Computing and Applied Sciences Impact

Isolation and characterisation of hydrocarbon-degrading microorganisms from soils contaminated with used engine oil

2026-03-04T18:13:02+00:00

Soil contamination with used engine oil is a widespread environmental issue, posing risks to ecosystems and human health. The high levels of noxious compounds, such as trace elements and organic compounds that are composed of polycyclic aromatic rings (PAHs), immediately in used engine oil can disrupt various ecosystem reformations, like biogeochemical cycling, carbon sequestration, and the degradation of humus. Soil samples were collected from mechanic workshops where there are traces of hydrocarbons, and microorganisms were isolated using enrichment techniques with used engine oil as the sole carbon source, and the isolates were subjected to some biochemical tests. The results obtained revealed that the mean count of heterotrophic bacteria ranged from 2.0 x10⁸± 0.1 to 1.1 x 10⁸± 0.2 CFU/g while the mean count of hydrocarbon-utilising bacteria varied from 5.4 x 10⁷± 0.07 to 1.3 x 10⁷± 0.05 CFU/g, and the fungal populations ranged from 2.9 x 10⁷± 0.4 CFU/g to 1.0 x 10⁷± 0.1 CFU/g. A total of 12 hydrocarbon-degrading bacterial species and 16 filamentous fungi were isolated, characterized and identified. Some of the characterised isolates were Alcaligenes aquatilis > Pseudomonas sp. > Acinetobacter >Bacillus subtilis > Corynebacterium sp., and Flavobacterium sp. These oil-degrading organisms revealed hydrocarbon-degrading potential and bioremediation of the oil-contaminated sites.

Analytical and numerical study of the time-fractional Schrödinger equation for a free particle

2026-06-01T16:36:40+00:00

This study investigates the time-fractional Schrödinger equation (TFSE) for a free particle using the Caputo fractional derivative. The model extends the classical Schrödinger equation by incorporating memory effects through a non-integer order time derivative. By applying the Fourier transform method, an explicit solution is derived in terms of the Mittag–Leffler function, which generalizes the classical exponential evolution. The analysis reveals that the resulting dynamics are non-unitary, leading to a time-dependent total probability that deviates from the conservation property of standard quantum mechanics. Numerical illustrations demonstrate the influence of the fractional order ν on wave packet evolution and probability behavior. The results highlight the role of fractional calculus in modeling non-Markovian quantum systems and provide insight into the transition from fractional to classical dynamics as v→1.

An operator–theoretic analysis of the Adomian–Neumann series for the forced damped wave equation

2026-06-04T21:46:18+00:00

We establish an operator–theoretic framework for the Adomian–Neumann series applied to the forced damped wave equation with homogeneous Dirichlet boundary conditions in this paper. The second–order time derivative being inverted gives rise to a Volterra integral equation in time, by means of showing the Dirichlet Laplacian. Using this formulation, we demonstrate that the Adomian decomposition recursion is equivalent to the Neumann series expansion of the corresponding Volterra operator. As a result, the solution can be represented in terms of iterated time integrals and thus adopts a resolvent-type representation. In appropriate Sobolev spaces, we prove a convergence theorem, where factorial decay of successive terms arises naturally from repeated time integration. Furthermore, the resulting expansion is shown to reconstruct the Taylor series of the solution with respect to time. A Fourier mode example is presented to illustrate the analytical results.

Construction of semisymmetric entropic quasigroups

2026-06-20T18:26:47+00:00

Elliptic curves are non-singular cubic plane-curves over a field containing at least one point and naturally form a group, where the associative property is based on Cayley-Bacharach theorem. A semisymmetric entropic (medial) quasigroup (SEQ) is a non-commutative generalization of this principle. This is a magma satisfying the pair of identities: and. Every SEQ is associated (not necessarily uniquely) with an Abelian group. In this paper, we give methods for constructing SEQs based on their corresponding Abelian groups. In particular, we show that SEQs are central quasigroups.

Leveraging artificial intelligence and big data analytics for poverty alleviation and social development: a review

2026-09-15T22:02:10+00:00

Poverty reduction remains one of the most pressing global development challenges, requiring innovative approaches for identifying vulnerable populations, targeting interventions, and monitoring outcomes. Rapid advances in Artificial Intelligence (AI), Machine Learning (ML), and Big Data Analytics (BDA) have created new opportunities to complement conventional poverty assessment methods, which often rely on costly, infrequent household surveys that are susceptible to measurement errors and reporting biases. AI-driven approaches leverage high-resolution satellite imagery, mobile phone metadata, digital financial transactions, administrative records, and social media data to generate timely and spatially detailed insights into poverty dynamics. This study presents a systematic literature review of publications from 2014 to 2024, supplemented by recent policy reports and selected case studies, to examine the application of AI and BDA in poverty alleviation across finance, agriculture, healthcare, education, and social protection. The review further evaluates ethical, governance, and institutional issues through the World Bank's 4Cs AI readiness framework, comprising connectivity, compute, context, and competency. Findings indicate that AI and BDA have significant potential to enhance poverty measurement, improve service delivery, and support evidence-based policymaking. However, their long-term effectiveness depends on responsible deployment, inclusive governance, robust data protection, investment in digital infrastructure and human capacity, and locally adaptive implementation strategies. Unlike previous sector-specific reviews, this study provides a comprehensive cross-sectoral synthesis integrating technological, ethical, governance, and developmental perspectives for Low- and Middle-Income Countries (LMICs).

Effect of microplastic distribution on diversity of microbenthic fauna of Sub-Saharan Africa tropical mangrove ecosystems

2026-10-28T02:22:13+00:00

Microplastic (MP) pollution poses a growing threat to mangrove ecosystems, particularly in tropical regions where ecological and socioeconomic dependencies are high. This study investigated MP contamination in sediment, water, and microbenthic fauna across selected mangrove sites (Ikpa River Basin and Qua Iboe River Estuary) in Sub-Saharan Africa. Using standardized sampling and spectroscopic techniques (μFTIR and SEM), MPs were detected in all sample types, with higher concentrations near urban and industrial zones. Polymer analysis identified polyethylene, polypropylene, and polystyrene as dominant types. A strong negative correlation (r = -0.72, p < 0.05) was found between MP load and the Shannon-Wiener diversity index (H′) of microbenthic fauna. Sites with elevated MP levels showed reduced species richness and lacked sensitive taxa such as polychaetes and amphipods. We observed MP bioaccumulation and histopathological effects, including gut obstruction and epithelial damage, in Capitella capitata and Hyalella spp. These findings highlight the urgent need for pollution control and conservation strategies in African mangrove habitats.