论文学语言的变异性

语言本身的非系统性与文学创作的审美特性是促进文学语言产生变异的重要原因。在创作过程中,作家要把握和表现那些有多种可能性、无限发展性的事物,要写出自己的独特感受,使文学语言只得“化常为变”,而语言的非系统性则提供了物质上的可能。文学语言的变异性表现为语音变异、语义变异和语法变异。     

Robust Control in Water Management

Since surface water flows are often stochastic, there is a role for water reservoirs in protecting users against uncertainty. We assume uncertainty regarding the probability distribution for the stochastic variable. Thus the decision allows for a range of approximate models that could be true, and the problem can be solved using robust optimal control. This paper analyses the implications of a robust framework on resource management decisions, using the case of water as an illustration. Robust choices are compared with those of a benchmark stochastic model and the emergence of precautionary behaviour is discussed.     

The Impact of Portfolio Location Uncertainty on Probabilistic Seismic Risk Analysis

Probabilistic seismic risk analysis is a well‐established method in the insurance industry for modeling portfolio losses from earthquake events. In this context, precise exposure locations are often unknown. However, so far, location uncertainty has not been in the focus of a large amount of research. In this article, we propose a novel framework for treatment of location uncertainty. As a case study, a large number of synthetic portfolios resembling typical real‐world cases were created. We investigate the effect of portfolio characteristics such as value distribution, portfolio size, or proportion of risk items with unknown coordinates on the variability of loss frequency estimations. The results indicate that due to loss aggregation effects and spatial hazard variability, location uncertainty in isolation and in conjunction with ground motion uncertainty can induce significant variability to probabilistic loss results, especially for portfolios with a small number of risks. After quantifying its effect, we conclude that location uncertainty should not be neglected when assessing probabilistic seismic risk, but should be treated stochastically and the resulting variability should be visualized and interpreted carefully.     

A Probabilistic Approach to Assess External Doses to the Public Considering Spatial Variability of Radioactive Contamination and Interpopulation Differences in Behavior Pattern

Dose assessment is an important issue from the viewpoints of protecting people from radiation exposure and managing postaccident situations adequately. However, the radiation doses received by people cannot be determined with complete accuracy because of the uncertainties and the variability associated with any process of defining individual characteristics and in the dose assessment process itself. In this study, a dose assessment model was developed based on measurements and surveys of individual doses and relevant contributors (i.e., ambient dose rates and behavior patterns) in Fukushima City for four population groups: Fukushima City Office staff, Senior Citizens’ Club, Contractors’ Association, and Agricultural Cooperative. In addition, probabilistic assessments were performed for these population groups by considering the spatial variability of contamination and interpopulation differences resulting from behavior patterns. As a result of comparison with the actual measurements, the assessment results for participants from the Fukushima City Office agreed with the measured values, thereby validating the model and the approach. Although the assessment results obtained for the Senior Citizens’ Club and the Agricultural Cooperative differ partly from the measured values, by addressing further considerations in terms of dose reduction effects due to decontamination and the impact of additional exposure sources in agricultural fields, these results can be improved. By contrast, the measurements obtained for the participants from the Contractors’ Association were not reproduced well in the present study. To assess the doses to this group, further investigations of association members’ work activities and the related dose reduction effects are needed.     

Quantifying Water Pathogen Risk in an Epidemiological Framework

Traditionally, microbial risk assessors have used point estimates to evaluate the probability that an individual will become infected. We developed a quantitative approach that shifts the risk characterization perspective from point estimate to distributional estimate, and from individual to population. To this end, we first designed and implemented a dynamic model that tracks traditional epidemiological variables such as the number of susceptible, infected, diseased, and immune, and environmental variables such as pathogen density. Second, we used a simulation methodology that explicitly acknowledges the uncertainty and variability associated with the data. Specifically, the approach consists of assigning probability distributions to each parameter, sampling from these distributions for Monte Carlo simulations, and using a binary classification to assess the output of each simulation. A case study is presented that explores the uncertainties in assessing the risk of giardiasis when swimming in a recreational impoundment using reclaimed water. Using literature-based information to assign parameters ranges, our analysis demonstrated that the parameter describing the shedding of pathogens by infected swimmers was the factor that contributed most to the uncertainty in risk. The importance of other parameters was dependent on reducing the a priori range of this shedding parameter. By constraining the shedding parameter to its lower subrange, treatment efficiency was the parameter most important in predicting whether a simulation resulted in prevalences above or below non outbreak levels. Whereas parameters associated with human exposure were important when the shedding parameter was constrained to a higher subrange. This Monte Carlo simulation technique identified conditions in which outbreaks and/or nonoutbreaks are likely and identified the parameters that most contributed to the uncertainty associated with a risk prediction.     

Risk Assessment of Listeria monocytogenes: Impact of Individual Cell Variability on the Exposure Assessment Step

Recently, the lag phase research in predictive microbiology is focusing more on the individual cell variability, especially for pathogenic microorganisms that typically occur in very low contamination levels, like Listeria monocytogenes. In this study, the effect of this individual cell lag phase variability was introduced in an exposure assessment study for L. monocytogenes in a liver paté. A basic framework was designed to estimate the contamination level of paté at the time of consumption, taking into account the frequency of contamination and the initial contamination levels of paté at retail. Growth was calculated on paté units of 150 g, comparing an individual-based approach with a classical population-based approach. The two different protocols were compared using simulations. If only the individual cell lag variability was taken into account, important differences were observed in cell density at the time of consumption between the individual-based approach and the classical approach, especially at low inoculum levels, resulting in high variability when using the individual-based approach. Although, when all variable factors were taken into account, no significant differences were observed between the different approaches, allowing the conclusion that the individual cell lag phase variability was overruled by the global variability of the exposure assessment framework. Even in more extreme conditions like a low inoculum level or a low water activity, no differences were created in cell density at the time of consumption between the individual-based approach and the classical approach. This means that the individual cell lag phase variability of L. monocytogenes has important consequences when studying specific growth cases, especially when the applied inoculum levels are low, but when performing more general exposure assessment studies, the variability between the individual cell lag phases is too limited to have a major impact on the total exposure assessment.     

Importance of Uncertainty and Variability to Predicted Risks from Trophic Transfer of PCBs in Dredged Sediments

Biomagnification of organochlorine and other persistent organic contaminants by higher trophic level organisms represents one of the most significant sources of uncertainty and variability in evaluating potential risks associated with disposal of dredged materials. While it is important to distinguish between population variability (e.g., true population heterogeneity in fish weight, and lipid content) and uncertainty (e.g., measurement error), they can be operationally difficult to define separately in probabilistic estimates of human health and ecological risk. We propose a disaggregation of uncertain and variable parameters based on: (1) availability of supporting data; (2) the specific management and regulatory context (in this case, of the U.S. Army Corps of Engineers/U.S. Environmental Protection Agency tiered approach to dredged material management); and (3) professional judgment and experience in conducting probabilistic risk assessments. We describe and quantitatively evaluate several sources of uncertainty and variability in estimating risk to human health from trophic transfer of polychlorinated biphenyls (PCBs) using a case study of sediments obtained from the New York-New Jersey Harbor and being evaluated for disposal at an open water off-shore disposal site within the northeast region. The estimates of PCB concentrations in fish and dietary doses of PCBs to humans ingesting fish are expressed as distributions of values, of which the arithmetic mean or mode represents a particular fractile. The distribution of risk values is obtained using a food chain biomagnification model developed by Gobas by specifying distributions for input parameters disaggregated to represent either uncertainty or variability. Only those sources of uncertainty that could be quantified were included in the analysis. Results for several different two-dimensional Latin Hypercube analyses are provided to evaluate the influence of the uncertain versus variable disaggregation of model parameters. The analysis suggests that variability in human exposure parameters is greater than the uncertainty bounds on any particular fractile, given the described assumptions.     

Human Interindividual Variability–A Major Source of Uncertainty in Assessing Risks for Noncancer Health Effects

For noncancer effects, the degree of human interindividual variability plays a central role in determining the risk that can be expected at low exposures. This discussion reviews available data on observations of interindividual variability in (a) breathing rates, based on observations in British coal miners; (b) systemic pharmacokinetic parameters, based on studies of a number of drugs; (c) susceptibility to neurological effects from fetal exposure to methyl mercury, based on observations of the incidence of effects in relation to hair mercury levels; and (d) chronic lung function changes in relation to long-term exposure to cigarette smoke. The quantitative ranges of predictions that follow from uncertainties in estimates of interindividual variability in susceptibility are illustrated.     

A variational model of preference under uncertainty

A familiar example devised by Daniel Ellsberg to highlight the effects of event ambiguity on preferences is transformed to separate aleatory uncertainty (chance) from epistemic uncertainty. The transformation leads to a lottery acts model whose states involve epistemic uncertainty; aleatory uncertainty enters into the statedependent lotteries. The model proposes von Neumann-Morgenstern utility for lotteries, additive subjective probability for states, and the use of across-states standard deviation weighted by a coefficient of aversion to variability to account for departures from Anscombe-Aumann subjective expected utility. Properties of the model are investigated and a partial axiomatization is provided.     

从模因论看网络新词语的构词特点

网络的普及导致一些网络词语迅速流行,这些网络流行词语在构词方面具有类比词和谐音词占主流、字母数字和图形符号混用等特点。按照模因论的观点,网络词语的流行相当于语言模因的复制与传播,模因、特别是强势模具有的变异性、时尚性是形成网络流行语构词特点的的内在动因。