Hybrid nanofluids have several potential applications in various industries, including electronics cooling, automotive cooling systems, aerospace engineering, and biomedical applications. The primary goal of the study is to provide more information about the characteristics of a steady and incompressible stream of a hybrid nanofluid flowing over a thin, inclined needle. This fluid consists of two types of nanoparticles: non-magnetic nanoparticles (aluminium oxide) and magnetic nanoparticles (ferrous oxide). The base fluid for this nanofluid is a mixture of water and ethylene glycol in a 50:50 ratio. The effects of inclined magnetic fields and joule heating on the hybrid nanofluid flow are considered. The Runge-Kutta fourth-order method is used to numerically solve the partial differential equations and governing equations, which are then converted into ordinary differential equations using similarity transformations. Natural convection refers to the fluid flow that arises due to buoyancy forces caused by temperature differences in a fluid. In the context of an inclined needle, the shape and orientation of the needle have significantly affected the flow patterns and heat transfer characteristics of the nanofluid. These analyses protest that raising the magnetic parameter results in an increase in the hybrid nanofluid thermal profile under slip circumstances. Utilizing the potential of hybrid nanofluids in a variety of technical applications, such as energy systems, biomedicine, and thermal management, requires an understanding of and ability to manipulate these effects.

The study evaluated 33 accessions of groundnut in the field, consisting of 23 landraces from Nasarawa communities in Nigeria and 10 inbred lines. Assessment entailed the determination of plant survivorship, yield related parameters and pathological indices while genetic diversity study was undertaken using SSR and RAPD molecular markers. Data analysis was done on the Minitab 17.0 software. Significant variability was noted in all traits except in pod sizes, seed sizes and % infected seeds. About 33.3% of the accessions had a survival rate of ≥ 70.0% where 9/10 Inbred lines were found with overall yield (kg/ha) ranging from 4.0 ± 1.6 in Akwashiki-Doma to 516.8 ± 46.9 kg/ha in Samnut 24 × ICGV–91328. Five accessions (15.5%) had pathological indices of zero indicating no traces of any disease of any type and they included one landrace called Agric-Dazhogwa and four Inbred lines: Samnut 25 × ICGV–91317, Samnut 26 × ICGV–19324, Samnut 26 × ICGV–91328 and Samnut 26 × ICGV–91319. Coefficients of yield determination R2 by survivorship and pathological index were 50.6% and 15%, respectively. A fit model was established (Yield in kg/ha = –146 − 7.94 × Pi + 5.88 × S). Susceptibility to diseases depends on the type of variety (χ2(32) = 127.67, P = 0.00). Yield was significantly affected by BNR@30 (F = 5.47, P = 0.025, P < 0.05) and DSV@60*RUST@60 interaction effect (F = 4.39, P = 0.044, P < 0.05). The similarity coefficient ranged from 28.57 to 100 in plant morphology. Four varieties had no amplified bands with SSR primers whereas amplified bands were present only in four landraces accessions using the RAPD primer. The dendrogram generated by molecular data gave three groups where genetic similarity ranged from 41.4 to 100.0. The Inbred lines were noted for their high survivorship, good yield and disease resistance. Samnut 24 × ICGV–91328, an inbred line, had the highest yield but was susceptible to diseases. Among the landraces, Agric-Musha, Bomboyi-Dugu and Agric-Dazhogwa were selected for high survivorship and disease resistance. The selected inbred lines and landraces are valuable genetic resources that may harbour useful traits for breeding and they should be presented to the growers based on their unique agronomic values. The highest yielding inbred lines should be improved for resistance to late leaf spot diseases while the outstanding landraces should be improved for yield.

The silver nanoparticles (AgNPs) exhibit unique and tunable plasmonic properties. The size and shape of these particles can manipulate their localized surface plasmon resonance (LSPR) property and their response to the local environment. The LSPR property of nanoparticles is exploited by their optical, chemical, and biological sensing. This is an interdisciplinary area that involves chemistry, biology, and materials science. In this paper, a polymer system is used with the optimization technique of blending two polymers. The two polymer composites polystyrene/poly (4-vinylpyridine) (PS/P4VP) (50:50) and (75:25) were used as found suitable by their previous morphological studies. The results of 50, 95, and 50, 150 nm thicknesses of silver nanoparticles deposited on PS/P4VP (50:50) and (75:25) were explored to observe their optical sensitivity. The nature of the polymer composite embedded with silver nanoparticles affects the size of the nanoparticle and its distribution in the matrix. The polymer composites used are found to have a uniform distribution of nanoparticles of various sizes. The optical properties of Ag nanoparticles embedded in suitable polymer composites for the development of the latest plasmonic applications, owing to their unique properties, were explored. The sensing capability of a particular polymer composite is found to depend on the size of the nanoparticle embedded in it. The optimum result has been found for silver nanoparticles of 150 nm thickness deposited on PS/P4VP (75:25).

This study informs the academic and policy debate on the policy effectiveness of exchange rate interventions on exchange rate levels and volatility. Using a constructed data set comprising daily data on exchange rates, monetary policy fundamentals, exchange rate intervention dates and magnitudes of those interventions as well as financial news speculation of such interventions, we empirically estimate the policy effectiveness of Bank of Japan interventions in the exchange rate over the 12-year period between 2010 and 2022. This allows us to investigate the policy effectiveness of a variety of exchange rate interventions, or news of exchange rate interventions, across different time-horizons. We find that policy interventions in the yen exchange rate are more effective over short-horizons than long-horizons, more effective when the policy objective is a competitive devaluation of the yen rather than a revaluation, and more effective at influencing the level of the yen against major world currencies other than the US dollar. In fact, for the yen-dollar rate, we find that policy interventions may have the unintended consequences of weakening the yen (when the policy intention is to strengthen it) and increasing volatility in the yen-dollar exchange rate.

The significance of infrastructure development as a determinant of economic growth has been widely studied by economists and policymakers. Though there is no much debate about the importance of infrastructure on growth, the extent to which infrastructure affects growth in the long run is often debated among researchers. This paper aims to examine the effect of infrastructure development on economic growth in ten sub-Saharan Africa. This study uses balanced panel data of ten African countries, particularly sub-Saharan Africa over the period of 2010–2020 by analyzing a set of independent variables with relation to the dependent, which is GDP per capita. The study has found that water supply & sanitation index and electricity index have positive and significant relationship with economic growth, while transport index and Information & Communications (ICT) have negative relationship with economic growth in these countries.

National governments and academic higher education institutions continue to realign human resource development (HRD) strategies to address the gaps in HRD mandate. This study will investigate new and recalibrated skills that higher institutions (HEIs) professionals and the labor force produce to reconfigure curriculum development in tertiary education. The study extracts narrative from 6 curriculum developers, 3 HRD heads and h3 manpower organizations on the labor landscapes from different local and multinational industries from entry-level to mid-career ranges through case scenario-based interviews and focus group discussions to determine the skills around motivation, innovativeness, and adaptability and subsequently integrate strategic initiatives to reconfigure the compatibility of these skills from higher education institutions to post-pandemic industries. The findings reveal skills that can be managed at the individual level, e.g., self-motivation and adaptability as well as the need to emerge from the technological pressures by adapting to organizational and clientele demands. These human resource traits become the mantra of surviving and progressing in a landscape shaped by the pre- and post-pandemic setting and become the basis of HEI programs to match the needs of the labor force and the industries.