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In this study, a new multiobjective optimisation-based approach for Wind Farm Layout Optimisation (WFLO) is developed. The proposed approach combines four distinct Evolutionary algorithms (EA) based on multiobjective optimisation methods into a more powerful parallel method. The four combined algorithms are: the Radial Space Division based EA (RSEA), the Reference Points based EA (RPEA), RVEA embedded with the reference vector regeneration strategy (RVEAa) and the Reference Vector Guided EA (RVEA). The proposed approach is PRPSVEAa, where the letter P stands for parallel, and the remaining letters are used from different combined methods. In this research, four case studies have been investigated using four different commercial wind turbines where the hub heights of Wind Turbines (WT) are kept the same in some cases and varied in some. The results indicate that the Pareto set of solutions varies from each other with different numbers of WT as they spread over a wide region. This offers the designer the most suitable layout solution based on technical and economic factors. The obtained result can also be used to plan for future extensions of the research work.

Abstract Free-living bacterial community and abundance have been investigated extensively under different soil management practices. However, little is known about their nitrogen (N) fixation abilities, and how their contributions to N budgets impact plant growth, yield, and carbon (C) and N cycling enzymes in a long-term consecutive sugarcane monoculture farming system, under contrasting amendments, along different soil horizons. Here, nifH gene amplicon was used to investigate diazotrophs bacterial community and abundance by leveraging high-throughput sequencing (HTS). Moreover, edaphic factors in three soil depths (0–20, 20–40, and 40–60 cm) under control (CK), organic matter (OM), biochar (BC), and filter mud (FM) amended soils were investigated. Our analysis revealed that β-glucosidase activity, acid phosphatase activity, ammonium (NH4 +-N), nitrate (NO3 –N), total carbon (TC), total nitrogen (TN), and available potassium (AK) were considerably high in 0–20 cm in all the treatments. We also detected a significantly high proportion of Proteobacteria and Geobacter in the entire sample, including Anabaena and Enterobacter in 0–20 cm soil depth under the BC and FM amended soils, which we believed were worthy of promoting edaphic factors and sugarcane traits. This phenomenon was further reinforced by network analysis, where diazotrophs bacteria belonging to Proteobacteria exhibited strong and positive associations soil electrical conductivity (EC), soil organic matter content (SOM) available phosphorus (AP), TN, followed by NH4+-N and NO3 –N, a pattern that was further validated by Mantel test and Pearson’s correlation coefficients analyses. Furthermore, some potential N-fixing bacteria, including Burkholderia, Azotobacter, Anabaena, and Enterobacter exhibited a strong and positive association with sugarcane agronomic traits, namely, sugarcane stalk, ratoon weight, and chlorophyll content. Taken together, our findings are likely to broaden our understanding of free-living bacteria N-fixation abilities, and how their contributions to key soil nutrients such as N budgets impact plant growth and yield, including C and N cycling enzymes in a long-term consecutive sugarcane monoculture farming system, under contrasting amendments, along different soil horizons.

IntroductionThe utilization of biochar (BC) as a soil amendment in agriculture has gained significant traction among many farmers and researchers, primarily due to its eco-friendly role in boosting crop output. However, the performance of specific metabolites (e.g., zeatin, melatonin, sucrose, and phenyllactic acid) in the various tissues of sugarcane plant (leaf, stem, and root) and rhizosphere soil-deemed plant growth and stress regulators in a long-term BC-amended field remains poorly understood. Additionally, literature on the shift in soil attributes and crop growth triggered by the strong response of these bioactive compounds to longterm BC utilization remains undocumented.MethodsMetabolome integrated with highthroughput sequencing analyses were conducted to identify and quantify the performance of plant growth and stress-regulating metabolites in a long-term BC-amended field. Additionally, we investigated how the response of these compounds to BC-treated soil influences crop traits and soil biochemical properties.ResultsWe also identified and quantified the performance of pathogenic bacteria and unraveled the association between these compounds and potential plant growth-promoting bacteria. The BC-supplemented soil significantly boosted the crop traits, including brix, sucrose content, and chlorophyll, as well as soil nutrients, such as soil total nitrogen (TN), ammonium (NH4+-N), and nitrate (NO3--N). We also noticed that metabolite-deemed plant growth and stress regulators, including melatonin and phenyllactic acid, were enriched considerably in the stem and root tissues of the BC-amended soil. Zeatin in the leaf, stem, and root tissues exhibited the same trend, followed by sucrose in the leaf tissue of the BC-treated soil, implying that the strong response of these compounds to BC utilization contributed to the promotion of crop traits and soil quality. Pathogenic bacteria belonging to Proteobacteria and Acidobacteria were suppressed under the BC-supplemented soil, especially in the root tissue and rhizosphere soil, whereas plant growth-regulating bacteria, mainly Bradyrhizobium, responded strongly and positively to several metabolites.DiscussionOur finding provides valuable information for agronomists, farmers, and environmentalists to make informed decisions about crop production, land use, and soil management practices. Proper soil assessment and understanding of the interaction between the attributes of soil, BC, and metabolites are essential for promoting sustainable agriculture practices and land conservation.

BackgroundCoronavirus disease 2019 (COVID-19) has emerged as an important cause of morbidity and mortality worldwide. The aim of this study is to identify the clinical predictors of mortality among patients with COVID-19 pneumonia during first and second waves in a treatment center in northwestern Nigeria.MethodsThis was a retrospective cohort study of 195 patients hospitalized with COVID-19 between April 2020 to March 2021 at a designated COVID-19 isolation center in Kano State, Northwest Nigeria. Data were summarized using frequencies and percentages. Unadjusted odds ratios and 95% confidence intervals and p-values were obtained. To determine independent determinants of mortality, we performed a stepwise multivariate logistic regression model.ResultsOf 195 patients studied, 21(10.77%) patients died. Males comprised 158 (81.03%) of the study population. In the adjusted stepwise logistic regression analysis, age>64 years (OR = 9.476, 95% CI: 2.181-41.165), second wave of the pandemic (OR = 49.340, 95% CI:6.222-391.247), cardiac complications (OR = 24.984, 95% CI: 3.618-172.508), hypertension (OR = 5.831, 95% CI:1.413-24.065) and lowest systolic blood pressure while on admission greater than or equal to 90mmHg were independent predictors of mortality (OR = 0.111, 95%CI: 0.021-0.581).ConclusionStrategies targeted to prioritize needed care to patients with identified factors that predict mortality might improve patient outcome.

This paper aims to optimally design a PV/Wind/Diesel Hybrid Microgrid System (HMS) for a small number of houses considering load uncertainty for the city of Yanbu, Saudi Arabia. Designing such a hybrid system with all the renewable and non-renewable sources, storage devices, converters, and loads is a complicated task. A multiobjective approach has been adopted to optimize the microgrid design. Two methodologies are available for solving such multiobjective problems. In the first approach, the problem is transformed into a single objective one (using aggregation, for instance), whereas, the second technique treats objectives simultaneously and independently as adopted in this paper. The proposed approach offers the Pareto front; a set of solutions in one run opening the door of choosing the most suitable solution from the available options based on the experience, expertise and requirement of the designer. This paper presents a novel approach of using Decomposition Based Multiobjective Evolutionary Algorithm (MOEA/D) to optimally design the PV/Wind/Diesel HMS considering load uncertainty. Loss of Power Supply Probability (LPSP) and Cost of Electricity (COE) are considered as the objective functions of the optimization problem. Furthermore, two separate load cases of 5 and 10 houses are tested to verify the robustness of the approach. The obtained results are beneficial in assisting researchers and practitioners in selecting the optimal configuration of the microgrid.

Objectives Nigeria reported an upsurge in cholera cases in October 2020, which then transitioned into a large, disseminated epidemic for most of 2021. This study aimed to describe the epidemiology, diagnostic performance of rapid diagnostic test (RDT) kits and the factors associated with mortality during the epidemic.Design A retrospective analysis of national surveillance data.Setting 33 of 37 states (including the Federal Capital Territory) in Nigeria.Participants Persons who met cholera case definition (a person of any age with acute watery diarrhoea, with or without vomiting) between October 2020 and October 2021 within the Nigeria Centre for Disease Control surveillance data.Outcome measures Attack rate (AR; per 100 000 persons), case fatality rate (CFR; %) and accuracy of RDT performance compared with culture using area under the receiver operating characteristic curve (AUROC). Additionally, individual factors associated with cholera deaths and hospitalisation were presented as adjusted OR with 95% CIs.Results Overall, 93 598 cholera cases and 3298 deaths (CFR: 3.5%) were reported across 33 of 37 states in Nigeria within the study period. The proportions of cholera cases were higher in men aged 5–14 years and women aged 25–44 years. The overall AR was 46.5 per 100 000 persons. The North-West region recorded the highest AR with 102 per 100 000. Older age, male gender, residency in the North-Central region and severe dehydration significantly increased the odds of cholera deaths. The cholera RDT had excellent diagnostic accuracy (AUROC=0.91; 95% CI 0.87 to 0.96).Conclusions Cholera remains a serious public health threat in Nigeria with a high mortality rate. Thus, we recommend making RDT kits more widely accessible for improved surveillance and prompt case management across the country.

Snakebite envenoming (SBE) is a neglected public health problem, especially in Asia, Latin America and Africa. There is inadequate knowledge of venom toxicokinetics especially from African snakes. To mimic a likely scenario of a snakebite envenoming, we used an enzyme-linked immunosorbent assay (ELISA) approach to study the toxicokinetic parameters in rabbits, following a single intramuscular (IM) administration of Northern Nigeria Naja nigricollis venom. We used a developed and validated non-compartmental approach in the R package PK to determine the toxicokinetic parameters of the venom and subsequently used pharmacometrics modelling to predict the movement of the toxin within biological systems. We found that N. nigricollis venom contained sixteen venom protein families following a mass spectrometric analysis of the whole venom. Most of these proteins belong to the three-finger toxins family (3FTx) and venom phospholipase A2 (PLA2) with molecular weight ranging from 3 to 16 kDa. Other venom protein families were in small proportions with higher molecular weights. The N. nigricollis venom was rapidly absorbed at 0.5 h, increased after 1 h and continued to decrease until the 16th hour (Tmax), where maximum concentration (Cmax) was observed. This was followed by a decrease in concentration at the 32nd hour. The venom of N. nigricollis was found to have high volume of distribution (1250 ± 245 mL) and low clearance (29.0 ± 2.5 mL/h) with an elimination half-life of 29 h. The area under the curve (AUC) showed that the venom remaining in the plasma over 32 h was 0.0392 ± 0.0025 mg h.L−1, and the mean residence time was 43.17 ± 8.04 h. The pharmacometrics simulation suggests that the venom toxins were instantly and rapidly absorbed into the extravascular compartment and slowly moved into the central compartment. Our study demonstrates that Nigerian N. nigricollis venom contains low molecular weight toxins that are well absorbed into the blood and deep tissues. The venom could be detected in rabbit blood 48 h after intramuscular envenoming.

Abstract Background Straw retention is a substitute for chemical fertilizers, which effectively maintain organic matter and improve microbial communities on agricultural land. The purpose of this study was to provide sufficient information on soil fungal community networks and their functions in response to straw retention. Hence, we used quantitative real-time PCR (qRT-PCR), Illumina MiSeq (ITS rRNA) and FUNGuild to examine ITS rRNA gene populations, soil fungal succession and their functions under control (CK) and sugarcane straw retention (SR) treatments at different soil layers (0–10, 10–20, 20–30, and 30–40 cm) in fallow fields. Result The result showed that SR significantly enhanced ITS rRNA gene copy number and Shannon index at 0–10 cm soil depth. Fungi abundance, OTUs number and ACE index decreased with the increasing soil depth. The ANOSIM analysis revealed that the fungal community of SR significantly differed from that of CK. Similarly, significant difference was also observed between topsoil (0–20 cm) and subsoil (20–40 cm). Compared with CK, SR decreased the relative abundance of the pathogen, while increased the proportion of saprotroph. Regarding soil depth, pathogen relative abundance in topsoil was lower than that in subsoil. Besides, both sugarcane straw retention and soil depths (topsoil and subsoil) significantly altered the co-occurrence patterns and fungal keystone taxa closely related to straw decomposition. Furthermore, both SR and topsoil had higher average clustering coefficients (aveCC), negative edges and varied modularity. Conclusions Overall, straw retention improved α-diversity, network structure and fungal community, while reduced soil pathogenic microbes across the entire soil profile. Thus, retaining straw to improve fungal composition, community stability and their functions, in addition to reducing soil-borne pathogens, can be an essential agronomic practice in developing a sustainable agricultural system.

Abstract Background Automatic generation control (AGC) of multi-area interconnected power system (IPS) is often designed with negligible cross-coupling between the load frequency control (LFC) and automatic voltage regulation (AVR) loops. This is because the AVR loop is considerably faster than that of LFC. However, with the introduction of slow optimal control action on the AVR, positive damping effect can be achieved on the LFC loop thereby improving the frequency control. In this paper, LFC synchronized with AVR in three-area IPS is proposed. Model predictive controller (MPC) configured in a dense distributed pattern, due to its online set-point tacking is used as the supplementary controller. The dynamics of the IPS subjected to multi-area step and random load disturbances are studied. The efficacy of the developed scheme is ascertained by simulating the disturbed system in MATLAB/Simulink. Results Based on the comparative analysis on the system responses, it is established that by cross-coupling the LFC loop with AVR, reductions of 66.45% and 59.09% in the frequency and tie-line power maximum deviations respectively are observed, while the respective settling times are found to be reduced by 29.68% and 22.77% when compared with the uncoordinated control scheme. In addition, the standard deviation and variance of the integral time absolute error of the system’s responses have reduced by 23.21% and 20.83% respectively compared to those obtained in a similar study. Conclusions The reduction in the maximum deviations and settling times in the system states indicates that introducing the voltage control via AVR loop has improved the frequency control significantly. While the lower standard deviation and variance of the integral time absolute error signify improvement in the robustness of the developed algorithm. However, this improvement is at the detriment of the controller size and computational complexity. In the uncoordinated control scheme, the control vector is one-dimensional, while in the coordinated scheme, the control vector is two-dimensional for each CA.

ObjectivesMany students seem to find pharmacology learning very challenging due to the complexity and variety of drugs they have to study. The number of drugs the students have to learn, the duration of time to learn the medications, and the evolving nature of diseases demanded learning beyond the classroom walls. This study explored and described nursing students' experiences in community and hospital-based pharmacy practice sites during their service-learning and its implications for pharmacology pedagogical practices.MethodsKolb's learning theory provided the framework to explore nursing students' 48-hour service-learning experiences at community/hospital-based pharmacies in Belize and its implications for pharmacology pedagogy. The study utilized two qualitative approaches, reflective journals and focus group interviews, to collect data from 46 second-year nursing students. NVivo software and coding schemes were employed to analyze the data from the interviews and reflective journals.ResultsStudents reported learning medications, integrating classroom pharmacological knowledge at pharmacy practice sites, acquiring and enhancing communication skills, interpreting prescriptions, dispensing medications, drug calculations, taking inventory, doing vital signs, and patient education. In addition, students reported experiencing inter-professional relationships as healthcare team members. Anxiety was a major challenge experienced by many students at the beginning of the service-learning experience.ConclusionsThis study highlights the importance of experiential learning of pharmacology amongst second year nursing students, offering the opportunity to inform and support pharmacotherapeutics educators in designing strategies for more effective teaching of medications to nursing students. It also supports the addition of pharmacy placements to the nursing curriculum' as it shows that nursing students can learn medications, skills, and teamwork from experiential pharmacy site posting. Combining classroom instruction with pharmacy experiential service learning might be an effective complement for teaching nursing pharmacology.

Background Exploring high-quality organic amendments has been a focus of sustainable agriculture. Filtered mud (FM), a sugar factory waste derived from sugarcane stems, could be an alternative organic amendment for sugarcane production. However, the effects of its application proportions on soil fertility, nutrient cycling, structure of soil bacterial and fungal communities, and the growth of sugarcane in clay-loam soils remain unexplored. Methods Three application proportions of FM: (FM1-(FM: Soil at 1:4), FM2-(FM: Soil at 2:3), and FM3-(FM: Soil at 3:2)) were evaluated on sugarcane growth and soil nutrient cycling. High throughput sequencing was also employed to explore soil microbial dynamics. Results We observed that FM generally increased the soil’s nutritional properties while improving NO3− retention compared to the control, resulting in increased growth parameters of sugarcane. Specifically, FM1 increased the concentration of NH4+−N, the N fraction preferably taken up by sugarcane, which was associated with an increase in the plant height, and more improved growth properties, among other treatments. An increase in the proportion of FM also increased the activity of soil nutrient cycling enzymes; urease, phosphatase, and β-glucosidase. High throughput sequencing revealed that FM reduced the diversity of soil bacteria while having insignificant effects on fungal diversity. Although increasing FM rates reduced the relative abundance of the phyla Proteobacteria, its class members, the Gammaproteobacteria and Betaproteobacteria containing some N-cycling related genera, were stimulated. Also, FM stimulated the abundance of beneficial and lignocellulose degrading organisms. These included the bacterial phyla Actinobacteria, Bacteroidetes, Acidobacteria, Chloroflexi, and the fungal phylum Ascomycota. The distribution of the soil microbial community under FM rates was regulated by the changes in soil pH and the availability of soil nutrients. Since FM1 showed more promise in improving the growth properties of sugarcane, it could be more economical and sustainable for sugarcane production in clay-loam soils.

Most industrial processes are regulated using PID control. However, many such processes often operate far from optimally because PID may not be the most suitable control method. Moreover, second-order models represent a large class of all controlled systems. This work studies the performance of some commonly used industrial PID controllers relative to MPC to understand when it is more suitable to use Model predictive control. MPC is used for this comparison because it has been the most successful industrial controller after PID. It can be concluded from the studies that improved performance can be achieved with MPC, even for modest dead time and when the damping ratio is relatively low. These improvements are prominent for dead-time dominant systems, whose dead-time to time-constant ratio is at least three.

The current oil industry is moving towards digitalization, which is a good opportunity that will bring value to all its stakeholders. The digitalization of oil and gas discovery, which are production-based industries, is driven by enabling technologies which include machine learning (ML) and big data analytics. However, the existing Metocean system generates data manually using sensors such as the wave buoy, anemometer, and acoustic doppler current profiler (ADCP). Additionally, these data which appear in ASCII format to the Metocean system are also manual and silos. This slows down provisioning, while the monitoring element of the Metocean data path is partial. In this paper, we demonstrate the capabilities of ML for the development of Metocean data integration interoperability based on intelligent operations and automation. A comprehensive review of several research studies, which explore the needs of ML in oil and gas industries by investigating the in-depth integration of Metocean data interoperability for intelligent operations and automation using an ML-based approach, is presented. A new model integrated with the existing Metocean data system using ML algorithms to monitor and interoperate with maximum performance is proposed. The study reveals that ML is one of the crucial and key enabling tools that the oil and gas industries are now focused on for implementing digital transformation, which allows the industry to automate, enhance production, and have less human capacity. Lastly, user recommendations for potential future investigations are offered.

Despite progress in understanding diazotrophic distribution in surface soils, few studies have investigated the distribution of diazotrophic bacteria in deeper soil layers. Here, we leveraged high-throughput sequencing (HTS) of nifH genes obtained to assess the influence of biochar amended soil (BC) and control (CK), and soil depths (0-20, 20-40 and 40-60 cm) on diazotrophic abundance and community structures, soil enzyme activities and physio-chemical properties. Multivariate ANOVA analysis revealed that soil depth had profound impact on majority of the soil parameters measured than fertilization. Although soil physio-chemical properties, enzymes activities, diazotrophic genera and enriched operational taxonomic units (OTUs) were significantly influenced across the entire soil profiles, we also observed that BC amended soil significantly increased cane stalk height and weight, nitrate (NO3-), ammonium (NH4+), organic matter (OM), total carbon (TC) and available potassium (AK), and enhanced diazotrophic genera in soil depth 0-20 cm compared to CK treatment. Soil TC, total nitrogen (TN), OM and NH4+ were the major impact factors shifting diazotrophic community structures in soil depth 0-20 cm. Overall, these results were more pronounced in 0-20 cm soil depth in BC than CK treatment.

The development of efficient metal doped semiconductors for Photovoltaic applications has gained a lot of research attention. In this present paper, pure and silver nanoparticles (AgNPs)-modified TiO2 nanocrystals (NCs) with different amount of AgNPs (say 50, 100, 150, 200, and 250 µL) were achieved and the effects of AgNPs on the TiO2 NCs were explored systematically. The optical, structural and morphological properties were probed using UV-visible spectrophotometer, X-ray diffraction (XRD), and scanning electron microscope (SEM). The results of the optical studies showed a characteristic peak of TiO2 and the redshifting of the peak position was observed by introducing AgNPs. The synergetic effects from AgNPs and TiO2 results to diminished band gap. The XRD result confirmed the formation of a tetragonal anatase TiO2 phase with a decrease in crystallite size with increasing AgNPs content. The SEM images show enhanced nucleation and film growth with presence of shining surface which can be seen to contribute to good photon management by enhancing light scattering. The unadulterated TiO2 and AgNPs-modified TiO2 have spherical morphology and uniform size distribution ranging from 20 to 30 nm. This study established the view that surface modification of TiO2 with AgNPs is a viable approach towards achieving an efficient light photocatalyst. [ABSTRACT FROM AUTHOR]

Efficient control schemes for ill-conditioned systems, such as the high-purity distillation column, can be challenging and costly to design and implement. In this paper, we propose a distributed control scheme that utilizes well-designed excitation signals to identify the system. Unlike traditional systems, we found that a summation of correlated and uncorrelated signals can yield better excitation of the plant. Our proposed distributed model predictive control (MPC) scheme uses a shifted input sequence to address loop interactions and reduce the computational load. This approach deviates from traditional schemes that use iteration, which can increase complexity and computational load. We initially tested the proposed method on the linear model of a highly coupled 2 × 2 process and compared its performance with decentralized proportional-integral-derivative (PID) controllers and centralized MPC. Our results show improved performance over PID controllers and similar results to centralized MPC. Furthermore, we compared the performance of the proposed approach with a centralized MPC on a nonlinear model of a distillation column. The results for the second study also demonstrated comparable performance between the two controllers with the decentralised control slightly outperforming the centralised MPC in some cases. These findings are promising and may be of interest to practitioners that are more comfortable with tuning decentralised loops. [ABSTRACT FROM AUTHOR]