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For high‐performance quantum‐dot light‐emitting‐diode (QD‐LED), it is imperative to resolve the charge imbalance. In this paper, the solution to resolve the charge imbalance is introduced to mix two polymer hole transport layer (HTL) materials. [ABSTRACT FROM AUTHOR]

Gaming display market has been increased over the recent years and is expected to further grow. For immersive gaming experience high refresh rate driving is required and thus very fast response time LC is essential to enable better gaming experience. We have been looking for ways to improve response time of Liquid Crystal devices through LC mixture concept development. In this paper, we would like to demonstrate new mixtures with significantly improved switching speed parameter beyond limits by introduction licristal® XtraFast LC single. [ABSTRACT FROM AUTHOR]

We report the current state‐of‐the‐art in liquid crystal and reactive mesogen formulation properties and show how they relate to device performance for both passive and active photonic components for current and future non‐display applications. Development trends and trade‐offs of the formulation properties will be discussed looking into the future. [ABSTRACT FROM AUTHOR]

Paper membranes made from vulcanized cellulose were used for the pervaporation (PV) of aqueous solutions containing methanol, ethanol, and isopropanol. It was noted that the vulcanized cellulose paper membranes (VCPM) could effectively separate alcohol and water from the mixture solutions. To observe the effect of the separation of alcohol aqueous mixtures, the permeation behavior of water and alcohol was examined by means of the separation factor and the permeation flux. The values of the permeation flux in the ethanol/water mixtures were found to vary from 6.2 kg/mh to 2.1 kg/mh, as the concentration of ethanol increased from 8 to 87 wt %, and the separation factor (α) changed from α = 2.6 to 6.6, respectively. This showed that the VCPM enhanced the separation of water and alcohol. The highest value observed for the permeation flux was 11 kg/mh at 87 wt % of methanol concentration and the separation factor at this condition was 4.1. It was shown also that an efficient separation was obtained in the isopropanol/water mixture with a separation factor of 16.6. The contact angles of alcohol/water droplets on the VCPM were measured as well as the wettability of the membrane. There was a tendency of decrease for the contact angle, as the alcohol concentration decreased. This suggested that the solvent wettability decreased in high alcohol concentrations. It was concluded that a high permeabilitty of water through the VCPM resulted in the separation of alcohols and water in the PV process. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011 [ABSTRACT FROM AUTHOR]

Highly birefringent liquid crystals have always been desired by many applications in visible, infrared and recently other spectral regions such as THz and GHz as a active medium for various devices fabrication eg. light shutters, shifters, attenuators, filters, electronic lenses, delay lines, antennas, varactors and laser beam steerers. Our own results in the field have been combined with more important ones from literature and have been summarized and reviewed. Special attention will be given to compounds with oligophenyl and tolane based rigid cores for which dual approach of dipol moment generation have been applied (see figure below). [ABSTRACT FROM AUTHOR]

In recent days, a combination of finite mixture model (FMM) and hidden Markov model (HMM) is becoming popular for partitioning heterogeneous temporal data into homogeneous groups (clusters) with homogeneous time points (regimes). The regression mixtures commonly considered in this approach can also accommodate for covariates present in data. The classical fixed covariate approach, however, may not always serve as a reasonable assumption as it is incapable of accounting for the contribution of covariates in cluster formation. This paper introduces a novel approach for detecting clusters and regimes in time series data in the presence of random covariates. The computational challenges related to the proposed model has been discussed, and several simulation studies are performed. An application to United States COVID-19 data yields meaningful clusters and regimes. [ABSTRACT FROM AUTHOR]

Melamine is a chemical compound generating a very characteristic Raman signature. This component is fraudulently added to milk to artificially increase its nitrogen content (and thereby its apparent protein content). In this paper, we evaluate the ability of a specific wide‐field Fourier‐based Raman imaging system to identify melamine. The melamine is studied in powder form or diluted and dried out on SERS (surface‐enhanced Raman spectroscopy) Cu2O‐Ag substrate, which enhances the Raman signature. In both forms, we show that the spatial content of the information is an asset to characterize the samples; on SERS, we demonstrate the inhomogeneity of the deposition, and in powder form, we identify melamine as individual grain mixed with milk powder. The specific wide‐field imaging technology features much higher laser excitation with lower local intensity than traditional point to point Raman measurement, thereby reducing the acquisition time for full data sets. [ABSTRACT FROM AUTHOR]

Summary: This paper develops the Finite Mixture Roy model for count variables and uses this semiparametric model to analyze the effect of supplemental Medigap private insurance on the demand for prescription drugs for the U.S. elderly unemployed Medicare population. The model is an extension of the Count Roy model, which produces unrealistic treatment effects when observed count patterns are consistent with finite mixtures. To estimate the numbers of components in the mixtures for individuals with and without Medigap, this paper adopts the random permutation sampler. The considered application motivates two additional features of the model. Specifically, the smoothly mixing regression approach is utilized to model the probabilities of the components, and a continuous instrumental variable is allowed to enter the treatment equation nonparametrically. Strong evidence is found that there are two components both in the treated and untreated states. These lower and higher utilization components are interpreted as relatively healthy and unhealthy groups. The estimated treatment effects show that Medigap insurance provides incentives to increase prescription drug utilization by 2%. The results are consistent with adverse selection. [ABSTRACT FROM AUTHOR]

Several recent works have tackled the estimation issue for the unidimensional four‐parameter logistic model (4PLM). Despite these efforts, the issue remains a challenge for the multidimensional 4PLM (M4PLM). Fu et al. (2021) proposed a Gibbs sampler for the M4PLM, but it is time‐consuming. In this paper, a mixture‐modelling‐based Bayesian MH‐RM (MM‐MH‐RM) algorithm is proposed for the M4PLM to obtain the maximum a posteriori (MAP) estimates. In a comparison of the MM‐MH‐RM algorithm to the original MH‐RM algorithm, two simulation studies and an empirical example demonstrated that the MM‐MH‐RM algorithm possessed the benefits of the mixture‐modelling approach and could produce more robust estimates with guaranteed convergence rates and fast computation. The MATLAB codes for the MM‐MH‐RM algorithm are available in the online appendix. [ABSTRACT FROM AUTHOR]

Fourier transform infrared (FTIR) spectroscopy is frequently used for archaeological studies related to fire, allowing, among other things, researchers to distinguish between unheated and heated clay minerals. However, heat signatures are not always clear‐cut in infrared spectra of bulk sediments, as spectra occasionally appear with ambiguous absorbance bands attributed to hydroxyl (OH) in clay minerals. This paper presents an experimental study addressing this interpretational problem by considering the effect of mixtures of heated and unheated clay, a phenomenon expected in archaeological sites. After creating experimental mixtures and testing them using bulk FTIR spectroscopy, our results indicate that even a relatively small amount of unheated clay—only ca. 5%–10% mixed into a fully heated deposit—will result in ambiguous infrared spectra that are difficult to interpret. For comparison, ambiguous bulk FTIR spectra from two archaeological contexts—an ashy fill within a pit installation and a hearth—were studied with FTIR microspectroscopy, which demonstrated the presence of unheated clay within a largely heated deposit. Micromorphological observations explain the mixed nature of the investigated archaeological contexts, in this case, primarily via bioturbation. Our results thus emphasize the importance of microcontextual analysis of clay minerals. Furthermore, these results indicate that heated deposits are likely missed altogether in some archaeological contexts where only bulk FTIR analyses have been conducted. [ABSTRACT FROM AUTHOR]

Benchtop nuclear magnetic resonance (NMR) spectrometers are being employed in a wide variety of applications from undergraduate teaching and research in academia to quality control and process monitoring in industrial settings. Incorporating benchtop NMR in some of these applications presents opportunities for new practical uses of the technology and challenges that truly test the capabilities of compact NMR spectrometers. For instance, the use of protonated solvents in manufacturing or process monitoring requires separating and quantitating the analyte signals of interest from the strong (overwhelming) response from the solvents. Furthermore, due to the lower field strength available with permanent magnet spectrometers, the NMR spectra of complex mixtures can be more difficult to analyze due to partial or complete signal overlap. To address some of these challenges and to extend the range of applications of benchtop NMR, we investigate NMR techniques that enable quantitative analysis of different components in mixtures. These pulse sequences can be used to suppress one or multiple solvent peaks, to filter out signals by spin–spin relaxation time (T2), or to separate signal components by a molecule's diffusion coefficient (NMR diffusometry). In this paper, we discuss quantitative analysis of excipients in buffers for therapeutic proteins to highlight the usefulness of these NMR pulse sequences in the analysis of complex samples with benchtop NMR spectrometers. [ABSTRACT FROM AUTHOR]

The separation of short‐chain hydrocarbon mixtures is of great significance for the efficient utilization of fossil energy. Liquid–liquid extraction, as one of the commonly used treatment methods, has significant advantages in terms of operation conditions and energy consumption. As a new dipolar aprotic solvent developed in recent years, dihydrolevoglucosenone (Cyrene) has a wide range of sources and a green composition. In this paper, the liquid–liquid equilibrium and extraction mechanism of Cyrene and five hydrocarbon mixtures with short carbon chains, including toluene/n‐heptane, toluene/cyclohexane, n‐hexane/cyclohexane, n‐pentane/pentene, and n‐hexane/hexene, have been studied by combining experiments and quantum chemical calculations, and the extraction effects under different conditions have been investigated. The results showed that the forces between Cyrene and the different solutes are mainly van der Waals (VDW) forces dominated by dispersion forces, with some weak hydrogen bonds present. Due to the difference in interaction energy, the order of extraction selectivity was toluene‐n‐heptane > toluene‐cyclohexane > n‐hexane‐hexene > n‐hexane‐cyclohexane > n‐pentane‐pentene, and the order of distribution coefficients of the extracted components (aromatics, olefins, and cycloalkanes) was toluene > pentene > hexene > cyclohexane. The dissolution processes of all systems were heat‐absorbing, and they all reached the extraction equilibrium within 60 s. The reliability of the experimental data was verified using the Othmer–Tobias equation and the Hand equation, and the binary interaction parameters of all systems were obtained by the non‐random two liquid (NRTL) model, providing basic data and references for the subsequent studies on the separation of Cyrene and short‐chain hydrocarbons. [ABSTRACT FROM AUTHOR]

In this paper, new statistical algorithms for accurate peak detection in the metabolomic data are proposed. Specifically, liquid chromatograph‐mass spectrometry data are analyzed. The discretized skew‐t mixture model for peak detection is proposed. It shows great flexibility and capability in fitting skewed or heavy‐tailed peaks. The methodology is further extended to cross‐sample peak alignment for identifying the true peaks. A measure of peak credibility is provided through the assessment of misclassification probabilities between two cross‐sample peaks. The proposed algorithms are applied to spike‐in data with promising results. [ABSTRACT FROM AUTHOR]

Analysing data from educational tests allows governments to make decisions for improving the quality of life of individuals in a society. One of the key responsibilities of statisticians is to develop models that provide decision‐makers with pertinent information about the latent process that educational tests seek to represent. Mixtures of t$$ t $$ factor analysers (MtFA) have emerged as a powerful device for model‐based clustering and classification of high‐dimensional data containing one or several groups of observations with fatter tails or anomalous outliers. This paper considers an extension of MtFA for robust clustering of censored data, referred to as the MtFAC model, by incorporating external covariates. The enhanced flexibility of including covariates in MtFAC enables cluster‐specific multivariate regression analysis of dependent variables with censored responses arising from upper and/or lower detection limits of experimental equipment. An alternating expectation conditional maximization (AECM) algorithm is developed for maximum likelihood estimation of the proposed model. Two simulation experiments are conducted to examine the effectiveness of the techniques presented. Furthermore, the proposed methodology is applied to Peruvian data from the 2007 Early Grade Reading Assessment, and the results obtained from the analysis provide new insights regarding the reading skills of Peruvian students. [ABSTRACT FROM AUTHOR]

Plant Protection Products (PPPs) are widely used to maintain high productivity and protect crops, but can have unintended toxic effects on beneficial non‐target soil organisms. To avoid unacceptable adverse effects of PPPs on soil organisms, a prospective risk assessment is carried out, which focuses on individual substances and their effects on a few individual species or groups. However, the reality of agricultural soils consists of complex networks of organisms exposed to mixtures of several PPP active substances. It is therefore essential to monitor PPP residues in soils. This paper describes the ConSoil project and its proposed framework for monitoring PPP residues in Swiss Agricultural soils which includes and integrates (1) risk‐based reference values for PPP residues in soil and (2) indicators of their effects on long‐term soil fertility. For risk‐based reference values, a proposal has been developed to derive Soil Guideline Values (SGVs) for PPP residues and a mixture risk assessment concept is being developed. Regarding indicators, a toolbox of ecological and ecotoxicological indicators will be proposed to reflect the protection goal of long‐term soil fertility in agricultural soils. For this objective, standardised and/or well‐established bioindicator methods will be selected for the key soil organisms that support soil fertility. To integrate SGVs and the biomonitoring toolbox, an adapted TRIAD approach is proposed, where generic SGVs are used as a screening tool to identify monitoring sites potentially at risk and to trigger more detailed monitoring. Detailed monitoring will refine the SGVs based on site‐specific characteristics and implement the bioindicator toolbox to measure the effects of PPP residues and their risk to long‐term soil fertility. As a novel integrated framework, it is essential to use the data generated in detailed assessments to calibrate and refine the SGVs and bioindicator tools and improve the monitoring over time. [ABSTRACT FROM AUTHOR]

The present paper is dedicated to the structural stability of the linear model of a mixture of two porous solids. It is shown that the variation of the characteristic coefficients that describe the coupling of the various mechanical effects involved in the model in concern does not destroy its structure. This means that any small variation of these coefficients leads to small variations in the corresponding solutions of the associated initial boundary value problems. For this purpose, more mathematical estimates are presented describing precisely the continuous dependence of the solutions with respect to all external given data of the initial boundary value problem, as well as with respect to appropriate measures of the set of coupling parameters. This allows the conclusion that the model of the mixture of porous materials is consistent. In particular, it is believed that the estimates obtained in terms of structural stability are particularly meaningful with regard to the materials used in building contexts and the related decay phenomena. [ABSTRACT FROM AUTHOR]

In this paper, we consider the pointwise space–time behaviors of solutions for the dynamic combustion of compressible reactive mixture. The pointwise estimates of global solutions are established in the whole space R3$\mathbb {R}^3$ by using the Green's function method. These estimates also show the wave propagation of the solution. As a by‐product, the Lp$L^p$‐norm decay rates of the solution are achieved. [ABSTRACT FROM AUTHOR]

In a two-mode network, the nodes are divided into two types (primary nodes and secondary nodes), and connections exist only between nodes of different types. In reality, in such a two-mode network, one-mode network connections may also exist among primary nodes, and these two kinds of networks are usually not independent and coexistent. In this paper, we first propose a group Rasch mixture network model that focuses on the connections between primary nodes and secondary nodes, while incorporating the group structure and linkage information of primary nodes. We then develop a modified expectation–maximization algorithm to estimate the proposed model with a λ-BIC method for selecting the tuning parameter. Additionally, we provide a likelihood-ratio test statistic to examine whether the two kinds of networks are independent and implement the leave-one-out method to construct a network prediction rule. Finally, we establish asymptotic results and demonstrate the numerical performance of the proposed methods using both simulations and the Last.fm dataset. [ABSTRACT FROM AUTHOR]

Summary: Any knowledge extraction relies (possibly implicitly) on a hypothesis about the modelled‐data dependence. The extracted knowledge ultimately serves to a decision‐making (DM). DM always faces uncertainty and this makes probabilistic modelling adequate. The inspected black‐box modeling deals with "universal" approximators of the relevant probabilistic model. Finite mixtures with components in the exponential family are often exploited. Their attractiveness stems from their flexibility, the cluster interpretability of components and the existence of algorithms for processing high‐dimensional data streams. They are even used in dynamic cases with mutually dependent data records while regression and auto‐regression mixture components serve to the dependence modeling. These dynamic models, however, mostly assume data‐independent component weights, that is, memoryless transitions between dynamic mixture components. Such mixtures are not universal approximators of dynamic probabilistic models. Formally, this follows from the fact that the set of finite probabilistic mixtures is not closed with respect to the conditioning, which is the key estimation and predictive operation. The paper overcomes this drawback by using ratios of finite mixtures as universally approximating dynamic parametric models. The paper motivates them, elaborates their approximate Bayesian recursive estimation and reveals their application potential. [ABSTRACT FROM AUTHOR]

Honeybees (Apis mellifera) frequently live in complex environments where exposure to mixtures of pesticides is possible. Although several studies have expressed concern regarding the combined effects of pesticide mixtures, other studies did not find increased toxicity. Thus, the primary objective of this study was to identify peer‐reviewed literature measuring the toxicity of pesticide mixtures to honeybees and determine how frequently synergistic interactions occur. Many experiments (258) were identified that met the criteria for inclusion. When considering all experiments, 34% of experiments had model deviation ratios (MDR; expected toxicity/observed toxicity) greater than 2, suggesting greater‐than‐additive toxicity. Twelve percent of experiments had MDR values greater than 5, with several studies exceeding 100. However, most experiments that had higher MDRs included azole fungicides or acaricides as a component of the mixture. After removal of these groups, only 8% of experiments exceeded an MDR of 2, and no experiments exceeded 5. Moreover, the influence of the azole fungicides was dose dependent. If only experiments that used azole exposure at environmentally relevant concentrations were considered, azole fungicides had limited impact on neonicotinoid insecticides. However, pyrethroid insecticides still had greater than expected toxicity with 80% of experiments having MDR values greater than 2. Acaricides also had greater than expected incidence of synergy with approximately 30% of studies reporting MDR values greater than 2. It should be noted that even the azole studies considered environmentally relevant frequently used maximum exposure rates and worst‐case exposure scenarios. The primary finding is that synergy is uncommon except for a few cases where known synergists (azole fungicides) and pesticides with variable metabolism potential, such as some pyrethroids, are in combination. Future work is still needed to refine the relevance of azole fungicides at commonly occurring environmental concentrations. Integr Environ Assess Manag 2022;18:1694–1704. © 2022 SETAC KEY POINTS: When evaluating all pesticide‐mixture studies in the literature, evidence of synergy is common for honeybees.The majority of studies where synergy was found to occur involved azole fungicides, known synergists, in combination with insecticides with variable metabolism potential, such as some pyrethroids.Environmental relevance of applied concentrations should be considered when evaluating the results of pesticide mixtures studies.Synergy involving neonicotinoid insecticides is uncommon when only considering environmentally relevant concentrations of azole fungicide. [ABSTRACT FROM AUTHOR]

This paper proposes an unsupervised algorithm for learning a finite mixture of scaled Dirichlet distributions. Parameters estimation is based on the maximum likelihood approach, and the minimum message length (MML) criterion is proposed for selecting the optimal number of components. This research work is motivated by the flexibility issues of the Dirichlet distribution, the widely used model for multivariate proportional data, which has prompted a number of scholars to search for generalizations of the Dirichlet. By introducing the extra parameters of the scaled Dirichlet, several useful statistical models could be obtained. Experimental results are presented using both synthetic and real datasets. Moreover, challenging real‐world applications are empirically investigated to evaluate the efficiency of our proposed statistical framework. [ABSTRACT FROM AUTHOR]

Reliability analysis and evaluation of systems with multiple failure modes is extremely challenging. In this paper, a novel, efficient, and accurate system reliability method is proposed based on the second‐order approximation and the mixture important sampling (mixture‐IS) method. The proposed method does not require the construction of surrogate models and integrates the advantages of second‐order approximation and mixture‐IS strategies, which can greatly reduce the computational effort of estimating the system failure probability as well as ensuring the accuracy. The accuracy and efficiency of the proposed method are verified by several numerical and engineering problems, and comparisons are made against other existing reliability methods. The results indicate that the method can effectively reduce the number of limit state function calls and achieve high computational accuracy. [ABSTRACT FROM AUTHOR]

Long‐term creep compliance is one of the most important mechanical properties for evaluating the long‐term behavior of concrete structures. This paper aims to optimize machine‐learning models to predict this viscoelastic property. The most relevant dataset available in the literature is considered, cleaned, and preprocessed to optimize the outcome. The advanced XGBoost model, which is to be the most effective shallow machine‐learning model for modeling tabular datasets, is employed in this study to maximize model accuracy. Short‐term creep compliances of a given sample at typical ages are used as input features to model the long‐term creep compliance of concrete. This approach outperforms standard machine‐learning approaches that do not include short‐term creep as an input feature. Indeed, the short‐term behavior of concrete strongly influents its long‐term one. The optimized machine model presented herein is accurate and useful for practical applications. It uses input features that are easy to obtain to predict long‐term creep compliance up to several decades, which is difficult and expensive to measure. [ABSTRACT FROM AUTHOR]

Assessing the ecological risk of contaminants in the field typically involves consideration of a complex mixture of compounds which may or may not be detected via instrumental analyses. Further, there are insufficient data to predict the potential biological effects of many detected compounds, leading to their being characterized as contaminants of emerging concern (CECs). Over the past several years, advances in chemistry, toxicology, and bioinformatics have resulted in a variety of concepts and tools that can enhance the pragmatic assessment of the ecological risk of CECs. The present Focus article describes a 10+‐ year multiagency effort supported through the U.S. Great Lakes Restoration Initiative to assess the occurrence and implications of CECs in the North American Great Lakes. State‐of‐the‐science methods and models were used to evaluate more than 700 sites in about approximately 200 tributaries across lakes Ontario, Erie, Huron, Michigan, and Superior, sometimes on multiple occasions. Studies featured measurement of up to 500 different target analytes in different environmental matrices, coupled with evaluation of biological effects in resident species, animals from in situ and laboratory exposures, and in vitro systems. Experimental taxa included birds, fish, and a variety of invertebrates, and measured endpoints ranged from molecular to apical responses. Data were integrated and evaluated using a diversity of curated knowledgebases and models with the goal of producing actionable insights for risk assessors and managers charged with evaluating and mitigating the effects of CECs in the Great Lakes. This overview is based on research and data captured in approximately about 90 peer‐reviewed journal articles and reports, including approximately about 30 appearing in a virtual issue comprised of highlighted papers published in Environmental Toxicology and Chemistry or Integrated Environmental Assessment and Management. Environ Toxicol Chem 2023;42:2506–2518. © 2023 SETAC. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA. [ABSTRACT FROM AUTHOR]

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In the present paper, we report the synthesis of highly functionalized nanomaterials carefully nanoengineered to catalyze the semi‐hydrogenation of acetylene in ethylene‐rich mixtures. Surface functionalization and structure modification of a series of bimetallic PdAg nanoparticles was performed using HHDMA as stabilizer and alloying the active palladium phase with silver. Bimetallic PdAg NPs with adjustable Pd/Ag ratio were prepared in water through a novel one‐pot methodology using hydrogen gas as a benign reducing agent and cyanide as additive. UV‐Vis studies indicated the formation of the bimetallic nanostructures through a sequential displacement‐galvanic reduction process mediated by cyanide. The series of colloidal NPs were deposited onto alumina and successfully applied as catalysts in the selective hydrogenation of acetylene in ethylene rich mixtures. Geometric and electronic promotion of Ag over Pd based catalysts was evidenced by the increase of the ethylene selectivity with the Ag content. The reactivity of these materials demonstrated the applicability of HHDMA stabilized NPs in a gas phase reaction of industrial interest and the success of combining several strategies for the enhancement of the alkene selectivity. [ABSTRACT FROM AUTHOR]

Relatives tend to have more DNA in common than unrelated people. The closer the biological relationship, the higher the chance of alleles being identical by descent between the individuals. Therefore, when considering a mixed DNA profile, close relatives of the true contributor may not always be excluded as a possible contributor to a mixture due to allele sharing. In these situations, it might be more appropriate under the alternate proposition to consider that the DNA could have originated from a relative of the person of interest rather than an unrelated individual. The probabilistic genotyping software STRmix™ automatically provides LRs considering close biological relatives as alternate sources of the DNA. In this paper, we investigate the support for siblings of the true contributor to a mixture (who are not present in the mixture themselves). We interpret the mixtures and assign LRs using STRmix™ and investigate whether the resulting LRs could be used to indicate whether the true contributor could be a sibling of the POI. Most siblings will have one or more alleles that are not observed in the mixture profile. Support for siblings to have contributed can only occur when allelic dropout is a possibility at the loci where the siblings have alleles that are not observed in the profile. In these data, that was only observed in components with assigned template of 588 rfu or less. [ABSTRACT FROM AUTHOR]

Methoxy‐bridge polar monomer has high dielectric anisotropy, which can reduce the driving voltage of the panel and save energy; olefinic‐chain monomer can effectively reduce the rotational viscosity and improve the response speed of the panel, while the polar alkene monomer has both low rotational viscosity and high dielectric anisotropy, which has a good application prospect. At present, the industry does not have too much verification and analysis of the collocation about the collocation of two monomers. In this paper, the reliability of liquid crystal materials containing polar methoxide monomers and polar alkene monomer was tested. The results showed that VHR (Voltage Holding Ratio) performance was worse in the experimental group with the two monomers. And with the extension of UV irradiation time, the difference between the experimental group and the control group was more obvious. A further test of IS (Image Sticking) was conducted on a 32‐inch display platform. The results showed that the liquid crystal containing both two monomers was tested NG, while the control group was OK. [ABSTRACT FROM AUTHOR]

In the present paper, study the acoustical properties of lead oxide nanoparticles through the measurement of ultrasonic velocity and density of lead oxide nanoparticles as a ligand in 70% dioxane + water, 70% methanol + water, and 70% ethanol + water mixtures‐based solutions has been carried out, this measurement is important for understanding the particle–particle, particle–solvent, and molecular interaction. The reported nanoparticles of lead oxide by using biological method such as using plant extract, but their acoustical properties of lead oxide nanoparticles are attracted the attentions of many researchers. Hence, the present investigation is focused on the study of acoustical parameters of lead oxide nanoparticles like adiabatic compressibility (β), acoustic impedance (Z), free length, and relative association by using the nanofluid interferometer. These measurements are carried out at frequency 2 MHz and temperature 305 K (at room temperature). The obtained results are helped to observe the behavior of ultrasonic velocity and acoustic properties at different concentrations range of ligand (i.e., lead oxide nanoparticle) such as 0.01, 0.05, 0.10, and 0.15 mol dm−3 reveal the presence of interaction between particle–particle, particle and solvent. [ABSTRACT FROM AUTHOR]

Summary: When it is suspected that the treatment effect may only be strong for certain subpopulations, identifying the baseline covariate profiles of subgroups who benefit from such a treatment is of key importance. In this paper, we propose an approach for subgroup analysis by firstly introducing Bernoulli‐gated hierarchical mixtures of experts (BHME), a binary‐tree structured model to explore heterogeneity of the underlying distribution. We show identifiability of the BHME model and develop an EM‐based maximum likelihood method for optimization. The algorithm automatically determines a partition structure with optimal prediction but possibly suboptimal in identifying treatment effect heterogeneity. We then suggest a testing‐based postscreening step to further capture effect heterogeneity. Simulation results show that our approach outperforms competing methods on discovery of differential treatment effects and other related metrics. We finally apply the proposed approach to a real dataset from the Tennessee's Student/Teacher Achievement Ratio project. [ABSTRACT FROM AUTHOR]

In this paper, we consider a Kudryashov‐Sinelshchikov equation that describes pressure waves in a mixture of a liquid and gas bubbles taking into consideration the viscosity of liquid and the heat transfer between liquid and gas bubbles. We show that this equation is rich in conservation laws. These conservation laws have been found by using the direct method of the multipliers. We apply the Lie group method to derive the symmetries of this equation. Then, by using the optimal system of 1‐dimensional subalgebras we reduce the equation to ordinary differential equations. Finally, some exact wave solutions are obtained by applying the simplest equation method. [ABSTRACT FROM AUTHOR]

We propose tractable symmetric exponential families of distributions for multivariate vectors of 0's and 1's in p dimensions, or what are referred to in this paper as binary vectors, that allow for nontrivial amounts of variation around some central value μ∈{0,1}p. We note that more or less standard asymptotics provides likelihood‐based inference in the one‐sample problem. We then consider mixture models where component distributions are of this form. Bayes analysis based on Dirichlet processes and Jeffreys priors for the exponential family parameters prove tractable and informative in problems where relevant distributions for a vector of binary variables are clearly not symmetric. We also extend our proposed Bayesian mixture model analysis to datasets with missing entries. Performance is illustrated through simulation studies and application to real datasets. [ABSTRACT FROM AUTHOR]

This paper analyses risk quantification for three main stock market index exchange‐traded funds in world financial markets. We compare the relative performance of a set of parametric and semi‐nonparametric models in terms of both value‐at‐risk and expected shortfall backtesting techniques. To this end, we explore the result of the jointly elicitability of these two risk measures. We provide a new mixture of Gram–Charlier distributions that have been used in this framework for the first time and derive a close formula for directly computing expected shortfall. This model is compared to the Gaussian (benchmark model), Student's t, generalized Pareto (a case of the extreme value theory) and mixtures of Gram–Charlier distributions. The results show that peaks‐over‐threshold (extreme value theory) and flexible Gram–Charlier approximations are suitable to quantify market risk and mitigate concerns about possible financial instabilities generated by misuse of exchange‐traded funds trading. [ABSTRACT FROM AUTHOR]

Clustering as an essential technique has matured into a capable solution to address the gap between the growing availability of data and deriving the knowledge from them. In this paper, we propose a novel clustering method "variational learning of infinite multivariate Beta mixture models." The motivation behind proposing this technique is the flexibility of mixture models to fit the data. This approach has the capability to infer the model complexity and estimate model parameters from the observed data automatically. Moreover, as a label‐free method, it could also address the problem of high costs of medical data labeling, which can be undertaken just by medical experts. The performance of the model is evaluated on real medical applications and compared with other similar alternatives. We demonstrate the ability of our proposed method to outperform widely used methods in the field as it has been shown in experimental results. [ABSTRACT FROM AUTHOR]

New energetic composites with enhanced reactive performances while allowing the safe handling according to their sensitivity thresholds are presented. This paper combines different approaches: the intimate contact between the compounds, the particle size reduction and the processing of composite materials to maintain the oxygen balance close to zero. The Spray Flash Evaporation process enables the fast crystallization at the submicron scale by combining an oxidizer, ammonium dinitramide ADN and two secondary explosives (RDX and HMX). The morphologies of the particles were analyzed and compared with slow evaporation tests. An intimate mixing between the two components (crystallized by SFE) is highlighted and core‐shell structure is evidenced by advanced techniques such as 2D and 3D confocal Raman microscopy. The composites offer outstanding energetic performances compared to sole explosives. It paves the way to new energetic compositions based on current materials. [ABSTRACT FROM AUTHOR]

The four‐parameter logistic model (4PLM) has recently attracted much interest in various applications. Motivated by recent studies that re‐express the four‐parameter model as a mixture model with two levels of latent variables, this paper develops a new expectation–maximization (EM) algorithm for marginalized maximum a posteriori estimation of the 4PLM parameters. The mixture modelling framework of the 4PLM not only makes the proposed EM algorithm easier to implement in practice, but also provides a natural connection with popular cognitive diagnosis models. Simulation studies were conducted to show the good performance of the proposed estimation method and to investigate the impact of the additional upper asymptote parameter on the estimation of other parameters. Moreover, a real data set was analysed using the 4PLM to show its improved performance over the three‐parameter logistic model. [ABSTRACT FROM AUTHOR]

The density of CO2 + crude oil mixtures is one of the most important parameters influencing CO2 diffusion and migration in oil reservoirs. However, it would be quite time consuming to obtain comprehensive density data for CO2 + alkane mixtures over a wide range of temperatures and pressures via experimental methods, therefore the development of a reliable model for predicting the densities of various CO2 + alkane mixtures with high accuracy is crucial. In this paper, the parameters (m, σ, and ε/k) in the perturbed‐chain statistical associating fluid theory (PC‐SAFT) Equation of State (EoS) were optimized by correlating density data of pure n‐alkanes from heptane to nonadecane (except undecane and hexadecane). For comparison, the G‐S PC‐SAFT and HTHP PC‐SAFT EoS(s) were also employed to fit the densities of these n‐alkanes, and the results demonstrated that the PC‐SAFT EoS with the optimized parameters in this study exhibited superior accuracy. Subsequently, by correlating density data of CO2 + alkane mixtures containing C7–C14 alkanes, the binary interaction parameter kij was optimized. Furthermore, for the first time, correlations between the optimized parameters (m, σ, ε/k, and kij) and alkane carbon number (n) were established. These correlations provided PC‐SAFT EoS with a good universality and scalability for density prediction. Using the parameters calculated from these correlations, the densities of hexadecane and saturated CO2 + alkane mixtures containing C10–C20 alkanes were successfully predicted with relatively high accuracy. This work provides a new way for modeling the thermodynamic properties of CO2 + alkane mixtures. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper deals with Aspen Plus and Aspen Dynamics of the middle vessel batch distillation for the separation of mixtures of ethanol/propanol/butanol. Two configurations of middle vessel batch distillation have been considered, namely, the conventional middle vessel batch distillation (Configuration 1) and the modified middle vessel batch distillation column (Configuration 2). Steady‐state simulations have been performed in Aspen Plus and exported to Aspen Dynamics for dynamic simulation. Dynamic studies show that Configuration 1 requires less time than Configuration 2 to obtain more than 95% of the compositions of ethanol, propanol, and butanol. The efficacy of the two controllers is assessed by the performance indices of integral of square error, integral of absolute error, and integral of time‐weighted absolute error. Configuration 1 is found to have better performance than Configuration 2. [ABSTRACT FROM AUTHOR]

This paper deals with the effect of basalt fibres on fracture toughness of asphalt mixture. For this purpose, basalt fibres with three different contents (i.e., 0.1%, 0.2%, and 0.3% by weight of asphalt mixture) and lengths (ie, 4, 8, and 12 mm) are incorporated into asphalt mixture to prepare fibre‐reinforced asphalt mixtures. Fracture tests are then carried out on these mixtures under four different modes of loading (i.e., pure mode I, pure mode II, and two mixed modes of I/II) using semicircular bend (SCB) specimens. The results exhibit that the fracture toughness increases with the enhancement of the fibre content. In addition, increase in the length of basalt fibre results in reduction of the fracture toughness of asphalt mixture. However, the asphalt mixture containing 0.3% of basalt fibres with the length of 4 mm shows the highest fracture toughness compared with other mixtures. It is also found that the basalt fibre improves mode I fracture toughness of asphalt mixtures more significantly than mode II one. Statistical analysis is also performed on the experimental data. Analysis of ANOVA demonstrates that all the three factors investigated in this study (i.e., length of basalt fibre, content of basalt fibre, and mode of loading) have significant influence on the fracture toughness of asphalt mixtures. [ABSTRACT FROM AUTHOR]

Summary: Mixture regression models have been widely used in business, marketing and social sciences to model mixed regression relationships arising from a clustered and thus heterogeneous population. The unknown mixture regression parameters are usually estimated by maximum likelihood estimators using the expectation–maximisation algorithm based on the normality assumption of component error density. However, it is well known that the normality‐based maximum likelihood estimation is very sensitive to outliers or heavy‐tailed error distributions. This paper aims to give a selective overview of the recently proposed robust mixture regression methods and compare their performance using simulation studies. [ABSTRACT FROM AUTHOR]

The preparation process and the final properties of new thermoplastic lead‐free medium voltage (MV) insulation compounds based on the thermoplastic vulcanized (TPV) technology are reported and discussed at molecular level. The TPV MV insulation compounds were prepared starting from a peroxide curable lead free MV insulation, which is the actual market benchmark. For this reason, they were extensively investigated in comparison to the standard lead free MV insulation. The results of the dynamic vulcanization process were evaluated and related to the formulation. Now in the present paper we are reporting a detailed analysis of the molecular changes induced by the vulcanization reaction with reference to the different polymers and low molecular weight additives present in the starting mixture. The results are analyzed with reference to the used polyolefins structure with the aim to provide insights helping to relate the formulation at molecular level to the behavior of the final complex materials thus offering an useful tool to a priori design of TPVs with the desired ultimate properties. [ABSTRACT FROM AUTHOR]

We consider the problem of detection of features in the presence of clutter for spatio‐temporal point patterns. In previous studies, related to the spatial context, Kth nearest‐neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation‐maximization algorithm. This paper extends this methodology to the spatio‐temporal context by considering the properties of the spatio‐temporal Kth nearest‐neighbor distances. For this purpose, we make use of a couple of spatio‐temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions of such Kth nearest‐neighbor distances and present an intensive simulation study together with an application to earthquakes. [ABSTRACT FROM AUTHOR]

This paper presents a bi‐level model to optimize automated‐vehicle‐friendly subnetworks in urban road networks and an efficient algorithm to solve the model, which is relevant for the transition period with vehicles of different automation levels. We formulate the problem as a network design problem, define solution requirements, present an effective solution method that meets those requirements, and compare its performance with two other solution algorithms. Numerical examples for network of Delft are presented to demonstrate the concept and solution algorithm performances. Results indicate that our proposed solution outperforms competing ones in all criteria considered. Furthermore, our findings show that the optimal configuration of these subnetworks depends on the level of demand; lower penetration rates of automated vehicles call for less dense subnetworks, and thereby less investments. Nonetheless, a large proportion of benefits are already achievable with low‐density subnetworks. Denser subnetworks can deliver higher benefits with higher penetration rates. [ABSTRACT FROM AUTHOR]

The study presented in this paper aimed at evaluating the impact of different nanosized additives, including an organophilic nanoclay and multiwall carbon nanotubes, on the fatigue properties of dense‐graded asphalt mixtures. Cyclic direct tension fatigue tests were carried out, and the corresponding results were interpreted by means of a simplified version of the visco‐elastic continuum damage model. The experimental investigation also included linear viscoelastic characterization of the considered materials. Results derived from tests carried out on the mixtures containing nanosized additives were compared with those obtained for a reference standard mixture. It was found that the use of the abovementioned additives can give a substantial contribution to the enhancement of the fatigue damage resistance of asphalt mixtures. Moreover, when comparing the two types of additives, it was observed that organophilic nanoclays can outperform multiwall carbon nanotubes. [ABSTRACT FROM AUTHOR]

Miscible fluid mixtures, like pouring honey into water, Coca Cola into strong wine, are common phenomena in our daily life. While two miscible fluids are mixed together, their appearances in terms of colors and shapes will change due to their mixing interaction. The interaction between the mixture components could be regarded as a combination of the diffusing process and demixing process. If the former dominates the interaction, it is miscible; otherwise, it is immiscible. The complex microscopic interplay between the mixture components makes the simulation highly challenging. So far, there have been some dedicated research in computer graphics dealing with immiscible mixtures, but few works have been done focusing on miscible mixtures. In this paper, for the first time, we introduce a two-fluid lattice Boltzmann method (LBM), called TFLBM, applied to miscible binary mixtures. Different from other similar methods, the viscous and diffusing properties of the fluid in our work are considered separately, so that the physical insight is exposed more clearly and rationally. In addition, the operation of LBM is mostly a linear local computation, and graphics processing unit (GPU) has been utilized to achieve real-time simulation. Copyright © 2006 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Background: Many alcohol research questions require methods that take a person-centered approach because the interest is in finding heterogeneous groups of individuals, such as those who are susceptible to alcohol dependence and those who are not. A person-centered focus also is useful with longitudinal data to represent heterogeneity in developmental trajectories. In alcohol, drug, and mental health research the recognition of heterogeneity has led to theories of multiple developmental pathways. Methods: This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. Methods discussed include latent class analysis, latent transition analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. These methods are presented in a general latent variable modeling framework that expands traditional latent variable modeling by including not only continuous latent variables but also categorical latent variables. Results: Four examples that use the National Longitudinal Survey of Youth (NLSY) data are presented to illustrate latent class analysis, latent class growth analysis, growth mixture modeling, and general growth mixture modeling. Latent class analysis of antisocial behavior found four classes. Four heavy drinking trajectory classes were found. The relationship between the latent classes and background variables and consequences was studied. Conclusions: Person-centered and variable-centered analyses typically have been seen as different activities that use different types of models and software. This paper gives a brief overview of new methods that integrate variable- and person-centered analyses. The general framework makes it possible to combine these models and to study new models serving as a stimulus for asking research questions that have both person- and variable-centered aspects. [ABSTRACT FROM AUTHOR]

Sesquiterpene lactones (SL) have been reported with various biological effects. Among the described SL skeletons, hirsutinolide and glaucolide have not been extensively studied by mass spectrometry (MS), especially how to distinguish them in organic matrices. Thus, this paper reports (1) a strategy of their differentiation based on MS behavior during the ionization and (2) a proposal of the fragmentation pattern for both SL‐subtypes. ESI(+)‐HRMS data of four isolated SL (hirsutinolides 1 and 3; glaucolides 2 and 4) were recorded by direct and UPLC water‐sample combined injections. These analyses revealed that hirsutinolides and glaucolides formed [M+Na]+ ion during the operation of the direct MS injection, and ([M+Na]+ and [M+H‐H2O]+) and [M+H]+ ions were respectively observed for hirsutinolides and glaucolides during the operation of combined UPLC water and sample MS injection. Computational simulations showed that the complex hirsutinolide (1)‐Na+ formed with a lower preparation energy compared with the complex glaucolide (2)‐Na+. However, despite their different behavior during the ionization process, ESI(+)‐HRMS/MS analyses of 1‐4 gave similar fragmentation patterns at m/z 277, 259, 241, and 231 that can be used as diagnostic ions for both skeletons. Moreover, the differentiation strategy based on the nature of the complex SL‐adducts and their MS/MS fragmentation pattern were successfully applied for the chemical characterization of the extract from Vernonanthura tweedieana using UPLC‐ESI‐HRMS/MS. Among the characterized metabolites, SL with hirsutinolide and glaucolide skeletons showed the aforementioned diagnostic fragments and an ionization behavior that was similar to those observed during the water‐sample combined injection. [ABSTRACT FROM AUTHOR]

In the present paper, the analysis of thermal modes of solid phase synthesis in the volume of mechanically activated powder mixtures was conducted. As a basic model, the Carter‐Valensi model of solid phase interaction in powder systems was used. This model was considered from point of view of non‐isothermal kinetics for the first time. Using the maximum temperature method, the critical ignition conditions of the mixture and the conditions of thermal explosion degeneration were determined. The corresponding diagrams of critical parameters were obtained and the parametric regions of thermal explosion existence were defined. The results presented allows solving the technologically important problem of demarcation of fast (thermal explosion) and slow (isothermal sintering) synthesis modes. Thus, it becomes possible to control the chemical activity of a heterogeneous reaction purposefully. [ABSTRACT FROM AUTHOR]

Recent discussions on a forensic discussion group highlighted the prevalence of a practice in the application of inclusion probabilities when dropout is possible that is of significant concern. In such cases, there appears to be an unpublished practice of calculation of an inclusion probability only for those loci at which the profile of interest (hereafter the suspect) is fully included among the alleles present in the crime scene sample and to omit those loci at which the suspect has alleles that are not fully represented among the alleles in the mixture. The danger is that this approach may produce apparently strong evidence against a surprisingly large fraction of noncontributors. In this paper, the risk associated with the approach of ignoring loci with discordant alleles is assessed by simulation. [ABSTRACT FROM AUTHOR]

Abstract: The dielectric pulse effect is of interest for many applications such as sensors, smart triggers, and energy storage. In this paper, a general approach to achieve a room temperature dielectric pulse effect via solid–liquid phase transition in organic mixtures formed by conductive surfactants and insulating fluid is introduced. The dielectric pulse is caused by the self‐formed blocking layer appearing during the solid–liquid phase transition by mixing Span80 and hexadecane. Using 50 Vol% Span80/hexadecane mixture, the dielectric peak intensity of 1191.6 is achieved at 11.9 °C. The dielectric peak intensity and the trigger temperature of mixtures can be tuned by changing the proportions of the components, the temperature ramping rate, and the components. The generality of the approach is also demonstrated in other organic matter such as Span series, alcohols, alkanes and their mixtures. [ABSTRACT FROM AUTHOR]