Advances in Research

A Boundary-Adapted Crank–Nicolson-Induced Mamadu–Njoseh Basis Functions for the Solution of Parabolic Partial Differential Equations

2026-10-15T05:16:25+00:00

A boundary-adapted Crank–Nicolson-induced Mamadu–Njoseh basis-functions (CN-MNBF) framework is developed for the numerical solution of one-dimensional parabolic partial differential equations. The method combines a weighted Mamadu–Njoseh polynomial approximation in space with Crank–Nicolson time discretization. To enforce homogeneous Dirichlet conditions exactly, the numerical implementation uses boundary-adapted trial functions obtained by multiplying each Mamadu–Njoseh polynomial (MNP) by the boundary factor (1 - x²) on the transformed interval [-1,1]. The resulting mass and spatial-operator matrices are assembled directly in this constrained space. For the diffusion problem, a weighted energy argument establishes dissipativity and the associated Crank–Nicolson update is contractive in the mass-matrix norm. The fully discrete error splits into spatial approximation and temporal discretization components, with the temporal component second-order under standard smoothness assumptions. Numerical illustrations show decreasing spatial error and, for a sufficiently rich spatial approximation, approximately second-order temporal convergence. We interpret the induced basis as an operator-adapted representation of the Crank–Nicolson evolution rather than a new finite-dimensional spatial span.

Automated Genetic Algorithm-Based Impedance Bandwidth Optimization of a Triangular U-Slotted Microstrip Patch Antenna Using Python and HFSS

2026-10-15T05:28:12+00:00

Microstrip patch antenna optimisation using full-wave electromagnetic simulations can become computationally expensive when multiple geometrical parameters are involved. This paper presents a Python–PyAEDT-based automated optimisation framework for enhancing the impedance bandwidth of a compact triangular U-slotted microstrip patch antenna. The antenna was initially designed for operation around 5 GHz on a 40 mm × 40 mm substrate and was subsequently modified to a compact 24 mm × 30 mm FR-4 substrate. The final configuration incorporates additional triangular and circular patch elements, a U-shaped slot, and a modified ground structure. Following the initial antenna modelling and parameterisation in Ansys High Frequency Structure Simulator (HFSS), the framework automatically updates six geometrical parameters, executes electromagnetic simulations, extracts the reflection coefficient (S₁₁), and calculates the continuous −10 dB impedance bandwidth. Genetic Algorithm (GA)-based optimisation and script-based random search were each evaluated using 100 HFSS simulations. The GA achieved an impedance bandwidth of 2357.65 MHz over approximately 3.202–5.559 GHz, with a minimum S₁₁ of −24.128 dB. In comparison, random search achieved a bandwidth of 2260.37 MHz over approximately 3.459–5.720 GHz, with a minimum S₁₁ of −25.852 dB. The GA-based solution provided an impedance bandwidth 4.30% greater than that of the random-search solution in the recorded runs, whereas random search produced a more negative minimum S₁₁. The recorded total wall-clock times were 32.42 minutes for GA and 50.34 minutes for random search. These results demonstrate the feasibility of automating antenna optimisation and comparing alternative search strategies under an equal simulation budget. However, because each method was evaluated in a single run and employed a different candidate-selection criterion, repeated trials are required to establish the robustness of the observed performance difference.

Assessment of Groundwater Potential and Artificial Recharge Zones Using GIS and Remote Sensing in Kabul City, Afghanistan

2026-10-19T19:00:19+00:00

Background: Groundwater is the primary source of water supply in Kabul City, Afghanistan, but rapid population growth, unplanned urbanization, excessive groundwater abstraction, and climate variability have contributed to declining groundwater levels. Despite increasing groundwater stress, spatially explicit information on groundwater potential and suitable artificial recharge areas remains limited, creating a need for integrated and cost-effective groundwater assessment approaches.

Objective: This study aimed to assess the spatial distribution of groundwater potential and identify suitable areas for artificial groundwater recharge in Kabul City using Geographic Information Systems (GIS) and Remote Sensing (RS) techniques.

Methods: An integrated GIS–RS framework was applied using thematic layers representing major hydro-environmental factors, including topography, slope, drainage density, geology, lithology, soil characteristics, land use/land cover (LULC), river networks, and surface water bodies. The thematic layers were standardised and assigned appropriate weights before being integrated through a GIS-based weighted overlay analysis to delineate groundwater potential and artificial recharge suitability zones.

Results: The groundwater potential assessment revealed considerable spatial variation across Kabul City and classified the study area into three categories: Good, Moderate, and Low groundwater potential zones. A substantial proportion of the study area was classified as a Good potential zone, indicating favourable conditions for groundwater recharge and storage. These areas were generally associated with gentle slopes, lower elevations, permeable geological formations, suitable soil characteristics, and relatively low drainage density. Moderate-potential areas showed intermediate recharge and groundwater occurrence conditions, while Low-potential areas were mainly associated with mountainous terrain, steep slopes, and densely urbanized areas characterised by increased surface runoff and limited infiltration.

Conclusion: The findings demonstrate that groundwater occurrence in Kabul City is controlled by the combined effects of topographic, geological, hydrological, soil, and land-use characteristics. The integrated GIS–RS and weighted overlay approach provides an efficient, reliable, and cost-effective tool for groundwater potential assessment in data-limited environments. The resulting groundwater potential and artificial recharge suitability maps provide practical scientific support for prioritizing recharge zones, regulating groundwater abstraction, planning groundwater development, and implementing sustainable groundwater conservation strategies in Kabul City. The methodology can also be adapted for groundwater-stressed and semi-arid regions elsewhere in Afghanistan.

Drivers of Sustainable Procurement Practices and Their Effect on Organisational Performance in the Northern Region of Ghana

2026-10-23T08:10:55+00:00

Sustainable procurement integrates economic, environmental and social considerations into purchasing decisions and may contribute to organisational performance. This study examined the drivers of sustainable procurement practices and their relationship with organisational performance among selected public-sector organisations in the Tamale Metropolis of Ghana. It focused on organisational and external factors, including management support, funding, supplier availability and relationships, environmental regulation, government enforcement, supplier resistance, expertise and training. A quantitative survey approach was used, with data collected through a structured questionnaire and analysed using descriptive statistics and regression analysis. The findings indicated that sustainable procurement practices were positively associated with organisational performance. The overall regression model showed that sustainable procurement practices explained 73.1% of the variance in organisational performance. Among the dimensions examined, green purchasing, ethical sourcing and supplier involvement accounted for 57.5%, 49.0% and 61.5% of the variance in organisational performance, respectively. Respondents also identified adequate funding, lower implementation costs, access to sustainable suppliers, appropriate environmental regulation, strong supplier relationships, effective government regulation and enforcement, top-management support, and expertise and training as relevant implementation drivers. The study indicates that effective sustainable procurement depends on the interaction of internal organisational capacity and external institutional conditions and that stronger implementation is associated with improved organisational outcomes within the study setting.

Thermal Management, Packaging, and Electro-thermal Co-design of Wide- and Ultra-Wide-Bandgap Power Devices

2026-10-14T11:26:40+00:00

Background: Wide- and ultra-wide-bandgap (WBG/UWBG) power devices offer higher blocking-field capabilities and faster switching, but increasing power density presents significant thermal management and packaging challenges. Heat dissipation depends on semiconductor properties, thermal interfaces, package geometry and cooling conditions. However, translating material- and interface-level thermal improvements into reliable device and converter performance remains challenging because of differences in operating conditions and electro-thermal constraints.

Aims: To assess thermal transport, packaging and electro-thermal co-design constraints in WBG/UWBG power devices.

Study Design: Focused narrative review.

Methodology: Thirty journal articles were compared by structure, measurement or modelling methods, operating conditions and evidence limitations. The search was updated on 7 August 2026.

Findings: Interfaces, anisotropy, package geometry and duty cycle can outweigh bulk conductivity advantages. Thermal improvements can coexist with electrical degradation. Interface measurements, simulations and pulsed demonstrations do not establish continuous converter performance or service life.

Conclusion: Coupled thermal, electrical and packaging assessment is essential. The priority gaps are matched-condition comparisons, manufacturing variability and durability under representative converter operation.

Predictive Sentiment Analysis and Proactive Service Intelligence: Implications for Long-Term Customer Loyalty and Retention-A Scoping Review

2026-10-15T07:37:45+00:00

Background: Predictive sentiment analysis and proactive service intelligence are increasingly used to identify deteriorating customer relationships and support targeted service responses, yet evidence is distributed across marketing, customer relationship management, service research and business analytics.

Objective: This scoping review maps the evidence linking sentiment analysis, predictive customer analytics and proactive service with customer loyalty and retention and develops an integrated conceptual synthesis.

Methods: The review was guided by established scoping-review methodology and PRISMA-ScR. Nine multidisciplinary databases were searched, supplemented by backward citation searching and citation tracking. Evidence was charted by study design, industry, technology, data type, analytical method, customer-intelligence construct, service mechanism and relationship outcome.

Results: A total of 515 records were identified, 60 full-text reports were assessed and 32 sources were included. The mapped evidence indicates that textual sentiment signals can add predictive value when combined with behavioural and transactional data; AI-enabled customer analytics can support churn-risk identification and personalised service; and proactive service may translate customer intelligence into timely interventions. However, prediction accuracy should not be equated with intervention effectiveness, and direct longitudinal evidence for durable loyalty and retention remains limited. Trust, privacy, explainability, human oversight and responsible data use emerged as important boundary conditions.

Conclusions: The literature supports a conceptual pathway from customer data to sentiment intelligence, predictive risk assessment, proactive intervention and relationship outcomes, but the pathway should be interpreted as an evidence-informed synthesis rather than a validated causal model. Future research should prioritise longitudinal and experimental evaluations of intervention effects and heterogeneous treatment response.

Green Construction Technologies and Applications for Transportation Infrastructure: A Narrative Review

2026-10-17T12:05:04+00:00

Transportation infrastructure provides long-term connectivity but generates environmental burdens through material production, construction, operation, maintenance and end-of-life management. This narrative review examines green construction technologies for roads, bridges and tunnels, focusing on recycled pavement materials, warm-mix asphalt, low-carbon concrete, alternative binders, construction machinery, ecological interventions, digital technologies and circular resource use. The review organises the literature around infrastructure life-cycle stages and considers engineering applicability, potential environmental benefits and trade-offs involving durability, cost, constructability and local supply conditions. The evidence indicates that reclaimed asphalt pavement, recycled aggregates, warm-mix asphalt and supplementary cementitious materials have established or emerging practical applications, whereas wider implementation of some alternative binders and digitally integrated systems requires further field evidence and institutional capacity. Environmental outcomes depend on mixture quality, transport distances, production energy, electricity carbon intensity and future maintenance rather than on recycled content or any individual technology alone. Differences in functional units, system boundaries, background data and recycling assumptions limit direct comparison among life-cycle assessments. Implementation is also influenced by technical standards, contractor capabilities, procurement arrangements and local recovery infrastructure. The review identifies priorities for long-term field validation, regional life-cycle inventories, integrated environmental and economic assessment, and stronger connections between digital monitoring and measurable resource and emissions outcomes. These findings support context-sensitive selection of green technologies that maintains required infrastructure performance while addressing cumulative environmental impacts.

Upcycling Agricultural Byproducts into High-performance Adsorbents for Water Remediation

2026-10-22T13:02:44+00:00

Agricultural by-products are generated in substantial quantities, and their disposal or burning can contribute to environmental pollution. This review examines the potential of agricultural residues as raw or modified biosorbents for removing contaminants from water and wastewater. It considers representative materials derived from fruit stones, husks, shells and plant residues, together with their reported performance in removing metal ions, dyes and selected organic pollutants. The reviewed studies describe adsorption processes involving surface functional groups and mechanisms such as electrostatic interactions, ion exchange, complexation and physical adsorption. Material composition, porosity, surface modification, solution pH, initial pollutant concentration and contact time influence reported adsorption performance. Chemical and physical treatments can improve sorption properties, although their effectiveness depends on the biomass source and target contaminant. The reported findings also show that pollutant removal may differ between controlled laboratory solutions and complex wastewater matrices, where coexisting substances can affect adsorption. Consequently, performance estimates obtained under different experimental conditions require cautious interpretation. The review identifies regeneration, treatment of pollutant-loaded adsorbents, application to real wastewater and integration with other treatment technologies as important considerations for practical use. Overall, agricultural by-products offer potential feedstocks for wastewater-treatment adsorbents while providing an opportunity to reuse solid residues. Further evaluation under representative operating conditions is needed before broader application can be established.