Search Results (52,989)

In histopathological image segmentation, existing methods often show low sensitivity to small lesions and indistinct boundaries, leading to missed detections. Since, in clinical diagnosis, the consequences of missed detection are more serious than false alarms, this study proposes ClinSegNet, a recall-oriented and human-centred framework for reliable histopathology screening. ClinSegNet employs a composite optimisation strategy, termed HistoLoss, which balances stability and boundary refinement while prioritising recall. An uncertainty-driven refinement mechanism is further introduced to target high-uncertainty cases with limited fine-tuning cost. In addition, a clinical data processing pipeline was developed, where pixel-level annotations were automatically derived from IHC-to-H&E mapping and combined with public datasets, enabling effective training under limited clinical data conditions. Experiments on the NuInsSeg and NuInsSeg-UHS datasets showed that ClinSegNet achieved recall scores of 0.8803 and 0.8917, further improved to 0.8983 and 0.9053 with HITL refinement, while maintaining competitive Dice and IoU. Comparative and ablation studies confirmed the complementary design of the framework and its advantage in capturing small or complex lesions. In conclusion, ClinSegNet provides a clinically oriented, recall-prioritised framework that enhances lesion coverage, reduces the risk of missed diagnosis, and offers both a methodological basis for future human-in-the-loop systems and a feasible pipeline for leveraging limited clinical data. Full article

Aerosol–cloud interaction remains one of the largest sources of uncertainty in weather and climate modeling. This study investigates the impacts of aerosols on the macro- and microphysical properties of different cloud types over East Asia, based on nine years of joint satellite observations from CloudSat, CALIPSO, and MODIS, combined with ERA5 reanalysis data. Results reveal pronounced cloud-type dependence in aerosol effects on cloud fraction, cloud top height, and cloud thickness. Aerosols enhance the development of convective clouds while suppressing the vertical extent of stable stratiform clouds. For ice-phase structures, ice cloud fraction and ice water path significantly increase with aerosol optical depth (AOD) in deep convective and high-level clouds, whereas mid- to low-level clouds exhibit reduced ice crystal effective radius and ice water content, indicating an “ice crystal suppression effect.” Even after controlling for 14 meteorological variables, partial correlations between AOD and cloud properties remain significant, suggesting a degree of aerosol influence independent of meteorological conditions. Humidity and wind speed at different altitudes are identified as key modulating factors. These findings highlight the importance of accounting for cloud-type differences, moisture conditions, and dynamic processes when assessing aerosol–cloud–climate interactions and provide observational insights to improve the parameterization of aerosol indirect effects in climate models. Full article

Labor shortages in seedling nurseries, particularly in manual inspection and replanting, hinder operational efficiency despite advancements in automation. This study aims to develop a cost-effective, GPU-free machine vision system to automate the detection of deficient seedlings in plug trays, specifically for small-scale nursery operations. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. The proposed Deficiency Detection and Replanting Positioning (DDRP) machine integrates low-cost components including an Intel RealSense Depth Camera D435, Raspberry Pi 4B, stepper motors, and a programmable logic controller (PLC). It utilizes OpenCV’s Haar cascade algorithm, HSV color space conversion, and Otsu thresholding to enable real-time image processing without GPU acceleration. Under controlled laboratory conditions, the DDRP-Machine achieved high detection accuracy (96.0–98.7%) and precision rates (82.14–83.78%). Benchmarking against deep-learning models such as YOLOv5x and Mask R-CNN showed comparable performance, while requiring only one-third to one-fifth of the cost and avoiding complex infrastructure. The Batch Detection (BD) mode significantly reduced processing time compared to Continuous Detection (CD), enhancing real-time applicability. The DDRP-Machine demonstrates strong potential to improve seedling inspection efficiency and reduce labor dependency in nursery operations. Its modular design and minimal hardware requirements make it a practical and scalable solution for resource-limited environments. This study offers a viable pathway for small-scale farms to adopt intelligent automation without the financial burden of high-end AI systems. Future enhancements, adaptive lighting and self-learning capabilities, will further improve field robustness and including broaden its applicability across diverse nursery conditions. Full article

The growing importance of environmental technologies in a circular economy requires the use of tools that allow a realistic assessment of their economic efficiency. Classical investment indicators, such as NPV or IRR, are proving inadequate in the case of installations whose main objective is not to maximise profit but to reduce waste and emissions. There is a lack of tools in the literature that would allow for an unambiguous assessment of the unit cost of waste treatment, taking into account the life cycle of the installation and market conditions. This study aims to assess the feasibility of using the Levelised Cost of Waste (LCOW) indicator, modelled on the Levelised Cost of Energy (LCOE) from the energy sector, as a planning and decision-making tool in the waste management sector. In this study, an LCOW calculation model was developed and applied to analyse textile waste pyrolysis technology. Simulations were conducted for three plant scales (1000, 5000, and 10,000 Mg/year), and a sensitivity analysis was performed to examine the relationship between the LCOW and by-product prices, energy costs, capital expenditures, and CO₂ emissions. The results confirm that the LCOW is a helpful tool for determining tariffs, identifying subsidy thresholds and comparing technology options. Its application is particularly well suited to small-scale environmental investments where classical approaches fail. Full article

Celery (Apium graveolens L.) is a widely cultivated leafy vegetable of significant agronomic and nutritional importance. Owing to its high nutritional value, global demand for celery has steadily increased. However, under natural cultivation conditions, uncontrolled light exposure often prolongs the seedling stage and impairs celery growth quality. Improving the nutritional quality of celery through artificial regulation of the light environment has therefore become an important research focus. This work aimed to elucidate the impact of varying light–dark cycles on the growth characteristics and nutritional attributes of celery. Six light–dark cycle treatments (4 h/2 h, 8 h/4 h, 16 h/8 h, 24 h/12 h, 32 h/16 h, and 40 h/20 h) were applied, using ‘Oster Ziyu Xiangqin’ as the plant material under a constant light intensity of 400 μmol·m⁻²·s⁻¹. The results revealed that the 24 h/12 h light–dark treatment significantly enhanced plant height, total fresh weight, and root vigor and showed superior performance in photosynthetic and chlorophyll fluorescence parameters. The 32 h/16 h treatment significantly enhanced the accumulation of soluble sugars, proteins, total phenolic compounds, and flavonoids, as well as the activities of antioxidant enzymes, while reducing nitrate-nitrogen levels. In conclusion, the 24 h/12 h light–dark cycle was most conducive to the growth and photosynthetic performance of celery, whereas the 32 h/16 h treatment optimally enhanced its nutritional quality and antioxidant capacity. Full article

Nitrogen-modified atmosphere technology, due to its effectiveness in pest control, is widely used in grain storage as an eco-friendly preservation method. This study compared the quality changes in unhulled rough rice (paddy) stored under nitrogen-modified atmosphere and conventional conditions. Fatty acid value (FAV), reactive oxygen species (ROS) content, coenzyme levels, antioxidant enzyme activities, and concentrations of central carbon metabolism-related metabolites of paddy were monitored during storage under different storage conditions. The results revealed that compared to conventional storage, nitrogen-modified atmosphere resulted in lower FAV and ROS levels, as well as higher pyridine nucleotides contents and antioxidant enzyme activities, including superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), and glutathione reductase (GR). Metabolomic profiling demonstrated that N₂-MAS induced metabolic changes characterized by the down-regulation of 2-hydroxyglutaric acid and the up-regulation of fructose 6-phosphate, glucose 1-phosphate, glycerol 3-phosphate, gluconic acid, fumaric acid, and malic acid, which collectively contribute to reduced oxidative damage and enhanced preservation quality. These findings elucidated the mechanism of N₂-MAS-delayed quality deterioration and revealed the regulatory role of the antioxidant system and central carbon metabolism. Full article

Rolling element bearings are commonly used in rotating machines. Bearing fault detection and diagnosis play a critical role in machine operations to recognize bearing faults at their early stage and prevent machine performance degradation, improve operation quality, and reduce maintenance costs. Although many fault detection techniques are proposed in the literature for bearing condition monitoring, reliable bearing fault detection remains a challenging task in this research and development field. This study proposes an enhanced Teager–Kaiser (eTK) technique for bearing fault detection and diagnosis. Vibration signals are used for analysis. The eTK technique is novel in two aspects: Firstly, an empirical mode decomposition analysis is suggested to recognize representative intrinsic mode functions (IMFs) with different frequency components. Secondly, an eTK denoising filter is proposed to improve the signal-to-noise ratio of the selected IMF features. The analytical signal spectrum analysis is conducted to identify representative features for bearing fault detection. The effectiveness of the proposed eTK technique is verified by experimental tests corresponding to different bearing conditions. Full article

This study investigates the adsorption behavior of natural sepiolite for the removal of cadmium (Cd²⁺), copper (Cu²⁺), and nickel (Ni²⁺) ions from aqueous solutions under batch conditions. The sepiolite was extensively characterized prior to adsorption experiments. Mineralogical analysis confirmed the presence of crystalline sepiolite, while DTG-TGA revealed thermal stability with distinct weight loss linked to surface and structural water. BET analysis indicated a high surface area of 194 m²/g and a mesoporous structure favorable for adsorption. Batch experiments evaluated the effects of contact time, pH, adsorbent dosage, and initial metal concentration. Adsorption was highly pH-dependent, with maximum removal near-neutral pH values. Higher adsorbent dosages reduced in a lower adsorption capacity per unit mass, primarily because the fixed amount of solute was distributed over a larger number of available sites, leading to unsaturation of the adsorbent surface and possible particle agglomeration. Isotherm modeling revealed that the Langmuir model provided the best fit, indicating monolayer adsorption with maximum adsorption capacities of 15.95 mg/g for Cd(II), 37.31 mg/g for Cu(II), and 17.83 mg/g for Ni(II). Langmuir constants indicated favorable interactions. Kinetics showed rapid adsorption within the first hour, reaching equilibrium at 240 min through surface adsorption and intraparticle diffusion. Cu(II) exhibited the fastest uptake, while Ni(II) adsorbed more slowly, suggesting differences in diffusion rates among the metal ions. Desorption using 0.1 N HCl achieved over 80% efficiency for all metals, confirming sepiolite reusability. Overall, raw sepiolite is an effective, low-cost adsorbent for removing potentially toxic elements from water. Full article

Buildings with electrified heat pump systems, onsite photovoltaic (PV) generation, and energy storage offer strong potential for demand flexibility. This study compares two storage configurations, thermal energy storage (TES) and battery energy storage (BESS), to evaluate their impact on cooling performance and cost savings. A Model Predictive Control (MPC) framework was developed to optimize system operations, aiming to minimize costs while maintaining occupant comfort. Results show that both configurations achieve substantial savings relative to a baseline. The TES system reduces daily operating costs by about 50%, while the BESS nearly eliminates them (over 90% reduction) and cuts grid electricity use by more than 65%. The BESS achieves superior performance because it can serve both the controllable heating, ventilation, and air conditioning (HVAC) system and the home’s broader electrical loads, thereby maximizing PV self-consumption. In contrast, the TES primarily influences the thermal load. These findings highlight that the choice between thermal and electrical storage greatly affects system outcomes. While the BESS provides a more comprehensive solution for whole-home energy management by addressing all electrical demands, further techno-economic evaluation is needed to assess the long-term feasibility and trade-offs of each configuration. Full article

The arbuscular mycorrhizal fungi (AMF) form symbiotic, mutually beneficial relationships in the rhizosphere, and modulate phosphorus’ (P) availability to regulate plant growth, nutrient uptake, and quality. However, their roles in cut-flower species remain poorly understood. The aim of this study was to evaluate the effects of single and dual inoculation with Glomus intraradices and G. mosseae on Lisianthus (Eustoma grandiflorum) grown under three P levels (10, 20, and 40 mg kg⁻¹) in greenhouse conditions. Under intermediate P, dual-inoculated plants exhibited the greatest above-ground vigor, with increases in stem length (+31%), dry shoot weight (+67%), and highest shoot P (+54%) and N (+23%) content, compared with non-inoculated controls. Under low P, dual inoculation maximized dry root weight (+63%) and mycorrhizal colonization, whereas AMF effects diminished at high P. Principal component analysis showed that there were distinct mycorrhizal interactions (PCA2, 20.3% variance) and a close integration between vegetative growth and nutrient accumulation (PCA1, 54.3% variance). For the first time, this study demonstrates that Lisianthus exhibits a strong response to dual AMF inoculation, offering a novel strategy to enhance growth, nutrition, and ornamental quality when P fertilization is optimized. By reducing chemical fertilizer use, this dual AMF–P management offers a sustainable framework for high-quality cut-flower production. Full article

Metal additive manufacturing (MAM), also referred to as 3D printing, has proven remarkable in the fabrication of complex metal components in multiple sectors. However, the assessment of this revolutionary process through bending fatigue is frequently impeded due to concerns about mechanical and physical conditions of the printed components. The unique layer-by-layer production process results in varied microstructures, anisotropy, and intrinsic defects that considerably differ from traditionally manufactured wrought metals. This review article aims to integrate and evaluate historical and contemporary research on the bending fatigue of additively manufactured materials. More specifically, the impact of process parameters, build orientation, surface conditions, and post-processing techniques such as machining, surface treatments, and polishing on bending fatigue performance are summarized. Adopting prediction methodologies is emphasized to facilitate flaw detection and thereby ensuring the safe and reliable deployment of AM parts in dynamic load carrying applications. Some future research directions are proposed, including the (i) the development of standardized specimens and test protocols, (ii) the adaptation to miniaturization to overcome challenges in high throughput fatigue testing, (iii) the application of emerging geometries such as the Krouse specimen for mechanistic investigations, and (iv) the possibility of developing a correlation across different testing methods and materials to reduce experimental burden. By synthesizing the recent progresses and identifying unresolved challenges, this review outlines an organized and clear pathway towards future research for the deployment of advanced bending fatigue characterization in AM process. The novel idea of adapting miniaturized Krouse geometries in the bending fatigue testing of additively manufactured metals is a viable prospect for the feasible fabrication of AM fatigue coupons with reduced specimen preparation defects and enhanced fatigue strength. Full article

In the context of carbon neutrality, ammonia-coal co-firing is considered an effective way to reduce emissions from coal-fired units. This paper takes a 125 MW tangential combustion boiler as the research object and combines CFD and CHEMKIN models to study the effects of ammonia injection position (L1–L3) and blending ratio (0–30%) on combustion characteristics and NO generation. The results indicate that L1 (same-layer premixed injection) can form a continuous and stable flame structure and maintain low NO emissions. L2 (fuel-staged configuration) shows the highest burnout rate and strong denitration potential under high mixing conditions, while L3 has an unstable flow field and the worst combustion structure. NO emissions show a typical “first rise and then fall” trend with the blending ratio. L1 performs optimally in the range of 15–20%, and L2 peaks at 20%. Mechanism analysis indicates that R430 is the main NO generation reaction, while R15 and R427 dominate the NO reduction process. The synergistic reaction between NH_x free radicals and coke can effectively inhibit the formation of NO and improve combustion efficiency. Full article

Plant-derived wastes are increasingly explored as organic matter sources for sustainable agriculture. Tea waste, a by-product of industrial tea processing, is often regarded as an environmental pollutant, yet its potential for agricultural use remains conditional and requires careful evaluation. This study examined the effects of factory-derived tea waste on kale (Brassica oleracea var. acephala) under drought stress. Plants were grown in soils amended with 5% or 10% tea waste and subjected to mild (75% field capacity) and moderate (50% field capacity) water deficits, compared with full irrigation (100% field capacity). Fifteen morphological and physiological parameters were assessed, and data were analyzed using principal component analysis (PCA) and correlation heatmaps to identify trait associations and stress markers. Drought stress significantly reduced all growth and yield traits, with stronger effects under more severe water deficit. Tea waste generally exacerbated stress impacts, increasing damage indices, reducing plant height, and lowering chlorophyll values. However, 10% tea waste under non-stress conditions increased plant and root dry weights without negatively affecting other traits, suggesting a partial nutrient contribution. In contrast, 5% tea waste aggravated stress effects, likely due to phenolic and caffeine toxicity. Overall, raw tea waste was found to be unsuitable for kale production under drought conditions. To harness its potential, bioactive compounds must be degraded or removed, and the material stabilized through composting or biochar conversion for safe integration into drought-resilient systems. Full article

Phosphatidylserine (PS) holds considerable importance in both the food and medical sectors; however, its biosynthesis is critically dependent on phospholipase D (PLD). The practical application of PLD is constrained by pronounced side reactions in its free form and by reduced selectivity when immobilized. To address these challenges, this study employed a sequential strategy involving bioimprinting to hyperactivate PLD, followed by microencapsulation via ionotropic gelation within an alginate–chitosan matrix. This approach induced conformational rigidification, enabling PLD to maintain its hyperactivated state in aqueous environments. Under optimal conditions, the encapsulation efficiency reached 78.56%, and the enzyme activity recovery achieved 105.27%. The immobilized bioimprinted PLD demonstrated exceptional catalytic performance, achieving a 94.68% PS yield within 20 min, which significantly surpassed that of free PLD (85.82% in 150 min) and non-imprinted immobilized PLD (90.34% in 60 min). This represents 7.27-fold and 2.14-fold efficiency improvements, respectively. Furthermore, the biocatalyst exhibited outstanding storage stability, thermal stability, and reusability (77.53% yield after 8 cycles). To our knowledge, this is the first report combining bioimprinting with alginate-chitosan microencapsulation via ionotropic gelation, which yielded remarkably enhanced PLD activity. These findings highlight the strong potential of this method for efficient PS production. Full article

The present study investigates the twofold effect of home–work spillover on life satisfaction through intrinsic work motivation and meaning derived from work, with family flexibility as a moderator. Based on Self-Determination Theory and the Work–Home Resources model, we test a moderated parallel mediation model whereby both positive and negative spillover from home affect life satisfaction through motivational and meaning pathways, depending on the level of family flexibility. 735 working adults completed validated measures of work-related flow, work meaning, home–work interaction (negative and positive), family flexibility, and life satisfaction. PROCESS macro (Model 59) via 5000 bootstrapped samples indicated that home negatively influencing work was associated with lower life satisfaction, mainly via reduced work meaning, particularly for individuals with low family flexibility. Conversely, positive work–home interaction was associated with higher work meaning and, indirectly, greater life satisfaction, with this effect being stronger when family flexibility was lower. Intrinsic motivation was associated with life satisfaction through mediation only when family flexibility was higher. These results indicate work meaning and family context compensatory and buffering effects on well-being. The research adds to integrative work–life interface models by delineating conditional psychological processes that enable employee flourishing. Full article