Search Results (12,823)

The Lower Anti-Atlas Supergroup (LAAS) constitutes a major Proterozoic sedimentary archive exposed along the northern margin of the West African Craton (WAC), yet its age, internal stratigraphy, and regional correlations remain controversial. This study integrates detailed sedimentological investigations, lithostratigraphic correlations, petrography, and new LA-ICP-MS U–Pb zircon geochronology from the Igherm Inlier (western Anti-Atlas, Morocco) to refine the evolution of the LAAS. Three representative stratigraphic sections allow subdivision of the succession into five lithostratigraphic units: the Coarse-Grained Quartz Sandstone, Lower Siliciclastic–Carbonate, Quartz Sandstone, Upper Siliciclastic–Carbonate, and Volcanic units. These units are correlated, from base to top, with the Tasserda Formation, Ifrane n’Taghatine Formation, Oumoula (Mimount) Formation, Tizi n’Taghatine Group, and Tachdamt Formation recognized elsewhere in the Anti-Atlas. Sedimentological data indicate deposition within a long-lived shallow-water system that evolved from tide-influenced braided fluvial channels, through mixed tidal-flat and peritidal platform environments, to extensional basaltic volcanism. Newly identified reworked volcanic tuffs from the Lower Siliciclastic–Carbonate Unit yield a maximum depositional age of 1857 ± 33 Ma, providing the first direct temporal constraint for this interval. Additional maximum depositional ages of 1880 ± 30 Ma for the Oumoula Formation and 1970 ± 29 Ma and 1904 ± 41 Ma for the Tizi n’Taghatine Group are consistent with previously published constraints. Detrital zircon populations with predominantly Paleoproterozoic and subordinate Archean dates were likely derived from the WAC. Correlation of zircon age spectra with those of the Taoudeni Basin supports the existence of extensive intracratonic depositional systems that evolved across the WAC during the Nuna and Rodinia supercontinent cycles, culminating in Tonian syn-rift magmatism represented by the ca. 883 Ma Tachdamt Formation. Full article

Bioenergy crops are widely regarded as a promising approach to support renewable energy production, diversify farm income, and enhance land-use efficiency. Despite these potential benefits, adoption rates remain low, and empirical understanding of landowners’ decision-making processes is still emerging. This study examines landowners’ interest in and likelihood of adopting bioenergy crops, explicitly differentiating between early-stage interest and near-term adoption intentions. Survey data from 207 landowners are analyzed using a bivariate probit model to identify key factors influencing both outcomes. The results reveal a marked disparity between expressed interest and adoption likelihood, with a significantly greater proportion of landowners indicating interest than those willing to adopt in the near term. Economic orientation increases adoption interest by 9.5 percentage points, while identity orientation increases adoption likelihood by 6.6 percentage points. Determinants such as increased awareness, land size, experience, and participation in conservation programs exert varying influences across different decision stages. These findings suggest that stated interest and stated near-term adoption likelihood represent related but distinct dimensions of adoption readiness, shaped by different economic, identity-based, and institutional factors. Effective promotion of bioenergy crops requires more than general awareness campaigns. Policies should combine financial incentives, technical assistance, market development support, and outreach strategies that present bioenergy crops as compatible with landowners’ economic goals, stewardship values, recreational uses, and long-term attachment to their land. Full article

Aeolian sand bodies unrelated either to coastal barrier systems of Holocene or earlier age or to modern beaches have been identified along the central New South Wales coast of southeast Australia. Some of these deposits cap headlands or are located above high sea-cliffs. Others lie below modern sea-levels, whilst one substantial dune field extends 12 km inland. Many of these have previously been interpreted as Early Holocene cliff-top dunes, the product of the migration of beach sands up aeolian sand ramps at the foot of the sea-cliffs of the region and onto the cliff tops. The rising sea-levels of the Middle Holocene eroded the ramps and cut off the supply of sand to the dunes, allowing them to stabilise. But re-investigation shows that these dune fields accumulated at times of low Quaternary sea-levels, with a particle-size distribution suggestive of an inland rather than a coastal origin. We therefore propose an alternative model for the accumulation of these features. At times of low sea-level, sediments exposed on the inner shelf were reworked onto the adjacent coast by onshore winds, where they accumulated in locations unconnected to the modern or the earlier Holocene coastal aeolian sedimentary regime. This model challenges the conventional story that the dominant glacial maximum winds across southeastern Australia were from the west (and thus offshore). This pattern of sediment accumulation and its associated wind regime may have been more stable (continuing for over 30 000 years) and more long-lived (repeated through at least the last two glacial cycles) than has previously been believed. Although the cliff-top dune model has been widely applied, we question its suitability in its type location and suggest a more cautious approach to its application elsewhere. We argue that the products of the landward aeolian reworking of sediment exposed on the continental shelf have been overlooked, despite their potential for the preservation of long-term environmental records. Full article

Temperature variability and weather-related fluctuations significantly affect the energy, agricultural, and industrial sectors that are highly sensitive to meteorological changes. These conditions may lead to financial losses caused by demand fluctuations and operational disruptions. This study aims to develop a fractional weather-derivative pricing model based on temperature dynamics by integrating the Ornstein–Uhlenbeck (OU) process, the classical Black–Scholes model (BSM), and the fractional Black–Scholes model (fBSM). Daily temperature data from 2016 to 2025 obtained from the Bandung Geophysical Station, West Java, Indonesia, were used as the basis of analysis. Temperature dynamics were modeled using an OU process, and parameter estimation was conducted using Ordinary Least Squares (OLS). The strike price was determined using Historical Burn Analysis (HBA), whereas weather-derivative pricing was performed using call and put option approaches under both the BSM and fBSM frameworks, incorporating the Hurst parameter to capture long-term memory effects. The results indicate that the fractional Black–Scholes model analytical solution is obtained using the Daftardar–Gejji Aboodh method. Furthermore, the OU process successfully captured daily temperature dynamics, yielding a Mean Absolute Percentage Error (MAPE) of 4.344% and a Root Mean Square Error (RMSE) of 1.396 C, indicating high predictive accuracy across both relative and absolute error measures. In addition, the fBSM consistently generated higher option values than the classical BSM, particularly under higher observed temperatures during the study period and at higher strike prices. These findings demonstrate that long-term memory significantly influences effective volatility and option valuation. This study is expected to contribute to the development of weather derivative models that more realistically represent temperature dynamics and to serve as a reference for weather derivative pricing, hedging, and decision-making, as well as for more measurable, systematic, and sustainable climate-related financial analysis using derivative pricing frameworks. Full article

Animal infectious diseases impose severe economic burdens on livestock industries, threaten wildlife populations, and compromise food security. Although vaccination remains the cornerstone of disease prevention, conventional vaccine platforms are often constrained by safety, efficacy, or manufacturing scalability. This narrative review provides a comprehensive analysis of the state of the art in herpesvirus-vectored vaccines for veterinary applications, focusing on five well-characterized alphaherpesviruses: Bovine herpesvirus type 1 (BoHV-1), Pseudorabies virus (PRV), Marek’s disease virus (MDV), Equine herpesvirus type 1 (EHV-1), and Duck enteritis virus (DEV). The intrinsic characteristics of herpesviruses, including large, stable genomes; the capacity for foreign gene insertion; broad host tropism; and the ability to elicit robust humoral and cellular immunity, are examined, and their performance is compared with that of traditional vaccine platforms. Key advances in vectored vaccine development are highlighted, from proof-of-concept studies to the creation of advanced multivalent constructs. These approaches demonstrate protective efficacy against a range of significant animal pathogens, including foot-and-mouth disease virus, porcine reproductive and respiratory syndrome virus, avian influenza virus, infectious bursal disease virus, and West Nile virus. The literature was identified through systematic searches of PubMed, Google Scholar, and Web of Science (1990–2026), followed by title/abstract screening and reference chaining. Future directions in vector engineering, mucosal delivery, and synthetic biology approaches are considered. Herpesvirus-vectored vaccines represent a versatile platform for enhancing animal health, supporting sustainable agriculture, and mitigating zoonotic risks. Full article

Background: Lung cancer causes more deaths than any other malignancy worldwide, accounting for 2.2 million new cases and 1.8 million deaths in 2020. Extracting structured clinical knowledge from unstructured French-language oncology records remains methodologically unresolved in Tunisian and Francophone healthcare systems, where validated natural language processing tools do not yet exist. This study examined the effectiveness of transformer-based named-entity recognition for automated clinical annotation of Tunisian lung cancer reports. Aim: The study aimed to (i) establish performance baselines for four transformer-based models on a publicly available thoracic radiology dataset, (ii) evaluate five models, including a French biomedical specialist, on a newly constructed Tunisian clinical corpus, and (iii) demonstrate prototype deployment feasibility for structured clinical decision support. Methods: An initial comparative study evaluated BERT, RoBERTa, BioClinicalBERT, and CamemBERT using the official RadGraph dataset partitions, which natively comprise a total of 600 annotated thoracic radiology reports distributed across a standardized 80/10/10 split. Subsequently, five models were evaluated on 200 manually annotated diagnostic reports from Mami Pneumo-Phthisiology Hospital, Tunis. For the Tunisian corpus, a five-fold cross-validation approach was implemented to ensure robust performance estimation, followed by final evaluation on a dedicated hold-out test set. All models were trained for a maximum of 10 epochs, with a learning rate of 5 × 10⁻⁵ and a batch size of 16. Results: Based on the initial comparative study on the RadGraph dataset, where RoBERTa was the top performer and achieved the highest F1-score of 0.873 (precision: 0.869, recall: 0.877), we evaluated its specialized biomedical variant, DR-BERT, on our Tunisian clinical dataset. DR-BERT demonstrated strong generalization on the hold-out test set with an F1-score of 0.824, outperforming the baseline RoBERTa (test F1: 0.791) and showing competitive performance relative to multilingual BERT (0.843 ± 0.005 in five-fold cross-validation). A prototype interface generated structured clinical summaries encompassing prior conditions, imaging modalities, and TNM staging. Conclusion: Language- and domain-adapted transformer models effectively extract structured clinical entities from French-language Tunisian lung cancer reports. DR-BERT’s superior generalization on unseen data confirms that biomedical pretraining in the target language is a key driver of robust performance in specialized French oncology text. This work establishes foundational infrastructure for NLP-driven oncology data management in Tunisia and comparable Francophone settings. Full article

Against the backdrop of global carbon neutrality, the cross-regional allocation of green electricity is pivotal for energy transition, yet its impact on inclusive economic growth and regional equity remains contentious. This study addresses the spatial welfare mismatch arising from large-scale power transmission in China. Utilizing provincial panel data from 2006 to 2022 and employing the staggered rollout of Ultra-High Voltage (UHV) lines as a quasi-natural experiment, we apply advanced econometric models, including CS-DID and Bartik instrumental variables, to identify causal effects. Empirical results reveal an asymmetric “cost-benefit separation” effect: while green electricity imports significantly bolster high-quality development (HQD) in eastern recipient regions, exports exert a drag on western provinces by triggering capital outflow, profit deprivation, and ecological load. Consequently, regional HQD gaps exhibit divergence rather than convergence. However, we find that fiscal ecological compensation acts as a critical moderating buffer, effectively reversing this trend and driving conditional convergence and sustainable regional development. Heterogeneity analysis further indicates that market-oriented electricity reforms and “East Data, West Computing” infrastructure mitigate these negative externalities. These findings underscore the necessity of shifting from a purely engineering-focused transmission model to an institutional framework centered on energy justice, offering actionable insights for achieving SDG 7 and SDG 10 synergies. Full article

The Gulf of Mexico, a geologically complex environment, supports mesophotic coral ecosystems, with reefs such as the Pinnacle Trend, Flower Garden Banks National Marine Sanctuary, the Florida Middle Ground reef system, and Pulley Ridge. Mountain Top Bank is a dome-shaped hardground feature located 60–150 m below the sea surface along the Mississippi–Alabama shelf. It appears to prolong the Pinnacle Trend towards the southeast, bridging the gap between mesophotic coral reefs east and west of the Mississippi Canyon. Shipborne high-resolution multibeam data (bathymetry, backscatter, and water-column) and an AUV photomosaic were collected over the site during several oceanographic expeditions. Data were analyzed and compiled into an ArcGIS geodatabase to produce the first benthic habitat map of Mountain Top Bank. The site is characterized by a network of outcrops and boulders interspersed within a predominately sandy environment. Different seabed features were correlated with the presence and abundance of a diverse array of biota across the phyla of Cnidaria, Porifera, Mollusca, Chordata, Echinodermata, and Rhodophyta. We found the benthic assemblage to be similar to those found at the Pinnacle Trend, supporting the hypothesis that Mountain Top Bank is part of the same reef system and acts as a topographic bridge between ecosystems on the east and west of the Mississippi Canyon. Full article

Agriophyllum squarrosum (L.) Moq. (sand rice) is a drought-tolerant psammophytic species with high potential as a climate-resilient food crop due to its nutritional value and adaptation to arid environments. This study evaluates morphometric and biochemical variation in seeds from five natural populations across the deserts of Kazakhstan to assess their breeding potential. Seed morphometric traits showed moderate variability (CVs of 4.71–17.98%), with strong positive correlations among seed length, width, and thousand-seed weight, indicating coordinated development. In contrast, biochemical traits, particularly amino acid composition, exhibited substantially higher variability (CV up to 174.9%), reflecting metabolic flexibility under different environmental conditions. Among the amino acids reliably quantified in this study, histidine was the most abundant, while cysteine, tyrosine, and alanine showed high variability. Total protein content remained relatively stable, reaching up to 34.96% in superior accessions. Multivariate analyses revealed significant population differentiation: Akt1 was the most distinct, whereas Alm1 exhibited superior seed size and mass. Weak correlations between morphometric and biochemical traits suggest their partial independence. Integrated multivariate evaluation identified Akt2 and Alm1 as the most promising populations for breeding. Overall, the observed variation highlights strong potential to select genotypes that combine improved seed size with favorable biochemical characteristics, based on the five amino acids quantified above the LOQ, thereby supporting breeding and domestication efforts. Full article

Recent advancements in structural engineering have driven the development of sophisticated damping mechanisms aimed at reducing the detrimental effects of structural vibrations. As a result, accurate numerical modeling and analytical evaluation have become essential for assessing structural stability and enhancing seismic resilience. This study introduces a model-updating framework to develop analytical constitutive models for structural damping systems. The proposed approach employs a genetic algorithm (GA) to calibrate model parameters by minimizing the discrepancy between analytical predictions and experimental responses. Experimental force–displacement hysteresis data and displacement time-history records are used at both the element and system levels for model calibration. The methodology is applied to a rubber isolator, a 10-story structure equipped with Pall friction dampers, and a 6-story structure with friction dampers to evaluate its performance under different dynamic characteristics and damping mechanisms. The results indicate that the proposed approach achieves very high accuracy, with prediction errors reduced to negligible levels for both force and displacement responses in all cases. Consistent performance is observed using both global and local displacement measures in friction-damped systems, indicating the robustness of the proposed method. Overall, the findings indicate that the GA-based model-updating framework provides an efficient and reliable tool for improving the predictive capability of analytical models of structures with nonlinear damping devices and is suitable for practical structural engineering applications. Full article

Investigating the spatial correlation characteristics and configurational pathways of ecological space service value (ESSV) is of importance for alleviating urban ecological pressure. This study, focusing on the northern slope of the Tianshan Mountains in China, employs the modified value equivalent method, gravity model, and configurational analysis model to elucidate the spatiotemporal evolution mechanisms of ESSV. The results demonstrate that: (1) The extent of ecological space decreased sharply (328.25 km²), primarily converting to other ecological space. Among these, the grassland ecological space experienced the largest reduction (215.34 km²), whereas the decline in forest ecological space was relatively modest (58.85 km²). (2) ESSV showed a fluctuating but overall increasing trend, with ΔESSV dominated by negative changes. Spatially, the pattern was characterized by higher values in the west, lower values in the east, and a contiguous high-value area in the central region. (3) The network of ESSV exhibited multiple connections and multiple cores, with the strength of network linkages continuously strengthening and showing a trend of expansion from the central region toward the south and north. (4) High ESSV depends on the configurational effects of multidimensional resilience factors. Several configurational modes were identified, including single-core resilience-driven and multi-dimensional resilience synergy-driven modes. Full article

This study investigated the impact of recreational use on trails in the Atlantic Forest (Ubatuba Municipality, São Paulo State, Brazil) using physical, chemical and geochemical indicators. Five trails with different morphological characteristics were selected, and paired samples were collected from the trail surface (TR) and trail-side slope (TA). The statistical approach combined local analyses for each trail with global clustering (n = 19) using Student’s t-test, along with multivariate modeling through Principal Component Analysis (PCA) and Pearson correlation. The analysis included physical attributes (bulk density, particle size and porosity), chemical attributes (pH, organic matter and macronutrients) and geochemical compositions (major oxides and trace elements determined by XRF). The overall results reveal systematic compaction in the trail surface (TR), with bulk density increasing from 1.32 g/cm³ (TA) to 1.37 g/cm³ (TR) (p = 0.038), and total porosity decreasing from 47.26% to 45.34% (p = 0.016). In contrast, the geochemical oxide composition (SiO₂, Al₂O₃, Fe₂O₃) remained stable (p > 0.05), indicating the resilience of the mineral matrix. However, significant local dynamics (p < 0.05) in K₂O and MgO were observed in more preserved trails, associated with surface compaction and fragmentation of the litter layer, and phosphorus showed strong dependence on organic matter (r = 0.85). Multivariate analysis indicates that degradation is predominantly physical and micromorphological at the local scale, with bulk density and porosity being the most sensitive indicators for environmental monitoring. Full article

The construction industry is characterised by high raw materials consumption and large waste generation. Upcycling waste construction materials offers an opportunity to reduce embodied carbon emissions while creating community assets. This paper examines how integrated design supports the effective reuse of waste materials from a modular building factory through the design of a community garden pavilion. Using Whole Lifecycle Assessment, the carbon impacts of three scenarios were evaluated. Case 1, the baseline scenario, represented the traditional temporary accommodation system using new materials with a hybrid steel–timber structure. Case 2 adopts new materials for the timber frame structure, combined with reused wooden pallets for the envelope. Case 3 represents an upcycling scenario where structural and envelope materials are reused from the modular building factory’s waste streams. Results show that the whole-life carbon emissions were 15,892.32 kgCO₂e for Case 1, 4293.25 kgCO₂e for Case 2, and 3044.99 kgCO₂e for Case 3, representing reductions of 73% and 81%, respectively, compared with the baseline. The findings demonstrate that integrated design and industrial material reuse can significantly reduce embodied carbon across a building’s life cycle. Recommendations for applying modular factory waste in community-led urban projects are provided. Full article

Slaughterhouse wastewater introduces potentially toxic elements into aquatic ecosystems, yet bioaccumulation patterns in commercial fish species and associated human health risks remain underexplored in West Africa. This study quantified zinc (Zn), lead (Pb), iron (Fe), magnesium (Mg), chromium (Cr), and cadmium (Cd) in three ecologically distinct fish species—Oreochromis niloticus (Nile tilapia), Clarias gariepinus (African sharptooth catfish), and Mugil cephalus (Flathead grey mullet)—from two slaughterhouse-impacted rivers (Transamadi and Mgbuosimini) and a control site (Iwofe) in Rivers State, Nigeria. Metal concentrations were measured using atomic absorption spectrophotometry. Two-way ANOVA assessed species and location effects. Principal component analysis (PCA) was performed, with Mg used as a potential geogenic tracer, as its loading pattern was independent of Pb and Cd and consistent with the natural background. A Water Quality Index (WQI) classified Mgboshimini and Iwofe as having poor water quality (WQI > 75), while Transamadi had medium quality. Health risks were evaluated using estimated daily intake (EDI), target hazard quotients (THQ), and hazard indices (HI) following USEPA guidelines. Metal levels varied significantly by species and location (p < 0.001). Flathead grey mullet from Mgbuosimini had the highest Pb (1.50 ± 0.05 mg/kg) and Cd (0.41 ± 0.02 mg/kg), exceeding EU maximum levels for fish muscle (Pb 0.30 mg/kg, Cd 0.05 mg/kg) by 500% and 800%, respectively. PCA explained 77.5% of the variance, with Pb and Cd clustering as anthropogenic sources, while Mg loaded independently. THQ for Pb approached unity in Flathead grey mullet (0.88), and THQ for Cd reached 0.97. HI exceeded 1.0 in all species from Mgbuosimini, peaking at 2.07 in Flathead grey mullet. Uncertainty analysis (using ±SD) gave a HI range of 1.89–2.25 for this species, all above the safety threshold. Carcinogenic risk for Flathead grey mullet (3.97 × 10⁻⁴) approached the upper acceptable limit. Slaughterhouse effluent appears to elevate Pb and Cd burdens in fish, with detritivorous Flathead grey mullet posing the highest health risk. Exceedance of safety thresholds and HI > 1.0 indicate potential non-carcinogenic and carcinogenic risks. We recommend improved wastewater treatment and species-specific consumption advisories. Full article

Introduction: Understanding population structure is essential for effective fishery management, and otolith shape analysis provides a robust framework for detecting spatial variation in marine fish populations. The bluefish (Pomatomus saltatrix), a commercially important and widely distributed species along the southeastern and southern Brazilian coast, may exhibit subtle population structuring that is still not fully resolved. Methodology: Otolith contour variation was analyzed using two complementary approaches: Elliptical Fourier Descriptors (EFD) and Wavelet Transformed Descriptors (WTD). A total of 75 individuals (25/site) were sampled from Rio de Janeiro, São Paulo, and Santa Catarina, with total lengths ranging from 33.2 to 45.5 cm. Multivariate analyses included Permutational Multivariate Analysis of Variance (PERMANOVA), pairwise Hotelling’s t-tests (HT²), Flexible Discriminant Analysis (FDA), and jackknife reclassification matrices (JKC). Results: For the EFD approach, PERMANOVA showed no significant differences among localities, while FDA revealed partial overlap among groups and a JKC overall reclassification accuracy of 46%. In contrast, the WTD approach detected significant spatial differences, with PERMANOVA indicating overall variation among localities and HT² identifying significant differences between Santa Catarina and the other regions. FDA improved visual separation of Rio de Janeiro samples, although the JCK accuracy decreased to 35%. Conclusion: The combined results suggest the presence of weak to moderate spatial structuring in P. saltatrix along the studied coastline. However, inconsistencies among analytical approaches and relatively low reclassification success rate to the original site indicate that the observed differentiation is insufficient to conclusively define distinct population units, remaining compatible with either a single stock exhibiting spatial heterogeneity or weakly differentiated subpopulations. Full article