Robustα-Fe_(2)O_(3)/Epoxy Resin Superhydrophobic Coatings for Anti-icing Property

α-Fe_(2)O_(3)/epoxy resin composite superhydrophobic coating was prepared withα-Fe_(2)O_(3) nanoparticles and epoxy resin by spin coating method.The coating without epoxy resin has higher contact angle(CA)and lower ice adhesion strength(IAS),but the mechanical properties are poor.Theα-Fe_(2)O_(3)/epoxy resin composite superhydrophobic coating exhibits good mechanical durability.In addition,compared with the bare aluminum substrate,the Ecorr of the composite coating is positive and the Jcorr is lower.The inhibition efficiency of the composite coating is as high as 99.98%in 3.5 wt%NaCl solution.The difference in the microstructure caused by the two preparation methods leads to the changes in mechanical properties and corrosion resistance of composite superhydrophobic coating.

Methods to prevent side marks from rusting on heavy steel plates

When a steel plate produced by a steel plant leaves the factory,its upper surface should be marked with the specification,variety,batch number,and other identifying information,and its side should be marked with a side marking.The side marking contains the plate number,specification,batch number,and other information,which are convenient for customers to accurately identify relevant information after stacking.However,because of the influence of weather,environment,and other factors,the side marking becomes unidentifiable when the steel plate is corroded,affecting the customer’s loading,unloading,and other operations.The development and application of side anticorrosion devices and cleaning of finished heavy steel plates with antirust agents will solve the problem of unrecognizable side marking due to corrosion.

Coffee Leaf Rust(Hemileia vastatrix)Disease in Coffee Plants and Perspectives by the Disease Control

Coffee Leaf Rust(CLR)is caused by Hemileia vastatrix in Coffea spp.It is one of the most dangerous phytopathogens for coffee plantations in terms of coffee productivity and coffee cup quality.In this review,we resume the problem of CLR in Mexico and the pathogenesis of H.vastatrix.The review abord plant-pathogen interactions which lead a compatible or incompatible interactions and result in CLR disease or resistance,respectively.The review abord Coffea spp.defense response pathways involved in H.vastatrix pathogenicity.Additionally,current measures to control H.vastatrix proliferation and germination were aborded focused on phytosanitary actions,and biological and chemical control.Finally,new trendlines to reduce the impact of CLR as nanoparticles and nanotechnology were analyzed.

Study of Flow and Heat Transfer in an Ejector-Driven Swirl Anti-Icing Chamber

The formation of ice on the leading edge of aircraft engines is a serious issue,as it can have catastrophic consequences.The Swirl Anti-Icing(SAI)system,driven by ejection,circulates hot fluid within a 360°annular chamber to heat the engine inlet lip surface and prevent icing.This study employs a validated Computational Fluid Dynamics(CFD)approach to study the impact of key geometric parameters of this system on flow and heat transfer characteristics within the anti-icing chamber.Additionally,the entropy generation rate and exergy efficiency are analyzed to assess the energy utilization in the system.The research findings indicate that,within the considered flow range,reducing the nozzle specific areaφfrom 0.03061 to 0.01083 can enhance the ejection coefficient by over 60.7%.This enhancement increases the air circulating rate,thereby intensifying convective heat transfer within the SAI chamber.However,the reduction inφalso leads to a significant increase in the required bleed air pressure and a higher entropy generation rate,indicating lower exergy efficiency.The nozzle angleθnotably affects the distribution of hot and cold spots on the lip surface of the SAI chamber.Increasingθfrom 0°to 20°reduces the maximum temperature difference on the anti-icing chamber surface by 60 K.

Neurosyphilis complicated by anti-γ-aminobutyric acid-B receptor encephalitis: A case report

BACKGROUND Syphilis is an infectious disease caused by Treponema pallidum that can invade the central nervous system,causing encephalitis.Few cases of anti-N-methyl-Daspartate receptor autoimmune encephalitis(AE)secondary to neurosyphilis have been reported.We report a neurosyphilis patient with anti-γ-aminobutyric acid-B receptor(GABABR)AE.CASE SUMMARY A young man in his 30s who presented with acute epileptic status was admitted to a local hospital.He was diagnosed with neurosyphilis,according to serum and cerebrospinal fluid(CSF)tests for syphilis.After 14 d of antiepileptic treatment and anti-Treponema pallidum therapy with penicillin,epilepsy was controlled but serious cognitive impairment,behavioral,and serious psychiatric symptoms were observed.He was then transferred to our hospital.The Mini-Mental State Examination(MMSE)crude test results showed only 2 points.Cranial magnetic resonance imaging revealed significant cerebral atrophy and multiple fluidattenuated inversion recovery high signals in the white matter surrounding both lateral ventricles,left amygdala and bilateral thalami.Anti-GABABR antibodies were discovered in CSF(1:3.2)and serum(1:100).The patient was diagnosed with neurosyphilis complicated by anti-GABABR AE,and received methylprednisolone and penicillin.Following treatment,his mental symptoms were alleviated.Cognitive impairment was significantly improved,with a MMSE of 8 points.Serum anti-GABABR antibody titer decreased to 1:32.The patient received methylprednisolone and penicillin after discharge.Three months later,the patient’s condition was stable,but the serum anti-GABABR antibody titer was 1:100.CONCLUSION This patient with neurosyphilis combined with anti-GABABR encephalitis benefited from immunotherapy.

Rust语言在Web开发的应用研究

随着互联网技术的飞速发展,Web应用已成为人们日常生活和工作中不可或缺的一部分。但随着Web应用的规模和复杂性的不断增长,传统的开发语言在性能、安全性和并发性方面逐渐面临挑战。Rust作为一种新兴的系统级编程语言,以其高效、安全和并发性强的特点,逐渐在Web开发中得到广泛应用。

Rust语言在核电安全级仪控研发应用探讨

在核安全级(1E)仪控应用中,基于处理器的应用绝大部分使用C语言来实现。针对C语言存在弱内存管理、弱数据类型、易于出错的指针控制等天然语言缺陷,提出了更安全的Rust编程语言在核电仪控中应用可能性的探讨。首先分析了C语言固有特性的安全缺陷和Rust语言的安全优势,其次结合核电行业安全软件关键需求探讨了Rust语言的切实应用场景,并阐述了Rust语言应用于核电仪控面临着极大的挑战。最后,为推动核电仪控领域应用更安全的编程语言,提出了积极的展望。

Improvement to anti-rust property of hot rolled rebar by compact oxide scale

A method was proposed to improve the anti-rust property of hot rolled rebar, which uses oil–water emulsion cooling instead of water cooling after hot rolling. The experiments were carried out by two cooling methods, one cooled by water, the other cooled by oil–water emulsion. The results of wet/dry cyclic accelerated corrosion test showed that the anti-rust property of rebar cooled by oil–water emulsion was better than that by water obviously. The results of OM, SEM and EPMA analysis indicated that these two scales contained three layers: an outer Fe_3O_4 layer, an intermediate Fe O layer with island-shaped pro-eutectoid Fe_3O_4, an inner eutectoid Fe_3O_4 layer. For the water cooled rebar, all three layers of oxide scale were relatively thin. Moreover, the scale had plenty of defects such as porosity, and crack. However, for the oil–water emulsion cooled rebar, all three layers of oxide scale were relatively thick and compact, which played an important role in protecting the rebar from atmospheric rust.

Rust语言安全研究综述

Rust是为了解决系统编程领域的安全性问题,而设计的一门面向系统编程的兼具类型安全、内存安全和并发安全的新型程序设计语言,强调安全性和高性能,已经在操作系统内核、Web浏览器、网络协议栈、数据库和区块链等底层软件系统的构建中得到了越来越广泛的应用。现有研究表明,尽管Rust的设计目标是保证安全性,但其自身仍然存在许多安全问题。作为一门系统编程语言,Rust的安全性直接影响到基于Rust开发的软件系统的安全性。随着Rust的广泛应用,对Rust语言安全的研究显得尤为重要。Rust语言安全研究正在成为研究热点,并且在近几年已经取得了较大研究进展。本综述基于该研究领域已经公开发表的46篇研究论文,对该领域的相关研究进行了系统整理、分析和总结:首先,研究分析了Rust的核心安全特性,包括函数式编程范式、强多态类型系统、基于所有权模型的自动内存管理、对非安全代码的显式标记和隔离;其次,提出了Rust语言安全研究领域的分类学,将已有研究分为安全实证研究、漏洞检测研究、安全增强研究和形式化验证研究四个热点方向,并分别对这四个方向上的相关研究进行了综述、深入分析和总结,同时分析了四个研究方向的内在联系;最后,指出了该研究领域的待解决的科学问题,并对未来可能的研究方向进行了展望,提出了四个潜在的研究方向,以期为相关领域的研究者提供有价值的参考。

Fine mapping and transcriptome sequencing reveal candidate genes conferring all-stage resistance to stripe rust on chromosome arm 1AL in Chinese wheat landrace AS1676

Stripe rust, caused by Puccinia striiformis f. sp. tritici(Pst), threatens wheat production worldwide, and resistant varieties tend to become susceptible after a period of cultivation owing to the variation of pathogen races. In this study, a new resistance gene against Pst race CYR34 was identified and predicted using the descendants of a cross between AS1676, a highly resistant Chinese landrace, and Avocet S, a susceptible cultivar. From a heterozygous plant from a F7recombinant inbred line(RIL) population lacking the Yr18 gene, a near-isogenic line(NIL) population was developed to map the resistance gene. An allstage resistance gene, YrAS1676, was identified on chromosome arm 1AL via bulked-segregant exomecapture sequencing. By analyzing a large NIL population consisting of 6537 plants, the gene was further mapped to the marker interval between KA1A_485.36 and KA1A_490.13, spanning 485.36–490.13 Mb on1AL. A total of 66 annotated genes have been reported in this region. To characterize and predict the candidate gene(s), an RNA-seq was performed using NIL-R and NIL-S seedlings 3 days after CYR34 inoculation. Compared to NIL-S plants, NIL-R plants showed stronger immune reaction and higher expression levels of genes encoding pathogenesis-associated proteins. These differences may help to explain why NIL-R plants were more resistant to Pst race CYR34 than NIL-S plants. By combining fine-mapping and transcriptome sequencing, a calcium-dependent protein kinase gene was finally predicted as the potential candidate gene of YrAS1676. This gene contained a single-nucleotide polymorphism. The candidate gene was more highly expressed in NIL-R than in NIL-S plants. In field experiments with Pst challenge,the YrAS1676 genotype showed mitigation of disease damage and yield loss without adverse effects on tested agronomic traits. These results suggest that YrAS1676 has potential use in wheat stripe rust resistance breeding.

Green rusts-derived iron oxide nanostructures catalyze NO reduction by CO

Green rusts with brucite-like layers of hydroxide intercalated with anions constitute a family of diverse precursors for the synthesis of iron oxides via dehydration,but precise structural control of the resulting oxides with respect to the size and shape at the nanometer level remains challenging due to the easy oxidation of the ferrous species.Herein,we report a new synthetic strategy for the facile preparation of fibrous-like green rusts by using appropriate balancing anions(CO_(3)^(2-)and SO_(4)^(2-))in ethylene glycol to regulate the morphology.Depending on the type of the intercalating anion,the green rusts were converted into hematite with fibrous-or plate-like shapes upon thermal activation.When evaluated in the reaction of NO reduction by CO,these iron oxides showed a prominent shape-dependent catalytic behavior.The fibrous-like Fe_(2)O_(3)was much more catalytically active and structurally robust than the plate-like analogue.Combined spectroscopic and microscopic characterizations on the nanostructured iron oxides revealed that the superior performance of the fibrous-like Fe_(2)O_(3)stemmed from a facile Fe_(2)O_(3)/Fe_(3)O_(4)redox cycle and a higher density of active sites for NO activation.

High-resolution genetic mapping and identification of candidate genes for the wheat stem rust resistance gene Sr8155B1

Stem rust,caused by Puccinia graminis f.sp.tritici(Pgt),threatens global wheat production.Development of cultivars with increased resistance to stem rust by identification,mapping,and deployment of resistance genes is the best strategy for controlling the disease.In this study,we performed fine mapping and characterization of the all-stage stem rust resistance(Sr)gene Sr8155B1 from the durum wheat line 8155-B1.In seedling tests of biparental populations,Sr8155B1 was effective against six Chinese Pgt races tested.In a segregating population of 5060 gametes,Sr8155B1 was mapped to a 0.06-cM region flanked by markers Pku2772 and Pku43365,corresponding to 1.5-and 2.7-Mb regions in the Svevo and Chinese Spring reference genomes.Both regions include several typical nucleotide-binding leucine-rich repeat(NLR)and protein kinase genes that represent candidate genes.Among them,three NLR genes and three receptor-like protein kinases were highly polymorphic between the parental lines and their transcripts were upregulated in the homozygous resistant line TdR2 relative to its susceptible sister line TdS4.Four markers(Pku2772,Pku43365,Pku2950,and Pku3721)developed in this study,together with seedling resistance responses,correctly predicted Sr8155B1 absence or presence in 78 tetraploid wheat genotypes tested.The presence of Sr8155B1 in tetraploid wheat accessions CItr 14916,PI 197492,and PI 197493 was confirmed by mapping in three F_(2)populations.The genetic map and linked markers developed in this study may accelerate the deployment of Sr8155B1-mediated resistance in wheat breeding programs.

Prevention of Q235 Steel Corrosion using Waterborne Rust Inhibitor

Sorbitol,triethanolamine,sodium benzoate,boric acid,and sodium carbonate were mixed to prepare a waterborne rust inhibitor.A temperature and humidity accelerated corrosion test was applied to investigate the corrosion behaviour of waterborne rust inhibitor coated Q235 steel and original Q235 steel,which was carried out in a temperature and humidity test chamber(WSHW-1000)at a temperature of 80℃and humidity of 95%.Compared with the original Q235,waterborne rust inhibitor coated Q235 has better resistance to corrosion in hot and humid ambient conditions.Electrochemical impedance spectroscopy and potentiodynamic polarization were measured with a three-electrode cell in 3.5%NaCl aqueous solution on a CHI760E potentiostat/galvanostat.Molecular dynamics was simulated to verify the synergistic corrosion inhibitory mechanism of sodium carbonate and triethanolamine.The test shows that the prepared waterborne rust inhibitor can reduce the tendency of Q235 to corrosion and can also effectively reduce the corrosion rate.

Investigation of Aegilops umbellulata for stripe rust resistance,heading date,and the contents of iron,zinc,and gluten protein

Aegilops umbellulata(UU)is a wheat wild relative that has potential use in the genetic improvement of wheat.In this study,46 Ae.umbellulata accessions were investigated for stripe rust resistance,heading date(HD),and the contents of iron(Fe),zinc(Zn),and seed gluten proteins.Forty-two of the accessions were classified as resistant to stripe rust,while the other four accessions were classified as susceptible to stripe rust in four environments.The average HD of Ae.umbellulata was significantly longer than that of three common wheat cultivars(180.9 d vs.137.0 d),with the exception of PI226500(138.9 d).The Ae.umbellulata accessions also showed high variability in Fe(69.74-348.09 mg kg^(-1))and Zn(49.83-101.65 mg kg^(-1))contents.Three accessions(viz.,PI542362,PI542363,and PI554399)showed relatively higher Fe(230.96-348.09 mg kg^(-1))and Zn(92.46-101.65 mg kg^(-1))contents than the others.The Fe content of Ae.umbellulata was similar to those of Ae.comosa and Ae.markgrafii but higher than those of Ae.tauschii and common wheat.Aegilops umbellulata showed a higher Zn content than Ae.tauschii,Ae.comosa,and common wheat,but a lower content than Ae.markgrafii.Furthermore,Ae.umbellulata had the highest proportion of γ-gliadin among all the species investigated(Ae.umbellulata vs.other species=mean 72.11%vs.49.37%;range:55.33-86.99%vs.29.60-67.91%).These results demonstrated that Ae.umbellulata exhibits great diversity in the investigated traits,so it can provide a potential gene pool for the genetic improvement of these traits in wheat.

Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20%every year.The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques.The experienced evaluators take time to identify the disease which is highly laborious and too costly.If wheat rust diseases are predicted at the development stages,then fungicides are sprayed earlier which helps to increase wheat yield quality.To solve the experienced evaluator issues,a combined region extraction and cross-entropy support vector machine(CE-SVM)model is proposed for wheat rust disease identification.In the proposed system,a total of 2300 secondary source images were augmented through flipping,cropping,and rotation techniques.The augmented images are preprocessed by histogram equalization.As a result,preprocessed images have been applied to region extraction convolutional neural networks(RCNN);Fast-RCNN,Faster-RCNN,and Mask-RCNN models for wheat plant patch extraction.Different layers of region extraction models construct a feature vector that is later passed to the CE-SVM model.As a result,the Gaussian kernel function in CE-SVM achieves high F1-score(88.43%)and accuracy(93.60%)for wheat stripe rust disease classification.

Spray Prediction Model for Aonla Rust Disease Using Machine Learning

Disease prediction in plants has acquired much attention in recent years.Meteorological factors such as:temperature,relative humidity,rainfall,sunshine play an important role in a plan’s growth only if they are present in adequate amounts as required by the plant.On the other hand,if the factors are inadequate,they may also support the growth of a disease in the plants.The current study focuses on the Rust disease in Aonla fruits and leaves by utilizing a real time dataset of weather parameters.Fifteen different models are tested for spray prediction on conducive days.Two resampling techniques,random over sampling(ROS)and synthetic minority oversampling technique(SMOTE)have been used to balance the dataset and five different classifiers:support vector machine(SVM),logistic regression(LR),k-nearest neighbor(kNN),decision tree(DT)and random forest(RF)have been used to classify a particular day based on weather conditions as conducive or non-conducive.The classifiers are then evaluated based on four performance metrics:accuracy,precision,recall and F1-score.The results indicate that for imbalanced dataset,kNN is appropriate with high precision and recall values.Considering both balanced and imbalanced dataset models,the proposed model SMOTE-RF performs best among all models with 94.6%accuracy and can be used in a real time application for spray prediction.Hence,timely fungicide spray prediction without over spraying will help in better productivity and will prevent the yield loss due to rust disease in Aonla crop.

引进美国小麦种质资源抗病性及品质性状鉴定

为了挖掘新的种质资源,本研究对引自美国的442份小麦材料对白粉病和条锈病的抗病性、蛋白含量以及高分子量麦谷蛋白(HMW-GS)亚基组成进行了鉴定分析。抗病性鉴定结果显示,153份材料抗白粉病,27份抗条锈病,6份兼抗两种病害。蛋白质含量达到GB/T 17892-1999《优质小麦强筋小麦》一等(粗蛋白质含量≥15.0%)的样品有143份。高分子量麦谷蛋白检测发现,供试材料共含18种HMW-GS亚基和100种不同亚基组合类型,其中N,7+9,5+10出现次数最多,优质亚基1、2*、7^(oe)、17+18、5+10的材料分别占总材料数的25.6%、5.2%、27.8%、7.7%和25.6%,含7^(oe),5+10亚基的有36份,含2*,5+10亚基的有1份,含2*,7^(oe)亚基的有7份。综合抗病性及品质分析结果显示,PI 17738等11份材料至少抗1种病害,且蛋白含量≥15.0%,湿面筋含量≥35.0%,同时含有稀有优质亚基。以上11份材料可作为我国优质、抗病小麦培育亲本,为我国小麦抗病和品质遗传改良提供优异基因源。

小麦条锈病抗性基因定位及分子标记技术研究进展

条锈病流行对小麦生产造成巨大损失,选育和种植持久抗性品种是防治小麦条锈病最经济有效的策略。为达到多基因聚合培育持久抗病品种的目标,必须不断发掘抗病种质、解析其抗病遗传机制并开发分子标记。基于文献,对条锈病抗性基因发掘涉及的抗病性、分子标记、基因定位方法和定位进展及其在育种中的应用进行了综述,明确了小麦条锈病基因定位涉及技术的现状、局限性及优势,从而为后续的条锈病抗性基因发掘、多基因聚合和持久抗性小麦品种的选育与生产布局提供技术指导,以降低西北麦区和小麦主产区条锈病流行的频率,进一步促进国家粮食安全。

车用铸铁零配件切削液的开发、应用及维护研究

文章针对铸铁内燃机等汽车零配件单机加工和集中供液加工的不同需求,采用石蜡基或环烷基基础油与乳化剂、防锈剂、油性剂等不同功能添加剂进行复配,通过一系列试验优化,研发了具有优异防锈性的铸铁单机用切削液及兼具防锈性和润滑性的集中供液切削液。开发产品不含亚硝酸钠、壬基酚等物质,符合GB/T 32812环保要求,并获得较广泛工业应用。同时文章根据应用情况,提出了切削液维护指标建议及异常排查处理建议。

基于时间序列植被指数的小麦条锈病抗性等级鉴定方法

条锈病严重影响小麦产量,培育抗条锈病的小麦品种至关重要。针对传统育种中抗性鉴定手段单一、效率低的问题,该研究提出了一种通过小麦冠层植被指数的时间序列实现对条锈病不同抗性等级的高效鉴定方法。该方法利用无人机采集自然发病的育种群体小麦(共600个样本,516个基因型)冠层多时相的光谱图像,使用随机蛙跳算法和ReliefF算法筛选出6个条锈病病害严重度的敏感特征:归一化色素叶绿素指数(normalized pigment chlorophyll index,NPCI)、沃尔贝克指数(woebbecke index,WI)、叶绿素红边指数(chlorophyll index rededge,CIrededge)、绿大气抵抗植被指数(green atmospherically resistant index,GARI)、归一化差分植被指数(normalized difference vi,NDVI)、叶绿素绿指数(chlorophyll index green,CIgreen),这些敏感特征在试验群体中的时间序列符合条锈病的发病规律,验证了其作为条锈病发病严重度敏感特征的有效性;基于支持向量机(support vector machine,SVM)算法使用上述敏感特征建立条锈病病害严重度等级分类模型,在测试集的表现中,与使用未经过筛选的原始特征所建立的模型相比在精度、平均准确率、平均召回率和F1分数上分别仅下降6.2%、3.3%、2.7%、4.0%,证明了所筛选敏感特征的有效性;针对一般机器学习算法难以捕捉不同抗性等级样本之间较小的特征变化差异的问题,提出了一种从植被指数时间序列转化生成的二维图像中提取特征实现条锈病抗性等级分类的方法。将敏感特征中能够较好区分不同抗病等级的4个时间序列植被指数(NPCI、GARI、NDVI、WI),通过格拉姆角场方法生成格拉姆角和场图像,并制作成数据集,使用DenseNet121网络进行训练,以实现不同条锈病抗病等级的分类。建立的条锈病抗性等级分类模型中,由NPCI时间序列图像建立的分类模型测试效果最佳,其准确率为0.837,召回率为0.834,F1分数可达0.833,能够较好地实现对群体小麦不同品种(系)的条锈病抗性等级差异的区分,表明基于光谱植被指数时间序列的小麦条锈病抗性等级识别方法可以用于小麦抗病育种中抗性等级的鉴定,并可为其他作物的病害抗性等级鉴定提供一定的参考。