In many optical metrology techniques,fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns.Despite extensive research efforts for decades,h...In many optical metrology techniques,fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns.Despite extensive research efforts for decades,how to extract the desired phase information,with the highest possible accuracy,from the minimum number of fringe patterns remains one of the most challenging open problems.Inspired by recent successes of deep learning techniques for computer vision and other applications,we demonstrate for the first time,to our knowledge,that the deep neural networks can be trained to perform fringe analysis,which substantially enhances the accuracy of phase demodulation from a single fringe pattern.The effectiveness of the proposed method is experimentally verified using carrier fringe patterns under the scenario of fringe projection profilometry.Experimental results demonstrate its superior performance,in terms of high accuracy and edge-preserving,over two representative single-frame techniques:Fourier transform profilometry and windowed Fourier transform profilometry.展开更多
With the advances in scientific foundations and technological implementations,optical metrology has become versatile problem-solving backbones in manufacturing,fundamental research,and engineering applications,such as...With the advances in scientific foundations and technological implementations,optical metrology has become versatile problem-solving backbones in manufacturing,fundamental research,and engineering applications,such as quality control,nondestructive testing,experimental mechanics,and biomedicine.In recent years,deep learning,a subfield of machine learning,is emerging as a powerful tool to address problems by learning from data,largely driven by the availability of massive datasets,enhanced computational power,fast data storage,and novel training algorithms for the deep neural network.It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology.Unlike the traditional,,physics-basedH approach,deep-learning-enabled optical metrology is a kind of,/data-drivenw approach,which has already provided numerous alternative solutions to many challenging problems in this field with better performances.In this review,we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology.We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning,followed by a comprehensive review of its applications in various optical metrology tasks,such as fringe denoising,phase retrieval,phase unwrapping,subset correlation,and error compensation.The open challenges faced by the current deep-learning approach in optical metrology are then discussed.Finally,the directions for future research are outlined.展开更多
Studies concerning the pathophysiological connection between obesity and osteoporosis are currently an intriguing area of research.Although the onset of these two diseases can occur in a different way,recent studies h...Studies concerning the pathophysiological connection between obesity and osteoporosis are currently an intriguing area of research.Although the onset of these two diseases can occur in a different way,recent studies have shown that obesity and osteoporosis share common genetic and environmental factors.Despite being a risk factor for health,obesity has traditionally been considered positive to bone because of beneficial effect of mechanical loading,exerted by high body mass,on bone formation.However,contrasting studies have not achieved a clear consensus,suggesting instead that excessive fat mass derived from obesity condition may not protect against osteoporosis or,even worse,could be rather detrimental to bone.On the other hand,it is hitherto better established that,since adipocytes and osteoblasts are derived from a common mesenchymal stem cell precursor,molecules that lead to osteoblastogenesis inhibit adipogenesis and vice versa.Here we will discuss the role of the key molecules regulating adipocytes and osteoblasts differentiation,which are peroxisome proliferators activated receptor-γand Wnts,respectively.In particular,wewill focus on the role of both canonical and non-canonical Wnt signalling,involved in mesenchymal cell fate regulation.Moreover,at present there are no experimental data that relate any influence of the Wnt inhibitor Sclerostin to adipogenesis,although it is well known its role on bone metabolism.In addition,the most common pathological condition in which there is a simultaneous increase of adiposity and decrease of bone mass is menopause.Given that postmenopausal women have high Sclerostin level inversely associated with circulating estradiol level and since the sex hormone replacement therapy has proved to be effective in attenuating bone loss and reversing menopause-related obesity,we hypothesize that Sclerostin contribution in adipogenesis could be an active focus of research in the coming years.展开更多
The cornea has unique features that make it a useful model for regenerative medicine studies. It is an avascular, transparent, densely innervated tissue and any pathological changes can be easily detected by slit lamp...The cornea has unique features that make it a useful model for regenerative medicine studies. It is an avascular, transparent, densely innervated tissue and any pathological changes can be easily detected by slit lamp examination. Corneal sensitivity is provided by the ophthalmic branch of the trigeminal nerve that elicits protective reflexes such as blinking and tearing and exerts trophic support by releasing neuromediators and growth factors. Corneal nerves are easily evaluated for both function and morphology using standard instruments such as corneal esthesiometer and in vivo confocal microscope. All local and systemic conditions that are associated with damage of the trigeminal nerve cause the development of neurotrophic keratitis, a rare degenerative disease. Neurotrophic keratitis is characterized by impairment of corneal sensitivity associated with development of persistent epithelial defects that may progress to corneal ulcer, melting and perforation. Current neurotrophic keratitis treatments aim at supporting corneal healing and preventing progression of corneal damage. Novel compounds able to stimulate corneal nerve recovery are in advanced development stage. Among them, nerve growth factor eye drops showed to be safe and effective in stimulating corneal healing and improving corneal sensitivity in patients with neurotrophic keratitis. Neurotrophic keratitis represents an useful model to evaluate in clinical practice novel neuro-regenerative drugs.展开更多
Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a sing...Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.展开更多
Frailty is a critical intermediate status of the aging process with a multidimensional and multisystem nature and at higher risk for adverse health-related outcomes,including falls,disability,hospitalizations,institut...Frailty is a critical intermediate status of the aging process with a multidimensional and multisystem nature and at higher risk for adverse health-related outcomes,including falls,disability,hospitalizations,institutionalization,mortality,dementia,and Alzheimer’s disease.Among different frailty phenotypes,oral frailty has been recently suggested as a novel construct defined as a decrease in oral function with a coexisting decline in cognitive and physical functions.We briefly reviewed existing evidence on operational definitions of oral frailty,assessment and screening tools,and possible relationships among oral frailty,oral microbiota,and Alzheimer’s disease neurodegeneration.Several underlying mechanism may explain the oral health-frailty links including undernutrition,sarcopenia linked to both poor nutrition and frailty,psychosocial factors,and the chronic inflammation typical of oral disease.Oral microbiota may influence Alzheimer’s disease risk through circulatory or neural access to the brain and the interplay with periodontal disease,often causing tooth loss also linked to an increased Alzheimer’s disease risk.On this bases,COR388,a bacterial protease inhibitor targeting Porphyromonas gingivalis implicated in periodontal disease,is now being tested in a double-blind,placebocontrolled Phase II/III study in mild-to-moderate Alzheimer’s disease.Therefore,oral status may be an important contributor to general health,including Alzheimer’s disease and latelife cognitive disorders,suggesting the central role of preventive strategies targeting the novel oral frailty phenotype and including maintenance and improvement of oral function and nutritional status to reduce the burden of both oral dysfunction and frailty.展开更多
Imaging through scattering media is one of the hotspots in the optical field, and impressive results have been demonstrated via deep learning(DL). However, most of the DL approaches are solely data-driven methods and ...Imaging through scattering media is one of the hotspots in the optical field, and impressive results have been demonstrated via deep learning(DL). However, most of the DL approaches are solely data-driven methods and lack the related physics prior, which results in a limited generalization capability. In this paper, through the effective combination of the speckle-correlation theory and the DL method, we demonstrate a physics-informed learning method in scalable imaging through an unknown thin scattering media, which can achieve high reconstruction fidelity for the sparse objects by training with only one diffuser. The method can solve the inverse problem with more general applicability, which promotes that the objects with different complexity and sparsity can be reconstructed accurately through unknown scattering media, even if the diffusers have different statistical properties. This approach can also extend the field of view(FOV) of traditional speckle-correlation methods. This method gives impetus to the development of scattering imaging in practical scenes and provides an enlightening reference for using DL methods to solve optical problems.展开更多
The crystalline lens is a transparent,biconvex structure in the eye that,along with the cornea,helps to refract light to be focused on the retina and,by changing shape,it adjusts focal distance（accommodation）.The th...The crystalline lens is a transparent,biconvex structure in the eye that,along with the cornea,helps to refract light to be focused on the retina and,by changing shape,it adjusts focal distance（accommodation）.The three classes of structural proteins found in the lens areα,β,and γ crystallins.These proteins make up more than 90% of the total dry mass of the eye lens.Other components which can be found are sugars,lipids,water,several antioxidants and low weight molecules.When ageing changes occur in the lens,it causes a gradual reduction in transparency,presbyopia and an increase in the scattering and aberration of light waves as well as a degradation of the optical quality of the eye.The main changes that occur with aging are： 1） reduced diffusion of water from the outside to the inside of the lens and from its cortical to its nuclear zone; 2）crystalline change due to the accumulation of high molecular weight aggregates and insoluble proteins; 3）production of advanced glycation end products（AGEs）,lipid accumulation,reduction of reduced glutathione content and destruction of ascorbic acid.Even if effective strategies in preventing cataract onset are not already known,good results have been reached in some cases with oral administration of antioxidant substances such as caffeine,pyruvic acid,epigallocatechin gallate（EGCG）,α-lipoic acid and ascorbic acid.Furthermore,methionine sulfoxide reductase A（MSRA） over expression could protect lens cells both in presence and in absence of oxidative stress-induced damage.Nevertheless,promising results have been obtained by reducing ultraviolet-induced oxidative damage.展开更多
Differential phase contrast microscopy(DPC) provides high-resolution quantitative phase distribution of thin transparent samples under multi-axis asymmetric illuminations. Typically, illumination in DPC microscopic sy...Differential phase contrast microscopy(DPC) provides high-resolution quantitative phase distribution of thin transparent samples under multi-axis asymmetric illuminations. Typically, illumination in DPC microscopic systems is designed with two-axis half-circle amplitude patterns, which, however, result in a non-isotropic phase contrast transfer function(PTF). Efforts have been made to achieve isotropic DPC by replacing the conventional half-circle illumination aperture with radially asymmetric patterns with three-axis illumination or gradient amplitude patterns with two-axis illumination. Nevertheless, the underlying theoretical mechanism of isotropic PTF has not been explored, and thus, the optimal illumination scheme cannot be determined. Furthermore, the frequency responses of the PTFs under these engineered illuminations have not been fully optimized, leading to suboptimal phase contrast and signal-to-noise ratio for phase reconstruction. In this paper, we provide a rigorous theoretical analysis about the necessary and sufficient conditions for DPC to achieve isotropic PTF. In addition,we derive the optimal illumination scheme to maximize the frequency response for both low and high frequencies(from 0 to 2 NAobj) and meanwhile achieve perfectly isotropic PTF with only two-axis intensity measurements.We present the derivation, implementation, simulation, and experimental results demonstrating the superiority of our method over existing illumination schemes in both the phase reconstruction accuracy and noise-robustness.展开更多
BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is an emerging liver disease and currently the most common cause of incidental abnormal liver tests.The pathogenesis of NAFLD is multifactorial and many mechanisms th...BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is an emerging liver disease and currently the most common cause of incidental abnormal liver tests.The pathogenesis of NAFLD is multifactorial and many mechanisms that cause fatty liver infiltration,inflammation,oxidative stress and progressive fibrosis have been proposed.Obstructive sleep apnea(OSA)may be linked with the pathogenesis and the severity of NAFLD.AIM To study the association between NAFLD and OSA considering also the efficacy of continuous positive airway pressure(CPAP)treatment.METHODS A Pub Med search was conducted using the terms"non-alcoholic fatty liver disease AND(obstructive sleep apnea OR obstructive sleep disorders OR sleep apnea)".Research was limited to title/abstract of articles published in English in the last 5 years;animal and child studies,case reports,commentaries,letters,editorials and meeting abstracts were not considered.Data were extracted on a standardized data collection table which included:First author,publication year,country,study design,number of patients involved,diagnosis and severity of OSA,diagnosis of NAFLD,patient characteristics,results of the study.RESULTSIn total,132 articles were initially retrieved on Pub Med search and 77 in the last five years.After removal of irrelevant studies,13 articles were included in the qualitative analysis.There was a total of 2753 participants across all the studies with a mean age between 42 and 58 years.The proportion of males ranged from21%to 87.9%and the mean body mass index ranged from 24.0 to 49.9 kg/m2.The results of this review showed an increased prevalence of NAFLD in patients with diagnosis of OSA,even in the absence of coexisting comorbidities such as obesity or metabolic syndrome.Furthermore,the severity of NAFLD is associated with the increase in OSA severity.Effective CPAP treatment,although not always decisive,may stabilize or slow NAFLD progression with benefits on metabolic and cardiovascular functions.CONCLUSION In NAFLD patients,although asymptomatic,it is recom展开更多
We present a new label-free three-dimensional(3D)microscopy technique,termed transport of intensity diffraction tomography with non-interferometric synthetic aperture(TIDT-NSA).Without resorting to interferometric det...We present a new label-free three-dimensional(3D)microscopy technique,termed transport of intensity diffraction tomography with non-interferometric synthetic aperture(TIDT-NSA).Without resorting to interferometric detection,TIDT-NSA retrieves the 3D refractive index(RI)distribution of biological specimens from 3D intensity-only measurements at various illumination angles,allowing incoherent-diffraction-limited quantitative 3D phase-contrast imaging.The unique combination of z-scanning the sample with illumination angle diversity in TIDT-NSA provides strong defocus phase contrast and better optical sectioning capabilities suitable for high-resolution tomography of thick biological samples.Based on an off-the-shelf bright-field microscope with a programmable light-emitting-diode(LED)illumination source,TIDT-NSA achieves an imaging resolution of 206 nm laterally and 520 nm axially with a high-NA oil immersion objective.We validate the 3D RI tomographic imaging performance on various unlabeled fixed and live samples,including human breast cancer cell lines MCF-7,human hepatocyte carcinoma cell lines HepG2,mouse macrophage cell lines RAW 264.7,Caenorhabditis elegans(C.elegans),and live Henrietta Lacks(HeLa)cells.These results establish TIDT-NSA as a new non-interferometric approach to optical diffraction tomography and 3D label-free microscopy,permitting quantitative characterization of cell morphology and time-dependent subcellular changes for widespread biological and medical applications.展开更多
Phase retrieval from fringe images is essential to many optical metrology applications.In the field of fringe projection profilometry,the phase is often obtained with systematic errors if the fringe pattern is not a p...Phase retrieval from fringe images is essential to many optical metrology applications.In the field of fringe projection profilometry,the phase is often obtained with systematic errors if the fringe pattern is not a perfect sinusoid.Several factors can account for non-sinusoidal fringe patterns,such as the non-linear input–output response(e.g.,the gamma effect)of digital projectors,the residual harmonics in binary defocusing projection,and the image saturation due to intense reflection.Traditionally,these problems are handled separately with different well-designed methods,which can be seen as“one-to-one”strategies.Inspired by recent successful artificial intelligence-based optical imaging applications,we propose a“one-to-many”deep learning technique that can analyze non-sinusoidal fringe images resulting from different non-sinusoidal factors and even the coupling of these factors.We show for the first time,to the best of our knowledge,a trained deep neural network can effectively suppress the phase errors due to various kinds of non-sinusoidal patterns.Our work paves the way to robust and powerful learning-based fringe analysis approaches.展开更多
This paper firstly introduces the general situation of cotton planting areas in China and cotton industry in Xinjiang,and the current situation of intellectual property protection of Xinjiang's cotton industry.The...This paper firstly introduces the general situation of cotton planting areas in China and cotton industry in Xinjiang,and the current situation of intellectual property protection of Xinjiang's cotton industry.Then,it analyzes the main problems in its intellectual property protection and high-quality development.On this basis,it comes up with the recommendations for high-quality development of cotton industry in Xinjiang under the strategy of strengthening the country with intellectual property.The recommendations include improving the level of creation of creative intellectual property rights,building an intellectual property rule system in the entire cotton industry chain in Xinjiang,building protected zones for production of major high quality agricultural product cotton,establishing a demonstration zone to undertake the transfer of the domestic cotton textile and garment industry,undertaking education on the sense of community for the Chinese nation in response to the Xinjiang cotton incident,and developing the"Belt and Road"blue market for Xinjiang cotton and its products.展开更多
In 2021,Xinjiang's cotton output was 5.129 million t,accounting for 89.50%of China's total.The autonomous region produces high-quality long-staple cotton,natural colored cotton,fine-staple cotton(upland cotton...In 2021,Xinjiang's cotton output was 5.129 million t,accounting for 89.50%of China's total.The autonomous region produces high-quality long-staple cotton,natural colored cotton,fine-staple cotton(upland cotton),organic cotton,etc.The southern Xinjiang cotton area is one of the three major long-staple cotton(island cotton)producing regions in the world.This paper introduced the history of cotton planting and breeding in Xinjiang from the aspects of cultural relics records,history of entering Xinjiang,historical achievements of breeding and breeding leaders.We studied the intellectual property protection of cotton breeding in the autonomous region from the aspects of biological genetic resources,invention patents,utility model patents and new plant varieties,analyzed the six main problems existing in cotton breeding and its intellectual property protection,and discussed the tactics for cotton breeding and its intellectual property protection in Xinjiang under the strategy of strengthening the country with intellectual property.Eight suggestions in response to the Xinjiang cotton incident were also put forward,including establishing a Xinjiang national cotton germplasm nursery,protecting biological genetic resources,and strengthening the protection of creative intellectual property rights in the field of breeding to escort technological innovation in the cotton seed industry.展开更多
We propose a high-accuracy artifacts-free single-frame digital holographic phase demodulation scheme for relatively lowcarrier frequency holograms-deep learning assisted variational Hilbert quantitative phase imaging(...We propose a high-accuracy artifacts-free single-frame digital holographic phase demodulation scheme for relatively lowcarrier frequency holograms-deep learning assisted variational Hilbert quantitative phase imaging(DL-VHQPI).The method,incorporating a conventional deep neural network into a complete physical model utilizing the idea of residual compensation,reliably and robustly recovers the quantitative phase information of the test objects.It can significantly alleviate spectrum-overlapping-caused phase artifacts under the slightly off-axis digital holographic system.Compared to the conventional end-to-end networks(without a physical model),the proposed method can reduce the dataset size dramatically while maintaining the imaging quality and model generalization.The DL-VHQPI is quantitatively studied by numerical simulation.The live-cell experiment is designed to demonstrate the method's practicality in biological research.The proposed idea of the deep learning-assisted physical model might be extended to diverse computational imaging techniques.展开更多
The impact of apolipoprotein E(ApoE)isoforms on sporadic Alzheimer's disease has long been studied;however,the influences of apolipoprotein E gene(APOE)on healthy and pathological human brains are not fully unders...The impact of apolipoprotein E(ApoE)isoforms on sporadic Alzheimer's disease has long been studied;however,the influences of apolipoprotein E gene(APOE)on healthy and pathological human brains are not fully understood.ApoE exists as three common isoforms(ApoE2,ApoE3,and ApoE4),which differ in two amino acid residues.Traditionally,ApoE binds cholesterol and phospholipids and ApoE isoforms display diffe rent affinities for their receptors,lipids transport and distribution in the brain and periphery.The role of ApoE in the human depends on ApoE isoforms,brain regions,aging,and neural injury.APOE E4 is the strongest genetic risk factor for sporadic Alzheimer's disease,considering its role in influencing amyloid-beta metabolism.The exact mechanisms by which APOE gene variants may increase or decrease Alzheimer's disease risk are not fully understood,but APOE was also known to affect directly and indirectly tau-mediated neurodegeneration,lipids metabolism,neurovascular unit,and microglial function.Consistent with the biological function of ApoE,ApoE4 isoform significantly alte red signaling pathways associated with cholesterol homeostasis,transport,and myelination.Also,the rare protective APOE variants confirm that ApoE plays an important role in Alzheimer's disease pathogenesis.The objectives of the present mini-review were to describe classical and new roles of various ApoE isoforms in Alzheimer's disease pathophysiology beyond the deposition of amyloid-beta and to establish a functional link between APOE,brain function,and memory,from a molecular to a clinical level.APOE genotype also exerted a heterogeneous effect on clinical Alzheimer's disease phenotype and its outcomes.Not only in learning and memory but also in neuro psychiatric symptoms that occur in a premorbid condition.Cla rifying the relationships between Alzheimer's disease-related pathology with neuropsychiatric symptoms,particularly suicidal ideation in Alzheimer's disease patients,may be useful for elucidating also the underlying pathophysiological pro展开更多
AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was...AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.展开更多
This paper introduced the grape industry in Xinjiang and its agricultural intellectual property resources,and analyzed six major problems such as the ineffective leading role of intellectual property rights in high-qu...This paper introduced the grape industry in Xinjiang and its agricultural intellectual property resources,and analyzed six major problems such as the ineffective leading role of intellectual property rights in high-quality development.Finally,it proposed eight strategies to build a national-level regional fine-grain breeding base for grapes and develop“agricultural chips”in the context of the strategy of strengthening the country with intellectual property and innovation-driven development strategy.展开更多
Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives...Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe analysis.However,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice.To this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) module.By parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods.Guided by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks.Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during training.The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.展开更多
Non-line-of-sight(NLOS)imaging is a challenging task aimed at reconstructing objects outside the direct view of the observer.Nevertheless,traditional NLOS imaging methods typically rely on intricate and costly equipme...Non-line-of-sight(NLOS)imaging is a challenging task aimed at reconstructing objects outside the direct view of the observer.Nevertheless,traditional NLOS imaging methods typically rely on intricate and costly equipment to scan and sample the hidden object.These methods often suffer from restricted imaging resolution and require high system stability.Herein,we propose a single-shot high-resolution NLOS imaging method via chromato-axial differential correlography,which adopts low-cost continuous-wave lasers and a conventional camera.By leveraging the uncorrelated laser speckle patterns along the chromato-axis,this method can reconstruct hidden objects of diverse complexity using only one exposure measurement.The achieved background stability through singleshot acquisition,along with the inherent information redundancy in the chromato-axial differential speckles,enhances the robustness of the system against vibration and colored stain interference.This approach overcomes the limitations of conventional methods by simplifying the sampling process,improving system stability,and achieving enhanced imaging resolution using available equipment.This work serves as a valuable reference for the real-time development and practical implementation of NLOS imaging.展开更多
基金This work was financially supported by the National Natural Science Foundation of China(61722506,61705105,and 11574152)the National Key R&D Program of China(2017YFF0106403)+2 种基金the Outstanding Youth Foundation of Jiangsu Province(BK20170034)the China Postdoctoral Science Foundation(2017M621747)the Jiangsu Planned Projects for Postdoctoral Research Funds(1701038A).
文摘In many optical metrology techniques,fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns.Despite extensive research efforts for decades,how to extract the desired phase information,with the highest possible accuracy,from the minimum number of fringe patterns remains one of the most challenging open problems.Inspired by recent successes of deep learning techniques for computer vision and other applications,we demonstrate for the first time,to our knowledge,that the deep neural networks can be trained to perform fringe analysis,which substantially enhances the accuracy of phase demodulation from a single fringe pattern.The effectiveness of the proposed method is experimentally verified using carrier fringe patterns under the scenario of fringe projection profilometry.Experimental results demonstrate its superior performance,in terms of high accuracy and edge-preserving,over two representative single-frame techniques:Fourier transform profilometry and windowed Fourier transform profilometry.
基金National Natural Science Foundation of China(U21B2033,62075096,62005121)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+3 种基金"333 Engineering"Research Projea of Jiangsu Province(BRA2016407)Jiangsu Provincial"One belt and one road"innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Open Research Fund of Jiangsu Key Laboratory of Spearal Imaging&Intelligent Sense(JSGP202105).
文摘With the advances in scientific foundations and technological implementations,optical metrology has become versatile problem-solving backbones in manufacturing,fundamental research,and engineering applications,such as quality control,nondestructive testing,experimental mechanics,and biomedicine.In recent years,deep learning,a subfield of machine learning,is emerging as a powerful tool to address problems by learning from data,largely driven by the availability of massive datasets,enhanced computational power,fast data storage,and novel training algorithms for the deep neural network.It is currently promoting increased interests and gaining extensive attention for its utilization in the field of optical metrology.Unlike the traditional,,physics-basedH approach,deep-learning-enabled optical metrology is a kind of,/data-drivenw approach,which has already provided numerous alternative solutions to many challenging problems in this field with better performances.In this review,we present an overview of the current status and the latest progress of deep-learning technologies in the field of optical metrology.We first briefly introduce both traditional image-processing algorithms in optical metrology and the basic concepts of deep learning,followed by a comprehensive review of its applications in various optical metrology tasks,such as fringe denoising,phase retrieval,phase unwrapping,subset correlation,and error compensation.The open challenges faced by the current deep-learning approach in optical metrology are then discussed.Finally,the directions for future research are outlined.
文摘Studies concerning the pathophysiological connection between obesity and osteoporosis are currently an intriguing area of research.Although the onset of these two diseases can occur in a different way,recent studies have shown that obesity and osteoporosis share common genetic and environmental factors.Despite being a risk factor for health,obesity has traditionally been considered positive to bone because of beneficial effect of mechanical loading,exerted by high body mass,on bone formation.However,contrasting studies have not achieved a clear consensus,suggesting instead that excessive fat mass derived from obesity condition may not protect against osteoporosis or,even worse,could be rather detrimental to bone.On the other hand,it is hitherto better established that,since adipocytes and osteoblasts are derived from a common mesenchymal stem cell precursor,molecules that lead to osteoblastogenesis inhibit adipogenesis and vice versa.Here we will discuss the role of the key molecules regulating adipocytes and osteoblasts differentiation,which are peroxisome proliferators activated receptor-γand Wnts,respectively.In particular,wewill focus on the role of both canonical and non-canonical Wnt signalling,involved in mesenchymal cell fate regulation.Moreover,at present there are no experimental data that relate any influence of the Wnt inhibitor Sclerostin to adipogenesis,although it is well known its role on bone metabolism.In addition,the most common pathological condition in which there is a simultaneous increase of adiposity and decrease of bone mass is menopause.Given that postmenopausal women have high Sclerostin level inversely associated with circulating estradiol level and since the sex hormone replacement therapy has proved to be effective in attenuating bone loss and reversing menopause-related obesity,we hypothesize that Sclerostin contribution in adipogenesis could be an active focus of research in the coming years.
文摘The cornea has unique features that make it a useful model for regenerative medicine studies. It is an avascular, transparent, densely innervated tissue and any pathological changes can be easily detected by slit lamp examination. Corneal sensitivity is provided by the ophthalmic branch of the trigeminal nerve that elicits protective reflexes such as blinking and tearing and exerts trophic support by releasing neuromediators and growth factors. Corneal nerves are easily evaluated for both function and morphology using standard instruments such as corneal esthesiometer and in vivo confocal microscope. All local and systemic conditions that are associated with damage of the trigeminal nerve cause the development of neurotrophic keratitis, a rare degenerative disease. Neurotrophic keratitis is characterized by impairment of corneal sensitivity associated with development of persistent epithelial defects that may progress to corneal ulcer, melting and perforation. Current neurotrophic keratitis treatments aim at supporting corneal healing and preventing progression of corneal damage. Novel compounds able to stimulate corneal nerve recovery are in advanced development stage. Among them, nerve growth factor eye drops showed to be safe and effective in stimulating corneal healing and improving corneal sensitivity in patients with neurotrophic keratitis. Neurotrophic keratitis represents an useful model to evaluate in clinical practice novel neuro-regenerative drugs.
基金This work was supported by National Natural Science Foundation of China(62075096,62005121,U21B2033)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+4 种基金“333 Engineering”Research Project of Jiangsu Province(BRA2016407)Jiangsu Provincial“One belt and one road”innovation cooperation project(BZ2020007)Fundamental Research Funds for the Central Universities(30921011208,30919011222,30920032101)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX21_0273)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105).
文摘Single-shot high-speed 3D imaging is important for reconstructions of dynamic objects.For fringe projection profilometry(FPP),however,it is still challenging to recover accurate 3D shapes of isolated objects by a single fringe image.In this paper,we demonstrate that the deep neural networks can be trained to directly recover the absolute phase from a unique fringe image that involves spatially multiplexed fringe patterns of different frequencies.The extracted phase is free from spectrum-aliasing problem which is hard to avoid for traditional spatial-multiplexing methods.Experiments on both static and dynamic scenes show that the proposed approach is robust to object motion and can obtain high-quality 3D reconstructions of isolated objects within a single fringe image.
文摘Frailty is a critical intermediate status of the aging process with a multidimensional and multisystem nature and at higher risk for adverse health-related outcomes,including falls,disability,hospitalizations,institutionalization,mortality,dementia,and Alzheimer’s disease.Among different frailty phenotypes,oral frailty has been recently suggested as a novel construct defined as a decrease in oral function with a coexisting decline in cognitive and physical functions.We briefly reviewed existing evidence on operational definitions of oral frailty,assessment and screening tools,and possible relationships among oral frailty,oral microbiota,and Alzheimer’s disease neurodegeneration.Several underlying mechanism may explain the oral health-frailty links including undernutrition,sarcopenia linked to both poor nutrition and frailty,psychosocial factors,and the chronic inflammation typical of oral disease.Oral microbiota may influence Alzheimer’s disease risk through circulatory or neural access to the brain and the interplay with periodontal disease,often causing tooth loss also linked to an increased Alzheimer’s disease risk.On this bases,COR388,a bacterial protease inhibitor targeting Porphyromonas gingivalis implicated in periodontal disease,is now being tested in a double-blind,placebocontrolled Phase II/III study in mild-to-moderate Alzheimer’s disease.Therefore,oral status may be an important contributor to general health,including Alzheimer’s disease and latelife cognitive disorders,suggesting the central role of preventive strategies targeting the novel oral frailty phenotype and including maintenance and improvement of oral function and nutritional status to reduce the burden of both oral dysfunction and frailty.
基金National Natural Science Foundation of China(62031018,61971227)Jiangsu Provincial Key Research and Development Program(BE2018126)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX200264)。
文摘Imaging through scattering media is one of the hotspots in the optical field, and impressive results have been demonstrated via deep learning(DL). However, most of the DL approaches are solely data-driven methods and lack the related physics prior, which results in a limited generalization capability. In this paper, through the effective combination of the speckle-correlation theory and the DL method, we demonstrate a physics-informed learning method in scalable imaging through an unknown thin scattering media, which can achieve high reconstruction fidelity for the sparse objects by training with only one diffuser. The method can solve the inverse problem with more general applicability, which promotes that the objects with different complexity and sparsity can be reconstructed accurately through unknown scattering media, even if the diffusers have different statistical properties. This approach can also extend the field of view(FOV) of traditional speckle-correlation methods. This method gives impetus to the development of scattering imaging in practical scenes and provides an enlightening reference for using DL methods to solve optical problems.
文摘The crystalline lens is a transparent,biconvex structure in the eye that,along with the cornea,helps to refract light to be focused on the retina and,by changing shape,it adjusts focal distance（accommodation）.The three classes of structural proteins found in the lens areα,β,and γ crystallins.These proteins make up more than 90% of the total dry mass of the eye lens.Other components which can be found are sugars,lipids,water,several antioxidants and low weight molecules.When ageing changes occur in the lens,it causes a gradual reduction in transparency,presbyopia and an increase in the scattering and aberration of light waves as well as a degradation of the optical quality of the eye.The main changes that occur with aging are： 1） reduced diffusion of water from the outside to the inside of the lens and from its cortical to its nuclear zone; 2）crystalline change due to the accumulation of high molecular weight aggregates and insoluble proteins; 3）production of advanced glycation end products（AGEs）,lipid accumulation,reduction of reduced glutathione content and destruction of ascorbic acid.Even if effective strategies in preventing cataract onset are not already known,good results have been reached in some cases with oral administration of antioxidant substances such as caffeine,pyruvic acid,epigallocatechin gallate（EGCG）,α-lipoic acid and ascorbic acid.Furthermore,methionine sulfoxide reductase A（MSRA） over expression could protect lens cells both in presence and in absence of oxidative stress-induced damage.Nevertheless,promising results have been obtained by reducing ultraviolet-induced oxidative damage.
基金National Natural Science Foundation of China(NSFC)(61722506,11574152)Final Assembly “13th FiveYear Plan” Advanced Research Project of China(30102070102)+6 种基金Equipment Advanced Research Fund of China(61404150202)National Defense Science and Technology Foundation of China(0106173)Outstanding Youth Foundation of Jiangsu Province of China(BK20170034)Key Research and Development Program of Jiangsu Province(BE2017162)“333 Engineering”Research Project of Jiangsu Province(BRA2016407)Fundamental Research Funds for the Central Universities(30917011204)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(3091801410411)
文摘Differential phase contrast microscopy(DPC) provides high-resolution quantitative phase distribution of thin transparent samples under multi-axis asymmetric illuminations. Typically, illumination in DPC microscopic systems is designed with two-axis half-circle amplitude patterns, which, however, result in a non-isotropic phase contrast transfer function(PTF). Efforts have been made to achieve isotropic DPC by replacing the conventional half-circle illumination aperture with radially asymmetric patterns with three-axis illumination or gradient amplitude patterns with two-axis illumination. Nevertheless, the underlying theoretical mechanism of isotropic PTF has not been explored, and thus, the optimal illumination scheme cannot be determined. Furthermore, the frequency responses of the PTFs under these engineered illuminations have not been fully optimized, leading to suboptimal phase contrast and signal-to-noise ratio for phase reconstruction. In this paper, we provide a rigorous theoretical analysis about the necessary and sufficient conditions for DPC to achieve isotropic PTF. In addition,we derive the optimal illumination scheme to maximize the frequency response for both low and high frequencies(from 0 to 2 NAobj) and meanwhile achieve perfectly isotropic PTF with only two-axis intensity measurements.We present the derivation, implementation, simulation, and experimental results demonstrating the superiority of our method over existing illumination schemes in both the phase reconstruction accuracy and noise-robustness.
文摘BACKGROUND Non-alcoholic fatty liver disease(NAFLD)is an emerging liver disease and currently the most common cause of incidental abnormal liver tests.The pathogenesis of NAFLD is multifactorial and many mechanisms that cause fatty liver infiltration,inflammation,oxidative stress and progressive fibrosis have been proposed.Obstructive sleep apnea(OSA)may be linked with the pathogenesis and the severity of NAFLD.AIM To study the association between NAFLD and OSA considering also the efficacy of continuous positive airway pressure(CPAP)treatment.METHODS A Pub Med search was conducted using the terms"non-alcoholic fatty liver disease AND(obstructive sleep apnea OR obstructive sleep disorders OR sleep apnea)".Research was limited to title/abstract of articles published in English in the last 5 years;animal and child studies,case reports,commentaries,letters,editorials and meeting abstracts were not considered.Data were extracted on a standardized data collection table which included:First author,publication year,country,study design,number of patients involved,diagnosis and severity of OSA,diagnosis of NAFLD,patient characteristics,results of the study.RESULTSIn total,132 articles were initially retrieved on Pub Med search and 77 in the last five years.After removal of irrelevant studies,13 articles were included in the qualitative analysis.There was a total of 2753 participants across all the studies with a mean age between 42 and 58 years.The proportion of males ranged from21%to 87.9%and the mean body mass index ranged from 24.0 to 49.9 kg/m2.The results of this review showed an increased prevalence of NAFLD in patients with diagnosis of OSA,even in the absence of coexisting comorbidities such as obesity or metabolic syndrome.Furthermore,the severity of NAFLD is associated with the increase in OSA severity.Effective CPAP treatment,although not always decisive,may stabilize or slow NAFLD progression with benefits on metabolic and cardiovascular functions.CONCLUSION In NAFLD patients,although asymptomatic,it is recom
基金This work was supported by the National Natural Science Foundationof China(61905115,62105151,U21B2033)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+2 种基金Youth Foundationof Jiangsu Province(BK20190445,BK20210338)Fundamental ResearchFundsfortheCentral Universities(30920032101)Open Research Fund of Jjiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(USGP202105).
文摘We present a new label-free three-dimensional(3D)microscopy technique,termed transport of intensity diffraction tomography with non-interferometric synthetic aperture(TIDT-NSA).Without resorting to interferometric detection,TIDT-NSA retrieves the 3D refractive index(RI)distribution of biological specimens from 3D intensity-only measurements at various illumination angles,allowing incoherent-diffraction-limited quantitative 3D phase-contrast imaging.The unique combination of z-scanning the sample with illumination angle diversity in TIDT-NSA provides strong defocus phase contrast and better optical sectioning capabilities suitable for high-resolution tomography of thick biological samples.Based on an off-the-shelf bright-field microscope with a programmable light-emitting-diode(LED)illumination source,TIDT-NSA achieves an imaging resolution of 206 nm laterally and 520 nm axially with a high-NA oil immersion objective.We validate the 3D RI tomographic imaging performance on various unlabeled fixed and live samples,including human breast cancer cell lines MCF-7,human hepatocyte carcinoma cell lines HepG2,mouse macrophage cell lines RAW 264.7,Caenorhabditis elegans(C.elegans),and live Henrietta Lacks(HeLa)cells.These results establish TIDT-NSA as a new non-interferometric approach to optical diffraction tomography and 3D label-free microscopy,permitting quantitative characterization of cell morphology and time-dependent subcellular changes for widespread biological and medical applications.
基金National Natural Science Foundation of China(61722506,62075096)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+7 种基金Jiangsu Provincial“One Belt and One Road”Innovation Cooperation Project(BZ2020007)Final Assembly“13th Five-Year Plan”Advanced Research Project of China(30102070102)Equipment Advanced Research Fund of China(61404150202)Jiangsu Provincial Key Research and Development Program(BE2017162)Outstanding Youth Foundation of Jiangsu Province of China(BK20170034)National Defense Science and Technology Foundation of China(2019-JCJQ-JJ-381)“333 Engineering”Research Project of Jiangsu Province(BRA2016407)Fundamental Research Funds for the Central Universities(30920032101).
文摘Phase retrieval from fringe images is essential to many optical metrology applications.In the field of fringe projection profilometry,the phase is often obtained with systematic errors if the fringe pattern is not a perfect sinusoid.Several factors can account for non-sinusoidal fringe patterns,such as the non-linear input–output response(e.g.,the gamma effect)of digital projectors,the residual harmonics in binary defocusing projection,and the image saturation due to intense reflection.Traditionally,these problems are handled separately with different well-designed methods,which can be seen as“one-to-one”strategies.Inspired by recent successful artificial intelligence-based optical imaging applications,we propose a“one-to-many”deep learning technique that can analyze non-sinusoidal fringe images resulting from different non-sinusoidal factors and even the coupling of these factors.We show for the first time,to the best of our knowledge,a trained deep neural network can effectively suppress the phase errors due to various kinds of non-sinusoidal patterns.Our work paves the way to robust and powerful learning-based fringe analysis approaches.
基金Supported by Foundation for Key Program of Hubei Province (LX201827)
文摘This paper firstly introduces the general situation of cotton planting areas in China and cotton industry in Xinjiang,and the current situation of intellectual property protection of Xinjiang's cotton industry.Then,it analyzes the main problems in its intellectual property protection and high-quality development.On this basis,it comes up with the recommendations for high-quality development of cotton industry in Xinjiang under the strategy of strengthening the country with intellectual property.The recommendations include improving the level of creation of creative intellectual property rights,building an intellectual property rule system in the entire cotton industry chain in Xinjiang,building protected zones for production of major high quality agricultural product cotton,establishing a demonstration zone to undertake the transfer of the domestic cotton textile and garment industry,undertaking education on the sense of community for the Chinese nation in response to the Xinjiang cotton incident,and developing the"Belt and Road"blue market for Xinjiang cotton and its products.
基金Supported by Hubei Provincial Major Research Project(LX201827)。
文摘In 2021,Xinjiang's cotton output was 5.129 million t,accounting for 89.50%of China's total.The autonomous region produces high-quality long-staple cotton,natural colored cotton,fine-staple cotton(upland cotton),organic cotton,etc.The southern Xinjiang cotton area is one of the three major long-staple cotton(island cotton)producing regions in the world.This paper introduced the history of cotton planting and breeding in Xinjiang from the aspects of cultural relics records,history of entering Xinjiang,historical achievements of breeding and breeding leaders.We studied the intellectual property protection of cotton breeding in the autonomous region from the aspects of biological genetic resources,invention patents,utility model patents and new plant varieties,analyzed the six main problems existing in cotton breeding and its intellectual property protection,and discussed the tactics for cotton breeding and its intellectual property protection in Xinjiang under the strategy of strengthening the country with intellectual property.Eight suggestions in response to the Xinjiang cotton incident were also put forward,including establishing a Xinjiang national cotton germplasm nursery,protecting biological genetic resources,and strengthening the protection of creative intellectual property rights in the field of breeding to escort technological innovation in the cotton seed industry.
基金We are grateful for financial supports from the National Natural Science Foundation of China(61905115,62105151,62175109,U21B2033,62227818)Leading Technology of Jiangsu Basic Research Plan(BK20192003)+5 种基金Youth Foundation of Jiangsu Province(BK20190445,BK20210338)Biomedical Competition Foundation of Jiangsu Province(BE2022847)Key National Industrial Technology Cooperation Foundation of Jiangsu Province(BZ2022039)Fundamental Research Funds for the Central Universities(30920032101)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense(JSGP202105,JSGP202201)National Science Center,Poland(2020/37/B/ST7/03629).The authors thank F.Sun for her contribution to this paper in terms of language expression and grammatical correction.
文摘We propose a high-accuracy artifacts-free single-frame digital holographic phase demodulation scheme for relatively lowcarrier frequency holograms-deep learning assisted variational Hilbert quantitative phase imaging(DL-VHQPI).The method,incorporating a conventional deep neural network into a complete physical model utilizing the idea of residual compensation,reliably and robustly recovers the quantitative phase information of the test objects.It can significantly alleviate spectrum-overlapping-caused phase artifacts under the slightly off-axis digital holographic system.Compared to the conventional end-to-end networks(without a physical model),the proposed method can reduce the dataset size dramatically while maintaining the imaging quality and model generalization.The DL-VHQPI is quantitatively studied by numerical simulation.The live-cell experiment is designed to demonstrate the method's practicality in biological research.The proposed idea of the deep learning-assisted physical model might be extended to diverse computational imaging techniques.
文摘The impact of apolipoprotein E(ApoE)isoforms on sporadic Alzheimer's disease has long been studied;however,the influences of apolipoprotein E gene(APOE)on healthy and pathological human brains are not fully understood.ApoE exists as three common isoforms(ApoE2,ApoE3,and ApoE4),which differ in two amino acid residues.Traditionally,ApoE binds cholesterol and phospholipids and ApoE isoforms display diffe rent affinities for their receptors,lipids transport and distribution in the brain and periphery.The role of ApoE in the human depends on ApoE isoforms,brain regions,aging,and neural injury.APOE E4 is the strongest genetic risk factor for sporadic Alzheimer's disease,considering its role in influencing amyloid-beta metabolism.The exact mechanisms by which APOE gene variants may increase or decrease Alzheimer's disease risk are not fully understood,but APOE was also known to affect directly and indirectly tau-mediated neurodegeneration,lipids metabolism,neurovascular unit,and microglial function.Consistent with the biological function of ApoE,ApoE4 isoform significantly alte red signaling pathways associated with cholesterol homeostasis,transport,and myelination.Also,the rare protective APOE variants confirm that ApoE plays an important role in Alzheimer's disease pathogenesis.The objectives of the present mini-review were to describe classical and new roles of various ApoE isoforms in Alzheimer's disease pathophysiology beyond the deposition of amyloid-beta and to establish a functional link between APOE,brain function,and memory,from a molecular to a clinical level.APOE genotype also exerted a heterogeneous effect on clinical Alzheimer's disease phenotype and its outcomes.Not only in learning and memory but also in neuro psychiatric symptoms that occur in a premorbid condition.Cla rifying the relationships between Alzheimer's disease-related pathology with neuropsychiatric symptoms,particularly suicidal ideation in Alzheimer's disease patients,may be useful for elucidating also the underlying pathophysiological pro
文摘AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.
基金Youth Project of National Social Science Fund of China(22CMZ015).
文摘This paper introduced the grape industry in Xinjiang and its agricultural intellectual property resources,and analyzed six major problems such as the ineffective leading role of intellectual property rights in high-quality development.Finally,it proposed eight strategies to build a national-level regional fine-grain breeding base for grapes and develop“agricultural chips”in the context of the strategy of strengthening the country with intellectual property and innovation-driven development strategy.
基金funded by National Key Research and Development Program of China (2022YFB2804603,2022YFB2804604)National Natural Science Foundation of China (62075096,62205147,U21B2033)+7 种基金China Postdoctoral Science Foundation (2023T160318,2022M711630,2022M721619)Jiangsu Funding Program for Excellent Postdoctoral Talent (2022ZB254)The Leading Technology of Jiangsu Basic Research Plan (BK20192003)The“333 Engineering”Research Project of Jiangsu Province (BRA2016407)The Jiangsu Provincial“One belt and one road”innovation cooperation project (BZ2020007)Open Research Fund of Jiangsu Key Laboratory of Spectral Imaging&Intelligent Sense (JSGP202105)Fundamental Research Funds for the Central Universities (30922010405,30921011208,30920032101,30919011222)National Major Scientific Instrument Development Project (62227818).
文摘Recently,deep learning has yielded transformative success across optics and photonics,especially in optical metrology.Deep neural networks (DNNs) with a fully convolutional architecture (e.g.,U-Net and its derivatives) have been widely implemented in an end-to-end manner to accomplish various optical metrology tasks,such as fringe denoising,phase unwrapping,and fringe analysis.However,the task of training a DNN to accurately identify an image-to-image transform from massive input and output data pairs seems at best naive,as the physical laws governing the image formation or other domain expertise pertaining to the measurement have not yet been fully exploited in current deep learning practice.To this end,we introduce a physics-informed deep learning method for fringe pattern analysis (PI-FPA) to overcome this limit by integrating a lightweight DNN with a learning-enhanced Fourier transform profilometry (Le FTP) module.By parameterizing conventional phase retrieval methods,the Le FTP module embeds the prior knowledge in the network structure and the loss function to directly provide reliable phase results for new types of samples,while circumventing the requirement of collecting a large amount of high-quality data in supervised learning methods.Guided by the initial phase from Le FTP,the phase recovery ability of the lightweight DNN is enhanced to further improve the phase accuracy at a low computational cost compared with existing end-to-end networks.Experimental results demonstrate that PI-FPA enables more accurate and computationally efficient single-shot phase retrieval,exhibiting its excellent generalization to various unseen objects during training.The proposed PI-FPA presents that challenging issues in optical metrology can be potentially overcome through the synergy of physics-priors-based traditional tools and data-driven learning approaches,opening new avenues to achieve fast and accurate single-shot 3D imaging.
基金National Natural Science Foundation of China(61971227,62031018,62101255)Jiangsu Provincial Key Research and Development Program(BE2022391)China Postdoctoral Science Foundation(2021M701721,2023T160319)。
文摘Non-line-of-sight(NLOS)imaging is a challenging task aimed at reconstructing objects outside the direct view of the observer.Nevertheless,traditional NLOS imaging methods typically rely on intricate and costly equipment to scan and sample the hidden object.These methods often suffer from restricted imaging resolution and require high system stability.Herein,we propose a single-shot high-resolution NLOS imaging method via chromato-axial differential correlography,which adopts low-cost continuous-wave lasers and a conventional camera.By leveraging the uncorrelated laser speckle patterns along the chromato-axis,this method can reconstruct hidden objects of diverse complexity using only one exposure measurement.The achieved background stability through singleshot acquisition,along with the inherent information redundancy in the chromato-axial differential speckles,enhances the robustness of the system against vibration and colored stain interference.This approach overcomes the limitations of conventional methods by simplifying the sampling process,improving system stability,and achieving enhanced imaging resolution using available equipment.This work serves as a valuable reference for the real-time development and practical implementation of NLOS imaging.
