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Abstract This research offers a novel methodology for quantifying water needs by assessing weather variables, applying a combination of data preprocessing approaches, and an artificial neural network (ANN) that integrates using a genetic algorithm enabled particle swarm optimisation (PSOGA) algorithm. The PSOGA performance was compared with different hybrid-based metaheuristic algorithms’ behaviour, modified PSO, and PSO as benchmarking techniques. Based on the findings, it is possible to enhance the standard of initial data and select optimal predictions that drive urban water demand through effective data processing. Each model performed adequately in simulating the fundamental dynamics of monthly urban water demand as it relates to meteorological variables, proving that they were all successful. Statistical fitness measures showed that PSOGA-ANN outperformed competing algorithms.

The shift, towards cars (EVs) plays a role in the global effort to combat climate change by reducing dependence on fossil fuels. An important part of this shift involves creating user EV charging systems. This study looks into how a connected coil design in a wireless power transfer system can help overcome challenges in EV charging when dealing with varying loads. We examine how well the system performs under load resistances that mimic states of charge and battery capacities in EVs. By assessing the stability of output voltage and efficiency of power transfer across these loads we focus on maintaining resonance within the system. Our findings show that the LCCL to LC WPT system maintains efficiency in power transfer (50-94) % when Coupling Coefficient change (0-0.9) at load resistance 3ꭥ and stable output voltage when facing changes in load resistance (1-4.5)ꭥ. This suggests that the system is resilient against load variations, which's crucial for real world EV charging situations. This research supports the potential of WPT systems as an efficient solution to meet the evolving demands of EV infrastructure leading towards increased adoption of EVs and a sustainable future, for transportation.

The need to develop the concrete industry has increased with the increase in environmental damage resulting from building and construction operations. In the present research, the Numerical study of shear behavior of geopolymer concrete beams without stirrups by using the ANSYS program. It also includes concrete modelling to study the behavior of geopolymer concrete (GPC). The longitudinal reinforcements of beams (without stirrups) were "basalt fiber reinforced polymer bars". In order to enhance the shear behavior of the specimens, various types of fibers were added to geopolymer concrete (GPC): "steel fibers (SF), synthetic polypropylene fibers (PF), polyvinyl alcohol fibers (PVF), and carbon fibers (CF)". A numerical analysis was performed by the ANSYS version 15 program to study many parameters affecting the shear behavior of geopolymer concrete, such as longitudinal reinforcements,, and the inclusion of the opening. The results indicated that using steel fibers (SF) in geopolymer concrete increased the load failure of the tested specimens. On the other hand, using carbon fibers (CF) in the geopolymer concrete enhanced the ductility factor of these beams. The load capacity of the geopolymer concrete specimen is enhanced with longitudinal reinforcement by the CFRP bar compared to those reinforcements by BFRP bars. While the use of GFRP bars was less efficient than BFRP bars. Using FRP bars, and steel bars in strengthening geopolymer concrete beams with openings enhanced the failure load of these specimens.

Abstract Background Malaria remains a major global health problem although there was a remarkable achievement between 2000 and 2015. Malaria drug resistance, along with several other factors, presents a significant challenge to malaria control and elimination efforts. Numerous countries in sub-Saharan Africa have documented the presence of confirmed or potential markers of partial resistance against artemisinin, the drug of choice for the treatment of uncomplicated Plasmodium falciparum malaria. The World Health Organization (WHO) recommends regular surveillance of artemisinin therapeutic efficacy to inform policy decisions. Methods This study aimed to evaluate the therapeutic efficacy of artemether-lumefantrine (AL), which is the first-line treatment for uncomplicated P. falciparum malaria in Ethiopia since 2004. Using a single-arm prospective evaluation design, the study assessed the clinical and parasitological responses of patients with uncomplicated P. falciparum malaria in Metehara Health Centre, central-east Ethiopia. Out of 2332 malaria suspects (1187 males, 1145 females) screened, 80 (50 males, 30 females) were enrolled, followed up for 28 days, and 73 (44 males, 29 females) completed the follow up. The study was conducted and data was analysed by employing the per-protocol and Kaplan–Meier analyses following the WHO Malaria Therapeutic Efficacy Evaluation Guidelines 2009. Results The results indicated rapid parasite clearance and resolution of clinical symptoms, with all patients achieving complete recovery from asexual parasitaemia and fever by day (D) 3. The prevalence of gametocytes decreased from 6.3% on D0 to 2.5% on D2, D3, D7, and ultimately achieving complete clearance afterward. Conclusion The overall cure rate for AL treatment was 100%, demonstrating its high efficacy in effectively eliminating malaria parasites in patients. No serious adverse events related to AL treatment were reported during the study, suggesting its safety and tolerability among the participants. These findings confirm that AL remains a highly efficacious treatment for uncomplicated P. falciparum malaria in the study site after 20 years of its introduction in Ethiopia.

Abstract Background Plasmodium vivax malaria is a leading cause of morbidity in Ethiopia. The first-line treatment for P. vivax is chloroquine (CQ) and primaquine (PQ), but there have been local reports of CQ resistance. A clinical study was conducted to determine the efficacy of CQ for the treatment of P. vivax malaria in southern Ethiopia. Methods In 2021, patients with P. vivax mono-infection and uncomplicated malaria were enrolled and treated with 25 mg/kg CQ for 3 consecutive days. Patients were followed for 28 days according to WHO guidelines. The data were analysed using per-protocol (PP) and Kaplan‒Meier (K‒M) analyses to estimate the risk of recurrent P. vivax parasitaemia on day 28. Results A total of 88 patients were enrolled, 78 (88.6%) of whom completed the 28 days of follow-up. Overall, 76 (97.4%) patients had adequate clinical and parasitological responses, and two patients had late parasitological failures. The initial therapeutic response was rapid, with 100% clearance of asexual parasitaemia within 48 h. Conclusion Despite previous reports of declining chloroquine efficacy against P. vivax, CQ retains high therapeutic efficacy in southern Ethiopia, supporting the current national treatment guidelines. Ongoing clinical monitoring of CQ efficacy supported by advanced molecular methods is warranted to inform national surveillance and ensure optimal treatment guidelines.

Abstract Changes in protein turnover play an important role in dynamic physiological processes, including skeletal muscle regeneration, which occurs as an essential part of tissue repair after injury. The inability of muscle tissue to recapitulate this regenerative process can lead to the manifestation of clinical symptoms in various musculoskeletal diseases, including muscular dystrophies and pathological atrophy. Here, we employed a workflow that couples deuterated water (2H2O) administration with mass spectrometry (MS) to systematically measure in-vivo protein turnover rates across the muscle proteome in 8-week-old male C57BL6/J mice. We compared the turnover kinetics of over 100 proteins in response to cardiotoxin (CTX) induced muscle damage and regeneration at unique sequential stages along the regeneration timeline. This analysis is compared to gene expression data from mRNA-sequencing (mRNA-seq) from the same tissue. The data reveals quantitative protein flux signatures in response to necrotic damage, in addition to sequential differences in cell proliferation, energy metabolism, and contractile gene expression. Interestingly, the mRNA changes correlated poorly with changes in protein synthesis rates, consistent with post-transcriptional control mechanisms. In summary, the experiments described here reveal the signatures and timing of protein flux changes during skeletal muscle regeneration, as well as the inability of mRNA expression measurements to reveal changes in directly measured protein turnover rates. The results of this work described here provide a better understanding of the muscle regeneration process and could help to identify potential biomarkers or therapeutic targets.

Salinity is a classic problem in planning the quality of freshwater resources management. Recent studies related to hybrid machine learning models have shown it's capability to simulate salinity dynamics. However, previous studies of metaheuristic algorithms have not dealt with comparing single- and hybrid-based algorithms in much detail. The present study aimed to develop univariate salinity by applying an artificial neural network model (ANN) integrated with (hybrid-based) coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA). The methodology was developed and tested using electrical conductivity (EC) and total dissolved solids (TDS) data collected from the Euphrates River in Babylon Province, Iraq, from 2010 to 2019. The CPSOCGSA performance was evaluated by various single-based ones, including multi-verse optimiser (MVO), marine predator's optimisation algorithm (MPA), particle swarm optimiser (PSO), and the slim mould algorithm (SMA). The principal finding here confirms that hybrid-based outperformed four single-based algorithms based on different criteria. The outcomes for TDS were 0.004, 0.0248, and 0.98 for CPSOCGSA-ANN technique concern scatter index (SI), root-mean-squared error (RMSE), and correlation coefficient (R2), respectively. For EC, the results were 0.96 for R2, 0.0386 for RMSE, and 0.006 for SI. Due to its predictive accuracy, the proposed CPSOCGSA-ANN approach is suggested as a potential strategy for predicting monthly salinity data. Considering agriculture's vital role in Babylon Province's economy, this study may help inform future freshwater quality management decisions.

This research aims to use numerical methods to analyze concrete beams with different reinforcement ratios. Two software packages – ABAQUS and OpenSeesPy – were employed to achieve this task. Empirical stress–strain relationships were utilized to forecast the concrete’s stress–strain behavior. The numerical analysis results were compared with previously published experimental results, and the findings showed a reasonable similarity. The results were consistent with the published laboratory results, particularly for ultimate and yield loads, with no more than 10% differences. However, the ultimate deflection variation was higher. For the first control beam, denoted as B 2−12, ABAQUS predicted a 24.64% difference in ultimate deflection, while OpenSeesPy predicted a 35.83% difference for the second beam, sampled as B 2–16. However, the ultimate deflection for the remaining beams differed by less than 10%. Meanwhile, the difference in yield deflection was greater than in ultimate deflection, with OpenSeesPy showing a maximum difference of 18.51%. The maximum ductility was found to occur at a reinforcement ratio equal to 0.0016. Additionally, OpenSeesPy was faster than ABAQUS in computation while still producing satisfactory agreement with experimental results.

The study aims to show the emergence of UNESCO chairs in Iraqi universities and the activities carried out to achieve the goals of sustainable development, as each chair was established to achieve one of these goals, which left its impact on some educational and social sectors, and thus the importance of the study emanates from the need to indicate the establish of UNESCO chairs in Iraqi universities and the activities that strengthened their establishment, activity and local and international initiatives, as well as to identify what these chairs have achieved from the sustainable development goals.

This paper introduces a robust approach, integrating a Virtual Inertia Controller (VIC) with a modified demand response controller for an islanded Multi-Microgrid (MMG) system, accommodating high levels of Renewable Energy Sources (RESs). In these MGs, the low inertia in the system has an undesirable impact on the stability of MG frequency. As a result, it leads to a weakening of the MGs overall performance. A novel fractional derivative virtual inertia is integrated into the VIC loop to address this issue. This enhancement aims to fortify the MG’s stability and robust performance, particularly when facing contingencies. Furthermore, a modified demand response controller has been incorporated into the proposed inertia control technique to mitigate the frequency fluctuations and reduce stress on the energy storage system (ESS). Fractional Order Proportional Integral Derivative (FOPID) controllers have been employed to regulate the active power output of the biodiesel generators and the Geothermal station in the MG. The hybrid sparrow search and mountain gazelle optimizer algorithm (SSAMGO) optimizes the parameters for the three-loop controller. Time-domain simulations assess the effectiveness of proposed controllers in enhancing system frequency stability. SSAMGO’s performance was comprehensively evaluated, comparing it to various optimization algorithms in diverse scenarios. The results obtained from the MMG system demonstrate that utilizing the proposed controller technique, optimized with hybrid SSAMGO parameters, yields notable improvements in settling time by 24.68%, 46.20%, 7.52%, and 61.01%, steady-state error values by 72.56%, 98.18%, 98.73%, and 6.67%, undershoot by 105.76%, 144.23%, 19.23%, and 7.69% compared to other state-of-the-art algorithms presented in the literature. Finally, the proposed control technique’s effectiveness and robustness are assessed in comparison to conventional inertia control across various system scenarios. These scenarios encompass random load demand fluctuations, real-time changes in RES, and a wide spectrum of system operations, including situations with reduced damping and inertia and high levels of load variation.

This paper presents a novel approach to developing a work roll prediction model that takes into account both the mechanism and condition influences on work roll wear. This was accomplished by conducting an analytic calculation of work roll mechanism influence, constructing a work roll wear model, and combining the wear mechanism with actual wear data. The resulting model is applicable to both symmetric and asymmetric wear of the work roll, and experimental results showed that the relative error between measured and predicted values was less than 5%, with a maximum error of below 15%. This level of accuracy is sufficient for predicting roll wear and lays the foundation for improved strip shape control and roll design. Furthermore, this approach has the potential to generate significant economic benefits and has wide-ranging applications.

COVID-19 is hastening the adoption of online learning and teaching worldwide, and across all levels of education. While many of the typical learning and teaching transactions such as lecturing and communicating are easily handled by contemporary online learning technologies, others, such as assessment of learning outcomes with closed book examinations are fraught with challenges. Among other issues to do with students and teachers, these challenges have to do with the ability of teachers and educational organizations to ensure academic integrity in the absence of a live proctor when an examination is being taken remotely and from a private location. A number of online proctoring tools are appearing on the market that portend to offer solutions to some of the major challenges. But for the moment, they too remain untried and tested on any large scale. This includes the cost of the service and their technical requirements. This paper reports on one of the first attempts to properly evaluate a selection of these tools and offer recommendations for educational institutions. This investigation, which was carried out at the University of the South Pacific, comprised a four-phased approach, starting with desk research that was followed with pilot testing by a group of experts as well as students. The elimination of a tool in every phase was based on the 'survival of the fittest' approach with each phase building upon the milestones and deliverables from the previous phase. This paper presents the results of this investigation and discusses its key findings.