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Abstract Distributed denial of service (DDoS) attack is one of the most hazardous assaults in cloud computing or networking. By depleting resources, this attack renders the services unavailable to end users and leads to significant financial and reputational damage. Hence, identifying such threats is crucial to minimize revenue loss, market share, and productivity loss and enhance the brand reputation. In this study, we implemented an effective intrusion detection system using deep learning approach. The suggested framework includes three phases: Data pre-processing, Data balancing, and Classification. First, we prepare the valid data, which is helpful for further processing. Then, we balance the given pre-processed data by Conditional generative adversarial network (CGAN), and as a result, we can minimize the bias towards the majority classes. Finally, we distinguish whether the traffic is attack or benign using a stacked sparse denoising autoencoder (SSDAE) with a firefly-black widow (FA-BW) hybrid optimization algorithm. All these experiments are validated through the CICDDoS2019 dataset and compared with well-received techniques. From these findings, we observed that the proposed strategy detects DDoS attacks significantly more accurately than other approaches. Based on our findings, this study highlights the crucial role played by advanced deep learning techniques and hybrid optimization algorithms in strengthening cybersecurity against DDoS attacks.

The extract obtained from the stem bark of Khaya ivorensis has been utilized for malaria treatment. Given the rising resistance of malaria parasites to current medications, exploring new pharmacological targets is essential. Metalloaminopeptidases, particularly PfM1AP, have been identified as promising targets due to their vital role in the survival of the parasite. This study employed computational modeling to evaluate the binding affinities and interaction characteristics of 165 compounds found in K. ivorensis with PfM1AP. The top five compounds showed binding affinities ranging from −18.306 to −13.073 kcal/mol, significantly higher than the standard ligand's − 7.97 kcal/mol. Among these, pentagalloylglucose displayed the strongest binding affinity and most stable interactions, suggesting its potential as a PfM1AP inhibitor. ADMET analysis revealed some limitations regarding oral bioavailability and permeability through the blood-brain barrier; however, these compounds exhibited favorable safety profiles with low predicted toxicity levels. Despite the pharmacokinetic challenges, their high binding affinities and stable interactions indicate their potential as effective antimalarial agents. These results highlight the need for further experimental validation and optimization to improve the drug-like properties of these compounds, particularly concerning bioavailability and pharmacokinetic issues. Ultimately, this research contributes to the growing body of work aimed at developing innovative antimalarial treatments and lays the groundwork for future studies focused on targeted approaches against malaria.

ABSTRACT A method has been developed for separating a mixture of calcium, magnesium and sodium sulfates obtained through the interaction of sulfuric acid and waste from the water purification process generated by using membrane filters. The primary goal of this method is to extract gypsum and produce gypsum‐based binders. Patterns were identified regarding how various types, ratio and quantities of additives: blast furnace slag, granite screenings, portland cement, electric steel smelting slag affect the water‐gypsum ratio, strength properties, and water resistance of high‐strength gypsum binders. It was found that adding a single‐component additive specifically to enhance water resistance does not significantly impact these properties. Complex additives have been developed based on Portland cement, granulated blast furnace slag, electric furnace slag, expanded clay dust, and granite screenings of various fractions. These additives are designed to maximize the water resistance of high‐strength gypsum binder based on synthetic calcium sulfate dihydrate. As a result, the water resistance coefficient increased from 0.45 to 0.52. Additionally, a technological block diagram of the process has been proposed.

IntroductionWhen implemented by national and regional regulatory agencies good review practices (GRevPs) support the timely high-quality review of medicines for enhanced patients’ availability to safe, quality and efficacious innovative and generic products. It is important that all aspects of GRevPs are continuously evaluated and updated to promote the continuous improvement of regulatory systems at national and regional levels. The aim of this study was to assess and compare the GRevPs of the national medicines regulatory agencies (NMRAs) of Burkina Faso, Cote d’Ivoire, Ghana, Nigeria, Senegal, Sierra Leone and Togo, who are active participants of the ECOWASMRH initiative to identify opportunities for improvement.MethodsThe Optimising Efficiencies in Regulatory Agencies questionnaire, was completed by each of the NMRAs, which facilitates the assessment of GRevPs, which in turn affect the regulatory review processes.ResultsExcept for Cote d’Ivoire and Nigeria which are autonomous, the other five NMRAs operate within the administrative structure of their respective Health Ministry, to regulate medical products for human use, medical devices and diagnostics. Apart from Togo, the agencies receive partial funding from their governments as well as from regulatory fees. Population in the seven countries ranges from 8.6 million to 211.4 million. All the NMRAs had measures in place to achieve quality in their review processes, although there were some remaining initiatives related to transparency and communication, continuous improvement and training and education, to be implemented. Of the ten quality decision-making practices Ghana had implemented nine into a framework, Togo eight, Cote d’Ivoire seven, Nigeria six, and Burkina Faso five; while Sierra Leone has partially implemented all ten and Senegal had not implemented any of the quality decision-making practices.ConclusionThe study compared the organisation, GRevPs and quality decision-making processes of the NMRAs that actively participate in the ECOWAS-MRH initiative. Though some differences were identified with regard to organisation, a significant number of good review practice initiatives and quality decision-making practices were identified yet to be implemented to promote continuous improvement in the regulatory processes of the NMRAs.

Abstract Background Epispadias is a rare form of genito-urinary congenital anomaly and presentation in the middle-ages is even rarer. The reproductive outcome of treatment which was almost immediate, highlights the life changing effect of appropriate treatment for this condition in a middle-aged patient. We hereby report this rare case of a middle-aged man presenting with complete male epispadias with background infertility and the outcome of effective treatment. (Reviewer #1. Comment 1). Case presentation Our patient is a 54-year-old security guard who presented to our facility in February 2022 (Reviewer #1. Comment 3) with passage of urine from an abnormal opening since birth. Examination revealed a middle-aged man having ammoniacal smell. He had a spade like glans penis, ventral hooding, urethral meatus at the root of the penis dorsally with no chordee. He was diagnosed to have complete male epispadias (CME) for which he eventually had a modified Cantwell–Ransley procedure under general anaesthesia. About 3 months after the procedure, patient was able to impregnate his wife, a feat he will be achieving for the first time in his life. Conclusions The right treatment irrespective of age at presentation could significantly improve the quality of life of patients as evidenced by our patient whom after surgery was able to impregnate his wife for the first time at 54 years of age.

This study assessed health insurance uptake, and payment preferences for health insurance enrollment, and identified barriers and facilitators of the utilization of health insurance amongst residents in Lagos State.

Background: The choice of method of dying by suicide can determine the lethality of a suicide attempt, especially among males and females. However, a less attention has been paid to this area of research among Nigerian authors. Objective: The objectives of this study were to investigate the distribution of completed suicide across methods of suicide among decedents and to examine the odds ratio of males using hanging or poisoning methods. Materials and Methods: This retrospective chart-based study was conducted among those who died by suicide and whose cases were reported at the police stations. The data were collected by checking the files at the homicide and suicide departments at the police headquarters in southwest Nigeria. Ethical approval was obtained for the study. Descriptive statistics and logistic regressions were used to analyze the data. Results: The results revealed that 78.3% were male, while females were 21.7%. 53.7% of the sampled population died by hanging and 23.2% died by poisoning. 8.9% of the decedents died by self-harm suicide. Suicide choices traceable to mental illness and jumping/drowning were 6.4% and 6.4%, respectively, while suicide by gunshot (1.5%) was less prominent. Furthermore, the result showed that there was a 3% likelihood that a male would die by hanging. Conclusion: Males are 3% more likely to die by hanging and are less likely to die by poisoning.

Abstract When drilling wells for energy explorations, it is important to regulate the formation pressures appropriately to prevent kicks, which can lead to unimaginable loss of lives and properties. This is usually done by controlling the equivalent circulating density (ECD), which responds to the dynamic conditions that occur during drilling. The conventional approach to determine ECD is via mathematical modeling or downhole measurements. However, the downhole measurement tools can be very expensive, and the mathematical models do not provide a high degree of accuracy. Some previous authors have proposed using machine learning (ML) techniques to improve the degree of accuracy of the ECD predictions. In this work, we employed an extreme gradient-boosting (XGBoost) methodology to predict ECD values. The model's accuracy was determined using correlation coefficients (R2) and root mean square errors (RMSE) as their performance metrics. The results showed a strong prediction capability with an R2 and RMSE of 1.00 and 0.0005 for the training data and an R2 and RMSE of 0.989 and 0.023 for the testing/blind data set, respectively. The developed model outperformed those obtained using other popular machine learning techniques. Lastly, an interpretation of the model results showed that mud weight, weight on hook, and standpipe pressure contributed the most to the ECD prediction values.

A certificate is evidence of participating in a process, and anyone who holds a certificate is believed to have the prerequisites necessary to handle what the certificate qualifies them for. However, this perception might be incorrect if the certificate has been obtained by taking shortcuts. [Objective] In this paper, a compartmental model was developed to quantify factors that could put the authenticity of a certificate in doubt by examining the trade-off between academic standards and failure rates in the context of tertiary education institutions in Nigeria. [Methodology] The model was validated using several mathematical theorems. Equilibria for the model and the threshold for acceptable academic performance were derived. Stability analysis was carried out by using the stability theory of differential equations based on the derived acceptable academic performance threshold. [Results] The theoretical results for the model were validated through numerical simulations, and the results from the simulations linked acceptable failure rates to academic performance falling below the threshold of the institutions’ standards. [Conclusions] The policy implication of the result is that an increase in the supply of qualified graduates into Nigeria’s labor markets, as well as a reduction in the rate of unemployment, is a function of maintaining academic standards.

Despite decades of rapid plastic production in Nigeria, lack of sufficient data limits knowledge of pollution contribution from micro- and nanoplastics (MNPs). This study investigates the abundance, shapes and colour of MNPs alongside associated pollutants such as polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) in Aarin River, Oyo town, Southwestern Nigeria, over two seasons (rainy and dry). The MNPs were of four size categories - 125, 75, 53 and 0.45 μm. The MNP level was notably higher in the rainy season (130.5 ± 3.5 particles/L (pts/L) in water and 30,384.5 ± 55.0 particles/kg (dry weight) in sediment) compared to the dry season (113.0 ± 5.0 pts/L in water and 2763.5 ± 28.5 pts/kg in sediment), with 53 and 75 μm-sized MNPs predominant in both seasons. Most of the MNPs were fragment-shaped and transparent white in colour. X-ray diffraction, scanning electron microscopy, and Fourier Transform Infrared spectroscopy revealed polyethylene, polypropylene, polyethylene terephthalate, and polysulfone to be prominent MNP constituents. The associated PAHs ranged from 43.40 to 615.77 μg/L and 21.90–599.84 μg/kg (dw) in the predigested water and sediment samples, respectively, with naphthalene having the highest concentration. Iron (Fe), lead (Pb), and chromium (Cr) account for most HMs in both water and sediment. Following organic and inorganic matter digestion, HMs and PAHs were reduced by 99 % and 83 %, respectively. The multivariate analysis of variance (MANOVA) and principal component analysis (PCA) indicated significant effects of seasonal variations and sample type on MNPs and pollutant concentrations. The results emphasize the critical role MNPs play in transporting pollutants.

In most software systems operating within low-resource environments, the persistently encountered challenges related to network availability often result in compromised performance or even complete system failure. To address this issue, software developers frequently resort to ad hoc measures to mitigate these challenges. To offer a more comprehensive solution, this paper introduces an all-encompassing approach in the form of a design pattern. This design pattern uses offline functionalities with localised storage, emphasising the distinction between offline storage and synchronisation, presenting a versatile and high-level methodology for overcoming the recurrent network-related challenges intrinsic to low-resource environments. We describe the use of the design pattern in some real-world use cases, thereby illustrating how a single design pattern is the foundation for many seemingly disparate software engineering approaches. This design pattern holds the potential to significantly redefine the manner in which network availability challenges are approached and addressed.

The increasing demand for insulating bricks, driven by climate change and the rising costs of construction, has led to the exploration of alternative building materials. Clay, which is readily available in our environments, emerged as a viable option. When fired, it achieves sufficient stability to provide effective insulation. While numerous studies have experimented with various types of fired bricks, little attention has been given to modeling their results. This study evaluates the experimental outcomes obtained from the use of locally sourced bulk clay for building construction. Wood sawdust (WSD) was added as a pore former in proportions of 0, 1, 2, 3, 4, and 5 wt%, and firing was performed at 1200 °C and 1400 °C. The influence of these input variations on the properties of the clay bricks was assessed and analyzed using the response surface method. The results revealed that the input variables (WSD and firing temperature) significantly influenced the responses with p-values below 5 %. However, interactions between the input factors had a marginal effect on the outcomes. Optimal performance was achieved with 1.6 wt% WSD and a firing temperature of 1200 °C, demonstrating that the developed fired bricks are suitable for insulation in building construction under these optimal conditions.

This article focuses on the effects of Brownian motion and thermophoresis convection in the stagnation point flow of a Maxwell upper-convected fluid over a non-Darcian porous surface with slip conditions and a magnetic inclination effect. The Maxwell dissipative fluid accounts for Joule heating due to an imposed magnetic field and porous medium resistance. At the same time, the Cattaneo-Christov heat flux model represents thermal relaxation in contrast to the conventional Fourier law. The resulting nonlinear partial differential equations are transformed into ordinary differential equations (ODEs) using similarity variables. The analysis revealed the influence of dimensionless numbers, including Deborah, Eckert, Prandtl, chemical reaction, thermal relaxation, inclination and slip parameters. The findings were presented using graphs and tables. An increase in the thermophoresis parameter notably led to higher concentration and temperature profiles. In contrast, increasing Brownian motion (Nb) decreased the solutal boundary layer thickness but enhanced the thermal boundary layer.

The rising global cost of housing demands innovative solutions to improve construction materials and reduce expenses, making affordable housing more attainable. This study investigates the synergistic benefits of eco-friendly additives—kenaf fiber and glass powder—in masonry applications aimed at affordable housing solutions. The aim is to identify the effect of different kenaf fiber and glass powder proportions on lateritic brick. Kenaf fiber was incorporated into a cement-lateritic clay mix at varying percentages (0.5 %, 1.0 %, 1.5 %, and 2.0 %), while glass powder replaced cement at levels of 10 %, 20 %, 30 %, and 40 %. The reference mix was prepared as 20 % cement, 20 % sand, and 60 % laterite clay while the water/cement ratio was maintained at 0.4. Results indicate that kenaf fiber and glass powder significantly improve compressive, flexural, and splitting strengths compared to the reference mix. However, kenaf fiber exhibits a reduction in ultrasonic velocity. The dosage of kenaf fiber and glass powder profoundly influences the hybrid material properties. The study has revealed that 4 % of glass powder and 1 % of kenaf fiber highly improved the compressive strength, flexural strength and ultrasonic velocity of the mixes. On the other hand, 4 % of glass powder and 1.5 % of kenaf fiber highly improved the splitting strength of the material. These results were supported by a predictive model validated against experimental data. Optimization reveals an optimum mix with 20.44 % cement replacement (comprising 15.91 % cement, 4.08 % glass powder, and 1.19 % kenaf fiber), 20 % sand and 58.80 % clay, offering balanced performance for masonry bricks in affordable mass housing construction.

BackgroundGenerative artificial intelligence (Gen-AI) has emerged as a transformative tool in research and education. However, there is a mixed perception about its use. This study assessed the use, perception, prospect, and challenges of Gen-AI use in higher education.MethodsThis is a prospective, cross-sectional survey of university students in the United Kingdom (UK) distributed online between January and April 2024. Demography of participants and their perception of Gen-AI and other AI tools were collected and statistically analyzed to assess the difference in perception between various subgroups.ResultsA total of 136 students responded to the survey of which 59% (80) were male. The majority were aware of Gen-AI and other AI use in academia (61%) with 52% having personal experience of the tools. Grammar correction and idea generation were the two most common tasks of use, with 37% being regular users. Fifty-six percent of respondents agreed that AI gives an academic edge with 40% holding a positive overall perception about the use in academia. Comparatively, there was a statistically significant difference in overall perception between different age ranges (I2 = 27.39; p = 0.002) and levels of education (I2 = 20.07; p

Abstract The impacts of climate change (CC) on droughts are well documented, but the effects of land-use change (LUC) are poorly understood. This study compares the projected individual and combined impacts of these stressors on future droughts (2021–2050), with respect to baseline (1981–2010) in one of the major tributaries of the Mekong River. LUC impacts on hydrological droughts are minimal compared to CC, with the latter expected to shorten the recurrence interval of a 20-year return period event to every 14 years. Both CC and LUC have significant impacts on agricultural droughts with heightened sensitivity. ‘Once in a Decade’ agricultural droughts will be 40% (35%) longer and 88% (87%) more severe under the CC (LUC) scenario. Under both stressors, the events occurring every 20 years will be twice as frequent. Results highlight the intensification of future droughts and the urgency for actions to mitigate/adapt to climate change and manage land use. Future policy shall holistically address agricultural water management, sustainable land use management, and crop management to cope with future droughts. We recommend developing resilient agricultural practices, enhanced water resource management strategies, and incorporating drought risk into land-use planning to mitigate the compounded impacts of CC and LUC.

Abstract Background The need for online adaptations of research instruments became more pronounced amidst the COVID-19 pandemic. This study sought to modify the REALD-30 for online application (eREALD-30) and evaluate its content validity and internal reliability among medical and dental students in Nigeria. Methods The eREALD-30 required participants to identify if each of the listed words were related to dentistry by ticking either a ‘yes’ or ‘no’ response with the option to mark ‘don’t know’ for words they were unsure about. Scores ranged from 0 to 30. Five oral health experts reviewed the eREALD-30 for cultural appropriateness, while content validity was evaluated by 10 medical and dental students. Internal reliability was assessed with 320 students recruited from 15 medical and dental schools spanning the country’s six geopolitical zones. These students also completed an oral health status assessment tool. Data collection utilized an online survey platform. Validity of the eREALD-30 was determined through correlation analysis between eREALD-30 scores and the oral health status assessment tool. Furthermore, binary logistic regression analysis was employed to explore the assocations between participants’ oral health status and their oral health literacy, adjusting for age, sex, and level of medical and dental education. Results Out of the respondents, 178 (55.6%) exhibited poor oral health literacy, while 205 (64.1%) reported having good oral health status. Those with good oral health literacy demonstrated significantly higher odds of having good oral health status (OR: 1.61; 95% CI: 1.02–2.54; p = 0.04). However, individuals with good oral health literacy had increased odds of good oral health status after adjusting for confounding factors,, though this association did not retain statistical significance (AOR: 1.39; 95% CI: 0.86–2.24; p = 0.17). The eREALD-30 displayed strong internal consistency (Cronbach alpha = 0.933), indicating its reliability in assessing oral health literacy levels, alongside a high content validity score of 0.90. Conclusion The study finding suggests that the e-version of the REALD-30 was reliable and valid for use among medical and dental students in Nigeria.

In this study, we introduce a computational algorithm for solving Integro-Differential Equations (IDEs) using Bernstein polynomials as basis functions. The algorithm approximates the solution by expressing it in terms of Bernstein polynomials and substituting this assumed solution into the IDE. Collocating the resulting equation at evenly spaced points yields a system of linear algebraic equations, which is solved via matrix inversion to find the Bernstein coefficients. These coefficients are then used to construct the approximate solution. Numerical examples demonstrate the method's accuracy and efficiency, highlighting its advantages in reducing computational effort.

Road traffic accidents (RTA) have been of concern both in developed and developing nations of the world. This study examined the road accident trends in Osun State, Nigeria, over 7 years (2015 to 2021). The dataset used is secondary data obtained from the Federal Road Safety Commission (FRSC), Osun State, Nigeria. This includes the number of cases (fatal, serious, and minor), the number of people dead, and the number of people injured. Multivariate Time Series analysis shows that an average of 243 and 44 people were injured and killed, respectively, quarterly. For the total of 1859 reported cases, 6809 and 1232 people were injured and killed, respectively, for the 7 years. The Vector Autoregressive (VAR) model was applied to study the underlying patterns and forecast future values for the number of deaths and injuries for the year 2022. Based on the value of Akaike's Information Criteria (AIC) and Bayesian's Information Criteria (BIC), the model with the constant was the best of all. The result of the forecast indicates that 245 people are predicted to be injured in the first quarter of 2022 and 243 people in the second, third, and fourth quarters. 44 people are predicted to be killed in the first quarter of 2022 and 45 people in the second, third, and fourth quarters, accident occurrence for the 7 years has a low severity index. According to the findings, it was discovered that the number of people injured and killed in traffic accidents has been rising over time. This is the outcome of several variables, including environmental, human, and road-related factors. Therefore, to decrease traffic-related deaths and injuries, the government and concerned non-governmental organizations must embark on educating drivers about defensive driving, enforcing road traffic laws, and traffic education to the populace.

A recent report indicated that one hundred and thirty thousand Nigerians were lately infected with HIV with the majority of infections resulting from unguarded vaginal sex. About two-thirds of new HIV infections in adults exist in women. Male circumcision and male condoms limit the danger of HIV infection, but the adoption of these procedures is beyond the control of Nigerian women due to gender inequality and gender-based violence against women in the country. In an attempt to provide a mathematical framework to examine a potential female-controlled strategy of HIV acquisition in Nigeria, a mathematical model is modified and analyzed for the transmission of HIV by incorporating pre-exposure prophylaxis (PrEP) in the form of a microbicide. The solutions of the model are proved to be positive. The critical points of the model and the epidemic threshold known as the reproduction number are also derived. The restricted case of total compliance to the use of the microbicide is analyzed by proving the global stability of the disease-free equilibrium (DFE) of the model. The general case which permits individuals to default the microbicide is also investigated by proving the global stability of the endemic equilibrium (EE) of the model. Numerical simulation is carried out to verify the analytical results and the results of the simulation show that strict compliance and consistent use of the microbicide may tend HIV acquisition among Nigerian women to zero.

Preserving and innovating indigenous languages is crucial for maintaining cultural heritage and facilitating community development in this digital age. Understanding the digital landscape of IsiXhosa language digitization efforts, however, remains underexplored. This systematic scoping review aims to map the existing literature on digitalization efforts for IsiXhosa language preservation and innovation. A scoping review was conducted, guided by PRISMA-ScR, on relevant literature pertaining to isiXhosa digitization, preservation, and innovations. Two databases were searched (Scopus and Web of Science), and additional articles were identified through a grey literature search (Google Scholar) to identify other relevant literature. Data were extracted in terms of title, year, country, language, digitization efforts, and summary of main findings and results related to isiXhosa language preservation and innovation. A total of 85 unique articles were included from 479 records, leading to the identification of five themes under the digitization efforts. Most studies were conducted in South Africa, accounting for about 78% of the total articles. As such, significant efforts were identified in grammar and morphology, speech recognition, and machine translation. There are unresolved gaps and challenges (such as large and high-quality datasets) that must be addressed. Nevertheless, the efforts demonstrate an increased acceptance of the significance of protecting and improving indigenous African languages, such as isiXhosa, in this era of digital technology.

A low-resource environment has limitations in terms of resources, such as limited network availability and low-powered computing devices. In such environments, it is arguably more difficult to set up new software systems, maintain existing software, and migrate between software systems. This paper presents a survey of software systems for low-resource environments to highlight the challenges (social and technical) and concepts. A qualitative methodology is employed, consisting of an extensive literature review and comparative analysis of selected software systems. The literature covers academic and non-academic sources, focusing on identifying software solutions that address specific challenges in low-resource environments. The selected software systems are categorized based on their ability to overcome challenges such as limited technical skills, device constraints, and socio-cultural issues. The study reveals that despite noteworthy progress, unresolved challenges persist, necessitating further attention to enable the optimal performance of software systems in low-resource environments.

Malaria is a significant global health burden, particularly in regions with limited healthcare resources. Pharmaceutical interventions, specifically artemisinin-based combination therapies (ACTs), have long been the mainstay of malaria treatment due to their proven efficacy in eliminating Plasmodium parasites. Herbal medicine has also gained attention as a potential alternative or adjunctive therapy. Nevertheless, the emergence of drug-resistant strains, notably in Southeast Asia and Africa, poses a considerable challenge to the effectiveness of these pharmaceutical treatments. Using low-value alternating electromagnetic field (EMF) radiation as an anti-malaria treatment is a novel approach that requires further investigation to determine its therapeutic potential. This research studies the comparative analysis of the effect of pharmaceutical intervention, herbal medicine, and low-value alternating EMF as anti-malaria treatments. The research methodology involves a systematic literature review of relevant scientific databases, design, construction, and administration of 20mT & 30mT electromagnetic field, Lumartem and Thitonia Diversifolia (Jume 12) to plasmodium berghei-infected mice for four days consecutively at the same time interval. Results revealed that all treatments were significantly effective. Lumartem is maximally effective from the third day, while Tihonia Diversifolia was maximally effective on the second day. EMF 10mT was maximally effective on the third day, while EMF 20mT did not fully align with the non-infected mice trend, but it is likely to align if treatment continues. The results of this comparative study will contribute to the body of knowledge regarding the effectiveness of pharmaceutical, herbal medicine, and low-value alternating electromagnetic field treatments for malaria.

Suicide is a major global public health problem, with profound implications for individuals, families, and communities. In the United Kingdom (UK), despite efforts to detect and manage suicidal ideas, suicide rates persist, especially among middle-aged men and women, particularly those aged 45 to 54 years. Recent global challenges, such as the COVID-19 pandemic, climate change, conflict, and the environmental crisis, have raised concerns about an increase in suicide rates, particularly among young people. As a result, a population-wide preventive approach based on evidence is imperative to mitigate the projected increase in suicides. To evaluate the effectiveness of suicide prevention strategies, there is a need for an objective and universally accepted risk assessment approach that does not currently exist. This review examines the current landscape of suicide prevention in the United Kingdom and evaluates the strengths and limitations of existing suicide risk assessments tools. The current suicide prevention tools used, including machine learning and mobile applications are discussed. Also, the epidemiological trends in the various regions of the UK, risk factors including age, sex, and socio-economic status are assessed to provide context. Through this discourse, we hope to provide valuable insight for clinicians, researchers, and policy makers about the current landscape of suicide, especially within the United Kingdom, while presenting recommendations regarding areas that require further research and improvement. Accordingly, suicide prevention is and will continue to be a major focus of both the national health service and research in the UK in the strive to reduce the rate of suicide across all regions. Indeed, headways have been made in the use of technology in preventing suicide both locally and globally. However, research should in the future investigate the value of personalized interventions tailored to the various risk factors of suicide and based on appropriate screening and assessment tools.

Background: Night shift duties are crucial in the ICU to ensure care continuity, where critically ill patients require round-the-clock care. However, cumulative night shift duties may disturb circadian rhythm, insomnia, fatigue, and depression, and require further elucidation. Objectives: This study aims to examine the negative consequences of various night shift patterns on insomnia, fatigue, and mental health of ICU Workers. Methods: A cross-sectional study examined how cumulative night shift duty affects insomnia, fatigue, and mental health in critical care providers (CCPs). Results: A total of 1006 participants completed this study between June 2022 and March 2023, including 54.5 % males. About 35 % were between 20 and 30 years of age, and Respiratory Therapists accounted for approximately 46.5 % of the entire sample. Most of our respondents (476; 47 %) reported working night shifts, with a monthly range of 8–15 nights. The prevalence rates for moderate to severe clinical insomnia, fatigue, and moderate to severe depression were 42 %, 48 %, and 32 %, respectively. CCPs working 8–15 nights had a 2-fold risk of clinical insomnia than those working fewer than eight nights with (AOR) and 95 % (CI) of 2.12 and 1.41–3.20, while those working ≥16 nights per month had a greater incidence of clinical insomnia compared to those working

The necessity for environmentally friendly transportation systems has prompted the proliferation of electric vehicles (EVs) in low-voltage (LV) distribution networks. However, large-scale integration and simultaneous charging of EVs can create power quality challenges for the distribution grid. It is therefore important to assess the impact of connecting EVs for charging in existing distribution networks and determine the hosting capacity (HC) of such a network. This paper uses a deterministic time-series method and stochastic method based on a simplified Monte Carlo simulation to estimate the HC of single-phase and three-phase EV charging, respectively, for a South African low-voltage distribution network containing 21 households. Voltage drop and equipment loading are the performance indices (PI) considered for the impact assessment and HC estimation in this study. The impact assessment result confirms that increasing EV charging penetration will result in a corresponding movement of the PIs toward the allowable limits. The results show that the HC is 5–8 three-phase EVs charging simultaneously for the worst-case scenario and 9–13 EVs for the best-case scenario. Furthermore, the single-phase HC for the popular 3.7 kW EV charger is 15 and 8 EVs for the best-case and worst-case scenarios, respectively. The result showing the seasonal variation in HC and for other EV charging power is also presented. The difference in HC for the worst-case and best-case scenarios portrays the effect that the location of charging has on the HC.

Renewable energy has emerged as a promising solution to address the challenges of climate change, energy security, and socio-economic development. South Africa, with its abundant renewable energy resources, has made significant strides in the utilization of renewable energy over the past decade. This paper provides a comprehensive review of the progress of renewable energy advancement in South Africa, examining the policies, initiatives, and achievements in various renewable energy sectors. This study explores the country’s transition from a heavily coal-dependent energy system to a diversified and sustainable energy mix. It analyses the growth of renewable energy technologies, such as wind power and solar photovoltaic (PV), highlighting the key milestones, challenges, and opportunities. Furthermore, this paper discusses the role of government support, regulatory frameworks, and private sector investments in driving renewable energy deployment in South Africa. Finally, it identifies the prospects and potential areas for further advancement in the renewable energy sector. This review aims to contribute to the understanding of South Africa’s renewable energy journey and provides valuable insights for policy-makers, researchers, and stakeholders involved in the sustainable energy transition.

This paper presents a mathematical model aimed at studying the global behaviour and optimal control strategies for Typhoid fever. The primary objective of this study is to identify the most effective control strategy that minimizes the spread of the disease. To achieve this, we calculate the effective and basic reproduction numbers and utilize them to investigate the existence and stability of the equilibria. Furthermore, we investigate the global impact of each model parameter on the variables using Latin Hypercube Sampling and Partial Rank Correlation Coefficient. The necessary conditions of the optimal control problem are analyzed using Pontryagin’s maximum principle, and the numerical values of the model parameters are estimated using the maximum likelihood estimator. The results indicate that the optimal use of vaccination for susceptible individuals, as well as the screening and treatment of asymptomatic infected individuals, have a significant impact on reducing the spread of the disease in endemic regions.

Education has been regarded as a major route to economic prosperity. Its potentials, if properly exploited, have the tendency to revolutionize a nation’s productivity, income, and development. [Objetive] In this work, a mathematical model was formulated, and an epidemiological modeling approach was explored to derive the necessary and sufficient conditions for agricultural and industrial transformation in Nigeria in terms of education. The use of mathematics to quantify such a phenomenon is relatively new. [Methodology] Ample mathematics theorems were employed to test for the existence, boundedness, and positivity of the model’s solutions which are basic features of a valid epidemiological model. The model was solved to derive the equilibrium points, and the analytic threshold that governed revolution in industry and agriculture in terms of education was derived. Stability and sensitivity analyses were conducted via the stability theory of nonlinear differential equations and normalized forward sensitivity index, respectively. Simulations were later conducted using the Maple software to validate the analytical results. [Results] A government expenditure of 25% on education with or without corruption did not make education functional. Also, an increase in expenditure on education to 65% but with corruption of more than 30% retarded functional education. In general, education became functional when government investment in education attained 60%, with corruption levels lower than 20%. [Conclusions] Both the analytical and numerical results linked agricultural transformation and industrial revolution through functional education to massive investment in education and victory over corruption.

Diabetes mellitus is a global health problem, escalating at a disturbing rate due to unbalanced lifestyles and some underlying health issues. In this work, a system of first-order linear ordinary differential equations as well as numerical simulations were employed to gain insight into the dynamics of the disease. The theoretical outcomeof the analysis was derived in terms of the model parameters while computer simulation was used to assess the behavior of the model in terms of the parameter values. Both the theoretical and numerical studies of the model revealed lifestyles and effective treatment as the parameters to be targeted for effective reduction in both diabetes prevalence and mortality. It is therefore concluded that diabetes prevalence and mortality reduction is a function of adjustment in unbalanced lifestyles as well as improvement in diabetes treatment.

Abstract The study investigates some biological indices and chemical compositions of Callinectes amnicola and their potential for reuse in the context of the circular economy paradigm. The total of 322 mixed-sex C. amnicola collected over a period of six months was examined. The morphometric and meristic characteristics were estimated for biometric assessment. The gonads were obtained from the female crabs for gonadosomatic indices. The shell was obtained using the hand removal technique by detaching it from the crab body. The edible and shell portions were processed separately and subjected to chemical analysis. Our findings showed that females had the highest sex ratio across the six months. The slope values (b) for both sexes exhibited negative allometric growth across all months since the slope values obtained were less than 3 (b

Abstract Background information The unprecedented depletion of the productive workforce has been majorly attributed to road traffic crashes (RTCs). The attendant consequences of this depletion have been found to constitute a serious global public health challenge, with the use of psychoactive substances among drivers implicated in every three of five motor vehicle accidents. Hence, this study assessed the pattern and explored the determinants of substance abuse among commercial bus drivers in Umuahia, Abia State. Methods A descriptive cross-sectional design was used for the study. Four hundred commercial bus drivers were recruited from selected motor parks in Abia-state, using a multistage sampling technique from October to December 2020. A pretested, interviewer-administered questionnaire was administered to obtain socio-demographics and information on substance abuse. Data were analyzed using IBM SPSS version 25; bivariate analysis was done using Chi-square. The level of significance was at 5%. Results The mean age of the respondents was 40.03 ± 10.50 years. The proportion of respondents who had ever abused a psychoactive substance was 74.6%. The most commonly abused substances among drivers include alcohol (51%), cigarettes (27%), and alcoholic herbal mixtures (16%). The study participants had poor knowledge (54.5%) and poor perception (63.2%) about psychoactive substance abuse. Among the factors found to be significantly associated with substance abuse among respondents were ethnicity (p = 0.002), religion (p = 0.009) and monthly income (p = 0.013) of the respondents, poor knowledge (p

Recent interest in using natural fibers as fillers in various composite materials has sparked the desire of researchers and manufacturing businesses to develop natural fiber composites that may be used as alternative, cheap, sustainable and ecoefficient materials in automobiles. In that respect, the present study was tailored towards harnessing the attractive properties of jute fiber and Tetracarpidium conophorum (African walnut shell particulate) along with thermoplastic “polypropylene”, to develop composite materials with improved properties which can be adopted in automobiles. Alkaline treated African walnut shell particulate (AWSP) and jute fiber were added to polypropylene at a proportion of 2–8 wt% and 5–30 wt% respectively in the presence of 2 wt% maleated polypropylene. Samples were developed at 170 °C and 0.25 kPa pressure, and their mechanical, wear and flow properties were assessed. The result revealed that an improvement of 51.98 %, 42.26 %, 55.23 %, 30.95 %, 54.36 % for flexural strength, tensile strength, impact strength, compressive strength, and hardness respectively. However, a reduction of 380. 48 % and 78.98 % were observed for wear loss and melt flow. The Taguchi Optimization revealed that 2 wt% AWSP and 20 wt% jute fiber addition gave the optimum mechanical performance. The research proved that the hybridization of jute fiber and AWSP resulted in improved polypropylene composites which can be adopted for automobile applications.

The use of ashes derived from various waste sources as supplements to synthesized ceramic reinforcement in metal matrices has been established. However, studies involving a combination of particulates from three different sources are rare. In a bid to further knowledge in this aspect of research and develop a green aluminium composite for automobile applications, the present investigation studied the implication of adding palm kernel shell ash (PKA), rice husk ash (RHA), and waste steel particles (STP) to the morphology and strength behaviour of Al-6061-T6 alloy. The experimental design was undertaken via the Box–Behnken design (BBD) of the response surface method. A 4% STP at a constant dose was mixed with PKA and RHA at varying proportions and stirring temperatures according to the BBD. The experimental outcome revealed that the responses were greatly influenced by microstructural evolution. From the surface plots, 2–4% RHA and PKA enhanced tensile and flexural strengths, while 4–6% led to a decline in strength. Meanwhile, 2–6% of the particles are favourable to the enhancement of tensile and compressive strengths and moduli. Temperatures between 700 and 800 °C favored response improvement, whereas temperatures between 800 and 900 °C were detrimental to responses. Developed regression models for the responses were validated to be good representations of the experimental outcomes. The optimum mix was obtained at 4.81% PKA, 5.41% RHA, and a stirring temperature of 803 °C. The validation experiment conducted portrayed reliable responses with

The year 2020 arrives with COVID-19. The pandemic poses a formidable threat to human existence at onset but is fought with various measures of which quarantine and hospitalization play a key role. In this article, a COVID-19 transmission mathematical model is developed to assess how quarantine and hospitalization aid improvement in the recovery of both asymptomatic and symptomatic infectious individuals during the toughest period of the pandemic in the year 2020. The basic properties of the model in terms of positivity and boundedness of solutions are discussed based on some ample mathematics theorems. The control reproductive ratio is derived using the next generation matrix approach and the local and global stabilities are investigated via stability theory of differential equations, which depend on the size of the derived control reproductive ratio. Numerical simulation is performed to confirm the analytical results. Findings from the simulation show that quarantine and hospitalization are helpful in averting imminent destruction posed by the pandemic in the years 2020 and early 2021 by reducing both COVID-19 transmission and mortality.

Recent studies are evaluating the use of particulates fabricated from agro-based residues as reinforcement for enhancing the properties of aluminium alloys. This report focuses on the optimization approach and modeling of responses for future prediction, which are absent from the majority of studies involving particle reinforcement of an aluminum matrix. Herein, palm kernel shell ash (PKA) and rice husk ash (RHA) were incorporated with 4 wt% of WSD and used as fillers in the Aluminium-6061 matrix at variable proportions. The response surface approach was utilized in the experiment design, modeling, and outcome optimization. The independent variables are the proportions of PKA and RHA and stir casting temperature. Yield, ultimate tensile, impact strength, elastic modulus, and fracture toughness are examined as response parameters. The results demonstrated that the microstructural property played a significant role in the responses. Incorporating PKA and RHA into the Al-6061 matrix improved the response parameters. Temperatures in the range of 700 and 800 °C enhanced the property parameters, even though temperatures within 800 and 900 °C caused a decline in response. The dependence of the responses on the pattern between property variables was revealed by surface and contour plots. The development of models for predicting responses. Optimal conditions were reached at 4.03% PKA, 5.12% RHA, and 787 °C, with an error

The objective of this paper is to propose two new hybrid root finding algorithms for solving transcendental equations. The proposed algorithms are based on the well-known root finding methods namely the Halley's method, regula-falsi method and exponential method. We show using numerical examples that the proposed algorithms converge faster than other related methods. The first hybrid algorithm consists of regula-falsi method and exponential method (RF-EXP). In the second hybrid algorithm, we use regula falsi method and Halley's method (RF-Halley). Several numerical examples are presented to illustrate the proposed algorithms, and comparison of these algorithms with other existing methods are presented to show the efficiency and accuracy. The implementation of the proposed algorithms is presented in Microsoft Excel (MS Excel) and the mathematical software tool Maple.

Interpreting geophysical data requires solving nonlinear optimization problem(s) in inversion. Analytical methods such as least-square have some intrinsic limitations, which include slow convergence and dimensionality, making heuristic-based swarm intelligence a better alternative. Large-scale nonlinear optimization problems in inversion can be solved effectively using a technique within the swarm intelligence family called Particle Swarm Optimization (PSO). This study evaluates the inversion of geoelectrical resistivity data with global particle swarm optimization (GPSO). We attempted to invert field vertical electrical sounding data for a multi-layered 1-D earth model using the developed particle swarm optimization algorithm. The result of the PSO-interpreted VES data was compared with that of the least square inversion result from Winresist 1.0. According to the PSO-interpreted VES results, satisfactory solutions may be attained with a swarm of 200 or fewer particles, and convergence can be reached in fewer than 100 iterations. The GPSO inversion approach has a maximum capacity of 100 iterations, more than the least square inversion algorithm of the Winresist, which has a maximum capacity of 30 iterations. The misfit error of GPSO inversion is 6.14×10−7, much lower than that of the least square inversion of 4.0. The GPSO inversion model has lower and upper limit values of the geoelectric layer parameters model to fit the true model better. The limitations of the developed PSO inversion scheme include a slower execution time of the inversion procedures than the least-square inversion. There is a need for a priori knowledge of the number of layers from borehole reports in the study area. The PSO inversion scheme, however, estimates inverted models closer to the true solutions with greater accuracy than the least-square inversion scheme.

Broken brown rice is usually categorised as raw material with low market value while watermelon seeds are discarded as waste. Therefore, this study aimed to develop brown rice-watermelon seeds extruded snacks by evaluating the effects of extrusion conditions (feed moisture content (12–16%), exit barrel temperature (120 -140ºC), and barrel screw speed (300 rpm - 420 rpm)) on its composition, bioactive constituents, and glycemic index. Polynomial regression was used to model the composition, bioactive constituents, and glycemic index while response optimizer was used to optimise the protein content of the extruded snacks. At a mixing ratio of 90% brown rice flour and 10% watermelon seeds powder, the effect of extrusion conditions on the moisture content of the extruded snacks ranged from 3.03 to 4.57%, protein content (11.24 to 16.20%), crude fat (0.77 to 1.08%), crude fibre (2.07 to 2.77%), ash (2.05 to 2.63%) and carbohydrate (73.66 to 79.36%). The total phenolic content of the extruded snacks ranged between 8.14 and 10.15 mg GAE/g, total flavonoid content (1.8 and 2.11 mg QE/100 g), DPPH radical scavenging activity (10.05% and 14.22%), and Glycemic index (60.00 and 67.24). The regression models showed the adequacy to predict the composition, bioactive constitutes and glycemic index of the snacks while the optimum conditions gave extruded snacks with 17.71% protein content. The glycemic index of the extruded snacks is intermediate. Conclusively, the developed extruded snacks served as an avenue to exploit the usage of underutilized broken brown rice and watermelon seeds to produce nutrient-rich value-added extruded product.

Abstract Towards developing a polymeric matrix characterized by high strength to cost ratio, polypropylene (PP) was hybridized with low-cost particulate snail shell (PSS) and kenaf fiber (KF) via compression moulding at 180 °C and 0.2 MPa. The developed composites were grouped into three and labeled as mix 2, 4, and 10. Each group entailed the blend of 5, 10, 20, and 30 wt% KF with 2, 4, 10 wt% PSS respectively. From the results, it is observed that the hardness value was enhanced by the blend of 5 to 30 wt% KF and 2, 4, and 10 wt% PSS. However, 2 wt% PSS mix with 5 to 30 wt% KF resulted in progressive improvement in impact, compressive, flexural, and tensile strengths values. The 4 wt% PSS yielded consecutive increase in impact, compressive and flexural strength when combined with 5 and 10 wt% KF. However, it was observed that subsequent addition of 20 and 30 wt% KF led to a marginal reduction in the strength values. The tensile strength attained optimum value when 4 wt% PSS was commixed with 30 wt% KF. Conversely, the combinations of 10 wt% PSS with 5, 10, 20, and 30 wt% KF had no significant improvement to the mechanical properties of PSS/KF-bio-PP composite (except for hardness) siring strength decrease. Taguchi optimization revealed that the collage of 4 wt% PSS and 10 wt% KF presented optimum mix for hybrid bio-PP composite.

The rabies virus usually transmits either from animal to man or animal to animal or human to human as the case may be but the major transmitters of the virus are dogs globally. In this work, an integer order SEIR epidemic model was formulated to quantify and give an insight into the spread of rabies within the dog population. The integer order model was studied qualitatively and its results were obtained theoretically before it was modified into the non-integer order counterpart to cater for the data agreement deficiency associated with the integer order epidemic models. As rabies prevalence varies from localities to localities, the theoretical outcomes of the analysis could reveal the genuine picture of rabies dynamics in a particular locality if the actual rabies data of the locality is available.

For additional strength increase, 5, 10, and 15% TiC was added to the quinary CoCrFeMnNi high entropy alloy (HEA) at laser powers of 100, 400, and 700 watts while selective laser melting method was engaged in the fabrication. Microstructure, porosity, density, yield and tensile strengths, elongation, and microhardness are among the parameters analyzed. As TiC appreciated from 5 to 15%, the microstructure revealed that the particles were dispersed within the matrix. Also, the addition ensued grain size refinement with increasing particle proportion. Meanwhile, 15% caused an increase in porosity, 0–10% TiC dosage and 100–700 watts laser power led to a decrease in porosity. The same dosage of TiC resulted in a linear improvement in microhardness even as 0–15% TiC ensued gradual reductions in density and elongation Increases in laser power between 100 and 700 watts were detrimental to elongation but beneficial to density and microhardness enhancement. For composites produced at 100–700 watts laser power, 5–10% TiC increased yield and ultimate tensile strengths whereas 15% TiC decreased strength. For every TiC addition, laser power 100 - 400 watts generally showed an improvement in strength and microhardness, whereas 700 watts depicted a decrease in strength and microhardness. The optimal input combination was predicted by the developed models to be 15% TiC and 504 watts laser power. Since the deviation between anticipated outcome and validation values for the responses is

The interannual El Niño-Southern Oscillation (ENSO) and the Boreal Summer Intraseasonal Oscillation (BSISO) strongly modulate sub-seasonal to seasonal rainfall variability, leading to dry extreme rainfall events (DEREs) over Northeast (NE) Thailand. In this study, the ability of climate models to simulate the ENSO-BSISO-induced DEREs and associated synoptic features are evaluated using self-organizing maps. Observed DEREs occur most frequently during ENSO Neutral and La Niña conditions, when enhanced convection is located over central India and the Bay of Bengal. The intensity of observed DEREs are strengthened during El Niño when enhanced convection is observed over the western Pacific region. The climate models exhibit a diverse frequency of DEREs during ENSO phases, with some models showing better skill than others. On intraseasonal time scales, observed DEREs are favored when enhanced BSISO convection in phases 3–5 is located over the Bay of Bengal and the western Pacific region. Five models out of the 19 examined capture the observed pattern during BSISO phases 4 and 5, while only three models capture the BSISO phase 3 behavior. Composite maps of observed DEREs during the combined BSISO and ENSO conditions indicate that BSISO convection increases (decreases) DERE frequency during El Niño and Neutral (La Niña) phase(s). Climate models can simulate the occurrence of dry events associated with the combined BSISO and ENSO phases, but they do so in different BSISO phases.

BackgroundAsymptomatic malaria infections have received less attention than symptomatic malaria infections in major studies. Few epidemiological studies on asymptomatic malaria infections have often focused on pregnant women and children under-five years of age as the most vulnerable groups. However, there is limitation on data regarding asymptomatic infections among the old adult populations, particularly in the study area. Therefore, this study determined the prevalence of asymptomatic malaria infection by microscopy and its determinants among residents of Ido- Ekiti, Southwestern Nigeria.MethodsA hospital-based cross-sectional study was conducted between July and September 2021 among 232 consenting apparently healthy individuals aged 40 years and above who were recruited during a free health screening program using a standardised interviewer-administered questionnaire. The questionnaire sought information on respondents' socio-demographics, presence and types of co-morbidity, and the prevention methods being adopted against malaria infection. Venous blood samples were collected and processed for asymptomatic infections using Giemsa-stained blood smear microscopy. Data were analysed using SPSS version 21. Multivariate logistic regression was used to identify factors associated with asymptomatic infections.ResultsOf the total 232 respondents, 19.0% (48/232) were confirmed to be infected with Plasmodium falciparum (95% confidence interval (CI): 14.1% - 24.6%). Lack of formal education (Adjusted odds ratio (AOR): 5.298, 95% (CI): 2.184-13.997), being diabetic (AOR: 4.681, 95% CI: 1.669-16.105), and not sleeping under Long Lasting Insecticide Net (LLINs) (AOR: 4.594, 95% CI: 1.194-14.091), were the determinants of asymptomatic Plasmodium falciparum infection.ConclusionThe prevalence of asymptomatic Plasmodium falciparum was 19%. Lack of formal education, being diabetic, and not sleeping under LLINs were the determinants of asymptomatic infections.

Objectives: Cancer and diabetes are two diseases known to bypass socio-demographic segregation, hence the increased focus on their molecular mechanism for therapeutic intervention. Their connection was unclear using traditional biomedical methods until omics technology shows how specific aetiological factors seem to contribute to their initiation and progression. The Genome-wide association study (GWAS) was considered a ground-breaking tool which highlights the roles specific genetic variations like single nucleotide polymorphisms (SNPs) play in the surveillance, diagnosis and treatment of diseases like cancer and diabetes. Methods: While some common missense SNP variants have been investigated and reported, we used bioinformatics tools to predict all known conditions previously reported to link pancreatic cancer and diabetes mellitus subtypes based on metabolism and cell proliferation for their structural and functional significance. The variants were limited to five known genes: epigenetic regulators (EZH2, SIRT1) and pan-peroxisome proliferator-activated receptors (PPARA, PPARD, PPARG). Results: The class filter shows that obesity is a common risk factor. In the result projected, six missense variant rs1232898090, rs1800206, rs1801282, rs1805192 rs121909244 and rs777334819 were discovered to be associated with fifteen different deleterious amino acid point change in the PPARA and PPARG genes. Likewise, the phyre 2 and SwissModel homology modelling analysis revealed proteins with an identifier; 2FVJ, 2P54, 3DZU, 3E00, 4BCR and 6FZG to be common with high alignment coverage and percentage identity for the missense SNP variants. Conclusion: Overall, this analysis provides important insights into how genetic variants can be selected, screened and proposed to inform target selection for other downstream insilico and experimental validation, significant in developing new therapeutics for cancer and diabetes.

Abstract Stir casting is a common metallurgical route in the casting of aluminum composites. Series of work done in this aspect considered the development of the composites with fixed stir casting parameters without applying an optimization approach. These parameters affect the microstructure and performance of the composites. The study is focused on the optimization of the stir casting parameters in the production of Al 7075 reinforced with TiO2 microparticles for performance improvement. Three stir casting parameters of stirring temperature, speed, and time were varied and optimized using the central composite design technique of the response surface method. Properties evaluated were ultimate tensile strength, hardness, impact strength, elastic modulus, and compressive strength. ANOVA results showed that the three stir casting parameters had a significant impact on the property responses. Five quadratic models were established for the properties linking them to the factors. The models were confirmed to be statistically significant at a confidence level of 95% and variations were observed to be

Conventional highway design approaches have primarily focused on the use of guidelines in the design of highways. These design guidelines provide nominal safety where conservative percentile values of the design inputs are used to account for the uncertainty associated with the inputs. Reliability-based analysis (RBA) been one of the elements of reliability, availability, maintainability, and safety (RAMS) has been identified as an effective method to account for the uncertainty in the design input and to assess the risk related to a particular design. RBA approaches have effectively been used for certain purposes in other disciplines. In highway geometric design literature, these methods were also investigated and showed promise. Given the compelling importance of RBA in highway design, this paper provides a systematic analysis and evaluation of RBA applications for ten highway geometric elements: stopping sight distance, passing sight distance, intersection sight distance, horizontal curve design, vertical curve design, number of freeway lanes, highway grade length, truck escape ramp, and design guide calibration. The review consists of four parts: the concept of RAMS, background on reliability theories, applications in highway geometric design, and guidelines for the use of reliability analysis. The literature review revealed that the application of reliability-based analysis in highway geometric design leads to significant improvements in traffic safety. It is our hope that this paper will serve as a source of information on RBA for highway designers and practitioners, promoting its development and application in highway geometric design.