QUANTIS: Data quality assessment tool by clustering analysis

Automatically generated kinetic networks are ideally validated against a large set of accurate, reproducible, and easy-to-model experimental data. However, although this might seem simple, it proves to be quite challenging. QUANTIS, a publicly available Python package, is specifically developed to evaluate both the precision and accuracy of experimental data and to ensure a uniform, quick processing, and storage strategy that enables automated comparison of developed kinetic models. The precision is investigated with two clustering techniques, PCA and t-SNE, whereas the accuracy is probed with checks for the conservation laws. First, the developed tool processes, evaluates, and stores experimental yield data automatically. All data belonging to a given experiment, both unprocessed and processed, are stored in the form of an HDF5 container. The demonstration of QUANTIS on three different pyrolysis cases showed that it can help in identifying and overcoming instabilities in experimental datasets, reduce mass and molar balance closure discrepancies, and, by evaluating the visualized correlation matrices, increase understanding in the underlying reaction pathways. Inclusion of all experimental data in the HDF5 file makes it possible to automate simulating the experiment with CHEMKIN. Because of the employed InChI string identifiers for molecules, it is possible to automate the comparison experiment/simulation. QUANTIS and the concepts demonstrated therein is a potentially useful tool for data quality assessment, kinetic model validation, and refinement.     

Simulating ion clustering in potassium thiocyanate aqueous solutions with various ion-water models

Using a molecular dynamics simulation technique,we compared several commonly used ion-water models to describe the microscopic structures and dynamics in KSCN aqueous solutions.Results are compared with observations of femtosecond infrared vibrational-energy transfer and anisotropy measurements.The Jorgensen/TIP4P model is found to provide the best reproduction of clustering properties such as percentage of clustered ions,cluster-size distribution,concentration dependence of the water,and ion-rotation time constants.     

Inverse colloidal crystal membranes for hydrophobic interaction membrane chromatography

A collaborative study on the robustness and portability of a capillary electrophoresis‐mass spectrometry method for peptide mapping was performed by an international team, consisting of 13 independent laboratories from academia and industry. All participants used the same batch of samples, reagents and coated capillaries to run their assays, whereas they utilized the capillary electrophoresis‐mass spectrometry equipment available in their laboratories. The equipment used varied in model, type and instrument manufacturer. Furthermore, different types of sheath‐flow capillary electrophoresis–mass spectrometry interfaces were used. Migration time, peak height and peak area of ten representative target peptides of trypsin‐digested bovine serum albumin were determined by every laboratory on two consecutive days. The data were critically evaluated to identify outliers and final values for means, repeatability (precision within a laboratory) and reproducibility (precision between laboratories) were established. For relative migration time the repeatability was between 0.05 and 0.18% RSD and the reproducibility between 0.14 and 1.3% RSD. For relative peak area repeatability and reproducibility values obtained were 3–12 and 9–29% RSD, respectively. These results demonstrate that capillary electrophoresis‐mass spectrometry is robust enough to allow a method transfer across multiple laboratories and should promote a more widespread use of peptide mapping and other capillary electrophoresis‐mass spectrometry applications in biopharmaceutical analysis and related fields.     

Flexible and powerful strategy for qualitative and quantitative analysis of valepotriates in Valeriana jatamansi Jones using high‐performance liquid chromatography with linear ion trap Orbitrap mass spectrometry

Valeriana jatamansi Jones is an important medicinal plant and its quality is closely related to its region of origin. In the current study, we utilized a flexible and powerful strategy for comprehensive evaluation of the quality diversity for 15 regions in China. The method was based on a hybrid linear ion trap‐Orbitrap mass spectrometry platform. For structure characterization, fragmentation patterns were detected by analyzing a series of standard compounds using data dependent multistage mass spectrometry acquisition. A fragment ion database for valepotriates was established, and the acquired data were high throughput filtered by fragment ion search for compound identification. For quantitative purposes, we normalized the mass spectrometry data of 15 samples using SIEVE 2.0 and the differences in composition were analyzed using principal component analysis combined with hierarchical clustering analysis. The results identified a total of 92 compounds from Valeriana jatamansi Jones. Samples from Dali, Kunming, and Baoshan have better qualities and concentrations of the main active constituents. To verify our strategy, we compared the valtrate, acevaltrate, and baldrinal contents using high‐performance liquid chromatography with diode array detector. We developed and validated a comprehensive qualitative and quantitative analytical method to achieve quality control of Valeriana jatamansi Jones.     

Study on convergence and error of a numerical method for solving systems of nonlinear Fredholm–Volterra integral equations of Hammerstein type

The aim of this paper is to present an efficient analytical and numerical procedure for solving systems of nonlinear Fredholm–Volterra integral equations of the Hammerstein type with the aid of fixed point techniques and the usual Schauder basis in an adequate Banach space.     

基于两阶段灰色聚类模型的新疆经济社会发展水平评价研究

通过两阶段灰色聚类模型选择影响经济社会发展水平,基础设施建设,相关产业发展水平以及区域经济基础四个一级指标的10个二级指标来构建区域经济社会发展水平评价指标体系,以2013年新疆14地州市相关数据为样本,运用基于改进的中心点混合三角白化权函数把新疆各地州市从经济社会发展的角度划分成4个区域,为"新丝绸之路经济带"下新疆各地州的经济与社会发展定位提供依据最后找出属于三、四级经济圈内地区经济与社会发展落后的原因并提出相关建议.     

Identifying Mixtures of Mixtures Using Bayesian Estimation

The use of a finite mixture of normal distributions in model-based clustering allows us to capture non-Gaussian data clusters. However, identifying the clusters from the normal components is challenging and in general either achieved by imposing constraints on the model or by using post-processing procedures. Within the Bayesian framework, we propose a different approach based on sparse finite mixtures to achieve identifiability. We specify a hierarchical prior, where the hyperparameters are carefully selected such that they are reflective of the cluster structure aimed at. In addition, this prior allows us to estimate the model using standard MCMC sampling methods. In combination with a post-processing approach which resolves the label switching issue and results in an identified model, our approach allows us to simultaneously (1) determine the number of clusters, (2) flexibly approximate the cluster distributions in a semiparametric way using finite mixtures of normals and (3) identify cluster-specific parameters and classify observations. The proposed approach is illustrated in two simulation studies and on benchmark datasets. Supplementary materials for this article are available online.     

Lithium Bis(oxalate)borate Additive for Self-repairing Zincophilic Solid Electrolyte Interphases towards Ultrahigh-rate and Ultra-stable Zinc Anodes

The artificial solid electrolyte interphase (SEI) plays a pivotal role in Zn anode stabilization but its long-term effectiveness at high rates is still challenged. Herein, to achieve superior long-life and high-rate Zn anode, an exquisite electrolyte additive, lithium bis(oxalate)borate (LiBOB), is proposed to in situ derive a highly Zn²⁺-conductive SEI and to dynamically patrol its cycling-initiated defects. Profiting from the as-constructed real-time, automatic SEI repairing mechanism, the Zn anode can be cycled with distinct reversibility over 1800 h at an ultrahigh current density of 50 mA cm⁻², presenting a record-high cumulative capacity up to 45 Ah cm⁻². The superiority of the formulated electrolyte is further demonstrated in the Zn||MnO₂ and Zn||NaV₃O₈ full batteries, even when tested under harsh conditions (limited Zn supply (N/P≈3), 2500 cycles). This work brings inspiration for developing fast-charging Zn batteries toward grid-scale storage of renewable energy sources.     

Host–Guest Doping in Flexible Organic Crystals for Room-Temperature Phosphorescence

Organic single crystals (OSCs) with excellent flexibility and unique optical properties are of great importance due to their broad applicability in optical/optoelectronic devices and sensors. Nevertheless, fabricating flexible OSCs with room-temperature phosphorescence (RTP) remains a great challenge. Herein, we propose a host–guest doping strategy to achieve both RTP and flexibility of OSCs. The single-stranded crystal is highly bendable upon external force application and can immediately return to its original straight shape after removal of the stress, impressively emitting bright deep-red phosphorescence. The theoretical and experimental results demonstrate that the bright RTP arises from Förster resonance energy transfer (FRET) from the triphenylene molecules to the dopants. This strategy is both conceptually and synthetically simple and offers a universal approach for the preparation of flexible OSCs with RTP.