Search Results (440)

Soil available nitrogen (AN) is a critical nutrient for plant absorption and utilization. Accurately mapping its spatial distribution is essential for improving crop yields and advancing precision agriculture. In this study, 188 AN soil samples (0–20 cm) were collected at Heshan Farm, Nenjiang County, Heihe City, Heilongjiang Province, in 2023. The soil available nitrogen content ranged from 65.81 to 387.10 mg kg⁻¹, with a mean value of 213.85 ± 61.16 mg kg⁻¹. Sentinel-2 images and normalized vegetation index (NDVI) and enhanced vegetation index (EVI) time series data were acquired on the Google Earth Engine (GEE) platform in the study area during the bare soil period (April, May, and October) and the growth period (June–September). These remote sensing variables were combined with soil sample data, crop type information, and crop growth period data as predictive factors and input into a Random Forest (RF) model optimized using the Optuna hyperparameter tuning algorithm. The accuracy of different strategies was evaluated using 5-fold cross-validation. The research results indicate that (1) the introduction of growth information at different growth periods of soybean and maize has different effects on the accuracy of soil AN mapping. In soybean plantations, the introduction of EVI data during the pod setting period increased the mapping accuracy R² by 0.024–0.088 compared to other growth periods. In maize plantations, the introduction of EVI data during the grouting period increased R² by 0.004–0.033 compared to other growth periods, which is closely related to the nitrogen absorption intensity and spectral response characteristics during the reproductive growth period of crops. (2) Combining the crop types and their optimal period growth information could improve the mapping accuracy, compared with only using the bare soil period image (R² = 0.597)—the R² increased by 0.035, the root mean square error (RMSE) decreased by 0.504%, and the mapping accuracy of R² could be up to 0.632. (3) The mapping accuracy of the bare soil period image differed significantly among different months, with a higher mapping accuracy for the spring data than the fall, the R² value improved by 0.106 and 0.100 compared with that of the fall, and the month of April was the optimal window period of the bare soil period in the present study area. The study shows that when mapping the soil AN content in arable land, different crop types, data collection time, and crop growth differences should be considered comprehensively, and the combination of specific crop types and their optimal period growth information has a greater potential to improve the accuracy of mapping soil AN content. This method not only opens up a new technological path to improve the accuracy of remote sensing mapping of soil attributes but also lays a solid foundation for the research and development of precision agriculture and sustainability. Full article

In the context of global warming, polar tourism is developing rapidly, and the demand for polar cruise travel in the Northwest Passage continues to increase, while sea ice has long been a key factor limiting the development of polar cruise tourism. This study focuses on the operational risk of sea ice on cruise ships in the Northwest Passage (NWP), aiming to provide a scientific basis for ensuring the safety of cruise ship navigation and promoting the sustainable development of polar tourism. Based on ice data from 2015 to 2024, this study used the Polar Operational Limit Assessment Risk Indexing System (POLARIS) methodology recommended by the International Maritime Organization (IMO) to establish three scenarios for the route of ice class IC cruise ships: light ice, normal ice, and heavy ice. The navigable windows were systematically analyzed and critical waters along the route were identified. The results indicate that the navigable windows for IC ice-class cruise ships under light ice conditions are from mid-July to early December, while the navigable period under normal ice conditions is only from mid- to late September, and navigation is not possible under heavy ice conditions. The study identified Larsen Sound, Barrow Strait, Bellot Strait and Eastern Beaufort Sea as critical waters on the NWP cruise route. Among them, Larsen Sound and Eastern Beaufort Sea have a more prominent impact on voyage scheduling because their navigation weeks overlap less with other waters. This study provides a new idea for the risk assessment of polar cruise ships in ice regions. The research results can provide an important reference for the safe operation of polar cruise ships in the NWP and the decision-making of relevant parties. Full article

The growing interest in alternative fuels stems from the need to reduce greenhouse gas emissions and promote sustainable development. Despite the dominance of fossil fuels in aviation, pulsejet engines offer a promising platform for testing new fuels due to their simple design and fuel versatility. This study presents a multi-criteria analysis of alternative fuels for use in pulsejet engines, emphasizing environmental impacts. Both gaseous (biogas, ethyne, LPG, and natural gas) and liquid fuels (methanol, ethanol, biodiesel, Jet A-1, and SAF) were examined. Exhaust emissions (CO₂, H₂O, CO) were simulated in Ansys 2025 based on literature data and chemical calculations. Additional factors analyzed included calorific value, production cost, thermal expansion, density, life cycle emissions (LCA), CO₂ emissions per fuel mass, and renewable energy content. Using the zero-unitization method, results were normalized into a single aggregate variable for each fuel. The highest values were recorded for biogas and methanol, respectively, indicating their potential as alternative fuels. The findings support further development of sustainable fuels for pulsejet engines. Future research should address combustion optimization and noise reduction, enhancing viability in aviation and other transport sectors. Integration with the current fuel infrastructure is also recommended to facilitate broader implementation. Full article

Mulberry (Morus spp.), as an economically significant crop in sericulture and medicinal applications, faces severe threats to leaf yield and quality from pest and disease infestations. Traditional detection methods relying on chemical pesticides and manual observation prove inefficient and unsustainable. Although computer vision and deep learning technologies offer new solutions, existing models exhibit limitations in natural environments, including low recognition rates for small targets, insufficient computational efficiency, poor adaptability to occlusions, and inability to accurately identify structural features such as leaf veins. We propose Mamba-YOLO-ML, an optimized model addressing three key challenges in vision-based detection: Phase-Modular Design (PMSS) with dual blocks enhancing multi-scale feature representation and SSM selective mechanisms and Mamba Block, Haar wavelet downsampling preserving critical texture details, and Normalized Wasserstein Distance loss improving small-target robustness. Visualization analysis of the detection performance on the test set using GradCAM revealed that the enhanced Mamba-YOLO-ML model demonstrates earlier and more effective focus on characteristic regions of different diseases compared with its predecessor. The improved model achieved superior detection accuracy with 78.2% mAP50 and 59.9% mAP50:95, outperforming YOLO variants and comparable Transformer-based models, establishing new state-of-the-art performance. Its lightweight architecture (5.6 million parameters, 13.4 GFLOPS) maintains compatibility with embedded devices, enabling real-time field deployment. This study provides an extensible technical solution for precision agriculture, facilitating sustainable mulberry cultivation through efficient pest and disease management. Full article

Living mulch intercropping systems are considered as nature-based solutions with a low environmental footprint for managing weeds, improving biodiversity and agroecosystem sustainability. In drylands, however, they may increase intra/inter-specific competition for water, reducing crop productivity. We tested conservation tillage (TLG) carob plots with and without irrigation (TLG_irr; TLG_dry) vs. rainfed intercropping systems of carob and (i) thyme (Thymbra capitata; T-System) or (ii) clover (Trifolium squarrosum; C-System), strategically planted on the south (sun)-exposed soil side (SES) of carobs, to reduce soil temperature/evaporation. Carob water relations, productivity and environmental footprints were examined for three years under semi-arid, low weed-competition (Skarinou-SKR) and arid high weed-competition (Vrysoules-VRY) conditions in Cyprus. Carob yield efficiency (kg/m³) in SKR, was >27% higher for the T-System (p < 0.05; SES cover ca. 85%; year-3), matching a higher leaf water content (p < 0.001) compared to TLG_dry. The T-System reached 28% and 56% of TLG_irr yields during very dry and normal rainfall years; TLG_dry yields approached zero. For VRY, no negative impacts on carob leaf water, at 25% SES cover, were found. SKR’s C-System improved leaf water content (p < 0.05) for only one year. The T-System also outperformed TLG_irr and TLG_dry in terms of reducing irrigation needs and energy consumption, breaking new grounds for dryland agroforestry. Full article

This research is focused on water governance problems in La Marina Alta District, in the province of Alicante (southeastern Spain). The district has a public management body, Consorcio de Abastecimiento y Saneamiento de Aguas de los Municipios de La Marina Alta (CASAMA), which has been inoperative since its creation in 1987. Although La Marina Alta has sufficient water resources in situations of hydrological normality, they are significantly affected by the impacts of climate change, insufficient water treatment technology and the absence of storage and regulation infrastructure. As a consequence, periods of scarcity and overexploitation of aquifers, together with high-demand situations, have generated scenarios of a lack of drinking water with reputational damage and uncertainty for the future of agricultural operations. Thus, the aim of this work is to propose the adoption of integrated water resource management strategies that will increase the resilience of this sub-basin in La Marina Alta. To this end, the contribution of new non-conventional resources to the water pool, combined with an efficient network of infrastructure, and all this supported by effective governance structures, would be essential to achieve a sustainable balance between demand and supply, preserving the environmental values of the territory. Full article

The 1992 reform of the European Common Agricultural Policy (CAP) introduced the Land Parcel Identification System (LPIS), a geodatabase of land parcels used to monitor and regulate agricultural subsidies. Traditionally, the LPIS has relied on high-resolution aerial orthophotos; however, recent advancements in very-high-resolution (VHR) satellite imagery present new opportunities to enhance its effectiveness. This study explores the feasibility of utilizing PlanetScope, a commercial VHR optical satellite constellation, to map agricultural parcels within the LPIS. A test was conducted in Umbria, Italy, integrating existing datasets with a series of PlanetScope images from 2023. A segmentation workflow was designed, employing the Normalized difference Vegetation Index (NDVI) alongside the Edge segmentation method with varying sensitivity thresholds. An accuracy evaluation based on geometric metrics, comparing detected parcels with cadastral references, revealed that a 30% scale threshold yielded the most reliable results, achieving an accuracy rate of 83.3%. The results indicate that the short revisit time of PlanetScope compensates for its lower spatial resolution compared to traditional orthophotos, allowing accurate delineation of parcels. However, challenges remain in automating parcel matching and integrating alternative methods for accuracy assessment. Further research should focus on refining segmentation parameters and optimizing PlanetScope’s temporal and spectral resolution to strengthen LPIS performance, ultimately fostering more sustainable and data-driven agricultural management. Full article

Forest age is a key factor in determining the carbon sequestration capacity and trends of forests. Based on the Google Earth Engine platform and using the topographically complex and climatically diverse Southeastern Tibet as the study area, we propose a new method for forest age estimation that integrates multi-source remote-sensing data with machine learning. The study employs the Continuous Degradation Detection (CODED) algorithm combined with spectral unmixing models and Normalized Difference Fraction Index (NDFI) time series analysis to update forest disturbance information and provide annual forest distribution, mapping young forest distribution. For undisturbed forests, we compared 12 machine-learning models and selected the Random Forest model for age prediction. The input variables include multiscale satellite spectral bands (Sentinel-2 MSI, Landsat series, PROBA-V, MOD09A1), vegetation parameter products (canopy height, productivity), data from the Global Ecosystem Dynamics Investigation (GEDI), multi-band SAR data (C/L), vegetation indices (e.g., NDVI, LAI, FPAR), and environmental factors (climate seasonality, topography). The results indicate that the forests in Southeastern Tibet are predominantly overmature (>120 years), accounting for 87% of the total forest cover, while mature (80–120 years), sub-mature (60–80 years), intermediate-aged (40–60 years), and young forests (< 40 years) represent relatively lower proportions at 9%, 1%, 2%, and 1%, respectively. Forest age exhibits a moderate positive correlation with stem biomass (r = 0.54) and leaf-area index (r = 0.53), but weakly negatively correlated with L-band radar backscatter (HV polarization, r = −0.18). Significant differences in reflectance among different age groups are observed in the 500–1000 nm spectral band, with 100 m resolution PROBA-V data being the most suitable for age prediction. The Random Forest model achieved an overall accuracy of 62% on the independent validation set, with canopy height, L-band radar data, and temperature seasonality being the most important predictors. Compared with 11 other machine-learning models, the Random Forest model demonstrated higher accuracy and stability in estimating forest age under complex terrain and cloudy conditions. This study provides an expandable technical framework for forest age estimation in complex terrain areas, which is of significant scientific and practical value for sustainable forest resource management and global forest resource monitoring. Full article

Climate change has driven global awareness of environmental issues, leading to the adoption of clean technologies aimed at reducing Greenhouse Gas (GHG) emissions. An effective method to assess environmental mitigation is the quantification of the Product Carbon Footprint (PCF) in the Life Cycle Assessment (LCA) of production processes. In the oil extraction industry, artificial lift systems use electro submersible pumps (ESPs) that can now incorporate new operating principles based on permanent magnet motors (PMMs) and CanSystem (CS) as an alternative to traditional normal induction motors (NIMs) and can help lower the carbon footprint. This study compares the PCF of ESPs equipped with PMMs and CS versus NIMs, using LCA methodologies in accordance with ISO 14067:2018 for defining the Functional Unit (FU) and ISO 14064-1:2019 to calculate the GHG inventory and the amount of CO₂ equivalent per year. The analysis spans five key stages and 14 related activities. For ESPs with NIMs, this study calculated 999.9 kg of raw materials, 1491.66 kW/h for manufacturing and storage, and 5.77 × 10⁴ kW/h for use. In contrast, ESPs with PMMs and CS required 656 kg of raw materials and consumed 4.44 × 10⁴ kW/h during use, resulting in an 23% reduction in energy consumption. This contributed to an 21.9% decrease in the PCF. The findings suggest that PMMs and CS offer a sustainable solution for reducing GHG emissions in oil extraction processes globally. Full article

Infective endocarditis (IE) of the tricuspid and pulmonary valve accounts for 5 to 10% of all IE cases and, compared with left-sided IE, is often associated with intravenous (i.v.) drug use, presence of intracardiac devices, and central venous catheters (CVCs), including permanent—Hickman catheter (HC). We report a case of a 71-year-old female patient on a chronic hemodialysis (HD) program who had developed IE. Her first symptoms were fever and malaise. Transthoracic echocardiography (TTE) and transesophageal echocardiography (TEE) examinations were performed, revealing vegetations on the tip of HC and the anterior and posterior leaflets of the tricuspid valve (TV). Three blood culture bottles were positive for Enterococcus spp. The HC was replaced with a new CVC to continue HD. After a six-week antibiotic treatment, most clinical symptoms were resolved, and there was a decrease in vegetation size with normalization of inflammatory markers and negative follow-up blood cultures. After this initial improvement in the patient’s condition, the clinical course was complicated by the development of Citrobacter koseri bacteremia and sepsis. Despite adequate antibiotic therapy, the condition progressed to septic shock, which was soon followed by a fatal outcome. IE treatment in HD patients requires long-term broad-spectrum antibiotic therapy, and also, in patients without arteriovenous fistula (AVF), the CVC should be replaced after each HD during IE and sepsis treatment to minimize the patient’s exposure to a foreign body that is susceptible to bacterial colonization. A colonized foreign body is a focus for sustained and spreading infection, and its presence prevents adequate antibiotic treatment until the focus of infection is removed. Full article

While China’s current energy policies predominantly adopt single-factor energy efficiency (SFEE) as the benchmark, academic research increasingly advocates total-factor energy efficiency (TFEE) assessments. This study examines the differences between these two energy efficiency evaluation paradigms in the context of sustainable development goals, particularly exploring the extent of such divergences. Guided by the “energy input minimization” principle, we construct a time-series dynamic analytical framework to systematically compare the impact of SFEE and TFEE on regional energy efficiency rankings from a sustainable development perspective. Specifically, this paper innovatively incorporates “new driving forces” into the production function, establishing a green development-oriented evaluation system that reveals the measurement bias of traditional production frameworks on energy efficiency and its influence on regional rankings. The results demonstrate: (1) China’s regional energy efficiency rankings remain largely consistent under both evaluation systems, with only minor adjustments for individual provinces, confirming the feasibility of adopting SFEE in policy formulation as an effective method for evaluating and comparing regional energy efficiency; (2) For most provinces under the “new normal” economic development context, continued use of traditional production frameworks would lead to underestimation of TFEE. After introducing factors such as human capital, intangible capital, technological innovation, and business environments, China’s energy efficiency polarization gap widens. The evaluation of efficiency indicators provides theoretical foundations and micro-level evidence for energy policy formulation under the “dual-carbon” goals. Full article

Background/Objectives: Sickle cell disease (SCD) is caused by a β-globin gene mutation (βGlu6Val) that produces sickle hemoglobin (HbS). When deoxygenated, HbS polymerizes, leading to red blood cell (RBC) sickling; therefore, hemoglobin is a central therapeutic target for SCD. Current strategies include increasing the levels of oxygenated HbS (which cannot polymerize) and/or directly destabilizing the deoxygenated HbS polymer. This study aimed to design and synthesize next-generation Michael acceptor antisickling hemoglobin modifiers (MMA-206, MMA-207, MMA-208, and MMA-209) and evaluate their antisickling efficacy. Methods: Four Michael acceptor compounds (MMA-206 to MMA-209) were synthesized and characterized. Their pharmacologic activities and modes of action were assessed in vitro using disulfide exchange reaction with normal hemoglobin, sickling inhibition assays with sickle red blood cells, and hemoglobin oxygen equilibrium curve analysis with normal and sickle red blood cells. Results: MMA-206 exhibited the strongest antisickling activity, outperforming previously studied Michael acceptor antisickling agents. All four MMA analogues bound to hemoglobin at βCys93, destabilizing the low-oxygen-affinity T-state and thereby preventing deoxygenation-induced HbS polymerization and RBC sickling. In addition, they appeared to directly destabilize the HbS polymer, indicating a second mechanism of action. Furthermore, time-dependent oxygen equilibrium measurements confirmed that their pharmacologic effect was sustained over time in vitro. Conclusions: The new Michael acceptor compounds, particularly MMA-206, demonstrated potent antisickling effects via dual mechanisms and showed sustained activity. These findings highlight Michael acceptor compounds’ promise as hemoglobin oxygen-affinity modulators for the treatment of SCD. Full article

The bio-prospecting of bioactive phytochemicals from invasive flora presents a sustainable paradigm for the ecologically conscious management of major invasive pest S. invicta. Ageratina adenophora, while recognized for its allelopathic insecticidal properties, exhibits poorly characterized toxicological profiles and mechanistic underpinnings against S. invicta, warranting systematic investigation to elucidate its mode of action. This study elucidates the bioactive insecticidal compounds of A. adenophora and their toxicological impacts on S. invicta, including behavioral, metabolic, and enzymatic perturbations, via liquid chromatography–mass spectrometry (LC-MS) profiling. The ethanol extracts of the roots, stems, and leaves of A. adenophora have shown control effects on S. invicta, with an LC₅₀ (50% lethal concentration) of 331.847, 188.256, and 166.253 mg/mL at 48 h, respectively. Metabolite profiling of A. adenophora revealed that safranal and dihydrocoumarin are relatively high in plant leaves, and they showed significant insecticidal activity and behavioral inhibitory effects on S. invicta with LC₅₀ 349.042 mg/L and 118.336 mg/L at 48 h, respectively. Notably, these two bioactive compounds disrupted the normal energy production through glucose metabolism and the citrate cycle, which eventually led to the death of S. invicta. Further, these two compounds also activated the detoxification metabolic pathway of S. invicta. These findings provide a theoretical basis for the use of these bioactive compounds in the integrated management of S. invicta and may lead to the development of a new biopesticide. Full article

Alkali-activated materials have gained increasing popularity in the field of soil barrier materials due to their high strength and low environmental impact. However, barrier materials made from alkali-activated materials still suffer from long setting times and poor barrier performance in acidic, alkaline, and saline environments, which hinders the sustainable development of green alkali-activated materials. Herein, coconut shell biochar, sodium silicate-based adhesives, and polyether polyol/polypropylene polymers were used for multi-stage material modification. The modified materials were evaluated for barrier performance, rapid formation, and resistance to acidic, alkaline, and saline environments, using metrics such as compressive strength, permeability, mass loss, and VOC diffusion efficiency. The results indicated that adhesive modification reduced the material’s setting time from 72 to 12 h. Polymer modification improved resistance to corrosion by 15–20%. The biochar-containing multi-stage modified materials achieved VOC diffusion barrier efficiency of over 99% in both normal and corrosive conditions. These improvements are attributed to the adhesive accelerating calcium silicate hydration and forming strength-enhancing compounds, the polymer providing corrosion resistance, and biochar enhancing the volatile organic compounds (VOC) barrier properties. The combined modification yielded a highly effective multi-stage green barrier material suitable for rapid barrier formation and corrosion protection. These findings contribute to evaluating multi-level modified barrier materials’ effectiveness and potential benefits in this field and provide new insights for the development of modified, green, and efficient alkali-activated barrier materials, promoting the green and sustainable development of soil pollution control technologies. Full article

Extreme weather events and rising temperatures pose significant risks, not only in urban areas but also in metropolitan forests, that affect the well-being of the people who visit them. City forests are considered one of the best bets for mitigating high temperatures within civic areas. Such areas modulate microclimates in contemporary cities, offering environmental, social, and economic advantages. Therefore, comprehending the intricate relationships between municipal forests and the climatic changes of various destinations is crucial for attaining healthier and more sustainable city environments for people. In this research, the thermal comfort index (Modified Temperature–Humidity Index (MTHI)) has been analysed using Landsat images of six urban forests in London during July 2022, when the area first experienced record-breaking temperatures of over 40 °C. Our results show a significant growth in the MTHI that goes from 2.5 (slightly hot) under normal conditions to 3.4 (hot) during the heat wave period. This situation intensifies the environmental discomfort for visitors and highlights the necessity to enhance their adaptability to future temperature increases. In turn, it was found that the places most affected by heat waves are those that have grass cover or that have small associated buildings. Conversely, forested regions or those with lakes and/or ponds exhibit lower temperatures, which results in enhanced resilience. These findings are noteworthy in their concentration on one of the UK’s most severe heat waves and illustrate the efficacy of integrating spectral measurements with statistical analyses to formulate customized regional initiatives. Therefore, the results reported will allow the implementation of new planning and adaptation policies such as incorporating thermal comfort into planning processes, improving green and blue amenities, increasing tree densities that are resilient to rising temperatures, and increasing environmental comfort conditions in metropolitan forests. Finally, the applicability of this approach in similar urban contexts is highlighted. Full article