BACKGROUND Gastrointestinal(GI)tumors are among the most prevalent malignancies,and surgical intervention remains a primary treatment modality.However,the complexity of GI surgery often leads to prolonged recovery and...BACKGROUND Gastrointestinal(GI)tumors are among the most prevalent malignancies,and surgical intervention remains a primary treatment modality.However,the complexity of GI surgery often leads to prolonged recovery and high postoperative complication rates,which threaten patient safety and functional outcomes.Enhanced recovery after surgery(ERAS)principles have been shown to improve perioperative outcomes through evidence-based,multidisciplinary care pathways.Despite its widespread adoption,there is a paucity of research focusing specifically on optimizing ERAS-guided nursing processes in the post-anesthesia care unit(PACU)and evaluating its impact on perioperative safety in patients undergoing GI tumor surgery.This study aimed to investigate whether an ERASbased PACU nursing protocol could enhance recovery,reduce complications,and improve patient safety in this surgical population.AIM To explore the impact of optimizing the recovery room nursing process based on ERAS on the perioperative safety of patients with GI tumors.METHODS A total of 260 patients with GI tumors who underwent elective surgeries under general anesthesia in our hospital from August 2023 to August 2025 and were then observed in the recovery unit(PACU)were selected.They were randomly divided into the observation group(the PACU nursing process was optimized based on ERAS)and the control group(the conventional PACU nursing process was adopted)by the random number grouping method,with 130 cases in each group.The time of gastric tube removal,urinary catheter removal,defecation time,hospital stay,time of leaving the room after tube removal,retention time in the recovery room,occurrence of complications,satisfaction and readmission rate were compared between the two groups after entering the room.Compare the occurrence of adverse events in the PACU nursing process between the two groups.RESULTS The time of gastric tube removal,urinary catheter removal,defecation time,hospital stay,retention time in the recovery room,total incidence of complications and readmission rate in the observation group were significantly lower than those in the control group,and the satisfaction rate was higher than that in the control group(P<0.05).The occurrence of adverse events in the PACU nursing process in the observation group was lower than that in the control group(P<0.05).CONCLUSION Optimizing the PACU nursing process based on ERAS can effectively accelerate the recovery process of patients undergoing GI tumor surgery,reduce adverse events,improve nursing satisfaction,and at the same time,lower the incidence of adverse events in the PACU nursing process,providing a more refined management basis for clinical practice.展开更多
Objective:To systematically explore the effectiveness of combining Enhanced Recovery After Surgery(ERAS)nursing and empathy intervention for postoperative patients with glioma.Methods:A total of 54 patients with gliom...Objective:To systematically explore the effectiveness of combining Enhanced Recovery After Surgery(ERAS)nursing and empathy intervention for postoperative patients with glioma.Methods:A total of 54 patients with glioma undergoing surgical treatment were selected for the study.The patients were admitted to the hospital between April 2023 and April 2025.The patients were divided into an observation group(n=27)and a control group(n=27)based on a random number table method.Relevant intervention indicators were compared between the two groups.Results:Compared with the control group,the postoperative recovery indicators in the observation group showed significant differences(P<0.05).After intervention,the scores of stress psychological indicators,FMA,NHISS,and ADL in the observation group were all better than those in the control group(P<0.05).The incidence of complications in the observation group was significantly lower than that in the control group(P<0.05).Conclusion:The combined application of empathy intervention and ERAS nursing effectively regulates the postoperative stress psychological state of patients with glioma,significantly improves their limb and neurological functions as well as daily living abilities,accelerates postoperative recovery,and reduces complications.This approach is feasible for wider implementation.展开更多
3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with m...3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.展开更多
Due to the complex structural hierarchy,with deeply nested associative relations between entities such as equipment,specifications,and business processes,intelligent power grid engineering is challenging.Meanwhile,lim...Due to the complex structural hierarchy,with deeply nested associative relations between entities such as equipment,specifications,and business processes,intelligent power grid engineering is challenging.Meanwhile,limited by the fragmented data and loss of contextual information,the generated reports are prone to the problems such as content redundancy and omission of critical information,failing to meet the demands of efficient decision-making and accurate management in modern power systems.To address these issues,this paper proposes a knowledge graph(KG)-enhanced framework to automatically generate electric power engineering reports.In the KG construction phase,a feature-fused entity recognition model named BERT-BiLSTM-CRF is adopted to improve the accuracy of entity recognition in scenarios involving power engineering professional terminology,thereby solving the problem of ambiguous entity boundaries in traditional models;then a BERT-attention relation extraction model is proposed to enhance the completeness of extracting complex hierarchical and implicit relations in power grid data.In the report generation phase,an improved Transformer architecture is adopted to accurately transform structured knowledge into natural language reports that comply with engineering specifications,addressing the issue of semantic inconsistency caused by the loss of structural information in existing models.By validating with real-world projects,the results show that the proposed framework significantly outperforms existing baseline models in entity recognition,confirming its superiority and applicability in practical engineering.展开更多
An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale...An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.展开更多
Let G=(V,E)be a connected graph.For an integer h≥0,a subset F■V(G)(resp.F■E(G))of G,if any,is called an h-restricted vertex cut(resp.h-restricted edge cut)of G,if G-F is disconnected and every vertex in G-F has at ...Let G=(V,E)be a connected graph.For an integer h≥0,a subset F■V(G)(resp.F■E(G))of G,if any,is called an h-restricted vertex cut(resp.h-restricted edge cut)of G,if G-F is disconnected and every vertex in G-F has at least h neighbors.The cardinality of a minimum h-restricted vertex-cut(resp.h-restricted edge cut)of G is the h-restricted connectivity(resp.h-restricted edge connectivity)of G,and denoted by κ^(h)(G)(resp.λ^(h)(G)).The enhanced hypercube Q_(n,κ)(1≤k≤n)is a variant of the hypercube Q_(n).In this paper,we consider the h-restricted connectivity of Q_(n,κ) for 2≤k≤n-1.Our main results are as follows:(1)κ^(h)(Q_(n,κ))=2^(h)(n-h+1)for 4≤k≤n-1 and 0≤h≤n-3,λ^(h)(Q_(n,κ))=2^(h)(n-h+1)for 2≤k≤n-1 and 0≤h≤n-2.(2)κ^(h)(Q_(n,3))=2^(h-1)(n-h+1)for n≥5 and 4≤h≤n-1,κ^(h)(Q_(n,2))=2^(h-1)(n-h+1)for n≥4 and 3≤h≤n-1.(3)κ^(3)(Q_(n,3))=6n-16 for n≥5,κ^(2)(Q_(n,3))=4n-8 for n≥4 and κ^(2)(Q_(n,2))=3n-5 for n≥3,κ^(1)(Q_(n,3))=2n and κ^(3)(Q_(n,2))=2n-2 for n≥3.展开更多
This research proposes an improved Puma optimization algorithm(IPuma)as a novel dynamic recon-figuration tool for a photovoltaic(PV)array linked in total-cross-tied(TCT).The proposed algorithm utilizes the Newton-Raph...This research proposes an improved Puma optimization algorithm(IPuma)as a novel dynamic recon-figuration tool for a photovoltaic(PV)array linked in total-cross-tied(TCT).The proposed algorithm utilizes the Newton-Raphson search rule(NRSR)to boost the exploration process,especially in search spaces with more local regions,and boost the exploitation with adaptive parameters alternating with random parameters in the original Puma.The effectiveness of the introduced IPuma is confirmed through comprehensive evaluations on the CEC’20 benchmark problems.It shows superior performance compared to both established and modern metaheuristic algorithms in terms of effectively navigating the search space and achieving convergence towards near-optimal regions.The findings indicated that the IPuma algorithm demonstrates considerable statistical promise and surpasses the performance of competing algorithms.In addition,the proposed IPuma is utilized to reconfigure a 9×9 PV array that operates under different shade patterns,such as lower triangular(LT),long wide(LW),and short wide(SW).In addition to other programmed approaches,such as the Whale optimization algorithm(WOA),grey wolf optimizer(GWO),Harris Hawks optimization(HHO),particle swarm optimization(PSO),gravitational search algorithm(GSA),biogeography-based optimization(BBO),sine cosine algorithm(SCA),equilibrium optimizer(EO),and original Puma,the indicated method is contrasted to the traditional configurations of TCT and Sudoku.In addition,the metrics of mismatch power loss,maximum efficiency improvement,efficiency improvement ratio,and peak-to-mean ratio are calculated to assess the effectiveness of the indicated approach.The proposed IPuma improved the generated power by 36.72%,28.03%,and 40.97%for SW,LW,and LT,respectively,outperforming the TCT configuration.In addition,it achieved the best maximum efficiency improvement among the algorithms considered,with 26.86%,21.89%,and 29.07%for the examined patterns.The results highlight the superiority and competence of the proposed approach in both convergence rates and stability,as well as applicability to dynamically reconfigure the PV system and enhance its harvested energy.展开更多
Objective:To analyze the impact of improved emergency integrated nursing on the treatment effectiveness and safety of emergency trauma patients.Methods:Study duration:December 2024 to December 2025.Observation target:...Objective:To analyze the impact of improved emergency integrated nursing on the treatment effectiveness and safety of emergency trauma patients.Methods:Study duration:December 2024 to December 2025.Observation target:emergency trauma patients in our hospital.Sample size:92 cases.Using computer-based grouping,the 92 patients were divided into two equally sized groups:a control group of 46 patients who received conventional emergency nursing care,and an observation group of 46 patients who underwent an improved emergency integrated nursing model.The treatment-related indicators,treatment effectiveness,and incidence of adverse events were evaluated in both groups.Results:After intervention,the pre-hospital emergency care time,emergency diagnosis time,total emergency rescue duration,and examination waiting time in the control group were all longer than those in the observation group(p<0.05);the treatment effectiveness in the control group(effective rate:82.61%)was worse than that in the observation group(effective rate:95.65%),p<0.05;compared with the control group,the observation group had a lower incidence of adverse events,p<0.05.Conclusion:Implementing an improved emergency integrated nursing model for emergency trauma patients helps streamline the treatment process,enhance treatment effectiveness,and reduce the incidence of adverse events.展开更多
The development of synthetic hybrid biological systems integrating photosynthetic organisms with organic-abiotic functional materials holds significant promise for enhancing photosynthetic processes.The artificial reg...The development of synthetic hybrid biological systems integrating photosynthetic organisms with organic-abiotic functional materials holds significant promise for enhancing photosynthetic processes.The artificial regulation of the state transition between photosystem I(PSI)and photosystem II(PSII)represents a strategic and promising approach for improving the efficiency of natural photosynthesis.In this study,we demonstrate that poly(benzimidazolium-phenylthiophene)(CP4)featuring a flexible cationic backbone exhibits superior ultraviolet light-harvesting capability.The polymer CP4 enhanced PSI activity in Chlorella pyrenoidosa(C.pyrenoidosa),subsequently promoting PSII activity and augmenting overall photosynthetic performance.During light-dependent reactions,CP4 significantly accelerated photosynthetic electron transfer,resulting in a 330%increase in the production of oxygen and 93%and 96%increases in the ATP and NADPH contents,respectively.In the context of dark reactions,CP4 facilitated the conversion and utilization of light energy,leading to a 6%increase in both carbohydrate and protein contents.These findings indicate that synthetic light-harvesting polymer materials exhibit considerable application potential in the field of biomass production through enhancement of natural photosynthetic efficiency.展开更多
Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods,this paper proposes the IPKE-MoE framework,which consists of three parts,namely,a sensitive w...Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods,this paper proposes the IPKE-MoE framework,which consists of three parts,namely,a sensitive word variant extraction framework,a sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer.First,sensitive word variants are precisely extracted through dynamic iterative prompt templates and the context-aware capabilities of Large Language Models(LLMs).Next,the extracted variants are used to construct a knowledge enhancement layer for sensitive word variants based on RoCBert models.Specifically,after locating variants via n-gram algorithms,variant types are mapped to embedding vectors and fused with original word vectors.Finally,a mixture-of-experts(MoE)classification layer is designed(sensitive word,sentiment,and semantic experts),which decouples the relationship between sensitiveword existence and text toxicity throughmultiple experts.This framework effectively combines the comprehension ability of Large Language Models(LLMs)with the discriminative ability of smaller models.Our two experiments demonstrate that the sensitive word variant extraction framework based on dynamically iterated prompt templates outperforms other baseline prompt templates.TheRoCBert models incorporating the sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer achieve superior classification performance compared to other baselines.展开更多
It is difficult to recover chrysocolla from sulfidation flotation which is closely related to the mineral surface composition.In this study,the effects of fluoride roasting on the surface composition of chrysocolla we...It is difficult to recover chrysocolla from sulfidation flotation which is closely related to the mineral surface composition.In this study,the effects of fluoride roasting on the surface composition of chrysocolla were investigated,its impact on sulfidation flotation was explored,and the mechanisms involved in both fluoride roasting and sulfidation flotation were discussed.With CaF_(2)as the roasting reagent,Na_(2)S·9H_(2)O as the sulfidation reagent,and sodium butyl xanthate(NaBX)as the collector,the results of the flotation experiments showed that fluoride roasting improved the floatability of chrysocolla,and the recovery rate increased from 16.87%to 82.74%.X-ray diffraction analysis revealed that after fluoride roasting,approximately all the Cu on the chrysocolla surface was exposed in the form of CuO,which could provide a basis for subsequent sulfidation flotation.The microscopy and elemental analyses revealed that large quantities of"pagoda-like"grains were observed on the sulfidation surface of the fluoride-roasted chrysocolla,indicating high crystallinity particles of copper sulfide.This suggests that the effect of sulfide formation on the chrysocolla surface was more pronounced.X-ray photoelectron spectroscopy revealed that fluoride roasting increased the relative contents of sulfur and copper on the surface and that both the Cu~+and polysulfide fractions on the surface of the minerals increased.This enhances the effect of sulfidation,which is conducive to flotation recovery.Therefore,fluoride roasting improved the effect of copper species transformation and sulfidation on the surface of chysocolla,promoted the adsorption of collectors,and improved the recovery of chrysocolla from sulfidation flotation.展开更多
Bayan Obo rare earth mine is the largest light rare earth resource worldwide,primarily extracts rare earth elements(REEs)from mixed RE concentrates with bastnaesite and monazite.Nevertheless,the adoption of the concen...Bayan Obo rare earth mine is the largest light rare earth resource worldwide,primarily extracts rare earth elements(REEs)from mixed RE concentrates with bastnaesite and monazite.Nevertheless,the adoption of the concentrated sulfuric acid roasting metallurgical process has resulted in damage to the environment.Therefore,this paper adopted the method of selective mineral phase transformation(MPT)followed by enhanced micro-flotation.By determining the optimal MPT co nditions,the flotation recovery of bastnaesite-roasted products by the collector(phthalic acid,PA)is improved,and the enhanced separation of bastnaesite with monazite is realized.The results show that with the increase of roasting temperature and time,the bastnaesite decomposition product is CeOF and monazite does not change significantly.Subsequent micro-flotation exhibits a gradual decline in the PA consumption of bastnaesiteroasted products,while the flotation recovery of monazite-roasted products remains poor.The artificial mixed ore experiments result in a CeOF foam product with a content of 94.14%and a recovery of 85.80%,and a monazite tank product with a content of 73.53%and a recovery of 87.87%.Compared with the preroasting ore,the surface and interior of bastnaesite-roasted products develop numerous cracks and porosities,and no obvious structural damage is observed in monazite-roasted particles.As the roasting temperature increases,the mineral particles undergo recrystallization or closure,reducing the specific surface area of bastnaesite-roasted products and enhancing hydrophobicity,leading to diminished PA consumption.Fourier transform infrared and other flotation-relation tests show that PA is chemisorbed on the surface of CeOF.The MPT conditions are optimized in this study,which provides a reference for further advancing the efficient separation of bastnaesite and monazite.展开更多
Formic acid(FA)is particularly prominent for its ubiquity and structural simplicity among atmospheric organic acids,and exerts a significant influence on atmospheric acidity.However,the potential contribution of FA to...Formic acid(FA)is particularly prominent for its ubiquity and structural simplicity among atmospheric organic acids,and exerts a significant influence on atmospheric acidity.However,the potential contribution of FA to the primary stage of new particle formation(NPF)remains unclear.Herein,molecular dynamics(MD),density functional theory(DFT)and the atmospheric cluster dynamics code(ACDC)model have been utilized to evaluate the mechanism of FA participation in atmospheric SA(sulfuric acid)-A(ammonia)clusters.The MD simulations qualitatively suggest that FA can aggregate with SA and A to form larger clusters,and the aggregation time of the largest clusters decreases as the temperature decreases.The DFT and ACDC findings indicate that the ternary SA-A-FA system is thermodynamically more stable at low temperatures(238.15 K).Simultaneously,in regions with low temperatures,high[FA](10^(11)molecules/cm3),low[SA](106 molecules/cm3)and high[A](10^(11)molecules/cm^(3)),FA significantly enhances SA-A cluster formation rates.The low-temperature NPF mechanism implies that FA could facilitate the growth of pure SA-A clusters via a“catalytic”mechanism and play an integral role in the genesis of critical clusters as a“participant”.This dual role differs from the“catalytic”role exhibited by malonic and glycolic acids in our previous studies.This discovery could help identify the sources of unexplained NPFs in regions with high FA concentrations,such as densely forested areas with abundant vegetation,regions affected by biomass burning,or periods with elevated vehicle exhaust emissions and the release of volatile organic compounds like isoprene and terpenoids.展开更多
Enhancing the efficiency of phase-change heat storage is vital for maximizing the utilization of renewable energy.This study examines the synergistic effect of non-uniformly shaped fins and nanoparticles on the meltin...Enhancing the efficiency of phase-change heat storage is vital for maximizing the utilization of renewable energy.This study examines the synergistic effect of non-uniformly shaped fins and nanoparticles on the melting performance of phase-change storage tanks.The problem is addressed using a finite volume framework coupled with the enthalpy–porosity method,with the numerical model rigorously validated against experimental data.The analysis explores the influence of varying fin deflection angles and nanoparticle concentrations on melting dynamics.It is shown that a downward fin deflection of 6◦reduces melting time to 570 s,representing a 20.8% improvement over uniform fins.Introducing 1% nanoparticles further accelerates melting,reducing time by 36.54% compared to the nanoparticle-free case.The combined strategy of 6◦fin deflection and 1%nanoparticle addition shows the most economic heat storage rate,achieving an exceptional 80.74% enhancement relative to a tank with uniform fins.展开更多
The virtual preassembly of super-high steel bridge towers faces a challenge in the efficient and precise extraction of complex cross-sectional features.Factors such as fabrication errors,gravity-induced deformations,a...The virtual preassembly of super-high steel bridge towers faces a challenge in the efficient and precise extraction of complex cross-sectional features.Factors such as fabrication errors,gravity-induced deformations,and temperature fluctuations can compromise the accuracy of contour extraction.To address these limitations,an improved Alpha-shape-based point cloud contour extraction method is proposed.The proposed approach uses a hierarchical strategy to process three-dimensional laser scanning point clouds.The processed data are then subjected to curvatureadaptive voxel filtering to reduce acquisition noise.In addition,an enhanced iterative closest point(ICP)variant with correspondence validation accurately aligns the discrete point cloud segments.The proposed curvature-responsive Alpha-shape framework enables multiscale contour delineation through topology-adaptive threshold modulation,which resolves boundary ambiguities in geometrically complex cross-sections.The method was experimentally validated using field-acquired measurement datasets from the Zhangjinggao Yangtze River Bridge tower segments,confirming its capability to reconstruct noncanonical cross-sectional geometries.Three contour extraction methods,including Poisson reconstruction,the conventional Alpha-shape algorithm,and random sample consensus with ICP(RANSAC-ICP),were compared to evaluate the performance of the proposed Alpha-shape algorithm.The results demonstrate that the proposed method achieves superior contour extraction accuracy and data reduction efficiency,highlighting its effectiveness in contour extraction tasks.展开更多
Mango(Mangifera indica L.)is one of the main economic crops in Hainan,China,prized for its distinctive flavor and high nutritional value.It is also rich in health-promoting antioxidants such as vitamin C and flavonoid...Mango(Mangifera indica L.)is one of the main economic crops in Hainan,China,prized for its distinctive flavor and high nutritional value.It is also rich in health-promoting antioxidants such as vitamin C and flavonoids.Enhanced ultraviolet-B(UV—B)radiation,a growing global environmental concern,alters plant antioxidant systems,with increased flavonoid accumulation as a common adaptive response.However,its effects on mango fruit remain largely unexplored.To investigate the antioxidant responses of mango to enhanced UV-B radiation and identify key responsive flavonoid compounds and regulatory genes,we exposed‘Tainong 1’mango fruits growing under natural light to 96 kJ·m^(-2)·d^(-1)of UV-B radiation to simulate high UV-B conditions.Treated fruits were smaller in size and had a pulp of a more intense yellow colour.Further,malondialdehyde content in treated fruits was higher during the phase of rapid fruit enlargement.Additionally,treated fruits showed increased sugar-acid ratios,total phenol,total flavonoid,carotenoid,and ascorbic acid contents.Furthermore,they showed significantly enhanced antioxidant activity,as measured by the FRAP,ABTS,and DPPH assays.Extensive targeted metabolomic-analysis identified flavonoids as the largest category of compounds differentially expressed in treated and control groups.Quantitative metabolomics of flavonoids identified hyperoside,quercimeritrin,and(-)-catechin gallate as the key flavonoid metabolites responsive to UV-B treatment.Transcriptome analysis revealed an enrichment of the flavonoid biosynthesis pathway,with most associated differentially expressed genes showing upregulation.Furthermore,qRT-PCR analysis confirmed that the expression of the genes MiCHS7,MiCHI1,MiCHI2,MiFLS,MiF3H2,and MiF3H3 correlated with changes in key flavonoid metabolites.Indeed,correlation analysis indicated that MiCHS7,MiCHI1,MiFLS,and MiF3H3 are potential key genes involved in flavonoid accumulation under UV-B treatment.Thus,our study provides a theoretical basis for breeding for new resilient varieties and developing UV-B-resistant mango cultivation techniques.展开更多
High-resolution remote sensing imagery is essential for critical applications such as precision agriculture,urban management planning,and military reconnaissance.Although significant progress has been made in singleim...High-resolution remote sensing imagery is essential for critical applications such as precision agriculture,urban management planning,and military reconnaissance.Although significant progress has been made in singleimage super-resolution(SISR)using generative adversarial networks(GANs),existing approaches still face challenges in recovering high-frequency details,effectively utilizing features,maintaining structural integrity,and ensuring training stability—particularly when dealing with the complex textures characteristic of remote sensing imagery.To address these limitations,this paper proposes the Improved ResidualModule and AttentionMechanism Network(IRMANet),a novel architecture specifically designed for remote sensing image reconstruction.IRMANet builds upon the Super-Resolution Generative Adversarial Network(SRGAN)framework and introduces several key innovations.First,the Enhanced Residual Unit(ERU)enhances feature reuse and stabilizes training through deep residual connections.Second,the Self-Attention Residual Block(SARB)incorporates a self-attentionmechanism into the Improved Residual Module(IRM)to effectivelymodel long-range dependencies and automatically emphasize salient features.Additionally,the IRM adopts amulti-scale feature fusion strategy to facilitate synergistic interactions between local detail and global semantic information.The effectiveness of each component is validated through ablation studies,while comprehensive comparative experiments on standard remote sensing datasets demonstrate that IRMANet significantly outperforms both the baseline and state-of-the-art methods in terms of perceptual quality and quantitative metrics.Specifically,compared to the baseline model,at a magnification factor of 2,IRMANet achieves an improvement of 0.24 dB in peak signal-to-noise ratio(PSNR)and 0.54 in structural similarity index(SSIM);at a magnification factor of 4,it achieves gains of 0.22 dB in PSNR and 0.51 in SSIM.These results confirm that the proposedmethod effectively enhances detail representation and structural reconstruction accuracy in complex remote sensing scenarios,offering robust technical support for high-precision detection and identification of both military and civilian aircraft.展开更多
With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper pro...With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.展开更多
A versatile spectroelectrochemical measurement method of surface-enhanced Raman scattering spectroscopy is developed,and its capability is assessed in an actual electrochemical system.The spectroelectrochemical cell c...A versatile spectroelectrochemical measurement method of surface-enhanced Raman scattering spectroscopy is developed,and its capability is assessed in an actual electrochemical system.The spectroelectrochemical cell consists of a plasmonic sensor with metal nanoparticles and a wire-type working electrode.The advantages of this method over conventional surface-enhanced Raman scattering methods are as follows:1)surface-enhanced Raman scattering for electrode materials that show little plasmon resonance;and 2)measurement without undesirable influences on the physical and chemical states of the electrode surface and transport phenomena of reaction species.During the measurement,the sensor contacts the working electrode wire at a single point,allowing the surface-enhanced Raman scattering signal to be obtained from the interfacial area of the working electrode surface without significantly disturbing the mass transfer of the reaction species.As plasmon-active metal nanoparticles are modified on the sensor surface in advance,destructive and complicated pretreatment processes on the working electrode are not required.The method is applied to the in situ analysis of electrolyte decomposition reactions in a Li metal battery to reveal the potential of each decomposition product of an organic solvent containing Li.The obtained surface-enhanced Raman scattering spectrum corresponding to the voltammogram reveals the pathway for obtaining decomposition products,such as Li_(2)CO_(3).In particular,Li_(2)O_(2)was clearly detected with our setup.It is also revealed from the setup that the Ni electrode surface,in contrast to the Cu,does not hold a stable Li-containing composite layer.Such in situ chemical information will contribute to the effective interfacial design of high-performance batteries.展开更多
基金Supported by 2025 Henan Medical Education Research Project,No.WJLX2025038.
文摘BACKGROUND Gastrointestinal(GI)tumors are among the most prevalent malignancies,and surgical intervention remains a primary treatment modality.However,the complexity of GI surgery often leads to prolonged recovery and high postoperative complication rates,which threaten patient safety and functional outcomes.Enhanced recovery after surgery(ERAS)principles have been shown to improve perioperative outcomes through evidence-based,multidisciplinary care pathways.Despite its widespread adoption,there is a paucity of research focusing specifically on optimizing ERAS-guided nursing processes in the post-anesthesia care unit(PACU)and evaluating its impact on perioperative safety in patients undergoing GI tumor surgery.This study aimed to investigate whether an ERASbased PACU nursing protocol could enhance recovery,reduce complications,and improve patient safety in this surgical population.AIM To explore the impact of optimizing the recovery room nursing process based on ERAS on the perioperative safety of patients with GI tumors.METHODS A total of 260 patients with GI tumors who underwent elective surgeries under general anesthesia in our hospital from August 2023 to August 2025 and were then observed in the recovery unit(PACU)were selected.They were randomly divided into the observation group(the PACU nursing process was optimized based on ERAS)and the control group(the conventional PACU nursing process was adopted)by the random number grouping method,with 130 cases in each group.The time of gastric tube removal,urinary catheter removal,defecation time,hospital stay,time of leaving the room after tube removal,retention time in the recovery room,occurrence of complications,satisfaction and readmission rate were compared between the two groups after entering the room.Compare the occurrence of adverse events in the PACU nursing process between the two groups.RESULTS The time of gastric tube removal,urinary catheter removal,defecation time,hospital stay,retention time in the recovery room,total incidence of complications and readmission rate in the observation group were significantly lower than those in the control group,and the satisfaction rate was higher than that in the control group(P<0.05).The occurrence of adverse events in the PACU nursing process in the observation group was lower than that in the control group(P<0.05).CONCLUSION Optimizing the PACU nursing process based on ERAS can effectively accelerate the recovery process of patients undergoing GI tumor surgery,reduce adverse events,improve nursing satisfaction,and at the same time,lower the incidence of adverse events in the PACU nursing process,providing a more refined management basis for clinical practice.
文摘Objective:To systematically explore the effectiveness of combining Enhanced Recovery After Surgery(ERAS)nursing and empathy intervention for postoperative patients with glioma.Methods:A total of 54 patients with glioma undergoing surgical treatment were selected for the study.The patients were admitted to the hospital between April 2023 and April 2025.The patients were divided into an observation group(n=27)and a control group(n=27)based on a random number table method.Relevant intervention indicators were compared between the two groups.Results:Compared with the control group,the postoperative recovery indicators in the observation group showed significant differences(P<0.05).After intervention,the scores of stress psychological indicators,FMA,NHISS,and ADL in the observation group were all better than those in the control group(P<0.05).The incidence of complications in the observation group was significantly lower than that in the control group(P<0.05).Conclusion:The combined application of empathy intervention and ERAS nursing effectively regulates the postoperative stress psychological state of patients with glioma,significantly improves their limb and neurological functions as well as daily living abilities,accelerates postoperative recovery,and reduces complications.This approach is feasible for wider implementation.
基金supported by the National Natural Science Foundation of China(Grant Nos.52304139,52325403)the CCTEG Coal Mining Research Institute funding(Grant No.KCYJY-2024-MS-10).
文摘3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.
基金supported by State Grid Shanghai Economic Research Institute under Grant No.SGTYHT/23-JS-004.
文摘Due to the complex structural hierarchy,with deeply nested associative relations between entities such as equipment,specifications,and business processes,intelligent power grid engineering is challenging.Meanwhile,limited by the fragmented data and loss of contextual information,the generated reports are prone to the problems such as content redundancy and omission of critical information,failing to meet the demands of efficient decision-making and accurate management in modern power systems.To address these issues,this paper proposes a knowledge graph(KG)-enhanced framework to automatically generate electric power engineering reports.In the KG construction phase,a feature-fused entity recognition model named BERT-BiLSTM-CRF is adopted to improve the accuracy of entity recognition in scenarios involving power engineering professional terminology,thereby solving the problem of ambiguous entity boundaries in traditional models;then a BERT-attention relation extraction model is proposed to enhance the completeness of extracting complex hierarchical and implicit relations in power grid data.In the report generation phase,an improved Transformer architecture is adopted to accurately transform structured knowledge into natural language reports that comply with engineering specifications,addressing the issue of semantic inconsistency caused by the loss of structural information in existing models.By validating with real-world projects,the results show that the proposed framework significantly outperforms existing baseline models in entity recognition,confirming its superiority and applicability in practical engineering.
基金supported by Yunnan Power Grid Co.,Ltd.Science and Technology Project:Research and application of key technologies for graphical-based power grid accident reconstruction and simulation(YNKJXM20240333).
文摘An optimized volt-ampere reactive(VAR)control framework is proposed for transmission-level power systems to simultaneously mitigate voltage deviations and active-power losses through coordinated control of large-scale wind/solar farms with shunt static var generators(SVGs).The model explicitly represents reactive-power regulation characteristics of doubly-fed wind turbines and PV inverters under real-time meteorological conditions,and quantifies SVG high-speed compensation capability,enabling seamless transition from localized VAR management to a globally coordinated strategy.An enhanced adaptive gain-sharing knowledge optimizer(AGSK-SD)integrates simulated annealing and diversity maintenance to autonomously tune voltage-control actions,renewable source reactive-power set-points,and SVG output.The algorithm adaptively modulates knowledge factors and ratios across search phases,performs SA-based fine-grained local exploitation,and periodically re-injects population diversity to prevent premature convergence.Comprehensive tests on IEEE 9-bus and 39-bus systems demonstrate AGSK-SD’s superiority over NSGA-II and MOPSO in hypervolume(HV),inverse generative distance(IGD),and spread metrics while maintaining acceptable computational burden.The method reduces network losses from 2.7191 to 2.15 MW(20.79%reduction)and from 15.1891 to 11.22 MW(26.16%reduction)in the 9-bus and 39-bus systems respectively.Simultaneously,the cumulative voltage-deviation index decreases from 0.0277 to 3.42×10^(−4) p.u.(98.77%reduction)in the 9-bus system,and from 0.0556 to 0.0107 p.u.(80.76%reduction)in the 39-bus system.These improvements demonstrate significant suppression of line losses and voltage fluctuations.Comparative analysis with traditional heuristic optimization algorithms confirms the superior performance of the proposed approach.
文摘Let G=(V,E)be a connected graph.For an integer h≥0,a subset F■V(G)(resp.F■E(G))of G,if any,is called an h-restricted vertex cut(resp.h-restricted edge cut)of G,if G-F is disconnected and every vertex in G-F has at least h neighbors.The cardinality of a minimum h-restricted vertex-cut(resp.h-restricted edge cut)of G is the h-restricted connectivity(resp.h-restricted edge connectivity)of G,and denoted by κ^(h)(G)(resp.λ^(h)(G)).The enhanced hypercube Q_(n,κ)(1≤k≤n)is a variant of the hypercube Q_(n).In this paper,we consider the h-restricted connectivity of Q_(n,κ) for 2≤k≤n-1.Our main results are as follows:(1)κ^(h)(Q_(n,κ))=2^(h)(n-h+1)for 4≤k≤n-1 and 0≤h≤n-3,λ^(h)(Q_(n,κ))=2^(h)(n-h+1)for 2≤k≤n-1 and 0≤h≤n-2.(2)κ^(h)(Q_(n,3))=2^(h-1)(n-h+1)for n≥5 and 4≤h≤n-1,κ^(h)(Q_(n,2))=2^(h-1)(n-h+1)for n≥4 and 3≤h≤n-1.(3)κ^(3)(Q_(n,3))=6n-16 for n≥5,κ^(2)(Q_(n,3))=4n-8 for n≥4 and κ^(2)(Q_(n,2))=3n-5 for n≥3,κ^(1)(Q_(n,3))=2n and κ^(3)(Q_(n,2))=2n-2 for n≥3.
基金funded by the Deanship of Scientific Research and Libraries,Princess Nourah bint Abdulrahman University,through the Program of Research Project Funding After Publication,grant No.(RPFAP-82-1445)。
文摘This research proposes an improved Puma optimization algorithm(IPuma)as a novel dynamic recon-figuration tool for a photovoltaic(PV)array linked in total-cross-tied(TCT).The proposed algorithm utilizes the Newton-Raphson search rule(NRSR)to boost the exploration process,especially in search spaces with more local regions,and boost the exploitation with adaptive parameters alternating with random parameters in the original Puma.The effectiveness of the introduced IPuma is confirmed through comprehensive evaluations on the CEC’20 benchmark problems.It shows superior performance compared to both established and modern metaheuristic algorithms in terms of effectively navigating the search space and achieving convergence towards near-optimal regions.The findings indicated that the IPuma algorithm demonstrates considerable statistical promise and surpasses the performance of competing algorithms.In addition,the proposed IPuma is utilized to reconfigure a 9×9 PV array that operates under different shade patterns,such as lower triangular(LT),long wide(LW),and short wide(SW).In addition to other programmed approaches,such as the Whale optimization algorithm(WOA),grey wolf optimizer(GWO),Harris Hawks optimization(HHO),particle swarm optimization(PSO),gravitational search algorithm(GSA),biogeography-based optimization(BBO),sine cosine algorithm(SCA),equilibrium optimizer(EO),and original Puma,the indicated method is contrasted to the traditional configurations of TCT and Sudoku.In addition,the metrics of mismatch power loss,maximum efficiency improvement,efficiency improvement ratio,and peak-to-mean ratio are calculated to assess the effectiveness of the indicated approach.The proposed IPuma improved the generated power by 36.72%,28.03%,and 40.97%for SW,LW,and LT,respectively,outperforming the TCT configuration.In addition,it achieved the best maximum efficiency improvement among the algorithms considered,with 26.86%,21.89%,and 29.07%for the examined patterns.The results highlight the superiority and competence of the proposed approach in both convergence rates and stability,as well as applicability to dynamically reconfigure the PV system and enhance its harvested energy.
文摘Objective:To analyze the impact of improved emergency integrated nursing on the treatment effectiveness and safety of emergency trauma patients.Methods:Study duration:December 2024 to December 2025.Observation target:emergency trauma patients in our hospital.Sample size:92 cases.Using computer-based grouping,the 92 patients were divided into two equally sized groups:a control group of 46 patients who received conventional emergency nursing care,and an observation group of 46 patients who underwent an improved emergency integrated nursing model.The treatment-related indicators,treatment effectiveness,and incidence of adverse events were evaluated in both groups.Results:After intervention,the pre-hospital emergency care time,emergency diagnosis time,total emergency rescue duration,and examination waiting time in the control group were all longer than those in the observation group(p<0.05);the treatment effectiveness in the control group(effective rate:82.61%)was worse than that in the observation group(effective rate:95.65%),p<0.05;compared with the control group,the observation group had a lower incidence of adverse events,p<0.05.Conclusion:Implementing an improved emergency integrated nursing model for emergency trauma patients helps streamline the treatment process,enhance treatment effectiveness,and reduce the incidence of adverse events.
基金supported by the National Key R&D Program of China(Nos.2023YFC3404200,2023YFC34042012023YFC3404202)+1 种基金the National Natural Science Foundation of China(No.22575253)the Beijing Natural Science Foundation(No.Z220025)。
文摘The development of synthetic hybrid biological systems integrating photosynthetic organisms with organic-abiotic functional materials holds significant promise for enhancing photosynthetic processes.The artificial regulation of the state transition between photosystem I(PSI)and photosystem II(PSII)represents a strategic and promising approach for improving the efficiency of natural photosynthesis.In this study,we demonstrate that poly(benzimidazolium-phenylthiophene)(CP4)featuring a flexible cationic backbone exhibits superior ultraviolet light-harvesting capability.The polymer CP4 enhanced PSI activity in Chlorella pyrenoidosa(C.pyrenoidosa),subsequently promoting PSII activity and augmenting overall photosynthetic performance.During light-dependent reactions,CP4 significantly accelerated photosynthetic electron transfer,resulting in a 330%increase in the production of oxygen and 93%and 96%increases in the ATP and NADPH contents,respectively.In the context of dark reactions,CP4 facilitated the conversion and utilization of light energy,leading to a 6%increase in both carbohydrate and protein contents.These findings indicate that synthetic light-harvesting polymer materials exhibit considerable application potential in the field of biomass production through enhancement of natural photosynthetic efficiency.
基金funded by the National Natural Science Foundation of China(Grant No.62441212)the Major Project of the Natural Science Foundation of Inner Mongolia(Grant No.2025ZD008).
文摘Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods,this paper proposes the IPKE-MoE framework,which consists of three parts,namely,a sensitive word variant extraction framework,a sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer.First,sensitive word variants are precisely extracted through dynamic iterative prompt templates and the context-aware capabilities of Large Language Models(LLMs).Next,the extracted variants are used to construct a knowledge enhancement layer for sensitive word variants based on RoCBert models.Specifically,after locating variants via n-gram algorithms,variant types are mapped to embedding vectors and fused with original word vectors.Finally,a mixture-of-experts(MoE)classification layer is designed(sensitive word,sentiment,and semantic experts),which decouples the relationship between sensitiveword existence and text toxicity throughmultiple experts.This framework effectively combines the comprehension ability of Large Language Models(LLMs)with the discriminative ability of smaller models.Our two experiments demonstrate that the sensitive word variant extraction framework based on dynamically iterated prompt templates outperforms other baseline prompt templates.TheRoCBert models incorporating the sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer achieve superior classification performance compared to other baselines.
基金financially supported by the National Natural Science Foundation of China(No.52374259)the Open Fund of the State Key Laboratory of Mineral Processing Science and Technology,China(No.BGRIMM-KJSKL-2023-11)the Major Science and Technology Projects in Yunnan Province,China(No.202302 AF080004)。
文摘It is difficult to recover chrysocolla from sulfidation flotation which is closely related to the mineral surface composition.In this study,the effects of fluoride roasting on the surface composition of chrysocolla were investigated,its impact on sulfidation flotation was explored,and the mechanisms involved in both fluoride roasting and sulfidation flotation were discussed.With CaF_(2)as the roasting reagent,Na_(2)S·9H_(2)O as the sulfidation reagent,and sodium butyl xanthate(NaBX)as the collector,the results of the flotation experiments showed that fluoride roasting improved the floatability of chrysocolla,and the recovery rate increased from 16.87%to 82.74%.X-ray diffraction analysis revealed that after fluoride roasting,approximately all the Cu on the chrysocolla surface was exposed in the form of CuO,which could provide a basis for subsequent sulfidation flotation.The microscopy and elemental analyses revealed that large quantities of"pagoda-like"grains were observed on the sulfidation surface of the fluoride-roasted chrysocolla,indicating high crystallinity particles of copper sulfide.This suggests that the effect of sulfide formation on the chrysocolla surface was more pronounced.X-ray photoelectron spectroscopy revealed that fluoride roasting increased the relative contents of sulfur and copper on the surface and that both the Cu~+and polysulfide fractions on the surface of the minerals increased.This enhances the effect of sulfidation,which is conducive to flotation recovery.Therefore,fluoride roasting improved the effect of copper species transformation and sulfidation on the surface of chysocolla,promoted the adsorption of collectors,and improved the recovery of chrysocolla from sulfidation flotation.
基金Project supported by the National Key R&D Program of China(2022YFC2905800)the National Natural Science Foundation of China(52174242)the National Youth Talent Support Program(QNBJ-2023-03)。
文摘Bayan Obo rare earth mine is the largest light rare earth resource worldwide,primarily extracts rare earth elements(REEs)from mixed RE concentrates with bastnaesite and monazite.Nevertheless,the adoption of the concentrated sulfuric acid roasting metallurgical process has resulted in damage to the environment.Therefore,this paper adopted the method of selective mineral phase transformation(MPT)followed by enhanced micro-flotation.By determining the optimal MPT co nditions,the flotation recovery of bastnaesite-roasted products by the collector(phthalic acid,PA)is improved,and the enhanced separation of bastnaesite with monazite is realized.The results show that with the increase of roasting temperature and time,the bastnaesite decomposition product is CeOF and monazite does not change significantly.Subsequent micro-flotation exhibits a gradual decline in the PA consumption of bastnaesiteroasted products,while the flotation recovery of monazite-roasted products remains poor.The artificial mixed ore experiments result in a CeOF foam product with a content of 94.14%and a recovery of 85.80%,and a monazite tank product with a content of 73.53%and a recovery of 87.87%.Compared with the preroasting ore,the surface and interior of bastnaesite-roasted products develop numerous cracks and porosities,and no obvious structural damage is observed in monazite-roasted particles.As the roasting temperature increases,the mineral particles undergo recrystallization or closure,reducing the specific surface area of bastnaesite-roasted products and enhancing hydrophobicity,leading to diminished PA consumption.Fourier transform infrared and other flotation-relation tests show that PA is chemisorbed on the surface of CeOF.The MPT conditions are optimized in this study,which provides a reference for further advancing the efficient separation of bastnaesite and monazite.
基金supported by the National Natural Science Foundation of China(Nos.22203052,22073059 and 22006158)the Education Department of Shaanxi Provincial Government(No.23JC023).
文摘Formic acid(FA)is particularly prominent for its ubiquity and structural simplicity among atmospheric organic acids,and exerts a significant influence on atmospheric acidity.However,the potential contribution of FA to the primary stage of new particle formation(NPF)remains unclear.Herein,molecular dynamics(MD),density functional theory(DFT)and the atmospheric cluster dynamics code(ACDC)model have been utilized to evaluate the mechanism of FA participation in atmospheric SA(sulfuric acid)-A(ammonia)clusters.The MD simulations qualitatively suggest that FA can aggregate with SA and A to form larger clusters,and the aggregation time of the largest clusters decreases as the temperature decreases.The DFT and ACDC findings indicate that the ternary SA-A-FA system is thermodynamically more stable at low temperatures(238.15 K).Simultaneously,in regions with low temperatures,high[FA](10^(11)molecules/cm3),low[SA](106 molecules/cm3)and high[A](10^(11)molecules/cm^(3)),FA significantly enhances SA-A cluster formation rates.The low-temperature NPF mechanism implies that FA could facilitate the growth of pure SA-A clusters via a“catalytic”mechanism and play an integral role in the genesis of critical clusters as a“participant”.This dual role differs from the“catalytic”role exhibited by malonic and glycolic acids in our previous studies.This discovery could help identify the sources of unexplained NPFs in regions with high FA concentrations,such as densely forested areas with abundant vegetation,regions affected by biomass burning,or periods with elevated vehicle exhaust emissions and the release of volatile organic compounds like isoprene and terpenoids.
文摘Enhancing the efficiency of phase-change heat storage is vital for maximizing the utilization of renewable energy.This study examines the synergistic effect of non-uniformly shaped fins and nanoparticles on the melting performance of phase-change storage tanks.The problem is addressed using a finite volume framework coupled with the enthalpy–porosity method,with the numerical model rigorously validated against experimental data.The analysis explores the influence of varying fin deflection angles and nanoparticle concentrations on melting dynamics.It is shown that a downward fin deflection of 6◦reduces melting time to 570 s,representing a 20.8% improvement over uniform fins.Introducing 1% nanoparticles further accelerates melting,reducing time by 36.54% compared to the nanoparticle-free case.The combined strategy of 6◦fin deflection and 1%nanoparticle addition shows the most economic heat storage rate,achieving an exceptional 80.74% enhancement relative to a tank with uniform fins.
基金The National Natural Science Foundation of China(No.52338011)the Start-up Research Fund of Southeast University(No.RF1028624058)+1 种基金the Southeast University Interdisciplinary Research Program for Young Scholarsthe National Key Research and Development Program of China(No.2024YFC3014103).
文摘The virtual preassembly of super-high steel bridge towers faces a challenge in the efficient and precise extraction of complex cross-sectional features.Factors such as fabrication errors,gravity-induced deformations,and temperature fluctuations can compromise the accuracy of contour extraction.To address these limitations,an improved Alpha-shape-based point cloud contour extraction method is proposed.The proposed approach uses a hierarchical strategy to process three-dimensional laser scanning point clouds.The processed data are then subjected to curvatureadaptive voxel filtering to reduce acquisition noise.In addition,an enhanced iterative closest point(ICP)variant with correspondence validation accurately aligns the discrete point cloud segments.The proposed curvature-responsive Alpha-shape framework enables multiscale contour delineation through topology-adaptive threshold modulation,which resolves boundary ambiguities in geometrically complex cross-sections.The method was experimentally validated using field-acquired measurement datasets from the Zhangjinggao Yangtze River Bridge tower segments,confirming its capability to reconstruct noncanonical cross-sectional geometries.Three contour extraction methods,including Poisson reconstruction,the conventional Alpha-shape algorithm,and random sample consensus with ICP(RANSAC-ICP),were compared to evaluate the performance of the proposed Alpha-shape algorithm.The results demonstrate that the proposed method achieves superior contour extraction accuracy and data reduction efficiency,highlighting its effectiveness in contour extraction tasks.
基金financially supported by the National Natural Science Foundation of China(Grant No.32160677)the Hainan University Mango Research System.
文摘Mango(Mangifera indica L.)is one of the main economic crops in Hainan,China,prized for its distinctive flavor and high nutritional value.It is also rich in health-promoting antioxidants such as vitamin C and flavonoids.Enhanced ultraviolet-B(UV—B)radiation,a growing global environmental concern,alters plant antioxidant systems,with increased flavonoid accumulation as a common adaptive response.However,its effects on mango fruit remain largely unexplored.To investigate the antioxidant responses of mango to enhanced UV-B radiation and identify key responsive flavonoid compounds and regulatory genes,we exposed‘Tainong 1’mango fruits growing under natural light to 96 kJ·m^(-2)·d^(-1)of UV-B radiation to simulate high UV-B conditions.Treated fruits were smaller in size and had a pulp of a more intense yellow colour.Further,malondialdehyde content in treated fruits was higher during the phase of rapid fruit enlargement.Additionally,treated fruits showed increased sugar-acid ratios,total phenol,total flavonoid,carotenoid,and ascorbic acid contents.Furthermore,they showed significantly enhanced antioxidant activity,as measured by the FRAP,ABTS,and DPPH assays.Extensive targeted metabolomic-analysis identified flavonoids as the largest category of compounds differentially expressed in treated and control groups.Quantitative metabolomics of flavonoids identified hyperoside,quercimeritrin,and(-)-catechin gallate as the key flavonoid metabolites responsive to UV-B treatment.Transcriptome analysis revealed an enrichment of the flavonoid biosynthesis pathway,with most associated differentially expressed genes showing upregulation.Furthermore,qRT-PCR analysis confirmed that the expression of the genes MiCHS7,MiCHI1,MiCHI2,MiFLS,MiF3H2,and MiF3H3 correlated with changes in key flavonoid metabolites.Indeed,correlation analysis indicated that MiCHS7,MiCHI1,MiFLS,and MiF3H3 are potential key genes involved in flavonoid accumulation under UV-B treatment.Thus,our study provides a theoretical basis for breeding for new resilient varieties and developing UV-B-resistant mango cultivation techniques.
基金funded by the Henan Province Key R&D Program Project,“Research and Application Demonstration of Class Ⅱ Superlattice Medium Wave High Temperature Infrared Detector Technology”,grant number 231111210400.
文摘High-resolution remote sensing imagery is essential for critical applications such as precision agriculture,urban management planning,and military reconnaissance.Although significant progress has been made in singleimage super-resolution(SISR)using generative adversarial networks(GANs),existing approaches still face challenges in recovering high-frequency details,effectively utilizing features,maintaining structural integrity,and ensuring training stability—particularly when dealing with the complex textures characteristic of remote sensing imagery.To address these limitations,this paper proposes the Improved ResidualModule and AttentionMechanism Network(IRMANet),a novel architecture specifically designed for remote sensing image reconstruction.IRMANet builds upon the Super-Resolution Generative Adversarial Network(SRGAN)framework and introduces several key innovations.First,the Enhanced Residual Unit(ERU)enhances feature reuse and stabilizes training through deep residual connections.Second,the Self-Attention Residual Block(SARB)incorporates a self-attentionmechanism into the Improved Residual Module(IRM)to effectivelymodel long-range dependencies and automatically emphasize salient features.Additionally,the IRM adopts amulti-scale feature fusion strategy to facilitate synergistic interactions between local detail and global semantic information.The effectiveness of each component is validated through ablation studies,while comprehensive comparative experiments on standard remote sensing datasets demonstrate that IRMANet significantly outperforms both the baseline and state-of-the-art methods in terms of perceptual quality and quantitative metrics.Specifically,compared to the baseline model,at a magnification factor of 2,IRMANet achieves an improvement of 0.24 dB in peak signal-to-noise ratio(PSNR)and 0.54 in structural similarity index(SSIM);at a magnification factor of 4,it achieves gains of 0.22 dB in PSNR and 0.51 in SSIM.These results confirm that the proposedmethod effectively enhances detail representation and structural reconstruction accuracy in complex remote sensing scenarios,offering robust technical support for high-precision detection and identification of both military and civilian aircraft.
文摘With the rapid development of intelligent navigation technology,efficient and safe path planning for mobile robots has become a core requirement.To address the challenges of complex dynamic environments,this paper proposes an intelligent path planning framework based on grid map modeling.First,an improved Safe and Smooth A*(SSA*)algorithm is employed for global path planning.By incorporating obstacle expansion and cornerpoint optimization,the proposed SSA*enhances the safety and smoothness of the planned path.Then,a Partitioned Dynamic Window Approach(PDWA)is integrated for local planning,which is triggered when dynamic or sudden static obstacles appear,enabling real-time obstacle avoidance and path adjustment.A unified objective function is constructed,considering path length,safety,and smoothness comprehensively.Multiple simulation experiments are conducted on typical port grid maps.The results demonstrate that the improved SSA*significantly reduces the number of expanded nodes and computation time in static environmentswhile generating smoother and safer paths.Meanwhile,the PDWA exhibits strong real-time performance and robustness in dynamic scenarios,achieving shorter paths and lower planning times compared to other graph search algorithms.The proposedmethodmaintains stable performance across maps of different scales and various port scenarios,verifying its practicality and potential for wider application.
基金is partly based on the results obtained from the“Research and Development Initiative for Scientific Innovation of New Generation Batteries 2 and 3(RISING2 and RISING3)”projects commissioned by the New EnergyIndustrial Technology Development Organization(NEDO),Japan(Project codes:JPNP16001 and JPNP21006).
文摘A versatile spectroelectrochemical measurement method of surface-enhanced Raman scattering spectroscopy is developed,and its capability is assessed in an actual electrochemical system.The spectroelectrochemical cell consists of a plasmonic sensor with metal nanoparticles and a wire-type working electrode.The advantages of this method over conventional surface-enhanced Raman scattering methods are as follows:1)surface-enhanced Raman scattering for electrode materials that show little plasmon resonance;and 2)measurement without undesirable influences on the physical and chemical states of the electrode surface and transport phenomena of reaction species.During the measurement,the sensor contacts the working electrode wire at a single point,allowing the surface-enhanced Raman scattering signal to be obtained from the interfacial area of the working electrode surface without significantly disturbing the mass transfer of the reaction species.As plasmon-active metal nanoparticles are modified on the sensor surface in advance,destructive and complicated pretreatment processes on the working electrode are not required.The method is applied to the in situ analysis of electrolyte decomposition reactions in a Li metal battery to reveal the potential of each decomposition product of an organic solvent containing Li.The obtained surface-enhanced Raman scattering spectrum corresponding to the voltammogram reveals the pathway for obtaining decomposition products,such as Li_(2)CO_(3).In particular,Li_(2)O_(2)was clearly detected with our setup.It is also revealed from the setup that the Ni electrode surface,in contrast to the Cu,does not hold a stable Li-containing composite layer.Such in situ chemical information will contribute to the effective interfacial design of high-performance batteries.
