Iranian Journal of Science and Technology, Transactions A: Science最新文献

The changes in vegetation cover in Mecca City, Saudi Arabia, from 2014 to 2024 are analyzed in this research, utilizing the Normalized Difference Vegetation Index (NDVI) from Landsat imagery. The NDVI provides valuable information on vegetation density and health, offering insights into environmental changes over time. The findings suggest that the city witnessed a positive shift in vegetation health over the span of ten years, mainly attributed to an increase in precipitation (66.9 mm, measured as the difference in mean annual rainfall between 2014 and 2023 derived from CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data), representing a notable departure from the decade-long baseline) and human-driven water conservation initiatives, though the statistical significance of this trend relative to long-term climatic norms warrants cautious interpretation given the limited record length. The vegetation in the research area was classified into four groups: Dense Vegetation, Moderate Vegetation, Sparse Vegetation/Bare Soil, and No Vegetation (Water/Urban). The research revealed a 2.07% uptick in Dense Vegetation between 2014 and 2024, accompanied by a decrease in bare land. Alongside looking back at past data, the study employs machine learning models to estimate NDVI values for 2030, using historical data from 2015 to 2023. The models utilized encompass Artificial Neural Networks (ANN), Decision Tree Regression, Random Forest Regression, and others. The ANN model anticipates an upward NDVI trend, projecting a 2030 NDVI of 0.0313, indicating potential enhancements in vegetation health if current conditions persist. Conversely, the Random Forest model anticipates a reduction in vegetation coverage, projecting an NDVI of 0.01462 for the same year, suggesting potential degradation under specific circumstances. The Decision Tree model aligns more closely with the ANN, projecting an NDVI of 0.01654. These varied projections underscore both the potential for vegetation recovery and the possibility of decline, contingent on environmental management practices and climate variability. The results underscore the significance of adaptable land and resource management strategies, particularly in dry regions like Mecca City, to guarantee sustainable vegetation growth and biodiversity conservation amid ongoing climate changes.

This article investigates the existence and stability of solutions for a class of generalized hybrid Langevin differential systems involving the (Psi )-Hilfer fractional derivative. Utilizing Dhage fixed-point theorem and Banach fixed point theorem, we establish sufficient conditions for the existence and uniqueness of solutions. The stability of these solutions is analyzed in the sense of Ulam–Hyers–Rassias, with the results framed under suitable assumptions on the nonlinear terms and the fractional operator. Furthermore, examples are provided to illustrate the relevance of the theoretical results by offering a solid foundation for comprehending fractional hybrid systems. This work contributes both theoretical and practical insights to the subject of fractional differential systems.

The Daitari Iron Ore Deposit of the Singhbhum Craton, eastern India, hosts extensive goethite-bearing ores that exhibit significant variability in field relations, internal textures, and mineral associations. This study investiGAtes the modes of occurrence, microstructural characteristics, and micro-compositional features of goethite occurring both as a dominant ore-forming phase and as an accessory mineral within different primary and modified iron ore varieties. The evolution of goethite and its role in iron ore transformation across different ore types remain poorly constrained, particularly with respect to the relationship between texture and compositional variability. Field and petrographic observations reveal diverse megascopic and microscopic textures, including laminated, massive, botryoidal, colloform, radiating, and spongy forms, reflecting heterogeneous pathways of iron redistribution and mineral transformation. Reflected-light microscopy reveals transitional relationships between goethite and hematite, indicating progressive replacement, recrystallization, and localized dehydration. Electron Probe Micro-Analyzer (EPMA) data indicate that goethite associated with goethitic ores is chemically distinct from accessory goethite, exhibiting higher Fe₂O₃ contents and more compositionally evolved characteristics. These contrasts indicate that goethite formation at Daitari occurred during multiple stages of near-surface evolution, rather than through a single uniform process. Nevertheless, the absence of isotopic and trace-element constraints limits definitive interpretation of the processes governing goethite formation. The results highlight the importance of integrating textural and compositional characteristics in understanding iron ore evolution and provide a refined framework for evaluating goethite-rich iron ores in Archean cratonic terrains.

In this study, we investigate the (beta )-decay properties of proton-rich nuclei with atomic numbers Z = 21–30 using the proton-neutron quasiparticle random phase approximation (pn-QRPA) model. Our analysis includes Gamow–Teller (GT) strength distributions, half-lives, log (textit{ft}) values, and stellar weak interaction rates under terrestrial and stellar conditions. A fully microscopic pn-QRPA framework was employed to carry out the calculations. The calculated GT strength distributions show good agreement with experimental data. The predicted (beta )-decay half-lives reproduce the measured values for more than (90%) of the nuclei within a factor of 10. The computed log (textit{ft}) values show decent agreement and are reproduced within a factor of 2 compared to the measured data. We computed the stellar ((beta ^{+})+ EC) decay rates and compared them with previous calculations such as large-scale shell model (LSSM) and the independent particle model (IPM). In high density regime, as the core temperature increased, our pn-QRPA based rates were found to up an order of magnitude smaller than those predicted by LSSM and IPM rates. These results provide crucial nuclear physics inputs for modeling the rapid-proton capture (rp) nucleosynthesis process, particularly in post-core silicon burning phases of massive star evolution. The present study enhances the reliability of the pn-QRPA approach in predicted (beta )-decay properties and highlights its importance in astrophysical nucleosynthesis simulations. In our pn-QRPA calculations, no explicit quenching factor was used.

Despite the expanding petroleum refinery sector in the Kurdistan Region of Iraq, a multi-pathway human health risk assessment (HRA) linking spatial soil contamination to child and adult receptor risks has not been reported for the Erbil Oil Refinery, the region’s largest crude-processing facility. This study presents the first three-pathway (ingestion, dermal, inhalation) HRA of 17 potentially toxic metals and total petroleum hydrocarbons (TPH) in surface soils from 22 sites across the ~ 350 km² refinery impact zone, following USEPA RAGS methodology with inverse distance weighting (IDW) spatial mapping. Geo-accumulation indices revealed severe beryllium enrichment (Class 5) together with moderate-to-heavy cadmium and lead contamination, concentrated in an industrial cluster proximal to the refinery; principal component analysis identified refinery–vehicular emissions as the dominant contamination source. Non-carcinogenic risk was acceptable for adult receptors but unacceptable for children at all 22 sampling sites, with ingestion as the dominant exposure pathway and beryllium the primary hazard driver. Carcinogenic risk remained within the tolerable range for both receptors, with arsenic as the principal carcinogenic contributor. By providing a spatially explicit, evidence-based risk baseline, these findings underline the urgent need for child-targeted soil remediation and risk management near petroleum refinery facilities in semi-arid environments.

Graphical Abstract

Recently, some classical operators have been modified by incorporating the compactly supported wavelets. In this work, we present a modification of the Szász operators by using the concept of wavelets. We compute the moments and central moments, and investigate various approximation properties associated with these operators.

This paper establishes sharp bounds on the parameter (beta in mathbb {R}) for differential subordination problems of the form

where (0 < alpha le 1), p is analytic in (mathbb {D}) with (p(0)=1), and h(z) is a univalent function mapping (mathbb {D}) onto a convex domain containing 1. We specifically examine important cases including the Bernoulli lemniscate (sqrt{1+{z}}) and exponential function (e^{z}). Our approach leverages geometric properties of Gaussian hypergeometric functions ({_2F_1}(a,b,c;{z})) and confluent hypergeometric functions ({_1F_1}(a,c;{z})) to obtain optimal results. The function (varphi _c({z},alpha )) maps (mathbb {D}) univalently onto a cardioid domain for each (alpha in (0,1]), allowing us to introduce and study a new Ma-Minda class of cardioid-starlike functions (mathcal {S}^*_c(alpha )). As applications, we derive sufficient conditions for analytic functions to belong to (mathcal {S}^*_c(alpha )), extending previous work on geometric function theory. The results are shown to be sharp through both analytical proofs and numerical verification.

This work studies the existence and attractivity of periodic solutions in a class of reaction–diffusion systems with distributed multi-delays, motivated by neural field models and population dynamics. We consider a class of linear partial differential equation with multidelays. By combining semi-Fredholm operator perturbation and fixed-point methods, we derive sufficient conditions for the existence of periodic solutions under non-compacity assumption on the semigroup generated by the linear part of the equation. As a concrete application, we analyze a spatially extended neural field model with synaptic delays and provide numerical simulations to illustrate our results.

In this article, we extend several relation-theoretic notions to topological spaces. We introduce relation preserving contraction mapping into topological spaces and utilize the same to extend Banach contraction principle in topological spaces employing a binary relation. To illustrate the validity of our main result, we provide a concrete example along with a MATLAB-based visualization of the convergence behavior. Furthermore, we demonstrate the applicability of our main result by finding a solution for fractional differential equation under some suitable assumptions.

Reliable species identification is fundamental for biodiversity assessment and wildlife conservation. Here, we applied mitochondrial DNA barcoding to 90 unidentified mammalian specimens housed in the Natural History Museum of Iran’s Department of Environment using three mitochondrial markers, COI, D‑loop, and Cytb. COI sequences (643 bp) were successfully obtained from 55 specimens representing 23 species, while D‑loop (669 bp) and Cytb (755 bp) sequences were generated from 27 to 8 specimens, respectively, improving the identification of taxa unresolved by COI alone. Sequence similarity searches against GenBank references showed 96–100% identity values and enabled the identification of 45 mammalian species. Bayesian phylogenetic analyses recovered well‑supported species‑specific clusters, consistent with taxonomic assignments. Pairwise genetic distances estimated using the Kimura two‑parameter (K2P) model revealed clear interspecific divergence (> 2%) for most taxa, whereas closely related species exhibited comparatively low mitochondrial divergence. Our findings demonstrate the effectiveness of combining multiple mitochondrial markers for accurate species‑level identification of Iranian mammals and provide new reference sequences for future molecular, ecological, and conservation studies.