Aims: This review examines AI-assisted methods for satellite orbit determination and prediction, clock-bias forecasting, thermospheric-density calibration, atmospheric-delay modelling, and integrated GNSS correction. It identifies recurrently successful approaches, limitations in the current evidence, and priorities for future research. Study Design: A structured narrative synthesis of foundational and recent literature published through early 2026 was undertaken. Targeted keyword searches and backward citation checking were used to identify studies of classical machine learning, recurrent and attention-based networks, ensembles, graph neural networks, and physics-informed neural networks. Evidence was organised by task, data regime, baseline, forecast horizon, metric, and reported limitation; no pooled meta-analysis was performed. Results: Across the reviewed orbit studies, hybrid residual-learning schemes were the most recurrently successful design, although no pooled effect was estimated. In one thermospheric-density evaluation, AI calibration improved mean absolute percentage error by 61% against NRLMSISE-00 and 39% against JB-08. In one one-day GPS clock experiment, QP-assisted BPNN, WNN, LSTM, and GRU models improved on quadratic polynomial prediction by about 39%, 58%, 27%, and 29%, respectively. In a separate four-city dataset, a graph-based model reduced horizontal positioning error by 40-80% relative to the tested deep-learning baselines. These values are study-specific, not general effect estimates. Common barriers were limited cross-satellite generalisation, scarce precise LEO data, computational constraints, weak uncertainty calibration, and separate orbit and clock pipelines. Conclusion: AI can improve specific parts of the orbit and clock correction chain when models are evaluated against suitable physical or statistical baselines. The evidence favours transferable, physics-informed, uncertainty-aware, and computationally efficient joint models, supported by common benchmarks and independent validation.
Oil and gas exploration can both introduce and redistribute potentially toxic metals and naturally occurring radioactive material across the soils and water bodies of surrounding communities, opening exposure pathways that reach well beyond the immediate production site. This study evaluated the human-health risk from heavy metals and the radiological risk from naturally occurring radionuclides in soil and water sampled from the Apkai and Umusedege oil-field communities in Ndokwa East and Ndokwa West Local Government Areas of Delta State, Nigeria. Sixty-three soil samples and eleven water samples were analysed using atomic absorption spectrophotometry, X-ray fluorescence spectroscopy, gross alpha/beta counting and gamma-ray spectrometry, covering Ni, Cr, Cu, Co, Pb, Cd, Fe, Mn, As and Zn. Human-health risk was modelled for children and adults using USEPA exposure equations across ingestion, inhalation and dermal-contact pathways; the pathway-level components were audited directly against their own reported totals by direct summation of their reported pathway contributions. Once audited, the combined soil-and-water hazard index came to 2.53 for children and 13.60 for adults, with ingestion the dominant soil pathway for both groups and an unusually large adult water-dermal contribution driving the adult total; both hazard indices exceed the HI = 1 screening threshold. Total excess lifetime cancer risk from heavy-metal exposure was 7.18×10⁻⁶ for children and 2.40×10⁻⁶ for adults, both remaining within the USEPA-adopted acceptable range. In water, gross alpha and beta activities averaged 1184 and 2164 mBq L⁻¹ respectively, peaking at 3160 and 6145 mBq L⁻¹, with corresponding mean annual effective doses of 2.154, 1.133 and 0.566 mSv y⁻¹ (alpha) and 4.087, 2.106 and 1.053 mSv y⁻¹ (beta) for adults, children and infants respectively. Gamma spectrometry of soil gave mean activity concentrations of 36.102 Bq kg⁻¹ for ²²⁶Ra, 50.237 Bq kg⁻¹ for ²³²Th and 251.903 Bq kg⁻¹ for ⁴⁰K, with a mean absorbed dose rate of 42.22 nGy h⁻¹, annual effective dose of 0.076 mSv y⁻¹ and radium equivalent activity of 91.627 Bq kg⁻¹. Mean external hazard, internal hazard, gamma representative-level and alpha indices were 0.247, 0.335, 0.376 and 0.162 respectively, and the calculated radiological cancer risks were 3.18×10⁻⁶ for adults and 4.32×10⁻⁶ for the whole population. Taken together, the audited results point to heavy-metal exposure with elevated hazard indices for both children and adults as the primary human-health concern, while soil NORM levels imply comparatively low external radiological hazard. Water, in contrast, showed elevated gross alpha/beta activity and associated doses alongside the dominant adult dermal hazard quotient, and therefore warrants continued radiological and chemical monitoring, more targeted radionuclide-specific follow-up, and independent verification of the adult water-dermal exposure calculation.
The present work aims to investigate the effect of electron irradiation on the properties of silver selenide thin films. In this work, dendritic Ag₂Se thin films were synthesised via a facile, low-cost potentiostatic electrodeposition technique on fluorine-doped tin oxide (FTO) glass substrates. Silver nitrate (AgNO₃) and selenium dioxide (SeO₂) were employed as precursor sources, while ethylenediaminetetraacetic acid (EDTA) served as a complexing agent to regulate ion release and crystal growth (5 mM AgNO₃ + 2.5 mM SeO₂ + 0.05 M EDTA). The phase composition, crystallographic structure, surface morphology, and optical properties of the deposited films were systematically investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM), and optical absorption spectroscopy. XRD analysis confirmed the formation of crystalline Ag₂Se without detectable secondary phases, whereas SEM revealed the evolution of highly branched dendritic architectures with well-defined fractal characteristics. Optical studies demonstrated the characteristic absorption behaviour of Ag₂Se, indicating its suitability for semiconductor-based applications. Furthermore, the growth mechanism of the dendritic structures was explained through a comparative investigation of the as-deposited films and those subjected to electron-beam irradiation, providing insights into the role of diffusion-limited growth and post-deposition structural evolution. The present electrodeposition strategy offers a scalable and energy-efficient route for fabricating Ag₂Se dendritic thin films with controlled morphology, opening new opportunities for their integration into advanced optoelectronic, thermoelectric, and energy-conversion devices.
Tropical and equatorial territories combine the most intense sustained rainfall on the planet with an accelerating rollout of fifth-generation mobile networks in the centimetre and millimetre wave bands. The statistical apparatus used to translate environmental and atmospheric measurements into propagation predictions, however, was assembled largely from temperate-latitude datasets and from fixed links considerably longer than the urban small cells that dominate contemporary deployment. This review critically evaluates how statistical methods have been applied to environmental and atmospheric parameters governing fifth-generation propagation in the tropics, and asks whether the resulting evidence supports the confidence routinely placed in it. Five method families are examined: the estimation of point rainfall rate distributions and the conversion of long integration-time records to the one-minute reference; the regression of specific attenuation on rainfall rate through power-law coefficients derived from drop size spectra; the spatial statistics embedded in path reduction factors, effective rainfall rate formulations and site diversity models; the correlational and regression treatment of water vapour, temperature, refractivity, wind and vegetation; and supervised learning applied to path loss and attenuation time series. Convergent evidence establishes that rainfall rates exceeded for one hundredth of one per cent of an average year in equatorial sites are roughly an order of magnitude above temperate values, and that standard international recommendations systematically misestimate attenuation on paths shorter than one kilometre. Beyond this, the evidence weakens sharply. Reported model rankings rest on single-year records from a small number of sites, are assessed with inconsistent error statistics and almost never carry uncertainty intervals, so apparent superiority is frequently indistinguishable from sampling variation. Studies of non-precipitation parameters report correlations that reverse sign between seasons and regression models that explain little of the observed variance, yet these are often interpreted causally. Machine learning results are constrained by small, spatially autocorrelated datasets, by evaluation protocols that permit optimistic bias, and in some cases by reliance on simulator output as ground truth. Progress requires coordinated multi-site campaigns, open data, formal uncertainty quantification and validation protocols that test transfer rather than fit.
Accurate estimation of fine particulate matter (PM2.5) remains a major challenge in data-sparse regions such as West Africa because of limited ground-based monitoring networks and highly variable atmospheric conditions. This study evaluated statistical and machine-learning models for predicting ground-level PM2.5 concentrations across seven monitoring stations representing diverse ecological zones in Nigeria. Predictor variables included satellite-derived aerosol optical depth (AOD), meteorological parameters, gaseous pollutants, and temporal features. Ordinary Least Squares (OLS), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM), and stacked ensemble models were developed and evaluated using a consistent time-based training and testing strategy. Model performance was assessed using the coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (r), bias, normalized mean bias (NMB), and the Seasonal Stability Index (SSI). The results revealed substantial spatial and seasonal variability in model performance across Nigeria. Random Forest consistently achieved the highest predictive accuracy, producing the lowest regional mean RMSE (10.56 µg m⁻3) and ranking as the best-performing model at four of the seven monitoring stations. OLS demonstrated competitive performance in several locations, indicating that linear relationships remained important under certain environmental conditions, whereas XGBoost and LSTM generally exhibited lower predictive performance. In contrast, the MERRA-2 reanalysis dataset showed considerably larger prediction errors than the developed models. Seasonal analysis further demonstrated that model performance varied across ecological zones, with greater instability observed in the Sahel and more consistent predictions in the Guinea Coast. Overall, the findings demonstrated that ensemble tree-based machine learning models provided robust and reliable PM2.5 predictions in Nigeria and outperformed conventional statistical models and coarse-resolution reanalysis products. The proposed framework provides a practical approach for improving air quality assessment, exposure estimation, and evidence-based air pollution management in Nigeria and other data-sparse regions.
Electromagnetohydrodynamic (EMHD) flow over stretching surfaces plays a crucial role in the sophisticated processing of materials since it is essential to maintain precise control over momentum, heat, and mass transport to ensure high product quality. This study examined how to optimize Fourier-based EMHD flow and heat transfer over a surface that stretches exponentially, taking into consideration factors such as thermal radiation and Joule heating. The equations that define the boundary layer, which include electromagnetic forces, nonlinear surface stretching, and energy dissipation, were tackled using a Fourier spectral collocation method known for its high accuracy and efficiency in computations. A numerical analysis of the derived solutions was performed, highlighting how different material parameters impact the various fluid flow profiles, utilizing the Rosseland approximation for the radiation term. An increase in the Prandtl number leads to a reduction in the temperature profile, which verifies that controlling EMHD fluid flow on an exponentially stretching surface is advantageous for advanced material processing. It was found that the strength of the magnetic field, the radiation parameter, and the stretching rate significantly affect how velocities and temperatures are distributed within the boundary layer. Specifically, a stronger magnetic field reduces velocity while increasing the thickness of the thermal boundary layer, while radiation effects raise the temperature profiles throughout the flow domain. This research offers valuable insights into the parametric management of EMHD transport phenomena, showing how Fourier-based optimization can enhance heat transfer and flow management in industrial material processing systems.
This study investigates how different propagation environments influence the performance of Massive Multiple-Input Multiple-Output (MIMO) systems within a fifth-generation (5G) wireless communication framework using MATLAB-based simulation analysis. While many previous studies concentrated mainly on antenna scaling, limited attention has been given to the comparative influence of urban and rural propagation conditions under identical system configurations. To address this limitation, the present work evaluates the combined effect of antenna scaling and channel environment on communication performance using 8×8, 16×16, and 64×64 Massive MIMO antenna configurations. Urban communication conditions were modeled using Rayleigh fading channels to represent severe multipath and Non-Line-of-Sight (NLOS) propagation, whereas rural environments were represented using Rician fading channels characterized by stronger Line-of-Sight (LOS) signal components. Random binary data streams were generated and transmitted using Quadrature Amplitude Modulation (QAM) techniques through the configured MIMO channels with Additive White Gaussian Noise (AWGN) applied across varying Signal-to-Noise Ratio (SNR) levels. System performance was evaluated using Bit Error Rate (BER), Signal-to-Noise Ratio (SNR), and spectral efficiency. The simulation results revealed that increasing antenna configuration significantly improves communication reliability and signal quality across both propagation environments. BER values reduced progressively as antenna size increased from 8×8 to 64×64, while SNR and spectral efficiency improved correspondingly. The rural propagation environment consistently achieved lower BER and higher signal quality than the urban environment because of the stronger LOS signal component and reduced multipath interference. In contrast, urban environments experienced greater signal degradation due to severe scattering and fading effects, although larger antenna arrays substantially improved system stability under these conditions. The findings demonstrate that both antenna scaling and propagation environment strongly influence Massive MIMO performance in 5G communication systems. The study therefore provides additional insight into the design of environment-aware wireless deployment strategies capable of improving communication reliability and bandwidth utilization in heterogeneous propagation regions such as Nigeria.
Osteoporotic bone fractures require safe, repeatable monitoring approaches, particularly when repeated exposure to ionising radiation is undesirable. This study presents the simulation-based design of a compact wearable microstrip patch antenna for microwave assessment of bone-fracture conditions in osteoporotic patients. The antenna incorporates an elliptical tapered radiating patch and a microstrip feed structure on a flexible Rogers RT/duroid 5880 substrate, selected to support conformal placement near the lower limb. The proposed configuration was evaluated over the 1-6 GHz frequency range using CST Studio Suite and ANSYS HFSS. A multilayer lower-limb tissue model comprising skin, fat, muscle and osteoporotic bone was developed to examine antenna performance in proximity to biological tissue. Fractured, soft-callus, healed and healthy bone conditions were represented by changes in relative permittivity and conductivity. The simulated response showed impedance-matching behaviour, with return loss below -10 dB over the reported operating band and a voltage standing wave ratio below 2 within the useful matched region. The peak simulated gain was approximately 5.7 dBi. Specific absorption rate analysis at 2.45 GHz and 100 mW input power produced a maximum value of 1.8 W/kg in the tissue model. Differences in reflected microwave response were observed between fractured and healed bone models owing to changes in dielectric contrast. These results suggest that the proposed wearable antenna may warrant further investigation as a non-invasive microwave sensing element for bone-fracture monitoring. Fabrication, experimental validation and testing on realistic physical or clinical models are required before practical biomedical use can be established.
Aims: The activities of coal mining exploration in Maiganga leads to environmental and health concerns due to the presence of naturally occurring radionuclides. The potential health risks associated with exposure to natural radionuclides in soil require thorough and constant investigation. The study evaluated the activity concentrations of some selected radionuclides (226Ra, 232Th and 40K) and assessed excess lifetime cancer risk (ELCR) in soil samples of Maiganga mining site. Study Design: This study, was designed to evaluate the activity concentrations of some selected radionuclides (226Ra, 232Th and 40K) and assessed excess lifetime cancer risk (ELCR) in soil samples. Place and Duration of Study: Maiganga mining site, North-Eastern Nigeria between November 2024 and October 2025. Methodology: A total of ten (10) soil samples were systematically collected within the mine sites. Using energy dispersive x-ray fluorescence (ED-XRF) spectroscopic technique, the activity concentrations of some selected radionuclides (226Ra, 232Th and 40K) were determined. Results: The results showed that, the activity concentrations of 40K was 241.01 Bqkg-1 while 226Ra and 232Th were below the limit of detection. The analysis of radiation risk parameters (Raeq, D, AEDE, AGDE, Hex, Hin and ELCR) were found to be: 43.51 Bqkg-1, 21.43 nGyh-1, 0.03 mSvy-1, 151.03 µSvy-1, 0.12, 0.14 and respectively. Conclusion: The study concludes that, the study area is radiologically safe for both workers and the general public; since the radiation risk parameters were found to be below the recommended threshold values. Hence, continuous radiological assessment of the mining site is recommended to keep the potential radiation hazards as low as reasonably achievable (ALARA).
The sorting of different products has been reported to be a very tedious industrial process, complex and a global problem. Manual sorting creates consistency issues and involves a lot of manpower with reduced efficiency and accuracy. This study presents an automatic sorting and counting device using an LGT8F328 microcontroller. The device uses a TCS320 RGB colour sensor, two servo motors and a serial terminal used to display the data read from the colour sensor. The circuit was simulated using Proteus ver8.2, and the prototype was developed and tested for sensitivity, specificity and accuracy. Results show that the device sensitivity is 96.72%, specificity 95.08% and accuracy 95.90%. This implies that the device can accurately count and sort out 96.72% of colours but will fail to identify 3.28% of the same. Also, the device's accuracy of 95.90% implies that counting and sorting using this device conforms to the standard, and we are 95.9% sure. This work holds some significant advantages and benefits across various industrial applications, such as efficiency and accuracy, time and labour saving, consistency and reliability, versatility, customisation and reduced human intervention. It is very useful in a wide variety of industries, along with the help of a Programmable Logic Controller (PLC) and Supervisory Control and Data Acquisition (SCADA) system, especially in the packaging section. An automatic sorting machine enhances efficiency, practicality, and safety of operators. It ensures remarkable processing capacity.
This study presents a graph-theoretical and descriptive structure–property analysis of the linear \(\alpha\)-linked oligothiophenesbithiophene, terthiophene, quaterthiophene, sexithiophene, and octithiophene. From the common edge partition of theirhydrogen-suppressed molecular graphs, explicit closed forms are derived for fourteen degree-based descriptors: the first and second Zagreb, forgotten, Yemen, first and second hyper-Zagreb, three redefined Zagreb, Randi´c, Sombor, Yemen–Sombor, geometric–arithmetic, and atom–bond connectivity indices. Numerical values are obtained for all five molecules. Ten physicochemical endpoints reported in PubChem—polar surface area, molecular weight, complexity, XLogP3-AA, heavy-atom count, boiling point, enthalpy of vaporization, flash point, molar refractivity, and molar volume—are analyzed using descriptive linear regression. Every considered index is an affine function of oligomer length; therefore, the fourteen univariate regressions have identical fitted values and goodness-of-fit statistics for a fixed endpoint, although their slopes and intercepts differ. To avoid redundant reporting, the main text provides a compact endpoint-level summary and one representative index model, while all 140 descriptor–endpoint equations are supplied in the supplementary material. The models describe trends within this five-member homologous series and are not presented as externally validated predictive QSPR models.
Rapid growth in vehicle numbers has increased pressure on limited parking facilities, particularly in commercial areas and public offices. This study designed, simulated, constructed and evaluated a microcontroller-based automatic car parking control system with automatic gate shutdown. The system was simulated in Proteus using an ATmega328 microcontroller programmed in the Arduino language. Its principal units comprised two TCRT5000 infrared detectors for vehicle detection, a microcontroller, a servo motor, an LCD and a DC power supply. A prototype was constructed and tested to determine its sensitivity and accuracy in detecting vehicles entering and leaving the parking area and in controlling the entrance gate according to the recorded vehicle count. For vehicles entering the parking area, the system achieved a sensitivity of 98.40% and an accuracy of 94.42%. For vehicles leaving, the sensitivity and accuracy were 99.30% and 94.38%, respectively. The overall sensitivity was 98.85%, while the overall accuracy was 94.40%. These results indicate that the prototype detected and controlled most vehicle movements under the experimental conditions, although a small proportion of events was not correctly controlled. The system also displayed the parking status and operated the gate according to vehicle movement and available capacity. The developed prototype may support automated parking control in small parking facilities and reduce the manual effort and time associated with managing vehicle entry and exit.
Physics provides fundamental tools and conceptual frameworks for understanding complex environmental systems and processes. Through quantitative methods, modeling, measurement technologies, and theoretical constructs, physics underpins many contemporary approaches to environmental research and management. This review examines the major applications of physics in environmental studies, spanning atmospheric science, hydrology, climate dynamics, remote sensing, air and water quality monitoring, soil physics, and pollution modelling. Key physical principles, including fluid dynamics, thermodynamics, electromagnetic radiation, and mass and energy conservation, are essential for interpreting environmental phenomena from micro- to global scales. Techniques such as remote sensing, radiative transfer, and dispersion modeling are rooted in electromagnetic and fluid physics, offering spatially extensive and temporally resolved data critical for monitoring land cover, water quality, and atmospheric constituents. Physical models and measurement methods like eddy covariance provide direct estimates of energy and gas fluxes between Earth surface and atmosphere, crucial for climate and ecosystem studies. Physics also plays a central role in renewable energy technologies, noise and radiation pollution assessment, and emerging physics-informed computation methods such as physics-informed neural networks for pollutant source localization. By linking fundamental physical laws with environmental applications, this interdisciplinary field enhances predictive capability and informs sustainable policy. A comprehensive understanding of environmental challenges necessitates integrating physical methods with ecological, chemical, and socio-economic insights, positioning physics as indispensable in addressing global environmental change.
The assessment of Background Ionization Radiation [BIR] of Rumuagholu Town in Port Harcourt, River State was carried out using an in-situ approach. A well calibrated meter (radalert Tm 100) atomic radiation checking meter containing a Geiger Muller tube capable of detecting alpha, beta, gamma and X-rays within the temperature range of 100c and 500c. The work covered a total location of forty (40) points. At every location, two exposure rates were measured and averaged to one. The results obtained showed that the Average Exposure Rate measured, ranged from 0.0105 – 0.018mR/h with a mean value of 0.01363mR/h. The equivalent dose computed ranged from 0.8832 – 1.514mSvy-1 with a mean value of 1.1214mSvy-1. Again, absorbed dose ranged from 91.35 – 156.6 nGyh-1, with the mean value of 121-56nGyh-1. The annual effective dose equivalent (AEDE) ranged from 0.112 – 0.192 with a mean value of 0.1490mSvy-1. The excess life time cancer Risk (ELCR) ranged from 0.3908 – 0.6700 with a mean value of 0.504 x 10-3. All the results showed higher values against the World Accepted values and so Rumuagholu Town is Radiologically enhanced. Therefore, it is advisable for Nigeria nuclear regulatory Agency to educate the residents on the dangers of ionizing radiation. Similarly, residents should be advised to be on routine medical check- up to ascertain the level of their radiation exposure.
Fibonacci sequence, known for its mathematical elegance & recurrence properties, brings a novel approach to filter design. In this paper we aim to design 2nd order linear time invariant (LTI) systems using pairs of consecutive higher order Fibonacci numbers. The analyses of designed systems for their overall stability i.e in terms of Routh-Hauritz criterion, gain and phase margins reveal that all the designed transfer function are stable. The impulse response represents Dirac delta function and the step response is slightly over damped with damping ratio ζ ≈ 1.029. The magnitude response is similar to that of a low pass filter. Monte Carlo Simulations to predict their cut off frequency validates the theoretical analysis. We have showed that the cut off frequency is 0.618 times the square root of the product of Fibonacci pairs.
Laser irradiation represents a highly precise method for delivering thermal energy to superficial cancer cells while minimizing injury to surrounding healthy tissue. Mathematical modeling of laser–tissue interaction is essential for treatment planning and outcome prediction. This study presents a comprehensive numerical simulation of heat distribution during laser-induced thermal therapy for superficial tumors using COMSOL Multiphysics. The novelty of this work lies in a two-dimensional axisymmetric multilayered skin model with an embedded tumor domain to perform a detailed parametric analysis of critical treatment variables. A 2D cross-sectional skin model consisting of the epidermis, dermis, and subcutaneous layers was constructed, with a circular tumor embedded within the dermis. Heat transfer was modeled using Pennes’ bioheat equation coupled with a laser heat source described by the Beer–Lambert absorption model. A systematic parametric investigation was conducted across five critical variables: laser intensity (1–5 W/cm²), exposure duration (10–100 s), blood perfusion rate (0–0.005 s⁻¹), optical absorption coefficient of the tumor (100–1000 m⁻¹), and tumor geometry (radial dimension and depth). The simulation demonstrates that optimized laser parameters can selectively raise tumor temperature to the therapeutic hyperthermia range (42–45 °C) and induce localized thermal damage. For instance, under an intensity of 3 W/cm² applied for 50 seconds, the tumor center reached a peak temperature of ~48 °C, while surrounding healthy tissue remained below 40 °C. Approximately 87% of the tumor volume reached temperatures above the therapeutic hyperthermia threshold (42 °C), while about 18% exceeded the ablation threshold (>45 °C). The model underscores the critical role of parameter optimization, particularly laser intensity and exposure time, in enhancing the efficacy and safety of laser-based tumor therapy, providing a valuable framework for preclinical treatment planning.
This research presents the design and experimental application of an ultrasonic generator based on an IC 555 timer as a source of ultrasonic waves for bacterial inactivation. The developed system operated in the frequency range of 40-65 kHz and was experimentally evaluated using Grampositive and Gram-negative bacterial suspensions with fixed initial concentrations. The Grampositive bacterium used in this study was Staphylococcus aureus, while the Gram-negative bacterium was Escherichia coli.Bacterial samples were exposed to ultrasonic radiation at various
In this paper, the radii and the volume mix ratios of Urban aerosols were extracted from Optical Properties of Aerosols and Clouds (OPAC 4.0) at Relative Humidies of 0, 50, 70, 80, 90, 95, 98 and 99. The compositions of urban aerososl in OPAC 4.0 are water solubles (waso) insoluble (inso) and soot. A sensitivity analysis was carried out examining the sensitivity of effective hygroscopic growth and water activity as modeled with the Köhler equation. The effective radii and the effective hygroscopic growths were determined and applied to the Kohler theorem to determine the water activity and Kelvin effects. Different concentrations of aerosols were used in the Köhler equation. After applying Kohler theorem, it was discovered based on the values of the significance that, water activities dominate the Kelvin effects. To determine effective hygroscopic growth models with different water activity estimation models, three water activity models were applied, and these models are, Activity Parameterization (AP), Van’t Hoff factor (VH) and Effective hygroscopicity parameter (EH) models. The coefficient of determination (R2), was used to determine the best model(s). From the analysis of the three models, it can be concluded AP model out perform all the models with R2 ranging from 0.9999792 to 0.9999929 for soot,0.9999792 to0 .9999850 for waso, and 0.9999792 to 0.9999949 for inso, while that the VH models fit, of Frank et. al., (2007), both linear and quadratic become the second with R2, ranging from 0.999692 to 0.999797 for soot, 0.999692 to 0.998879 for waso and 0.999692 to 0.999541 for inso.
Measurement of background ionizing radiation of Tombia roundabout, Yenegoa, Bayelsa state was successfully carried out. This research was executed with the use of GQ GMC – 300E plus Geiger Muller counter nuclear Radiation meter to measure background ionizing radiation and Global Positioning System (GPS) to record the geographical coordinates of the sample location. The study location was divided into four (4) sub-locations linked with the Tombia roundabout and 30 sample points were randomly measured respectively. The exposure rate ranged from 0.011 mR/h to 0.13 mR/h with a mean value of 0.0118±0.0005 mR/h, which is quite lower than the acceptable limit of 0.0133 mR/h of ICRP, the absorbed dose ranged from 95.7 nGy/hr to 113.1 nGy/hr with a mean value of 102.2±4.16 nGy/hr, which is lesser than the world average of 89.0 nGy/hr (UNSCEAR). The Annual effective dose has varied from 0.15 mSv/y to 0.17 mSv/y with a mean value of 0.16±0.005 mSv/y, which is lower than the acceptable limit of 1.0 mSv/y(ICRP), and the excess lifetime cancer risk ranged from 0.51 to 0.61 with a mean value of 0.55±0.05 x10-³ which is quite higher than the world average of 0.29x10-³ (UNSCEAR). Even though there is no visible radiological health threat the chances of contracting the cancer-related illness is significant due to the value of ELCR. It is therefore recommended that the exposure to sources of ionizing radiation should be minimized, and the government should provide a waste management plan to protect the environment and the general populace.
This review provides a comprehensive and critical analysis of the recent progress (2021–2025) in the application of molybdenum disulphide (MoS2) and molybdenum diselenide (MoSe2) for renewable energy. We focus on three pivotal areas: electro catalytic hydrogen evolution (HER), photovoltaics (PV), and energy storage. We dissect the key strategies for material enhancement, including Nano structuring, phase and defect engineering, and the design of advanced heterostructures. A central theme is the critical trade-off between enhancing performance metrics—such as catalytic activity, power conversion efficiency, and specific capacity—and ensuring long-term operational stability and scalability. By synthesizing findings from recent literature, we highlight a paradigm shift from single-material systems to complex, multi-component composites where synergistic effects are paramount. We critically evaluate the role of computational screening in accelerating material discovery and identify persistent challenges, including interfacial instability, intrinsic conductivity limitations, and the gap between lab-scale demonstration and industrial viability. The review concludes by outlining key knowledge gaps and proposing high-priority research directions aimed at unlocking the full potential of these versatile 2D materials for a sustainable energy future.
