冠菌素诱导橡胶树次生乳管分化的形成层细胞CUT&Tag文库构建和初步分析

CUT&Tag技术是一种研究蛋白质-DNA互作的新方法,使用超高活性的新型pG-Tn5转座酶,在抗体引导下精准靶向切割目的蛋白附近的DNA序列,从而进行cDNA建库和测序分析。此技术在人类和动物研究中应用广泛,由于植物细胞结构特殊,该技术在植物研究中应用较少。在前期研究中,我们发现组蛋白乙酰化修饰参与茉莉酸诱导橡胶树次生乳管分化的调控,但其分子机制尚未阐明。本研究利用冠菌素(COR)诱导橡胶树萌条维管形成层分化次生乳管的实验系统,通过酶解法获取高质量的形成层区细胞原生质体,使用组蛋白H3乙酰化修饰抗体对次生乳管分化过程中发生组蛋白乙酰化修饰的区域进行原位识别,采用CUT&Tag技术成功构建COR处理橡胶树树皮形成层细胞的cDNA文库。对构建cDNA文库进行质检和测序分析,发现文库质量较好,并通过差异基因的GO和KEGG富集分析,发现生长素、类黄酮代谢和蛋白质泛素化等相关基因得到富集。本研究结果为使用CUT&Tag技术构建植物组织的cDNA文库提供操作方法,为解析组蛋白乙酰化修饰调控橡胶树次生乳管分化的分子机制提供理论基础。

表达Strep-tag II的重组塞内卡病毒的构建与鉴定

为构建表达Strep-tag II的重组塞内卡病毒(SVA),本研究在感染性cDNA克隆p SVA-I212V/S460L的基础上,采用重叠延伸PCR扩增Strep-tag II并采用无缝克隆法将其插入SVA VP1基因C端,构建感染性cDNA克隆,命名为p SVA-Strep,并采用双酶切和测序鉴定正确后,将p SVA-Strep转染BHK-21细胞拯救重组病毒,收集病变细胞上清,并将含有病毒的细胞上清和野生型SVA(SVA-WT)分别感染BHK-21细胞,以未感染病毒的BHK-21细胞作为阴性对照,感染后24 h分别以鼠源SVA VP2蛋白单克隆抗体(MAb)5D10(1∶1000)、鼠源Strep-tag II MAb(1∶2000)作为一抗,以FITC标记的山羊抗小鼠Ig G(1∶2000)为二抗,采用间接免疫荧光试验(IFA)对重组病毒鉴定。IFA结果显示,以鼠源SVA VP2蛋白MAb 5D10为一抗,SVA-WT和重组病毒感染的细胞均出现绿色荧光,以Strep-tag II MAb作为一抗时,仅有重组病毒感染的细胞出现绿色荧光,经SVA-WT感染的BHK-21细胞及阴性对照细胞均无绿色荧光,表明拯救了Strep-tag II标记的重组病毒,并将其命名为r SVA-Strep。将r SVA-Strep在BHK-21细胞中连续传10代,每隔2代采用引物VP1-F/R经PCR鉴定并对第10代重组病毒的VP1基因测序以鉴定r SVA-Strep的遗传稳定性。结果显示,每隔两代的重组病毒经PCR扩增后均出现约780 bp的目的条带,第10代重组病毒扩增的VP1基因测序结果显示Strep-tag II基因仍在重组病毒中,且无基因突变,表明r SVA-Strep的遗传稳定性较强;将SVA-WT和r SVA-Strep分别以MOI 0.01感染BHK-21细胞,在感染后4 h、8 h、12 h、24 h、36 h、48 h和72 h收获病毒测定病毒滴度并绘制生长曲线,结果显示在病毒感染36 h内r SVA-Strep和SVA-WT生长动力学基本一致,表明Strep-tag II的引入在病毒感染36 h内对SVA的复制基本无影响。采用0.2%甲醛充分灭活r SVA-Strep,并利用Strep-TactinRXT Purification纯化试剂盒纯化该灭活病毒,将r SVA-Strep灭活病毒上清加至Strep-Tactin亲和层析柱,分别用不同体积洗脱缓冲液依次洗脱病毒并通过western blot鉴定病毒的纯化效果。对纯化过程中不同洗脱液洗脱病毒的western blot结果显示,不同体积的洗脱液中E1、E2和E3均出现VP0和VP2两条带,且E1和E2的条带最明显,表明洗脱缓冲液的最佳洗脱体积约为2.2 CV;以上结果表明r SVA-Strep可通过Strep-Tactin亲和层析柱一步法纯化。本研究在SVA中插入Strep-tag II标签,为SVA灭活疫苗的快速纯化提供技术手段,也为其他病原的快速纯化方法的建立提供参考。

Serum proteins differentially expressed in gestational diabetes mellitus assessed using isobaric tag for relative and absolute quantitation proteomics

BACKGROUND As a well-known fact to the public,gestational diabetes mellitus(GDM)could bring serious risks for both pregnant women and infants.During this important investigation into the linkage between GDM patients and their altered expression in the serum,proteomics techniques were deployed to detect the differentially expressed proteins(DEPs)of in the serum of GDM patients to further explore its pathogenesis,and find out possible biomarkers to forecast GDM occurrence.METHODS Subjects were divided into GDM and normal control groups according to the IADPSG diagnostic criteria.Serum samples were randomly selected from four cases in each group at 24-28 wk of gestation,and the blood samples were identified by applying iTRAQ technology combined with liquid chromatography-tandem mass spectrometry.Key proteins and signaling pathways associated with GDM were identified by bioinformatics analysis,and the expression of key proteins in serum from 12 wk to 16 wk of gestation was further verified using enzyme-linked immunosorbent assay (ELISA).RESULTS Forty-seven proteins were significantly differentially expressed by analyzing the serum samples between the GDMgravidas as well as the healthy ones. Among them, 31 proteins were found to be upregulated notably and the rest16 proteins were downregulated remarkably. Bioinformatic data report revealed abnormal expression of proteinsassociated with lipid metabolism, coagulation cascade activation, complement system and inflammatory responsein the GDM group. ELISA results showed that the contents of RBP4, as well as ANGPTL8, increased in the serumof GDM gravidas compared with the healthy ones, and this change was found to initiate from 12 wk to 16 wk ofgestation.CONCLUSION GDM symptoms may involve abnormalities in lipid metabolism, coagulation cascade activation, complementsystem and inflammatory response. RBP4 and ANGPTL8 are expected to be early predictors of GDM.

Assessment of the performance of the TOPGNSS and ANN-MB antennas for ionospheric measurements using low-cost u-blox GNSS receivers

Low-cost GNSS receivers have recently been gaining reliability as good candidates for ionospheric studies. In line with these gains are genuine concerns about improving the performance of these receivers. In this work, we present a comprehensive investigation of the performances of two antennas(the u-blox ANN-MB and the TOPGNSS TOP-106) used on a low-cost GNSS receiver known as the u-blox ZED-F9P. The two antennas were installed on two identical and co-located u-blox receivers. Data used from both receivers cover the period from January to June 2022. Results from the study indicate that the signal strengths are dominantly greater for the receiver with the TOPGNSS antenna than for the receiver with the ANN-MB antenna, implying that the TOPGNSS antenna is better than the ANN-MB antenna in terms of providing greater signal strengths. Summarily, the TOPGNSS antenna also performed better in minimizing the occurrence of cycle slips on phase TEC measurements. There are no conspicuous differences between the variances(computed as 5-min standard deviations) of phase TEC measurements for the two antennas, except for a period around May-June when the TOPGNSS gave a better performance in terms of minimizing the variances in phase TEC. Remarkably, the ANN-MB antenna gave a better performance than the TOPGNSS antenna in terms of minimizing the variances in pseudorange TEC for some satellite observations. For precise horizontal(North and East) positioning, the receiver with the TOPGNSS antenna gave better results, while the receiver with the ANN-MB antenna gave better vertical(Up) positioning. The errors for the receivers of both antennas are typically within about 5 m(the monthly mean was usually smaller than 1 m) in the horizontal direction and within about 10 m(the monthly mean was usually smaller than 4 m) in the vertical direction.

Joint Modeling of Citation Networks and User Preferences for Academic Tagging Recommender System

In the tag recommendation task on academic platforms,existing methods disregard users’customized preferences in favor of extracting tags based just on the content of the articles.Besides,it uses co-occurrence techniques and tries to combine nodes’textual content for modelling.They still do not,however,directly simulate many interactions in network learning.In order to address these issues,we present a novel system that more thoroughly integrates user preferences and citation networks into article labelling recommendations.Specifically,we first employ path similarity to quantify the degree of similarity between user labelling preferences and articles in the citation network.Then,the Commuting Matrix for massive node pair paths is used to improve computational performance.Finally,the two commonalities mentioned above are combined with the interaction paper labels based on the additivity of Poisson distribution.In addition,we also consider solving the model’s parameters by applying variational inference.Experimental results demonstrate that our suggested framework agrees and significantly outperforms the state-of-the-art baseline on two real datasets by efficiently merging the three relational data.Based on the Area Under Curve(AUC)and Mean Average Precision(MAP)analysis,the performance of the suggested task is evaluated,and it is demonstrated to have a greater solving efficiency than current techniques.

A Novel Anti-Collision Algorithm for Large Scale of UHF RFID Tags Access Systems

When the radio frequency identification(RFID)system inventories multiple tags,the recognition rate will be seriously affected due to collisions.Based on the existing dynamic frame slotted Aloha(DFSA)algorithm,a sub-frame observation and cyclic redundancy check(CRC)grouping combined dynamic framed slotted Aloha(SUBF-CGDFSA)algorithm is proposed.The algorithm combines the precise estimation method of the quantity of large-scale tags,the large-scale tags grouping mechanism based on CRC pseudo-randomcharacteristics,and the Aloha anti-collision optimization mechanism based on sub-frame observation.By grouping tags and sequentially identifying themwithin subframes,it accurately estimates the number of remaining tags and optimizes frame length accordingly to improve efficiency in large-scale RFID systems.Simulation outcomes demonstrate that this proposed algorithmcan effectively break through the system throughput bottleneck of 36.8%,which is up to 30%higher than the existing DFSA standard scheme,and has more significant advantages,which is suitable for application in largescale RFID tags scenarios.

A U-Shaped Network-Based Grid Tagging Model for Chinese Named Entity Recognition

Chinese named entity recognition(CNER)has received widespread attention as an important task of Chinese information extraction.Most previous research has focused on individually studying flat CNER,overlapped CNER,or discontinuous CNER.However,a unified CNER is often needed in real-world scenarios.Recent studies have shown that grid tagging-based methods based on character-pair relationship classification hold great potential for achieving unified NER.Nevertheless,how to enrich Chinese character-pair grid representations and capture deeper dependencies between character pairs to improve entity recognition performance remains an unresolved challenge.In this study,we enhance the character-pair grid representation by incorporating both local and global information.Significantly,we introduce a new approach by considering the character-pair grid representation matrix as a specialized image,converting the classification of character-pair relationships into a pixel-level semantic segmentation task.We devise a U-shaped network to extract multi-scale and deeper semantic information from the grid image,allowing for a more comprehensive understanding of associative features between character pairs.This approach leads to improved accuracy in predicting their relationships,ultimately enhancing entity recognition performance.We conducted experiments on two public CNER datasets in the biomedical domain,namely CMeEE-V2 and Diakg.The results demonstrate the effectiveness of our approach,which achieves F1-score improvements of 7.29 percentage points and 1.64 percentage points compared to the current state-of-the-art(SOTA)models,respectively.

Differential Expression Analysis of Proteins Regulated by Rare Earth Cerium in Soybean Leaves at Seedling Stage

This study was to explore the functional mechanism of rare earth regulating soybean leaves and the characteristics and functions of differentially expressed proteins under the regulation of rare earth. In this study, Dongnong 42 was used as material, and 30 mg·L^(-1) CeCl_(3) solution was sprayed on soybean leaves at the seedling stage. Tandem mass tag(TMT) quantitative proteomics technique and bioinformatics analysis were used to identify soybean leaf proteins. A total of 8 510 proteins were identified, and 127 differentially expressed proteins(DEPs) in response to rare earth cerium regulation were identified, among which 64 were upregulated and 63 were down-regulated. The gene ontology(GO) annotation indicated that DEPs were mainly involved in metabolic process, cellular process, response to stimulus, biological regulation, and response to a stimulus;DEPs in cell module categories were mainly involved in cells, cell part, organelle, membrane, membrane part, organelle par, and protein-containing complex;DEPs in molecular functional categories were mainly involved in catalytic activity, binding and antioxidant activity. Kyoto encyclopedia of genes and genomes(KEGG) pathway significantly enriched starch and sucrose metabolism, glycolysis/gluconeogenesis, galactose metabolism, pentose phosphate pathway, and MAPK signaling pathway-plant. These DEPs were mainly involved in photosynthesis, glucose metabolism and stress response. Forty-six differential protein interaction networks were identified by protein interaction network analysis. This experiment provided a reference for studies of the mechanism of rare earth cerium regulating soybean leaf function from the proteomic perspective.

Unscented Kalman filter for a low-cost GNSS/IMU-based mobile mapping application under demanding conditions

For the last two decades,low-cost Global Navigation Satellite System(GNSS)receivers have been used in various applications.These receivers are mini-size,less expensive than geodetic-grade receivers,and in high demand.Irrespective of these outstanding features,low-cost GNSS receivers are potentially poorer hardwares with internal signal processing,resulting in lower quality.They typically come with low-cost GNSS antenna that has lower performance than their counterparts,particularly for multipath mitigation.Therefore,this research evaluated the low-cost GNSS device performance using a high-rate kinematic survey.For this purpose,these receivers were assembled with an Inertial Measurement Unit(IMU)sensor,which actively transmited data on acceleration and orientation rate during the observation.The position and navigation parameter data were obtained from the IMU readings,even without GNSS signals via the U-blox F9R GNSS/IMU device mounted on a vehicle.This research was conducted in an area with demanding conditions,such as an open sky area,an urban environment,and a shopping mall basement,to examine the device’s performance.The data were processed by two approaches:the Single Point Positioning-IMU(SPP/IMU)and the Differential GNSS-IMU(DGNSS/IMU).The Unscented Kalman Filter(UKF)was selected as a filtering algorithm due to its excellent performance in handling nonlinear system models.The result showed that integrating GNSS/IMU in SPP processing mode could increase the accuracy in eastward and northward components up to 68.28%and 66.64%.Integration of DGNSS/IMU increased the accuracy in eastward and northward components to 93.02%and 93.03%compared to the positioning of standalone GNSS.In addition,the positioning accuracy can be improved by reducing the IMU noise using low-pass and high-pass filters.This application could still not gain the expected position accuracy under signal outage conditions.

34.TAG·西海美术馆:面朝大海的艺术长廊

设计:让·努维尔事务所地点:山东青岛西海岸新区时间:2012—2021年规模:17000 m^(2)TAG·西海美术馆位于一座半岛的海边,远离市区^([1,2])。从规划意图看,整个项目由美术馆和艺术工坊两部分组成,但由于工坊部分处于停工状态,艺术社区氛围尚未形成,作为主体建筑的美术馆便成了荒野中的孤独存在,公众可达性较差(图1)。尽管如此,从设计研究角度,这座美术馆仍有许多精彩看点值得关注。

TAG HEUER 竞速激情

继去年以卡莱拉系列Skipper计时码表的精钢版本标志着品牌重返帆船运动与航海领域之后,TAG Heuer泰格豪雅如今欣然发布一款以18K 5N玫瑰金打造的全新版本。金质的Skipper计时码表与精钢版本类似,同样基于2023年前期为纪念卡莱拉系列计时码表60周年推出且热销的“玻璃盒”(glassbox)设计,并搭载品牌自制机心Heuer 02(型号:TH20-06),这是一款为帆船赛计时而特别调整的Heuer 02机心。

TAG HEUER 传奇之作 全面提升

传奇的卡莱拉泛美公路赛以其在墨西哥的严苛挑战而闻名,杰克·豪雅(Jack Heuer)以此为灵感,为TAG HEUER泰格豪雅卡莱拉系列腕表赋予了这一独特且极具影响力的名字。该系列凭借持续挑战边界的精准度,迅速赢得了市场的青睐并占据表迷的腕间,时至今日依旧风靡全球。在对系列进行了无数次的演绎后,日前泰格豪雅再度带来多款全新作品,将竞速传承、前沿材质及创新设计巧妙融合,一方面,是对2016年焕新的备受赞誉的卡莱拉系列运动风格计时码表的大胆演绎,另一方面,标志着该系列的又一次升级演变。

一种含SNAP-tag TM底物的硫醇荧光探针

合成了一种同时含α,β-不饱和酮活性位点和SNAP-tag TM底物的香豆素母体探针香豆素-烯酮-苯甲氨基鸟嘌呤(CAKBG).通过测试探针CAKBG的紫外-可见吸收光谱和荧光发射光谱,发现探针CAKBG在极性溶剂(例如,甘油、乙二醇、水、DMSO)中有更长的吸收波长,且探针CAKBG对溶液的pH变化不敏感.此外,光谱实验发现生物硫醇Cys和Hcy均能引起探针CAKBG的最大吸收波长发生蓝移,且当激发波长为405 nm时,Cys和Hcy均能导致探针CAKBG在487 nm处的荧光发射峰明显增强.细胞成像结果表明,含有SNAP-tag TM底物的硫醇荧光探针CAKBG在活细胞中可以对Cys、Hcy进行荧光成像.综上,SNAP-Tag TM蛋白标签技术有望今后在硫醇荧光探针的细胞成像中得到推广应用.

铜麦6号苗期耐高铵与耐盐特性的鉴定及TaGS基因的表达模式分析

为鉴定小麦品种铜麦6号的耐高铵及耐盐特性,对铜麦6号、中国春及抗逆性较强的烟农19、三抗10号、矮优王、烟农21、山农25的发芽势和发芽率进行测定,发现铜麦6号的耐铵指数位列第一,耐盐指数位列第二。以中国春为对照品种,在高铵、高盐及其双重胁迫处理下,测定其苗期的叶片鲜重、根鲜重、主根和第一叶叶片长度以及根冠比,发现高铵、高盐及其双重胁迫处理7 d后,铜麦6号的上述指标均不同程度高于中国春(除铜麦6号的根冠比在高盐处理1 d后低于中国春外),说明铜麦6号具有较强的耐高铵和耐高盐特性。进一步采用qRT-PCR检测小麦苗期谷氨酰胺合成酶TaGS基因家族成员(根中TaGS1;1、TaGS1;2和TaGS1;3基因以及叶片中TaGS2基因)的表达模式,发现高铵、高盐及其双重处理均可诱导铜麦6号苗期TaGS基因上调表达,且高盐处理下上调表达更明显,其中除高铵与高盐双重处理7 d后的TaGS1;2基因以及高铵和高盐处理1 d后的TaGS2基因在铜麦6号中的表达量低于中国春外,其他三种处理不同时间点铜麦6号中这两个基因的相对表达量均不同程度高于中国春。这些结果说明,铜麦6号苗期TaGS基因家族与其耐高铵和耐高盐特性相关,其中TaGS1;2和TaGS2基因的贡献较大。

Rational design and low-cost fabrication of multifunctional separators enabling high sulfur utilization in long-life lithium-sulfur batteries

The lithium-sulfur(Li-S)battery with an ultrahigh theoretical energy density has emerged as a promising rechargeable battery system.However,the practical applications of Li-S batteries are severely plagued by the sluggish reaction kinetics of sulfur species and notorious shuttling of soluble lithium polysulfides(LiPSs)intermediates that result in low sulfur utilization.The introduction of functional layers on separators has been considered as an effective strategy to improve the sulfur utilization in Li-S batteries by achieving effective regulation of LiPSs.Herein,a promising self-assembly strategy is proposed to achieve the low-cost fabrication of hollow and hierarchically porous Fe_(3)O_(4)nanospheres(p-Fe_(3)O_(4)-NSs)assembled by numerous extremely-small primary nanocrystals as building blocks.The rationally-designed p-Fe_(3)O_(4)-NSs are utilized as a multifunctional layer on the separator with highly efficient trapping and conversion features toward LiPSs.Results demonstrate that the nanostructured p-Fe_(3)O_(4)-NSs provide chemical adsorption toward LiPSs and kinetically promote the mutual transformation between LiPSs and Li_(2)S_(2)/Li_(2)S during cycling,thus inhibiting the LiPSs shuttling and boosting the redox reaction kinetics via a chemisorption-catalytic conversion mechanism.The enhanced wettability of the p-Fe_(3)O_(4)-NSs-based separator with the electrolyte enables fast transportation of lithium ions.Benefitting from these alluring properties,the functionalized separator with p-Fe_(3)O_(4)-NSs endows the battery with an admirable rate performance of 877 mAh g^(−1)at 2 C,an ultra-durable cycling performance of up to 2176 cycles at 1 C,and a promising areal capacity of 4.55 mAh cm^(−2)under high-sulfur-loading and lean-electrolyte conditions(4.29 mg cm^(−2),electrolyte/ratio:8μl mg^(−1)).This study will offer fresh insights on the rational design and low-cost fabrication of multifunctional separator to strengthen electrochemical reaction kinetics by regulating LiPSs conversion for developing efficient and long-life Li-S batteries.

Tandem Mass Tag-based proteomics analysis reveals the vital role of inflammation in traumatic brain injury in a mouse model

Proteomics is a powerful tool that can be used to elucidate the underlying mechanisms of diseases and identify new biomarkers.Therefore,it may also be helpful for understanding the detailed pathological mechanism of traumatic brain injury(TBI).In this study,we performed Tandem Mass Tag-based quantitative analysis of cortical proteome profiles in a mouse model of TBI.Our results showed that there were 302 differentially expressed proteins in TBI mice compared with normal mice 7 days after injury.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that these differentially expressed proteins were predominantly involved in inflammatory responses,including complement and coagulation cascades,as well as chemokine signaling pathways.Subsequent transcription factor analysis revealed that the inflammation-related transcription factors NF-κB1,RelA,IRF1,STAT1,and Spi1 play pivotal roles in the secondary injury that occurs after TBI,which further corroborates the functional enrichment for inflammatory factors.Our results suggest that inflammation-related proteins and inflammatory responses are promising targets for the treatment of TBI.

Intelligent SLAM Algorithm Fusing Low-Cost Sensors at Risk of Building Collapses

When firefighters search inside a building that is at risk of collapse due to abandonment or disasters such as fire,they use old architectural drawings or a simple monitoring method involving a video device attached to a robot.However,using these methods,the disaster situation inside a building at risk of collapse is difficult to detect and identify.Therefore,we investigate the generation of digital maps for a disaster site to accurately analyze internal situations.In this study,a robot combined with a low-cost camera and twodimensional light detection and ranging(2D-lidar)traverses across a floor to estimate the location of obstacles while drawing an internal map of the building.We propose an algorithm that detects the floor and then determines the possibility of entry,tracks collapses,and detects obstacles by analyzing patterns on the floor.The robot’s location is estimated,and a digital map is created based on Hector simultaneous localization and mapping(SLAM).Subsequently,the positions of obstacles are estimated based on the range values detected by 2D-lidar,and the position of the obstacles are identified on the map using the map update method in semantic SLAM.All equipment are implemented using low-specification devices,and the experiments are conducted using a low-cost robot that affords near-real-time performance.The experiments are conducted in various actual internal environments of buildings.In terms of obstacle detection performance,almost all obstacles are detected,and their positions identified on the map with a high accuracy of 89%.

Efficient and robust missing key tag identification for large-scale RFID systems

Radio Frequency Identification(RFID)technology has been widely used to identify missing items.In many applications,rapidly pinpointing key tags that are attached to favorable or valuable items is critical.To realize this goal,interference from ordinary tags should be avoided,while key tags should be efficiently verified.Despite many previous studies,how to rapidly and dynamically filter out ordinary tags when the ratio of ordinary tags changes has not been addressed.Moreover,how to efficiently verify missing key tags in groups rather than one by one has not been explored,especially with varying missing rates.In this paper,we propose an Efficient and Robust missing Key tag Identification(ERKI)protocol that consists of a filtering mechanism and a verification mechanism.Specifically,the filtering mechanism adopts the Bloom filter to quickly filter out ordinary tags and uses the labeling vector to optimize the Bloom filter's performance when the key tag ratio is high.Furthermore,the verification mechanism can dynamically verify key tags according to the missing rates,in which an appropriate number of key tags is mapped to a slot and verified at once.Moreover,we theoretically analyze the parameters of the ERKI protocol to minimize its execution time.Extensive numerical results show that ERKI can accelerate the execution time by more than 2.14compared with state-of-the-art solutions.

Prototyping low-cost automatic weather stations for natural disaster monitoring

Weather events put human lives at risk mostly when people might occupy areas susceptible to natural disasters.Deploying Professional Weather Stations(PWS)in vulnerable areas is key for monitoring weather with reliable measurements.However,such professional instrumentation is notably expensive while remote sensing from a number of stations is paramount.This imposes challenges on the large-scale weather station deployment for broad monitoring from large observation networks such as in Cemaden—The Brazilian National Center for Monitoring and Early Warning of Natural Disasters.In this context,in this paper,we propose a Low-Cost Automatic Weather Station(LCAWS)system developed from Commercial Off-The-Shelf(COTS)and open-source Internet of Things(IoT)technologies,which provides measurements as reliable as a reference PWS for natural disaster monitoring.When being automatic,LCAWS is a stand-alone photovoltaic system connected wirelessly to the Internet in order to provide real-time reliable end-to-end weather measurements.To achieve data reliability,we propose an intelligent sensor calibration method to correct measures.From a 30-day uninterrupted observation with sampling in minute resolution,we show that the calibrated LCAWS sensors have no statistically significant differences from the PWS measurements.As such,LCAWS has opened opportunities for reducing maintenance costs in Cemaden's observational network.

Mobilizing the seed storage oil in milk thistle (Silybum marianum) can supply energy for seed germination and early seedling growth and apply as TAGs breakdown marker

Milk thistle(Silybum marianum)is a crucial medicinal plant containing a large amount of oil.In the study,the changes in storage oil during seed germination and seedling transition from heterotrophic phases were investigated.The results showed that seed oil decreased from 19.53%to 0.88%on the 7th day of seedling development.Oil hydrolysis continued until the 4th day of germination with a low slope,but then increased the use of oils in seed germination end seedling growth metabolism.The results indicated that the quantitative changes in fatty acids,presented at lower amount,were relatively higher than dominant fatty acids.There were decreasing phenolic content in the developing seedlings,but overall,lowest level of total phenolic content can be attributed to the control(30.52 mg⋅100 g⋅Oil^(-1)).In contrast,the maximum peroxide value(2.58 meq⋅kg Oil^(-1))in the developing seedling was observed on the last day of the experiment.The results showed that there was a significant correlation between saturated fatty acid,unsaturated fatty acid,and lipase activity.However,the correlation between lipase activity and polyunsaturated fatty acids was significantly higher than between lipase activity and monounsaturated fatty acids(R^(2)=90%and R^(2)=77%,respectively).Therefore,the lipolysis process acts selectively in milk thistle oils.According to the results,C12:0 exhibits a greater impact on the early seedling growth rather than on the germination process and is one of the determining factors in the transition from heterotroph to autotroph.Also,it can be a marker for TAGs breakdown.