Investigating the Structure of the Children's Concentration and Empathy Scale Using Exploratory Graph Analysis

The current paper investigates the structural validity of the Children's Concentration and Empathy Scale (CCES), which was designed based on Montessori's developmental theory to assess, using teacher ratings, the coherence of attention-related characteristics (concentration, empathy, and normalization) in children from 1.5 to 12 years old. The dimensionality analysis was carried out using exploratory graph analysis (EGA), and the stability of the items and factors were checked using a bootstrap version of EGA, and the results contrasted to exploratory factor analysis. The results point to a four-factor structure (emotion regulation, fantasy, task engagement, and empathy) after eliminating items with low replicability across bootstrapped samples. Beyond pointing to ways to improve the CCES, our paper presents a number of data analytical strategies that can be useful for studies investigating the structural validity of measurement instruments and demonstrates how EGA can effectively be used in the scale construction and validation process. Our manuscript and results are fully reproducible and are available on the Open Science Framework.

On the stiffness of surfaces with non-Gaussian height distribution

In this work, the stiffness, i.e., the derivative of the load-separation curve, is studied for self-affine fractal surfaces with non-Gaussian height distribution. In particular, the heights of the surfaces are assumed to follow a Weibull distribution. We find that a linear relation between stiffness and load, well established for Gaussian surfaces, is not obtained in this case. Instead, a power law, which can be motivated by dimensionality analysis, is a better descriptor. Also unlike Gaussian surfaces, we find that the stiffness curve is no longer independent of the Hurst exponent in this case. We carefully asses the possible convergence errors to ensure that our conclusions are not affected by them.

A review of smart manufacturing reference models based on the skeleton meta-model

Standards will allow interoperability among stakeholders in the upcoming super-connected world. A smart manufacturing reference model (SMRM) is under development inside JWG21 between ISO and IEC. Based on a dimensionality analysis and the skeleton meta-model, the eight proposed SMRMs are reviewed and compared. The SMRMs are classified according to the number of lifecycle axes and the number of dimensional axes. Also, how the concept of a digital twin can be accommodated in an SMRM is investigated.

Conductive anomalies related to the Mérida Andes derived from the 3D inversion of a magnetotelluric profile

<div><span>Abstract</span> <div>The geodynamic settings of north-western Venezuela are conditioned by the expulsion of the North Andean Block (NAB), and the deformational structures related to the Caribbean – South America plate interactions. The most prominent feature is the 100 km wide Mérida Andes (MA) that reach from the Colombian border to the Caribbean coast over more than 500 km. We present the analysis of a magnetotelluric (MT) profile acquired at 72 broadband sites along a 240 km long profile with station spacing between 3 and 5 km across the central part of the MA, including the sedimentary Maracaibo (MB) and Barinas-Apure (BAB) basins. Phase Tensors (PT) are consistent with 1D/2D dimensionality above the MB and the BAB, however, stations above the MA show a clear 3D dimensionality, with the induction vectors indicating the presence of off-profile structures. Following the dimensionality analysis, 3D inversions of the entire dataset were performed, employing the finite differences code ModEM. The results are in agreement with prominent geological structures, and are particularly effective in modelling the depth extensions of major fault systems. A conductive structure east from the profile at mid crustal levels seems to correlate with the tectonic escape of the Trujillo block, which is part of the NAB.</div> </div>

Multidimensionality evaluation of supply chain management integration

Integration is constantly reported in the literature as an essential feature of SCM. However, it is as difficult to define as to operationalize it, resulting in a lack of information on how to increase the level of integration among members. Thus, this research aims to evaluate the dimensionality of SCI, to check alignment with the features identified in the literature using multivariate statistical analysis. The methodology used was based on a questionnaire to assess the level of companies integration with suppliers of its supply chain. This instrument consisted of 21 items, with response options: yes, no or not applicable. The questions focused on evaluating the integration with suppliers, so each company consulted could answer a questionnaire for each supplier, since the intensity of relationships varies. Thus, 41 companies participated in the survey, resulting in 205 responses. Full-information item factor analysis and principal component analysis on the correlation matrix tetrachoric were used for the instrument dimensionality analysis. They are appropriate procedures for analysis of dichotomous variables. The results of this analysis enabled grouping the questionnaire items in the following underlying factors: trust, information sharing, partnership, collaboration or cooperation, and coordination. The identification of such factors such as dimensions of SCI enables greater understanding on how to raise the level of integration among the members of a supply chain.

Protocol: validation of the INCODE barometer to measure the innovation compe-tence through the Rasch Measurement Theory

<p class="Abstract">This communication presents a protocol in order to show the different phases that must be followed in order to validate the INCODE barometer, which is used to measure the innovation competence, with Rasch Measurement Theory. Five phases are stated: dimensionality analysis, individual reliability and validity analysis of ítems and persons, global reliability and validity analysis, and cathegory analysis.</p>