The potential value of mosses for stormwater management in urban environments

Plant-based stormwater management systems such as green roofs are typically composed exclusively of vascular plants. Yet, mosses have several desirable properties that could warrant their more widespread use in green roof applications. In natural systems mosses are important primary colonizers of bare ground, and their establishment improves water storage and provides numerous soil benefits including carbon and nitrogen sequestration. Additionally, mosses often facilitate the establishment and survival of vascular plants at otherwise environmentally harsh or stressful sites. Despite their potential value, few studies have investigated the functional performance of mosses on green roofs. In this study we evaluated the establishment success and potential stormwater performance of three candidate moss species. We also directly compared the runoff and thermal characteristics of replicate moss covered green roofs to vascular planted and bare roofs. Candidate mosses had high water holding capacities, storing 8–10 times their weight in water compared to only 1.3 times for typical green roof medium. Mock-up roof sections composed of mosses and medium had delayed and reduced runoff flows relative to medium only sections, although the magnitude of these effects varied with moss species. In field trials all three mosses survived a harsh rooftop environment with limited summer irrigation, although lateral growth after one year was minimal. Green roofs planted solely with Racomitrium canescens had between 12–24% higher stormwater retention than vascular or medium only roofs. Moss cover also ameliorated temperature fluctuations on green roofs. Hourly heating rates were buffered to a similar degree (less than half that of surface temperatures) 5 cm below the surface of both moss covered and medium only roofs. In contrast, cooling under the surface of the moss roof was nearly 6 times faster than under the medium only roof. These results demonstrate the potential for mosses to be valuable components of green roofs, either in combination with vascular plants or planted exclusively.     

The big story about small stories: Narratives of crime and terrorism

The ‘big story/small story’ distinction has emerged as a discrete approach to narrative analysis. Proponents of this approach are critical of the ‘big stories’ elicited by structural analysts, which they see as highly structured narratives of past experiences, typically elicited in an interview context. In contrast, they highlight the importance of studying the fragmented, contextualised ‘small stories’ that arise in everyday conversation/interaction. We question the basis of this distinction and we suggest that it unnecessarily proliferates analytic categories. Further, we suggest that the methodologies followed by ‘small stories’ analysts are often similar to those used to elicit ‘big stories’ and are hence open to similar criticisms; in particular, a failure to fully consider the issue of (contextual) naturalism. Drawing on interviews of crime/terrorism in Northern Ireland, we show how these data comprise both ‘big stories’ and ‘small stories’ within the same context and often within the same narrative.     

Testing for qualitative interaction of multiple sources of informative dropout in longitudinal data

Longitudinal studies suffer from patient dropout. The dropout process may be informative if there exists an association between dropout patterns and the rate of change in the response over time. Multiple patterns are plausible in that different causes of dropout might contribute to different patterns. These multiple patterns can be dichotomized into two groups: quantitative and qualitative interaction. Quantitative interaction indicates that each of the multiple sources is biasing the estimate of the rate of change in the same direction, although with differing magnitudes. Alternatively, qualitative interaction results in the multiple sources biasing the estimate of the rate of change in opposing directions. Qualitative interaction is of special concern, since it is less likely to be detected by conventional methods and can lead to highly misleading slope estimates. We explore a test for qualitative interaction based on simultaneous confidence intervals. The test accommodates the realistic situation where reasons for dropout are not fully understood, or even entirely unknown. It allows for an additional level of clustering among participating subjects. We apply these methods to a study exploring tumor growth rates in mice as well as a longitudinal study exploring rates of change in cognitive functioning for Alzheimer's patients.     

Borrowing Information across Populations in Estimating Positive and Negative Predictive Values

A marker's capacity to predict risk of a disease depends on disease prevalence in the target population and its classification accuracy, i.e. its ability to discriminate diseased subjects from non-diseased subjects. The latter is often considered an intrinsic property of the marker; it is independent of disease prevalence and hence more likely to be similar across populations than risk prediction measures. In this paper, we are interested in evaluating the population-specific performance of a risk prediction marker in terms of positive predictive value (PPV) and negative predictive value (NPV) at given thresholds, when samples are available from the target population as well as from another population. A default strategy is to estimate PPV and NPV using samples from the target population only. However, when the marker's classification accuracy as characterized by a specific point on the receiver operating characteristics (ROC) curve is similar across populations, borrowing information across populations allows increased efficiency in estimating PPV and NPV. We develop estimators that optimally combine information across populations. We apply this methodology to a cross-sectional study where we evaluate PCA3 as a risk prediction marker for prostate cancer among subjects with or without previous negative biopsy.     

一个新的稳健ARCH检验和YJ-GARCH模型

 众所周知,Engle (1982) 的ARCH检验对于条件均值模型误设并不稳健,特别地,当条件均值是非线性过程而我们仅对之建立线性模型时,它过度地拒绝真实的原假设,导致出现严重的水平扭曲 (size distortion)。因此,本文在文献当中首次利用Yeo-Johnson变换方法来转换均值模型的因变量以排除ARCH 过程中均值部分的非线性,进而提出一个新的稳健ARCH检验以及一个新的GARCH模型——Yeo-Johnson (YJ) GARCH模型。蒙特卡罗模拟结果表明,稳健的ARCH检验在水平 (size) 和势 (power) 方面的表现要显著优于Engle (1982) 的ARCH检验。对上证综指收益率的实证研究结果表明,YJ-GARCH模型的拟合效果要显著优于线性GARCH模型。     

Longitudinal dynamic analyses of cognition in the health and retirement study panel

The purpose of this paper is to highlight some classic issues in the measurement of change and to show how contemporary solutions can be used to deal with some of these issues. Five classic issues will be raised here: (1) Separating individual changes from group differences; (2) options for incomplete longitudinal data over time, (3) options for nonlinear changes over time; (4) measurement invariance in studies of changes over time; and (5) new opportunities for modeling dynamic changes. For each issue we will describe the problem, and then review some contemporary solutions to these problems base on Structural Equation Models (SEM). We will fit these SEM to using existing panel data from the Health & Retirement Study (HRS) cognitive variables. This is not intended as an overly technical treatment, so only a few basic equations are presented, examples will be displayed graphically, and more complete references to the contemporary solutions will be given throughout.     

Vendor Selection with Bundling: A Comment*

In a recent article by Rosenthal, Zydiak, and Chaudhry (1995), a mixed integer linear programming model was introduced to solve the vendor selection problem for the case in which the vendor can sell items individually or as part of a bundle. Each vendor offered only one type of bundle, and the buyer could purchase at most one bundle per vendor. The model employed n(m+ 1) binary variables, where n is the number of vendors and m is the number of products they sell. The existing model can lead to a purchasing paradox: it may force the buyer to pay more to receive less. We suggest a reformulation of the same problem that (i) eliminates this paradox and reveals a more cost-effective purchasing strategy; (ii) uses only n integer variables and significantly reduces the computational workload; and (iii) permits the buyer to purchase more than one bundle per vendor.     

Designing Lateral Organizations: An Analysis of the Benefits,Costs, and Enablers of Nonhierarchical Organizational Forms*

Twenty-first century organizations will require designs that enable them to cope with turbulent environments. Organizations have experimented with lateral organizational designs for this purpose, but research evidence concerning these forms is sparse. We analyzed data obtained from 512 employees within eight diverse organizations implementing flexible lateral organizations. Using a sequence comparison methodology, we were able to identify and categorize the major costs, benefits, and enablers associated with implementing these forms of complex organizations. Propositions for effectively managing lateral relations were tested and managerial implications were explored.     

Bias and precision of measures of survival gain from right‐censored data

In cost‐effectiveness analyses of drugs or health technologies, estimates of life years saved or quality‐adjusted life years saved are required. Randomised controlled trials can provide an estimate of the average treatment effect; for survival data, the treatment effect is the difference in mean survival. However, typically not all patients will have reached the endpoint of interest at the close‐out of a trial, making it difficult to estimate the difference in mean survival. In this situation, it is common to report the more readily estimable difference in median survival. Alternative approaches to estimating the mean have also been proposed. We conducted a simulation study to investigate the bias and precision of the three most commonly used sample measures of absolute survival gain – difference in median, restricted mean and extended mean survival – when used as estimates of the true mean difference, under different censoring proportions, while assuming a range of survival patterns, represented by Weibull survival distributions with constant, increasing and decreasing hazards. Our study showed that the three commonly used methods tended to underestimate the true treatment effect; consequently, the incremental cost‐effectiveness ratio (ICER) would be overestimated. Of the three methods, the least biased is the extended mean survival, which perhaps should be used as the point estimate of the treatment effect to be inputted into the ICER, while the other two approaches could be used in sensitivity analyses. More work on the trade‐offs between simple extrapolation using the exponential distribution and more complicated extrapolation using other methods would be valuable. Copyright © 2015 John Wiley & Sons, Ltd.     

Prosecuting the prosecutor: The makings of the Michael Morton Act

Prosecutorial misconduct is not a rare event, but it often goes undetected, unreported, or no action is taken by the criminal justice system. However, when one Texas prosecutor, Ken Anderson, served jail time for wrongfully prosecuting an innocent man, Michael Morton, for murdering his wife, he made history. Anderson withheld exculpatory evidence leading to Morton wrongfully serving 25 years before being released with new DNA evidence. However, Anderson only served a five-day sentence and $500 fine. We discuss the case in the context of inequality and legal realism in the criminal justice system. Also, we look at the implications and new legal action taken by the state of Texas to try and combat this problem, along with looking at these secretive occupational subcultures.