Parallel Samples Research Articles

A distributed surrogate system assisted differential evolutionary algorithm for computationally expensive history matching problems

Recently, surrogate assisted evolutionary algorithms (SAEAs) are widely studied and applied for history matching problems due to surrogate models can accelerate convergence. However, most of the SAEAs lose the ability of parallel sampling due to the introduction of surrogate models, in which, a small number of potential solutions are selected for evaluation in each iteration. Generally, history matching involves a large number of numerical simulations, and the role of parallel computing cannot be ignored. To address this issue, this paper proposes a distributed surrogate system assisted differential evolution algorithm, termed DSS-DE. A distributed surrogate system (DSS) based on ensemble learning techniques is first developed, which builds a large number of basic learners before optimization, to effectively approximate different regions in the search space. Following that, performing multiple differential evolution (DE) optimizers with different mutation operators concurrently to sample a set of solutions to find as many as possible local or global optima of the data mismatch objective function. Moreover, based on the DSS prediction, a parallel infill strategy is designed to screen the potential promising solutions. Combined with the convolutional variational autoencoder (CVAE) based parameterization technique, a history matching workflow is developed. Empirical studies on two multimodal benchmark functions demonstrate that the proposed algorithm can obtain high-quality solutions on a limited computational budget. Furthermore, the proposed history matching workflow is validated on three synthetic waterflooding reservoir case studies with different geological characteristics. The test results show that the effectiveness of the proposed algorithm for history matching problems.

Does the Two-Child Policy Affect the Consumption Upgrade of “Two-Child Families”: Based on CFPS Data from the Chinese Family Tracking Survey

Purpose – In the context of the continued low consumption rate of Chinese residents, the increasingly aged society in China, and the decline in the birth rate, the Chinese government has gradually liberalized the fertility policy. The twochild policy has undergone policy adjustments from “only child of both parties” in 2011 to “only child of one party” in 2014, and then to the “Universal” policy in 2016, which marked the complete end of the “one-child policy” implemented since the 1970s. The purpose of this paper is to assess the effect of the “two-child birth policy” on the consumption upgrading of urban households, and to explore the mechanism of the effect. Design/Methodology/Approach – Through the quasi-natural experiment of the “two-child policy”, empirical analysis is carried out using the panel data of the China Family Tracking Survey (CFPS) database from 2012-2018. In order to improve sample selection bias and endogenous problems as much as possible, double-difference (PSM-DID) methods based on propensity score matches were adopted to construct the experimental and control groups to empirically test the impact of the second-child policy. A robustness test was carried out through methods such as parallel trend tests and sample size reduction. Further heterogeneity analysis of the policy action mechanism was conducted using the triple difference method (DDD). Findings – (1) In general, the “two-child policy” has promoted the upgrading of household consumption levels and consumption structures. (2) Furthermore, research findings of a triple difference (DDD) model were that the effect of fertility policy between household consumption levels and consumption structure was different across target households with different levels of household wealth. That is, the higher the wealth level of the household, the more the fertility policy promoted an increase in household consumption and an upgrade of the consumption structure, but for education consumption expenditure, regardless of household wealth level, the fertility policy promoted a significant increase in household consumption expenditure and had a “crowding out effect” on other developmental hedonic consumption of the household, and the lower the wealth level, the more pronounced the crowding-out effect. Research Implications – This paper studies the consumption of urban residents from the perspective of the characteristics of family population structure. It uses Chinese empirical data to test the applicability of relevant consumption theories in China, and provides perfect unique sample data for the academic community. By exploring the mechanism of the impact of the fertility policy on the consumption level and structure of residents, it can provide a reference for evaluating past population and economic policies. However, it provides a theoretical basis and guidance for the formulation of population and economic policies in the future, and the implementation of supporting policies for the “Three-Child Policy”.

Accelerated Asymmetric Reaction Screening with Optical Assays

AbstractAsymmetric reaction development often involves optimization of several mutually dependent parameters that affect the product yield and enantiomeric excess. Widely available high-throughput experimentation equipment and optical sensing assays can drastically streamline comprehensive optimization efforts and speed up the discovery process at reduced cost, workload, and waste production. A variety of chiroptical assays that utilize fluorescence, UV, and circular dichroism measurements to determine reaction yields and ee values are now available, enabling the screening of numerous small-scale reaction samples in parallel with multi-well plate technology. Many of these optical methods considerably shorten work-up protocols typically required for traditional asymmetric reaction analysis and some can be directly applied to crude mixtures thus eliminating cumbersome separation and purification steps altogether.1 Introduction2 Fluorescence Assays3 UV Sensing Methods4 Sensing with Circular Dichroism Probes5 Hybrid Approaches6 Optical Analysis with Intrinsically CD-Active Reaction Products7 Conclusion

Research on 3D Rendering Effect of Marine Bionic Packaging Container Based on Deep Learning and Visualization

Three-dimensional rendering includes the test of system development environment and running environment. Three-dimensional rendering influencing factors test: the number and size of parallel blocks affect the average rendering frame rate of 26.9 when the number is 9600 and the size is 10 × 10, and the average rendering frame rate is 13.7 when the number is 600 and the size is 40 × 40. According to relevant data, it is inferred that the average rendering frame rate is higher when the number of parallel blocks is large and the size of parallel blocks is small, and the number is inversely proportional to the size. The rendering window size also has a relative influence on the rendering frame rate. When the window size is 600 × 400, only the terrain frame rate is 77.3, and when the window size is 1200 × 800, the frame rate is 68.1, which shows that when only the terrain frame rate is rendered, the frame rate decreases with the increase in the window size, and its performance is not high when only CPU is used. However, when CPU is combined with GPU, the performance is greatly improved, reaching the highest of 29.3 and the lowest of 21.5, which is much higher than that when only CPU is used. According to the influence of the number of sampling points on the frame rate, the 5 × 5 sampling method and 2 × 2 sampling method proposed in this paper have better frame rate performance than the traditional template shadow method. Through the above data, we know that the number of parallel blocks, size, window size, sampling method, and other factors have a certain impact on the average rendering frame rate. Marine bionics is a marginal subject between marine biology and technical engineering science. Deep networks have had a huge impact on the field of machine learning research and application, but at the same time, they cannot clearly explain the ins and outs of deep networks. People have been working to understand the complex process more thoroughly. Since humans’ cognition and experience of the world mainly come from vision, good visualization can effectively help people understand the deep network and perform effective optimization and adjustment.

Physicochemical Properties of Dentine Subjected to Microabrasive Blasting and Its Influence on Bonding to Self-Adhesive Prosthetic Cement in Shear Bond Strength Test: An In Vitro Study.

The aim of this in vitro study was to assess the influence of microabrasive blasting on the physicochemical properties of dentine and shear bond strength (SBS) of self-adhesive resin cement (Maxcem Elite, Kerr, Orange, CA, USA) bonded to the dentine surface. Ninety cylindrical specimens with exposed dentine of human teeth were prepared and divided into three randomized, parallel sample sets A, B, and C. Groups B and C were subjected to abrasive blasting using a micro-sandblasting device (Microetcher IIa, Danville Materials, Carlsbad, CA, USA) with two gradations of Al2O3 abrasives (Group B, abrasion with a gradation of 50 μm; group C, abrasion with a gradation of 27 μm). SEM imaging, profilometry, chemical composition analysis, contact angle measurements, surface free energy, and SBS tests were performed. The resulting data were statistically analyzed using the Statistica software (ver. 13.3, Tibco Software Inc., Palo Alto, CA, USA). Microabrasive blasting caused changes in surface topography, structural features, and the connection strength between the dentin surface and self-adhesive prosthetic cement. Air microabrasion through the multifactorial positive reorganization of the treated surface of dentine is recommended as a pretreatment method in fixed prosthodontics adhesive cementation protocols.

Fast and Easy Nanopore Sequencing Workflow for Rapid Genetic Testing of Familial Hypercholesterolemia.

Familial hypercholesterolemia (FH) is an autosomal dominant lipid metabolism disorder characterized by severely elevated plasma low-density lipoprotein cholesterol levels. The disease is caused by mutations in 3 genes (LDLR, APOB and PCSK9) while over 90% of the mutations are located within the LDLR gene. Thus, genetic analysis of the LDLR gene is the first step in the genetic diagnosis of FH. However, conventional methods like Sanger and NextGen sequencing are still costly and time-consuming. In contrast, Oxford Nanopore technology sequencing is an emerging third-generation sequencing technology featured by easy operability, low cost, small size and the capability of parallel sample sequencing. Here, we present an easy Nanopore-sequencing-based workflow for the rapid genetic testing of FH taking only 3 days and costing less than $50 per sample without the requirement for deep bioinformatic knowledge. Using our workflow, we were able to identify the underlying pathogenic variants of 10 FH patients including one novel, not yet recorded pathogenic variants. Our workflow allows the rapid evaluation of the pathogenic variants by utilizing detailed variant information from Ensembl. Additionally, our workflow is not restricted to sequencing the LDLR gene alone but can be easily adapted to the other FH-causing genes and more importantly, to any desired gene contributing to any hereditary disease. Therefore, our workflow is an attractive opportunity for every diagnostic laboratory to offer fast and easy in-house genetic diagnostics.

Investigation on the microscopic damage mechanism of fracturing fluids to low-permeability sandstone oil reservoir by nuclear magnetic resonance

Hydraulic fracturing has become an essential stimulation treatment for improving the development efficiency of low-permeability oil reservoirs. However, fracturing fluid inevitably causes reservoir damage. This study proposed a combined method of microscopic and macroscopic experiments to investigate the nature of formation damage of fracturing fluid by quantifying its influence on porosity, permeability, and pore structure. Nuclear magnetic resonance technology combined with core flooding test and parallel sample comparison method was applied to quantitatively evaluate the damage degree and identify the main damage types of hydroxypropyl guar (HPG) fracturing fluid and slickwater fracturing fluid. The microscopic damage mechanisms of these fracturing fluids were analyzed by thin section petrography, X-ray diffraction, rate-controlled mercury intrusion, scanning electron microscopy, and wettability tests. The results show that the total permeability damage degree of HPG fracturing fluid filtrate is 30.43%, of which water sensitivity, water lock, and macromolecule adsorption account for 6.06%, 23.26%, and 1.11%, respectively. Water lock is the major damage factor. Regarding the damage of slickwater fracturing fluid filtrate, water sensitivity causes the severest damage, corresponding to 39.08% of core permeability loss, whereas macromolecule adsorption and water lock contribute 13.21% and 0.97%, respectively. Water sensitivity damage causes reduced porosity, decreased permeability, and narrower pores, resulting from hydration, swelling, dispersion and migration of clay minerals. Water lock damage increases the movable pore volume, decreases the permeability, increases the pore radius, decreases the throat radius, and increases the pore throat ratio, which increases the flow resistance to the oil phase. The magnitude of water lock damage is closely related to the surfactant content and performance, rock wettability, and pore throat radius ratio. Macromolecule adsorption damage leads to a decrease in permeability, a reduction in the number of large pores, an increase in the number of small throats, and an increase in the pore throat radius ratio due to the absorption and retention of macromolecules on the surfaces of the pores and throats. Increasing the flowback volume of slickwater fracturing fluid can recover part of the macromolecule absorption damage. This research can provide a reliable reference for the optimization of fracturing fluid performance, enhancement of the fracturing effect and reservoir protection of low-permeability reservoirs.

Sub-Nyquist sampling system for pulse streams based on non-ideal filters

Recent developed finite rate of innovation (FRI) sampling framework provides an efficient way for sub-Nyquist sampling of pulse streams, which are widely applied to the fields of radar and wireless communication. Most researches of FRI sampling structure were implemented in hardware based on filter banks. However, the non-ideal effects of the filters would lead to low reconstruction accuracy. In this paper, we propose a two-channel sub-Nyquist sampling system for pulse streams, which significantly improves the reconstruction performance of the system under non-ideal filters hardware environment. The proposed scheme consists of two parallel sampling channels. The pulse streams and its basis signal are modulated and filtered with non-ideal low pass filters, followed by sampling at twice the cut-off frequency. By setting the cut-off frequency of the filter, the number of samples of different numbers is obtained, and the Fourier coefficients of the different frequency bands of these signals are obtained from the obtained samples. Such a technique allows for recovery of an arbitrary pulse with different frequency spectrum, which greatly improves the flexibility of the sampling system. Then we propose a joint parameters recovery algorithm to reconstruct the pulse streams, which can effectively eliminate non-ideal effects. Finally, we design a hardware prototype to verify the feasibility and effectiveness of the proposed system. Simulation and hardware experiments have shown that the proposed system greatly improves the signal reconstruction accuracy.

Shale Reservoir Heterogeneity: A Case Study of Organic-Rich Longmaxi Shale in Southern Sichuan, China

Shale reservoir heterogeneity is strong, which seriously affects shale gas reservoir evaluation and reserves estimation. The Longmaxi Formation shale of the Luzhou block in southern Sichuan was taken as an example to characterize the pore distribution of shale over the full scale using micro-computed tomography (CT), focusing on ion beam scanning electron microscopy (FIB-SEM) and small-angle neutron scattering (SANS); further, the heterogeneity of the shale pore distribution over the full scale was explored quantitatively within different scales. The results show that shale micropores are dominated by microfractures that are mainly developed along the bedding direction and associated with organic matter, contributing 1.24% of porosity. Shale nanopores are more developed, contributing 3.57–4.72% porosity and have strong heterogeneity locally at the microscale, but the pore distribution characteristics show lateral homogeneity and vertical heterogeneity at the macroscale. In the same layer, the porosity difference is only 0.1% for the sheet samples with 2 cm adjacent to each other. Therefore, in shale core experiments in which parallel samples are needed for comparison, parallel samples should be in the same bedding position. This paper explores the extent of heterogeneity over the full scale of pore distribution from macro to micro, which has important significance for accurately characterizing the pore distribution of shale and further carrying out reservoir evaluation and estimation of reserves.

Batch sequential adaptive designs for global optimization

Efficient global optimization (EGO) is one of the most popular sequential adaptive design (SAD) methods for expensive black-box optimization problems. A well-recognized weakness of the original EGO in complex computer experiments is that it is serial, and hence the modern parallel computing techniques cannot be utilized to speed up the running of simulator experiments. For those multiple points EGO methods, the heavy computation and points clustering are the obstacles. In this work, a novel batch SAD method, named “Accelerated EGO”, is forwarded by using a refined sampling/importance resampling (SIR) method to search the points with large expected improvement (EI) values. The computation burden of the new method is much lighter, and the points clustering is also avoided. The efficiency of the proposed batch SAD is validated by nine classic test functions with dimension from 2 to 12. The empirical results show that the proposed algorithm indeed can parallelize original EGO, and gain much improvement compared against the other parallel EGO algorithm especially under high-dimensional case. Additionally, the new method is applied to the hyper-parameter tuning of support vector machine (SVM) and XGBoost models in machine learning. Accelerated EGO obtains comparable cross validation accuracy with other methods and the CPU time can be reduced a lot due to the parallel computation and sampling method.

TCD-Net: A Novel Deep Learning Framework for Fully Polarimetric Change Detection Using Transfer Learning

Due to anthropogenic and natural activities, the land surface continuously changes over time. The accurate and timely detection of changes is greatly important for environmental monitoring, resource management and planning activities. In this study, a novel deep learning-based change detection algorithm is proposed for bi-temporal polarimetric synthetic aperture radar (PolSAR) imagery using a transfer learning (TL) method. In particular, this method has been designed to automatically extract changes by applying three main steps as follows: (1) pre-processing, (2) parallel pseudo-label training sample generation based on a pre-trained model and fuzzy c-means (FCM) clustering algorithm, and (3) classification. Moreover, a new end-to-end three-channel deep neural network, called TCD-Net, has been introduced in this study. TCD-Net can learn more strong and abstract representations for the spatial information of a certain pixel. In addition, by adding an adaptive multi-scale shallow block and an adaptive multi-scale residual block to the TCD-Net architecture, this model with much lower parameters is sensitive to objects of various sizes. Experimental results on two Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) bi-temporal datasets demonstrated the effectiveness of the proposed algorithm compared to other well-known methods with an overall accuracy of 96.71% and a kappa coefficient of 0.82.

Simultaneous detection of heavy metals in solutions by electrodeposition assisted laser induced breakdown spectroscopy

Detection of heavy metals in solutions has been performed using laser-induced breakdown spectroscopy (LIBS) combined with electrodeposition (ED). A polished aluminum (Al) sheet serves as the cathode in the three-electrode system. Four heavy metal ions were concentrated at the same time, namely, copper (Cu2+), cadmium (Cd2+), chromium (Cr3+), and nickel (Ni2+). The results of experiments demonstrated that it was more conducive to the enrichment of heavy metal elements when the pH of the solution was in the range of 6–8.5. The smoother the aluminum electrode was polished with the metallographic sandpaper, the better the uniformity of enrichment and the repeatability of the experiment. After optimizing the experimental conditions, the relative standard deviation (RSD) values of a laser single-shot of four polished aluminum electrodes were all below 20%. When the aluminum electrode was polished with 5000-mesh metallographic sandpaper, the RSD value between parallel samples was only 0.03%. The limits of detection of the elements are 4.86 μg/l for Cd2+, 2.17 μg/l for Cr3+, 2.44 μg/l for Cu2+, and 10.49 μg/l for Ni2+ after being concentrated in a mixed solution for 15 min, respectively. The results indicated that the LIBS technique coupled with ED could be a reliable and accurate method for the detection of heavy metals in solution.

Comparison of parallel infill sampling criteria based on Kriging surrogate model

One of the key issues that affect the optimization effect of the efficient global optimization (EGO) algorithm is to determine the infill sampling criterion. Therefore, this paper compares the common efficient parallel infill sampling criterion. In addition, the pseudo-expected improvement (EI) criterion is introduced to minimizing the predicted (MP) criterion and the probability of improvement (PI) criterion, which helps to improve the problem of MP criterion that is easy to fall into local optimum. An adaptive distance function is proposed, which is used to avoid the concentration problem of update points and also improves the global search ability of the infill sampling criterion. Seven test problems were used to evaluate these criteria to verify the effectiveness of these methods. The results show that the pseudo method is also applicable to PI and MP criteria. The DMP and PEI criteria are the most efficient and robust. The actual engineering optimization problems can more directly show the effects of these methods. So these criteria are applied to the inverse design of RAE2822 airfoil. The results show the criterion including the MP has higher optimization efficiency.

Atypical response to bacterial coinfection and persistent neutrophilic bronchoalveolar inflammation distinguish critical COVID-19 from influenza.

Neutrophils are recognized as important circulating effector cells in the pathophysiology of severe coronavirus disease 2019 (COVID-19). However, their role within the inflamed lungs is incompletely understood. Here, we collected bronchoalveolar lavage (BAL) fluids and parallel blood samples of critically ill COVID-19 patients requiring invasive mechanical ventilation and compared BAL fluid parameters with those of mechanically ventilated patients with influenza, as a non–COVID-19 viral pneumonia cohort. Compared with those of patients with influenza, BAL fluids of patients with COVID-19 contained increased numbers of hyperactivated degranulating neutrophils and elevated concentrations of the cytokines IL-1β, IL-1RA, IL-17A, TNF-α, and G-CSF; the chemokines CCL7, CXCL1, CXCL8, CXCL11, and CXCL12α; and the protease inhibitors elafin, secretory leukocyte protease inhibitor, and tissue inhibitor of metalloproteinases 1. In contrast, α-1 antitrypsin levels and net proteolytic activity were comparable in COVID-19 and influenza BAL fluids. During antibiotic treatment for bacterial coinfections, increased BAL fluid levels of several activating and chemotactic factors for monocytes, lymphocytes, and NK cells were detected in patients with COVID-19 whereas concentrations tended to decrease in patients with influenza, highlighting the persistent immunological response to coinfections in COVID-19. Finally, the high proteolytic activity in COVID-19 lungs suggests considering protease inhibitors as a treatment option.

Total Organic Carbon as a Quantitative Index of Micro- and Nano-Plastic Pollution.

The global pollution of micro- and nano-plastics (MNPs) calls for monitoring methods. As diverse mixtures of various sizes, morphologies, and chemical compositions in the environment, MNPs are currently quantified based on mass or number concentrations. Here, we show total organic carbon (TOC) as an index for quantifying the pollution of total MNPs in environmental waters. Two parallel water samples are respectively filtered with a carbon-free glass fiber membrane. Then, one membrane with the collected particulate substances is treated by potassium peroxodisulfate oxidation and Fenton digestion in sequence for quantifying the sum of MNPs and particulate black carbon (PBC) as TOCMNP&PBC using a TOC analyzer, another membrane is treated by sulfonation and Fenton digestion for quantifying PBC as TOCPBC, and the TOC of MNPs is calculated by subtracting TOCPBC from TOCMNP&PBC. The feasibility of our method is demonstrated by determination of various MNPs of representative plastic types and sizes (0.5-100 μm) in tap, river, and sea water samples, with low detection limits (∼7 μg C L-1) and high spiked recoveries (83.7-114%). TOC is a powerful index for routine monitoring of MNP pollution.

模拟计算平行样对流域生物信息流估算的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 模拟计算平行样对流域生物信息流估算的影响 DOI: 10.5846/stxb202104271109 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 农业农村部财政专项"长江渔业资源与环境调查"(CJDC-2017-14);中国水产科学研究院中央级公益性科研院所基本科研业务费专项(2020JBF01,2020TD08) Simulating the impacts of parallel samples on the estimations of upstream-to-downstream watershed biological information flow Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:流域生物信息流是流域生态学研究中的重要内容,是流域生态系统中的物质输移和能量输移过程的信息标记,是用eDNA技术调查评估河流水体中物种组成空间特征的基础。估算流域生物信息流是流域生态系统过程研究和eDNA技术调查评估河流水体中物种组成空间特征的关键。在有限的调查采样中,平行样的数量如何影响流域生物信息流的估算,尚待解答。基于随机抽样调查的基本原理,提出假设--采样数量不影响流域生物信息流估算结果的准确度,但会影响其精密度,然后通过问题简化转化和模拟计算,对该假设进行了检验。模拟计算结果显示,随着样点生物信息检出度(平行样数量)的增大,流域生物信息流估算结果会从偏小逐渐靠近流域生物信息流实际值,同时其99.9%置信区间也逐渐集中于流域生物信息流实际值。即样点生物信息检出度(平行样数量)对流域生物信息流估算的准确度和精密度均有影响。在实际调查研究过程中,建议先在所研究区域对平行样数量和样点生物信息检出度的关系进行预评估,然后基于流域生物信息流估算可信度目标在正式实施方案中经济有效地设置平行样,基于多平行样调查结果估算流域生物信息流,再根据各样点生物信息检出状况对流域生物信息流估算结果进行后验评估。 Abstract:Watershed biological information flow (WBIF) is defined as the path, processes and control of biological information transport, exchange, interaction and feedback among different spaces and systems along with watershed ecosystem processes, and could be partly described as the land-to-river and upstream-to-downstream bioinformation transportation (including organisms, nucleic acids, peptides and other biomarkers), which is driven by the hydrologic processes of watershed systems. The WBIF labels the transport of organic matter and energy. The WBIF integrates the ecological processes of environmental DNA (eDNA), including the origin, state, transport, and fate of eDNA, and makes it possible that the species composition in river system is monitored and assessed using eDNA. The WBIF estimation is the key for watershed ecosystem processes studying and riverine biodiversity monitoring. However, in practice, the parallel samples in each sampling site always are limited. And how parallel samples would impact WBIF estimation is unknown. Based on the principles of stochastic sampling survey, we hypothesized that parallel samples would not impact the accuracy of the WBIF estimation, but affect the precision of the WBIF estimation. Then, we transformed this hypothesis into a set of formulas and tested it with a series of analog computation. Results showed that the number of parallel samples (efficiency of detection) affected both the accuracy and precision of the WBIF estimation. The optimal WBIF estimation was less than the actual WBIF in any condition. Along with the increase of parallel samples (efficiency of detection), the optimal WBIF estimation gradually neared to the actual WBIF, the range of WBIF estimation gradually focused on the actual WBIF. In other words, more parallel samples (higher efficiency of detection) led higher accuracy and precision of the WBIF estimation. In addition, the actual WBIF affected both the accuracy and precision of the WBIF estimation too. Larger actual WBIF led higher accuracy and precision of the WBIF estimation. The relative relationship between the number of biological information types in upstream and downstream samples affected both the accuracy and precision of the WBIF estimation too. The accuracy and precision of WBIF estimation would be higher when the number of biological information types in upstream samples was more than those in downstream samples. So, we suggest that in the work of watershed ecosystem processes studying and riverine biodiversity monitoring, the relationship between parallel sample number and detection efficiency should be assessed, the suitable parallel sample number should be estimated based on the reliability target of WBIF estimation, the sampling program should be designed with suitable parallel samples, the WBIF should be estimated based on all parallel samples of each sampling site, at last the estimated results of WBIF should be re-evaluated according to the posterior probability of WBIF in different conditions. The current work provided the framework and methodology reference for the post-evaluation. 参考文献 相似文献 引证文献

An LC/MS/MS method for quantifying testosterone and dehydroepiandrosterone sulfate in four different serum samples during a single run.

Simultaneous measurements of the circulating testosterone (TS) and dehydroepiandrosterone sulfate (DHEAS) are deemed to be helpful for the assessment of men's health. Liquid chromatography/electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) is the most reliable methodology for this purpose; however, it has room for improvement in analysis throughput. In this study, a quadruplicate of the Girard reagents was used to develop an LC/ESI-MS/MS method capable of quantifying TS and DHEAS in four different serum samples in a single run. The four serum samples were separately pretreated, derivatized with one of four Girard reagents, and then combined. The LC/ESI-MS/MS analysis of the combined sample provided the androgen concentrations of four serum samples in parallel. The method had practical measuring ranges, in which good precision and accuracy, as well as negligible matrix effects were verified. The speed-up capability of the developed method was evaluated through the analysis of ten batches of serum samples (total 40 samples); the method saved a 60% post-pretreatment analysis time compared to the non-derivatization method for 40 samples.

Metabolically-incorporated deuterium in myelin localized by neutron diffraction and identified by mass spectrometry.

Myelin is a natural and dynamic multilamellar membrane structure that continues to be of significant biological and neurological interest, especially with respect to its biosynthesis and assembly during its normal formation, maintenance, and pathological breakdown. To explore the usefulness of neutron diffraction in the structural analysis of myelin, we investigated the use of in vivo labeling by metabolically incorporating non-toxic levels of deuterium (2H; D) via drinking water into a pregnant dam (D-dam) and her developing embryos. All of the mice were sacrificed when the pups (D-pups) were 55 days old. Myelinated sciatic nerves were dissected, fixed in glutaraldehyde and examined by neutron diffraction. Parallel samples that were unfixed (trigeminal nerves) were frozen for mass spectrometry (MS). The diffraction patterns of the nerves from deuterium-fed mice (D-mice) vs. the controls (H-mice) had major differences in the intensities of the Bragg peaks but no appreciable differences in myelin periodicity. Neutron scattering density profiles showed an appreciable increase in density at the center of the lipid-rich membrane bilayer. This increase was greater in D-pups than in D-dam, and its localization was consistent with deuteration of lipid hydrocarbon, which predominates over transmembrane protein in myelin. MS analysis of the lipids isolated from the trigeminal nerves demonstrated that in the pups the percentage of lipids that had one or more deuterium atoms was uniformly high across lipid species (97.6% ​± ​2.0%), whereas in the mother the lipids were substantially less deuterated (60.6% ​± ​26.4%) with levels varying among lipid species and subspecies. The mass distribution pattern of deuterium-containing isotopologues indicated the fraction (in %) of each lipid (sub-)species having one or more deuteriums incorporated: in the D-pups, the pattern was always bell-shaped, and the average number of D atoms ranged from a low of ∼4 in fatty acid to a high of ∼9 in cerebroside. By contrast, in D-dam most lipids had more complex, overlapping distributions that were weighted toward a lower average number of deuteriums, which ranged from a low of ∼3–4 in fatty acid and in one species of sulfatide to a high of 6–7 in cerebroside and sphingomyelin. The consistently high level of deuteration in D-pups can be attributed to their de novo lipogenesis during gestation and rapid, postnatal myelination. The widely varying levels of deuteration in D-dam, by contrast, likely depends on the relative metabolic stability of the particular lipid species during myelin maintenance. Our current findings demonstrate that stably-incorporated D label can be detected and localized using neutron diffraction in a complex tissue such as myelin; and moreover, that MS can be used to screen a broad range of deuterated lipid species to monitor differential rates of lipid turnover. In addition to helping to develop a comprehensive understanding of the de novo synthesis and turnover of specific lipids in normal and abnormal myelin, our results also suggest application to studies on myelin proteins (which constitute only 20–30% by dry mass of the myelin, vs. 70–80% for lipid), as well as more broadly to the molecular constituents of other biological tissues.

Determination of Oil Pollutants by Microchannel Laser Induced Fluorescence Technology

Laser-induced fluorescence technology is an effective method for detecting oil pollutants. The laser induced fluorescence detection system was developed, and four parallel microchannel sample pools were designed to improve the detection accuracy of fluorescence signals. The grating scanning system is improved by introducing grating feedback link to improve the wavelength scanning accuracy of the system.The experimental results show that the wavelength scanning resolution of the microchannel laser-induced fluorescence detection system is improved by 0.4 nm. Aiming at the defects of the traditional parallel factor algorithm which is sensitive to the sample components, slow operation speed and easy to fall into local convergence, the generalized inverse singular value decomposition is used to improve the parallel factor algorithm. Configure different concentrations of diesel, gasoline and kerosene solution samples. The experimental verification shows that the excitation-emission spectra of each component obtained by the improved parallel factor algorithm are highly consistent with the measured spectral characteristics, indicating that the microchannel laser-induced fluorescence detection system combined with the improved parallel factor analysis method can accurately identify oil pollutants.

基于精氨酸酶切的蛋白质C端肽段富集方法的优化及评估

基于聚合物的蛋白质C端反向富集策略是用于研究蛋白质C端最为广泛的策略之一。目前,基于胰蛋白酶(trypsin)切割精氨酸残基C端(ArgC型酶切)的蛋白C端组学方法对蛋白质C端的鉴定深度仍有待提高。为解决这一问题,该研究对此方法进行了优化和评估:建立了基于“V型”过滤装置的“一锅法”富集流程,避免了副反应的干扰,缩短了样本的制备时间;优化了蛋白水平乙酰化反应条件,最大限度地降低了丝氨酸、苏氨酸、酪氨酸残基上的副反应,提高了肽段鉴定的可信性;优化了基于固相萃取枪头膜片过滤柱(StageTip柱)的样品分离过程,使C端肽段的鉴定深度增加至原来的4倍。通过以上优化,按照肽段水平错误发现率(FDR)<0.01、离子分数(ion score)≥20,且C端带有乙醇胺修饰的数据筛选标准,从人HEK 293T细胞中共鉴定出696个蛋白质C端。若仅要求肽段水平FDR<0.01,鉴定数目进一步增加到933个,这是基于聚合物富集策略的蛋白质C端组学方法所得的最大数据集之一。探索了胰蛋白酶镜像酶(LysargiNase)切割精氨酸残基N端(ArgN型酶切)与不同肽段N端衍生化修饰组合对蛋白质C端鉴定数目和种类的影响,“LysargiNase酶切+肽段N端乙酰化”新策略在原有“胰蛋白酶酶切+肽段N端二甲基化”策略的基础上将鉴定蛋白质C端的种类提升了47%。综上,该研究通过对基于Arg型酶切的蛋白C端组学方法的优化,提升了C端肽段的鉴定深度,扩大了C端肽段鉴定的覆盖范围。该方法将有望成为系统性表征蛋白质C端的有力工具。