Employing dynamic fuzzy membership functions to assess environmental performance in the supplier selection process

The proposed system illustrates that logic fuzzy can be used to aid management in assessing a supplier's environmental performance in the supplier selection process. A user-centred hierarchical system employing scalable fuzzy membership functions implement human priorities in the supplier selection process, with particular focus on a supplier's environmental performance. Traditionally, when evaluating supplier performance, companies have considered criteria such as price, quality, flexibility, etc. These criteria are of varying importance to individual companies pertaining to their own specific objectives. However, with environmental pressures increasing, many companies have begun to give more attention to environmental issues and, in particular, to their suppliers’ environmental performance. The framework presented here was developed to introduce efficiently environmental criteria into the existing supplier selection process and to reflect on its relevant importance to individual companies. The system presented attempts to simulate the human preference given to particular supplier selection criteria with particular focus on environmental issues when considering supplier selection. The system considers environmental data from multiple aspects of a suppliers business, and based on the relevant impact this will have on a Buying Organization, a decision is reached on the suitability of the supplier. This enables a particular supplier's strengths and weaknesses to be considered as well as considering their significance and relevance to the Buying OrganizationPeer reviewe

The Small Subunit rRNA Modification Database

The Small Subunit rRNA Modification Database provides a listing of reported post-transcriptionally modified nucleosides and sequence sites in small subunit rRNAs from bacteria, archaea and eukarya. Data are compiled from reports of full or partial rRNA sequences, including RNase T1 oligonucleotide catalogs reported in earlier literature in studies of phylogenetic relatedness. Options for data presentation include full sequence maps, some of which have been assembled by database curators with the aid of contemporary gene sequence data, and tabular forms organized by source organism or chemical identity of the modification. A total of 32 rRNA sequence alignments are provided, annotated with sites of modification and chemical identities of modifications if known, with provision for scrolling full sequences or user-dictated subsequences for comparative viewing for organisms of interest. The database can be accessed through the World Wide Web at http://medlib.med.utah.edu/SSUmods

Mobile Device Use Among Rural, Low-Income Families and the Feasibility of an App to Encourage Preschoolers' Physical Activity: Qualitative Study.

BackgroundAs mobile devices are becoming ubiquitous, technology-based interventions provide a promising strategy to positively influence health behaviors of families with young children. However, questions remain about the feasibility and acceptability of intervention delivery via mobile apps in low-income, rural settings and among families with preschoolers.ObjectiveThe aims of this study were to understand the content and context of mobile device use for preschoolers; explore parent beliefs on this topic, including the acceptability of intervention delivery via mobile devices; and test a prototype of an app to encourage preschoolers' physical activity with both parents and children.MethodsParents (n=29) were recruited from 5 preschool centers in eastern, rural Colorado to complete a semistructured telephone interview regarding preschoolers' mobile device use. A second sample of parents (n=31) was recruited from the same preschool centers to view the app prototype independently and provide feedback. A third sample of preschool children (n=24) was videotaped using the app in small groups to measure engagement and record their responses to the app.ResultsFive key content areas emerged from the telephone interviews: (1) mobile devices are an important part of families' everyday routines, and parents have parameters governing their use; (2) parents often use mobile devices as a tool for behavior management; (3) parents clearly distinguish between mobile device use for learning versus entertainment; (4) parents have an overarching desire for balance in regard to their child's mobile device use; and (5) parents were generally supportive of the idea of using mobile apps for intervention delivery. From the app prototype testing with parents, participants reacted positively to the app and felt that it would be useful in a variety of situations. Testing with preschoolers showed the children were highly engaged with the app and a majority remained standing and/or actively moving through the entire length of the app.ConclusionsMobile devices are already integrated into most families' daily routines and appear to be an acceptable method of intervention delivery in low-income families in rural Colorado. The physical activity app represents an innovative way to reach these families and, with further improvements based on participant feedback, will provide children with a unique opportunity to practice key movement skills

Inference After Estimation of Breaks

In an important class of econometric problems, researchers select a target parameter by maximizing the Euclidean norm of a data-dependent vector. Examples that can be cast into this frame include threshold regression models with estimated thresholds, and structural break models with estimated breakdates. Estimation and inference procedures that ignore the randomness of the target parameter can be severely biased and misleading when this randomness is non-negligible. This paper proposes conditional and unconditional inference in such settings, reflecting the data-dependent choice of target parameters. We detail the construction of quantile-unbiased estimators and confidence sets with correct coverage, and prove their asymptotic validity under data generating process such that the target parameter remains random in the limit. We also provide a novel sample splitting approach that improves on conventional split-sample inference

Inference after estimation of breaks

In an important class of econometric problems, researchers select a target parameter by maximizing the Euclidean norm of a data-dependent vector. Examples that can be cast into this frame include threshold regression models with estimated thresholds and structural break models with estimated break dates. Estimation and inference procedures that ignore the randomness of the target parameter can be severely biased and misleading when this randomness is non-negligible. This paper studies conditional and unconditional inference in such settings, accounting for the data-dependent choice of target parameters. We detail the construction of quantile-unbiased estimators and confidence sets with correct coverage, and prove their asymptotic validity under data generating process such that the target parameter remains random in the limit. We also provide a novel sample splitting approach that improves on conventional split-sample inference

Inference on winners

Many questions in econometrics can be cast as inference on a parameter selected through optimization. For example, researchers may be interested in the effectiveness of the best policy found in a randomized trial, or the bestperforming investment strategy based on historical data. Such settings give rise to a winner’s curse, where conventional estimates are biased and conventional confidence intervals are unreliable. This paper develops optimal confidence sets and median-unbiased estimators that are valid conditional on the parameter selected and so overcome this winner’s curse. If one requires validity only on average over target parameters that might have been selected, we develop hybrid procedures that combine conditional and projection confidence sets and offer further performance gains that are attractive relative to existing alternatives

Co-Emergence of Specialized Endothelial Cells from Embryonic Stem Cells.

A well-formed and robust vasculature is critical to the health of most organ systems in the body. However, the endothelial cells (ECs) forming the vasculature can exhibit a number of distinct functional subphenotypes like arterial or venous ECs, as well as angiogenic tip and stalk ECs. In this study, we investigate the in vitro differentiation of EC subphenotypes from embryonic stem cells (ESCs). Using our staged induction methods and chemically defined mediums, highly angiogenic EC subpopulations, as well as less proliferative and less migratory EC subpopulations, are derived. Furthermore, the EC subphenotypes exhibit distinct surface markers, gene expression profiles, and positional affinities during sprouting. While both subpopulations contained greater than 80% VE-cad+/CD31+ cells, the tip/stalk-like EC contained predominantly Flt4+/Dll4+/CXCR4+/Flt-1- cells, while the phalanx-like EC was composed of higher numbers of Flt-1+ cells. These studies suggest that the tip-specific EC can be derived in vitro from stem cells as a distinct and relatively stable EC subphenotype without the benefit of its morphological positioning in the sprouting vessel

In Situ ATR-SEIRAS of Carbon Dioxide Reduction at a Plasmonic Silver Cathode.

Illumination of a voltage-biased plasmonic Ag cathode during CO2 reduction results in a suppression of the H2 evolution reaction while enhancing CO2 reduction. This effect has been shown to be photonic rather than thermal, but the exact plasmonic mechanism is unknown. Here, we conduct an in situ ATR-SEIRAS (attenuated total reflectance-surface-enhanced infrared absorption spectroscopy) study of a sputtered thin film Ag cathode on a Ge ATR crystal in CO2-saturated 0.1 M KHCO3 over a range of potentials under both dark and illuminated (365 nm, 125 mW cm-2) conditions to elucidate the nature of this plasmonic enhancement. We find that the onset potential of CO2 reduction to adsorbed CO on the Ag surface is -0.25 VRHE and is identical in the light and the dark. As the production of gaseous CO is detected in the light near this onset potential but is not observed in the dark until -0.5 VRHE, we conclude that the light must be assisting the desorption of CO from the surface. Furthermore, the HCO3- wavenumber and peak area increase immediately upon illumination, precluding a thermal effect. We propose that the enhanced local electric field that results from the localized surface plasmon resonance (LSPR) is strengthening the HCO3- bond, further increasing the local pH. This would account for the decrease in H2 formation and increase the CO2 reduction products in the light