Localized-domains staging structure and evolution in lithiated graphite

Intercalation provides to the host materials a means for controlled variation of many physical/chemical properties and dominates the reactions in metal‐ion batteries.Of particular interest is the graphite intercalation compounds with intriguing staging structures,which however are still unclear,especially in their nanostructure and dynamic transition mechanism.Herein,the nature of the staging structure and evolution of the lithium(Li)‐intercalated graphite was revealed by cryogenic‐transmission electron microscopy and other methods at the nanoscale.The intercalated Li‐ions distribute unevenly,generating local stress and dislocations in the graphitic structure.Each staging compound is found macroscopically ordered but microscopically inhomogeneous,exhibiting a localized‐domains structural model.Our findings uncover the correlation between the long‐range ordered structure and short‐range domains,refresh the insights on the staging structure and transition of Li‐intercalated/deintercalated graphite,and provide effective ways to enhance the reaction kinetic in rechargeable batteries by defect engineering.

Chronic hypotony management using endoscopy-assisted vitrectomy after severe ocular trauma or vitrectomy

·AIM: To report outcomes of endoscopy-assisted vitrectomy(EAV) in patients with chronic hypotony following severe ocular trauma or vitrectomy.·METHODS: This was a retrospective, noncomparative case series. Ciliary bodies were evaluated using ultrasound biomicroscopy pre-operatively and direct visualisation intraoperatively. All selected individuals(seven patients/seven eyes) underwent EAV. Removal of ciliary membrane and traction, gas/silicone oil tamponade(GT/SOT), and scleral buckling(SB) were performed in selected eyes. Outcome measurements mainly included intraocular pressure(IOP) and best-corrected visual acuity(BCVA).·RESULTS: Seven eyes from 7 male aphakic patients with a mean age of 45(range, 20-68)y were included in this study;the average follow-up time was 12(9-15)mo. GT was performed in 2 eyes;membrane peeling(MP) and SOT in 2 eyes;and MP, SOT, and SB in 3 eyes. The mean preand post-operative IOP were 4.5(range, 4.0±0.11 to 4.8±0.2) mm Hg and 9.9(range, 5.6±0.17 to 12.1±0.2) mm Hg at 52wk(12mo), respectively. BCVA improved in six eyes;one eye still showed light perception, and no bulbi phthisis was observed.·CONCLUSION: Endoscopy offers improved judgment and recognition and has an improved prognosis for chronic hypotony. Therefore, endoscopy can be an effective and promising operative technique for chronic traumatic hypotony management.

变频改造对电厂辅机安全性的影响分析

电厂辅机泵和风机在进行变频改造后的进行中,出现了一些设备故障,通过分析电厂变频改造实例,发现变频改造后的发电厂泵类设备容易出现一定区间内弯曲振动较大的现象,风机类设备容易出现轴裂纹、联轴器损坏和断叶片现象,设备上的滚动轴承还容易出现轴电流腐蚀现象。对上述现象的原因进行了分析,研究了轴泵弯曲和扭转振动,并给出了相应的预防和处理建议。

Protective effects of lipoic acid-niacin dimers against blue light-induced oxidative damage to retinal pigment epithelium cells

AIM: To evaluate the protective effects of lipoic acid-niacin(N2 L) dimers against blue light(BL)-induced oxidative damage to human retinal pigment epithelium(hRPE) cells in vitro.METHODS: h RPE cells were divided into a control group(CG), a BL group, an N2 L plus BL irradiation group, an α-lipoic acid(ALA) plus BL group, an ALA-only group, and an N2 L-only group. hRPE cellular viability was detected by performing 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium(MTT) bromide assays, and apoptosis was evaluated by annexin-V-PE/7-AAD staining followed by flow cytometry. Ultrastructural changes in subcellular organelles were observed by transmission electron microscopy. Reactive oxygen species formation was assayed by flow cytometry. The expression levels of the apoptosis-related proteins BCL-2 associated X protein(BAX), B-cell leukmia/lymphoma 2(BCL-2), and caspase-3 were quantified by Western blot analysis.RESULTS: BL exposure with a light density of 4±0.5 mW/cm2 exceeding 6 h caused hRPE toxicity, whereas treatment with a high dose of N2 L(100 mol/L) or ALA(150 mol/L) maintained cell viability at control levels. BL exposure caused vacuole-like degeneration, mitochondrial swelling, and reduced microvillus formation;however, a high dose of N2 L or ALA maintained the ultrastructure of hRPE cells and their organelles. High doses of N2 L and ALA also protected hRPE cells from BL-induced apoptosis, which was confirmed by Western blot analysis: BCL-2 expression significantly increased, while BAX and caspase-3 expression slightly decreased compared to the CG.CONCLUSION: High-dose N2 L treatment(>100 mol/L) can reduce oxidative damage in degenerating hRPE cells exposed to BL with an efficacy similar to ALA.

Van Herick法及河南眼科研究所改进法检查前房深度估测房角关闭的准确性研究

目的:研究Van Herick法及河南眼科研究所改进法检查前房深度估测房角关闭的准确性。方法:随机选取2018-06/2019-01于我院门诊就诊的40岁及以上患者52例100眼分别行Van Herick法和河南眼科研究所改进法检查前房深度,筛选出周边前房深度≤1/3 CT且>1/4 CT与周边前房深度≤1/4 CT人群,对Van Herick法与河南研究所改进法前房检查法结果进行一致性检验,再行房角镜检查与暗室下UBM检查分别检查周边房角是否关闭。结果:在Van Herick法估测周边前房深度≤1/3 CT且>1/4 CT的患眼中,行房角镜检查与UBM检查结果房角关闭的阳性率分别为39%与43%,在河南眼科研究所改进法估测周边前房深度≤1/3 CT且>1/4 CT的患眼中,行房角镜检查与UBM检查结果房角关闭的阳性率分别为46%与42%;在Van Herick法估测周边前房深度≤1/4 CT的患眼中,行房角镜检查与UBM检查结果房角关闭的阳性率分别为67%与89%;在河南眼科研究所改进法估测周边前房深度≤1/4 CT的患眼中,行房角镜检查与UBM检查结果房角关闭的阳性率分别为70%与100%;对Van Herick法与河南眼科研究所改进法进行一致性检验,在估测周边前房深度≤1/3CT且>1/4 CT时,Kappa值为0.85,一致性较好,在估测周边前房深度≤1/4 CT时,Kappa值为0.83,一致性较好;对房角镜检查结果及UBM检查结果进行一致性检验,在Van Herick法估测周边前房深度≤1/3 CT且>1/4 CT时,Kappa值为0.73,一致性一般,在Van Herick法估测周边前房深度≤1/4 CT时,Kappa值为0.40,一致性一般。对房角镜检查结果及UBM检查结果进行一致性检验,在河南眼科研究所改进法估测周边前房深度≤1/3 CT且>1/4 CT时,Kappa值为0.75,一致性较好,在河南眼科研究所改进法估测周边前房深度≤1/4 CT时,Kappa值为0,一致性较差。结论:Van Herick法及河南眼科研究所改进法前房深度检查在测量人群中房角关闭的具有一定的假阴性率,但准确性较高,仍适合作为估测房角关闭的初步检查方式。

Simulation of methane adsorption in diverse organic pores in shale reservoirs with multi-period geological evolution

In shale reservoirs,the organic pores with various structures formed during the thermal evolution of organic matter are the main storage site for adsorbed methane.However,in the process of thermal evolution,the adsorption characteristics of methane in multi type and multi-scale organic matter pores have not been sufficiently studied.In this study,the molecular simulation method was used to study the adsorption characteristics of methane based on the geological conditions of Longmaxi Formation shale reservoir in Sichuan Basin,China.The results show that the characteristics of pore structure will affect the methane adsorption characteristics.The adsorption capacity of slit-pores for methane is much higher than that of cylindrical pores.The groove space inside the pore will change the density distribution of methane molecules in the pore,greatly improve the adsorption capacity of the pore,and increase the pressure sensitivity of the adsorption process.Although the variation of methane adsorption characteristics of different shapes is not consistent with pore size,all pores have the strongest methane adsorption capacity when the pore size is about 2 nm.In addition,the changes of temperature and pressure during the thermal evolution are also important factors to control the methane adsorption characteristics.The pore adsorption capacity first increases and then decreases with the increase of pressure,and increases with the increase of temperature.In the early stage of thermal evolution,pore adsorption capacity is strong and pressure sensitivity is weak;while in the late stage,it is on the contrary.

基于有机小分子聚集体的荧光传感与生物成像

荧光分析法具有检测灵敏、响应快速、易于进行可视化和实时动态分析的特点,在临床诊断、环境监测、公众健康等领域有广泛应用.具有聚集诱导发光(AIE)性质的有机小分子聚集体克服了传统荧光分子在聚集态下的荧光淬灭问题,具有优异的发光性能,为设计荧光探针提供了新思路.本文综述了课题组近年来在有机小分子聚集体研究中的代表性成果,从分子结构、光物理学性质及其在荧光传感、细胞成像和肿瘤诊疗等领域的应用角度阐述基于有机小分子聚集体的荧光探针的设计思路和发展方向.

微重力下圆台形容器内角处毛细现象

在微重力环境中,液体通常吸附在夹角或缝隙中.积聚在这些区域的液体难以排出和使用.本文通过理论推导得到了微重力环境下圆台形容器内角处液体的气液界面轮廓.根据液体的润湿性和内角大小,界面轮廓可分为两种情况.一旦知道轮廓某个端点的坐标,就可以根据数学模型使用打靶法获得液面轮廓和体积.此外,如果轮廓端点的横坐标值无法测量得到,在给定液体体积的情况下,也可以使用二分法和打靶法获得液面轮廓.本文提出的方法比之前提出的基于Gibbs自由能的方法更容易.该方法也可用来预测其他结构间的液面轮廓.本文采用有限体积法开展数值模拟,仿真结果与理论值吻合良好.基于该数学模型,可准确预测圆台形容器内角处积聚液体的液面轮廓和体积.

Phenotypic Analysis of Diseased Plant Leaves Using Supervised and Weakly Supervised Deep Learning

Deep learning and computer vision have become emerging tools for diseased plant phenotyping.Most previous studies focused on image-level disease classification.In this paper,pixel-level phenotypic feature(the distribution of spot)was analyzed by deep learning.Primarily,a diseased leaf dataset was collected and the corresponding pixel-level annotation was contributed.A dataset of apple leaves samples was used for training and optimization.Another set of grape and strawberry leaf samples was used as an extra testing dataset.Then,supervised convolutional neural networks were adopted for semantic segmentation.Moreover,the possibility of weakly supervised models for disease spot segmentation was also explored.Grad-CAM combined with ResNet-50(ResNet-CAM),and that combined with a few-shot pretrained U-Net classifier for weakly supervised leaf spot segmentation(WSLSS),was designed.They were trained using image-level annotations(healthy versus diseased)to reduce the cost of annotation work.Results showed that the supervised DeepLab achieved the best performance(IoU=0.829)on the apple leaf dataset.The weakly supervised WSLSS achieved an IoU of 0.434.When processing the extra testing dataset,WSLSS realized the best IoU of 0.511,which was even higher than fully supervised DeepLab(IoU=0.458).Although there was a certain gap in IoU between the supervised models and weakly supervised ones,WSLSS showed stronger generalization ability than supervised models when processing the disease types not involved in the training procedure.Furthermore,the contributed dataset in this paper could help researchers get a quick start on designing their new segmentation methods in future studies.

Spectral Preprocessing Combined with Deep Transfer Learning to Evaluate Chlorophyll Content in Cotton Leaves

Rapid determination of chlorophyll content is significant for evaluating cotton’s nutritional and physiological status.Hyperspectral technology equipped with multivariate analysis methods has been widely used for chlorophyll content detection.However,the model developed on one batch or variety cannot produce the same effect for another due to variations,such as samples and measurement conditions.

End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses

Herbicides and heavy metals are hazardous substances of environmental pollution,resulting in plant stress and harming humans and animals.Identification of stress types can help trace stress sources,manage plant growth,and improve stress-resistant breeding.In this research,hyperspectral imaging(HSI)and chlorophyll fluorescence imaging(Chl-FI)were adopted to identify the rice plants under two types of herbicide stresses(butachlor(DCA)and quinclorac(ELK))and two types of heavy metal stresses(cadmium(Cd)and copper(Cu)).

A review on DFACS(II):Modeling and analysis of disturbances and noises

This paper presents Part II of a review on DFACS,which specifically focuses on the modeling and analysis of disturbances and noises in DFACSs.In Part I,the system composition and dynamics model of the DFACS were presented.In this paper,we discuss the effects of disturbance forces and noises on the system,and summarize various analysis and modeling methods for these interferences,including the integral method,frequency domain analysis method,and magnitude evaluation method.By analyzing the impact of disturbances and noises on the system,the paper also summarizes the system’s performance under slight interferences.Additionally,we highlight current research difficulties in the field of DFACS noise analysis.Overall,this paper provides valuable insights into the modeling and analysis of disturbances and noises in DFACSs,and identifies key areas for future research.

A review on DFACS(I):System design and dynamics modeling

The Drag-Free and Attitude Control System(DFACS)is a critical platform for various space missions,including high precision satellite navigation,geoscience and gravity field measurement,and space scientific experiments.This paper presents a comprehensive review of over sixty years of research on the design and dynamics model of DFACS.Firstly,we examine the open literature on DFACS and its applications in Drag-Free missions,providing readers with necessary background information on the field.Secondly,we analyze the system configurations and main characteristics of different DFACSs,paying particular attention to the coupling mechanism between the system configuration and dynamics model.Thirdly,we summarize the dynamics modeling methods and main dynamics models of DFACS from multiple perspectives,including common fundamentals and specific applications.Lastly,we identify current challenges and technological difficulties in the system design and dynamics modeling of DFACS,while suggesting potential avenues for future research.This paper aims to provide readers with a comprehensive understanding of the state-of-the-art in DFACS research,as well as the future prospects and challenges in this field.

Application of Visible/Near-Infrared Spectroscopy and Hyperspectral Imaging with Machine Learning for High-Throughput Plant Heavy Metal Stress Phenotyping:A Review

Heavy metal pollution is becoming a prominent stress on plants.Plants contaminated with heavy metals undergo changes in external morphology and internal structure,and heavy metals can accumulate through the food chain,threatening human health.Detecting heavy metal stress on plants quickly,accurately,and nondestructively helps to achieve precise management of plant growth status and accelerate the breeding of heavy metal-resistant plant varieties.Traditional chemical reagent-based detection methods are laborious,destructive,time-consuming,and costly.The internal and external structures of plants can be altered by heavy metal contamination,which can lead to changes in plants'absorption and reflection of light.Visible/near-infrared(V/NIR)spectroscopy can obtain plant spectral information,and hyperspectral imaging(HSI)can obtain spectral and spatial information in simple,speedy,and nondestructive ways.These 2 technologies have been the most widely used high-throughput phenotyping technologies of plants.This review summarizes the application of V/NIR spectroscopy and HSI in plant heavy metal stress phenotype analysis as well as introduces the method of combining spectroscopy with machine learning approaches for high-throughput phenotyping of plant heavy metal stress,including unstressed and stressed identification,stress types identification,stress degrees identification,and heavy metal content estimation.The vegetation indexes,full-range spectra,and feature bands identified by different plant heavy metal stress phenotyping methods are reviewed.The advantages,limitations,challenges,and prospects of V/NIR spectroscopy and HSI for plant heavy metal stress phenotyping are discussed.Further studies are needed to promote the research and application of V/NIR spectroscopy and HSI for plant heavy metal stress phenotyping.