Economic Strength and Micropolitan Statistical Areas: Looking Beyond Generalities

Facility location decisions serve an important role in setting up efficient and cost-effective supply chains. While metropolitan areas may appear an obvious choice for many companies, nonmetropolitan areas deserve consideration. In the past, nonmetropolitan areas have been broadly classified as “rural” with reports of economic decline. This research looks beyond the general category of nonmetropolitan by dividing the area into micropolitan statistical areas and non-core statistical areas. The authors use U.S. Census data from the years 2010 to 2016 to analyze changes in population, median household income, retail employment, and retail salaries in Alabama, Georgia, and Mississippi. Companies can use this more refined information approach to help identify specific counties outside metropolitan statistical areas that demonstrate growth and may provide suitable facility locations

Escape for Boone & Crocket

Eber Crocket is the owner of Boone & Crocket Trapper Supply (B&C). He feels like the environmental forces that are impacting his business are like a trap slowing closing on him. He is considering ideas to improve his store’s profitability. Demand for furs as fashion goods is a multi-million dollar industry. Twenty percent of this demand is met by wild fur which is harvested by trappers. Trapping suppliers serve as the middleman between small individual trappers and auction houses. These auction houses collect the raw fur pelts from trappers and trapping stores and hold them until one of their auctions. Members of the international fashion community are the principle buyers of wild fur. These firms are involved in the tanning, finishing and design work needed to turn a fur pelt into a finished garment. The fur industry is impacted by many environmental forces. Among them, sociocultural, regulatory and economic forces are key. Boone & Crocket Trapping Supply is small family-owned business located in central Minnesota It offers a wide selection of trapping-related goods and services. The majority of B&Cs profits come from the sale of traps, baits and other goods. The remaining profit comes from fur handing and auction fur sales. Your friend Eber wants your perspective on some of the new product and service ideas he is considering to make B&C more profitable. His ideas are to produce trapping baits, expand the condition of furs B&C buys, differentiate the store’s product line, enter the nuisance animal control business, or become involved in trapper’s education

How Regional Employment in the U.S. Automobile Industry Influences Consumer Ethnocentrism

The past three decades lay witness to major geographical evolution of the automobile industry in the United States. This study analyzes exactly how CETSCALE scores differ among a population that is currently either more or less economically impacted by automobile production and marketing. The analysis presented in this study illustrates a direct correlation between ethnocentric dispositions among consumers and employment opportunities in the automobile sector across U.S. Census Bureau geographical regions and divisions in each region. Comprehensive statistical details are provided that arguably demonstrate a change in what the phrase “Made in America” means, at least where automobile production is concerned

XplorSeq: A software environment for integrated management and phylogenetic analysis of metagenomic sequence data

<p>Abstract</p> <p>Background</p> <p>Advances in automated DNA sequencing technology have accelerated the generation of metagenomic DNA sequences, especially environmental ribosomal RNA gene (rDNA) sequences. As the scale of rDNA-based studies of microbial ecology has expanded, need has arisen for software that is capable of managing, annotating, and analyzing the plethora of diverse data accumulated in these projects.</p> <p>Results</p> <p>XplorSeq is a software package that facilitates the compilation, management and phylogenetic analysis of DNA sequences. XplorSeq was developed for, but is not limited to, high-throughput analysis of environmental rRNA gene sequences. XplorSeq integrates and extends several commonly used UNIX-based analysis tools by use of a Macintosh OS-X-based graphical user interface (GUI). Through this GUI, users may perform basic sequence import and assembly steps (base-calling, vector/primer trimming, contig assembly), perform BLAST (Basic Local Alignment and Search Tool; <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp>) searches of NCBI and local databases, create multiple sequence alignments, build phylogenetic trees, assemble Operational Taxonomic Units, estimate biodiversity indices, and summarize data in a variety of formats. Furthermore, sequences may be annotated with user-specified meta-data, which then can be used to sort data and organize analyses and reports. A document-based architecture permits parallel analysis of sequence data from multiple clones or amplicons, with sequences and other data stored in a single file.</p> <p>Conclusion</p> <p>XplorSeq should benefit researchers who are engaged in analyses of environmental sequence data, especially those with little experience using bioinformatics software. Although XplorSeq was developed for management of rDNA sequence data, it can be applied to most any sequencing project. The application is available free of charge for non-commercial use at <url>http://vent.colorado.edu/phyloware</url>.</p

Evolutionary connectionism: algorithmic principles underlying the evolution of biological organisation in evo-devo, evo-eco and evolutionary transitions

The mechanisms of variation, selection and inheritance, on which evolution by natural selection depends, are not fixed over evolutionary time. Current evolutionary biology is increasingly focussed on understanding how the evolution of developmental organisations modifies the distribution of phenotypic variation, the evolution of ecological relationships modifies the selective environment, and the evolution of reproductive relationships modifies the heritability of the evolutionary unit. The major transitions in evolution, in particular, involve radical changes in developmental, ecological and reproductive organisations that instantiate variation, selection and inheritance at a higher level of biological organisation. However, current evolutionary theory is poorly equipped to describe how these organisations change over evolutionary time and especially how that results in adaptive complexes at successive scales of organisation (the key problem is that evolution is self-referential, i.e. the products of evolution change the parameters of the evolutionary process). Here we first reinterpret the central open questions in these domains from a perspective that emphasises the common underlying themes. We then synthesise the findings from a developing body of work that is building a new theoretical approach to these questions by converting well-understood theory and results from models of cognitive learning. Specifically, connectionist models of memory and learning demonstrate how simple incremental mechanisms, adjusting the relationships between individually-simple components, can produce organisations that exhibit complex system-level behaviours and improve the adaptive capabilities of the system. We use the term “evolutionary connectionism” to recognise that, by functionally equivalent processes, natural selection acting on the relationships within and between evolutionary entities can result in organisations that produce complex system-level behaviours in evolutionary systems and modify the adaptive capabilities of natural selection over time. We review the evidence supporting the functional equivalences between the domains of learning and of evolution, and discuss the potential for this to resolve conceptual problems in our understanding of the evolution of developmental, ecological and reproductive organisations and, in particular, the major evolutionary transitions

Role of Dopamine D2 Receptors in Human Reinforcement Learning

Influential neurocomputational models emphasize dopamine (DA) as an electrophysiological and neurochemical correlate of reinforcement learning. However, evidence of a specific causal role of DA receptors in learning has been less forthcoming, especially in humans. Here we combine, in a between-subjects design, administration of a high dose of the selective DA D2/3-receptor antagonist sulpiride with genetic analysis of the DA D2 receptor in a behavioral study of reinforcement learning in a sample of 78 healthy male volunteers. In contrast to predictions of prevailing models emphasizing DA's pivotal role in learning via prediction errors, we found that sulpiride did not disrupt learning, but rather induced profound impairments in choice performance. The disruption was selective for stimuli indicating reward, while loss avoidance performance was unaffected. Effects were driven by volunteers with higher serum levels of the drug, and in those with genetically-determined lower density of striatal DA D2 receptors. This is the clearest demonstration to date for a causal modulatory role of the DA D2 receptor in choice performance that might be distinct from learning. Our findings challenge current reward prediction error models of reinforcement learning, and suggest that classical animal models emphasizing a role of postsynaptic DA D2 receptors in motivational aspects of reinforcement learning may apply to humans as well.Neuropsychopharmacology accepted article peview online, 09 April 2014; doi:10.1038/npp.2014.84

Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis

Comparison of four mathematical models to analyze indicator-dilution curves in the coronary circulation

While several models have proven to result in accurate estimations when measuring cardiac output using indicator dilution, the mono-exponential model has primarily been chosen for deriving coronary blood/plasma volume. In this study, we compared four models to derive coronary plasma volume using indicator dilution; the mono-exponential, power-law, gamma-variate, and local density random walk (LDRW) model. In anesthetized goats (N = 14), we determined the distribution volume of high molecular weight (2,000 kDa) dextrans. A bolus injection (1.0 ml, 0.65 mg/ml) was given intracoronary and coronary venous blood samples were taken every 0.5–1.0 s; outflow curves were analyzed using the four aforementioned models. Measurements were done at baseline and during adenosine infusion. Absolute coronary plasma volume estimates varied by ~25% between models, while the relative volume increase during adenosine infusion was similar for all models. The gamma-variate, LDRW, and mono-exponential model resulted in volumes corresponding with literature, whereas the power-model seemed to overestimate the coronary plasma volume. The gamma-variate and LDRW model appear to be suitable alternative models to the mono-exponential model to analyze coronary indicator-dilution curves, particularly since these models are minimally influenced by outliers and do not depend on data of the descending slope of the curve only

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition