Psychometric Properties of the Spanish Human System Audit Short-Scale of Transformational Leadership

The aim of this research is to examine the psychometric properties of a Spanish version of the Human System Audit transformational leadership short-scale (HSA-TFL-ES). It is based on the concept of Bass developed in 1985. The HSA-TFL is a part of the wider Human System Audit frame. We analyzed the HSA-TFL-ES in five different samples with a total number of 1,718 workers at five sectors. Exploratory Factor Analysis corroborated a single factor in all samples that accounted for 66% to 73% of variance. The internal consistency in all samples was good (α = .92 - .95). Evidence was found for the convergent validity of the HSA-TFL-ES and the Multifactor Leadership Questionnaire. These results suggested that the HSA-TFL short-scale is a psychometrically sound measure of this construct and can be used for a combined and first overall measurement.

Glassy magnetic phase driven by short range charge and magnetic ordering in nanocrystalline La1/3Sr2/3FeO3-δ: Magnetization, Mössbauer, and polarized neutron studies

The charge ordered La1/3Sr2/3FeO3−δ (LSFO) in bulk and nanocrystalline forms are investigated using ac and dc magnetization, M¨ossbauer, and polarized neutron studies. A complex scenario of short-range charge and magnetic ordering is realized from the polarized neutron studies in nanocrystalline specimen. This short-range ordering does not involve any change in spin state and modification in the charge disproportion between Fe3+ and Fe5+ compared to bulk counterpart as evident in the M¨ossbauer results. The refinement of magnetic diffraction peaks provides magnetic moments of Fe3+ and Fe5+ are about 3.15 μB and 1.57 μB for bulk, and 2.7 μB and 0.53 μB for nanocrystalline specimen, respectively. The destabilization of charge ordering leads to magnetic phase separation, giving rise to the robust exchange bias (EB) effect. Strikingly, EB field at 5 K attains a value as high as 4.4 kOe for average size ∼70 nm, which is zero for the bulk counterpart. A strong frequency dependence of ac susceptibility reveals cluster-glass-like transition around ∼65 K, below which EB appears. Overall results propose that finite-size effect directs the complex glassy magnetic behavior driven by unconventional short-range charge and magnetic ordering, and magnetic phase separation appears in nanocrystalline LSFO.

A short screener is valid for assessing mediterranean diet adherence among older spanish men and women

Ensuring the accuracy of dietary assessment instruments is paramount for interpreting diet-disease relationships. The present study assessed the relative and construct validity of the 14-point Mediterranean Diet Adherence Screener (MEDAS) used in the Prevencio´n con Dieta Mediterra´nea (PREDIMED) study, a primary prevention nutrition-intervention trial. A validated FFQ and the MEDAS were administered to 7146 participants of the PREDIMED study. The MEDASderived PREDIMED score correlated significantly with the corresponding FFQ PREDIMED score (r = 0.52; intraclass correlation coefficient = 0.51) and in the anticipated directions with the dietary intakes reported on the FFQ. Using Bland Altman"s analysis, the average MEDAS Mediterranean diet score estimate was 105% of the FFQ PREDIMED score estimate. Limits of agreement ranged between 57 and 153%. Multiple linear regression analyses revealed that a higher PREDIMED score related directly (P , 0.001) to HDL-cholesterol (HDL-C) and inversely (P , 0.038) to BMI, waist circumference, TG, the TG:HDL-C ratio, fasting glucose, and the cholesterol:HDL-C ratio. The 10-y estimated coronary artery disease risk decreased as the PREDIMED score increased (P , 0.001). The MEDAS is a valid instrument for rapid estimation of adherence to the Mediterranean diet and may be useful in clinical practice.

A short screener is valid for assessing mediterranean diet adherence among older spanish men and women

Ensuring the accuracy of dietary assessment instruments is paramount for interpreting diet-disease relationships. The present study assessed the relative and construct validity of the 14-point Mediterranean Diet Adherence Screener (MEDAS) used in the Prevencio´n con Dieta Mediterra´nea (PREDIMED) study, a primary prevention nutrition-intervention trial. A validated FFQ and the MEDAS were administered to 7146 participants of the PREDIMED study. The MEDASderived PREDIMED score correlated significantly with the corresponding FFQ PREDIMED score (r = 0.52; intraclass correlation coefficient = 0.51) and in the anticipated directions with the dietary intakes reported on the FFQ. Using Bland Altman"s analysis, the average MEDAS Mediterranean diet score estimate was 105% of the FFQ PREDIMED score estimate. Limits of agreement ranged between 57 and 153%. Multiple linear regression analyses revealed that a higher PREDIMED score related directly (P , 0.001) to HDL-cholesterol (HDL-C) and inversely (P , 0.038) to BMI, waist circumference, TG, the TG:HDL-C ratio, fasting glucose, and the cholesterol:HDL-C ratio. The 10-y estimated coronary artery disease risk decreased as the PREDIMED score increased (P , 0.001). The MEDAS is a valid instrument for rapid estimation of adherence to the Mediterranean diet and may be useful in clinical practice.

Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting

In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the management of networks, both for urban and interurban environments, and today’s road operator has increasingly complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic conditions. This paper presents a framework for detection pattern identification based on finite mixture models using the EM algorithm for parameter estimation. The computation results have been conducted taking into account the traffic data available in an urban network.