Current Journal of Applied Science and Technology

Quality Control Frameworks for Electronic Health Record Data Workflows in Resource-Constrained Settings: A Structured Review with Implications for Global Health Information Management

2026-07-10T13:21:46+00:00

Electronic health record (EHR) systems have been adopted at an accelerating pace across low- and middle-income countries (LMICs) as part of broader efforts to digitise health information management. The data these systems generate underpin clinical care, programme monitoring and national reporting obligations, yet their quality remains uneven and, in many settings, inadequately governed. This review synthesises the published evidence on quality control frameworks applied to EHR and related routine health information system (RHIS) data workflows in resource-constrained settings, drawing on conceptual data quality models, empirical facility-level assessments, and policy and governance literature. It traces the evolution of data quality thinking from generic information systems theory to health-sector-specific frameworks, and examines how completeness, accuracy, timeliness, consistency and confidentiality are operationalised across diverse health system contexts. Structural constraints, including unreliable electricity, limited connectivity, workforce shortages and weak supervisory feedback loops, recur as dominant determinants of poor data quality, while interoperability gaps and fragmented governance arrangements compound the problem at a systems level. Promising developments include offline-capable architectures, structured data quality review toolkits, and early applications of machine learning for anomaly detection, although evidence of their sustained impact in resource-constrained settings remains limited. The review concludes that durable improvement in EHR data quality depends less on technology procurement than on aligning organisational incentives, workforce capacity, governance arrangements and infrastructure investment around a coherent, locally adapted quality assurance framework. Implications for global health information management practice and policy are discussed alongside priority areas for future research.

Bridging the Public Health–Cloud Security Divide: Workforce Implications of the HIPAA Security Rule Modernization for Public Health Informatics

2026-07-13T13:02:39+00:00

The proposed modernization of the Health Insurance Portability and Accountability Act Security Rule represents the most substantial regulatory shift in United States health data protection since 2003. Triggered by escalating ransomware activity, the migration of health records to cloud infrastructure, and persistent deficiencies identified through federal enforcement, the rulemaking would convert many previously discretionary safeguards into mandatory technical controls, including multi-factor authentication, encryption of data at rest and in transit, and rapid incident reporting. Most commentary on the rule has approached it through a hospital compliance lens, yet its consequences reach deep into public health agencies, which increasingly depend on cloud-hosted surveillance, case-reporting, and laboratory information systems that handle protected health information on behalf of state, tribal, local, and territorial health departments. This review examines the workforce implications of this regulatory shift for public health informatics, drawing on literature spanning health information security, healthcare cybersecurity human factors, and public health informatics workforce development. It synthesises evidence on existing skills gaps within the governmental public health workforce, the technical and behavioural demands that cloud-based security controls will place on informatics personnel, and the structural mismatch between public health staffing models and the specialised competencies the modernised rule presumes. The review identifies workforce development strategies, including competency frameworks, cross-training pathways, behaviourally informed security training, and shared-service models, that may help narrow this gap. It concludes that without coordinated investment in public health informatics training and recruitment, the technical ambitions of the modernised Security Rule risk outpacing the operational capacity of the agencies tasked with implementing it.

Choosing and Validating Density Functionals for Quantum Materials: Strong Correlation, Spin–Orbit Coupling, Topology, and Two-Dimensional Magnetism

2026-07-24T10:53:27+00:00

Density functional theory (DFT) has become the principal computational instrument for predicting and interpreting the electronic, magnetic and topological properties of quantum materials, yet the reliability of any such prediction rests entirely on the exchange–correlation (XC) approximation chosen for the calculation. This review examines the practical problem facing a computational materials scientist: which functional, or combination of functional and correction scheme, is appropriate for a given class of quantum material, and how should that choice be validated. Four intersecting themes are addressed. First, the treatment of strong electron correlation in partially filled d- and f-shell compounds is discussed through the lens of the Hubbard-corrected DFT+U method, hybrid functionals and dynamical mean-field theory, with attention to the double-counting problem and the determination of the Hubbard interaction parameter. Second, the implementation of spin–orbit coupling and its consequences for the identification of topologically non-trivial band structures are reviewed, including high-throughput screening strategies and the special case of intrinsic magnetic topological insulators. Third, the emerging body of work on two-dimensional van der Waals magnets is surveyed, with emphasis on how functional choice, Hubbard corrections and dispersion corrections influence predicted exchange interactions, magnetic anisotropy and critical temperatures. Fourth, cross-cutting validation strategies are synthesised into a practical decision framework intended to guide functional selection according to the dominant physics of the material under study. Throughout, the meta-generalised-gradient approximation and its strongly constrained and appropriately normed variants are treated as a distinct and increasingly important middle ground between computationally economical semi-local functionals and costly many-body approaches. The review concludes that no single functional is universally reliable across strongly correlated, spin–orbit-coupled and low-dimensional magnetic systems, and that transparent, material-specific validation against experiment or higher-level theory remains indispensable.

Artificial Intelligence Reshaping Digital Ecosystems for Sustainable Development: A Critical Review

2026-07-27T13:16:41+00:00

Artificial intelligence (AI) has moved from a peripheral technical capability to a structural feature of digital ecosystems, reorganising how platforms, data infrastructures, and institutional actors coordinate value creation across economic, social, and environmental domains. This review synthesises recent peer-reviewed literature to examine how AI technologies are reshaping digital ecosystems in ways that bear on sustainable development. The review traces four interlinked themes: the architectural transformation of digital ecosystems from modular platforms towards AI-native, data-intensive coordination structures; the enabling contribution of AI to environmental, economic, and social dimensions of the Sustainable Development Goals; the material and environmental costs embedded in AI infrastructure, including energy demand, water consumption, and electronic waste; and the governance and equity challenges that determine whether AI-enabled digital ecosystems narrow or widen existing development gaps. Evidence from agriculture, circular economy platforms, and urban systems illustrates how sector-specific applications translate general-purpose AI capability into measurable sustainability outcomes, while also exposing persistent asymmetries in access, computational capacity, and regulatory readiness between advanced and developing economies. The review finds that AI's net contribution to sustainable development is neither uniformly positive nor uniformly negative but is contingent on governance quality, infrastructure transparency, and the extent to which efficiency gains are captured within circular and human-centric organisational models. The paper concludes that digital ecosystems reshaped by AI require deliberate institutional design, coordinated environmental accounting, and inclusive access mechanisms if their transformative potential is to translate into durable sustainability gains rather than a redistribution of ecological and social costs.

Decoupling Methane Emissions from Economic Growth in Burkina Faso: Evidence from Tapio Elasticity, Log-Mean Divisia Index Decomposition, and Environmental Kuznets Curve Analysis (1980–2018)

2026-07-11T11:36:58+00:00

This study assessed whether methane emissions decoupled from economic growth in Burkina Faso between 1980 and 2018 and identified the main drivers of the observed trend. A quantitative national time-series design was used, combining Tapio decoupling elasticity, additive Log-Mean Divisia Index decomposition, sectoral source analysis, and an exploratory Environmental Kuznets Curve assessment. Methane emissions data were obtained from FAOSTAT, gross domestic product data from the World Bank, and population data from the United Nations Population Division. The results show that methane emissions increased from 5.005 MtCO₂e in 1980 to 20.373 MtCO₂e in 2018, while real gross domestic product increased from USD 2.15 billion to USD 14.19 billion. Methane intensity rose during the 1980s and then declined, with a net fall of 38% over the full period, from 2325 to 1435 t CO₂e per million USD of gross domestic product, and a further fall of 57% from its 1990 peak. Tapio elasticity declined from 2.44 in the 1980s, an expansive negative decoupling state in Tapio's typology, to 0.26 in the 2010s, indicating weak decoupling. The Log-Mean Divisia Index decomposition showed that population growth and rising income per capita increased methane emissions, while declining methane intensity partly offset these upward pressures. Enteric fermentation remained the dominant methane source, accounting for 55% of total methane emissions in 2018, followed by manure management and rice cultivation with biomass burning. The full annual Environmental Kuznets Curve specification suggested an inverted-U pattern, but the estimated turning point coincides with a discontinuity in the FAOSTAT series around 1990 and is therefore treated as indicative rather than definitive. The findings indicate that Burkina Faso has achieved weak decoupling, that is, relative but not absolute decoupling of methane emissions from economic growth. Achieving absolute decoupling will require targeted methane mitigation in livestock, manure management, and biomass-burning practices.

Thermal Performance and Entropy Generation of MHD Casson Fluid with Temperature-Dependent Viscosity

2026-07-14T07:50:41+00:00

The thermal management and thermodynamic assessment of non-Newtonian fluid flow over stretching surfaces remain important in manufacturing and engineering processes involving electrically conducting fluids. This study examines the thermal performance and entropy generation of a steady, two-dimensional magnetohydrodynamic Casson fluid over a linearly stretching sheet, considering temperature-dependent viscosity and viscous dissipation. The flow is formulated under boundary-layer assumptions, with a transverse magnetic field applied normal to the stretching surface and the induced magnetic field neglected because of the small magnetic Reynolds number. The governing mass, momentum and energy equations are transformed into coupled nonlinear ordinary differential equations through similarity transformations. The resulting boundary-value problem is solved numerically using a shooting technique combined with the Runge–Kutta–Fehlberg method with adaptive step-size control, and the procedure is validated against limiting cases reported in the literature. The results show that the magnetic parameter suppresses the velocity field through the Lorentz force and increases thermal resistance within the boundary layer. The Casson parameter, viscosity variation parameter, Prandtl number and Eckert number produce distinct changes in the wall shear stress and local Nusselt number. Viscous dissipation acts as an internal heat source, increasing the fluid temperature and reducing the surface heat transfer rate. Entropy generation increases with stronger magnetic effects, higher viscous dissipation and larger Brinkman number, while the Bejan number indicates the relative contributions of heat transfer and fluid friction irreversibilities. These findings provide a numerical basis for assessing heat transfer and thermodynamic losses in MHD Casson fluid systems with variable viscosity under the stated assumptions.

Quality Attributes Associated with the Biophysical Indicators of Good Fried Plantain (Aloco)

2026-07-14T09:21:17+00:00

Several plantain breeding programmes have developed hybrids with improved agronomic performance and enhanced resistance to production constraints. However, their adoption may be limited if their sensory quality after processing does not meet end-user expectations. This study evaluated the quality attributes associated with high-quality fried plantain, locally known as aloco, using eleven contrasting plantain varieties, comprising eight landraces and three hybrids. Fruits were harvested at commercial maturity, ripened to the yellow stage, and processed into Aloco using a standardized frying protocol. Sensory quality was assessed by quantitative descriptive analysis using a trained panel, while instrumental texture was measured by penetrometry and texture profile analysis. The results showed that Aloco quality was mainly differentiated by texture and appearance-related attributes. Firmness, chewiness, astringency, greasy appearance, color homogeneity, stickiness between slices, and fat perception contributed to the sensory discrimination of the samples, whereas sweetness was not a major discriminating attribute under the conditions of this study. Landrace varieties, including Saci, French clair, French sombre, Corne 1, Orishele, Big Ebanga, and Corne bout rond, generally produced Aloco with a firmer texture, greater chewiness, lower stickiness, and more homogeneous color. In contrast, the hybrids SH3640, Pita 3, and FHIA 21, together with the landrace Zakoi, were associated with softer, stickier, and oilier products. Instrumental texture parameters were strongly associated with sensory texture attributes, particularly firmness and chewiness. These findings indicate that firmness, chewiness, stickiness, color homogeneity, and fat perception are relevant quality indicators for evaluating plantain suitability for Aloco preparation. The combined sensory and instrumental approach may support varietal screening and guide the selection of plantain materials better suited for producing high-quality fried products.

Development of a Wearable Sign-language Recognition Prototype with Dual LCD Feedback Using Flex Sensors and IMU Technology

2026-07-16T06:57:27+00:00

Aims: This engineering study aimed to develop and evaluate a low-cost wearable sign-language recognition prototype for controlled recognition of selected isolated American Sign Language (ASL) alphabet and number gestures using finger-flexion and hand-orientation signals. The system was not intended to provide complete natural-language interpretation.

Study Design: Prototype development and controlled bench and gesture testing of a sensor-integrated glove system.

Place and Duration of Study: STEM Science Center/student engineering laboratory, New Jersey, USA; project period: 06/2025 to 03/2026.

Methodology: Five 2.2-inch resistive flex sensors were stitched into a dual-layer glove and mechanically stabilised with hot glue and strain-relief routing. Each channel was connected to the analogue input of an Arduino Mega 2560 through voltage-divider/amplifier circuitry. An Arduino Nano 33 BLE Sense Rev2 mounted on the dorsum of the glove provided inertial measurement unit (IMU) data for orientation-sensitive gestures. Sensor readings were calibrated using rest and bent positions, smoothed, baseline-corrected, and interpreted using threshold- and rule-based mapping to gesture labels. The translated output was displayed on mirrored 20 x 4 I2C LCD screens, with serial/SD logging used during calibration and troubleshooting.

Results: Four of the five flex channels produced stable, repeatable, and separable motion signatures suitable for controlled isolated-gesture testing. Baseline levels for F1-F4 were high and distinct (approximately 630-845 ADC counts), with low baseline noise for F2-F4 (0.50-0.80 ADC counts). The F5 channel showed extreme baseline instability (SD 57.79 ADC counts; CV of approximately 132.9%), consistent with intermittent wiring, floating input, or divider instability. IMU roll and pitch signals provided orientation context that complemented flex-sensor patterns. Formal classification accuracy, confusion-matrix analysis, and multi-user generalisation were not claimed from the present dataset.

Conclusion: The prototype demonstrates that a low-cost microcontroller-based glove can capture interpretable multimodal signals for selected isolated ASL alphabet/number feedback under controlled conditions. The strongest engineering contribution is the integration of flex and IMU signals with dual LCD feedback and the systematic identification of channel-level reliability limits that must be addressed before larger-scale validation.

Multivariate Morphometric Characterisation and Phenotypic Diversity of Local, Exotic and Crossbred Rabbit Populations in Burkina Faso

2026-07-30T06:42:20+00:00

Rabbit production is an important short-cycle livestock activity in Burkina Faso, but the morphological diversity of local, exotic and crossbred populations remains insufficiently quantified. This study assessed phenotypic diversity and morphometric structuring of rabbit populations to support sustainable management and genetic improvement. Field data were collected from September to December 2023 in the Kadiogo and Guiriko regions. A total of 302 adult rabbits were initially sampled from 60 breeders, and, after data cleaning and outlier removal, 266 rabbits were analysed using 16 quantitative variables and 14 qualitative traits. Descriptive statistics, principal component analysis, hierarchical clustering on principal components, multiple correspondence analysis, linear discriminant analysis, analysis of variance and multivariate analysis of variance were applied. The first two principal components explained 52.60% of the total variance. The first component was mainly associated with body size traits, including body length, body weight and ear length, whereas the second component was related to conformation traits such as chest depth and hip width. Hierarchical clustering identified three morphological groups, but their partial overlap indicated a continuous phenotypic structure rather than clearly separated populations. Multiple correspondence and discriminant analyses also showed moderate differentiation among groups, with misclassification particularly evident among crossbred rabbits. Breed had a significant effect on most morphometric traits, and the multivariate analysis confirmed overall differences among populations (Wilks' lambda = 0.1693; p < 0.001). Local rabbits generally showed smaller body measurements, improved breeds showed higher values, and crossbreds occupied intermediate and variable positions. These findings indicate that rabbit populations in Burkina Faso are organised along a body size gradient, with substantial admixture. Morphometric characterisation therefore provides a useful basis for breeding decisions, although complementary molecular analyses are needed to refine population assessment.

Exploring the Pathways from Transformational Leadership to Employee Performance: The Mediating Role of Job Satisfaction

2026-07-30T11:03:16+00:00

Aim: This study examined the relationships between four dimensions of transformational leadership—idealised influence, inspirational motivation, intellectual stimulation, and individualised consideration—and employee performance through the mediating role of job satisfaction in Ghana’s pharmaceutical manufacturing industry.

Methodology: A quantitative, cross-sectional survey design was used. Data were obtained from 476 employees of pharmaceutical manufacturing firms through a structured questionnaire and purposive-convenience sampling. The measurement and structural models were assessed using partial least squares structural equation modelling in SmartPLS 4, including reliability, validity, direct-effect, and mediation analyses.

Findings: All four transformational leadership dimensions were positively and significantly associated with employee job satisfaction. Inspirational motivation showed the strongest relationship with job satisfaction, followed by individualised consideration, idealised influence, and intellectual stimulation. Job satisfaction was also positively and significantly associated with self-reported employee performance. The indirect-effect results indicated that job satisfaction significantly mediated the relationship between each transformational leadership dimension and employee performance, with the strongest indirect effect observed for inspirational motivation.

Conclusion: The study provides sector-specific evidence from Ghana’s pharmaceutical manufacturing industry and clarifies job satisfaction as an explanatory mechanism connecting transformational leadership behaviours with employee performance. The findings emphasise the practical relevance of visionary communication, ethical conduct, intellectual engagement, and individual support for strengthening employees’ workplace evaluations and performance. However, the cross-sectional and self-reported design does not permit causal inference.

Development of an Innovative Hybrid Renewable Energy System for Coastal Protection at the Downdrift End of the Cotonou Groin Field

2026-07-31T10:49:14+00:00

Coastal erosion at the downdrift end of the Cotonou groin field threatens shoreline stability, infrastructure, and coastal activities in Benin. This study develops a preliminary conceptual design for a hybrid coastal-protection system integrating a submerged breakwater, a wave energy converter (WEC), a photovoltaic (PV) installation, and a hydraulic sediment-pumping unit for artificial beach nourishment. Representative wave, sediment, and solar-resource parameters for the eastern Cotonou coastline were compiled from available studies and applied in simplified engineering calculations. Under the adopted assumptions, the WEC generated an estimated 38.56 kW for a 5 m effective capture width, whereas the pumping unit required approximately 6.05 kW at a discharge of 0.05 m³/s and a 5 m head. The PV array, comprising 10 m² of panels with 17% efficiency, produced an estimated 8.84 kWh per day. The calculated WEC output therefore exceeds the hydraulic power demand under the selected design conditions, while the PV component may provide complementary energy during periods of reduced wave activity. However, its daily energy yield does not independently demonstrate continuous pump operation. The proposed concept links wave attenuation, renewable-energy conversion, and managed sediment redistribution within one coastal-protection framework. The assessment remains preliminary and requires site-specific hydrodynamic and morphodynamic modelling, structural-stability analysis, seasonal energy-yield simulation, storage design, environmental assessment, economic evaluation, and field validation before technical viability or operational effectiveness can be established.