Search Results (42,504)

Land use planning in the Black Soil Region of Northeast China must be sustainable, taking into account food security, water use, GHG emissions, and economic returns. Current crop suitability mapping and single-objective optimization studies tend to analyze crop occurrence, crop structure, and spatial allocation independently, which is of little value in spatial planning. In this study, a three-stage integrated approach is proposed, involving deep learning crop occurrence mapping, multi-objective crop structure optimization, and suitability-guided spatial allocation. During Stage I, a lightweight U-Net semantic segmentation model, BlackSoilCropNet, is developed to provide per-pixel occurrence probabilities of rice, maize, soybean, and other types of crops based on Sentinel-2 time series and auxiliary environmental predictors. In stage II, NSGA II will optimize the area structure of the crops and reduce water consumption and GHG emissions with the maximum profit under the constraints of the cropland, water, and production. Selected Pareto optimal solutions are transformed to crop allocation maps and transition hotspot outputs in Stage III. The framework resulted in three viable planning options. The economic priority scenario resulted in the highest profit (USD 27.9 billion), with higher water consumption and emissions. The environmental-priority scenario resulted in a reduction in water use to 118.2 × 10⁹ m³ and emissions to 50.9 MtCO₂e, but at the cost of lower production and profits. There was a balance between economic stability and an improved environment in the balanced scenario. The framework provides a reproducible, geospatial decision support approach for sustainable farming planning and black soil conservation overall. Full article

Elucidating the response mechanisms of C-, N-, and P-cycling enzyme activities within soil aggregates to tea plantation age can provide a theoretical foundation for improving soil fertility, safeguarding soil health, and promoting the sustainable use of soil resources in tea plantations. In the present study, soil samples were collected from the 0–20 cm layer of tea plantations with different ages (3, 9, 16, and 24 years). Then, soil samples were separated into >2, 2–1, 1–0.25, and <0.25 mm aggregate size fractions using an optimal moisture sieving method, and the activities of β-glucosidase, invertase, urease, protease, and acid phosphatase were measured in each fraction. Across all tea plantation ages, the aggregate composition was dominated by the >2 mm fraction, whose content was significantly (p < 0.05) higher than that of other size fractions, averaging 54.47%. With increasing plantation age, the content of >2 mm aggregates first increased and then decreased, reaching a relatively high level at 16 years. The activities of β-glucosidase, invertase, urease, and protease in the tea plantation soils were predominantly distributed in the >2 mm aggregates, with average activities of 261.34, 585.31, 52.24, and 84.34 mg kg⁻¹ h⁻¹, respectively; in contrast, acid phosphatase activity was less affected by aggregate size. As plantation age increased, the activities of β-glucosidase, invertase, urease, and protease initially increased and then decreased, reaching relatively high levels at 16 years (322.98, 696.66, 67.00, and 100.98 mg kg⁻¹ h⁻¹, respectively), whereas acid phosphatase activity progressively increased with age. During the aggregate fractionation process, all enzyme activities were lost to varying degrees, with average recovery rates of 80.45% (β-glucosidase), 83.13% (invertase), 80.78% (urease), 82.16% (protease), and 81.66% (acid phosphatase). As the primary carriers of soil enzymes, the formation and stabilization of >2 mm aggregates are of great importance for promoting soil organic C and nutrient cycling. In tea plantation management, therefore, attention should be directed to the breakdown and disruption of >2 mm aggregates after 16 years of cultivation to maintain soil quality and sustain soil organic C and nutrient use efficiency. Full article

Surface functionalization of metallic implants is widely explored to enhance their performance and functionality. In this study, multifunctional hydrogel coatings based on poly(vinylpyrrolidone) and polyethylene glycol were developed and functionalized with a taxifolin (TAX) inclusion complex and collagen to introduce bioactive features. TAX, a naturally occurring flavonoid with antioxidant and anti-inflammatory properties, was incorporated using β-cyclodextrin to improve its stability and enable controlled release. The coatings were applied to titanium-hydroxyapatite composites and titanium sheet substrates to evaluate their applicability across surfaces with varying morphologies, ranging from porous to relatively smooth. The ceramic phase was modified with magnesium ions to enhance its bioactivity and better mimic the composition of natural bone tissue. FTIR and SEM analyses confirmed hydrogel formation and effective surface coverage. Degradation and incubation studies in simulated physiological environments demonstrated the material’s stability, while UV–Vis analysis indicated TAX release, highlighting the system’s potential as a carrier for flavonoid-based compounds. Indirect cytotoxicity studies using MC3T3-E1 preosteoblasts indicated low cytotoxicity and a favorable biological response of collagen- and taxifolin-modified systems. The developed coatings represent a versatile platform for surface modification of titanium-based biomaterials and demonstrate potential for application across substrates with diverse surface characteristics. Further studies are required to assess their biological potential. Full article

This study examines how energy-security shocks shape macroeconomic resilience in import-dependent economies and which energy-management strategies remain robust under alternative shock conditions. Using a balanced panel of 18 mainly European energy-importing economies and Türkiye for 2000–2024, the study constructs a Macroeconomic Resilience Index (MRI) from five dimensions: GDP growth, inflation, unemployment, current account balance, and industrial production growth. Inflation and unemployment are treated as inverse resilience indicators, and a Principal Component Analysis (PCA)-based alternative index is used as a robustness check. Methodologically, the study develops a hybrid framework that first applies a Shock-Augmented Cross-Sectionally Dependent Panel Quantile ARDL model to estimate heterogeneous shock effects across resilience levels, and then translates the econometric evidence into a Shock-Conditioned Bayesian Network–Regret MCDM model for strategy prioritization. The findings show that exchange-rate pressure is the most consistent long-run vulnerability channel, while energy intensity weakens resilience across short-run, benchmark, and quantile robustness results. The renewable energy share supports resilience under some conditions, but its effect depends on complementary investments in storage, grid flexibility, and demand-side capacity. Scenario results indicate that exchange-rate pressure produces the weakest resilience profile. The positive MRI value observed during combined-crisis years should be interpreted cautiously, as additional sensitivity evidence indicates that it mainly reflects the 2021–2022 post-pandemic rebound rather than a beneficial effect of shocks. Bayesian Network results identify macro-financial stabilization, import-dependency reduction, energy efficiency, and grid reliability as key resilience drivers. The regret-based MCDM results rank energy efficiency improvement as the most robust strategy, followed by energy import diversification. The study contributes by linking dynamic macroeconometric shock analysis with probabilistic scenario modeling and regret-sensitive decision support, offering an evidence-informed framework for prioritizing energy-security strategies in the sampled import-dependent economies. Full article

Polyvinyl alcohol (PVA)/chitosan (CS)-based films incorporated with Antrodia cinnamomea polysaccharide (ACP) and tea tree essential oil (TTEO) were developed using a solution casting method. The physicochemical, bioactive, and structural attributes, as well as the effects of these films on post-harvest ‘Yuluxiang’ pears, were assessed. The results demonstrated strong interactions among all functional components. The integration of ACP reinforced the mechanical properties of PVA/CS-based films, whereas the combined incorporation of ACP/TTEO enhanced water resistance, ultraviolet-light shielding ability, and barrier performance against oxygen and water vapor. Contact angle measurements showed that the PVA/CS/ACP/TTEO composite film exhibited superior wettability and adhesion to pear surfaces. Furthermore, the PVA/CS/ACP/TTEO composite film exhibited potent antibacterial activity, recording 99.99% inhibition against Staphylococcus aureus and 99.91% against Escherichia coli. TGA and DTG analyses suggested that ACP improved the thermal stability and restricted the film’s degradation rate. Antioxidant assays revealed that the incorporation of ACP and TTEO markedly elevated the antioxidant ability of the PVA/CS-based film. After 21 days of storage, the PVA/CS/ACP/TTEO composite film effectively maintained firmness, titratable acidity, vitamin C levels, and the activities of superoxide dismutase and catalase in post-harvest pears. Moreover, the composite film delayed fruit yellowing and oiliness, lowered the accumulation of hydrogen peroxide and malondialdehyde, and significantly reduced microbial counts (p < 0.05). This study demonstrates that the fabricated PVA/CS/ACP/TTEO composite film possesses the ability to extend the shelf life of perishable fruits under ambient storage conditions. Full article

Ensuring face stability is a pressing concern in slurry shield tunneling under high water pressure. Although slurry infiltration and filter cake formation are known to affect stability, the governing role of seepage forces in the failure mechanisms remains insufficiently understood, and existing models often oversimplify the regulating effect of filter cake permeability. To address this gap, a combined numerical–theoretical approach is developed that explicitly incorporates seepage effects into the failure analysis. A three-dimensional seepage model was developed to simulate transient pore water pressure distribution ahead of the tunnel face, considering filter cake properties, stratum permeability, and applied slurry pressure. Based on the computed seepage field and a wedge-prism composite failure mechanism, an upper-bound limit analysis model was formulated that accounts for the work done by seepage forces. Results reveal a filter cake permeability threshold of 1.0 × 10⁻⁷ m/s, below which further reduction yields negligible stability improvement. Parametric studies quantify the influences of internal friction angle, cohesion, depth-to-diameter ratio, and permeability contrast between soil and filter cake. Validation against field data from the Maliuzhou Tunnel demonstrated that the calculated limit pressures consistently lie below the field-measured slurry pressures, confirming the model’s reliability and its practical utility for guiding slurry pressure selection in complex ground conditions. Full article

Roadside LiDAR is a key sensing technology for intelligent transportation systems (ITSs) due to its high-precision spatial information and reliable monitoring of traffic environments. However, extracting traffic information from LiDAR point cloud data remains challenging because measurements are produced through angular sampling, causing the spacing between adjacent points to depend on radius and beam distribution. This study proposes a geometry-aware framework that incorporates LiDAR sampling geometry into the neighborhood criterion used to determine point-to-point association. The formulation defines neighborhood tolerance as a function of radial distance and vertical angular separation, enabling clustering decisions that are consistent with the sensing mechanism. In addition, the approach integrates deployment constraints based on sensor mounting height and region-of-interest limits to maintain physically meaningful connectivity under roadside sensing conditions. A systematic calibration procedure is conducted to estimate the scaling factor and radial spacing parameters and evaluate the method using both controlled and real-world datasets. Experimental results reveal that the proposed approach improves clustering accuracy and stability by reducing false negatives in sparse regions while avoiding excessive cluster merging in dense areas. The method demonstrates robust performance across varying sensing conditions and achieves higher accuracy than baseline approaches without parameter retuning, while introducing negligible computational overhead. Full article

To address the issues of thermal non-uniformity and insulation aging of converter transformers operating under long-term high electric field and high-temperature conditions in ultra-high-voltage direct current (UHVDC) transmission systems, this paper investigates the temperature field distribution characteristics of converter transformers based on electro–thermal–mechanical multiphysics coupling. By establishing a full-scale multiphysics simulation model of a ±800 kV converter transformer, the interactions among the electric field, temperature field, and mechanical stress field are comprehensively considered. The temperature gradient distribution and hotspot formation mechanisms within the valve-side winding and the lead-out structure are revealed. The results show that the internal temperature distribution of the converter transformer is non-uniform, resulting in a nonlinear distribution of material parameters in oil-paper insulation, which significantly affects the insulation performance. The research findings provide a theoretical basis and engineering reference for the structural optimization and thermal stability improvement of the main insulation system of converter transformers. Full article

Atmospheric CO₂ concentrations have reached significant levels during the industrial era, necessitating the implementation of effective carbon dioxide removal (CDR) technologies. Enhanced Rock Weathering (ERW) using basalt has emerged as a high-potential strategy, leveraging its mafic composition to sequester CO₂ as stable carbonates. This review analyzes ERW’s geochemical processes, application methods, and multifaceted co-benefits, such as restoring “background fertility” and improving soil structure. The literature indicates that while small-scale applications range from 1.5 to 6 Mg·ha⁻¹·yr⁻¹, intensive agricultural rates typically reach 40–100 Mg·ha⁻¹·yr⁻¹. Global models estimate a sequestration potential of up to 4.9 × 10⁹ Mg CO₂·yr⁻¹ for basalt, although field-scale results vary significantly, reaching uptake rates of up to 4 Mg CO₂·ha⁻¹ depending on pedological conditions and crop types. Despite this promise, transitioning to large-scale deployment faces critical hurdles, including operational difficulties in mechanized spreading and a scarcity of audited, long-term field data. Future research must prioritize standardized protocols and comprehensive economic analyses to bridge the gap between theoretical models and empirical evidence. Ultimately, ERW represents a multifaceted solution for climate stabilization and sustainable food security, provided that sequestration efficacy and environmental safety are rigorously verified through high-application field trials. Full article

There is an enormous rise in the amount of user-generated content on social media. That makes it easier for hateful and fake messages to spread, and threatens both societal stability and public trust in institutions. Most of current solutions have fundamental limitations due to modal limitations (i.e., each solution only uses one type of data at a time), lack of user context integration, poor synchronization across different types of data, and poor resilience to manipulation by adversaries. As a result, most solutions are subject to compound loss in terms of their ability to generalize well, classify correctly, or remain reliable when deployed in real-world environments. To address all of the above challenges, we propose a comprehensive and modular analytical framework consisting of five interconnected components that integrate contextual representation learning, multimodal semantic alignment, graph-based propagation modeling, adaptive inference, and consistency validation for hate speech and fake post detection. First is our Context-Driven Social Vector Extraction methodology, which provides enriched contextual embeddings by extracting and combining text-based metadata, image-based metadata, temporal metadata, and behavioral metadata. We use those embeddings in our second module, Multimodal Label Fusion via Mutual Co-Attention (CMF-MCA). Our CMF-MCA module incorporates two transformers with co-attention mechanisms that can mutually annotate text and images. In our third methodology, Semantic Propagation Graph for Hate and Fake Correlation (SPG-HFC), we implement a relational graph attention mechanism that captures both the influence of semantics and how communities propagate information about hate and fake posts. The fourth module, Adaptive Modality Routing via Reinforcement (AMR-R), routes based on the modality of the input and whether the input is simple enough to be classified using machine learning or complex enough to require deep learning. Finally, our Counterfactual Consistency Validation Engine (CCVE) is used after prediction to validate that the model’s predictions are consistent with the output data by creating counterfactuals and validating them. Therefore, in addition to improving the overall accuracy of hate speech and fake post detections, our proposed framework also improves its scalability and inference reliability. Additionally, because our framework allows multimodal classifications that include both context and behavior, it enables the scalable and trustworthy development of content moderation systems. Full article

Gravel soil used as backfill behind rockfall barriers in mountainous roads can extend structural service life and support sustainable resource utilization. However, rainfall-induced erosion may cause soil loss and reduce its buffering capacity. The fibers are short discrete fibers with a length of approximately 12 mm and an average diameter of 32.7 μm, corresponding to an aspect ratio of approximately 367. Reinforcement is achieved through fiber–soil interaction mechanisms, including particle bridging, interfacial friction, and pull-out resistance. The effects of polyurethane and fiber contents on compressive strength, shear strength, and impact resistance were evaluated using response surface methodology. Scanning electron microscopy was used to examine the microstructural features associated with the reinforcement mechanisms, and engineering-scale model tests were conducted to assess erosion and impact resistance under representative service conditions. The results show that polyurethane and fibers produce significant nonlinear enhancement effects on the mechanical properties of gravel soil, mainly through their individual contributions, whereas their interaction is limited. Multi-objective optimization indicates that the optimal mixture contains 6.8% polyurethane and 0.19% fiber, with prediction errors below 5%. The unconfined compressive strength of the gravelly soil increased from 107.6 kPa to 931.5 kPa, representing a 765.7% increase. Cohesion increased from 23.4 kPa to 83.44 kPa, representing a 256.4% increase. The internal friction angle increased from 43.4° to 61.23°, corresponding to a 41.08% increase. Under 1 h of intense rainfall erosion, the stabilized soil exhibited only slight surface particle detachment and maintained overall integrity. In impact tests, the velocity attenuation rate reached 65.6–71.4%. The proposed material provides a sustainable solution for improving buffer layers in rockfall barriers. Full article

Daunomycin (daunorubicin) is one of the most clinically significant anthracyclines used in chemotherapy, and its efficient production remains a major objective for biotechnological researchers. Industrial manufacturing relies on the fermentation of Streptomyces peucetius and Streptomyces coeruleorubidus, which produce daunomycin as a secondary metabolite under controlled conditions. This review will focus on the methods to enhance the total efficiency of biotechnological production, from upstream biosynthesis to downstream processing. Given the complexity of the daunomycin biosynthetic pathway in Streptomyces spp., substantial progress has been made in strain improvement to increase yield, metabolic robustness, and process stability. Advances in classical mutagenesis, pathway engineering, regulatory network modulation, and precursor supply optimization, along with rational medium design and advanced process control, have led to substantial increases in product titers and productivity. At the same time, innovations in downstream processes, such as extraction, purification and process integration, have increased recovery efficiency, product quality, and economic feasibility. With improvements in the production process, novel drug delivery modalities have been developed (e.g., drug carriers based on erythrocytes, drug nanocarriers based on hyaluronic acid) with increased efficiency and lower systemic toxicity. These developments indicate an evolution from pathway-level engineering to industrial-scale manufacturing and clinical application, underlining the evolution of daunomycin research and biotechnological production. Full article

This paper presents a proof-of-concept investigation into a novel hermetically sealed tunable-medium Extrinsic Fabry–Pérot Interferometer (EFPI) temperature sensor architecture. A series of tuneable-sensitivity EFPI temperature sensors is demonstrated, comprising a large-diameter fused silica diaphragm with a 800 $\mathrm{m}$ diameter, significantly exceeding conventional designs (typically ∼125 $\mathrm{m}$), with polished diaphragm thicknesses ranging from 28 to 49 $\mathrm{m}$, housed in hermetically sealed rigid melting point capillaries with a 1.8 mm internal diameter. By exploiting thermally induced pressure differentials generated by a tunable Krytox GPL 105 oil/air fill fraction within the sealed rigid cavity, the sensors demonstrate a continuously tuneable sensitivity design space spanning 0.45 to 190 $\mathrm{n}\mathrm{m}/\mathrm{K}$. An exact nonlinear thermal pressure model is derived and validated, replacing the linearised approximation which is shown to be inapplicable at fill fractions approaching unity. The low-sensitivity configuration (0.45 $\mathrm{n}\mathrm{m}/\mathrm{K}$) was characterised at the National Standards Authority of Ireland (NSAI) National Metrology Laboratory against ITS-90 fixed points: the Triple Point of Water (273.16 K) and the Gallium Fixed Point (302.9146 K), with traceability to the International Temperature Scale of 1990 (ITS-90), yielding an instrument-limited resolution of $<1.1$ mK, consistent with the metrological validation environment. The high-sensitivity configurations (21 and 190 $\mathrm{n}\mathrm{m}/\mathrm{K}$) were characterised on a laboratory bench, achieving instrument-limited theoretical resolutions of <24 $\mathrm{K}$ and $<2.6$$\mathrm{K}$ respectively, pending future metrological validation. The 190 $\mathrm{n}\mathrm{m}/\mathrm{K}$ sensitivity represents an improvement of approximately 21.7× over the closest directly comparable prior Citationutilised fusion splicing and manual polishing. Future development priorities include metrological validation of the high-sensitivity configurations, long-term stability characterisation, thermal cycling, and progression towards an all-glass hermetically sealed construction. Full article

Background: Postural disability develops in almost all patients with diabetic polyneuropathy (DPN). While transcutaneous electrical nerve stimulation (TENS) has proven effective in regressing sensory and motor impairments, its efficacy in improving postural control remains insufficiently studied. Purpose: To evaluate and compare the efficacy of direct peroneal and tibial high-frequency low-amplitude (HFLA) TENS and low-frequency high-amplitude (LFHA) TENS in correcting DPN-related postural disability, among European female patients without a documented history of falls, motor deficits, or pronounced electromyographic impairments, using computerized static posturography and the tandem walk test. Materials and methods: In this single-center, three-arm, randomized controlled trial (registration number: ISRCTN47534508, 3 December 2024), we conducted a longitudinal prospective analysis of European women with DPN-related postural disability. All enrolled patients were non-fallers with no motor deficits and baseline compound muscle action potential (CMAP) amplitudes of the peroneal and tibial nerves of at least 1.5 mV. The intervention groups received HFLA TENS (n = 24) or LFHA TENS (n = 25), while the control group underwent sham TENS (n = 24). Primary endpoints were assessed via static posturography and the tandem walk test (TWT); secondary endpoints were evaluated using hypoesthesia and pain evaluation, the Modified Clinical Test of Sensory Interaction in Balance (mCTSIB), and electromyography. Assessments were performed before treatment, immediately post-treatment, and at the conclusion of a 2-month follow-up period. Results: Comparative analysis incorporating the Bonferroni adjustment demonstrated that LFHA TENS is significantly superior to HFLA TENS. Post-treatment, LFHA TENS induced a reduction in envelope area by 20.7% under the eyes-open (EO) condition (p < α_adj; α_adj = 0.0028) and 32.9% under the eyes-closed (EC) condition (p < α_adj; α_adj = 0.0028), alongside a 16.6% decrease in the Romberg uotient (RQ) (p < α_adj; α_adj = 0.0056). Furthermore, LFHA TENS elicited a significant 39.0% reduction in velocity of CoP sway (VCS) under the EO condition (p < α_adj; α_adj = 0.0042), and decreased total CoP sway excursion by an average of 35.8% (EO) (p < α_adj; α_adj = 0.0042) and 43.8% (EC) (p < α_adj; α_adj = 0.0042) compared to baseline. In contrast, no statistically significant changes in these parameters were observed after HFLA TENS. Ultimately, LFHA TENS outperformed HFLA TENS in improving postural stability by 7.04% under the EO condition (p < α_adj; α_adj = 0.0042) and by 25.5% under the EC condition (p < α_adj; α_adj = 0.0042) in both the tandem walk test (TWT) and the Modified Clinical Test of Sensory Interaction on Balance (mCTSIB). Notably, a statistically significant increase in the CMAP amplitude of the affected peroneal nerves by 22.2% was observed exclusively following LFHA TENS treatment (p < α_adj; α_adj = 0.0056). Conclusions: The clinical efficacy of direct peroneal and tibial TENS compared to sham stimulation in reducing postural disability during both static and dynamic conditions was established in European female patients with moderate-to-severe DPN and unremarkable EMG impairments. Comparative analysis reveals a clear therapeutic superiority of LFHA TENS over HFLA TENS, as evidenced by significantly greater improvements in both posturographic parameters (envelope area, total CoP excursion under EO and EC conditions, and VCS under the EO condition) and functional clinical tests (TWT and mCTSIB), demonstrating long-term stability for up to 2 months post-intervention. Full article

This study explains how reinforcement learning (RL) contributes to congestion mitigation in inland freight terminal operations by testing a serial process model in which RL strengthens operational learning stability (OLStab), OLStab improves logistics efficiency, and logistics efficiency lowers congestion. Rather than presenting RL as a stand-alone congestion-reduction instrument, the paper examines a distinct inland-terminal application in which congestion emerges from interacting gate, yard, transfer, and dispatch frictions. Using a simulation-based explanatory design calibrated to a realistic macro-logistics context, and interpreting the results as simulation-informed evidence rather than direct field proof, the study analyzes 500 episode-level observations representing complete terminal runs under varying control conditions. The results show that RL positively affects OLStab, OLStab positively affects logistics efficiency, and logistics efficiency negatively affects congestion. The serial indirect pathway from RL through OLStab and logistics efficiency to congestion is statistically significant, whereas the direct effect of RL on congestion becomes non-significant once the mediators are introduced. Decision latency sensitivity does not significantly moderate the RL-to-OLStab relationship, suggesting that latency-related boundary conditions are more context-specific than the main capability pathway. The article contributes by offering a cautious simulation-based and mechanism-centered explanation of RL-enabled congestion mitigation in inland terminals, by treating OLStab as a simulation-grounded intermediate operational stability index, and by showing that the empirical pattern is better explained by theory-ordered simulator-level mechanism than by a residual direct RL effect. Full article