Search Results (444)

The occurrence and concentration of potentially toxic elements (PTE) in fertilizers are a concern in tropical regions, and soil properties affect their bioavailability for crops. Cadmium is the most easily bioavailable for plants and so the food chain, and it represents a stepping-stone toward safe food production. So, this study aimed to evaluate the ionomics, metabolism, and growth of potato, tobacco, and rice in response to liming and to monoammonium phosphates (MAP) from different geographic origins and PTE contents (MAP 1, MAP 2, MAP 3). For this, independent experiments were conducted with each crop using MAP fertilizers as a phosphorus source applied to a Red-Yellow Latosol, with and without liming. Our findings indicated that physiological changes were primarily influenced by liming rather than PTE. Most acidic soils negatively impacted plant growth and sugar content and induced metabolic adjustments related to proline. The higher level of Cd in MAP 3 reduced manganese and zinc and increased sugar in plant shoots. Rice also had a lower Cd bioaccumulation than potato and tobacco, followed by a higher tolerance to acidic soil. The concentrations of As, Cd, and Cr present in fertilizers did not impair the growth and life cycle of the evaluated plants; however, metabolic adjustments were observed. Full article

This study introduces a deterministic fractional-penalty refinement of Vogel’s Approximation Method (VAM) for generating high-quality initial basic feasible solutions (IBFS) in classical transportation problems. Unlike the traditional additive regret measure employed in VAM, the proposed method uses a multiplicative contrast ratio between the two smallest admissible costs in each row and column. This modification preserves the allocation structure of VAM while introducing scale-invariant prioritization that improves sensitivity to relative cost differences.The method was evaluated on thirty-four benchmark transportation problems drawn from the literature and self-constructed large-scale instances (up to $10\times 20$). Performance was assessed using percentage optimality gaps relative to optimal solutions obtained via the Stepping–Stone and MODI procedures. Across all instances, the proposed approach achieved a mean optimality gap of $2.78\%$, compared to $5.22\%$ for classical VAM, $14.97\%$ for the Least Cost Method (LCM), and $45.78\%$ for the Northwest Corner Method (NWCM). Dispersion of deviations was also reduced, indicating improved robustness across heterogeneous cost structures Statistical validation confirms the improvement over VAM: the paired t-test yielded $t=-3.17$ ($p=0.00163$, one-sided), and the Wilcoxon signed-rank test produced $p=6.10\times {10}^{-5}$. Computational experiments further show that the refinement does not increase runtime relative to classical IBFS procedures.The proposed method therefore constitutes a structured enhancement of VAM that improves initial solution quality while maintaining computational simplicity. Full article

Coral reefs in the South China Sea (SCS) are critical for regional marine biodiversity and ecosystem services but face escalating threats from climate change and anthropogenic stressors. However, a holistic evaluation of habitat suitability spanning the distinct environmental gradients from low-latitude deep-water atolls to high-latitude marginal reefs remains limited. This study utilized high-resolution remote sensing data and the MaxEnt (Maximum Entropy) model combined with Principal Component Analysis (PCA) to systematically map potential habitat suitability and elucidate the multi-scale environmental drivers shaping the realized niche of SCS corals. The results revealed significant spatial heterogeneity characterized by a distinct “High South, Low North” latitudinal gradient, with Unsuitable areas dominating 85.5% of the study region, followed by Marginally Suitable habitats at 5.0%, while the northern Nansha Islands were identified as the core distribution area with the highest suitability and continuity. Minimum Phosphate (Min. Phos.) concentration and Sea Surface Temperature (SST) were identified as the core environmental factors determining the spatial distribution of coral reefs in the South China Sea. The optimal environmental ranges were identified as: SST between 28.52 °C and 29.41 °C, water depth shallower than 34 m, extremely low phosphate (0–0.005 mmol/m³), and low cumulative thermal stress (DHW < 0.83 °C-weeks). Crucially, PCA further quantified two potential climate refugia: low-latitude thermal refugia in the southern Nansha Islands, characterized by high environmental stability, and high-latitude marginal refugia in the Beibu Gulf, which offer physical buffering against warming, while necessitating targeted efforts to mitigate the risks of habitat degradation and eutrophication driven by intensifying anthropogenic activities These findings challenge the traditional conservation view relying solely on high-latitude migration, advocating for a climate-resilient spatial planning strategy that prioritizes strict protection of southern biodiversity source banks while enhancing the connectivity of northern marginal stepping stones. Full article

The watershed boundaries in arid and semi-arid regions are critical zones where ecological vulnerability and socio-economic development are in severe conflict. The upper and middle reaches of the Yellow River basin are a typical example of this dilemma. Intensive land use and human developmental interventions in this region have severely disrupted the integrity and balance of the ecosystem. While spatially designated, networked conservation areas can effectively promote the integrity and balance of regional ecosystems, these areas may fail to capture dynamic changes in vulnerability. This study develops a “functional diagnosis-structural diagnosis-integrated optimization” framework. It integrates various scenarios to diagnose vulnerability under uncertainty and identifies bottlenecks in ecological networks. For functional diagnosis, the coupling of the sensitivity–resilience–pressure (SRP) model and the Ordered Weighted Averaging (OWA) algorithm accurately locates vulnerable areas within the regional ecosystem. In terms of structural diagnosis, the Morphological Spatial Pattern Analysis (MSPA), Minimum Cumulative Resistance model (MCR), and Circuit Theory are integrated to identify structural bottlenecks. The main findings of this study are as follows: (1) Functional Diagnosis: The coupling of SRP and OWA reveals the non-linear vulnerability responses to policy preferences and identifies areas that consistently exhibit functional vulnerability across different scenarios. (2) Structural Diagnosis: The circuit theory combined with MSPA and MCR analysis identifies 72 ecological pinch points. These bottlenecks represent the weakest structural nodes crucial for maintaining regional ecological robustness. (3) Coupled Delineation and Differentiated Restoration Strategies: High vulnerability areas identified by SRP and consistently vulnerable areas identified by OWA are combined to delineate four distinct ecological restoration units: Alpine Fragile Matrix Unit, Loess Hilly Soil Conservation Unit, Anthropogenic Pressure Pinch Point Unit, Key Structural Stepping Stone Unit. Differentiated ecological restoration strategies are proposed based on the varying sensitivity, resilience, and pressure characteristics of these units. The “functional-structural” coupled ecological vulnerability evaluation framework can precisely identify vulnerable areas. The delineated restoration units and their corresponding restoration strategies provide reference and supplementation for the protected areas system, offering transferable tools for enhancing regional ecological efficiency. Full article

Climate change is radically altering the Earth’s natural ecosystems, with temperature/precipitation alterations resulting in mismatches between specific ecosystems and their ‘new’ climatic profiles. Without political action to curb greenhouse gas emissions, most plant/animal species will need to move to higher latitudes to ensure survival. Many are incapable of migrating rapidly and will thus be reliant on human intervention to relocate to new regions (assisted migration). The first hypothetical steps of assisted migration are explored here, using the UK as a model. Urban parks/gardens have a history of hosting non-native plant species and could be used to test the validity of moving non-native plants and animals to regions of higher latitude. In this perspective paper, we added a small experimental component to examine public attitudes to species introductions into urban parks/gardens. Results showed support for using parks and gardens to protect both UK native and non-native wildlife. Indeed, >50% of respondents favoured utilising urban landscapes to conserve small non-native animals (e.g., tortoises and bee-eaters). These results imply there may be some public acceptance of assisted migration. Thus, the paper explores the potential to develop novel, but more sustainable ecosystems in new localities. Full article

A high-resolution flat-field grating spectrometer has been employed at the Livermore EBIT-I electron beam ion trap for observations of extreme-uv spectra of Ni-like ions Xe²⁶⁺ and Co-like ions Xe²⁷⁺. Multistep ionisation involving the long-lived 3d⁹4s ³D₃ level in the Ni-like ion as a stepping stone has a significant influence on the charge state distribution at a given electron beam energy, as has been reported elsewhere. Complementing those observations of 3d-4s $E2$ and $M3$ transitions from long-lived levels, the present report shows spectra of 3d-4p and 3d-4f $E1$ transitions that arise from the decays of short-lived levels in both ions and their neighbouring ions of higher charge states and provide bright reference signals for the changes in the charge state distribution. Their observation is serendipitously furthered by the visual absence of 3d-4d transitions from the observed spectra, although $M1$ and $E2$ transitions between these configurations are permitted. Full article

Processes for generating clean hydrogen from waste plastics through thermochemical methods such as pyrolysis and gasification are a promising solution for both waste management and clean energy initiatives. Then, this derived hydrogen powers the fuel cell, which produces electricity that can be directly fed to charge electric vehicles (EVs). Although this complex process has many challenges related to energy efficiency during the conversion processes—starting from the generation of hydrogen from thermochemical processes and hydrogen storage and followed by fueling the fuel cells and charging EV infrastructure—the simplistic conceptual modeling developed for this research demonstrates how an ecosystem of such processes can be made feasible commercially. Clean hydrogen generated using known techniques reported in the literature is promising for commercialization, but harnessing hydrogen from plastics offers additional benefits, such as reducing greenhouse gas (GHG) emissions. Overall, the feasibility of clean hydrogen using this methodology is not limited by potential cost inefficiencies, especially when savings from GHG emissions reduction are taken into account. EVs have become commercially viable thanks to high-energy-density Li-ion batteries. And therefore, research continues to optimize charging performance through the integration of renewable energy and battery storage systems. This study examines another potential of clean hydrogen: its use as a power source in grids, especially V-2-G (vehicle-to-grid) systems. Additionally, direct current (DC) power from a fuel cell powers an EV charger at DC input voltages for e-ambulances. In particular, this designed system operates on DC voltages throughout the power system, combining high-voltage direct current (HVDC) lines, renewable energy sources, DC-DC converters, DC EV chargers, and other supporting components. The literature review identified gaps in plastics production, waste management, and processes for converting them into useful energy. The presented model is a stepping stone towards a novel, innovative process for clean hydrogen production to power electric vehicle charging infrastructure for emergency response systems in healthcare, thereby improving public safety. The limitations of the study would be governed by the effective establishment of locations where waste management services are performed (for example, landfills) and adoption by local government authorities with deregulated power systems. Full article

Real-time trajectory forecasting for curling stones is essential for on-ice decision support, yet prior work often emphasizes offline analysis, fixed-window predictors, or physics-driven models that require additional measurements, and it rarely reports end-to-end feasibility under edge-computing constraints (latency and memory). This leaves a practical gap between accurate trajectory reconstruction and deployable rink-side guidance. To bridge this gap, we propose an online forecaster based on low-dimensional $(x,y)$ coordinate streams and a lightweight attention-enhanced Long Short-Term Memory (LSTM) architecture optimized for edge devices. The model uses a four-second sliding window (240 frames at 59.94 Hz) to predict fifteen seconds of future positions (900 frames) in a single multi-step forward pass, and an overlapping publication scheme is adopted to retain longer temporal context and stabilize continuous updates. We further provide a TensorFlow Lite (TFLite) conversion and quantization workflow to support on-device inference. Quantitatively, experiments on the CurlTracer dataset (1033 throws at 59.94 Hz) show that the proposed attention–LSTM achieves trajectory-level MAE/MdAE of 0.25/0.22 m over the full prediction horizon, improving over a plain LSTM (0.30/0.24 m) and a physics-based pivot-slide baseline (3.52/3.54 m). At two checkpoints, the first-step MAE/MdAE are 0.14/0.11 m and the mid-step MAE/MdAE are 0.21/0.18 m. For real-time feasibility, on a Raspberry Pi 4B the per-window latency is approximately 0.25 s (including I/O and post-processing), while CPU benchmarks show that TFLite variants provide 7–8× speedups over the original Keras runtime with only minor accuracy loss (e.g., window-level MAE 0.30–0.41 m across FP32/DRQ/FP16/INT8). Qualitatively, representative trajectory visualizations show good agreement in near/mid horizons and reasonable stopping-region guidance, supporting integration with a stone-mounted interface for actionable feedback. Full article

Heritage Building Information Modeling (HBIM) is accelerating the transition from reactive restoration to preventive conservation in architectural heritage management. Nevertheless, research at the heritage-cluster scale remains limited, particularly in terms of multi-source data integration, dynamic value–risk coupling, and lifecycle-oriented decision support. This study proposes an intelligent HBIM-based framework designed to support integrated data processing, automated value–risk assessment, and preventive intervention planning for masonry heritage clusters. The framework is validated through its application to the Suopo Ancient Watchtower Complex in Danba, Sichuan, consisting of 84 polygonal stepped-in stone towers. By integrating 3D laser scanning, unmanned aerial vehicle (UAV) oblique photogrammetry, and historical archival data, a closed-loop workflow is established, spanning data acquisition, parametric semantic modeling, and intervention prioritization. A dedicated parametric component library and hierarchical semantic database tailored to irregular polygonal masonry significantly enhance modeling consistency, semantic coherence, and cross-building reusability. Leveraging the Revit Application Programming Interface (API) and Dynamo, the framework embeds a value–risk model (P = V × R), enabling automated component-level evaluation, real-time visualization of conservation priorities, and one-click generation of intervention lists. Results demonstrate improved modeling accuracy, efficiency, and decision reliability compared with conventional manual workflows. The framework offers a scalable and replicable pathway for sustainable conservation of masonry heritage clusters in high-seismic regions and provides a foundation for future integration with IoT-enabled digital twin systems. Full article

Habitat loss and fragmentation threaten forest-dependent ungulates in subtropical mountain systems, yet integrative assessments linking habitat quality and landscape configuration remain limited. Here, we evaluated habitat suitability and identified core habitat patches for the endangered black muntjac (Muntiacus crinifrons) in Tongboshan National Nature Reserve using an Analytic Hierarchy Process–Habitat Suitability Index (AHP–HSI) framework integrated with camera-trap validation and landscape pattern analysis. Vegetation-related indicators (NDVI and vegetation type) were the dominant suitability drivers, and highly suitable habitats accounted for 62.9% of the reserve (8646.97 ha), forming three major forest blocks with low disturbance levels. Camera-trap detections (n = 58) showed strong concordance with model predictions (98.28% within moderately suitable or higher classes). Landscape metrics revealed contrasting spatial configurations between overall high-suitability habitats and optimal core patches, indicating that demographic source areas are embedded within fragmented peripheral mosaics. Medium patches and forested ridges may function as potential stepping stones and corridors facilitating movement across habitat clusters. These findings highlight the importance of maintaining functional connectivity and mitigating edge disturbances in buffer and experimental zones to ensure long-term population persistence and effective protected-area management for forest ungulates. Full article

This paper explores the complex interrelationships between biomass composition, thermochemical conversion pathways, carbon yield and other characteristics in order to expand the knowledge for biomass conversion processes and adapt them to specific requirements. A comprehensive characterization, chemical and thermal analysis of peach stone biomass, was performed. Thermogravimetric analysis, elemental analysis and low-temperature nitrogen sorption were also carried out in order to establish the composition and textural characteristics of the precursor material and obtained product. Carbon adsorbents were obtained from the studied biomass precursor under different conditions via one-step hydro-pyrolysis process by using steam activation at 800 °C. After research was conducted, it was established that cellulose is the main component, which influences the quantity and quality of the obtained adsorbent. The high content of hemicellulose reveals peach stones as a good candidate, especially for hydrothermal carbonization. High cellulose content (40%) in the biomass precursor is a prerequisite for the formation of porous texture in carbon adsorbent during hydro-pyrolysis. It was also shown that the carbon yield (26.70%) can be predicted and is highly dependent on the precursor composition. These results highlight the potential of peach stones as a valuable precursor for the production of sustainable, high-performance carbon adsorbents for environmental remediation. Full article

As in adults, urolithiasis is a significant health problem in children from an early age, having a very negative impact on health and quality of life and potentially leading to kidney function impairment. The occurrence of deposits in the urinary tract in a child is almost always the result of significant predisposing factors, including metabolic defects involving the kidney or the entire body (often inherited in a Mendelian fashion), urinary tract defects, or urinary tract infections. Among metabolic disturbances, idiopathic hypercalciuria, preceded by hypocitraturia, is the most common one. Any child with nephrolithiasis requires a careful metabolic evaluation, including blood tests, urinalysis, and, in many cases, molecular diagnosis. This narrative review presents the epidemiology, pathophysiology, and diagnostic process in children with nephrolithiasis. Special emphasis is put on pathophysiological pathways leading to metabolic kidney stone disease and metabolic diagnostic steps in children with urolithiasis, as metabolic disturbances are the most common cause of recurrent urolithiasis in Europe and North America. Nephrolithiasis should be treated as a symptom of renal or systemic disorders, and in every child, the cause of these disorders should be sought to prevent recurrence. Full article

Converting agricultural solid waste into porous biochar for HCHO adsorption is considered as a “two birds with one stone” strategy, which can achieve the environmental goal of “treating waste with waste”. Unfortunately, the HCHO adsorption performance of pristine biochar is generally unsatisfactory, which is derived from its poor surface activity and insufficient number of pores. In this study, a series of nitrogen-doped porous biochars with adjustable N-containing groups and porosity were synthesized by one-step pyrolysis of melamine and waste jujube pit in different mass ratios (NBC-x, x represented the mass ratio of melamine to waste jujube pit, x = 4–12) for HCHO adsorption. The HCHO adsorption tests indicated that the insertion of nitrogen-containing species improved the adsorption capacity of pristine biochar (BC). However, after the insertion of excessive nitrogen-containing species, the porosity of the samples significantly decreased due to the blockage of pores, which could be disadvantageous for HCHO adsorption. DFT calculation results showed that N doping (especially pyrrolic-N) significantly increased the maxima of absolute ESP values of the carbonaceous models and consequently enhanced the affinity between polar HCHO and carbonaceous models (varied from −20.65 kJ/mol to −33.26 kJ/mol). Thus, the NBC-8 possessing both substantial nitrogen content (19.81 wt. %) and developed porosity (specific surface area of 223 m²/g) exhibited the highest HCHO uptake of 6.30 mg/g. This was approximately 6.4 times larger than that of BC. This work not only deepens the understanding of the HCHO adsorption mechanism at molecular scale, but also concurrently offers a facile and eco-friendly route of N-doped porous biochar preparation, an efficient technology with high-value utilization of waste biomass resources, and a sustainable method of pollution remediation. Full article

The past decade has seen significant advancement in our understanding of DNA replication-coupled chromatin assembly, especially parental histone recycling that is essential for epigenetic inheritance. Leading strand-specific and lagging strand-specific pathways have been found to promote the transfer of parental histones H3-H4 to nascent DNA. It is now clear that the replisome initially characterized as the machinery that carries out the duplication of genomic DNA is also responsible for parental histone recycling. A series of replisome components including CMG (Cdc45-MCM-GINS) replicative helicase, DNA polymerases Polε, Polδ, Polα-primase, and FPC (Fork Protection Complex) that promote parental histone recycling exhibit histone-binding activities. Structural analyses of native and reconstituted replisomes, together with AlphaFold modeling of histone (H3-H4)₂ tetramer binding by replisome components, provided a framework for understanding the molecular mechanisms of parental histone recycling. A working model has emerged in which the mobile histone chaperone FACT (Facilitates Chromatin Transcription) binds parental histone (H3-H4)₂ tetramer or (H3-H4)₂-(H2A-H2B) hexamer on the front of the replication fork, and escorts it across the replisome to the daughter strands in the wake of the replication fork. In this model, parental histones transiently associate with the histone-binding modules in the replisome as steppingstones during their movement. Future studies are needed to elucidate the spatiotemporal coordination of the functions of replisome factors in parental histone transfer. Full article

The digitization of historic architecture increasingly relies on dense point clouds, yet the conversion of these datasets into structured Historic Building Information Models (HBIM) remains slow, inconsistent, and heavily dependent on manual interpretation. This paper introduces a classification-driven, mesh-based semi-automated workflow designed to close this gap by providing a controlled, repeatable path from raw TLS data to BIM-ready geometry. The method combines three elements strategically integrated into a unified framework: (1) pre-classified point cloud groups that establish a structured starting point, (2) mesh simplification and slice-based geometric reconstruction executed through Rhino and Grasshopper, and (3) direct BIM integration using Rhino.Inside.Revit to generate categorized HBIM components rather than passive mesh imports. The workflow is validated on an irregular exterior stone column from the historic chapel in Sopronhorpács, Hungary, an element characterized by surface erosion, asymmetric profiles, and deviations from verticality. This type of geometry typically challenges both manual modeling and fully automated shape-fitting. The proposed method reconstructed the column as a Revit Structural Column element with a substantial reduction in modeling time compared to a manual Scan-to-BIM workflow. A deviations analysis confirmed that the reconstructed geometry remained within the millimeter-level accuracy required for conservation-grade documentation. The study demonstrates that combining element-based classification, mesh preprocessing, and controlled semi-automation can significantly improve both the speed and reliability of Scan-to-HBIM processes without requiring technical expertise yet delivers results that align with the precision expected in scientific documentation. By formalizing the Pre-Classified Modeling Logic (PCML), the approach provides a foundation for reconstructing a wide range of heritage elements and establishes a practical step forward toward more efficient, interpretable, and accessible digital preservation practices. Full article