Improving confidence in tree species selection for challenging urban sites: a role for leaf turgor loss

High species diversity is argued to be the most important requisite for a resilient urban forest. In spite of this, there are many cities in the northern hemisphere that have very limited species diversity within their tree population. Consequently, there is an immense risk to urban canopy cover, if these over-used species succumb to serious pests or pathogens. Recognition of this should motivate the use of less commonly used species. Analysis of plant traits, such as the leaf water potential at turgor loss (Ψ_P0), can provide useful insights into a species’ capacity to grow in warm and dry urban environments. Therefore, the aim of this study was to evaluate Ψ_P0 of 45 tree species, the majority of which are rare in urban environments. To help evaluate the potential for using Ψ_P0 data to support future decision-making, a survey of professionals engaged with establishing trees in urban environments was also used to assess the relationship between the measured Ψ_P0 and the perceived drought tolerance of selected species. This study demonstrates that Ψ_P0 gives strong evidence for a species’ capacity to tolerate dry growing conditions and is a trait that varies substantially across species. Furthermore, Ψ_P0 was shown to closely relate to the experience of professionals involved in establishing trees in urban environments, thus providing evidence of its practical significance. Use of plant traits, such as Ψ_P0, should, therefore, give those specifying trees confidence to recommend non-traditional species for challenging urban environments.     

Mixtures of modified t-factor analyzers for model-based clustering,classification, and discriminant analysis

A novel family of mixture models is introduced based on modified t-factor analyzers. Modified factor analyzers were recently introduced within the Gaussian context and our work presents a more flexible and robust alternative. We introduce a family of mixtures of modified t-factor analyzers that uses this generalized version of the factor analysis covariance structure. We apply this family within three paradigms: model-based clustering; model-based classification; and model-based discriminant analysis. In addition, we apply the recently published Gaussian analogue to this family under the model-based classification and discriminant analysis paradigms for the first time. Parameter estimation is carried out within the alternating expectation-conditional maximization framework and the Bayesian information criterion is used for model selection. Two real data sets are used to compare our approach to other popular model-based approaches; in these comparisons, the chosen mixtures of modified t-factor analyzers model performs favourably. We conclude with a summary and suggestions for future work.     

You Wouldn't Like Me When I'm Angry: List Experiment Misreporting*

Objective. List experiment respondents may misreport the number of list items that they associate with in order to associate themselves with a socially desirable test item or to disassociate themselves from a socially undesirable test item. Tests for such misreporting were conducted. Methods. List experiments from the 1991 National Race and Politics Survey, the 2006 Cooperative Congressional Election Study, and the 2008 Cooperative Campaign Analysis Project were analyzed or reviewed. Results. Evidence suggested that some respondents deflated their report more than necessary to avoid association with a socially undesirable test item. Conclusions. List experiments may provide inaccurate estimates of the percentage of the population to which the test item applies, but the direction of bias is predictable.     

Doing Good,Public Good,and Public Value

In this article, using multiple illustrative case examples, we demonstrate that philanthropic institutions are in the business of creating public value. In framing the work of philanthropy more broadly to include the process of public value creation, philanthropic institutions and leaders are challenged to be more strategic not only in their mission‐fulfillment grant‐making with nonprofit organizations but also in the way they stimulate and encourage collaboration, create the “third space” necessary to incubate ideas to transform society, and leverage resources to increase the return on their investments toward system‐wide change. The implications for philanthropic actors and institutions suggest that the strategic contributions they make toward creation of public value are those that go beyond transactional performance measures, such as number of dollars spent or clients receiving services, to include ways that their investments are amplified by meaningful partnerships with nonprofit and other organizations, changed behaviors of institutions and individuals, and transformative public policies.     

Dirichlet models for square contingency tables

We consider the square contingency tables which arise when the same method of classification is applied twice. The hypothesis of marginal homogeneity is then relevant! and can be tested by various methods Models are discussed which contain marginal homogeneity as a special case. They include a class based on univariate and bivariate Dirichlet distributions. The question of ordered categories is briefly discussed. Applications are made to data on unaided distance vision.     

A new prototype system for optimized job shop scheduling

Optimal scheduling of shopfloor activities in an environment of discrete part manufacturing is discussed. The scheduling problem is a well known NP complete one. The main part, the sequencing problem, has been tackled using two techniques: virtual resources identification and taboo search heuristics. The first approach allowed the authors to reduce the complexity of the sequencing from a job shop to a general flow shop problem. On the other hand, the search for an optimal solution, with respect to a fixed strategy, has been achieved via the taboo search. A synthesis of the results of a large number of tests is presented as well as the results of an application to a real case. The latter is shown in comparison with the output of the system being presently used in the examined factory.     

Decentralized WIP-oriented manufacturing control (DEWIP)

DEWIP is a manufacturing control system for job shop environments aiming at achieving short and reliable lead times by establishing WIP control loops between the manufacturing work centres. The paper describes the mode of function, the setting of parameters and simulation results of the new manufacturing control system. The setting of parameters is done with the aid of the funnel model and the theory of logistic operating curves, both developed at the Institute of Production Systems at the University of Hanover. The simulation is conducted using industrial data and makes it possible to assess DEWIP with regard to lead times, WIP level, performance and schedule reliability. DEWIP is compared both with an uncontrolled process and with the manufacturing control systems Load oriented order release (LOOR), Conwip and Polca. The results suggest that DEWIP and the models employed for the setting of parameters are suitable for job shop production and therefore offer a valuable alternative to prevailing centralized manufacturing control systems.     

Nativity and Self‐Assessed Health among Pre‐Retirement Age Hispanics and Non‐Hispanic Whites1

Economic, social and familial resources are known to influence subjective health assessments. We examine the salience of nativity in determining how these resources influence self‐assessed health using a large, nationwide sample of Hispanic and non‐Hispanic white adults. The results indicate that while education, accumulated assets and marital status benefit the physical and emotional health of the native and foreign‐born, family resources and income are significant only for the native‐born. English language proficiency is a significant protective factor for both groups and is especially protective for immigrants. These surprising findings call into question previous studies stressing the positive role of the family in maintaining immigrant health.     

Causal Ordering of Basic Psychological Needs and Well-Being

What is the relationship between well-being and satisfaction of basic psychological needs overtime? The basic psychological needs theory is a subtheory of the self-determination theory that elaborates the concept of psychological needs and its relations to psychological health and well-being. The goals of this research was to establish the causal ordering between basic psychological needs and three psychological well-being indicators (subjective well-being, self-esteem and satisfaction with life), in a longitudinal study. We used a cross-lagged two-wave design. A total of 272 university students completed the questionnaire at the beginning and at the end of the semester. Relatedness at time 1 (T₁) had a positive and significant effect on all well-being indicators at time 2 (T₂); competence (T₁) had a positive and significant effect on all indicators except for self-esteem (T₂); finally, autonomy (T₁) did not have a significant effect on any of the well-being indicators (T₂). In conclusion, we confirm the causal ordering of competence and relatedness on well-being, according to the basic psychological needs subtheory. Universities, in general, and teachers, in particular, should promote relations between students and support the need of competence.