Malignant glaucoma treated by low-dose laser cycloplasty: a 1-year multicenter prospective noncomparative study

AIM:To report a one-year clinical outcomes of low-dose laser cycloplasty(LCP)among malignant glaucoma patients.METHODS:In this prospective,multicenter,noncomparative clinical study,participants with malignant glaucoma were recruited and underwent LCP at eight ophthalmic centers in China.Patients were followed up at 1wk,1,3,6,and 12mo.Intraocular pressure(IOP),number of glaucoma medications,anterior chamber depth(ACD),and complications were recorded.Anatomical success was defined as the reformation of the anterior chamber based on slit-lamp biomicroscopy.Recurrence was defined by the presence of a shallow orflat anterior chamber after initial recovery from treatment.RESULTS:A total of 34 eyes received LCP.Mean IOP and medications decreased from 36.1±11.5 mm Hg with 3.3±1.5 glaucoma medications pre-treatment to 20.9±9.8 mm Hg(P<0.001)with 2.9±1.6 medications(P=0.046)at 1d,and 17.4±6.7 mm Hg(P<0.001)with 1.3±1.7 medications(P<0.001)at 12mo.The ACD increased from 1.1±0.8 mm at baseline to 1.7±1.0 mm and to 2.0±0.5 mm at 1d and 12mo,respectively.A total of 32(94.1%)eyes achieved initial anatomical success.During follow-up,2(5.9%)eyes failed and 8(23.5%)eyes relapsed,yielding a 12-month anatomical success rate of 64.3%.Complications including anterior synechia(8.82%),choroidal/ciliary detachment(5.88%)and hypopyon(2.94%)were observed within 1wk.CONCLUSION:LCP is simple,safe,and effective in reforming the anterior chamber in malignant glaucoma.

Efficacy and safety of low-dose cyclophosphamide combined with lenvatinib, pembrolizumab and TACE for unresectable hepatocellular carcinoma:A single-center, prospective,single-arm clinical trial

Objective: Unresectable hepatocellular carcinoma(uHCC) continues to pose effective treatment options. The objective of this study was to assess the efficacy and safety of combining low-dose cyclophosphamide with lenvatinib, pembrolizumab and transarterial chemoembolization(TACE) for the treatment of uHCC.Methods: From February 2022 to November 2023, a total of 40 patients diagnosed with uHCC were enrolled in this small-dose, single-center, single-arm, prospective study. They received a combined treatment of low-dose cyclophosphamide with lenvatinib, pembrolizumab, and TACE. Study endpoints included progression-free survival(PFS), objective response rate(ORR), and safety assessment. Tumor response was assessed using the modified Response Evaluation Criteria in Solid Tumors(mRECIST), while survival analysis was conducted through KaplanMeier curve analysis for overall survival(OS) and PFS. Adverse events(AEs) were evaluated according to the National Cancer Institute Common Terminology Criteria for Adverse Events(version 5.0).Results: A total of 34 patients were included in the study. The median follow-up duration was 11.2 [95% confidence interval(95% CI), 5.3-14.6] months, and the median PFS(mPFS) was 15.5(95% CI, 5.4-NA) months.Median OS(mOS) was not attained during the study period. The ORR was 55.9%, and the disease control rate(DCR) was 70.6%. AEs were reported in 27(79.4%) patients. The most frequently reported AEs(with an incidence rate >10%) included abnormal liver function(52.9%), abdominal pain(44.1%), abdominal distension and constipation(29.4%), hypertension(20.6%), leukopenia(17.6%), constipation(17.6%), ascites(14.7%), and insomnia(14.7%). Abnormal liver function(14.7%) had the most common grade 3 or higher AEs.Conclusions: A combination of low-dose cyclophosphamide with lenvatinib, pembrolizumab, and TACE is safe and effective for u HCC, showcasing a promising therapeutic strategy for managing uHCC.

Analysis of the Efficacy of Low-Dose Betaloc Combined with Amiodarone in Treating Ventricular Arrhythmia

Objective:To explore and analyze the clinical effect of low-dose Betaloc combined with amiodarone in treating ventricular arrhythmia.Methods:70 patients with ventricular arrhythmia who were admitted to the Department of Cardiology of our hospital between August 2022 and August 2023 were selected as research subjects.They were divided into two groups using the coin-tossing method:the combination group(n=35)and the reference group(n=35).The combination group was treated with low-dose Betaloc and amiodarone,and the control group was treated with low-dose Betaloc alone.The treatment efficacy,cardiac function indicators,and related tested indicators of the two groups were compared.Results:The total efficacy of the treatment received by the combination group was much higher than that of the control group(P<0.05).Besides,after treatment,the cardiac function indicators such as left ventricular ejection fraction(LVEF),left ventricular end-systolic volume(LVESV),and cardiac index(CI)of the patients in the combination group were significantly better than those of the reference group(P<0.05).Furthermore,the high-sensitivity C-reactive protein(Hs-CRP),N-terminal prohormone of brain natriuretic peptide(NT-proBNP),adiponectin(APN),and other related test indicators of the patients in the combination group were significantly better than those of the reference group(P<0.05).Conclusion:Low-dose Betaloc combined with amiodarone has a noticeable effect in treating ventricular arrhythmia and deserves to be widely promoted.

Hformer:highly efficient vision transformer for low-dose CT denoising

In this paper,we propose Hformer,a novel supervised learning model for low-dose computer tomography(LDCT)denoising.Hformer combines the strengths of convolutional neural networks for local feature extraction and transformer models for global feature capture.The performance of Hformer was verified and evaluated based on the AAPM-Mayo Clinic LDCT Grand Challenge Dataset.Compared with the former representative state-of-the-art(SOTA)model designs under different architectures,Hformer achieved optimal metrics without requiring a large number of learning parameters,with metrics of33.4405 PSNR,8.6956 RMSE,and 0.9163 SSIM.The experiments demonstrated designed Hformer is a SOTA model for noise suppression,structure preservation,and lesion detection.

Successful treatment of patients with refractory idiopathic membranous nephropathy with low-dose Rituximab:A single-center experience

BACKGROUND The recognition of idiopathic membranous nephropathy(IMN)as an autoimmune disease has paved the way for the use of B-cell-depleting agents,such as Rituximab(RTX),which is now a first-line drug for treating IMN with proven safety and efficacy.Nevertheless,the usage of RTX for the treatment of refractory IMN remains controversial and challenging.AIM To evaluate the efficacy and safety of a new low-dose RTX regimen for the treatment of patients with refractory IMN.METHODS A retrospective study was performed on refractory IMN patients that accepted a low-dose RTX regimen(RTX,200 mg,once a month for five months)in the Xiyuan Hospital of Chinese Academy of Chinese Medical Sciences’Department of Nephrology from October 2019 to December 2021.To assess the clinical and immune remission data,we performed a 24 h urinary protein quantification(UTP)test and measured the serum albumin(ALB)and serum creatinine(SCr)levels,phospholipase A2 receptor(PLA2R)antibody titer,and CD19+B-cell count every three months.RESULTS A total of nine refractory IMN patients were analyzed.During follow-up conducted twelve months later,the results from the 24 h UTP decreased from baseline[8.14±6.05 g/d to 1.24±1.34 g/d(P<0.05)]and the ALB levels increased from baseline[28.06±8.42 g/L to 40.93±5.85 g/L(P<0.01)].Notably,after administering RTX for six months,the SCr decreased from 78.13±16.49μmol/L to 109.67±40.87μmol/L(P<0.05).All of the nine patients were positive for serum anti-PLA2R at the beginning,and four patients had normal anti-PLA2R titer levels at six months.The level of CD19+B-cells decreased to 0 at three months,and CD19+B-cell count remained at 0 up until six months of follow-up.CONCLUSION Our low-dose RTX regimen appears to be a promising treatment strategy for refractory IMN.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Experimental study on the effect of unloading rate on gneiss rockburst

Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates

Interactive holography offers unmatched levels of immersion and user engagement in the field of future display.Despite of the substantial progress has been made in dynamic meta-holography,the realization of real-time,highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations.In this study,we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates.To our knowledge,this is the first reported practical dynamic interactive metasurface holographic system.We spa-tially divided the metasurface device into multiple distinct channels,each projecting a reconstructed sub-pattern.The switching states of these channels were mapped to bitwise operations on a set of bit values,which avoids complex holo-gram computations,enabling an ultra-high computational frame rate.Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform.According to this methodology,we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay,color display,and on-the-fly hologram creation.Our technology presents an inspiration for advanced dynamic meta-holography,which is promising for a broad range of applications including advanced human-computer interaction,real-time 3D visualization,and next-generation virtual and augmented reality systems.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

This work aimed to construct an epidemic model with fuzzy parameters.Since the classical epidemic model doesnot elaborate on the successful interaction of susceptible and infective people,the constructed fuzzy epidemicmodel discusses the more detailed versions of the interactions between infective and susceptible people.Thenext-generation matrix approach is employed to find the reproduction number of a deterministic model.Thesensitivity analysis and local stability analysis of the systemare also provided.For solving the fuzzy epidemic model,a numerical scheme is constructed which consists of three time levels.The numerical scheme has an advantage overthe existing forward Euler scheme for determining the conditions of getting the positive solution.The establishedscheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy.The stability of the scheme for the considered fuzzy model is also provided.From the plotted results,it can beobserved that susceptible people decay by rising interaction parameters.

Fluorinated semi-interpenetrating polymer networks for enhancing the mechanical performance and storage stability of polymer-bonded explosives by controlling curing and phase separation rates

Herein, the effect of fluoropolymer binders on the properties of polymer-bonded explosives(PBXs) was comprehensively investigated. To this end, fluorinated semi-interpenetrating polymer networks(semiIPNs) were prepared using different catalyst amounts(denoted as F23-CLF-30-D). The involved curing and phase separation processes were monitored using Fourier-transform infrared spectroscopy, differential scanning calorimetry, a haze meter and a rheometer. Curing rate constant and activation energy were calculated using a theoretical model and numerical method, respectively. Results revealed that owing to its co-continuous micro-phase separation structure, the F23-CLF-30-D3 semi-IPN exhibited considerably higher tensile strength and elongation at break than pure fluororubber F2314 and the F23-CLF-30-D0 semi-IPN because the phase separation and curing rates matched in the initial stage of curing.An arc Brazilian test revealed that F23-CLF-30-D-based composites used as mock materials for PBXs exhibited excellent mechanical performance and storage stability. Thus, the matched curing and phase separation rates play a crucial role during the fabrication of high-performance semi-IPNs;these factors can be feasibly controlled using an appropriate catalyst amount.

INTERFACE BEHAVIOR AND DECAY RATES OF COMPRESSIBLE NAVIER-STOKES SYSTEM WITH DENSITY-DEPENDENT VISCOSITY AND A VACUUM

In this paper,we study the one-dimensional motion of viscous gas near a vacuum,with the gas connecting to a vacuum state with a jump in density.The interface behavior,the pointwise decay rates of the density function and the expanding rates of the interface are obtained with the viscosity coefficientμ(ρ)=ρ^(α)for any 0<α<1;this includes the timeweighted boundedness from below and above.The smoothness of the solution is discussed.Moreover,we construct a class of self-similar classical solutions which exhibit some interesting properties,such as optimal estimates.The present paper extends the results in[Luo T,Xin Z P,Yang T.SIAM J Math Anal,2000,31(6):1175-1191]to the jump boundary conditions case with density-dependent viscosity.

Genetic and Agronomic Parameter Estimates of Growth, Yield and Related Traits of Maize (Zea mays L.) under Different Rates of Nitrogen Fertilization

This study evaluated the genetic and agronomic parameter estimates of maize under different nitrogen rates. The trial was established at the Njala Agricultural Research Centre experimental site during 2021 and 2022 in a split block design with three maize varieties (IWCD2, 2009EVDT, and DMR-ESR-Yellow) and seven nitrogen (0, 30, 60, 90, 120, 150 and 180 kg∙N∙ha−1) rates. Findings showed that cob diameter and anthesis silking time (ASI) had intermediate heritability, ASI had high genetic advance, ASI and grain yield had high genotypic coefficient of variation (GCV), while traits with high phenotypic coefficient of variation (PCV) were plant height, ASI, grain yield, number of kernel per cob, number of kernel rows, ear length, and ear height. The PCV values were higher than GCV, indicating the influence of the environment in the studied traits. Nitrogen rates and variety significantly (p < 0.05) influenced grain yield production. Mean grain yields and economic parameter estimates increased with increasing nitrogen rates, with the 30 and 180 kg∙N∙ha−1 plots exhibiting the lowest and highest grain yields of 1238 kg∙ha−1 and 2098 kg∙ha−1, respectively. Variety and nitrogen effects on partial factor productivity (PFPN), agronomic efficiency (AEN), net returns (NR), value cost ratio (VCR) and marginal return (MR) indicated that these parameters were significantly affected (p < 0.05) by these factors. The highest PFPN (41.3 kg grain kg−1∙N) and AEN (29.4 kg grain kg−1∙N) were obtained in the 30 kg∙N∙ha−1 plots, while the highest VCR (2.8) and MR (SLL 1.8 SLL−1 spent on N) were obtained in the 180 kg∙N∙ha−1. The significant influence of variety and nitrogen on traits suggests that increasing yields and maximizing profits require use of appropriate nitrogen fertilization and improved farming practices that could be exploited for increased productivity of maize.

Present-day Upper-crustal Strain Rate Field in Southeastern Tibet and its Geodynamic Implications:Constraints from GPS Measurements with ABIC Method

The Earth’s surface kinematics and deformation are fundamental to understanding crustal evolution.An effective research approach is to estimate regional motion field and deformation fields based on modern geodetic networks.If the discrete observed velocity field is obtained,the velocity related fields,such as dilatation rate and maximum shear strain rate,can be estimated by applying varied mathematical approaches.This study applied Akaike's Bayesian Information Criterion(ABIC)method to calculate strain rate fields constrained by GPS observations in the southeast Tibetan Plateau.Comparison with results derived from other three methods revealed that our ABIC-derived strain rate fields were more precise.The maximum shear strain rate highlighted the Xianshuihe–Xiaojiang fault system as the main boundary for the outward migration of material in southeastern Tibet,indicating rotation of eastern Tibet material around the eastern Himalaya rather than whole extrusion along a fixed channel.Additionally,distinct dilatation rate patterns in the northeast and southwest regions of the fault system were observed.The northeast region,represented by the Longmenshan area,exhibited negative dilatational anomalies;while the southwest region,represented by the Jinsha River area north of 29°N,displayed positive dilatational anomalies.This indicates compression in the former and extension in the latter.Combined with deep geophysical observations,we believe that the upper and lower crusts of the Jinsha River area north of 29°N are in an entire expanding state,probably caused by the escape-drag effect of material.The presence of a large,low-viscosity region south of 29°N may not enable the entire escape of the crust,but instead result in a differential escape of the lower crust faster than the upper crust.

Intelligent reflecting surface for sum rate enhancement in MIMO systems

The research for the Intelligent Reflecting Surface(IRS)which has the advantages of cost and energy efficiency has been studied.Channel capacity can be effectively increased by appropriately setting the phase value of IRS elements according to the channel conditions.However,the problem of obtaining an appropriate phase value of IRs is difficult to solve due to the non-convex problem.This paper proposes an iterative algorithm for the alternating optimal solution in the Single User Multiple-Input-Multiple-Output(SU-MIMO)systems.The proposed iterative algorithm finds an alternating optimal solution that is the phase value of IRS one by one.The results show that the proposed method has better performance than that of the randomized IRS systems.The number of iterations for maximizing the performance of the proposed algorithm depends on the channel state between the IRS and the receiver.

Cooperative Rate Splitting Transmit Design for Full-Duplex-Enabled Multiple Multicast Communication Systems

This paper examines the performance of Full-Duplex Cooperative Rate Splitting(FD-CRS)with Simultaneous Wireless Information and Power Transfer(SWIPT)support in Multiple Input Single Output(MISO)networks.In a Rate Splitting Multiple Access(RSMA)multicast system with two local users and one remote user,the common data stream contains the needs of all users,and all users can decode the common data stream.Therefore,each user can receive some information that other users need,and local users with better channel conditions can use this information to further enhance the reception reliability and data rate of users with poor channel quality.Even using Cell-Center-Users(CCUs)as a cooperative relay to assist the transmission of common data can improve the average system speed.To maximize the minimum achievable rate,we optimize the beamforming vector of Base Station(BS),the common streamsplitting vector,the cooperative distributed beamvector and the strong user transmission power under the power budget constraints of BS and relay devices and the service quality requirements constraints of users.Since the whole problem is not convex,we cannot solve it directly.Therefore,we propose a low complexity algorithm based on Successive Convex Approximation(SCA)technology to find the optimal solution to the problemunder consideration.The simulation results show that FD C-RSMA has better gain andmore powerful than FD C-NOMA,HD C-RSMA,RSMA and NOMA.

Experimental clearance rate and intraguild predation of jellyfish Cyanea nozakii

Cyanea nozakii,a common jellyfish distributed in offshore China,has a complex trophic relationship with other zooplankton groups.However,few studies have reported the predation rates and prey selection patterns of C.nozakii medusae on different prey items.Research is also lacking on the intraguild predation of Aurelia coerulea(another common bloom jellyfish in offshore China)by C.nozakii.To address the knowledge gaps,the clearance rates of C.nozakii for different prey items,including copepods(small<1000μm and large>1000μm),fish larvae,and gelatinous prey(hydromedusae,A.coerulea ephyrae,and chaetognaths),were measured.The influence of predator size on the clearance rate was also determined.Additionally,we examined the intraguild predation of C.nozakii on A.coerulea medusae.The clearance rates of C.nozakii varied widely with prey organisms,being independent of prey concentrations.Gelatinous organisms,except for chaetognaths,were captured with considerably high efficiency,followed by fish larvae and copepods,indicating the preferential prey selection of gelatinous organisms by C.nozakii.The clearance rate increased linearly with the cross-sectional area of C.nozakii.Body size in medusae may,to some extents,underpin their capacity to capture more prey by increasing the encounter rate and capture success through ontogeny.C.nozakii preyed voraciously on A.coerulea in high feeding efficiency,but the clearance rate decreased with increasing A.coerulea(as prey)size.This phenomenon of intraguild predation suggests a speculative hypothesis of potential population regulation of A.coerulea by C.nozakii.The information regarding the feeding ecology of C.nozakii reported in this study is important for understanding plankton dynamics in marine ecosystems with extensive occurrences of this jellyfish.