Single Image Enhancement in Sandstorm Weather via Tensor Least Square

In this paper,we present a tensor least square based model for sand/sandstorm removal in images.The main contributions of this paper are as follows.First,an important intrinsic natural feature of outdoor scenes free of sand/sandstorm is found that the outlines in RGB channels are somewise similar,which discloses the physical validation using the tensor instead of the matrix.Second,a tensor least square optimization model is presented for the decomposition of edge-preserving base layers and details.This model not only decomposes the color image(taken as an inseparable indivisibility)in X,Y directions,but also in Z direction,which meets the statistical feature of natural scenes and can physically disclose the intrinsic color information.The model’s advantages are twofold:one is the decomposition of edgepreserving base layers and details that can be employed for contrast enhancement without artificial halos,and the other one is the color driving ability that makes the enhanced images as close to natural images as possible via the inherent color structure.Thirdly,the tensor least square optimization model based image enhancement scheme is discussed for the sandstorm weather images.Finally,the experiments and comparisons with the stateof-the-art methods on real degraded images under sandstorm weather are shown to verify our method’s efficiency.

LIC color texture enhancement algorithm for ocean vector field data based on HSV color mapping and cumulative distribution function

Texture-based visualization method is a common method in the visualization of vector field data.Aiming at adding color mapping to the texture of ocean vector field and solving the ambiguity of vector direction in texture image,a new color texture enhancement algorithm based on the Line Integral Convolution(LIC)for the vector field data is proposed,which combines the HSV color mapping and cumulative distribution function calculation of vector field data.This algorithm can be summarized as follows:firstly,the vector field data is convoluted twice by line integration to get the gray texture image.Secondly,the method of mapping vector data to each component of the HSV color space is established.And then,the vector field data is mapped into HSV color space and converted from HSV to RGB values to get the color image.Thirdly,the cumulative distribution function of the RGB color components of the gray texture image and the color image is constructed to enhance the gray texture and RGB color values.Finally,both the gray texture image and the color image are fused to get the color texture.The experimental results show that the proposed LIC color texture enhancement algorithm is capable of generating a better display of vector field data.Furthermore,the ambiguity of vector direction in the texture images is solved and the direction information of the vector field is expressed more accurately.

Generalized Uncertainty Inequalities on Fisher Information Associated with LCT

Uncertainty principle plays an important role in multiple fields such as physics,mathem-atics,signal processing,etc.The linear canonical transform(LCT)has been used widely in optics and information processing and so on.In this paper,a few novel uncertainty inequalities on Fisher information associated with linear canonical transform are deduced.These newly deduced uncer-tainty relations not only introduce new physical interpretation in signal processing,but also build the relations between the uncertainty lower bounds and the LCT transform parameters a,b,c and d for the first time,which give us the new ideas for the analysis and potential applications.In addi-tion,these new uncertainty inequalities have sharper and tighter bounds which are the generalized versions of the traditional counterparts.Furthermore,some numeric examples are given to demon-strate the efficiency of these newly deduced uncertainty inequalities.

Amplitude and Phase Analysis Based on Signed Demodulation for AM-FM Signal

This paper proposes a new amplitude and phase demodulation scheme different from the traditional method for AM-FM signals. The traditional amplitude demodulation assumes that the amplitude should be non-negative, and the phase is obtained under the case of non-negative amplitude, which approximates the true amplitude and phase but distorts the true amplitude and phase in some cases. In this paper we assume that the amplitude is signed (zero, positive or negative), and the phase is obtained under the case of signed amplitude by optimization, as is called signed demodulation. The main merit of the signed demodulation lies in the revelation of senseful physi- cal meaning on phase and frequency. Experiments on the real-world data show the efficiency of the method.

Time-Varying Bandpass Filter Based on Assisted Signals for AM-FM Signal Separation: A Revisit

In this paper, a new signal separation method mainly for AM-FM components blended in noises is revisited based on the new derived time-varying bandpass filter (TVBF), which can separate the AM-FM components whose frequencies have overlapped regions in Fourier transform domain and even have crossed points in time-frequency distribution (TFD) so that the proposed TVBF seems like a “soft-cutter” that cuts the frequency domain to snaky slices with rational physical sense. First, the Hilbert transform based decomposition is analyzed for the analysis of nonstationary signals. Based on the above analysis, a hypothesis under a certain condition that AM-FM components can be separated successfully based on Hilbert transform and the assisted signal is developed, which is supported by representative experiments and theoretical performance analyses on a error bound that is shown to be proportional to the product of frequency width and noise variance. The assisted signals are derived from the refined time-frequency distributions via image fusion and least squares optimization. Experiments on man-made and real-life data verify the efficiency of the proposed method and demonstrate the advantages over the other main methods.

Discrete Entropic Uncertainty Relations Associated with FRFT

Based on the definition and properties of discrete fractional Fourier transform (DFRFT), we introduced the discrete Hausdorff-Young inequality. Furthermore, the discrete Shannon entropic uncertainty relation and discrete Rényi entropic uncertainty relation were explored. Also, the condition of equality via Lagrange optimization was developed, as shows that if the two conjugate variables have constant amplitudes that are the inverse of the square root of numbers of non-zero elements, then the uncertainty relations reach their lowest bounds. In addition, the resolution analysis via the uncertainty is discussed as well.

Discrete Inequalities on LCT

Linear canonical transform (LCT) is widely used in physical optics, mathematics and information processing. This paper investigates the generalized uncertainty principles, which plays an important role in physics, of LCT for concentrated data in limited supports. The discrete generalized uncertainty relation, whose bounds are related to LCT parameters and data lengths, is derived in theory. The uncertainty principle discloses that the data in LCT domains may have much higher concentration than that in traditional domains.

单孔腹腔镜手术治疗Currarino综合征

目的总结单孔腹腔镜手术治疗Currarino综合征的经验及技巧。方法回顾性分析2018年1月至2023年10月广州医科大学附属妇女儿童医疗中心胃肠外科行单孔腹腔镜手术治疗的5例Currarino综合征(均为男性,年龄1~4岁)患儿的临床资料,评价其手术效果,总结手术经验。结果5例患儿均一期完成单孔腹腔镜下骶前肿物切除、结肠拖出吻合术,术中在单孔腹腔镜辅助下完成远端扩张结直肠游离后,经肛门拖出切除,断端封闭送回腹腔,再实施单孔腹腔镜下骶前肿物切除,最后完成结肠直肠吻合。5例均一期完成手术,无需经后矢状入路操作,无需行肠造瘘术,无中转开放或需增加trocar病例。平均手术时间240 min,术后住院时间中位数为9(7~11)d,术后均恢复良好,骶前肿物病理结果3例为成熟性畸胎瘤、1例为皮样囊肿,1例为脂肪瘤。随访6~48个月,无出血、尿潴留、肠梗阻、吻合口漏、伤口愈合不良、便秘复发、肿物复发等并发症,排便次数1~3次/d,1例术后出现轻度污粪1~2次/周,术后腹部均无可视性瘢痕。结论单孔腹腔镜手术治疗Currarino综合征具有直视下操作、创伤小、切口美观、避免后矢状入路等优点,术后短期效果满意。

Microwave triggered multifunctional nanoplatform for targeted photothermal-chemotherapy in castration-resistant prostate cancer

Lacking a precise targeting strategy,castration-resistant prostate cancer(CRPC)is still hard to be treat effectively.Exploring treatment options that can accurately target CPRC is an important issue with urgent need.In this study,a novel nanotechnologybased strategy had been developed for the precise target treatment of CRPC.By combining microwaves and photothermal therapy(PTT),this nanoplatform,cmHSP70-PL-AuNC-DOX,targets tumor tissues with outstanding precision and achieves better anti-tumor activity by simultaneously eliciting photothermal and chemotherapeutic effects.From nanotechnology,cmHSP70-modified and thermo-sensitive liposome-coated AuNC-DOX were prepared and used for CRPC-targeted photothermal ablation and chemotherapy.Doxorubicin(DOX)was selected as the chemotherapeutic agent for cytotoxicity.In terms of the curative scheme,prostate tissues were firstly pre-treated with microwaves to induce the expression of heat shock protein 70(HSP70)and its migration to the cell membrane,which was then targeted by HSP70 antibody(cmHSP70)coated on the nanoparticles to achieve accurate drug delivery.The nanoplatform then achieved precise ablation and controlled release of DOX under external near-infrared(NIR)irradiation.Through the implementation,the targeting,cell killing,and safety of this therapeutical strategy had been verified in vivo and in vitro.This work establishes an accurate,controllable,efficient,non-invasive,and safe treatment platform for targeting CRPC,provides a rational design for CRPC’s PTT,and offers new prospects for nanomedicines with great precision.

Wind resistance aerial path planning for efficient reconstruction of offshore ship

When the unmanned aerial vehicle(UAV)is applied to three-dimensional(3D)reconstruction of the offshore ship,it faces two problems:the battery capacity limitation of the UAV and the disturbance of the wind in the environment.Wind disturbance is generally not considered in the path planning process of the existing UAV 3D reconstruction path planning research.Therefore,the planned path is only suitable for no-wind or light-wind scenarios.For the 3D reconstruction of ship targets,we propose a UAV path planning method that can satisfy both reconstruction efficiency and wind disturbance resistance requirements.Firstly,the concept of model surface complexity is proposed to generate a more efficient candidate view set.Secondly,the Min–Max strategy and a new viewpoint construction method are used to generate the initial path.Thirdly,combined with the wind field model,a method for generating a stable path against wind disturbance based on the idea of interval optimization is proposed.Experimental results demonstrate that our method can adaptively determine the number of sample points and viewpoints according to ship’s geometric characteristics and further reduce the number of viewpoints without significantly affecting the reconstruction quality;the path planned by our method is also stable against wind disturbance.

Fucoidan sulfate from Sargassum fusiforme regulates the SARS-CoV-2 receptor AXL expression in human embryonic lung diploid fibroblast cells

Coronavirus disease 2019(COVID-19)is a global infectious disease that seriously endangers human life and health and affects normal social activities.Since the pandemic outbreak from December 2019 to February 2023,the total number of confirmed cases has exceeded 753 million,and the deaths caused by COVID-19 have reached 6.6 million(https://covid19.who.int;accessed on Feb.16,2023).

Time-Series Field Phenotyping of Soybean Growth Analysis by Combining Multimodal Deep Learning and Dynamic Modeling

The rate of soybean canopy establishment largely determines photoperiodic sensitivity,subsequently influencing yield potential.However,assessing the rate of soybean canopy development in large-scale field breeding trials is both laborious and time-consuming.High-throughput phenotyping methods based on unmanned aerial vehicle(UAV)systems can be used to monitor and quantitatively describe the development of soybean canopies for different genotypes.In this study,high-resolution and time-series raw data from field soybean populations were collected using UAVs.

DEKR-SPrior:An Efficient Bottom-Up Keypoint Detection Model for Accurate Pod Phenotyping in Soybean

The pod and seed counts are important yield-related traits in soybean.High-precision soybean breeders face the major challenge of accurately phenotyping the number of pods and seeds in a high-throughput manner.Recent advances in artificial intelligence,especially deep learning(DL)models,have provided new avenues for high-throughput phenotyping of crop traits with increased precision.However,the available DL models are less effective for phenotyping pods that are densely packed and overlap in insitu soybean plants;thus,accurate phenotyping of the number of pods and seeds in soybean plant is an important challenge.To address this challenge,the present study proposed a bottom-up model,DEKR-SPrior(disentangled keypoint regression with structural prior),for insitu soybean pod phenotyping,which considers soybean pods and seeds analogous to human people and joints,respectively.In particular,we designed a novel structural prior(SPrior)module that utilizes cosine similarity to improve feature discrimination,which is important for differentiating closely located seeds from highly similar seeds.To further enhance the accuracy of pod location,we cropped full-sized images into smaller and high-resolution subimages for analysis.The results on our image datasets revealed that DEKR-SPrior outperformed multiple bottom-up models,viz.,Lightweight-Open Pose,OpenPose,HigherH R Net,and DEKR,reducing the mean absolute error from 25.81(in the original DEKR)to 21.11(in the DEKR-SPrior)in pod phenotyping.This paper demonstrated the great potential of DEKR-SPrior for plant phenotyping,and we hope that DEKR-SPrior will help future plant phenotyping.

达芬奇机器人辅助Swenson-like巨结肠根治术

目的探讨达芬奇机器人辅助Swenson-like巨结肠根治术治疗8个月以内婴儿先天性常见型巨结肠的安全性、可行性、治疗效果和并发症。方法以广州医科大学附属妇女儿童医疗中心胃肠外科40例先天性常见型巨结肠患儿为研究对象,由同一外科医师实施手术,术式为三臂法机器人辅助Swenson-like巨结肠根治术。回顾性收集患儿术前、术中和术后临床资料进行分析,术后随访10~18个月。结果40例(男30例,女10例)先天性病患儿巨结肠(Hirschsprung disease,HSCR),平均手术月龄6±2个月,全部顺利完成手术,均无需中转开放及增加辅助孔,平均手术时间为152±17 min,其中机器人手术操作时间43±16 min,肛门部直肠分离时间6±2 min,术中出血量为2±1 ml,平均切除肠管长度25±7 cm,肠功能恢复时间为8±2 h,住院时间为6±1 d,术后疼痛评分为2±1分;40例术后6例(15%)需行肛门扩张;全部患儿均痊愈出院,围术期内均无手术并发症发生,术后主要并发症为肛周皮炎(7.5%)和小肠结肠炎(7.5%)。结论达芬奇机器人辅助Swenson-like巨结肠根治术适用于婴儿期先天性常见型巨结肠的治疗,近期效果良好。