估计感度分布中位数的两阶段优化序贯试验设计方法研究

感度试验在爆炸科学领域有非常广泛的应用,其中位数是含能材料的一个关键性能指标.高效估计感度分布中位数是实际工程应用中的重要问题.文章提出一种两阶段的优化序贯试验设计方法来估计感度分布的中位数,并将正交设计与两阶段优化序贯试验设计方法相结合给出了筛选影响含能材料安定性重要因子的试验设计方法.广泛的模拟比较验证了所提方法在小样本情况下可以获得感度分布中位数的准确估计,并且对模型假设和初始参数猜测具有一定的稳健性.当因子效应不是太小的时候,因子筛选方法可以准确地筛选出有显著影响的因子.     

可用于连续识别Cu^2+和阴离子、中性分子荧光探针的研究进展

铜(Cu)含量的高低直接影响着生命体的正常运转和自然体系的平衡.检测铜离子的方法多种多样,其中具有较高敏感度和选择性的荧光化学传感器应用更加广泛.综述了以Cu^2+为基的荧光化学传感器通过"替换"法实现了对阴离子S^2-, CN^-, H2PO4^-, PPi和I^-以及中性分子ATP、ADP和生物硫醇等的连续识别的研究进展.     

Precise Synthesis and Thin Film Self-Assembly of PLLA-b-PS Bottlebrush Block Copolymers

The ability of bottlebrush block copolymers (BBCPs) to self-assemble into ordered large periodic structures could greatly expand the scope of photonic and membrane technologies. In this paper, we describe a two-step synthesis of poly(l-lactide)-b-polystyrene (PLLA-b-PS) BBCPs and their rapid thin-film self-assembly. PLLA chains were grown from exo-5-norbornene-2-methanol via ring-opening polymerization (ROP) of l-lactide to produce norbornene-terminated PLLA. Norbonene-terminated PS was prepared using anionic polymerization followed by a termination reaction with exo-5-norbornene-2-carbonyl chloride. PLLA-b-PS BBCPs were prepared from these two norbornenyl macromonomers by a one-pot sequential ring opening metathesis polymerization (ROMP). PLLA-b-PS BBCPs thin-films exhibited cylindrical and lamellar morphologies depending on the relative block volume fractions, with domain sizes of 46–58 nm and periodicities of 70–102 nm. Additionally, nanoporous templates were produced by the selective etching of PLLA blocks from ordered structures. The findings described in this work provide further insight into the controlled synthesis of BBCPs leading to various possible morphologies for applications requiring large periodicities. Moreover, the rapid thin film patterning strategy demonstrated (>5 min) highlights the advantages of using PLLA-b-PS BBCP materials beyond their linear BCP analogues in terms of both dimensions achievable and reduced processing time.     

An Approach to NMR Assignment of Intrinsically Disordered Proteins

An efficient approach to NMR assignments in intrinsically disordered proteins is presented, making use of the good dispersion of cross peaks observed in [¹⁵N,¹³C′]‐ and [¹³C′,¹H^N]‐correlation spectra. The method involves the simultaneous collection of {3D (H)NCO(CAN)H and 3D (HACA)CON(CA)HA} spectra for backbone assignments via sequential H^N and H^α correlations and {3D (H)NCO(CACS)HS and 3D (HS)CS(CA)CO(N)H} spectra for side‐chain ¹H and ¹³C assignments, employing sequential ¹H data acquisitions with direct detection of both the amide and aliphatic protons. The efficacy of the approach for obtaining resonance assignments with complete backbone and side‐chain chemical shifts is demonstrated experimentally for the 61‐residue [¹³C,¹⁵N]‐labelled peptide of a voltage‐gated potassium channel protein of the Kv1.4 channel subunit. The general applicability of the approach for the characterisation of moderately sized globular proteins is also demonstrated.     

Sequential paired covariance for improved visualization of mass spectrometry imaging datasets

Untargeted analyses in mass spectrometry imaging produce hundreds of ion images representing spatial distributions of biomolecules in biological tissues. Due to the large diversity of ions detected in untargeted analyses, normalization standards are often difficult to implement to account for pixel-to-pixel variability in imaging studies. Many normalization strategies exist to account for this variability, but they largely do not improve image quality. In this study, we present a new approach for improving image quality and visualization of tissue features by application of sequential paired covariance (SPC). This approach was demonstrated using previously published tissue datasets such as rat brain and human prostate with different biomolecules like metabolites and N-linked glycans. Data transformation by SPC improved ion images resulting in increased smoothing of biological features compared with commonly used normalization approaches.     

Morita–Baylis–Hillman (MBH) Reaction Derived Nitroallylic Alcohols,Acetates and Amines as Synthons in Organocatalysis and Heterocycle Synthesis

The Morita–Baylis–Hillman (MBH) reaction is one of the most useful and efficient protocols for constructing new carbon–carbon bonds between an activated olefin and electrophiles in the presence of a tertiary amine/phosphine. Herein, we present the use of MBH alcohols, which are obtained from the reaction of nitrostyrenes with aldehydes, as well as acetates and amines derived thereof in several organocatalytic transformations. Densely functionalised MBH adducts can also be used to synthesise substituted heteroaromatic compounds, such as furan, pyrrole, pyrazole and imidazole derivatives.     

Advanced online mass spectrometry detection of proteins separated by capillary isoelectric focusing after sequential injection

Capillary isoelectric focusing hyphenated with mass spectrometry detection, following the sequential injection of the carrier ampholytes and the sample zone, is highly efficient for the characterization of proteins. The main advantage of the sequential injection protocol is that ampholytes, with pH ranges, which are not supposed to cover the isoelectric points of the sample components, can be used for separation. The method then allows online mass spectrometry detection of separated analytes either in the absence (substances that have left the pH gradient) or in the presence of low‐level ampholytes (substances that are migrating within the pH gradient). The appearance of the substances within, or outside the pH gradient depends on, e.g., the composition of the ampholytes (broad or narrow pH range) or on the composition of electrolyte solutions. The experiments performed in coated capillaries (with polyvinyl alcohol or with polyacrylamide) show that the amount and the injection length of the ampholytes influence the length of the pH gradient formed in the capillary.     

Status Set Sequential Pattern Mining Considering Time Windows and Periodic Analysis of Patterns

The traditional sequential pattern mining method is carried out considering the whole time period and often ignores the sequential patterns that only occur in local time windows, as well as possible periodicity. Therefore, in order to overcome the limitations of traditional methods, this paper proposes status set sequential pattern mining with time windows (SSPMTW). In contrast to traditional methods, the item status is considered, and time windows, minimum confidence, minimum coverage, minimum factor set ratios and other constraints are added to mine more valuable rules in local time windows. The periodicity of these rules is also analyzed. According to the proposed method, this paper improves the Apriori algorithm, proposes the TW-Apriori algorithm, and explains the basic idea of the algorithm. Then, the feasibility, validity and efficiency of the proposed method and algorithm are verified by small-scale and large-scale examples. In a large-scale numerical example solution, the influence of various constraints on the mining results is analyzed. Finally, the solution results of SSPM and SSPMTW are compared and analyzed, and it is suggested that SSPMTW can excavate the laws existing in local time windows and analyze the periodicity of the laws, which solves the problem of SSPM ignoring the laws existing in local time windows and overcomes the limitations of traditional sequential pattern mining algorithms. In addition, the rules mined by SSPMTW reduce the entropy of the system.     

Recent Developments in Flow Injection/Sequential Injection Liquid-Liquid Extraction for Atomic Spectrometric Determination of Metals and Metalloids

Abstract

This review aims to provide a critical overview of automated flow injection and sequential injection liquid-liquid extraction for preconcentration and/or separation of ultra-trace metal and metalloid species hyphenated with atomic spectrometric detection systems, including some new trends and applications in the subbranches of cloud point extraction (CPE), wetting film extraction (WFE), supported liquid membrane extraction (SLME), extraction chromatography (EChr), and liquid-phase microextraction (LPME) techniques. The analytical performance of flow-injection/sequential injection liquid-liquid extraction methods is markedly affected by the components of the flow network such as segmentor, extraction coil, and phase separator. Thus, an overall presentation of system components along with some novel strategies for interface with atomic spectrometers is discussed and exemplified with selected applications.