Toilet training age and influencing factors: a multicenter study

WOS: 000367570300010PubMed ID: 26690599To determine toilet training age and the factors influencing this in our country, 1500 children who had completed toilet training were evaluated in a multicenter study. The mean age of toilet training was 22.32 +/- 6.57 months. The duration it took to complete toilet training was 6.60 +/- 2.20 months on the average. In univariant analysis, toilet training age increased as the parental education level, specifically that of the mother, increased. The training age of children whose mothers had over 12 years of education differed significantly from that of children of mothers with less education. There was no significant difference in toilet training age with regard to the education level of the father, or the employment status of the mother. We also found significant differences with respect to family income level, toilet type and training method. In multivariant analysis, family income >5000 TL and use of a potty chair were determined to be factors affecting toilet training age. In conclusion, toilet training age in Turkey, a developing country, was found to be lower than that in developed countries

Final report on key comparison CCQM-K55.c (L-(+)-Valine): Characterization of organic substances for chemical purity

Under the auspices of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a key comparison, CCQM K55.c, was coordinated by the Bureau International des Poids et Mesures (BIPM) in 2012. Twenty National Measurement Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the mass fraction of valine present as the main component in the comparison sample for CCQM-K55.c. The comparison samples were prepared from analytical grade L-valine purchased from a commercial supplier and used as provided without further treatment or purification. Valine was selected to be representative of the performance of a laboratory's measurement capability for the purity assignment of organic compounds of low structural complexity [molecular weight range 100–300] and high polarity (pKOW > −2). The KCRV for the valine content of the material was 992.0 mg/g with a combined standard uncertainty of 0.3 mg/g. The key comparison reference value (KCRV) was assigned by combination of KCRVs assigned from participant results for each orthogonal impurity class. The relative expanded uncertainties reported by laboratories having results consistent with the KCRV ranged from 1 mg/g to 6 mg/g when using mass balance based approaches alone, 2 mg/g to 7 mg/g using quantitative 1H NMR (qNMR) based approaches and from 1 mg/g to 2.5 mg/g when a result obtained by a mass balance method was combined with a separate qNMR result. The material provided several analytical challenges. In addition to the need to identify and quantify various related amino acid impurities including leucine, isoleucine, alanine and α-amino butyrate, care was required to select appropriate conditions for performing Karl Fischer titration assay for water content to avoid bias due to in situ formation of water by self-condensation under the assay conditions. It also proved to be a challenging compound for purity assignment by qNMR techniques. There was overall excellent agreement between participants in the identification and the quantification of the total and individual related structure impurities, water content, residual solvent and total non-volatile content of the sample. Appropriate technical justifications were developed to rationalise observed discrepancies in the limited cases where methodology differences led to inconsistent results. The comparison demonstrated that to perform a qNMR purity assignment the selection of appropriate parameters and an understanding of their potential influence on the assigned value is critical for reliable implementation of the method, particularly when one or more of the peaks to be quantified consist of complex multiplet signals.JRC.D.2-Standards for Innovation and sustainable Developmen

The Relationship Between Firm Resilience to Supply Chain Disruptions and Firm Innovation

ThisFirm resiliencechapter discusses theSupply chain disruptions relationship betweenInnovationsupply chainSupply chaindisruption risk managementDisruption risk management and innovationInnovation management and examines whether a firm’s investment in innovationInnovation can improve the firm’s resilienceResilience to supply chainSupply chain disruption. We review the antecedents of both firm innovativeness and firm resilienceFirm resilience to supply chain disruptionsSupply chain disruptions, and we identify how investment in innovationInnovation can enhance a firm’s response to supply chain disruptionsSupply chain disruptions using a systematic literature review process. We identify leadershipLeadership, information sharing, and collaboration as practices that improve both firm innovationInnovation and firm resilienceFirm resilience to supply chainSupply chain disruption. We discuss future research directions to further examine the relationship between a firm’s innovationInnovation capability and the firm’s resilienceResilience to supply chain disruptionsSupply chain disruptions