Distinguishing between green building occupants’ reasoned and unplanned behaviours

Several frameworks incorporate social and psychological elements of environmentally significant behaviour, and most assume cognitive and deliberate decision-making. Household energy consumption behaviours, however, span a spectrum from reasoned and deliberate to unplanned and automatic. The aim of this paper is to advance knowledge of reasoned and unplanned behaviours in the context of pro-environmental action. Using results of a survey administered to occupants of an urban residential green building, this study explores five household consumption behaviours and tests the hypothesis that unplanned behaviours will be poorly predicted by a reasoned, values-based behavioural framework. Using path analyses, variables in a values-based framework are used to predict surveyed behaviours. Findings indicate that behaviours hypothesized to be unplanned were not well predicted by the values-based framework. The framework successfully predicted what was hypothesized to be a fully reasoned behaviour. Three potential reasons are discussed for the lack of prediction of some behaviours. A deeper understanding of how unplanned, automatic or habitual behaviours intervene in conservation intentions can help policy-makers and building designers better respond to influences of occupant behaviour on building performance.     

Impact of air‐handling system exhaust failure on dissemination pattern of simulant pathogen particles in a clinical biocontainment unit

Biocontainment units (BCUs) are facilities used to care for patients with highly infectious diseases. However, there is limited guidance on BCU protocols and design. This study presents the first investigation of how HVAC (heating, ventilation, air‐conditioning) operating conditions influence the dissemination of fluorescent tracer particles released in a BCU. Test conditions included normal HVAC operation and exhaust failure resulting in loss of negative pressure. A suspension of optical brightener powder and water was nebulized to produce fluorescent particles simulating droplet nuclei (0.5‐5 μm). Airborne particle number concentrations were monitored by Instantaneous Biological Analyzers and Collectors (FLIR Systems). During normal HVAC operation, fluorescent tracer particles were contained in the isolation room (average concentration = 1 × 10⁴ ± 3 × 10³/L_air). Under exhaust failure, the automated HVAC system maximizes airflow into areas adjacent to isolation rooms to attempt to maintain negative pressure differential. However, 6% of the fluorescent particles were transported through cracks around doors/door handles out of the isolation room via airflow alone and not by movement of personnel or doors. Overall, this study provides a systematic method for evaluating capabilities to contain aerosolized particles during various HVAC scenarios. Recommendations are provided to improve situation‐specific BCU safety.     

“Officially A Vegan Now”: On Meat and Renaissance Masculinity in Pro Football

In 2012 Arian Foster, a running back for the Houston Texans of the National Football League (NFL), announced via Twitter that he is “officially a vegan now” (Foster, July 6, 2012). Foster's announcement precipitated a torrent of attention by many who worriedly debated the impact that his new diet may have on his on-field performance. In this article, we unravel the threads that have woven together a picture of who Foster is and what his decision to go vegan means. We argue that a close look at the media response reveals deeply held beliefs about masculinity, race, class, and place and the ways in which food serves in the constitution of subjectivity in the context of pro-football in Texas. We conduct a contextual discourse analysis of the popular and sports media coverage of Foster's diet using an intersectional framework to elaborate how normative masculinity is further nuanced by the meanings attributed to race, place, sexuality, sport, aggression, violence, health, and productivity.     

Pheromone responsiveness is regulated by components of the Gpr1p‐mediated glucose sensing pathway in Saccharomyces cerevisiae

Many fungi have evolved mechanisms to assess environmental nutrient availability prior to the energy‐intensive process of mating. In this study, we examined one such system in Saccharomyces cerevisiae, involving a glucose‐sensing pathway mediated by Gpr1p and the pheromone‐induced mating pathway. Initially we observed that the mating pathway in MATa cells is sensitive to environmental glucose depletion. This phenomenon can be partially reversed with a high glucose spike, but not with the addition of low levels of glucose. Deletion of the low‐affinity glucose receptor, Gpr1p, eliminated this glucose‐induced recovery of pheromone responsiveness. We then determined the impact of GPR1 deletion on the mating pathway and observed that, in all end points studied, the mating pathway response to pheromone is reduced in the absence of Gpr1p. Similarly, elimination of the Gα for Gpr1p, Gpa2p, resulted in reduction in pheromone sensitivity in all assays studied. The negative effect of removing Gpr1p on mating pathway activation could be recovered by overexpressing the mating receptor, Ste2p. Furthermore, Ste2p levels are reduced in the absence of glucose and GPR1. These data suggest that activity of the GPCR‐mediated mating pathway in S. cerevisiae is modulated by extracellular glucose concentrations through the only other GPCR in MATa cells, Gpr1p. Copyright © 2014 John Wiley & Sons, Ltd.     

Path to Market for Compact Modular Fusion Power Cores

The benefits of an energy source whose reactants are plentiful and whose products are benign is hard to measure, but at no time in history has this energy source been more needed. Nuclear fusion continues to promise to be this energy source. However, the path to market for fusion systems is still regularly a matter for long-term (20?+?year) plans. This white paper is intended to stimulate discussion of faster commercialization paths, distilling guidance from investors, utilities, and the wider energy research community (including from ARPA-E). There is great interest in a small modular fusion system that can be developed quickly and inexpensively. A simple model shows how compact modular fusion can produce a low cost development path by optimizing traditional systems that burn deuterium and tritium, operating not only at high magnetic field strength, but also by omitting some components that allow for the core to become more compact and easier to maintain. The dominant hurdles to the development of low cost, practical fusion systems are discussed, primarily in terms of the constraints placed on the cost of development stages in the private sector. The main finding presented here is that the bridge from DOE Office of Science to the energy market can come at the Proof of Principle development stage, providing the concept is sufficiently compact and inexpensive that its development allows for a normal technology commercialization path.     

Correcting evaluation bias of relational classifiers with network cross validation

Recently, a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.). These methods specifically exploit the statistical dependencies among instances in order to improve classification accuracy. However, there has been little focus on how these same dependencies affect our ability to draw accurate conclusions about the performance of the models. More specifically, the complex link structure and attribute dependencies in relational data violate the assumptions of many conventional statistical tests and make it difficult to use these tests to assess the models in an unbiased manner. In this work, we examine the task of within-network classification and the question of whether two algorithms will learn models that will result in significantly different levels of performance. We show that the commonly used form of evaluation (paired t-test on overlapping network samples) can result in an unacceptable level of Type I error. Furthermore, we show that Type I error increases as (1) the correlation among instances increases and (2) the size of the evaluation set increases (i.e., the proportion of labeled nodes in the network decreases). We propose a method for network cross-validation that combined with paired t-tests produces more acceptable levels of Type I error while still providing reasonable levels of statistical power (i.e., 1−Type II error).     

The Effect of Relationship Characteristics and Relational Communication on Experiences of Hurt From Romantic Partners

This study expands the relational turbulence model (RTM; Solomon & Knobloch,) by theorizing about how characteristics of relationships and relational judgments influence people's experiences of hurtful messages. Previous applications of RTM to hurt have uncovered associations among relational characteristics that influence people's hurtful experiences; however, the process by which these characteristics influence experiences of hurt remains unclear. We propose that relational communication (specifically, perceptions of dominance, and disaffiliation) is the mechanism linking relational qualities to hurt. A multigroup SEM was conducted to test for the possibility of sex differences. Results showed that people's experiences of hurt vary as a function of both relationship characteristics and relational inferences. Results also indicated a difference in path coefficients for males and females.     

Quantitative biology of single neurons

The building blocks of complex biological systems are single cells. Fundamental insights gained from single-cell analysis promise to provide the framework for understanding normal biological systems development as well as the limits on systems/cellular ability to respond to disease. The interplay of cells to create functional systems is not well understood. Until recently, the study of single cells has concentrated primarily on morphological and physiological characterization. With the application of new highly sensitive molecular and genomic technologies, the quantitative biochemistry of single cells is now accessible.     

The Influence of Crystal Habit on the Prediction of Dry Powder Inhalation Formulation Performance Using the Cohesive–Adhesive Force Balance Approach

The aim of this investigation was to study the influence of crystalline habit of active pharmaceutical ingredients on the cohesive–adhesive force balance within model dry powder inhaler (DPI) formulations and the corresponding affect on DPI formulation performance. The cohesive–adhesive balance (CAB) approach to colloid probe atomic force microscopy (AFM) was employed to determine the cohesive and adhesive interactions of micronized budesonide particles against the {102} and {002} faces of budesonide single crystals and crystalline substrates of different sugars (cyclodextrin, lactose, trehalose, raffinose, and xylitol), respectively. These data were used to measure the relative level of cohesion and adhesion via CAB and the possible influence on in vitro performance of a carrier-based DPI formulation. Varying the crystal habit of the drug had a significant effect on the cohesive measurement of micronized budesonide probes, with the cohesive values on the {102} faces being approximately twice that on the {002} crystal faces. However, although different CAB values were measured with the sugars with respect to the crystal faces chosen for the cohesive-based measurement, the overall influence on the rank order of the CAB values was not directly influenced. For these data sets, the CAB gradient indicated that a decrease in the dominance of the adhesive forces led to a concomitant increase in fine particle delivery, reaching a plateau as the cohesive forces became dominant. The study suggested that crystal habit of the primary drug crystals influences the cohesive interactions and the resulting force balance measurements of colloid probe CAB analysis.