Search Results (34,538)

The integration of high-pressure grinding roller (HPGR) with pre-concentration techniques and stirred mills is recognized for its energy efficiency. Studies have suggested that the feed with a P₈₀ around 1 mm is acceptable for stirred mills or coarse particle flotation. Nonetheless, published experimental data characterizing the comminution behavior of single-stage HPGR circuits configured with a 1 mm screen aperture remain scarce. Moreover, extant research remains confined to laboratory scale. Consequently, critical performance metrics, including production capacity, screening efficiency, and process continuity, have not been substantively documented in the literature. In this paper, the HPGR performance in an industrial-scale HPGR/tower mill comminution circuit was assessed and optimized by laboratory and industrial tests. The research meticulously analyzed the impact of feed rate on the industrial-scale flip-flow screen and HPGR performance and found that the HPGR featuring two studded rolls with a diameter of 800 mm and a width of 400 mm, operating in a reverse classification circuit with a scalped feed by a 14.64 m² flip-flow screen while running continuously 24 h per day, is capable of producing a −1 mm comminution product suitable for tower mill feed. Under the optimal operating conditions identified, it achieved a specific energy consumption of 4.57 kWh/t with a feed rate of 27.08 t/h. Full article

Extensive practice has demonstrated that the continuous pursuit of high yields in the black soil region of Northeast China resulted in imbalances in soil nutrients and declines in both soil quality and water use efficiency. Alternate wetting and drying (AWD) irrigation offers a promising solution for increasing rice yield and maintaining soil fertility. However, the success of this irrigation method largely depends on its scheduling. This study examined the threshold effects of AWD on rice growth, yield, and soil nutrient availability in the Sanjiang Plain, a representative black soil region in Northeast China. A two-year trial was conducted from 2023 to 2024 at the Qixing National Agricultural Science and Technology Park. “Longjing 31,” a local cultivar, was selected as the experimental material. The lower limit of soil water content under AWD was set as the experimental factor, with three levels: −10 kPa (LA), −20 kPa (MA), and −30 kPa (SA). The local traditional irrigation practice, continuous flooding, served as the control treatment (CK). Indicators of rice growth and soil nutrient content were measured and analyzed at five growth stages: tillering, jointing, heading, milk ripening, and yellow ripening. The results showed that, compared to CK, AWD had minimal impact on rice plant height and tiller number, with no significant differences (p > 0.05). However, AWD affected leaf area index (LAI), shoot dry matter (SDM), yield, and soil nutrient availability. In 2023, control had little effect on rice plant height and tiller number among the different irrigation treatments. The LAI of LA was 11.1% and 22.5% higher than that of MA and SA, respectively, while SDM in LA was 10.5% and 17.2% higher than in MA and SA. Significant differences were found between LA and MA, as well as between LA and SA, whereas no significant differences were observed between MA and SA. The light treatment is beneficial to the growth and development of rice, while the harsh growth environment caused by the moderate and severe treatments is unfavorable to rice growth. The average contents of nitrate nitrogen (NO₃⁻-N), available phosphorus (AP), and available potassium (AK) in LA were 11.4%, 8.4%, and 9.3% higher than in MA, and 16.7%, 11.5%, and 15.0% higher than in SA, respectively. Significant differences were observed between LA and SA. This is because the light treatment facilitates the release of available nutrients in the soil, while the moderate and severe treatments hinder this process. Although panicle number per unit area and grain number per panicle in LA were 7.5% and 2.3% higher than in MA, and 10.8% and 2.2% higher than in SA, these differences were not statistically significant. Seed setting rate and thousand-grain weight showed little variation across irrigation treatments. The yield of LA was 10,233.3 kg hm⁻², 9.1% and 14.1% higher than that of MA and SA, respectively, with significant differences observed. Compared with the moderate and severe treatments, the light treatment increases indicators such as the number of panicles per unit area, grains per panicle, thousand-grain weight, and seed setting rate, resulting in significant differences among the treatments. Water use efficiency (WUE) decreased as the control level increased. The WUE of all AWD irrigation treatments was significantly higher than that of the control treatment (CK). Compared with CK, AWD reduces evaporation, percolation, and other water losses, leading to a significant decrease in water consumption. Meanwhile, the yield remains basically unchanged or even slightly increases, thus resulting in a higher WUE than CK. The trends in rice growth, soil nutrient indicators, and WUE in 2024 were generally consistent with those observed in 2023. In 2024, the yield of LA was 9832.7 kg hm⁻², 14.9% and 17.3% higher than that of MA and SA, respectively, with significant differences observed. Based on the results, the following conclusions are drawn: (1) AWD irrigation can affect the growth of rice, alter the status of available nutrients in the soil, and thereby cause changes in yield and WUE; (2) LA is the optimal treatment for increasing rice yield, improving the availability of soil available nutrients, and improving WUE; (3) Both MA and SA enhanced WUE; however, these practices negatively impacted rice growth and the concentration of soil available nutrients, leading to a concurrent decline in yield. To increase rice yield and maintain soil fertility, LA, with an irrigation upper limit of 30 mm and a soil water potential threshold of −10 kPa, is recommended for the Sanjiang Plain region. Full article

In recent years, the rapid development of underground engineering projects has driven a significant increase in the variety and quantity of excavation equipment. The wear of excavation tools significantly increases construction costs and reduces construction efficiency. The wear rate of excavation tools is closely related to the abrasiveness of the rock. The Cerchar abrasivity index (CAI) is the most widely used index for estimating rock abrasiveness. The primary objective of this paper is to develop a novel prediction model for CAI, which is established based on the mechanical properties and petrographic parameters of rocks. These parameters include uniaxial compressive strength, Brazilian splitting strength, quartz content, equivalent quartz content, average quartz size, brittleness indices, rock abrasive index, and Schimazek’s F-abrasiveness. Correlation analysis was used to conduct a preliminary analysis between CAI and single-influence parameters. The results indicated that a single factor is not suitable for directly predicting CAI. In addition, multiple linear regression (MLR) and a non-linear algorithm, gene expression programming (GEP), were used to establish new prediction models for CAI. A statistical comparison was conducted between the prediction accuracy of the GEP-based model and the MLR-based model. In comparison to the MLR-based model, the GEP-based model demonstrates higher accuracy in predicting CAI. Full article

Supercapacitors (SCs) are widely acknowledged for their high-power density as energy storage devices; designing electrode materials with both high efficiency and exceptional energy density remains a significant challenge. In this study, a flower-like iron-doped molybdenum sulfide on graphene nanosheets (FMS/G) was synthesized through a simple, efficient, and scalable solvothermal approach. The FMS/G composite demonstrated exceptional performance when employed as both positive and negative electrodes, owing to the effective incorporation of iron into the MoS₂ crystal lattice. This doping induces defects and facilitates abundant redox reactions, ultimately boosting electrochemical performance. The FMS/G composite demonstrates an ultrahigh specific capacitance of 931 F g⁻¹ at 1 A g⁻¹, along with excellent rate capability, retaining 582 F g⁻¹ at 20 A g⁻¹. It also exhibits remarkable cycling stability, maintaining 90.5% of its initial capacitance after 10,000 cycles. Furthermore, the assembled FMS/G-3//FMS/G-3 supercapacitor device achieves a superior energy density of 64.7 Wh kg⁻¹ at a power density of 0.8 kW kg⁻¹ with outstanding cycling stability, retaining 92% of its capacitance after 10,000 cycles. The remarkable capabilities of the flower-like FMS/G composite underscore its noteworthy potential for promoting effective energy storage systems. Full article

Zinc (Zn) is an essential micronutrient for plant growth, serving as a co-factor in enzymatic processes and pigment biosynthesis. In horticultural crops such as lettuce, Zn fertilization is increasingly relevant for optimizing yield and nutritional quality. In this study, a greenhouse pot experiment was conducted using Lactuca sativa L. cv. Romana Verano (Ramiro Arnedo) to evaluate the effects of four Zn sources with contrasting physio-chemical properties—ZnSO₄, a synthetic chelate containing DTPA, EDTA, and HEDTA, a Zn–lignosulphonate complex, and ZnO nanoparticles—applied to soil at rates of 15, 30, 60, and 120 mg Zn·kg⁻¹. Morphometric traits, photosynthetic pigmentation, and photosystem performance were assessed to determine differences in plant response. Results showed that low to moderate Zn supply (15–60 mg Zn·kg⁻¹) maintained growth, leaf number, stem diameter, and biomass without significant changes compared to the control. In contrast, the highest dose (120 mg Zn·kg⁻¹), particularly in chelated forms, led to reductions in growth and yield exceeding 80%, reflecting supra-optimal effects. Although lignosulphonate and nanoparticles sources lowered soil Zn availability, they did not affect lettuce growth or yield, indicating their potential as safer agricultural alternatives to conventional Zn fertilizers. Photosynthetic efficiency, measured through chlorophyll fluorescence and electron transport activity, was positively modulated by adequate Zn levels but declined at excessive concentrations. These findings highlight that Zn efficiency strongly depends on its chemical form and applied dose, providing practical insights for optimizing Zn fertilization strategies in lettuce and other horticultural crops. Full article

The Internet of Vehicles (IoV) relies on Vehicle-to-Everything (V2X) communications to enable cooperative perception among vehicles, infrastructures, and devices, where Vehicle-to-Infrastructure (V2I) links are crucial for reliable transmission. However, the openness of wireless channels exposes IoV to eavesdropping, threatening privacy and security. This paper investigates an Intelligent Reflecting Surface (IRS)-assisted interweave Cognitive IoV (CIoV) network to enhance physical layer security in V2I communications. A non-convex joint optimization problem involving spectrum allocation, transmit power for Vehicle Users (VUs), and IRS phase shifts is formulated. To address this challenge, a heterogeneous multi-agent (HMA) Mamba RainbowDQN algorithm is proposed, where homogeneous VUs and a heterogeneous secondary base station (SBS) act as distinct agents to simplify decision-making. Simulation results show that the proposed method significantly outperform benchmark schemes, achieving a 13.29% improvement in secrecy rate and a 54.2% reduction in secrecy outage probability (SOP). These results confirm the effectiveness of integrating IRS and deep reinforcement learning (DRL) for secure and efficient V2I communications in CIoV networks. Full article

Background/Objectives: Late diagnosis and inefficient treatment regimens lead to poor prognosis, with a low 5-year survival rate for both non-small-cell lung cancer (NSCLC) and small-cell lung cancer (SCLC). New targeted therapeutic agents can be developed and introduced only by first discovering new driver oncogenes and with a thorough investigation of the known driver genes. The aim of the current study is to investigate the prevalence of alterations in the eight most frequently altered genes in lung cancer—BRAF, EGFR, KRAS, ALK, ROS1, HER2, PD-L1 and PIK3CA. Methods: Real-time polymerase chain reaction (RT-PCR) was used to detect KRAS and EGFR mutations, multiplex PCR and microarray hybridization for KRAS/BRAF/PIK3CA mutations. Immunohistochemical analysis was performed for the detection of ALK, HER2/NEU, ROS-1 and PD-L1 alterations. Results: Overall, 221/603 patients (36.65%) had at least one genetic alteration, of which 22 patients (3.65%) had two genetic alterations and two patients had more than two genetic alterations. Additionally, 50 patients were identified with one or more KRAS mutations (8.29%), 45 patients with EGFR mutations (7.46%), and 1.82% with PIK3CA mutations and 0.66% with BRAF mutations. Furthermore, 50% of the co-occurring alterations were either on KRAS and PIK3CA genes (3/6), on KRAS and BRAF genes (2/6, 33.33%) or on EGFR and PIK3CA genes (1/6, 16.67%), and 10.45% of the patients exhibited PD-L1 overexpression, 5.31% ALK rearrangements, and 2.36% HER2/NEU expression, with no ROS-1 rearrangements detected. Conclusions: Comprehensive testing for somatic alterations in EGFR, BRAF, KRAS, and PIK3CA is significant in guiding therapeutic decisions in lung cancer management. Such testing should be routinely conducted to establish a thorough genetic profile of lung cancers in a manner that is both time-efficient and cost-effective. Full article

This study investigates the corrosion performance of reinforced steel in concrete subjected to carbonation and chloride ingress. Four systems were examined: normal concrete (NC15), chloride-exposed (ClC15), carbonated (COC15), and chloride-exposed carbonated concrete (COClC15). A comprehensive assessment was carried out using electrochemical testing, gravimetric weight loss, chloride profiling, Temkin adsorption isotherm modeling, and SEM analysis. Electrochemical results showed a marked increase in corrosion activity under combined chloride–carbonation exposure. The highest corrosion current density (i_corr) was obtained in COClC15 (0.4779 µA/cm²), compared with only 0.0106 µA/cm² for NC15. Gravimetric analysis confirmed these findings, with COClC15 exhibiting a corrosion rate nearly 1.5 times greater than ClC15 and 52 times higher than NC15 after 120 days. Chloride profiling revealed reduced binding efficiency in carbonated concrete; at 5 mm depth, COClC15 bound only 0.06% chloride, while ClC15 retained 0.43%. The Temkin adsorption isotherm further quantified the weakened binding capacity. The binding coefficient (β) of COClC15 was considerably lower than ClC15 and NC15, reflecting the impact of C–S–H decalcification and aluminate phase transformation into carboaluminates, which restrict Friedel’s salt formation. SEM micrographs corroborated these observations, showing extensive microstructural degradation in COClC15. This study revealed that the synergy of carbonation and chloride ingress reduces chloride-binding capacity, accelerates depassivation, and severely compromises the durability of reinforced concrete in aggressive environments. Full article

Metaheuristic algorithms are widely utilized as effective tools for solving complex optimization problems. Among them, the Harmony Search (HS) algorithm has garnered significant attention for its simple structure and excellent performance. The efficacy of the HS algorithm is heavily dependent on the configuration of its internal parameters, with the Harmony Memory Considering Rate (HMCR) and Pitch Adjusting Rate (PAR) playing pivotal roles. These parameters determine the probabilities of using the Random Generation (RG), Harmony Memory Consideration (HMC), and Pitch Adjustment (PA) operators, thereby controlling the balance between exploration and exploitation. However, a systematic empirical analysis of the interaction between these parameters and the characteristics of the problem at hand remains insufficient. Thus, this study conducts a comprehensive empirical analysis of the performance sensitivity of the HS algorithm to variations in HMCR and PAR values. The analysis is performed on a suite of 23 benchmark functions, encompassing diverse characteristics such as unimodality/multimodality and separability/non-separability, along with 5 real-world optimization problems. Through extensive experimentation, the performance for each parameter combination was evaluated on a rank-based system and visualized using heatmaps. The results experimentally demonstrate that the algorithm’s performance is most sensitive to the HMCR value across all function types, establishing that setting a high HMCR value (≥0.9) is a prerequisite for securing stable performance. Conversely, the optimal PAR value showed a direct correlation with the topographical features of the problem landscape. For unimodal problems, a low PAR value between 0.1 and 0.3 was more effective, whereas for complex multimodal problems with numerous local optima, a relatively higher PAR value between 0.3 and 0.5 proved more efficient in searching for the global optimum. This research provides a guideline into the parameter settings of the HS algorithm and contributes to enhancing its practical applicability by proposing a systematic parameter tuning strategy based on problem characteristics. Full article

The widespread presence of antibiotic residues, particularly norfloxacin (NFX), in food products and the environment has raised concern, underscoring the need for sensitive and selective detection methods. In this study, a novel broccoli-derived nitrogen-doped carbon quantum dots (N-CQDs) was synthesized via a green hydrothermal approach, 4-dimethylaminopyridine (DMAP) as both a nitrogen dopant and a functionalizing agent. The synthesized N-CQDs exhibit an average diameter of approximately ~4.2 nm and emit bright blue fluorescence, with a maximum emission at 445 nm upon excitation at 360 nm. A “Turn-ON” response toward NFX was achieved with a detection limit of 0.30 nM, attributed to hydrogen bonding and π–π stacking interactions that suppressed non-radiative decay. Moreover, the sensor demonstrates high selectivity for NFX, effectively distinguishing it from common interfering substances, including other antibiotics, organic acids, and biomolecules. The N-CQDs also exhibit excellent stability under diverse conditions, such as varying pH levels, high ionic strength, and prolonged irradiation. Finally, the practical applicability of the developed sensor was validated by detecting NFX in spiked broccoli extract and milk samples, with recovery rates ranging from 98.2% to 100.1% and relative standard deviations of less than 2.0%. This work presents a sustainable and efficient N-CQD-based fluorescent sensing platform, offering significant potential for rapid and reliable detection of NFX in food safety and environmental monitoring. Full article

Against the background of global warming, the carbon emission of cities accounts for more than 70%, and its carbon sink increase and emission reduction have become the research focus. The water bodies and green spaces in the urban blue–green space have a synergistic carbon sequestration effect, but current research pays less attention to the small and medium scales. Therefore, taking the waterfront green space on both sides of Qinhuai New River in Nanjing as the research object, this paper explores the impact of the synergy between water and greenery on the carbon sequestration efficiency of green space. The study first estimates the carbon sequestration efficiency of green spaces by integrating measured Leaf Area Index (LAI) data with the mean carbon sequestration rate per unit leaf area for typical tree and shrub species. It then constructs a set of water–green spatial relationship indicators and applies a random forest regression model to identify the key factors influencing carbon sequestration efficiency. Finally, multiple scenario models are developed to simulate the effects of green spaces on CO₂ reduction, thereby validating the roles of the identified influencing factors. The study found that waterfront green spaces tended to exhibit slightly higher carbon sequestration efficiency compared with non-waterfront green spaces. The proportion of 10 m forest land area and the proportion of 10–20 m forest land area had a higher impact on the carbon sequestration capacity of waterfront green space; that is, the closer the distance between the green space and the water, the better the carbon sequestration capacity. In order to improve the carbon sequestration efficiency of the waterfront area, the green space should be arranged along the water bank as much as possible, the depth of the green space should be increased, the proportion of the forest land area should be increased, the arbor and shrub should be planted evenly, and ribbon planting should be avoided. The study confirmed the synergistic effect of water and greenery in carbon sequestration benefits, providing data support and theoretical reference for the optimization and renewal of urban waterfront green space, and contributing to the realization of urban waterfront green space planning, design, and renewal with the goal of a high carbon sink. Full article

Excessive application of nitrogen (N) fertilizer increases the risk of soil NO₃^--N leaching in fluvial soil, threatening soil and groundwater quality and safety. Enhancing soil carbon (C) by returning straw to the field can efficiently improve soil quality. The process of increasing C/N by straw returning to regulate soil nitrogen transformation and mitigate NO₃⁻-N leaching, and the ecological threshold of straw application rate in fluvial soil need to be further explored. This study aims to research a series of soil C/N ratio treatments (including no straw, CK; C/N of 15, 20, 25, 30, 35 and 40), which were set up by adding straw at different application rates, and to investigate the underlying process of increasing C/N ratio by incorporating straw to mitigate NO₃⁻-N leaching. As the soil C/N ratio increased, the total soil nitrogen showed a fluctuating increase with the highest value in S40 treatment (increased by 358 mg kg⁻¹), while the NO₃⁻-N leaching amount reached the lowest value at the C/N ratio of 20, with an average reduction of 45% (decreased by 29.3 mg kg⁻¹) . Increasing soil C/N ratio significantly increased soil microbial biomass, cellulase, urease and N-acetyl-β-D-glucosaminidase activities while it decreased the net N mineralization rate, ammonification rate and nitrification rate. Principal component analysis showed that the NO₃^--N leaching was positively correlated with the ammonification rate, nitrification rate and net N mineralization rate, and negatively correlated with the abundances of bacteria, fungi and nitrogen-fixing genes (nifH) (p < 0.01). Structural equation model analysis showed that straw-regulated C/N, dissolved organic N and soil fungi were the most important factors affecting NO₃⁻-N leaching, followed by the ammonification rate. Overall, increasing soil C/N by adding straw could enhance soil microbial biomass (especially fungi) and enzyme activities to promote soil N storage and reduce net N mineralization, ammonification and nitrification to decrease NO₃⁻-N leaching. Full article

Micro-hydropower technologies are increasingly attracting attention due to their potential to contribute to sustainable energy generation. With the growing global demand for electricity, it is essential to research and innovate in the development of devices capable of harnessing hydroelectric potential through such technologies. In this context, the Archimedes screw generator (ASG) stands out as a device that potentially offers significant advantages for micro-hydropower generation. This study aimed, through a simplified yet effective method, to analyze and determine the simultaneous effects of the number of blades, inclination angle, and flow rate on the torque, mechanical power, and efficiency of an ASG. Computational Fluid Dynamics (CFD) was employed to obtain the torque and perform the hydrodynamic analysis of the devices, in order to compare the results of the optimal geometric and operational characteristics with previous studies. This proposal also helps guide future work in the preliminary design and evaluation of ASGs, considering the geometric and flow conditions that take full advantage of the available water resources. Under the specific conditions analyzed, the most efficient generator featured three blades, a 20° inclination, and an inlet flow rate of 24.5 L/s, achieving a mechanical power output of 117 W with an efficiency of 71%. Full article

In this paper, we propose a novel Dynamic Cipher Composition (DCC) based on multi-algorithm approach using the Library of Image Encryption Methods (LIEM). Unlike conventional static encryption schemes, the proposed DCC randomly selects and applies different encryption algorithms to spatially segmented regions of an image during each execution. To manage this process efficiently, the system employs two lightweight registers: one for configuration management and another for region-specific modality assignment, both indexed for streamlined storage and retrieval. Experimental evaluations conducted on standard test images demonstrate that the DCC achieves a near-optimal Shannon entropy, high values of Net Pixel Change Rate (NPCR) and Unified Average Changing Intensity (UACI), and negligible pixel correlation coefficients. These results confirm the scheme’s strong resistance to statistical, differential, and structural attacks, while preserving computational efficiency suitable for real-time applications such as telemedicine, cloud storage, and video surveillance systems. Full article

Background: Multimodal Deep learning has emerged as a crucial method for automated patient-specific quality assurance (PSQA) in radiotherapy research. Integrating image-based dose matrices with tabular plan complexity metrics enables more accurate prediction of quality indicators, including the Gamma Passing Rate (GPR) and dose difference (DD). However, modality imbalance remains a significant challenge, as tabular encoders often dominate training, suppressing image encoders and reducing model robustness. This issue becomes more pronounced under task heterogeneity, with GPR prediction relying more on tabular data, whereas dose difference prediction (DDP) depends heavily on image features. Methods: We propose BMMQA (Balanced Multi-modal Quality Assurance), a novel framework that achieves modality balance by adjusting modality-specific loss factors to control convergence dynamics. The framework introduces four key innovations: (1) task-specific fusion strategies (softmax-weighted attention for GPR regression and spatial cascading for DD prediction); (2) a balancing mechanism supported by Shapley values to quantify modality contributions; (3) a fast network forward mechanism for efficient computation of different modality combinations; and (4) a modality-contribution-based task weighting scheme for multi-task multimodal learning. A large-scale multimodal dataset comprising 1370 IMRT plans was curated in collaboration with Peking Union Medical College Hospital (PUMCH). Results: Experimental results demonstrate that, under the standard 2%/3 mm GPR criterion, BMMQA outperforms existing fusion baselines. Under the stricter 2%/2 mm criterion, it achieves a 15.7% reduction in mean absolute error (MAE). The framework also enhances robustness in critical failure cases (GPR < 90%) and achieves a peak SSIM of 0.964 in dose distribution prediction. Conclusions: Explicit modality balancing improves predictive accuracy and strengthens clinical trustworthiness by mitigating overreliance on a single modality. This work highlights the importance of addressing modality imbalance for building trustworthy and robust AI systems in PSQA and establishes a pioneering framework for multi-task multimodal learning. Full article