An assessment of the quality and educational adequacy of educational facilities and their perceived impact on the learning environment as reported by middle school administrators and teachers in Humble Independent School District, Humble, Texas

This quantitative study investigates the adequacy and quality of middle school facilities in Humble ISD middle schools as reported by the primary users of these facilities, the teachers and administrators. These middle school educators also provide an assessment of the impact that these facilities have on the learning environment. This study also assesses the quality and adequacy of these middle school facilities through a purely quantitative evaluation conducted by an unbiased assessment team. Humble ISD is undergoing unprecedented growth at all levels and has addressed the burgeoning elementary and high school aged growth occurring in the district by constructing and renovating these facilities. At the middle level, however, new facility construction is occurring at a slower pace. The purpose of this research is to ascertain which factors in each of these six facilities have the greatest quality and adequacy and the impact that they have on the learning environment. Furthermore, it is the purpose of this research to provide valuable and practical data, to which Humble ISD and others can refer in developing future building plans, renovating existing facilities, allocating funds, and creating student centered learning environments. This study also investigates the relationship between what educators perceive as adequate and quality facility factors and their perception of the impact that these factors have on the learning environment. Finally, this study reviews any congruency or agreement between educatorâÂÂs perception of adequacy and quality and architect assessment of adequacy and quality. Middle level students are the most influential group of adolescents and it is important that we provide facilities that meet their very specific needs. This research will ultimately and positively impact the learning environment for these children

Macroinvertebrate community response to inter-annual and regional river flow regime dynamics

Spatio-temporal variability in river flow is a fundamental control on instream habitat structure and riverine ecosystem biodiversity and integrity. However, long-term riverine ecological time-series to test hypotheses about hydrology–ecology interactions in a broader temporal context are rare, and studies spanning multiple rivers are often limited in their temporal coverage to less than five years. To address this research gap, a unique spatio-temporal hydroecological analysis was conducted of long-term instream ecological responses (1990–2000) to river flow regime variability at 83 sites across England and Wales. The results demonstrate clear hydroecological associations at the national scale (all data). In addition, significant differences in ecological response are recorded between three ‘regions’ identified (RM1–3*) associated with characteristics of the flow regime. The effect of two major supra-seasonal droughts (1990–1992 and 1996–1997) on inter-annual (IA) variability of the LIFE scores is evident with both events showing a gradual decline before and recovery of LIFE scores after the low flow period. The instream community response to high magnitude flow regimes (1994 and 1995) is also apparent, although these associations are less striking. The results demonstrate classification of rivers into flow regime regions offers a way to help unravel complex hydroecological associations. The approach adopted herein could easily be adapted for other geographical locations, where datasets are available. Such work is imperative to understand flow regime–ecology interactions in a longer term, wider spatial context and so assess future hydroecological responses to climate change and anthropogenic modification of riverine ecosystems

Selection of river flow indices for the assessment of hydroecological change

A wide range of ‘ecologically relevant’ hydrological indices (variables) have been identified as potential drivers of riverine communities. Recently, concerns have been expressed regarding index redundancy (i.e. similar patterns of variance) across the host of hydrological descriptors on offer to researchers and water resource managers. Some guiding principles are required to aid selection of the most statistically defensible and meaningful river flow indices for hydroecological analysis. In this short communication, we investigate the utility of a principal components analysis (PCA)-based method that identifies 25 hydrological variables to characterise the major modes of statistical variation in 201 hydrological indices for 83 rivers across England and Wales. The emergent variables, and all 201 hydrological variables, are used to develop regression models [for the whole data set and three river flow regime shape (i.e. annual hydrograph form) classes] for an 11-year macroinvertebrate community dataset (i.e. LIFE scores). The same ‘best’ models are produced using the PCA-based method and all 201 hydrological variables for two of the three river flow regime groups. However, weaker models are yielded by the PCA-based method for the remaining (flashy) river flow regime class and the whole data set (all 83 rivers). Thus, it is important to exercise caution when employing data reduction/ index redundancy approaches, as they may reject variables of ecological significance due to the assumption that the statistically dominant sources of hydrological variability are the principal drivers of, perhaps more subtle (sensitive), hydroecological associations

The pleasures and perils of inheritance

Facing death, reflecting on one’s legacies (material and ethical, personal and political) and the legal and interpersonal attempts to resolve or prevent inheritance conflicts, all bring to the fore constructions of memory and identity, intergenerational relations, and the complexities of doing and undoing family and kinship. Consequently, drawing attention to inheritance, keeping sight of it, and bringing it into play is a useful piece of the puzzle of ageing across a range of disciplines and this article provides an overview of some of the key themes in this emerging field

Flow variability and macroinvertebrate community response within riverine systems

River flow regimes, controlled by climatic and catchment factors, vary over a wide range of temporal and spatial scales. This hydrological dynamism is important in determining the structure and functioning of riverine ecosystems; however, such hydroecological associations remain poorly quantified. This paper explores and models relationships between a suite of flow regime predictors and macroinvertebrate community metrics from 83 rivers in England and Wales. A two-stage analytical approach was employed: (1) classification of 83 river basins based upon the magnitude and shape (form) of their long-term (1980 – 1999) average annual regime to group basins with similar flow responses; and (2) examination of relationships between a total of 201 flow regime descriptors identified by previous researchers and macroinvertebrate community metrics for the whole data set and long-term flow regime classes over an 11-year period (1990 – 2000). The classification method highlighted large-scale patterns in river flow regimes, identifying five magnitude classes and three shape classes. A west–east trend of flow regime magnitude (high-low) and timing (early-late peak) was displayed across the study area, reflecting climatic gradients and basin controls (e.g. lithology). From the suite of hydrological variables, those associated with the magnitude of the flow regime consistently produced the strongest relationships with macroinvertebrate community metrics for all sites and for the long-term regime composite classes. The results indicate that the classification (subdivision) of rivers into flow regime regions potentially offers a means of increasing predictive capacity and, in turn, better management of fluvial hydrosystems

Complete Genome Sequences of Paenibacillus Larvae Phages BN12, Dragolir, Kiel007, Leyra, Likha, Pagassa, PBL1c, and Tadhana

We present here the complete genomes of eight phages that infect Paenibacillus larvae, the causative agent of American foulbrood in honeybees. Phage PBL1c was originally isolated in 1984 from a P. larvae lysogen, while the remaining phages were isolated in 2014 from bee debris, honeycomb, and lysogens from three states in the USA

Model-driven discovery of synergistic inhibitors against <i>E. coli</i> and <i>S. enterica </i>serovar Typhimurium targeting a novel synthetic lethal pair, <i>aldA </i>and <i>prpC</i>

Mathematical models of biochemical networks form a cornerstone of bacterial systems biology. Inconsistencies between simulation output and experimental data point to gaps in knowledge about the fundamental biology of the organism. One such inconsistency centers on the gene aldA in Escherichia coli: it is essential in a computational model of E. coli metabolism, but experimentally it is not. Here we reconcile this disparity by providing evidence that aldA and prpC form a synthetic lethal pair, as the double knockout could only be created through complementation with a plasmid-borne copy of aldA. Moreover, virtual and biological screening against the two proteins led to a set of compounds that inhibited the growth of E. coli and Salmonella enterica serovar Typhimurium synergistically at 100 – 200 μM individual concentrations. These results highlight the power of metabolic models to drive basic biological discovery and their potential use to discover new combination antibiotics

What Is a Representative Brain? Neuroscience Meets Population Science

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas