, RED, NDV Irededge, Rededge, CIRE, and CI green. For taro the prediction yielded an RMSE of 14.5% and R2 = 0.96 μmol m-2 with CIrededge, GREEN, NIR, CIRE, and RGR as the most effective variables, ranked by significance. Additionally, the CCC estimation accuracies were significantly higher that the LCC estimation. This suggested that the CCC of NUS may be optimally estimated when compared to the LCC of sweet potato and taro throughout the development period. Overall, the results of this research imply that sweet potato and taro chlorophyll content can be optimally estimated using RF regression ensemble and UAV spectral variables across the growing season. This emphasizes how urgently UAV technology is needed to enhance the assessment of chlorophyll content and ultimately crop monitoring, offering insightful data for sustainable farming methods in food-insecure regions
Perceived healthfulness, nutrient content awareness, consumption, and intention to purchase selected ultraprocessed products among adults in South Africa
No full textObjective: To investigate the perceived healthfulness, nutrient content awareness, consumption, and intention to purchase selected ultraprocessed products (UPP) and their sociodemographic determinants. Design: Cross-sectional study involving secondary data analysis. Setting: This study was conducted in all nine provinces of South Africa. Participants: In total, 1951 adults (18–50 years), with 63.5% females and 66.3% from low socioeconomic group. Methods: Participants were shown A4 images of mock-branded UPP, with no nutrition information provided. Questions asked were based on the images to determine the nutrient content awareness, healthfulness perception, consumption frequency, and intention to purchase the UPP based on sociodemographic characteristics. Analysis: Descriptive statistics were conducted for nutrient content awareness, perceived healthfulness, consumption, and intention to purchase UPP. Associations with sociodemographic variables were determined using regression analyses: logistic regression for perceived healthfulness and nutrient content awareness, ordinary least square regression for UPP consumption, and intention to purchase was modeled as a latent variable in a multiple indicators multiple cause (MIMIC) model. Results: Over a third of participants (41.8%) were not aware that fruit juice is high in sugar. Only 13% of the participants perceived fruit juice as unhealthy and more than 50% showed the intention to purchase fruit juice, cereals, and yoghurt in the future. More than 50% reported consuming most UPP either daily or weekly. Perceived healthfulness was associated with gender, while UPP consumption was associated with education, age, gender, and being unemployed. Intention to purchase UPP was the only variable associated with socioeconomic status. Conclusion and Implications: Intervention strategies such as simplified front-of-pack labeling may have a role in improving nutrition awareness and discouraging UPP consumption