Academic literature on the topic 'Mixture missing mechanisms'

AbstractWe present an approach to inform decisions about nonresponse follow-up sampling. The basic idea is (i) to create completed samples by imputing nonrespondents’ data under various assumptions about the nonresponse mechanisms, (ii) take hypothetical samples of varying sizes from the completed samples, and (iii) compute and compare measures of accuracy and cost for different proposed sample sizes. As part of the methodology, we present a new approach for generating imputations for multivariate continuous data with nonignorable unit nonresponse. We fit mixtures of multivariate normal distributions to the respondents’ data, and adjust the probabilities of the mixture components to generate nonrespondents’ distributions with desired features. We illustrate the approaches using data from the 2007 U.S. Census of Manufactures.

Abstract Social isolation is a public health issue that is linked to poor health outcomes. However, the mechanisms underlying this association remain unclear. The main objective of this study was to explore whether changes in frailty moderated the relationship between changes in social isolation and changes in health outcomes over two years. We examined the mediating role of changes in frailty when the moderation hypothesis was not supported. A series of latent growth models (LGMs) were used to test our objectives using data from three waves of the FRéLE study among 1643 Canadian community-dwelling older adults aged 65 years and over. Missing data were handled by pattern mixture models with the assumption of missing not at random. We measured social isolation through social participation, social networks, and social support from different sources of social ties. We assessed frailty using the Fried frailty phenotype. Our moderation results revealed that high levels of changes in social participation, support from friends, nuclear, and extended family members, and social contacts with friends were associated with greater changes in cognitive and mental health among frail older adults with diminished physiological reserves compared to robust older adults. Additionally, changes in frailty mediated the effects of changes in social participation and social contacts and support from friends on changes in chronic conditions. This longitudinal study suggests that frailty moderated the relationships between social isolation and mental and cognitive health but not physical health. Overall, social support and strong friendship ties are key determinants of frail older adults’ health.

All-inorganic cesium lead bromine (CsPbBr3) perovskites have gained a tremendous potential in optoelectronics due to interesting photophysical properties and much better stability than the hybrid counterparts. Although pulsed laser deposition (PLD) is a promising alternative to solvent-based and/or thermal deposition approaches due to its versatility in depositing multi-elemental materials, deep understanding of the implications of both target composition and PLD mechanisms on the properties of CsPbBr3 films is still missing. In this paper, we deal with thermally assisted preparation of mechano-chemically synthesized CsPbBr3 ablation targets to grow CsPbBr3 films by PLD at the fluence 2 J/cm2. We study both Cs rich- and stoichiometric PbBr2-CsBr mixture-based ablation targets and point out compositional deviations of the associated films resulting from the mass distribution of the PLD-generated plasma plume. Contrary to the conventional meaning that PLD guarantees congruent elemental transfer from the target to the substrate, our study demonstrates cation off-stoichiometry of PLD-grown CsPbBr3 films depending on composition and thermal treatment of the ablation target. The implications of the observed enrichment in the heavier element (Pb) and deficiency in the lighter element (Br) of the PLD-grown films are discussed in terms of optical response and with the perspective of providing operative guidelines and future PLD-deposition strategies of inorganic perovskites.

This article introduces a robust extension of the mixture of factor analysis models based on the restricted multivariate skew- t distribution, called mixtures of skew- t factor analysis (MSTFA) model. This model can be viewed as a powerful tool for model-based clustering of high-dimensional data where observations in each cluster exhibit non-normal features such as heavy-tailed noises and extreme skewness. Missing values may be frequently present due to the incomplete collection of data. A computationally feasible EM-type algorithm is developed to carry out maximum likelihood estimation and create single imputation of possible missing values under a missing at random mechanism. The numbers of factors and mixture components are determined via penalized likelihood criteria. The utility of our proposed methodology is illustrated through analysing both simulated and real datasets. Numerical results are shown to perform favourably compared to existing approaches.

Abstract. The fraction of gasoline direct-injection (GDI) vehicles comprising the total vehicle pool is projected to increase in the future. However, thorough knowledge about the influence of GDI engines on important atmospheric chemistry processes is missing – namely, their contribution to secondary organic aerosol (SOA) precursor emissions, contribution to SOA formation, and potential role in biogenic–anthropogenic interactions. The objectives of this study were to (1) characterize emissions from modern GDI vehicles and investigate their role in SOA formation chemistry and (2) investigate biogenic–anthropogenic interactions related to SOA formation from a mixture of GDI-vehicle emissions and a model biogenic compound, α-pinene. Specifically, we studied SOA formation from modern GDI-vehicle emissions during the constant-load driving. In this study we show that SOA formation from GDI-vehicle emissions was observed in each experiment. Volatile organic compounds (VOCs) measured with the proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) could account for 19 %–42 % of total SOA mass generated in each experiment. This suggests that there were lower-volatility intermediate VOCs (IVOCs) and semi-volatile organic compounds (SVOCs) in the GDI-vehicle exhaust that likely contributed to SOA production but were not detected with the instrumentation used in this study. This study also demonstrates that two distinct mechanisms caused by anthropogenic emissions suppress α-pinene SOA mass yield. The first suppressing effect was the presence of NOx. This mechanism is consistent with previous reports demonstrating suppression of biogenic SOA formation in the presence of anthropogenic emissions. Our results indicate a possible second suppressing effect, and we suggest that the presence of anthropogenic gas-phase species may have suppressed biogenic SOA formation by alterations to the gas-phase chemistry of α-pinene. This hypothesized change in oxidation pathways led to the formation of α-pinene oxidation products that most likely did not have vapor pressures low enough to partition into the particle phase. Overall, the presence of gasoline-vehicle exhaust caused a more than 50 % suppression in α-pinene SOA mass yield compared to the α-pinene SOA mass yield measured in the absence of any anthropogenic influence.

We previously reported that parthenogenetic stem cells display abnormal centrosome and spindle formation that results in severe chromosome missegregation, with a high incidence of hypoploid karyotypes. Unexpectedly, this is not accompanied by a correspondingly high rate of apoptosis and, by contrast, parthenogenetic cells share the pluripotency, self-renewal and in vitro differentiation properties of their bi-parental counterparts. We hypothesise that this is possible through a series of adaptive mechanisms that include the presence of intercellular bridges similar to those that connect germ cells during spermatogenesis. This would provide a way for mutual exchange of missing cell products, thus alleviating the unbalanced chromosome distribution that would otherwise hamper normal cell functions. The presence of intercellular bridges was investigated in pig parthenogenetic embryonic stem cells (PESC) by transmission electron microscopy (TEM). Cultured cells were fixed in 2% glutaraldehyde and post-fixed in 1% osmic acid. After standard dehydration in ethanol series, samples were embedded in an Epon-Araldite 812 mixture and sectioned with a Reichert Ultracut S ultratome (Leica). Thin sections were stained and observed with a Jeol 1010 electron microscope. Pig PESC were also subjected to scanning electron microscopy (SEM). To this purpose, they were fixed and dehydrated as described above, covered with a 9-nm gold film by flash evaporation of carbon in an Emitech K 250 sputter coater (Emitech) and examined with an SEM-FEG Philips XL-30 microscope. To demonstrate functional trafficking activity through intercellular canals, fluorescent 10-kDa dextran was injected into the cytoplasm of a single cell with FemtoJet Microinjector (Eppendorf). Movement of the molecule from the injected cell to others was observed with a Nikon Eclipse TE200 microscope. Ultra-structural analysis of PESC demonstrated the existence of intercellular bridges that ensured cytoplasmic continuity among cells. These canals appeared variable in size and were characterised by the presence of stabilising actin patches. Furthermore, extensive movement of 10-kDa dextran among cells demonstrated functional intercellular trafficking through these communication canals, suggesting their use for transfer of mRNA, proteins and ribosomes among cells. Our results demonstrate that PESC present a wide network of functional intercellular bridges that may constitute an adaptive mechanism to support normal cell functions. This process is commonly observed in transformed cells and gives further support to the recent hypothesis that suggests the existence of common features and links between oncogenesis and self-renewal in pluripotent cell lines. Supported by AIRC IG 10376. PG was supported by INGM.

The elasticity (nutrient storage, litter decomposition, bioturbation of soil) and diversity of central European forest ecosystems has been reduced by centuries of overutilization. Since the middle of the nineteenth century, their development has been influenced by silvicultural measures, as well as by the deposition of acids and nutrients, especially nitrogen from anthropogenic sources, i.e., by a mixture of stabilizing and destabilizing external influences. During recent decades, most forest soils have been acidified by acid deposition resulting in low levels of nutrient cations and negative alkalinity in the soil solution. Widespread acute acidification of soil in the rooting zone is indicated by extremely high manganese (Mn) contents in leaves (fingerprint). Soil acidification has caused drastic losses of fine roots in subsoil, indicated by denuded structural root systems where adventitious fine root complexes exist only sporadically. Research at the organ (leaf, fine root, mycorrhiza) and cellular levels has provided much information on the effects of air pollutants and soil acidification on leaves and roots. There are considerable uncertainties, however, as to how changes in the status of leaves or roots are processed within the tree and ecosystem from one level of hierarchy to the next on an increasing spatial and time scale, and how these lead to decline symptoms like crown thinning, stand opening (as a consequence of dieback or perturbations), and changes in species composition (soil biota, ground vegetation, tree regeneration). At the tree level, nutrient imbalances (due to cation losses from soil, changes in the acid/base status of the soil, proton buffering in leaves, and N deposition), as well as disturbances in the transport system of assimilates and water, are suspected of causing the decline symptoms. Information on the filtering mechanisms at various hierarchical levels, especially in the case of a break in the hierarchy, is missing. The null hypothesis (no effects of air pollutants on forest ecosystems) can be considered to be falsified. Forest ecosystems are in transition. The current state of knowledge is not sufficient to define precisely the final state that will be reached, given continuously changing environmental conditions and human impacts. The hypothesis, however, of large-scale forest dieback in the near future is not backed by data and can be discarded.Key words: forest ecosystem, process hierarchy, air pollution, deposition, acidity, nitrogen.

Popular theories in political science regarding opinion-changing behavior postulate the existence of one or both of two broad categories of people: those with stable opinions over time; and those who appear to hold no solid opinion and, when asked to make a choice, do so seemingly at random. The model presented here explores evidence for a third category: durable changers. People in this group will change their opinions in a rational, informed manner, after being exposed to new information. Survey data collected at four time points over nearly two years track Swiss citizens' readiness to support pollution-reduction policies. We analyzed the data using finite mixture models that allow estimation of the percentage in the poluation falling in each category for each question as well as the frequency of certain types of relevant behaviors within each category. These models extend the finite mixture model structure used in Hill and Kriesi (2001a,b) to accommodate missing response data. This extension increases the sample size by nearly 60% and weakens the missing-data assumptions required. We describe augmented models and fitting algorithms corresponding to different assumptions about the missing-data mechanism as well as the differences in results obtained.

Purpose The prevalence estimates of binary variables in sample surveys are often subject to two systematic errors: measurement error and nonresponse bias. A multiple-bias analysis is essential to adjust for both biases. Methods In this paper, we linked the latent class log-linear and proxy pattern-mixture models to adjust jointly for measurement errors and nonresponse bias with missing not at random mechanism. These methods were employed to estimate the prevalence of any illicit drug use based on Iranian Mental Health Survey data. Results After jointly adjusting for measurement errors and nonresponse bias in this data, the prevalence (95% confidence interval) estimate of any illicit drug use changed from 3.41 (3.00, 3.81)% to 27.03 (9.02, 38.76)%, 27.42 (9.04, 38.91)%, and 27.18 (9.03, 38.82)% under “missing at random,” “missing not at random,” and an intermediate mode, respectively. Conclusions Under certain assumptions, a combination of the latent class log-linear and binary-outcome proxy pattern-mixture models can be used to jointly adjust for both measurement errors and nonresponse bias in the prevalence estimation of binary variables in surveys.

Abstract A common problem in multi-environment trials arises when some genotypeby- environment combinations are missing. In Arciniegas-Alarcón et al. (2010) we outlined a method of data imputation to estimate the missing values, the computational algorithm for which was a mixture of regression and lower-rank approximation of a matrix based on its singular value decomposition (SVD). In the present paper we provide two extensions to this methodology, by including weights chosen by cross-validation and allowing multiple as well as simple imputation. The three methods are assessed and compared in a simulation study, using a complete set of real data in which values are deleted randomly at different rates. The quality of the imputations is evaluated using three measures: the Procrustes statistic, the squared correlation between matrices and the normalised root mean squared error between these estimates and the true observed values. None of the methods makes any distributional or structural assumptions, and all of them can be used for any pattern or mechanism of the missing values.

Nesta tese apresentam-se desenvolvimentos metodológicos para analisar dados com omissão e também estudos delineados para compreender os resultados de tais análises. Escrutinam-se análises de sensibilidade bayesiana e clássica para dados com respostas categorizadas sujeitas a omissão. Mostra-se que as componentes subjetivas de cada abordagem podem influenciar os resultados de maneira não-trivial, independentemente do tamanho da amostra, e que, portanto, as conclusões devem ser cuidadosamente avaliadas. Especificamente, demonstra-se que distribuições \\apriori\\ comumente consideradas como não-informativas ou levemente informativas podem, na verdade, ser bastante informativas para parâmetros inidentificáveis, e que a escolha do modelo sobreparametrizado também tem um papel importante. Quando há omissão em variáveis explicativas, também é necessário propor um modelo marginal para as covariáveis mesmo se houver interesse apenas no modelo condicional. A especificação incorreta do modelo para as covariáveis ou do modelo para o mecanismo de omissão leva a inferências enviesadas para o modelo de interesse. Trabalhos anteriormente publicados têm-se dividido em duas vertentes: ou utilizam distribuições semiparamétricas/não-paramétricas, flexíveis para as covariáveis, e identificam o modelo com a suposição de um mecanismo de omissão não-informativa, ou empregam distribuições paramétricas para as covariáveis e permitem um mecanismo mais geral, de omissão informativa. Neste trabalho analisam-se respostas binárias, combinando um mecanismo de omissão informativa com um modelo não-paramétrico para as covariáveis contínuas, por meio de uma mistura induzida pela distribuição \\apriori\\ de processo de Dirichlet. No caso em que o interesse recai apenas em momentos da distribuição das respostas, propõe-se uma nova análise de sensibilidade sob o enfoque clássico para respostas incompletas que evita suposições distribucionais e utiliza parâmetros de sensibilidade de fácil interpretação. O procedimento tem, em particular, grande apelo na análise de dados contínuos, campo que tradicionalmente emprega suposições de normalidade e/ou utiliza parâmetros de sensibilidade de difícil interpretação. Todas as análises são ilustradas com conjuntos de dados reais.
We present methodological developments to conduct analyses with missing data and also studies designed to understand the results of such analyses. We examine Bayesian and classical sensitivity analyses for data with missing categorical responses and show that the subjective components of each approach can influence results in non-trivial ways, irrespectively of the sample size, concluding that they need to be carefully evaluated. Specifically, we show that prior distributions commonly regarded as slightly informative or non-informative may actually be too informative for non-identifiable parameters, and that the choice of over-parameterized models may drastically impact the results. When there is missingness in explanatory variables, we also need to consider a marginal model for the covariates even if the interest lies only on the conditional model. An incorrect specification of either the model for the covariates or of the model for the missingness mechanism leads to biased inferences for the parameters of interest. Previously published works are commonly divided into two streams: either they use semi-/non-parametric flexible distributions for the covariates and identify the model via a non-informative missingness mechanism, or they employ parametric distributions for the covariates and allow a more general informative missingness mechanism. We consider the analysis of binary responses, combining an informative missingness model with a non-parametric model for the continuous covariates via a Dirichlet process mixture. When the interest lies only in moments of the response distribution, we consider a new classical sensitivity analysis for incomplete responses that avoids distributional assumptions and employs easily interpreted sensitivity parameters. The procedure is particularly useful for analyses of missing continuous data, an area where normality is traditionally assumed and/or relies on hard-to-interpret sensitivity parameters. We illustrate all analyses with real data sets.

This introductory chapter provides an overview of the French imperial empire in the nineteenth century. France after Napoleon did not renounce empire. Instead, it became less interested in formal conquest and experimented with novel techniques of imperial domination. French proponents of informal empire usually looked back on the 1789 Revolution with a mixture of disillusion and dismay, while its collaborators outside France were mostly conservatives bent on reconciling economic modernization with the defence of their privileges. This informal civilizing mission was, in many respects, counter-revolutionary. Counter-revolutionary commitment to capitalism went hand in hand with a collaborative style of imperialism. Ultimately, France's largely informal empire made a significant contribution to nineteenth-century globalization, even if it employed subtler mechanisms of coercion and collaboration than the more formal British Empire ever did.

Pulsed detonation engines are considered to be the promising e¨ective propulsion systems for future space missions. The ignition system has always posed problems in commercial applications. Many experimental, theoretical, and numerical studies have been performed for the past years and various ignition systems (e. g., electric discharge, microwave discharge, laser radiation) have been tested. The propulsive performance of air-breathing pulsed detonation engines (PDEs) has been theoretically and numerically studied over a wide range of system con¦gurations, operating parameters, and §ight conditions. It has been suggested that discharges which create the quickest expanding high-temperature region or discharges which occupy a large volume are optimal for ignition because they can most rapidly and reliably bring the radius of the ignition kernel to its critical value for transition into a self-propagating §ame. Signi¦cant e¨orts are being spent on acceleration of fuel combustion and rising its e©ciency. Existing studies have mainly focused on optimizing fuel injection and mixing, repetitive initiation of detonation, and integration of detonation tubes with fuel inlets. Understanding of streamer propagation mechanism is of essential importance for the studies of electrical breakdown phenomena and their related applications. In this study, a subcritical microwave streamer discharge is used to initiate ignition of air fuel mixtures. The study focuses on investigation of possibilities of the use of microwave radiation to initiate combustion and detonation of air fuel mixtures. The results of experimental and computational studies related combustion and detonation of air propane mixture are presented. To initiate the combustion and detonation, the deep subcritical streamer discharge is used. The discharge is formed by a ¦eld with the intensity smaller than the minimum pulse intensity leading to the gas breakdown. An acceleration of combustion and a uniform temperature front are obtained and the possibility of combustion of fuel-lean mixture is con¦rmed. An increase in combustion e©ciency is also observed. Streamer discharge ignition of particularly lean air fuel mixture with air-to-fuel ratio greater than the §ammability limit has been demonstrated under normal conditions. The indirect evidence suggests that the ignition by the microwave discharge is of the nonthermal nature. The advantages of igniting the fuel mixture by streamer discharge is attributed to the ultraviolet radiation emitted by oxygen atoms subjected to the discharge. The ultraviolet radiation generation causes formation of the nonequilibrium cold plasma with avalanche increase in the number of free electrons. The microwave streamer ignition can be considered for the application in internal combustion engines to replace the conventional spark ignition.

The mission of the United States Military Academy (USMA) is “To educate, train, and inspire the Corps of Cadets so that each graduate is a commissioned leader of character committed to the values of Duty, Honor, Country; professional growth throughout a career as an officer in the United States Army; and a lifetime of selfless service to the nation.” [1] The academic program at the USMA is designed to meet the intellectual demands of this mission statement. One very unique aspect of this academic program is the requirement that each cadet take a minimum of five engineering courses regardless of his or her major or field of study. Because of this requirement, nearly one-third of every graduating class take Fluid Mechanics. The Fluid Mechanics course taught in the USMA’s Department of Civil and Mechanical Engineering differs from others throughout the country for two primary reasons: 1) Within every class there is a mixture of cadets majoring in engineering and those who are in other majors, such as languages, history, and political science, 2) Each cadet will be commissioned as a Second Lieutenant in the United States Army immediately upon graduation, [2] and [3]. In this course cadets learn about fluid mechanics and apply the principles to solve problems, with emphasis placed upon those topics of interest to the Army and Army systems that they will encounter as future officers. The course objectives are accomplished through four principal methods. The first is through engaging, interactive classroom instruction. Cadets learn about the principles of fluid statics, conservation laws, dimensional analysis, and external flow; specialized topics, such as compressible flow and open channel flow have also been integrated. The second method is through hands-on laboratory exercises. Pipe friction, wind tunnels, and smoke tunnels are examples of laboratories in which cadets take experimental measurements, analyze data, and reinforce concepts from the classroom. The third method occurs in the “Design of an Experiment” exercise. In groups, cadets design their own experiment—based upon an Army parachutist—that will predict the coefficient of drag of a parachute system. The fourth method is a hands-on design project that culminates in a competition. In teams, cadets build a water turbine to lift a weight on a pulley from ground level to a designated height. Competition categories include the torque competition, in which maximum lifted weight determines the winner and the power competition judged by minimum time to lift a designated weight. This project, implemented within the curriculum prior to formal instruction on the design process, requires cadets to develop their own design process through analysis, experimentation, and trial and error.