Mangrove forests are vital to coastal protection, biodiversity support, and climate regulation. In the Niger Delta, these ecosystems are increasingly threatened by oil spill incidents linked to intensive petroleum activities. This study investigates the extent of mangrove degradation between 1986 and 2022 in the lower Niger Delta, specifically the region between the San Bartolomeo and Imo Rivers, using remote sensing and machine learning. Landsat 5 TM (1986) and Landsat 8 OLI (2022) imagery were classified using the Support Vector Machine (SVM) algorithm. Classification accuracy was high, with overall accuracies of 98% (1986) and 99% (2022) and Kappa coefficients of 0.97 and 0.98. Healthy mangrove cover declined from 2804.37 km² (58%) to 2509.18 km² (52%), while degraded mangroves increased from 72.03 km² (1%) to 327.35 km² (7%), reflecting a 354.46% rise. Water bodies expanded by 101.17 km² (5.61%), potentially due to dredging, erosion, and sea-level rise. Built-up areas declined from 131.85 km² to 61.14 km², possibly reflecting socio-environmental displacement. Statistical analyses, including Chi-square (χ² = 1091.33, p < 0.001) and Kendall’s Tau (τ = 1, p < 0.001), showed strong correlations between oil spills and mangrove degradation. From 2012 to 2022, over 21,914 barrels of oil were spilled, with only 38% recovered. Although paired t-tests and ANOVA results indicated no statistically significant changes at broad scales, localized ecological shifts remain severe. These findings highlight the urgent need for integrated environmental policies and restoration efforts to mitigate mangrove loss and enhance sustainability in the Niger Delta.

In Côte d’Ivoire, the government and its development partners have implemented a national strategy to promote agroforestry and reforestation systems as a means to combat deforestation, primarily driven by agricultural expansion, and to increase national forest cover to 20% by 2045. However, the assessment of these systems through traditional field-based methods remains labor-intensive and time-consuming, particularly for the measurement of dendrometric parameters such as tree height. This study introduces a remote sensing approach combining drone-based Airborne Laser Scanning (ALS) with ground-based measurements to enhance the efficiency and accuracy of tree height estimation in agroforestry and reforestation contexts. The methodology involved two main stages: first, the collection of floristic and dendrometric data, including tree height measured with a laser rangefinder, across eight (8) agroforestry and reforestation plots; second, the acquisition of ALS data using Mavic 3E and Matrice 300 drones equipped with LiDAR sensors to generate digital canopy models for tree height estimation and associated error analysis. Floristic analysis identified 506 individual trees belonging to 27 genera and 18 families. Tree height measurements indicated that reforestation plots hosted the tallest trees (ranging from 8 to 16 m on average), while cocoa-based agroforestry plots featured shorter trees, with average heights between 4 and 7 m. A comparative analysis between ground-based and LiDAR-derived tree heights showed a strong correlation (R² = 0.71; r = 0.84; RMSE = 2.24 m; MAE = 1.67 m; RMSE = 2.2430 m and MAE = 1.6722 m). However, a stratified analysis revealed substantial variation in estimation accuracy, with higher performance observed in agroforestry plots (R² = 0.82; RMSE = 2.21 m and MAE = 1.43 m). These findings underscore the potential of Airborne Laser Scanning as an effective tool for the rapid and reliable estimation of tree height in heterogeneous agroforestry and reforestation systems.

Industrial plastics have seen considerable progress recently, particularly in manufacturing non-lethal projectile holders for shock absorption. In this work, a variety of percentages of alumina (Al₂O₃) and carbon black (CB) were incorporated into high-density polyethylene (HDPE) to investigate the additive material effect on the consistency of HDPE projectile holders. The final product with the desired properties was controlled via physical, thermal, and mechanical analysis. Our research focuses on nanocomposites with a semicrystalline HDPE matrix strengthened among various nanocomposites. In the presence of compatibility, mixtures of variable compositions from 0 to 3% by weight were prepared. The reinforcement used was verified by X-ray diffraction (XRD) characterization, and thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) were used for thermal property investigation. Alumina particles increased the composites’ thermal system and glass transition temperature. Mechanical experiments indicate that incorporating alumina into the matrix diminishes impact resistance while augmenting static rupture stress. Scanning electron microscopy (SEM) revealed a consistent load distribution. Ultimately, we will conduct a statistical analysis to compare the experimental outcomes and translate them into mathematical answers that elucidate the impact of filler materials on the HDPE matrix.

Potassium is an essential macronutrient for living creatures on earth and in plants, it plays a very significant role in determining the overall health of the plants. Although potassium is present in the soil, it is present in a form that is inaccessible to the plants, and hence synthetic harmful non-eco-friendly potassium fertilizers are used. To overcome this problem, the use of eco-friendly potassium-solubilizing bacteria comes into play. The goal of the present study was to assess the potassium-solubilizing bacteria that inhabit the farm rhizosphere, which demonstrate the presence of enzymes associated with plant growth promotion and antagonistic properties. A total of thirty-four isolates were isolated from the rhizosphere. All these isolates were subjected to a potassium solubilization test on Aleksandrov agar medium, out of which fourteen were found to possess potassium solubilizing ability. On the basis of the 16S rRNA gene sequencing, the most potential potassium-solubilizing bacterium was identified as Proteus mirabilis PSCR17. The plant growth promoting abilities and production of biocontrol enzymes of this isolate were evaluated, and the results indicated, in addition to potassium solubilization, the isolate was positive for indole acetic acid production, hydrogen cyanide production, amylase, catalase, cellulase, chitinase, and protease. The use of potassium fertilizers is harmful to the environment and ecosystem; hence, this study concludes that P. mirabilis PSCR17 can be used as a substitute for chemical potassium fertilizers to improve the growth and biocontrol traits of the plants in a sustainable manner after further research.

Two-dimensional hexagonal boron nitride nanosheets (h-BNNS) were synthesized on silver (Ag) substrates via a scalable, room-temperature atmospheric pressure plasma (APP) technique, employing borazine as a precursor. This approach overcomes the limitations of conventional chemical vapor deposition (CVD), which requires high temperatures (>800 °C) and low pressures (10⁻² Pa). The h-BNNS were characterized using FT-IR spectroscopy, confirming the presence of BN functional groups (805 cm⁻¹ and 1632 cm⁻¹), while FESEM/EDS revealed uniform nanosheet morphology with reduced particle size (80.66 nm at 20 min plasma exposure) and pore size (28.6 nm). XRD analysis demonstrated high crystallinity, with prominent h-BN (002) and h-BN (100) peaks, and Scherrer calculations indicated a crystallite size of ~15 nm. The coatings exhibited minimal disruption to UV-VIS reflectivity, maintaining Ag’s optical properties. Crucially, Vickers hardness tests showed a 39% improvement (38.3 HV vs. 27.6 HV for pristine Ag) due to plasma-induced cross-linking and interfacial adhesion. This work establishes APP as a cost-effective, eco-friendly alternative for growing h-BNNS on temperature-sensitive substrates, with applications in optical mirrors, corrosion-resistant coatings, energy devices and gas sensing.