Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their dia...Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.展开更多
The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adver...The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adversarial network(GAN)algorithm was proposed.Taking GAN as the basic framework,it combined a depthwise separable convolution module,attention mechanism,and reconstructed convolution module to realize the enhancement of underwater degraded images.Multi-scale features were captured by the depthwise separable convolution module,and the attention mechanism was utilized to enhance attention to important features.The reconstructed convolution module further extracts and fuses local and global features.Experimental results showed that the algorithm performs well in improving the color bias and blurring of underwater images,with PSNR reaching 27.835,SSIM reaching 0.883,UIQM reaching 3.205,and UCIQE reaching 0.713.The enhanced image outperforms the comparison algorithm in both subjective and objective metrics.展开更多
Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).Ho...Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).However,the detection and screening of transgenic lines remain major bottlenecks,being time-consuming,labor-intensive,and inefficient during transformation and subsequent mutation identification.A simple and efficient visual marker system plays a critical role in addressing these challenges.Recent studies demonstrated that the GmW1 and RUBY reporter systems were used to obtain visual transgenic soybean(Glycine max) plants(Chen L et al.2023;Chen et al.2024).展开更多
Chitosan(CS),a natural polymer derived from chitin found in the exoskeletons of crustaceans,has garnered significant interest in the pharmaceutical field due to its unique properties,including biocompatibility and bio...Chitosan(CS),a natural polymer derived from chitin found in the exoskeletons of crustaceans,has garnered significant interest in the pharmaceutical field due to its unique properties,including biocompatibility and biodegradability.In recent years,various studies have reported that CS can affect drug bioavailability,and interestingly,it works as an oral absorption enhancer and inhibitor.This review offers an in-depth analysis of the mechanisms underlying such a phenomenon and supports its application as a pharmaceutical excipient.CS enhances oral drug absorption through various mechanisms,such as interaction with the intestinal mucosa,tight junction modulation,inhibition of efflux transporters,enzyme inhibition,solubility and stability enhancement,and complexation.On the other side,CS exhibits the ability to inhibit the absorption of certain drugs by adsorbing to lipids and sterols,modulating bile acids and gut microbiota,altering drug-cell interaction at the polar interface,and mucus-mediated entrapment and interference.Future potential pharmaceutical research in this field includes elucidating the underneath absorption relevant mechanisms,rational use in formulations as excipient,exploring functional CS derivatives,and developing CS-based drug delivery systems.This comprehensive review highlights CS's versatile and significant role in enhancing and inhibiting oral drug absorption,providing insights into the complexities of drug delivery and the potential of CS to improve therapeutic outcomes.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
Background:Long non-coding RNAs(lncRNAs)act as epigenetic regulators for tumor hallmarks.This investigation sought to probe the carcinogenic trait of PAN3-AS1 across pan-cancer comprehensively.Methods:We studied the d...Background:Long non-coding RNAs(lncRNAs)act as epigenetic regulators for tumor hallmarks.This investigation sought to probe the carcinogenic trait of PAN3-AS1 across pan-cancer comprehensively.Methods:We studied the diagnostic and prognostic features and the immune landscape of PAN3-AS1 across pan-cancer by bioinformatics approaches.The hierarchical regulatory networks governing PAN3-AS1 expression in colon cancer were explored via chromatin immunoprecipitation,luciferase activity assays,and RNA immunoprecipitation,etc.We screened drugs sensitive to WAP four-disulfide core domain 13(WFDC13)by virtual screening and molecular docking.Results:Single-cell transcriptomics demonstrated that a variety of immune populations abnormally expressed PAN3-AS1 beyond tumor cells.Integration of data from multiple databases revealed that PAN3-AS1 was highly expressed and associated with a bad prognosis in various malignancies.Notably,PAN3-AS1 expression was correlated with a suppressive immune microenvironment.Moreover,we observed poor immunotherapy efficacy when PAN3-AS1 was highly expressed in melanoma.In vitro assays and functional enrichment analysis revealed that PAN3-AS1 was associated with cell proliferation and the immune response in colon cancer.Our experiments confirmed that PAN3-AS1 facilitated WFDC13 expression through competitive binding to hsa-miR-423-5p in colon cancer.Moreover,the present paper illustrated that enhancer activity exerts an important modulatory ability for PAN3-AS1 expression.Conclusion:In short,PAN3-AS1 is a valuable biomarker for diagnosis and prognosis.PAN3-AS1 exhibits linkage to a cold tumor immune microenvironment(TME)and forecasts durable benefit from immunotherapy.Addressing the PAN3-AS1/miR-423-5p/WFDC13 axis might provide a novel option for improving immunotherapy efficacy in colon cancer.展开更多
Vertebrate axis patterning requires precise control of the differentiation of neuromesodermal progenitors(NMPs),which generate spinal cord(SC)and presomitic mesoderm(PSM).Previously,we identified a gastrula-premarked ...Vertebrate axis patterning requires precise control of the differentiation of neuromesodermal progenitors(NMPs),which generate spinal cord(SC)and presomitic mesoderm(PSM).Previously,we identified a gastrula-premarked posterior enhancer(p-Enh)that is essential for posterior tissue development by regulating somite and SC in organogenetic embryos,while its role in early NMPs cells remains elusive.Here,using a highly efficient in vitro differentiation system,we found that the genetic removal of p-Enh leads to the aberrantly up-regulated PSM-related genes during both PSM and SC differentiation.Time-resolved transcriptomic analysis and experimental characterization revealed the activated PSM transcriptomic signature arose from disorganized NMPs composition,with an over-representation of the T^(high)SOX2^(low)NMPs subtype.Besides,through a newly developed bioinformatic tool,ST-Pheno,which effectively bridges the in vitro samples to in vivo embryonic phenotypes within spatiotemporal context,we determined that the over-produced T^(high)SOX2^(low)NMPs subtype is predominantly enriched in the anterior primitive streak and adjacent mesoderm region at E7.5,which may disrupt the proper development of NMPs towards prospective PSM and SC,ultimately leading to the posterior development failure.In summary,this study demonstrates a critical role of p-Enh in regulating NMPs subtype composition,which will broaden the molecular understanding of mammalian embryogenesis.展开更多
Weakly Supervised Semantic Segmentation(WSSS),which relies only on image-level labels,has attracted significant attention for its cost-effectiveness and scalability.Existing methods mainly enhance inter-class distinct...Weakly Supervised Semantic Segmentation(WSSS),which relies only on image-level labels,has attracted significant attention for its cost-effectiveness and scalability.Existing methods mainly enhance inter-class distinctions and employ data augmentation to mitigate semantic ambiguity and reduce spurious activations.However,they often neglect the complex contextual dependencies among image patches,resulting in incomplete local representations and limited segmentation accuracy.To address these issues,we propose the Context Patch Fusion with Class Token Enhancement(CPF-CTE)framework,which exploits contextual relations among patches to enrich feature repre-sentations and improve segmentation.At its core,the Contextual-Fusion Bidirectional Long Short-Term Memory(CF-BiLSTM)module captures spatial dependencies between patches and enables bidirectional information flow,yield-ing a more comprehensive understanding of spatial correlations.This strengthens feature learning and segmentation robustness.Moreover,we introduce learnable class tokens that dynamically encode and refine class-specific semantics,enhancing discriminative capability.By effectively integrating spatial and semantic cues,CPF-CTE produces richer and more accurate representations of image content.Extensive experiments on PASCAL VOC 2012 and MS COCO 2014 validate that CPF-CTE consistently surpasses prior WSSS methods.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
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
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
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
Low-light image enhancement(LLIE)remains challenging due to underexposure,color distortion,and amplified noise introduced during illumination correction.Existing deep learning–based methods typically apply uniform en...Low-light image enhancement(LLIE)remains challenging due to underexposure,color distortion,and amplified noise introduced during illumination correction.Existing deep learning–based methods typically apply uniform enhancement across the entire image,which overlooks scene semantics and often leads to texture degradation or unnatural color reproduction.To overcome these limitations,we propose a Semantic-Guided Visual Mamba Network(SGVMNet)that unifies semantic reasoning,state-space modeling,and mixture-of-experts routing for adaptive illumination correction.SGVMNet comprises three key components:(1)a semantic modulation module(SMM)that extracts scene-aware semantic priors from pretrained multimodal models—Large Language and Vision Assistant(LLaVA)and Contrastive Language–Image Pretraining(CLIP)—and injects them hierarchically into the feature stream;(2)aMixture-of-Experts State-Space Feature EnhancementModule(MoE-SSMFEM)that dynamically selects informative channels and activates specialized state-space experts for efficient global–local illumination modeling;and(3)a Text-Guided Mixture Mamba Block(TGMB)that fuses semantic priors and visual features through bidirectional state propagation.Experimental results demonstrate that on the low-light(LOL)dataset,SGVMNet outperforms other state-of-the-art methods in both quantitative and qualitative evaluations,and it also maintains low computational complexity with fast inference speed.On LOLv2-Syn,SGVMNet achieves 26.512 dB PSNR and 0.935 SSIM,outperforming RetinexFormer by 0.61 dB.On LOLv1,SGVMNet attains 26.50 dB PSNR and 0.863 SSIM.Furthermore,experiments on multiple unpaired real-world datasets further validate the superiority of SGVMNet,showing that the model not only exhibits strong cross-scene generalization ability but also effectively preserves semantic consistency and visual naturalness.展开更多
Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learni...Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.展开更多
Within contemporary healthcare systems, professional identity among specialized nurses serves as a pivotal intrinsic factor influencing the development of their core competencies. This review synthesizes existing rese...Within contemporary healthcare systems, professional identity among specialized nurses serves as a pivotal intrinsic factor influencing the development of their core competencies. This review synthesizes existing research, revealing that professional identity positively impacts the development of core competencies through multiple pathways, including psychological drive, behavioral facilitation, teamwork, and career stability. Building on this analysis, this paper proposes systematic enhancement strategies from four dimensions: education and training, organizational environment, cultural development, and individual growth, aiming to provide a reference for nursing practice and professional development.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
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
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
Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater imag...Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater image enhancement methods,although they can improve the image quality to some extent,often lead to problems such as detail loss and edge blurring.To address these problems,we propose FENet,an efficient underwater image enhancement method.FENet first obtains three different scales of images by image downsampling and then transforms them into the frequency domain to extract the low-frequency and high-frequency spectra,respectively.Then,a distance mask and a mean mask are constructed based on the distance and magnitude mean for enhancing the high-frequency part,thus improving the image details and enhancing the effect by suppressing the noise in the low-frequency part.Affected by the light scattering of underwater images and the fact that some details are lost if they are directly reduced to the spatial domain after the frequency domain operation.For this reason,we propose a multi-stage residual feature aggregation module,which focuses on detail extraction and effectively avoids information loss caused by global enhancement.Finally,we combine the edge guidance strategy to further enhance the edge details of the image.Experimental results indicate that FENet outperforms current state-of-the-art underwater image enhancement methods in quantitative and qualitative evaluations on multiple publicly available datasets.展开更多
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant No.(IFPDP-261-22).
文摘Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.
文摘The existence of absorption and reflection of light underwater leads to problems such as color distortion and blue-green bias in underwater images.In this study,a depthwise separable convolution-based generative adversarial network(GAN)algorithm was proposed.Taking GAN as the basic framework,it combined a depthwise separable convolution module,attention mechanism,and reconstructed convolution module to realize the enhancement of underwater degraded images.Multi-scale features were captured by the depthwise separable convolution module,and the attention mechanism was utilized to enhance attention to important features.The reconstructed convolution module further extracts and fuses local and global features.Experimental results showed that the algorithm performs well in improving the color bias and blurring of underwater images,with PSNR reaching 27.835,SSIM reaching 0.883,UIQM reaching 3.205,and UCIQE reaching 0.713.The enhanced image outperforms the comparison algorithm in both subjective and objective metrics.
基金supported by the Jilin Science and Technology Development Program,China (20240602032RC)the Jilin Agricultural Science and Technology Innovation Project,China (CXGC2024ZD001)+1 种基金the Jilin Agricultural Science and Technology Innovation Project,China (CXGC2024ZY012)the Jilin Province Development and Reform Commission-Project for Improving the Independent Innovation Capacity of Major Grain Crops,China (2024C002)。
文摘Emerging and powerful genome editing tools,particularly CRISPR/Cas9,are facilitating functional genomics research and accelerating crop improvement(Jiang et al.2021;Cao et al.2023;Chen C et al.2023;Liu et al.2023a).However,the detection and screening of transgenic lines remain major bottlenecks,being time-consuming,labor-intensive,and inefficient during transformation and subsequent mutation identification.A simple and efficient visual marker system plays a critical role in addressing these challenges.Recent studies demonstrated that the GmW1 and RUBY reporter systems were used to obtain visual transgenic soybean(Glycine max) plants(Chen L et al.2023;Chen et al.2024).
基金financially supported by National Key Research and Development Program of China (No.2021YFD1800900)National Natural Science Foundation of China (No.82073790)+2 种基金Special Fund for Youth Team of Southwest University (No.SWUXJLJ202306)Chongqing Science and Technology Commission (Nos.CSTB2022TIAD-LUX0001,CSTB2023NSCQ-JQX0002)Innovation Research 2035 Pilot Plan of Southwest University (No.SWUXDPY22007)。
文摘Chitosan(CS),a natural polymer derived from chitin found in the exoskeletons of crustaceans,has garnered significant interest in the pharmaceutical field due to its unique properties,including biocompatibility and biodegradability.In recent years,various studies have reported that CS can affect drug bioavailability,and interestingly,it works as an oral absorption enhancer and inhibitor.This review offers an in-depth analysis of the mechanisms underlying such a phenomenon and supports its application as a pharmaceutical excipient.CS enhances oral drug absorption through various mechanisms,such as interaction with the intestinal mucosa,tight junction modulation,inhibition of efflux transporters,enzyme inhibition,solubility and stability enhancement,and complexation.On the other side,CS exhibits the ability to inhibit the absorption of certain drugs by adsorbing to lipids and sterols,modulating bile acids and gut microbiota,altering drug-cell interaction at the polar interface,and mucus-mediated entrapment and interference.Future potential pharmaceutical research in this field includes elucidating the underneath absorption relevant mechanisms,rational use in formulations as excipient,exploring functional CS derivatives,and developing CS-based drug delivery systems.This comprehensive review highlights CS's versatile and significant role in enhancing and inhibiting oral drug absorption,providing insights into the complexities of drug delivery and the potential of CS to improve therapeutic outcomes.
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supported by the Shandong Province Medical and Health Technology Project(202303111442).
文摘Background:Long non-coding RNAs(lncRNAs)act as epigenetic regulators for tumor hallmarks.This investigation sought to probe the carcinogenic trait of PAN3-AS1 across pan-cancer comprehensively.Methods:We studied the diagnostic and prognostic features and the immune landscape of PAN3-AS1 across pan-cancer by bioinformatics approaches.The hierarchical regulatory networks governing PAN3-AS1 expression in colon cancer were explored via chromatin immunoprecipitation,luciferase activity assays,and RNA immunoprecipitation,etc.We screened drugs sensitive to WAP four-disulfide core domain 13(WFDC13)by virtual screening and molecular docking.Results:Single-cell transcriptomics demonstrated that a variety of immune populations abnormally expressed PAN3-AS1 beyond tumor cells.Integration of data from multiple databases revealed that PAN3-AS1 was highly expressed and associated with a bad prognosis in various malignancies.Notably,PAN3-AS1 expression was correlated with a suppressive immune microenvironment.Moreover,we observed poor immunotherapy efficacy when PAN3-AS1 was highly expressed in melanoma.In vitro assays and functional enrichment analysis revealed that PAN3-AS1 was associated with cell proliferation and the immune response in colon cancer.Our experiments confirmed that PAN3-AS1 facilitated WFDC13 expression through competitive binding to hsa-miR-423-5p in colon cancer.Moreover,the present paper illustrated that enhancer activity exerts an important modulatory ability for PAN3-AS1 expression.Conclusion:In short,PAN3-AS1 is a valuable biomarker for diagnosis and prognosis.PAN3-AS1 exhibits linkage to a cold tumor immune microenvironment(TME)and forecasts durable benefit from immunotherapy.Addressing the PAN3-AS1/miR-423-5p/WFDC13 axis might provide a novel option for improving immunotherapy efficacy in colon cancer.
基金supported in part by the National Key Basic Research and Development Program of China(2025YFE0200600,2018YFA0800100,2019YFA0801402)the Major Project of Guangzhou National Laboratory(GZNL2025C02014,GZNL2023A02005)+1 种基金the National Natural Science Foundation of China(32130030,32470866,31900454)the Union Project by Guangzhou National Laboratory and State Key Laboratory of Respiratory Disease,Guangzhou Medical University(GZNL2024B01007).
文摘Vertebrate axis patterning requires precise control of the differentiation of neuromesodermal progenitors(NMPs),which generate spinal cord(SC)and presomitic mesoderm(PSM).Previously,we identified a gastrula-premarked posterior enhancer(p-Enh)that is essential for posterior tissue development by regulating somite and SC in organogenetic embryos,while its role in early NMPs cells remains elusive.Here,using a highly efficient in vitro differentiation system,we found that the genetic removal of p-Enh leads to the aberrantly up-regulated PSM-related genes during both PSM and SC differentiation.Time-resolved transcriptomic analysis and experimental characterization revealed the activated PSM transcriptomic signature arose from disorganized NMPs composition,with an over-representation of the T^(high)SOX2^(low)NMPs subtype.Besides,through a newly developed bioinformatic tool,ST-Pheno,which effectively bridges the in vitro samples to in vivo embryonic phenotypes within spatiotemporal context,we determined that the over-produced T^(high)SOX2^(low)NMPs subtype is predominantly enriched in the anterior primitive streak and adjacent mesoderm region at E7.5,which may disrupt the proper development of NMPs towards prospective PSM and SC,ultimately leading to the posterior development failure.In summary,this study demonstrates a critical role of p-Enh in regulating NMPs subtype composition,which will broaden the molecular understanding of mammalian embryogenesis.
文摘Weakly Supervised Semantic Segmentation(WSSS),which relies only on image-level labels,has attracted significant attention for its cost-effectiveness and scalability.Existing methods mainly enhance inter-class distinctions and employ data augmentation to mitigate semantic ambiguity and reduce spurious activations.However,they often neglect the complex contextual dependencies among image patches,resulting in incomplete local representations and limited segmentation accuracy.To address these issues,we propose the Context Patch Fusion with Class Token Enhancement(CPF-CTE)framework,which exploits contextual relations among patches to enrich feature repre-sentations and improve segmentation.At its core,the Contextual-Fusion Bidirectional Long Short-Term Memory(CF-BiLSTM)module captures spatial dependencies between patches and enables bidirectional information flow,yield-ing a more comprehensive understanding of spatial correlations.This strengthens feature learning and segmentation robustness.Moreover,we introduce learnable class tokens that dynamically encode and refine class-specific semantics,enhancing discriminative capability.By effectively integrating spatial and semantic cues,CPF-CTE produces richer and more accurate representations of image content.Extensive experiments on PASCAL VOC 2012 and MS COCO 2014 validate that CPF-CTE consistently surpasses prior WSSS methods.
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 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.
文摘Low-light image enhancement(LLIE)remains challenging due to underexposure,color distortion,and amplified noise introduced during illumination correction.Existing deep learning–based methods typically apply uniform enhancement across the entire image,which overlooks scene semantics and often leads to texture degradation or unnatural color reproduction.To overcome these limitations,we propose a Semantic-Guided Visual Mamba Network(SGVMNet)that unifies semantic reasoning,state-space modeling,and mixture-of-experts routing for adaptive illumination correction.SGVMNet comprises three key components:(1)a semantic modulation module(SMM)that extracts scene-aware semantic priors from pretrained multimodal models—Large Language and Vision Assistant(LLaVA)and Contrastive Language–Image Pretraining(CLIP)—and injects them hierarchically into the feature stream;(2)aMixture-of-Experts State-Space Feature EnhancementModule(MoE-SSMFEM)that dynamically selects informative channels and activates specialized state-space experts for efficient global–local illumination modeling;and(3)a Text-Guided Mixture Mamba Block(TGMB)that fuses semantic priors and visual features through bidirectional state propagation.Experimental results demonstrate that on the low-light(LOL)dataset,SGVMNet outperforms other state-of-the-art methods in both quantitative and qualitative evaluations,and it also maintains low computational complexity with fast inference speed.On LOLv2-Syn,SGVMNet achieves 26.512 dB PSNR and 0.935 SSIM,outperforming RetinexFormer by 0.61 dB.On LOLv1,SGVMNet attains 26.50 dB PSNR and 0.863 SSIM.Furthermore,experiments on multiple unpaired real-world datasets further validate the superiority of SGVMNet,showing that the model not only exhibits strong cross-scene generalization ability but also effectively preserves semantic consistency and visual naturalness.
基金supported in part by the National Natural Science Foundation of China(62472146)the Key Technologies Research Development Joint Foundation of Henan Province of China(225101610001)。
文摘Deep transfer learning has achieved significant success in anomaly detection over the past decade,but data acquisition challenges in practical engineering hinder high-quality feature representation for few-shot learning tasks.To address this issue,a novel time-frequency-assisted deep feature enhancement(TFE)mechanism is proposed.Unlike traditional methods that integrate time-frequency analysis with deep neural networks,TFE employs a wavelet scattering transform to establish a parallel time-frequency feature space,where a dual interaction strategy facilitates collaboration between deep feature and time-frequency spaces through two operations:1)Enhancement,where a frequency-importance-driven contrastive learning(FICL)network transfers physically-aware information from wavelet scattering features to deep features,and 2)Feedback,which uses a detection rule adaptation module to minimize bias in wavelet scattering features based on deep feature performance.TFE is applied to a domain-adversarial anomaly detection framework and,through alternating training,significantly enhances both deep feature discriminative power and few-shot anomaly detection.Theoretical analysis confirms that the proposed dual interaction strategy reduces the upper bound of classification error.Experiments on benchmark datasets and a real-world industrial dataset from a large steel factory demonstrate TFE's superior performance and highlight the importance of frequency saliency in transfer learning.Thus,collaboration is shown to outperform integration for few-shot transfer learning in anomaly detection.
文摘Within contemporary healthcare systems, professional identity among specialized nurses serves as a pivotal intrinsic factor influencing the development of their core competencies. This review synthesizes existing research, revealing that professional identity positively impacts the development of core competencies through multiple pathways, including psychological drive, behavioral facilitation, teamwork, and career stability. Building on this analysis, this paper proposes systematic enhancement strategies from four dimensions: education and training, organizational environment, cultural development, and individual growth, aiming to provide a reference for nursing practice and professional development.
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.
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.
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supported in part by the National Natural Science Foundation of China[Grant number 62471075]the Major Science and Technology Project Grant of the Chongqing Municipal Education Commission[Grant number KJZD-M202301901].
文摘Underwater images often affect the effectiveness of underwater visual tasks due to problems such as light scattering,color distortion,and detail blurring,limiting their application performance.Existing underwater image enhancement methods,although they can improve the image quality to some extent,often lead to problems such as detail loss and edge blurring.To address these problems,we propose FENet,an efficient underwater image enhancement method.FENet first obtains three different scales of images by image downsampling and then transforms them into the frequency domain to extract the low-frequency and high-frequency spectra,respectively.Then,a distance mask and a mean mask are constructed based on the distance and magnitude mean for enhancing the high-frequency part,thus improving the image details and enhancing the effect by suppressing the noise in the low-frequency part.Affected by the light scattering of underwater images and the fact that some details are lost if they are directly reduced to the spatial domain after the frequency domain operation.For this reason,we propose a multi-stage residual feature aggregation module,which focuses on detail extraction and effectively avoids information loss caused by global enhancement.Finally,we combine the edge guidance strategy to further enhance the edge details of the image.Experimental results indicate that FENet outperforms current state-of-the-art underwater image enhancement methods in quantitative and qualitative evaluations on multiple publicly available datasets.
