MINIMIZERS OF L^(2)-SUBCRITICAL VARIATIONAL PROBLEMS WITH SPATIALLY DECAYING NONLINEARITIES IN BOUNDED DOMAINS

This paper is concerned with the minimizers of L^(2)-subcritical constraint variar tional problems with spatially decaying nonlinearities in a bounded domain Ω of R~N(N≥1).We prove that the problem admits minimizers for any M> 0.Moreover,the limiting behavior of minimizers as M→∞ is also analyzed rigorously.

Aerodynamic Design of Airfoils Based on Variable-Domain Variational Finite Element Method

Designing airfoils according to given pressure (or velocity) distribution is one kind of free boundary problems. Free boundary condition can be coupled with the flow governing equations by variable-domain variational calculus, which makes it possible to calculate simultaneously the flow field and the free boundary. An accurate deduction of the variable-domain variational principles is taken herein to design airfoils in compressible and incompressible flows. Furthermore, two grid types (H and O) are used in the calculation with better results for the O-type grid. It is shown that convergence is accelerated and good results can be obtained even if the initial guessed airfoil shape is a triangle, demonstrating the strong adaptability of this method.

Comment on “The diurnal variation pattern of choroidal thickness in macular region of young healthy female individuals using spectral domain optical coherence tomography”

Dear Editor,We have read and reviewed the article entitled＂The diurnal variation pattern of choroidal thickness in macular region of young healthy female individuals using spectral domain optical coherence tomography＂by Zhao et al^（[1]）with great interest.

Delineating homogeneous domains of fractured rocks using topological manifolds and deep learning

Determining homogeneous domains statistically is helpful for engineering geological modeling and rock mass stability evaluation.In this text,a technique that can integrate lithology,geotechnical and structural information is proposed to delineate homogeneous domains.This technique is then applied to a high and steep slope along a road.First,geological and geotechnical domains were described based on lithology,faults,and shear zones.Next,topological manifolds were used to eliminate the incompatibility between orientations and other parameters(i.e.trace length and roughness)so that the data concerning various properties of each discontinuity can be matched and characterized in the same Euclidean space.Thus,the influence of implicit combined effect in between parameter sequences on the homogeneous domains could be considered.Deep learning technique was employed to quantify abstract features of the characterization images of discontinuity properties,and to assess the similarity of rock mass structures.The results show that the technique can effectively distinguish structural variations and outperform conventional methods.It can handle multisource engineering geological information and multiple discontinuity parameters.This technique can also minimize the interference of human factors and delineate homogeneous domains based on orientations or multi-parameter with arbitrary distributions to satisfy different engineering requirements.

Multi-Modal Domain Adaptation Variational Autoencoder for EEG-Based Emotion Recognition

Traditional electroencephalograph(EEG)-based emotion recognition requires a large number of calibration samples to build a model for a specific subject,which restricts the application of the affective brain computer interface(BCI)in practice.We attempt to use the multi-modal data from the past session to realize emotion recognition in the case of a small amount of calibration samples.To solve this problem,we propose a multimodal domain adaptive variational autoencoder(MMDA-VAE)method,which learns shared cross-domain latent representations of the multi-modal data.Our method builds a multi-modal variational autoencoder(MVAE)to project the data of multiple modalities into a common space.Through adversarial learning and cycle-consistency regularization,our method can reduce the distribution difference of each domain on the shared latent representation layer and realize the transfer of knowledge.Extensive experiments are conducted on two public datasets,SEED and SEED-IV,and the results show the superiority of our proposed method.Our work can effectively improve the performance of emotion recognition with a small amount of labelled multi-modal data.

A Unified Variational Principle of Fluid Mechanics and Application on Solitary Subdomain or Point

-According to basic equations of fluid mechanics, this paper presents a unified variational principle of fluid mechanics (UVPFM) by using the optimization method of weighted residuals (OMWR). The advantages are as follows, the establishment of the functional and the variational principle is easy, it can change various problems of fluid mechanics derived by basic equations into a unified optimization problem, and the solution is the optimum one in some sense. According to the OMWR for the solitary subdomain, this paper uses UVPFM onto any solitary subdomain and gives the solution of the hydrodynamics equation which is suitable only for that solitary subdomain. According to the OMWR for solitary point, this paper uses UVPFM to any solitary point and gives the solution of the hydrodynamics equation (point solution) which is suitable only for that solitary point. As the solution for the solitary subdomain or solitary point is developed independently, the compatibility with other subdomain or other points, does not need to be considered, but all the boundary conditions and the supplementary derived residual equations obtained by running the derivative operations to the differential equation should be taken into account.

The diurnal variation pattern of choroidal thickness in macular region of young healthy female individuals using spectral domain optical coherence tomography

AIM： To investigate the pattern of diurnal variations of choroidal thickness of macular region of healthy individuals. ~ METHODS： A prospective study of 32 healthy female subjects was conducted. Each subject underwent 1） a questionnaire on daily schedule, 2） the Pittsburgh Sleep Quality Index questionnaire （PSQI）, and 3） ocular examinations including an eye dominance test, fundus photography, and sequential optical coherence tomography （OCT） imaging, on two separate days at five fixed 3h time intervals. Choroidal thickness was measured by two masked graders. RESULTS： A significant diurnal variation of choriodal thickness at fovea （P〈0.001）, at 500 μm nasal （P〈0.001）, temporal to fovea （P=0.01） or 1500 μm nasal to fovea （P= 0.001） was observed. The median choroidal thickness peaked at 11：00 at fovea （P=0.01）, at 500μm nasal （P = 0.009） and temporal （P=0.03） to fovea. The median amplitude of foveal choroidal thickness was 20.5 pm （13, 31） and 20.0 μm （12.5, 28.2） for the first and second series of measurements, respectively. The greater amplitude of foveal choroidal thickness was associated with thickner initial foveal choroidal thickness [ 0.05 （0.03, 0.08）, P= 0.01], dominant eye 10.51 （4.02, 14.60）, P=0.04] in the multivariate linear regression. CONCLUSION： Our data show a significant diurnal variation of the choroidal thickness at fovea, at 500 μm nasal and temporal to fovea and 1500 μm nasal to fovea. Thicker initial foveal choroidal thickness and being dominant eye may influence the amplitude of foveal choroidal thickness.

Relationship between variation of HBV preS function domains and clinical consequences of HBV infection

Objective:To investigate the relationship between variation of HBV preS genes and clinical consequencesof HBV infection. Methods: We selected 3 groups (3 in each) of HBV infected individuals including those of acuteinfection with complete recovery, chronic HBV carriers and chronic severe hepatitis B. The preS genes were amplified from serum samples with half nested PCR. The PCR products were cloned into M13 vectors and 10 cloneswere randomly selected for each individual and sequenced with standard methods. A total of 90 clones were sequenced and analyzed by DNA homological comparison. Results: The characteristics of the preS genes were significantly different in HBV-infected individuals with different clinical consequences.①As for acute hepatitis B, thepreS function domains were stable and no changes in epitopes for T and B cells were found. ②For chronic HBVcarriers, the function domains within preS proteins showed potentially changes with epitope drifts of T and B cellsbecause of the high variation of HBV preS genes. ③For chronic severe hepatitis B, there were special changes inthe function domains of B cells. The abnormally high immune response would cause severe liver injury in these individuals. Conclusion: This study provides experimental evidence for researches about the possible association ofvariation of preS1/S2 functional regions with clinical consequences.

Weighted Variational Minimization Model for Wavelet Domain Inpainting with Primal-Dual Method

To preserve the edges and details of the image,a new variational model for wavelet domain inpainting was proposed which contained a non-convex regularizer. The non-convex regularizer can utilize the local information of image and perform better than those usual convex ones. In addition, to solve the non-convex minimization problem,an iterative reweighted method and a primaldual method were designed. The numerical experiments show that the new model not only gets better visual effects but also obtains higher signal to noise ratio than the recent method.

Tomato detection method using domain adaptive learning for dense planting environments

This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.

The low Mach number limit of non-isentropic magnetohydrodynamic equations with large temperature variations in bounded domains

This paper verifies the low Mach number limit of the non-isentropic compressible magnetohydrodynamic(MHD)equations with or without the magnetic diffusion in a three-dimensional bounded domain when the temperature variation is large but finite.The uniform estimates of strong solutions are established in a short time interval independent of the Mach number,provided that the slip boundary condition for the velocity and the Neumann boundary condition for the temperature are imposed and the initial data is well-prepared.

A new two-step variational model for multiplicative noise removal with applications to texture images

Multiplicative noise removal problems have attracted much attention in recent years.Unlike additive noise,multiplicative noise destroys almost all information of the original image,especially for texture images.Motivated by the TV-Stokes model,we propose a new two-step variational model to denoise the texture images corrupted by multiplicative noise with a good geometry explanation in this paper.In the first step,we convert the multiplicative denoising problem into an additive one by the logarithm transform and propagate the isophote directions in the tangential field smoothing.Once the isophote directions are constructed,an image is restored to fit the constructed directions in the second step.The existence and uniqueness of the solution to the variational problems are proved.In these two steps,we use the gradient descent method and construct finite difference schemes to solve the problems.Especially,the augmented Lagrangian method and the fast Fourier transform are adopted to accelerate the calculation.Experimental results show that the proposed model can remove the multiplicative noise efficiently and protect the texture well.

Targeting neuronal PAS domain protein 2 and KN motif/ankyrin repeat domains 1:Advances in type 2 diabetes therapy

This editorial summarizes the latest literature on the roles of neuronal PAS domain protein 2 and KN motif/ankyrin repeat domain 1 in type 2 diabetes(T2D).We highlight their involvement inβ-cell dysfunction,explore their potential as therapeutic targets,and discuss the implications for new treatment strategies.We offer valuable insights into relevant gene regulation and cellular mechanisms relevant for the targeted management of T2D.

Research on Rotating Machinery Fault Diagnosis Based on Improved Multi-target Domain Adversarial Network

Aiming at the problems of low efficiency,poor anti-noise and robustness of transfer learning model in intelligent fault diagnosis of rotating machinery,a new method of intelligent fault diagnosis of rotating machinery based on single source and multi-target domain adversarial network model(WDMACN)and Gram Angle Product field(GAPF)was proposed.Firstly,the original one-dimensional vibration signal is preprocessed using GAPF to generate the image data including all time series.Secondly,the residual network is used to extract data features,and the features of the target domain without labels are pseudo-labeled,and the transferable features among the feature extractors are shared through the depth parameter,and the feature extractors of the multi-target domain are updated anatomically to generate the features that the discriminator cannot distinguish.The modelt through adversarial domain adaptation,thus achieving fault classification.Finally,a large number of validations were carried out on the bearing data set of Case Western Reserve University(CWRU)and the gear data.The results show that the proposed method can greatly improve the diagnostic efficiency of the model,and has good noise resistance and generalization.

Estimation-free spatial-domain image reconstruction of structured illumination microscopy

Structured illumination microscopy(SIM)achieves super-resolution(SR)by modulating the high-frequency information of the sample into the passband of the optical system and subsequent image reconstruction.The traditional Wiener-filtering-based reconstruction algorithm operates in the Fourier domain,it requires prior knowledge of the sinusoidal illumination patterns which makes the time-consuming procedure of parameter estimation to raw datasets necessary,besides,the parameter estimation is sensitive to noise or aberration-induced pattern distortion which leads to reconstruction artifacts.Here,we propose a spatial-domain image reconstruction method that does not require parameter estimation but calculates patterns from raw datasets,and a reconstructed image can be obtained just by calculating the spatial covariance of differential calculated patterns and differential filtered datasets(the notch filtering operation is performed to the raw datasets for attenuating and compensating the optical transfer function(OTF)).Experiments on reconstructing raw datasets including nonbiological,biological,and simulated samples demonstrate that our method has SR capability,high reconstruction speed,and high robustness to aberration and noise.

Origin of the presence/absence variation of the LTIA1/LTIA2 mini-ribonucleaseⅢgenes required for low-temperature growth in rice

A rice low temperature-induced albino variant was determined by the recessive ltia1 and ltia2 genes.LTIA1 and LTIA2 encode highly conserved mini-ribonucleasesⅢlocated in chloroplasts and expressed in aerial parts of the plant.At low temperature,LTIA1 and LTIA2 redundantly affect chlorophyll levels,non-photochemical quenching,photosynthetic quantum yield of PSⅡand seedling growth.LTIA1 and LTIA2 proteins are involved in splicing of atp F and the biogenesis of 16S and 23S rRNA in chloroplasts.Presence/absence variation of LTIA1,the ancestral copy,was found only in japonica but that of LTIA2 in all rice subgroups.Accessions with LTIA2 presence tended to be distributed more remote from the equator compared to those with LTIA2 absence.LTIA2 duplicated from LTIA1 at the early stage of divergence of the AA genome Oryza species but deleted againin O.nivara.In cultivated rice,absence of LTIA2 is derived from O.nivara.LTIA1 absence occurred more recently in japonica.

Slope displacement prediction based on multisource domain transfer learning for insufficient sample data

Accurate displacement prediction is critical for the early warning of landslides.The complexity of the coupling relationship between multiple influencing factors and displacement makes the accurate prediction of displacement difficult.Moreover,in engineering practice,insufficient monitoring data limit the performance of prediction models.To alleviate this problem,a displacement prediction method based on multisource domain transfer learning,which helps accurately predict data in the target domain through the knowledge of one or more source domains,is proposed.First,an optimized variational mode decomposition model based on the minimum sample entropy is used to decompose the cumulative displacement into the trend,periodic,and stochastic components.The trend component is predicted by an autoregressive model,and the periodic component is predicted by the long short-term memory.For the stochastic component,because it is affected by uncertainties,it is predicted by a combination of a Wasserstein generative adversarial network and multisource domain transfer learning for improved prediction accuracy.Considering a real mine slope as a case study,the proposed prediction method was validated.Therefore,this study provides new insights that can be applied to scenarios lacking sample data.

A Study to Observe Pulse Pressure Variation after Induction with Propofol for General Anesthesia

Background and Aims: Pulse pressure variation (PPV) is a reliable and predictive dynamic parameter presently being utilized for fluid responsiveness. In the operating room, fluid administration based on PPV monitoring helps the physician in deciding whether to volume resuscitate or use interventions in patients undergoing surgery. Propofol is an intravenous induction agent which lowers blood pressure. There are multiple causes such as depression in cardiac output, and peripheral vasodilatation for hypotension. We undertook this study to observe the utility of PPV as a guide to fluid therapy after propofol induction. Primary outcome of our study was to monitor PPV as a marker of fluid responsiveness for the hypotension caused by propofol induction. Secondary outcome included the correlation of PPV with other hemodynamic parameters like heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP);after induction with propofol at regular interval of time. Methods: A total number of 90 patients were recruited. Either of the radial artery was then cannulated under local anaesthesia with 20G VygonLeadercath arterial cannula and invasive monitoring transduced. A baseline recording of heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP) and PPV was then recorded. Patients were then induced with predetermined doses of propofol (2 mg/kg) and recordings of HR, SBP, DBP, and PPV were taken at 5, 10 and 15 minutes. Results: Intraoperatively, PPV was significantly higher at 5 minutes and significantly lower at 15 minutes after induction. It was observed that there were no statistically significant correlations between PPV and SBP or DBP. PPV was strongly and directly associated with HR. Conclusion: We were able to establish that PPV predicts fluid responsiveness in hypotension caused by propofol induction;and can be used to administer fluid therapy in managing such hypotension. However, PPV was not directly correlated with hypotension subsequent to propofol administration.

Consistency between domain wall oscillation modes and spin wave modes in nanostrips

Investigations on domain wall(DW) and spin wave(SW) modes in a series of nanostrips with different widths and thicknesses have been carried out using micromagnetic simulation. The simulation results show that the frequencies of SW modes and the corresponding DW modes are consistent with each other if they have the same node number along the width direction. This consistency is more pronounced in wide and thin nanostrips, favoring the DW motion driven by SWs.Further analysis of the moving behavior of a DW driven by SWs is also carried out. The average DW speed can reach a larger value of ~ 140 m/s under two different SW sources. We argue that this study is very meaningful for the potential application of DW motion driven by SWs.

Small temporal variation in abundance of virioplankton compared to bacterioplankton and phytoplankton in two bays in the northern South China Sea

Variations of picoplankton groups were investigated over a one-month period in Daya Bay and Sanya Bay,in the northern South China Sea.The two coastal regions exhibited different variation patterns in physicochemical parameters.Moreover,the diel variations of picoplankton groups were different between the two bays.The abundance of the picoplankton in Sanya Bay displayed a pronounced diel variation,while it was not significant in Daya Bay.In addition,some similar patterns of picoplankton abundance were discovered.In the two bays,virioplankton exhibited the smallest fluctuation range,whereas picocyanobacteria fluctuated most markedly.The fluctuation range of picoplankton groups was larger in spring tide than in neap tide,especially in Sanya Bay.Random forest model analysis demonstrated that the variation of picoplankton groups was attributed to physical and chemical factors in Sanya Bay and Daya Bay,respectively.Therefore,our findings suggest that virioplankton abundance can persist more stably in response to changing environmental conditions compared to bacterioplankton and picophytoplankton.