Strategic Social Partnerships for Change: A Framework for Building Sustainable Growth in Developing Countries

[Excerpt] One of the hallmarks of an increasingly global world is the opportunity for wider access to consumers, capital, and information from around the world. To capture global customers, companies and countries must build relationships that enhance access to knowledge, information, capital, and other resources needed to grow and compete effectively. As the importance of international relationships among varied groups of private investors, providers of services, and governments increases, the ability of developing countries to compete often is determined by the quality of their relationships with strategic partners

Grooming Future Hospitality Leaders: A Competencies Model

Competency models can be useful tools for identifying and grooming future leaders. Rather than base leadership assessment on personality traits or other unrelated characteristics, competency models specify the actions and behavior needed for successful leaders. While some hotel companies have begun to identify leadership competencies, the hotel industry does not have an overall competency model. Starting with competency models from other industries and the assessments from a pilot study, the authors compiled a list of 99 competencies or skills (grouped into eight overarching factors comprising 28 dimensions) that might contribute to leadership success in the hospitality industry. Those competencies were rated on a five-point scale, ranging from not at all important to extremely important, in a survey of 137 industry leaders. The competency labeled “self-management” was the top dimension (of the 28)—composed of ethics and integrity, time management, flexibility and adaptability, and self-development. Second in importance was competency in strategic positioning, comprising awareness of customer needs, commitment to quality, managing stakeholders, and concern for the community. (However, concern for the community was rated least important compared to the other three dimensions in that category). Industry knowledge, leadership, and interpersonal skill were factors that, while important, were ranked lower by the respondents

Contrast of LiFeAs with isostructural, isoelectronic, and non-superconducting MgFeGe

Stoichiometric LiFeAs at ambient pressure is an 18 K superconductor while isoelectronic MgFeGe is not, despite their extremely similar electronic structures. To investigate possible sources of this distinctively different superconducting behavior, we quantify the differences using first principles density functional theory, establishing first that the Fe total 3d occupations are identical in the two compounds. Individual 3d orbital occupations also differ very little ($\sim 0.01$). The differences in Fermi surfaces (FSs) do not seem significant; however a redistribution of bands just above the Fermi level does represent a possibly significant distinction. Because the bands and FSs of LiFeAs are less in agreement with experiment than for other iron-pnictides, we study the effects of additional exchange-correlations effects beyond GGA (the generalized gradient approximation) by applying the modified Becke-Johnson potential (mBJ) exchange potential, which gives much improved bandgaps in insulators compared to GGA and might be useful for semimetals such as the Fe-based superconductors. Overall, we conclude that the mBJ corrections do not improve the description of LiFeAs as compared to experiment

Considerations for studying transmission of antimicrobial resistant enteric bacteria between wild birds and the environment on intensive dairy and beef cattle operations

Background Wild birds using livestock facilities for food and shelter may contribute to dissemination of enteric pathogens or antimicrobial resistant bacteria. However, drivers of microbial exchange among wildlife and livestock are not well characterized. Predisposition for acquiring and retaining environmental bacteria may vary among species because of physiologic or behavioral differences, complicating selection of a bacterial model that can accurately characterize microbial connections among hosts of interest. This study compares the prevalence and antibiotic resistance phenotypes of two potential model bacterial organisms isolated from wild birds and their environments. Methods We compared prevalence and resistance profiles of Escherichia coli and Enterococcus species isolated from environmental swabs and bird feces on a residential control site, a confinement dairy, a pasture-based beef farm, and a confinement beef farm. Results Bird feces at all sites had low-to-moderate prevalence of Escherichia coli (range: 17–47%), despite potential for exposure on farms (range: 63–97%). Few Escherichia coli were isolated from the control environment. Enterococcus faecalis was dominant in birds at both beef farms (62% and 81% of Enterococcus isolates) and low-to-moderately prevalent at the dairy and control sites (29% and 23% of isolates, respectively). Antimicrobial resistance prevalence was higher in farm samples compared to those from the residential control, but distribution of resistant isolates varied between the bacterial genera. Birds on all farms carried resistant Enterococcus at similar rates to that of the environment, but resistance was less common in bird-associated Escherichia coli despite presence of resistant isolates in the farm environment. Discussion Bacterial species studied may affect how readily bacterial exchange among populations is detected. Selection of microbial models must carefully consider both the questions being posed and how findings might influence resulting management decisions

Spectroscopic scanning tunneling microscopy insights into Fe-based superconductors

In the first three years since the discovery of Fe-based high Tc superconductors, scanning tunneling microscopy (STM) and spectroscopy have shed light on three important questions. First, STM has demonstrated the complexity of the pairing symmetry in Fe-based materials. Phase-sensitive quasiparticle interference (QPI) imaging and low temperature spectroscopy have shown that the pairing order parameter varies from nodal to nodeless s\pm within a single family, FeTe1-xSex. Second, STM has imaged C4 -> C2 symmetry breaking in the electronic states of both parent and superconducting materials. As a local probe, STM is in a strong position to understand the interactions between these broken symmetry states and superconductivity. Finally, STM has been used to image the vortex state, giving insights into the technical problem of vortex pinning, and the fundamental problem of the competing states introduced when superconductivity is locally quenched by a magnetic field. Here we give a pedagogical introduction to STM and QPI imaging, discuss the specific challenges associated with extracting bulk properties from the study of surfaces, and report on progress made in understanding Fe-based superconductors using STM techniques.Comment: 36 pages, 23 figures, 229 reference

Genomic Analysis of QTLs and Genes Altering Natural Variation in Stochastic Noise

Quantitative genetic analysis has long been used to study how natural variation of genotype can influence an organism's phenotype. While most studies have focused on genetic determinants of phenotypic average, it is rapidly becoming understood that stochastic noise is genetically determined. However, it is not known how many traits display genetic control of stochastic noise nor how broadly these stochastic loci are distributed within the genome. Understanding these questions is critical to our understanding of quantitative traits and how they relate to the underlying causal loci, especially since stochastic noise may be directly influenced by underlying changes in the wiring of regulatory networks. We identified QTLs controlling natural variation in stochastic noise of glucosinolates, plant defense metabolites, as well as QTLs for stochastic noise of related transcripts. These loci included stochastic noise QTLs unique for either transcript or metabolite variation. Validation of these loci showed that genetic polymorphism within the regulatory network alters stochastic noise independent of effects on corresponding average levels. We examined this phenomenon more globally, using transcriptomic datasets, and found that the Arabidopsis transcriptome exhibits significant, heritable differences in stochastic noise. Further analysis allowed us to identify QTLs that control genomic stochastic noise. Some genomic QTL were in common with those altering average transcript abundance, while others were unique to stochastic noise. Using a single isogenic population, we confirmed that natural variation at ELF3 alters stochastic noise in the circadian clock and metabolism. Since polymorphisms controlling stochastic noise in genomic phenotypes exist within wild germplasm for naturally selected phenotypes, this suggests that analysis of Arabidopsis evolution should account for genetic control of stochastic variance and average phenotypes. It remains to be determined if natural genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes