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    The effect of a post‑anaesthesia high‑care unit (PAHCU) admission on mobilization, length of stay and in‑hospital mortality post‑surgery in low energy neck of femur fracture patients
    (Springer Link, 2024-01-09) Essa, S.; Venter, S.; Jordaan, J. D.
    Purpose/aim: With an ageing population and an increase in fragility fractures of the hip (FFH), the role of an anaesthetist is evolving to include more peri-operative care. A post-anaesthesia high-care unit (PAHCU) should enhance care in postoperative patients. To our knowledge, there are no studies that have investigated the effect of a PAHCU admission on postoperative outcomes after FFH. This study aimed to compare post-operative outcomes of FFH patients admitted to PAHCU versus a standard post-operative orthopaedic ward (POOW). Methodology: A retrospective cohort study was conducted on adult patients with FFH who underwent surgery between January 2019 and December 2020 at our institution. Data were sourced from electronic medical records. SPSS version 28 was used to analyse data. Results: A total of 231 patients were included. The PAHCU group (n = 35) displayed a higher burden of chronic illness and higher peri-operative risk scores as compared to the POOW group (n = 196). Median time to mobilize (TTM) in PAHCU was 84 h vs. 45 h in POOW group (p = 0.013). Median length of stay (LOS) in PAHCU was 133 h vs. 94 h in POOW (p = 0.001). The in-hospital mortality was 2.9% (n = 1) for PAHCU and 3.6% (n = 7) for POOW (p = 1). The 30-day mortality was 11.8% (n = 4) for PAHCU and 10.1% (n = 19) in POOW. Conclusion: PAHCU admission resulted in delayed time to surgery and TTM, together with prolonged LOS, compared to those managed in POOW. However, these mortality rates remained comparable in both groups. This study contributes valuable insights into post-operative care of FFH patients in a resource-poor setting.
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    Bovine tuberculosis in African buffalo (Syncerus caffer): Progression of pathology during infection
    (PLOS, 2022-11-11) Lakin, Hilary Ann; Tavalire, Hannah; Sakamoto, Kaori; Buss, Peter; Miller, Michele; Budischak, Sarah A.; Raum, Kristina; Ezenwa, Vanessa O.; Beechler, Brianna; Jolles, Anna
    Background Bovine tuberculosis (BTB) is a zoonotic disease of global importance endemic in African buffalo (Syncerus caffer) in sub-Saharan Africa. Zoonotic tuberculosis is a disease of global importance, accounting for over 12,000 deaths annually. Cattle affected with BTB have been proposed as a model for the study of human tuberculosis, more closely resembling the localization and progression of lesions in controlled studies than murine models. If disease in African buffalo progresses similarly to experimentally infected cattle, they may serve as a model, both for human tuberculosis and cattle BTB, in a natural environment. Methodology/Principal findings We utilized a herd of African buffalo that were captured, fitted with radio collars, and tested for BTB twice annually during a 4-year-cohort study. At the end of the project, BTB positive buffalo were culled, and necropsies performed. Here we describe the pathologic progression of BTB over time in African buffalo, utilizing gross and histological methods. We found that BTB in buffalo follows a pattern of infection like that seen in experimental studies of cattle. BTB localizes to the lymph nodes of the respiratory tract first, beginning with the retropharyngeal and tracheobronchial lymph nodes, gradually increasing in lymph nodes affected over time. At 36 months, rate of spread to additional lymph nodes sharply increases. The lung lesions follow a similar pattern, progressing slowly, then accelerating their progression at 36 months post infection. Lastly, a genetic marker that correlated to risk of M. bovis infection in previous studies was marginally associated with BTB progression. Buffalo with at least one risk allele at this locus tended to progress faster, with more lung necrosis. Conclusions/Significance The progression of disease in the African buffalo mirrors the progression found in experimental cattle models, offering insight into BTB and the interaction with its host in the context of naturally varying environments, host, and pathogen populations.
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    Flood frequency analysis – Part 2: Development of a modified plotting position
    (South African Water Research Commission., 2022-04-27) Van der Spuy D; Du Plessis JA
    The original plotting position concept was suggested more than a century ago. Since then, many alternative plotting position approaches have been developed. Despite a general lack of agreement around which plotting position is theoretically ‘correct’ and the ‘best’ to use, all plotting positions fail to adequately address outliers and data of similar magnitude. Hydrologists generally fail to acknowledge that the plotting position primarily offers an informative display of data, against which distributions can be compared, rather than an absolute measure of probability. This paper does not intend to challenge any of the many lengthy theoretical mathematical arguments, utilised to ‘prove’ why one plotting position is superior to the others. These theoretical arguments may very well be valid for a ‘population’ of flood peaks – the reality, however, is that hydrologists are confronted with the challenge of analysing very limited ‘samples’ of the population. Consequently, the plotting position issue demands a more pragmatic approach, rather than a purely theoretical approach. This paper illustrates various problems with existing plotting position techniques in use and offers an alternative approach and a more sensible plotting position technique, using Z-scores and referred to as the Z-set PP, against which distributions can be checked. The study further illustrates how effectively the Z‑set PP deals with outliers and its robustness with various record lengths. Although derived from a study of flood peak data obtained from South African flow-gauging sites, it is deemed that it will be universally applicable.
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    Deep Learning-Enabled Temperature Simulation of a Greenhouse Tunnel
    (IWACP, 2023) Jogunola, O.; Hull. K.J.; Mabitsela, M. M.; Phiri, E.E; Adebisi, B.; Booysen, MJ
    Agriculture is poised to suffer greatly from the effects of climate change. Prediction models, using deep learning, have been developed that can simulate and predict conditions in open field farming to combat the climate variability from climate change. However, deep learning used in precision agriculture, specifically greenhouse tunnels, is under-researched despite also being affected by this variability. Utilising tunnel data collected over 42 days, two hybrid deep learning models were designed. Specifically, a hybrid of convolutional neural network (CNN) and Long Short-Term Memory (LSTM), and a hybrid of CNN and Bidirectional LSTM (BLSTM). The models are designed to forecast the internal temperature of the tunnel to support its management. The cooling wet wall state, solar irradiance, inside and outside temperature of the tunnel are input variables to the developed deep-learning models. Two scenarios are discussed with the results, the first scenario includes all the external variables as input, while the second scenario only considers the internal temperature as input. Results show a performance improvement of 48% and 14% computation time for the CNN-LSTM compared to the CNN-BLSTM model for the two scenarios, respectively. In terms of the measured loss metrics, both models had varied performance and model fitness, with an average mean square error of 0.025 across the models and scenarios.
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    Towards a Cleaner Production of an Underutilised Legume, Bambara Groundnut
    (IWACP, 2023) Mabitsela, M. MA; Hull, K.JA; Mavengahama, SB.; Phiri, E.E.; Booysen, M.J
    Soilless cultivation systems such as aeroponics provide a more efficient, and clean food production of in areas where there is limited access to arable land for agricultural practices and drought-prone countries. The objective of this study was to evaluate the yield performance of seventy Bambara groundnut (BGN) landraces cultivated in aeroponics and compared with a traditional drip-irrigated hydroponic system with sawdust as a growing medium. The result showed that BGN landraces cultivated in aeroponics accumulated a high number of seeds, as compared to those landraces cultivated in hydroponics. However, BGN landraces cultivated in hydroponics recorded a high shoot dry weight and one hundred seed weight. The root length that could only be measured in BGN landraces cultivated in the aeroponics systems, showed that BGN root length can extend beyond one meter. Soilless cultivation systems with their high-water use efficiency have the potential of reducing production costs, thus making them accessible to farmers in countries where drought is a reality.