Search Results (3,179)

Mining of sulfide-rich deposits enhances the oxidation of sulfide minerals, generating acid mine drainage (AMD) characterized by high sulphate and dissolved metal concentrations and the formation of secondary iron minerals (hematite, goethite, and jarosite). As these minerals display diagnostic features in the visible–near-infrared (VNIR) region, multispectral satellite data provide a cost-effective means of monitoring. Here, the performances of Sentinel-2 and the VNIR bands from WorldView-3 are assessed and compared for the mapping and discrimination of secondary iron minerals in Sierra Minera de Cartagena–La Unión (SE Spain). Both datasets were analyzed using a band ratio and a parabola fitting technique focused on reflectance maxima. Band ratio results were interpreted as broad spectral patterns rather than definitive mineral identifications. Mineral maps were validated by applying X-ray diffraction on 74 surface soil samples. Although both sensors were able to reproduce the main spatial patterns of iron mineral distribution, Sentinel-2 data better discriminated hematite, goethite, and jarosite, especially when using the parabola fitting approach, whereas WorldView-3 VNIR data distinguished mainly hematite from the combined goethite–jarosite group. The better performance of Sentinel-2 is attributed to its red-edge and near-infrared band configuration. These findings indicate that freely available Sentinel-2 imagery can support systematic monitoring of oxidation processes in mining environments and contribute to environmental risk assessment in degraded landscapes. Full article

To address the ecological risks associated with highly mobile hexavalent chromium [Cr(VI)], woody biochar was functionalized with hydrogen peroxide (H₂O₂) to develop a dual-phase remediation material (H-BC) for aqueous and soil environments. Batch post-contact isotherm fitting yielded a Langmuir-fitted/extrapolated apparent retention capacity q_m of 77.44 mg/g at 328 K. This value reflects enhanced overall Cr(VI)-derived retention within the tested concentration range, rather than increased electrostatic affinity for chromate oxyanions. Empirical kinetic diagnostics and FTIR/XPS results were consistent with adsorption-coupled interfacial reduction, while DFT analysis provided qualitative support for the enhanced electronic responsiveness of H-BC. The OFG-enriched interface may facilitate short-range, non-electrostatic interfacial interactions and stabilize surface-associated Cr(III). Temperature-dependent apparent isotherm fitting suggested that elevated temperature favored the overall Cr(VI)-derived retention process under the tested conditions, and should not be interpreted as rigorous standard-state adsorption thermodynamics. Continuous-flow column leaching and accelerated wet–dry (W–D) aging experiments demonstrated that H-BC substantially suppressed the mobility of operationally filtered Cr(VI), achieving a maximum filtered-Cr(VI)-based retention efficiency of 99.98% under cyclic drying–rewetting conditions. Spatial configuration analysis indicated that homogeneous incorporation of H-BC improved soil–biochar contact and was more effective than stratified placement in limiting vertical filtered-Cr(VI) migration. Overall, oxidatively functionalized H-BC shows promise as a biomass-derived amendment for reducing Cr(VI) mobility in complex environmental matrices, although complete chromium mass redistribution will require future total-Cr and Cr(III)-resolved analyses. Full article

Traditional methods for screening high-melanin-yielding Auricularia heimuer strains are time-consuming and environmentally unfriendly. To address this issue, fifteen A. heimuer strains were used to determine the mycelial biomass, absorbance at 500 nm, CIE L*a*b* colorimetric values, and melanin yield of the fermentation broth. Pearson correlation analysis was performed to clarify the correlations among these indicators, and a regression equation was fitted to establish a rapid screening method. A total of 84 A. heimuer strains were used to verify this method, of which one high-melanin-yielding strain was obtained. The structural characterization and in vitro antioxidant activities of A. heimuer melanin (AHM) were determined. The results showed that the melanin yields of fifteen A. heimuer strains were extremely significantly positively correlated with absorbance at 500 nm (r = 0.880, p < 0.01). The fitted linear regression equation was Y = 0.0246X + 0.00094 (R² = 0.8756, p < 0.01). When 84 tested strains were investigated with this method, 8 strains (53.33%) exhibited relative differences below 10%, which is consistent with the satisfactory accuracy of the absorbance-based screening method. Finally, a high-melanin-yielding strain HMCC50028 was obtained, with a melanin yield of 0.0540 g/100 mL. The results of UV-Vis spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM) of AHM indicated that the melanin exhibited structural characteristics consistent with fungal melanins, belonging to the natural melanin family. In vitro assays demonstrated that AHM possessed excellent superoxide anion radical scavenging activity and ferric reducing power. Full article

Background: Public fitness facilities are high-contact environments that facilitate microbial transfer via shared surfaces; however, temporal dynamics and device-specific contamination patterns remain insufficiently characterized. Methods: A repeated-measures observational study was conducted in a fitness facility over five consecutive weekdays (Monday to Friday). A total of 180 surface samples were collected from 12 gym devices, each sampled three times daily (morning, noon, and evening). Surface-associated cultivable bacteria were recovered using culture-based methods followed by MALDI-TOF MS identification. Ecological metrics, including species richness and Shannon diversity, were calculated, and taxa were classified by origin (skin-associated versus environmental). Device-specific contamination profiles were developed using a composite index incorporating pathogen presence, contamination frequency, and persistence. Temporal trends and predictors of contamination were analyzed using mixed-effects regression models. All statistical analyses were performed in R. Results: A total of 248 bacterial isolates were identified, representing 61 species across 32 families, with a predominance of skin-associated taxa (72.2%). Sampling time point was a strong independent predictor of contamination (adjusted OR for noon vs. morning: 7.19; p < 0.001). While overall microbial diversity remained stable across devices (Shannon index, p = 0.44), substantial heterogeneity was observed in pathogen prevalence, multispecies burden, and persistence. The functional trainer and leg extension showed the highest composite risk scores (42.3%), while the ab crunch machine and upper body ergometer demonstrated significantly increasing contamination trends over the sampling period (p < 0.05). Co-occurrence analysis showed nonrandom microbial associations, with the strongest positive links between Micrococcus luteus and Staphylococcus saprophyticus (Φ = 0.76) and Staphylococcus aureus (Φ = 0.61). Conclusions: Gym equipment surfaces harbor predominantly human-associated microbial communities exhibiting dynamic temporal contamination patterns, and on selected devices, increasing the baseline contamination across consecutive cleaning cycles. The findings indicate that contamination patterns on shared fitness equipment are dominated by taxa commonly associated with human skin and support targeted hygiene interventions focused on frequently contacted devices and periods of elevated contamination. Full article

Nitrogen (N) plays an important role in the growth and development of potatoes, but overapplication of the nutrient compromises environmental systems’ sustainability and limits tuber productivity and quality. A two-season study was carried out in 2022 and 2023 at Ofcolaco in the Mopane District of South Africa to determine the influence of N and nano micronutrients on tuber bulking rate (TBR), crop growth rate (CGR), and stomatal activities. A Randomized Complete Block Design (RCBD) fitted into a split-split plot arrangement with four replications was employed with the hypothesis that N and nano micronutrients applications will not have an effect on growth, stomatal activity, and bulking rate of potato cultivars. The main-plot factor was N rates (0, 80, 160, and 240) kg Nha⁻¹; the sub-plot factor was nano-zinc (Zn) and copper (Cu) micronutrients, while cultivar, Mondial, and Valor were the sub-sub-plot factors. The application of N and nano Zn and Cu significantly influenced dry matter accumulation, TBR, CGR, and stomatal activities of both Mondial and Valor cultivars. From our study, the application of 160 kg Nha⁻¹ in conjunction with nano micronutrients resulted in an increase in dry matter in the two cultivars, in comparison with the application of 240 kg Nha⁻¹ without nano micronutrients. This observation was consistent in TBR and CGR in Mondial during the 2023 season. In 2022, the CGR under 160 kg Nha⁻¹, along with nano micronutrients in Valor, achieved 90% of the CGC of sole 240 kg Nha⁻¹. The physiological and plant growth parameters’ response to treatment in the two cultivars were generally optimized, when nano micronutrients were applied in conjunction with higher N rates of 160 and 240 kg Nha⁻¹. Significant principal component factors influencing variability in growth and physiological parameters varied between seasons. The findings generally demonstrated that 160 kg Nha⁻¹, in conjunction with micronutrients, has the potential to downsize N application in potato growth and development. Full article

Lifetime data arising in engineering reliability, survival analysis, actuarial science, and environmental studies often exhibit substantial right-skewness, extreme observations, and heterogeneous hazard-rate structures. Classical lifetime distributions may not adequately capture these characteristics, thereby affecting risk assessment, reliability evaluation, and predictive performance. In this paper, we introduce the Heavy-Tailed QLindley (HTQL) distribution, a new two-parameter heavy-tailed extension of the QLindley model obtained through the New Family of Heavy-Tailed (NFHT) transformation. The proposed distribution provides greater flexibility for modelling positively skewed and heavy-tailed data while preserving analytical tractability. The HTQL model accommodates increasing, decreasing, bathtub-shaped, unimodal, and nearly constant hazard rate functions, making it suitable for applications in reliability analysis, survival studies, actuarial science, and environmental modelling. Several mathematical and statistical properties of the HTQL distribution are derived, including explicit expressions for the quantile function, ordinary and incomplete moments, order statistics, and reliability measures. Important tail-based risk measures such as Value-at-Risk, Tail Value-at-Risk, Tail Variance, Tail Variance Premium, and Expected Shortfall are also obtained. Parameter estimation is investigated using maximum likelihood, ordinary least squares, Cramér–von Mises, and Bayesian approaches, together with bootstrap confidence intervals. A Monte Carlo simulation study is conducted to evaluate the finite-sample performance of the proposed estimators. The practical usefulness of the HTQL distribution is illustrated using three real-world datasets from pharmacokinetics, engineering reliability, and environmental studies. The empirical results show that the HTQL distribution provides highly competitive fits compared with several classical, Lindley-type, and heavy-tailed distributions. Overall, the proposed model constitutes a flexible and parsimonious alternative for modelling positive heavy-tailed data. Full article

Tracking highly maneuverable UAVs in complex maritime environments faces multiple challenges: dynamic sea surface interference and low-altitude occlusion make UAV motion trajectories difficult to predict; the strong maneuvering behavior of UAVs imposes high demands on tracking real-time performance and accuracy; and marine environmental noise and unstable shipborne sensor data lead to measurement incompleteness. These factors collectively limit the adaptability and robustness of existing maneuvering UAV tracking methods in complex maritime scenarios. In this context, accurate model recognition for UAVs becomes a key factor in improving tracking performance. Traditional interactive multiple model (IMM) methods rely on probabilistic weighting for model selection, suffering from response delays during UAV maneuvers, and fixed model sets cannot adapt to diverse maneuvering scenarios, resulting in degraded UAV velocity estimation accuracy. To address the above issues, this study proposes a dual long short-term memory (LSTM) cooperative network architecture, targeting the two key problems of incomplete measurements in shipborne radar measurements and inaccurate model probability estimation, and presents corresponding solutions. First, an online-trained LSTM-based incomplete-measurement compensation method is proposed, which achieves real-time fitting and restoration of historical measurement data, providing continuous and stable measurement inputs for shipborne platform UAV tracking in maritime environments. Second, building on this, an LSTM-based UAV model recognition method is developed to directly identify the UAV’s current motion model from multi-frame historical measurement information, effectively reducing maneuvering delays. Furthermore, GPS data is used to generate optimal model probabilities as training labels, thereby improving model reliability. Simulation results show that, under incomplete-measurement conditions, the proposed method can effectively reconstruct missing measurements and ensure measurement continuity. Under complete-measurement conditions, the proposed LSTM-based model recognition method significantly improves UAV model recognition accuracy and three-dimensional velocity estimation performance, demonstrating the effectiveness of deep learning for maneuvering UAV tracking from shipborne platforms in maritime environments. Full article

The unprecedented rate of technological advances, accelerated industry disruptions and social and environmental sustainability crises require very different business organizations from the traditional paradigm. The main research question for this paper is: What change (paradigm shift) is needed for South African business organizations to be future-fit? The paper introduces an integrated, transdisciplinary paradigmatic model of an emerging, progressive future business organization in South Africa, as mostly influenced by Western futurists, and proposes an understanding of the paradigm shift required in our socially constructed reality for such organizations to emerge. A multi-method methodology, based on complexity theory and a transdisciplinary approach, was developed and applied. The researcher’s conceptualization of a ‘paradigm’, focusing on language-based representations, is explicated as a theoretical foundation. Textual analyses, including corpus linguistics, of practitioner-focused literature were used to elicit concept maps (or domain models) of the shared, societal-level mental models of a South African business organization for two periods: (1) the Traditional Business Organization, and (2) a Progressive Future Business Organization. The outcomes were compared using a novel qualitative method, resulting in a proposed set of societal-level ontological shifts needed for a progressive organizational future. The study shows a paradigm shift to complexity and social responsibility, and the need for transdisciplinarity to reflect complex, integrated organizational realities. Full article

The occurrence of pharmaceutical residues in aquatic environments has become an important environmental challenge, encouraging the development of sustainable and low-cost treatment technologies. In this study, eggshell waste in the form of eggshell without membrane (ES) and eggshell with membrane (ESM) was investigated as a biosorbent for the removal of levomepromazine from aqueous solutions. The materials were characterized by XRD, FTIR, SEM–EDS, TGA, and pH_PZC analyses, confirming the predominance of calcite and the presence of functional groups potentially involved in adsorption. Batch adsorption experiments were conducted to evaluate the effects of pH, adsorbent dosage, contact time, initial levomepromazine concentration, and temperature. The adsorption capacity increased with increasing pH, reaching optimum performance under alkaline conditions, while equilibrium was attained within approximately 60 min. Kinetic data were best described by the pseudo-second-order model (R² > 0.99). Equilibrium studies showed that the Freundlich model provided the best fit to the experimental data, suggesting adsorption on heterogeneous surfaces. Regeneration experiments demonstrated that both adsorbents retained a substantial fraction of their adsorption performance after five adsorption–desorption cycles. FTIR analyses after adsorption and pH_PZC measurements suggest that electrostatic interactions and hydrogen bonding may contribute to levomepromazine uptake. Response surface methodology identified adsorbent dosage and initial concentration as the most influential operating parameters. Overall, the results demonstrate the potential of eggshell-derived materials as low-cost biosorbents for levomepromazine removal from aqueous media. Full article

Electrospun composite nanofibers represent an emerging strategy for the development of efficient fertilizer systems, as they enable modulation of the structural properties of the nanofibrous network and, consequently, the transport and release processes of nutrients. In this study, polyvinyl alcohol (PVA) nanofibers loaded with two different urea contents (0.09 g and 0.36 g) were fabricated and characterized to investigate how urea incorporation modifies the nanofiber morphology and influences urea release kinetics. SEM and EDS analyses confirmed that increasing urea content promotes surface roughnes and reduced nanofiber diameters, whereas XRD and FTIR demonstrated a decrease in crystallinity and the formation of hydrogen-bonded interactions between PVA chains and urea molecules, indicating that urea is incorporated within the PVA network rather than being superficially adsorbed on the nanofiber surface. These structural changes govern water retention and release kinetics: the 0.36 g formulation exhibited a 100-h induction period followed by multiphase diffusion, while the 0.09 g system displayed immediate release but lower final concentrations. Kinetic modeling revealed excellent fitting to the Higuchi and second-order models, confirming diffusion-controlled urea release modulated by internal interactions. The nanofiber network thus behaves as an active regulator of nitrogen mobility, overcoming the limitations of conventional coating-based fertilizers. These findings demonstrate the potential of PVA/urea nanofibers as scalable platforms for sustainable nitrogen delivery in agriculture, bridging morphology-driven polymer design with environmental performance. Full article

Optimizing wind turbine layout is a critical aspect of wind farm construction planning, and it directly affects the power generation efficiency, economic performance and environmental adaptability of the wind farm. Aimed at effectively solving grid-based wind turbine layout optimization problems, a modified Ivy algorithm is proposed in this study by introducing a multi-population mechanism, roulette fitness-distance balance (roulette FDB) selection mechanism, and a one-to-one replacement mechanism into the basic IVY algorithm. The proposed algorithm better balances the global search and the local exploitation, thus achieving better optimization capability. Four 10 × 10 grid-based wind turbine layout optimization (WTLO) benchmark cases covering full-wake and partial-wake models are adopted to validate the performance of the proposed algorithm via comparative analyses against six state-of-the-art meta-heuristic algorithms. The Jensen wake model is adopted to characterize wind turbine wake effects, and the Mosetti cost model serves as the optimization objective. Experimental and comparative results demonstrate that the proposed algorithm exhibits strong competitiveness and outperforms other algorithms in terms of convergence rate, accuracy and stability. Full article

The contamination of aquatic environments by cadmium and other toxic heavy metals represents a major environmental concern requiring efficient and operationally sustainable remediation strategies. In this work, iron oxide materials were synthesized through a microwave-assisted hydrothermal method and evaluated for Cd(II) removal from aqueous systems. Different precursor compositions and organic additives were initially screened in order to identify the most suitable adsorbent formulation. The selected Fe-Tart material was characterized by FTIR, SEM-EDS, and XRD analyses, revealing hydroxylated and poorly crystalline iron oxide structures with heterogeneous surface organization. Batch adsorption experiments were performed under controlled conditions to investigate the influence of pH and equilibrium adsorption behavior, while adsorption data were analyzed using Langmuir and Freundlich isotherm models. Cd(II) uptake showed strong pH dependence, with adsorption progressively increasing from acidic to near-neutral conditions and reaching approximately 80% removal at pH 7–8. The Langmuir model provided the best fitting results (R² = 0.988), suggesting preferential occupation of energetically comparable surface sites with a maximum adsorption capacity of 6.51 mg g⁻¹. The adsorption behavior was interpreted within a pH-dependent surface complexation framework involving hydroxylated iron oxide surfaces. Although the adsorption capacity remained lower than that reported for some highly engineered adsorbents, the results indicate that microwave-assisted synthesis may provide a relatively simple and rapid route for preparing iron oxide-based materials potentially applicable to water remediation systems. Full article

Deforestation promotes environmental changes capable of altering regional microclimatic dynamics, intensifying wildfires, and increasing population exposure to cardiovascular risk factors. This study investigated the spatiotemporal association between deforestation and acute myocardial infarction mortality across health regions of the Brazilian Amazon between 2000 and 2023. An ecological study design was adopted using data aggregated by health region and year. Generalized additive models with a negative binomial distribution were fitted to evaluate nonlinear associations between deforestation and acute myocardial infarction mortality, including temporal lag analyses of one, two, and three years. Spatial dynamics were further investigated through Bayesian spatiotemporal modeling incorporating structured spatial effects and a smoothed temporal trend. A significant nonlinear association was identified between deforestation and acute myocardial infarction mortality, with progressive risk intensification observed in areas subjected to greater environmental degradation. Lagged models demonstrated persistence of the association over time, suggesting cumulative effects of environmental exposure. Spatial analysis revealed an expansion of areas with elevated relative risk, particularly within the Arc of Deforestation of the Amazon region. Overall, the findings indicate that deforestation may act as an important socioenvironmental determinant of cardiovascular health in the Brazilian Amazon. Full article

The removal of recalcitrant industrial dyes from wastewater has emerged as a critical environmental challenge, particularly in the context of the accelerating decline of global freshwater reserves. Given that these contaminants originate predominantly from the effluents of textile, chemical, and related manufacturing sectors, the deployment of advanced treatment technologies prior to discharge is imperative to mitigate their ecological impact. This study investigates the photocatalytic degradation of indigo carmine using a synthesized MgAl–LDH material. LDH is shown to act as an active photocatalytic component rather than a support, with its remarkably simple synthesis offering a practical alternative to the complex catalysts dominating the current literature. The catalyst’s structural, morphological, and surface characteristics were comprehensively validated through XRD, SEM, EDX, and BET analyses. The catalyst was evaluated under varying hydrogen peroxide doses and across an initial dye concentration range of 5 × 10⁻⁵ to 5 × 10⁻⁴ M. Increasing the H₂O₂ volume (3.5–20 mL, corresponding to H₂O₂ excess ratios of 17.5–100) significantly enhanced the oxidation rate, whereas higher dye concentrations reduced efficiency due to photon competition and partial saturation of catalytic sites. These experiments provided the basis for extracting kinetic parameters and assessing the mechanistic pathways governing the photocatalytic process. The kinetic behavior of indigo carmine degradation was evaluated by fitting the experimental data to zero-order, first-order, and second-order empirical models to identify the rate law that best describes the reaction. Reusability tests showed that MgAl–LDH maintains high activity over multiple cycles, with only a moderate decline, demonstrating its stability and suitability for practical wastewater treatment applications. Full article

Walkability measurement has expanded from a small set of generic neighbourhood-level proxies into a heterogeneous field of indices, scored audits, perceived-environment scales, route-based instruments, and context-specific assessment instruments. This expansion has improved the sensitivity of walkability research, but it has also made it increasingly difficult to judge which instruments are appropriate for different users, walking purposes, and urban or environmental contexts. This review addresses this problem by comparing operational walkability instruments through an adapted walking-needs framework derived from the Expanded Hierarchy of Walking Needs (HoWN). Publications from 1990 to 2025 were identified through a structured search and screening workflow covering general walkability measurement, population-sensitive instruments, purpose-specific instruments, climate- and exposure-sensitive instruments, and urban-form-specific instruments. After eligibility assessment and consolidation, 46 walkability instruments were retained for comparative analysis. For this review, the framework is adapted from a behavioural hierarchy into an instrument-level comparative structure, with feasibility re-specified as basic environmental passability. The instruments are then compared across five tiers: feasibility, accessibility, safety, comfort, and pleasurability. The review shows that walkability measurement remains strongly concentrated in lower-order and functionally measurable dimensions, especially pedestrian infrastructure, destination access, connectivity, and traffic safety. By contrast, comfort, pleasurability, environmental exposure, personal security, and user-specific constraints are less consistently formalised and often appear only in specialised instruments. Population-, purpose-, climate-, and urban-form-sensitive instruments do not merely add indicators; they alter which walking needs become foundational in specific assessment scenarios. This review contributes a fit-for-purpose comparative logic for walkability measurement. It shows how a shared walking-needs framework can be used to diagnose coverage imbalance, identify scenario-specific threshold conditions, and guide the selection, adaptation, and transfer of instruments across different users, walking purposes, environmental exposures, and urban forms. Full article