A three decade mixed-method bibliometric investigation of the IEEE Transactions on Engineering Management

This paper offers a comprehensive overview of the IEEE Transactions on Engineering Management (IEEE TEM) from 1985 to 2017. This paper employs a mixed-method examination based on an in-depth interview with the new editor-in-chief regarding the challenges for the future of IEEE TEM, along with a bibliometric analysis of the journal. By using Web of Science Core Collection data, the analysis maps the knowledge produced and disseminated by IEEE TEM, revealing the most cited papers, the most frequently occurring keywords and the interconnection between them, the most prolific authors and their coauthorship network, and the most prolific countries for published articles. This paper also shows the main avenues of research covered by IEEE TEM and their evolution through the analysis of the correlation of keywords. This paper offers an example application of a mixed-method bibliometric analysis, seeking to extend the quantitative findings by including other sources of data

Sensitivity analysis of marine Controlled-Source Electromagnetic data

Electromagnetic sounding methods represent one of the few geophysical techniques that can provide information about the state and the properties of deep continental crust and upper mantle. In particular, marine Controlled-Source Electromagnetic (mCSEM) method is being applied to offshore hydrocarbon exploration and providing encouraging results, as it can complement the information obtained from seismic elaborations, mainly the position of the elastic discontinuities, with a map of electrical conductivity, the principal "discriminator" between conductive water-bearing rocks and non-conductive hydrocarbon accumulations. The processing of mCSEM data can be problematic due to the non-uniqueness of the solution, the environmental and equipment noise, and the high computational power required when dealing with 3D inversion. This paper proposes a simplified procedure to study and rank the sensitivity of mCSEM in a canonical 1D scenario, with a single resistive anomaly embedded in a homogeneous background. We analyze the sensitivity of the data with respect to the most important test parameters, namely the frequency, target depth, thickness, and resistivity. In addition, this procedure is also utilized to validate the so-called T-equivalence theorem. The results of this study could assist the interpreter to highlight the reliability of the inverted parameters in a complex inversion environment

Noncoding RNA

International audienc

Careggi Smart Hospital: A mobile app for patients, citizens and healthcare staff

This paper presents a mobile app called “Careggi Smart Hospital” which has been developed for the Careggi Polyclinic in Florence. The application is designed for Android smartphones and tablets and it is freely downloadable from the Google Play Store. It provides various useful tools to the hospital's users such as personnel and structures finding, way-finding and the possibility to access personal medical records collected on regional electronic health record

Parental and peer support and modelling in relation to domain-specific physical activity participation in boys and girls from Germany

Background Physical activity (PA) as a precondition of child development is related with social environmental correlates. However, domain-specific PA and gender issues have been neglected in studies on social support and modelling and PA in school-aged children. The aim of this study was to assess the relationships of parental and peer modelling and social support with domain-specific PA participation in a large sample of school-aged children, taking gender into account. Methods 3,505 school children aged 6 to 17 years old participated in the German nationwide ‘MoMo’ cohort-study. By using the MoMo-PAQ the participants and their parents provided self-report data on perceived social support and social modelling and domain-specific PA participation. Relationships of social environmental variables and the physical outcomes were analysed by logistic regression analyses. Results At secondary school level, girls were less likely than boys to participate in physical activity in and outside of sports clubs, extra-curricular physical activity and in outdoor play (p < 0.05), but at primary school level this pattern only applied to club sport (p < 0.01). Girls also received less social support than boys (p < 0.01). Physical activity participation in all domains was associated with any of the social support and modelling variables and differences between physical activity domains and between boys and girls occurred. Most consistently physical activity in sports clubs was related with the social environmental correlates in boys (primary school: R2 = 0.60; secondary school: R2 = 0.45) and girls (primary school: R2 = 0.53; secondary school: R2 = 0.47). Conclusions In future, reciprocal relationships of social environmental variables and PA should be considered in longitudinal studies to obtain insights into the direction of the associations. Furthermore, interventions encompassing the social environment and focussed particularly on the promotion of domain-specific PA in girls in secondary school-age are warranted

Parental and peer support and modelling in relation to domain-specific physical activity participation in boys and girls from Germany

Background Physical activity (PA) as a precondition of child development is related with social environmental correlates. However, domain-specific PA and gender issues have been neglected in studies on social support and modelling and PA in school-aged children. The aim of this study was to assess the relationships of parental and peer modelling and social support with domain-specific PA participation in a large sample of school-aged children, taking gender into account. Methods 3,505 school children aged 6 to 17 years old participated in the German nationwide ‘MoMo’ cohort-study. By using the MoMo-PAQ the participants and their parents provided self-report data on perceived social support and social modelling and domain-specific PA participation. Relationships of social environmental variables and the physical outcomes were analysed by logistic regression analyses. Results At secondary school level, girls were less likely than boys to participate in physical activity in and outside of sports clubs, extra-curricular physical activity and in outdoor play (p < 0.05), but at primary school level this pattern only applied to club sport (p < 0.01). Girls also received less social support than boys (p < 0.01). Physical activity participation in all domains was associated with any of the social support and modelling variables and differences between physical activity domains and between boys and girls occurred. Most consistently physical activity in sports clubs was related with the social environmental correlates in boys (primary school: R2 = 0.60; secondary school: R2 = 0.45) and girls (primary school: R2 = 0.53; secondary school: R2 = 0.47). Conclusions In future, reciprocal relationships of social environmental variables and PA should be considered in longitudinal studies to obtain insights into the direction of the associations. Furthermore, interventions encompassing the social environment and focussed particularly on the promotion of domain-specific PA in girls in secondary school-age are warranted

Charge transport in a CoPt3 nanocrystal microwire

The electrical characteristics of single CoPt3 nanocrystal microwires formed by magnetic field-directed growth from colloidal solutions are presented. The wires comprise disordered assemblies of discrete nanocrystals, separated from each other by protective organic ligand shells. Electrical data indicate that the activated charge transport properties of the wires are determined by the nanocrystal charging energy, governed by the size and capacitance of the individual nanocrystals. Focused ion beam-assisted deposition of Pt metal at the wire-electrode junctions is employed to optimize the wire-electrode contacts, whilst maintaining the nanocrystal-dominated transport characteristics of these one-dimensional nanocrystal structures. (C) 2004 American Institute of Physics. (DOI:10.1063/1.1830684

Social Support and Modelling in Relation to Physical Activity Participation and Outdoor Play in Preschool Children

Physical activity during early childhood is a prerequisite for healthy development in many cases. The aim of this study was to assess the relationships of social modelling and support from parents, peers, and siblings and domain-specific physical activity participation in a nationwide sample of preschool boys and girls from Germany. 519 preschool children aged 4–6 and one of their parents participated in the ‘MoMo’ Wave 1 Study between 2009 and 2012. Participants and their parents provided self-reported data on social support modelling, and domain-specific physical activity participation (physical activity in sports clubs, physical activity outside of sports clubs, and outdoor play). Parental, peer, and sibling support and modelling were related to domain-specific physical activity: Parental support was particularly relevant for physical activity in sports clubs, and peer support for outdoor play. Parental modelling was only related to physical activity outside of sports clubs: Maternal modelling was a positive correlate in girls and paternal modelling in boys, respectively. Sibling and peer modelling were especially relevant for physical activity in sports clubs. The results were heterogeneous regarding types and providers of support and modelling. Thus, different providers and types of support should be targeted in physical activity promotion programs for preschool children

Fractal dimension of cerebral white matter : A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment

Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of these changes are the most relevant for cognitive decline. It has also become evident that visually-rated alterations do not fully explain the neuroimaging correlates of cognitive decline in SVD. Fractal dimension (FD), a unitless feature of structural complexity that can be computed from high-resolution T1-weighted images, has been recently applied to the neuroimaging evaluation of the human brain. Indeed, white matter (WM) and cortical gray matter (GM) exhibit an inherent structural complexity that can be measured through the FD. In our study, we included 64 patients (mean age \ub1 standard deviation, 74.6 \ub1 6.9, education 7.9 \ub1 4.2 years, 53% males) with SVD and mild cognitive impairment (MCI), and a control group of 24 healthy subjects (mean age \ub1 standard deviation, 72.3 \ub1 4.4 years, 50% males). With the aim of assessing whether the FD values of cerebral WM (WM FD) and cortical GM (GM FD) could be valuable structural predictors of cognitive performance in patients with SVD and MCI, we employed a machine learning strategy based on LASSO (least absolute shrinkage and selection operator) regression applied on a set of standard and advanced neuroimaging features in a nested cross-validation (CV) loop. This approach was aimed at 1) choosing the best predictive models, able to reliably predict the individual neuropsychological scores sensitive to attention and executive dysfunctions (prominent features of subcortical vascular cognitive impairment) and 2) identifying a features ranking according to their importance in the model through the assessment of the out-of-sample error. For each neuropsychological test, using 1000 repetitions of LASSO regression and 5000 random permutations, we found that the statistically significant models were those for the Montreal Cognitive Assessment scores (p-value =.039), Symbol Digit Modalities Test scores (p-value =.039), and Trail Making Test Part A scores (p-value =.025). Significant prediction of these scores was obtained using different sets of neuroimaging features in which the WM FD was the most frequently selected feature. In conclusion, we showed that a machine learning approach could be useful in SVD research field using standard and advanced neuroimaging features. Our study results raise the possibility that FD may represent a consistent feature in predicting cognitive decline in SVD that can complement standard imaging