Strong coupling and catenary field enhancement in the hybrid plasmonic metamaterial cavity and TMDC monolayers

Strong coupling between resonantly matched surface plasmons of metals and excitons of quantum emitters results in the formation of new plasmon-exciton hybridized energy states.In plasmon-exciton strong coupling,plasmonic nanocavities play a significant role due to their ability to confine light in an ultrasmall volume.Additionally,two-dimensional transition metal dichalcogenides(TMDCs) have a significant exciton binding energy and remain stable at ambient conditions,making them an excellent alternative for investigating light-matter interactions.As a result,strong plasmon-exciton coupling has been reported by introducing a single metallic cavity.However,single nanoparticles have lower spatial confinement of electromagnetic fields and limited tunability to match the excitonic resonance.Here,we introduce the concept of catenary-shaped optical fields induced by plasmonic metamaterial cavities to scale the strength of plasmon-exciton coupling.The demonstrated plasmon modes of metallic metamaterial cavities offer high confinement and tunability and can match with the excitons of TMDCs to exhibit a strong coupling regime by tuning either the size of the cavity gap or thickness.The calculated Rabi splitting of Au-MoSe_2 and Au-WSe_2 heterostructures strongly depends on the catenary-like field enhancement induced by the Au cavity,resulting in room-temperature Rabi splitting ranging between 77.86 and 320 me V.These plasmonic metamaterial cavities can pave the way for manipulating excitons in TMDCs and operating active nanophotonic devices at ambient temperature.

A theoretical study of the signal enhancement mechanism of coaxial DP-LIBS

In the field of dual-pulse laser-induced breakdown spectroscopy(DP-LIBS)research,the pursuit of methods for determining pulse intervals and other parameters quickly and conveniently in order to achieve optimal spectral signal enhancement is paramount.To aid researchers in identification of optimal signal enhancement conditions and more accurate interpretation of the underlying signal enhancement mechanisms,theoretical simulations of the spatiotemporal processes of coaxial DP-LIBS-induced plasma have been established in this work.Using a model based on laser ablation and two-dimensional axisymmetric fluid dynamics,plasma evolutions during aluminum–magnesium alloy laser ablation under single-pulse and coaxial dualpulse excitations have been simulated.The influences of factors,such as delay time,laser fluence,plasma temperature,and particle number density,on the DP-LIBS spectral signals are investigated.Under pulse intervals ranging from 50 to 1500 ns,the time evolutions of spectral line intensity,dual-pulse emission enhancement relative to the single-pulse results,laser irradiance,spatial distribution of plasma temperature and species number density,as well as laser irradiance shielded by plasma have been obtained.The study indicates that the main reason behind the radiation signal enhancement in coaxial DP-LIBS-induced plasma is attributed to the increased species number density and plasma temperature caused by the second laser,and it is inferred that the shielding effect of the plasma mainly occurs in the boundary layer of the stagnation point flow over the target surface.This research provides a theoretical basis for experimental research,parameter optimization,and signal enhancement tracing in DP-LIBS.

Identifying the enhancement mechanism of Al/MoO_(3) reactive multilayered films on the ignition ability of semiconductor bridge using a one-dimensional gas-solid two-phase flow model

Energetic Semiconductor bridge(ESCB)based on reactive multilayered films(RMFs)has a promising application in the miniature and intelligence of initiator and pyrotechnics device.Understanding the ignition enhancement mechanism of RMFs on semiconductor bridge(SCB)during the ignition process is crucial for the engineering and practical application of advanced initiator and pyrotechnics devices.In this study,a one-dimensional(1D)gas-solid two-phase flow ignition model was established to study the ignition process of ESCB to charge particles based on the reactivity of Al/MoO_(3) RMFs.In order to fully consider the coupled exothermic between the RMFs and the SCB plasma during the ignition process,the heat release of chemical reaction in RMFs was used as an internal heat source in this model.It is found that the exothermal reaction in RMFs improved the ignition performance of SCB.In the process of plasma rapid condensation with heat release,the product of RMFs enhanced the heat transfer process between the gas phase and the solid charge particle,which accelerated the expansion of hot plasma,and heated the solid charge particle as well as gas phase region with low temperature.In addition,it made up for pressure loss in the gas phase.During the plasma dissipation process,the exothermal chemical reaction in RMFs acted as the main heating source to heat the charge particle,making the surface temperature of the charge particle,gas pressure,and gas temperature rise continuously.This result may yield significant advantages in providing a universal ignition model for miniaturized ignition devices.

The Tenth Anniversary of Free Trade Pilot Zones in China:Fundamental Experiences and Enhancement Strategies

Since the 18th National Congress of the Communist Party of China,the country has established 21 Free Trade Pilot Zones(FTZs),achieving significant pioneering results in reform and opening up and creating a strong demonstrative effect nationwide.The basic experience from a decade of FTZs includes:adhering to the centralized and unified leadership of the CPC Central Committee;combining top-level design with encouragement of grassroots innovation;leveraging the distinct characteristics and strengths of FTZs to form a differentiated development pattern;maintaining the integration of opening up with domestic reforms;using openness to drive reforms;and organically combining openness with national security assurance.Under the current and future new circumstances,China’s FTZs face new challenges and tasks.In accordance with the directives of the 20th National Congress of the Communist Party of China,an enhancement strategy for the FTZs needs to be implemented.This involves the following:First,accurately understanding and responding to the changing situation to create strategic opportunities.Second,shifting paradigms to implement innovation-driven strategies,using the new development pattern concept to guide the reform experiments and construction of the FTZs.Third,granting more autonomy to FTZs for reforms,pursuing progress while maintaining stability,and solidly advancing the reform experiments in the FTZs.Fourth,orderly expanding the opening up of the service sector and cautiously advancing the internationalization of the renminbi.Fifth,promoting innovative development in trade to build a strong trade nation.Sixth,establishing synergy with bilateral FTZs,Belt and Road cooperation,and national diplomatic strategies to enhance the linkage effect.

Effects of QD2R Numeracy Enhancement Strategy on the Mathematics Performance of Grade 10 Students

Learning mathematics requires an effective and strategic teaching approach.This study aimed to assess the mathematics performance of the learners with the implementation of the numeracy enhancement strategy QD2R(Questions,Drills,Repetition,and Recitation)and to propose a strategy implementation plan to elevate their performances.This study employed the use of a quasi-experimental research design,purposive sampling with 70 Grade 10 students of Lian National High School who were distributed equally to control and treatment groups.The pre-test and post-test results were statistically analyzed using independent and paired sample t-tests,and a survey questionnaire was examined by getting the mean and standard deviation.The results indicated that better performance was achieved by the students from the treatment group compared to the students from the control group,as revealed by the Mean Percentage Score(MPS)results,mean scores,and P values of their pre-test and post-test scores.The learners’perception of the implementation of this strategy was to a great extent,wherein it was perceived to be more helpful in concepts related to understanding the lesson compared to concepts related to developing their attitude and skills.Moreover,the proposed implementation plan of numeracy enhancement strategy QD2R had three expected outcomes:elevated understanding and performance in mathematics lessons;modified strategy to focus on the development of attitude and skills towards mathematics;and refined and well-implemented QD2R strategy in teaching mathematics.Relative to these expected outcomes,appropriate measures,timeframe,and resources of each were comprehensively formulated.

Does sevoflurane sedation in pediatric patients lead to“pseudo”leptomeningeal enhancement in the brain on 3 Tesla magnetic resonance imaging?

BACKGROUND Prominent leptomeningeal contrast enhancement(LMCE)in the brain is observed in some pediatric patients during sedation for imaging.However,based on clinical history and cerebrospinal fluid analysis,the patients are not acutely ill and do not exhibit meningeal signs.Our study determined whether sevoflurane inhalation in pediatric patients led to this pattern of‘pseudo’LMCE(pLMCE)on 3 Tesla magnetic resonance imaging(MRI).AIM To highlight the significance of pLMCE in pediatric patients undergoing enhanced brain MRI under sedation to avoid misinterpretation in reports.METHODS A retrospective cross-sectional evaluation of pediatric patients between 0-8 years of age was conducted.The patients underwent enhanced brain MRI under inhaled sevoflurane.The LMCE grade was determined by two radiologists,and interobserver variability of the grade was calculated using Cohen’s kappa.The LMCE grade was correlated with duration of sedation,age and weight using the Spearman rho rank correlation.RESULTS A total of 63 patients were included.Fourteen(22.2%)cases showed mild LMCE,48(76.1%)cases showed moderate LMCE,and 1 case(1.6%)showed severe LMCE.We found substantial agreement between the two radiologists in detection of pLMCE on post-contrast T1 imaging(kappa value=0.61;P<0.001).Additionally,we found statistically significant inverse and moderate correlations between patient weight and age.There was no correlation between duration of sedation and pLMCE.CONCLUSION pLMCE is relatively common on post-contrast spin echo T1-weighted MRI of pediatric patients sedated by sevoflurane due to their fragile and immature vasculature.It should not be misinterpreted for meningeal pathology.Knowing pertinent clinical history of the child is an essential prerequisite to avoid radiological overcalling and the subsequent burden of additional investigations.

Mobile Communication Voice Enhancement Under Convolutional Neural Networks and the Internet of Things

This study aims to reduce the interference of ambient noise in mobile communication,improve the accuracy and authenticity of information transmitted by sound,and guarantee the accuracy of voice information deliv-ered by mobile communication.First,the principles and techniques of speech enhancement are analyzed,and a fast lateral recursive least square method(FLRLS method)is adopted to process sound data.Then,the convolutional neural networks(CNNs)-based noise recognition CNN(NR-CNN)algorithm and speech enhancement model are proposed.Finally,related experiments are designed to verify the performance of the proposed algorithm and model.The experimental results show that the noise classification accuracy of the NR-CNN noise recognition algorithm is higher than 99.82%,and the recall rate and F1 value are also higher than 99.92.The proposed sound enhance-ment model can effectively enhance the original sound in the case of noise interference.After the CNN is incorporated,the average value of all noisy sound perception quality evaluation system values is improved by over 21%compared with that of the traditional noise reduction method.The proposed algorithm can adapt to a variety of voice environments and can simultaneously enhance and reduce noise processing on a variety of different types of voice signals,and the processing effect is better than that of traditional sound enhancement models.In addition,the sound distortion index of the proposed speech enhancement model is inferior to that of the control group,indicating that the addition of the CNN neural network is less likely to cause sound signal distortion in various sound environments and shows superior robustness.In summary,the proposed CNN-based speech enhancement model shows significant sound enhancement effects,stable performance,and strong adapt-ability.This study provides a reference and basis for research applying neural networks in speech enhancement.

Improving the Reading Skills of ALS Learners Through Project RICE(Reading Intervention and Comprehension Enhancement)

One of the major problems in the education sector is the reading skills of learners.Students enrolled in the Alternative Learning System(ALS)also experienced this scenario due to several circumstances.This study focused on the improvement of reading comprehension skills of ALS learners by means of project RICE(Reading Intervention and Comprehension Enhancement)as well as the issues and challenges.A quasi-experimental design was utilized in this study which was participated by 54 learners,composed of 27 learners under the experimental group and 27 under the control group.The result revealed that the learners in the experimental group changed from frustration level to instructional level after the implementation of project RICE while the learners in the control group changed from instructional level to inde-pendent level,thereby signifying a significant difference and the effectiveness of the project.Additionally,issues with time and resources were often encountered by the learners.

Finesse measurement for high-power optical enhancement cavity

Finesse is a critical parameter for describing the characteristics of an optical enhancement cavity(OEC). This paper first presents a review of finesse measurement techniques, including a comparative analysis of the advantages, disadvantages, and potential limitations of several main methods from both theoretical and practical perspectives. A variant of the existing method called the free spectral range(FSR) modulation method is proposed and compared with three other finesse measurement methods, i.e., the fast-switching cavity ring-down(CRD) method, the rapidly swept-frequency(SF) CRD method, and the ringing effect method. A high-power OEC platform with a high finesse of approximately 16000 is built and measured with the four methods. The performance of these methods is compared, and the results show that the FSR modulation method and the fast-switching CRD method are more suitable and accurate than the other two methods for high-finesse OEC measurements. The CRD method and the ringing effect method can be implemented in open loop using simple equipment and are easy to perform. Additionally, recommendations for selecting finesse measurement methods under different conditions are proposed, which benefit the development of OEC and its applications.

Optimal decision-making method for equipment maintenance to enhance the resilience of power digital twin system under extreme disaster

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events,causing surveillance and energy loss.This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters.Initially,the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes.Subsequently,it delves into communication and data processing mechanisms,specifically focusing on central data processing(CDP),communication routers(CRs),and phasor measurement units(PMUs),to re-establish an equipment recovery model based on these data transmission methodologies.Furthermore,it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution.The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system.The findings suggest that the proposed branch-and-bound algorithm significantly augments the observational capabilities of a power system with limited resources,thereby bolstering its stability and emergency response mechanisms.

A research on the effect of plasma spectrum collection device on LIBS spectral intensity

Only a small amount of spectral information is collected because the collection solid angle of the optical fiber probe and lens is very limited when collecting spectral information.To overcome this limitation,this study presents a novel method for acquiring plasma spectral information from various spatial directions.A parabolic-shaped plasma spectral collection device(PSCD)is employed to effectively collect more spectral information into the spectrometer,thereby enhancing the overall spectral intensity.The research objects in this study were soil samples containing different concentrations of heavy metals Pb,Cr,and Cd.The results indicate that the PSCD significantly enhances the spectral signal,with an enhancement rate of up to 45%.Moreover,the signal-to-noise ratio also increases by as much as 36%.Simultaneously,when compared to the absence of a device,it is found that there is no significant variation in plasma temperature when the PSCD is utilized.This observation eliminates the impact of the spatial effect caused by the PSCD on the spectral intensity.Consequently,a concentrationspectral intensity relationship curve is established under the PSCD.The results revealed that the linear fitting R^(2)for Pb,Cr,and Cd increased by 0.011,0.001,and 0.054,respectively.Additionally,the limit of detection(LOD)decreased by 0.361 ppm,0.901 ppm,and 0.602 ppm,respectively.These findings indicate that the spectral enhancement rate elevates with the increase in heavy metal concentration.Hence,the PSCD can effectively enhance the spectral intensity and reduce the detection limit of heavy metals in soil.

Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

The act of transmitting photos via the Internet has become a routine and significant activity.Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced.This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images.The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression.This paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during transmission.By employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious actions.Furthermore,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been accomplished.For applications involving the transmission and sharing of images across a network.The suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture transfer.An effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of responsibilities.This scheme ensures a large reduction in computational and energy requirements while minimizing image quality loss.This approach employs multi-scale characteristics to improve the resistance of signatures against image deterioration.The proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

Performance-control-orientated hybrid metal additive manufacturing technologies:state of the art,challenges,and future trends

Metal additive manufacturing(AM)technologies have made significant progress in the basic theoretical field since their invention in the 1970s.However,performance instability during continuous processing,such as thermal history,residual stress accumulation,and columnar grain epitaxial growth,consistently hinders their broad application in standardized industrial production.To overcome these challenges,performance-control-oriented hybrid AM(HAM)technologies have been introduced.These technologies,by leveraging external auxiliary processes,aim to regulate microstructural evolution and mechanical properties during metal AM.This paper provides a systematic and detailed review of performance-control-oriented HAM technology,which is categorized into two main groups:energy field-assisted AM(EFed AM,e.g.ultrasonic,electromagnetic,and heat)technologies and interlayer plastic deformation-assisted AM(IPDed AM,e.g.laser shock peening,rolling,ultrasonic peening,and friction stir process)technologies.This review covers the influence of external energy fields on the melting,flow,and solidification behavior of materials,and the regulatory effects of interlayer plastic deformation on grain refinement,nucleation,and recrystallization.Furthermore,the role of performance-control-oriented HAM technologies in managing residual stress conversion,metallurgical defect closure,mechanical property improvement,and anisotropy regulation is thoroughly reviewed and discussed.The review concludes with an analysis of future development trends in EFed AM and IPDed AM technologies.

Tissue optical clearing enhances efficacy of vascular targeted photodynamic therapy of mouse dorsal skin

Vascular-targeted photodynamic therapy(V-PDT)is an effective treatment for port wine stains(PWS).However,repeated treatment is usually needed to achieve optimal treatment outcomes,possibly due to the limited treatment light penetration depth in the PWS lesion.The optical clearing technique can increase light penetration in depth by reducing light scattering.This study aimed to investigate the V-PDT in combination with an optical clearing agent(OCA)for the therapeutic enhancement of V-PDT in the rodent skinfold window chamber model.Vascular responses were closely monitored with laser speckle contrast imaging(LSCI),optical coherence tomography angiography,and stereo microscope before,during,and after the treatment.We further quantitatively demonstrated the effects of V-PDT in combination with OCA on the blood flow and blood vessel size of skin microvasculature.The combination of OCA and V-PDT resulted in significant vascular damage,including vasoconstriction and the reduction of blood flow.Our results indicate the promising potential of OCA for enhancing V-PDT for treating vascular-related diseases,including PWS.

Topic highlight on texture and color enhancement imaging in gastrointestinal diseases

Olympus Corporation developed texture and color enhancement imaging(TXI)as a novel image-enhancing endoscopic technique.This topic highlights a series of hot-topic articles that investigated the efficacy of TXI for gastrointestinal disease identification in the clinical setting.A randomized controlled trial demonstrated improvements in the colorectal adenoma detection rate(ADR)and the mean number of adenomas per procedure(MAP)of TXI compared with those of white-light imaging(WLI)observation(58.7%vs 42.7%,adjusted relative risk 1.35,95%CI:1.17-1.56;1.36 vs 0.89,adjusted incident risk ratio 1.48,95%CI:1.22-1.80,respectively).A cross-over study also showed that the colorectal MAP and ADR in TXI were higher than those in WLI(1.5 vs 1.0,adjusted odds ratio 1.4,95%CI:1.2-1.6;58.2%vs 46.8%,1.5,1.0-2.3,respectively).A randomized controlled trial demonstrated non-inferiority of TXI to narrow-band imaging in the colorectal mean number of adenomas and sessile serrated lesions per procedure(0.29 vs 0.30,difference for non-inferiority-0.01,95%CI:-0.10 to 0.08).A cohort study found that scoring for ulcerative colitis severity using TXI could predict relapse of ulcerative colitis.A cross-sectional study found that TXI improved the gastric cancer detection rate compared to WLI(0.71%vs 0.29%).A cross-sectional study revealed that the sensitivity and accuracy for active Helicobacter pylori gastritis in TXI were higher than those of WLI(69.2%vs 52.5%and 85.3%vs 78.7%,res-pectively).In conclusion,TXI can improve gastrointestinal lesion detection and qualitative diagnosis.Therefore,further studies on the efficacy of TXI in clinical practice are required.

A Study on Enhancing Chip Detection Efficiency Using the Lightweight Van-YOLOv8 Network

In pursuit of cost-effective manufacturing,enterprises are increasingly adopting the practice of utilizing recycled semiconductor chips.To ensure consistent chip orientation during packaging,a circular marker on the front side is employed for pin alignment following successful functional testing.However,recycled chips often exhibit substantial surface wear,and the identification of the relatively small marker proves challenging.Moreover,the complexity of generic target detection algorithms hampers seamless deployment.Addressing these issues,this paper introduces a lightweight YOLOv8s-based network tailored for detecting markings on recycled chips,termed Van-YOLOv8.Initially,to alleviate the influence of diminutive,low-resolution markings on the precision of deep learning models,we utilize an upscaling approach for enhanced resolution.This technique relies on the Super-Resolution Generative Adversarial Network with Extended Training(SRGANext)network,facilitating the reconstruction of high-fidelity images that align with input specifications.Subsequently,we replace the original YOLOv8smodel’s backbone feature extraction network with the lightweight VanillaNetwork(VanillaNet),simplifying the branch structure to reduce network parameters.Finally,a Hybrid Attention Mechanism(HAM)is implemented to capture essential details from input images,improving feature representation while concurrently expediting model inference speed.Experimental results demonstrate that the Van-YOLOv8 network outperforms the original YOLOv8s on a recycled chip dataset in various aspects.Significantly,it demonstrates superiority in parameter count,computational intricacy,precision in identifying targets,and speed when compared to certain prevalent algorithms in the current landscape.The proposed approach proves promising for real-time detection of recycled chips in practical factory settings.

Physics-Constrained Robustness Enhancement for Tree Ensembles Applied in Smart Grid

With the widespread use of machine learning(ML)technology,the operational efficiency and responsiveness of power grids have been significantly enhanced,allowing smart grids to achieve high levels of automation and intelligence.However,tree ensemble models commonly used in smart grids are vulnerable to adversarial attacks,making it urgent to enhance their robustness.To address this,we propose a robustness enhancement method that incorporates physical constraints into the node-splitting decisions of tree ensembles.Our algorithm improves robustness by developing a dataset of adversarial examples that comply with physical laws,ensuring training data accurately reflects possible attack scenarios while adhering to physical rules.In our experiments,the proposed method increased robustness against adversarial attacks by 100%when applied to real grid data under physical constraints.These results highlight the advantages of our method in maintaining efficient and secure operation of smart grids under adversarial conditions.

Theoretical analysis and engineering application of controllable shock wave technology for enhancing coalbed methane in soft and low‑permeability coal seams

Coalbed methane(CBM)is a significant factor in triggering coal and gas outburst disaster,while also serving as a clean fuel.With the increasing depth of mining operations,coal seams that exhibit high levels of gas content and low permeability have become increasingly prevalent.While controllable shockwave(CSW)technology has proven effective in enhancing CBM in laboratory settings,there is a lack of reports on its field applications in soft and low-permeability coal seams.This study establishes the governing equations for stress waves induced by CSW.Laplace numerical inversion was employed to analyse the dynamic response of the coal seam during CSW antireflection.Additionally,quantitative calculations were performed for the crushed zone,fracture zone,and effective CSW influence range,which guided the selection of field test parameters.The results of the field test unveiled a substantial improvement in the gas permeability coefficient,the average rate of pure methane flowrate,and the mean gas flowrate within a 10 m radius of the antireflection borehole.These enhancements were notable,showing increases of 3 times,13.72 times,and 11.48 times,respectively.Furthermore,the field test performed on the CSW antireflection gas extraction hole cluster demonstrated a noticeable improvement in CBM extraction.After antireflection,the maximum peak gas concentration and maximum peak pure methane flow reached 71.2%and 2.59 m^(3)/min,respectively.These findings will offer valuable guidance for the application of CSW antireflection technology in soft and low-permeability coal seams.

Numerical study of flow and thermal characteristics of pulsed impinging jet on a dimpled surface

This research comprehensively investigates the flow and thermal characteristics of a pulsating impinging jet over a dimpled surface.It analyzes the impact of key parameters(e.g.,inlet velocity pulsation functions,pulsation frequency,amplitude,dimple pitch,dimple depth,Reynolds number)on flow patterns and heat transfer.Validated computational fluid dynamics and the Re-normalization group turbulence model are employed to accurately simulate complex turbulent flow behavior.Local and average heat transfer coefficients are calculated and compared to steady impingement cases,revealing the potential benefits of pulsation for heat transfer enhancement.The study also examines how pulsation-induced flow modulation and thermal mixing affect heat transfer mechanisms.Results indicate that combining fluctuating flow with a dimpled surface can improve heat transfer rates.In summary,increasing pulsation amplitude consistently enhances heat transfer,while the effect of frequency varies between impinging and wall jet zones.

Image enhancement with intensity transformation on embedding space

In recent times,an image enhancement approach,which learns the global transformation function using deep neural networks,has gained attention.However,many existing methods based on this approach have a limitation:their transformation functions are too simple to imitate complex colour transformations between low-quality images and manually retouched high-quality images.In order to address this limitation,a simple yet effective approach for image enhancement is proposed.The proposed algorithm based on the channel-wise intensity transformation is designed.However,this transformation is applied to the learnt embedding space instead of specific colour spaces and then return enhanced features to colours.To this end,the authors define the continuous intensity transformation(CIT)to describe the mapping between input and output intensities on the embedding space.Then,the enhancement network is developed,which produces multi-scale feature maps from input images,derives the set of transformation functions,and performs the CIT to obtain enhanced images.Extensive experiments on the MIT-Adobe 5K dataset demonstrate that the authors’approach improves the performance of conventional intensity transforms on colour space metrics.Specifically,the authors achieved a 3.8%improvement in peak signal-to-noise ratio,a 1.8%improvement in structual similarity index measure,and a 27.5%improvement in learned perceptual image patch similarity.Also,the authors’algorithm outperforms state-of-the-art alternatives on three image enhancement datasets:MIT-Adobe 5K,Low-Light,and Google HDRþ.