Derivative Spectroscopy and its Application at Detecting the Weak Emission/Absorption Lines

The development of spectroscopic survey telescopes like Large Sky Area Multi-Object Fiber Spectroscopic Telescope(LAMOST),Apache Point Observatory Galactic Evolution Experiment and Sloan Digital Sky Survey has opened up unprecedented opportunities for stellar classification.Specific types of stars,such as early-type emission-line stars and those with stellar winds,can be distinguished by the profiles of their spectral lines.In this paper,we introduce a method based on derivative spectroscopy(DS)designed to detect signals within complex backgrounds and provide a preliminary estimation of curve profiles.This method exhibits a unique advantage in identifying weak signals and unusual spectral line profiles when compared to other popular line detection methods.We validated our approach using synthesis spectra,demonstrating that DS can detect emission signals three times fainter than Gaussian fitting.Furthermore,we applied our method to 579,680 co-added spectra from LAMOST Medium-Resolution Spectroscopic Survey,identifying 16,629 spectra with emission peaks around the Hαline from 10,963 stars.These spectra were classified into three distinct morphological groups,resulting in nine subclasses as follows.(1)Emission peak above the pseudo-continuum line(single peak,double peaks,emission peak situated within an absorption line,P Cygni profile,Inverse P Cygni profile);(2)Emission peak below the pseudo-continuum line(sharp emission peak,double absorption peaks,emission peak shifted to one side of the absorption line);(3)Emission peak between the pseudo-continuum line.

Multi-circular formation control with reinforced transient profiles for nonholonomic vehicles:A path-following framework

This article investigates a multi-circular path-following formation control with reinforced transient profiles for nonholonomic vehicles connected by a digraph.A multi-circular formation controller endowed with the feature of spatial-temporal decoupling is devised for a group of vehicles guided by a virtual leader evolving along an implicit path,which allows for a circumnavigation on multiple circles with an anticipant angular spacing.In addition,notice that it typically imposes a stringent time constraint on time-sensitive enclosing scenarios,hence an improved prescribed performance control(IPPC)using novel tighter behavior boundaries is presented to enhance transient capabilities with an ensured appointed-time convergence free from any overshoots.The significant merits are that coordinated circumnavigation along different circles can be realized via executing geometric and dynamic assignments independently with modified transient profiles.Furthermore,all variables existing in the entire system are analyzed to be convergent.Simulation and experimental results are provided to validate the utility of suggested solution.

Evaluation of red soil-bentonite mixtures for compacted clay liners

Compacted clay liners are an integral part of the waste landfills,which are provided to contain the leachate within the landfills and protect the surrounding environment.Generally,locally available natural soils are used for the construction of compacted clay liners if they satisfy the design criteria.However,not all soils in their natural state satisfy all the design criteria for the liner materials.Thus,there is a definite need to modify the locally available natural soils by blending with bentonite to meet the required design criteria for the liners.In view of this,the present study evaluates the suitability of an Indian red soil enhanced with bentonite as a liner material.To achieve this,a series of experiments were carried out using locally available red soil and bentonite.First,the suitability of the red soil was evaluated as a liner material.The experimental results showed that the red soil met all the selection criteria stipulated by the Environmental Protection Agencies(EPAs)for the liners except the hydraulic conductivity criterion.Therefore,the red soil was mixed with bentonite contents of 10%,20%and 30%,and the red soil-bentonite mixtures were evaluated for their suitability for liners in their compacted state.Further,as the liners in the arid and semi-arid regions are subjected to moisture variations due to seasonal moisture fluctuations and other factors,the red soil-bentonite mixtures were subjected to wetdry cycles,and their suitability was evaluated after wet-dry cycles.The experimental results revealed that all the red soil-bentonite mixtures met the stipulated EPA criteria for the liners in the as-compacted state.However,the red soil-bentonite mixtures with 20%and 30%bentonite contents only satisfied the hydraulic conductivity requirement even after wet-dry cycles.The experimental findings were supplemented with the microstructural insights captured through digital camera images,scanning electron microscopy(SEM),and mercury intrusion porosimetry(MIP)studies.

ST-LaneNet: Lane Line Detection Method Based on Swin Transformer and LaneNet

The advancement of autonomous driving heavily relies on the ability to accurate lane lines detection.As deep learning and computer vision technologies evolve,a variety of deep learning-based methods for lane line detection have been proposed by researchers in the field.However,owing to the simple appearance of lane lines and the lack of distinctive features,it is easy for other objects with similar local appearances to interfere with the process of detecting lane lines.The precision of lane line detection is limited by the unpredictable quantity and diversity of lane lines.To address the aforementioned challenges,we propose a novel deep learning approach for lane line detection.This method leverages the Swin Transformer in conjunction with LaneNet(called ST-LaneNet).The experience results showed that the true positive detection rate can reach 97.53%for easy lanes and 96.83%for difficult lanes(such as scenes with severe occlusion and extreme lighting conditions),which can better accomplish the objective of detecting lane lines.In 1000 detection samples,the average detection accuracy can reach 97.83%,the average inference time per image can reach 17.8 ms,and the average number of frames per second can reach 64.8 Hz.The programming scripts and associated models for this project can be accessed openly at the following GitHub repository:https://github.com/Duane 711/Lane-line-detec tion-ST-LaneNet.

An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

Profiles of the Headspace Volatile Organic and Essential Oil Compounds from the Tunisian Cardaria draba (L.) Desv. and Its Leaf and Stem Epidermal Micromorphology

In this work, we investigated aroma volatiles emanated by dry roots, stems, leaves, flowers, and fruits of Cardariadraba (L.) Desv. growing wild in Tunisia and its aerial part essential oils (EOs) composition. A total of 37 volatileorganic compounds (96.7%–98.9%) were identified;4 esters, 4 alcohols, 7 hydrocarbons, 12 aldehydes, 5 ketones,1 lactone, 1 organosulfur compound, 2 organonitrogen compounds, and 1 acid. The hydrocarbons form the maingroup, representing 49.5%–84.6% of the total detected volatiles. The main constituent was 2,2,4,6,6-pentamethylheptane(44.5%–76.2%) reaching the highest relative percentages. Forty-two compounds were determined in thetwo fractions of EOs, representing 98.8% and 97.2% of the total oil composition, respectively. The principal componentswere hexadecanoic acid (34.6%), 6-methyl-5-hepten-2-one (18.3%), decanal (15.0%), 6,10,14-trimethyl-2-pentadecanone (13.2%), and n-pentacosane (13%). Micromorphological details of the leaf and stem epidermisusing light microscopy revealed polygonal cells with sinuous walls in the adaxial and abaxial leaf surfaces andnearly rectangular and long ones with linear and thick walls for the stem epidermis. The stomata complexes wereanisocytic in the leaf epidermis and mainly anisocytic and rarely paracytic in the stem epidermis. Non-glandulartrichomes were unbranched and long with an acute apex or short with a convex apex. The glandular ones wereidentified for the first time in this species. They were short-stalked with a large secretory head. The highest stomatalindex (17.02%) was recorded in the abaxial leaf surface. The identification of headspace volatiles and essentialoil compounds can be used to characterize this species, and the various epidermis micromorphologicalfeatures are very useful for biosystematics taxonomic studies within Brassicaceae.

Radical Hysterectomy in Cervical Cancer: Patients’ Epidemiological and Clinical Profiles and Perioperative Outcome in Two Referral Hospitals in Cameroon

Background: Cervical cancer (CC) is one of the most frequent cancers and the leading cause of death from gynecological cancer in Low and middle income countries, Cameroon inclusive. Surgery is the primary treatment modality when the disease is diagnosed at early stage. Radical hysterectomy in cervical cancer has not been evaluated in recent years in Cameroon. The purpose of this study is thus to evaluate the epidemiological and clinical features and short term outcomes of patients who underwent surgery. Patients and methods: This retrospective study was conducted at the Douala Gynaeco-obstetric and Pediatric Hospital and the Douala General Hospital. Cervical cancer patients who underwent Radical hysterectomy between January 2015 and December 2020 were included. A pre-established data collection tool was used to record socio-demographic, clinical and outcomes information from patients’ files;additional outcome information was obtained from phone calls. Descriptive analysis was done using the SPSS version 26. Bivariate analysis was used to determine associations between disease and patients characteristics and occurrence of adverse postoperative outcome. P value of 0.05 was considered. Results: Sixty one patients were enrolled. Their ages ranged from 33 to 74 years with a mean age of 51.95 ± 10.29 years. Over 85% of women were married, 65.57% were unemployed and 86.88% were multiparous. Only 28% had never done cervical cancer screening. Most patients had stage IB1 to IB2 stage disease (57.1%). Less than 9% underwent radical hysterectomy and 8 of those (13.11%) suffered intraoperative complications. Twenty-five patients (40.98%) presented immediate and short term complications. There was no significant association between the disease or patients’ characteristics and adverse outcomes. Conclusion: Cervical cancer patients are relatively young in our settings and only 9% of them reach the hospital at early stage. Postoperative adverse outcomes rate is higher than that reported in the literature. Sensitization on screening and awareness of early symptoms can reverse the situation.

Metabolic profiles and morphological characteristics of leaf tips among different sweet potato(Ipomoea batatas Lam.)varieties

Sweet potato leaf tips have high nutritional value,and exploring the differences in the metabolic profiles of leaf tips among different sweet potato varieties can provide information to improve their qualities.In this study,a UPLC-Q-Exactive Orbitrap/MS-based untargeted metabolomics method was used to evaluate the metabolites in leaf tips of 32 sweet potato varieties.Three varieties with distinct overall metabolic profiles(A01,A02,and A03),two varieties with distinct profiles of phenolic acids(A20 and A18),and three varieties with distinct profiles of flavonoids(A05,A12,and A16)were identified.In addition,a total of 163 and 29 differentially expressed metabolites correlated with the color and leaf shape of sweet potato leaf tips,respectively,were identified through morphological characterization.Group comparison analysis of the phenotypic traits and a metabolite-phenotypic trait correlation analysis indicated that the color differences of sweet potato leaf tips were markedly associated with flavonoids.Also,the level of polyphenols was correlated with the leaf shape of sweet potato leaf tips,with lobed leaf types having higher levels of polyphenols than the entire leaf types.The findings on the metabolic profiles and differentially expressed metabolites associated with the morphology of sweet potato leaf tips can provide useful information for breeding sweet potato varieties with higher nutritional value.

Learning Epipolar Line Window Attention for Stereo Image Super-Resolution Reconstruction

Transformer-based stereo image super-resolution reconstruction(Stereo SR)methods have significantly improved image quality.However,existing methods have deficiencies in paying attention to detailed features and do not consider the offset of pixels along the epipolar lines in complementary views when integrating stereo information.To address these challenges,this paper introduces a novel epipolar line window attention stereo image super-resolution network(EWASSR).For detail feature restoration,we design a feature extractor based on Transformer and convolutional neural network(CNN),which consists of(shifted)window-based self-attention((S)W-MSA)and feature distillation and enhancement blocks(FDEB).This combination effectively solves the problem of global image perception and local feature attention and captures more discriminative high-frequency features of the image.Furthermore,to address the problem of offset of complementary pixels in stereo images,we propose an epipolar line window attention(EWA)mechanism,which divides windows along the epipolar direction to promote efficient matching of shifted pixels,even in pixel smooth areas.More accurate pixel matching can be achieved using adjacent pixels in the window as a reference.Extensive experiments demonstrate that our EWASSR can reconstruct more realistic detailed features.Comparative quantitative results show that in the experimental results of our EWASSR on the Middlebury and Flickr1024 data sets for 2×SR,compared with the recent network,the Peak signal-to-noise ratio(PSNR)increased by 0.37 dB and 0.34 dB,respectively.

A Simple and Effective Surface Defect Detection Method of Power Line Insulators for Difficult Small Objects

Insulator defect detection plays a vital role in maintaining the secure operation of power systems.To address the issues of the difficulty of detecting small objects and missing objects due to the small scale,variable scale,and fuzzy edge morphology of insulator defects,we construct an insulator dataset with 1600 samples containing flashovers and breakages.Then a simple and effective surface defect detection method of power line insulators for difficult small objects is proposed.Firstly,a high-resolution featuremap is introduced and a small object prediction layer is added so that the model can detect tiny objects.Secondly,a simplified adaptive spatial feature fusion(SASFF)module is introduced to perform cross-scale spatial fusion to improve adaptability to variable multi-scale features.Finally,we propose an enhanced deformable attention mechanism(EDAM)module.By integrating a gating activation function,the model is further inspired to learn a small number of critical sampling points near reference points.And the module can improve the perception of object morphology.The experimental results indicate that concerning the dataset of flashover and breakage defects,this method improves the performance of YOLOv5,YOLOv7,and YOLOv8.In practical application,it can simply and effectively improve the precision of power line insulator defect detection and reduce missing detection for difficult small objects.

AMachine Learning Approach to User Profiling for Data Annotation of Online Behavior

The user’s intent to seek online information has been an active area of research in user profiling.User profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and motivations.Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation.The user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social platforms.However,a combination of multiple behaviors in profiling users has yet to be considered.This research takes a novel approach and explores user intent types based on multidimensional online behavior in information acquisition.This research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine learning.The research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data annotation.User feedback is based on online behavior and practices collected by using a survey method.The participants include both males and females from different occupation sectors and different ages.The data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their characteristics.Different techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of 1136.Feature average is computed to identify user intent type characteristics.The user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on their preferences in online content,platforms,criteria,and frequency.The study also validates the proposed template on user feedback data through Inter-Rater Agreement process using an external human rater.

Rigidity Symmetry Line for Thermodynamic Fluid Equations-of-State

We report progress towards a modern scientific description of thermodynamic properties of fluids following the discovery (in 2012) of a coexisting critical density hiatus and a supercritical mesophase defined by percolation transitions. The state functions density ρ(p,T), and Gibbs energy G(p,T), of fluids, e.g. CO2, H2O and argon exhibit a symmetry characterised by the rigidity, ω = (dp/dρ)T, between gaseous and liquid states along any isotherm from critical (Tc) to Boyle (TB) temperatures, on either side of the supercritical mesophase. Here, using experimental data for fluid argon, we investigate the low-density cluster physics description of an ideal dilute gas that obeys Dalton’s partial pressure law. Cluster expansions in powers of density relate to a supercritical liquid-phase rigidity symmetry (RS) line (ω = ρrs(T) = RT) to gas phase virial coefficients. We show that it is continuous in all derivatives, linear within stable fluid phase, and relates analytically to the Boyle-work line (BW) (w = (p/ρ)T = RT), and to percolation lines of gas (PB) and liquid (PA) phases by: ρBW(T) = 2ρPA(T) = 3ρPB(T) = 3ρRS(T)/2 for T TB. These simple relationships arise, because the higher virial coefficients (bn, n ≥ 4) cancel due to clustering equilibria, or become negligible at all temperatures (0 T TB) within the gas phase. The Boyle-work line (p/ρBW)T is related exactly at lower densities as T → TB, and accurately for liquid densities, by ρBW(T) = −(b2/b3)T. The RS line, ω(T) = RT, defines a new liquid-density ground-state physical constant (ρRS(0) = (2/3)ρBW(0) for argon). Given the gas-liquid rigidity symmetry, the entire thermodynamic state functions below TB are obtainable from b2(T). A BW-line ground-state crystal density ρBW(0) can be defined by the pair potential minimum. The Ar2 pair potential, ∅ij(rij) determines b2(T) analytically for all T. This report, therefore, advances the salient objective of liquid-state theory: an argon p(ρ,T) Equation-of-state is obtained from ∅ij(rij) for all fluid states, without any adjustable parameters.

Digital Twin Modeling and Simulation Optimization of Transmission Front and Middle Case Assembly Line

As the take-off of China’s macro economy,as well as the rapid development of infrastructure construction,real estate industry,and highway logistics transportation industry,the demand for heavy vehicles is increasing rapidly,the competition is becoming increasingly fierce,and the digital transformation of the production line is imminent.As one of themost important components of heavy vehicles,the transmission front andmiddle case assembly lines have a high degree of automation,which can be used as a pilot for the digital transformation of production.To ensure the visualization of digital twins(DT),consistent control logic,and real-time data interaction,this paper proposes an experimental digital twin modeling method for the transmission front and middle case assembly line.Firstly,theDT-based systemarchitecture is designed,and theDT model is created by constructing the visualization model,logic model,and data model of the assembly line.Then,a simulation experiment is carried out in a virtual space to analyze the existing problems in the current assembly line.Eventually,some improvement strategies are proposed and the effectiveness is verified by a new simulation experiment.

Research on Transmission Line Tower Tilting and Foundation State Monitoring Technology Based onMulti-Sensor Cooperative Detection and Correction

The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission.The tower’s tilt and severe deformation will cause the building to collapse.Many small changes caused the tower’s collapse,but the early staff often could not intuitively notice the changes in the tower’s state.In the current tower online monitoring system,terminal equipment often needs to replace batteries frequently due to premature exhaustion of power.According to the need for real-time measurement of power line tower,this research designed a real-time monitoring device monitoring the transmission tower attitude tilting and foundation state based on the inertial sensor,the acceleration of 3 axis inertial sensor and angular velocity raw data to pole average filtering pre-processing,and then through the complementary filtering algorithm for comprehensive calculation of tilt angle,the system meets the demand for inclined online monitoring of power line poles and towers regarding measurement accuracy,with low cost and power consumption.The optimization multi-sensor cooperative detection and correction measured tilt angle result relative accuracy can reach 1.03%,which has specific promotion and application value since the system has the advantages of unattended and efficient calculation.

Simulation and Experimental Study of Staple Line Reinforcement Surgery

The aim of this study was to evaluate the effectiveness of BM (basement membrane) and SIS (small intestine submucosa) composite extracellular matrix staple line reinforcement in surgical procedures through finite element modelling simulations and leak-proof performance experiments. The mechanical analyses of soft tissues with and without staple line reinforcement were performed by establishing finite element models of three tissues, namely, stomach, intestine and lungs, under the use scenarios of different anastomosis staple models;and the leak-proof performance of the staple line reinforcement was evaluated by simulating leak-proof experiments of gastric incision margins, intestinal sections, and lung incision margins in vitro. The results showed that the equivalent average stresses of the staple line reinforcement were increased by 20 kPa-68 kPa in gastric and intestinal tissues, and 8 kPa-22 kPa in lung tissues. and that the BM and SIS composite extracellular matrix staple line reinforcement could strengthen the anastomotic structure, and at the same time disperse the high stresses of the anastomosed tissues, which could effectively reduce the postoperative complications such as anastomotic bleeding and anastomotic leakage, and provide a safer and more effective optimized design for surgical mechanical anastomosis. It can effectively reduce postoperative complications such as anastomotic bleeding and anastomotic leakage, and provide a safer and more effective optimized design for surgical mechanical anastomosis.

N^(6)-腺苷甲基化修饰及其对LINE-1的调控机制

长散布元件-1(long interspersed elements-1,LINE-1)是现今在人类基因组中唯一具有自主转座能力的转座子,其转座会引起细胞基因组结构和功能的改变,是导致多种严重疾病的重要因素。在转座过程中,LINE-1 mRNA是转座中间体的核心,宿主细胞对其进行相关修饰直接影响转座。N^(6)-腺苷甲基化修饰(m^(6)A)是真核细胞RNA上最丰富且动态可逆的表观遗传修饰。目前发现m^(6)A修饰也存在于LINE-1 mRNA上,参与LINE-1整个生命周期的调控,影响其转座和基因组中LINE-1相邻基因的表达,进而影响基因组稳定性、细胞自我更新与分化潜能,在人类发育和疾病中具有重要作用。本文介绍了LINE-1 m^(6)A修饰的位置、功能以及相关机制,并总结了LINE-1的m^(6)A修饰对其转座调控的研究进展,以期为相关疾病发生发展的机制研究和治疗提供新的思路。

Multi-Branch Fault Line Location Method Based on Time Difference Matrix Fitting

The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.

Analysis of the Design and Application of a Novel CT Secondary Cable Line Calibrator

With the rapid development of electrical power systems,ensuring the accuracy and reliability of power transmis-sion has become particularly crucial.The secondary cable line calibrator for current transformers(CT)plays an essential role in calibrating electrical power systems.It is not only related to the safe operation of the system but also directly im-pacts the accuracy of energy metering.This study aims to design and analyze an efficient CT secondary cable line calibra-tor to explore its application effects in the power system.By thoroughly analyzing the characteristics of CT secondary ca-ble lines and the design requirements of the calibrator,this paper proposes an innovative design scheme for the calibrator.This device demonstrates significant effects in enhancing the accuracy and stability of power system calibration,providing robust technical support for the optimization and upgrade of the power system.This research not only offers a theoretical basis and practical guidance for the design and application of CT secondary cable line calibrators but also contributes new ideas and methods for the precise calibration and efficient management of the power system.

Online-SPE-UPLC-MS/MS检测生活污水中20种毒品

对生活污水的前处理进行优化,建立了一种在线固相萃取-超高效液相色谱-串联质谱法(Online-SPE-UPLC-MS/MS)同时测定污水中20种毒品及人口标记物的方法。用金属螯合剂Na_(2)EDTA·2H_(2)O处理污水后加入同位素内标,接着用滤膜过滤后,以双柱交替模式上样。用Waters Oasis HLB固相萃取柱(2.1 mm×30 mm,20μm)进行富集浓缩后,用流动相将固相萃取柱上吸附的目标物反冲洗到Waters ACQUITY UPLC HSS T3色谱柱(2.1 mm×100 mm,1.8μm)上。柱温40℃,以乙腈-0.1%(体积分数)甲酸水溶液为流动相,采用梯度程序洗脱。采用电喷雾离子源正离子、多反应监测(MRM)模式定量检测。可替宁的线性范围在20~5000 ng·L^(-1),其余20种物质的线性范围在1~250 ng·L^(-1)之间,相关系数R2均大于0.99,检出限在0.01~0.25 ng·L^(-1)之间,加标回收率在91.57%~113.94%,精密度均小于15%。基于Online-SPE-UPLC-MS/MS建立了同时测定污水中20种毒品及人口标记物方法,该方法操作简单、灵敏高,具有良好的准确度和精密度,已成功应用于城市污水中的毒品检测,用于监测毒品滥用情况。

Nonparametric Control Scheme for Monitoring Phase Ⅱ Nonlinear Profiles with Varied Argument Values

Profile monitoring is used to check the stability of the quality of a product over time when the product quality is best represented by a function at each time point.However,most previous monitoring approaches have not considered that the argument values may vary from profile to profile,which is common in practice.A novel nonparametric control scheme based on profile error is proposed for monitoring nonlinear profiles with varied argument values.The proposed scheme uses the metrics of profile error as the statistics to construct the control charts.More details about the design of this nonparametric scheme are also discussed.The monitoring performance of the combined control scheme is compared with that of alternative nonparametric methods via simulation.Simulation studies show that the combined scheme is effective in detecting parameter error and is sensitive to small shifts in the process.In addition,due to the properties of the charting statistics,the out-of-control signal can provide diagnostic information for the users.Finally,the implementation steps of the proposed monitoring scheme are given and applied for monitoring the blade manufacturing process.With the application in blade manufacturing of aircraft engines,the proposed nonparametric control scheme is effective,interpretable,and easy to apply.