A Video Analysis of Intra- and Inter-professional Leadership Behaviours Within “The Burns Suite”: Identifying Key Leadership Models

Objective Leadership is particularly important in complex highly interprofessional health care contexts involving a number of staff, some from the same specialty (intraprofessional), and others from different specialties (interprofessional). The authors recently published the concept of “The Burns Suite” (TBS) as a novel simulation tool to deliver interprofessional and teamwork training. It is unclear which leadership behaviors are the most important in an interprofessional burns resuscitation scenario, and whether they can be modeled on to current leadership theory. The purpose of this study was to perform a comprehensive video analysis of leadership behaviors within TBS. Methods A total of 3 burns resuscitation simulations within TBS were recorded. The video analysis was grounded-theory inspired. Using predefined criteria, actions/interactions deemed as leadership behaviors were identified. Using an inductive iterative process, 8 main leadership behaviors were identified. Cohen’s κ coefficient was used to measure inter-rater agreement and calculated as κ = 0.7 (substantial agreement). Each video was watched 4 times, focusing on 1 of the 4 team members per viewing (senior surgeon, senior nurse, trainee surgeon, and trainee nurse). The frequency and types of leadership behavior of each of the 4 team members were recorded. Statistical significance to assess any differences was assessed using analysis of variance, whereby a p < 0.05 was taken to be significant. Leadership behaviors were triangulated with verbal cues and actions from the videos. Results All 3 scenarios were successfully completed. The mean scenario length was 22 minutes. A total of 362 leadership behaviors were recorded from the 12 participants. The most evident leadership behaviors of all team members were adhering to guidelines (which effectively equates to following Advanced Trauma and Life Support/Emergency Management of Severe Burns resuscitation guidelines and hence “maintaining standards”), followed by making decisions. Although in terms of total frequency the senior surgeon engaged in more leadership behaviors compared with the entire team, statistically there was no significant difference between all 4 members within the 8 leadership categories. This analysis highlights that “distributed leadership” was predominant, whereby leadership was “distributed” or “shared” among team members. The leadership behaviors within TBS also seemed to fall in line with the “direction, alignment, and commitment” ontology. Conclusions Effective leadership is essential for successful functioning of work teams and accomplishment of task goals. As the resuscitation of a patient with major burns is a dynamic event, team leaders require flexibility in their leadership behaviors to effectively adapt to changing situations. Understanding leadership behaviors of different team members within an authentic simulation can identify important behaviors required to optimize nontechnical skills in a major resuscitation. Furthermore, attempting to map these behaviors on to leadership models can help further our understanding of leadership theory. Collectively this can aid the development of refined simulation scenarios for team members, and can be extrapolated into other areas of simulation-based team training and interprofessional education.

Surface thermal analysis of North Brabant cities and neighbourhoods during heat waves

The urban heat island effect is often associated with large metropolises. However, in the Netherlands even small cities will be affected by the phenomenon in the future (Hove et al., 2011), due to the dispersed or mosaic urbanisation patterns in particularly the southern part of the country: the province of North Brabant. This study analyses the average night time land surface temperature (LST) of 21 North-Brabant urban areas through 22 satellite images retrieved by Modis 11A1 during the 2006 heat wave and uses Landsat 5 Thematic Mapper to map albedo and normalized difference temperature index (NDVI) values. Albedo, NDVI and imperviousness are found to play the most relevant role in the increase of nighttime LST. The surface cover cluster analysis of these three parameters reveals that the 12 “urban living environment” categories used in the region of North Brabant can actually be reduced to 7 categories, which simplifies the design guidelines to improve the surface thermal behaviour of the different neighbourhoods thus reducing the Urban Heat Island (UHI) effect in existing medium size cities and future developments adjacent to those cities.

Content analysis model to analyze facets of social mission of public library on the Facebook and in the websites

In this paper we present the development and the implementation of a content analysis model for observing aspects relating to the social mission of the public library on Facebook pages and websites. The model is unique and it was developed from the literature. There were designed the four categories for analysis Generate social capital and social cohesion, Consolidate democracy and citizenship, Social and digital inclusion and Fighting illiteracies. The model enabled the collection and the analysis of data applied to a case study consisting of 99 Portuguese public libraries with Facebook page. With this model of content analysis we observed the facets of social mission and we read the actions with social facets on the Facebook page and in the websites of public libraries. At the end we discuss in parallel the results of observation of the Facebook of libraries and the websites. By reading the description of the actions of the social mission, the general conclusion and the most immediate is that 99 public libraries on Facebook and websites rarely publish social character actions, and the results are little satisfying. The Portuguese public libraries highlight substantially the actions in the category Generate social capital and social cohesion.

A Quantitative analysis of pulsed signals emitted by wild bottlenose dolphins

Common bottlenose dolphins (Tursiops truncatus), produce a wide variety of vocal emissions for communication and echolocation, of which the pulsed repertoire has been the most difficult to categorize. Packets of high repetition, broadband pulses are still largely reported under a general designation of burst-pulses, and traditional attempts to classify these emissions rely mainly in their aural characteristics and in graphical aspects of spectrograms. Here, we present a quantitative analysis of pulsed signals emitted by wild bottlenose dolphins, in the Sado estuary, Portugal (2011-2014), and test the reliability of a traditional classification approach. Acoustic parameters (minimum frequency, maximum frequency, peak frequency, duration, repetition rate and inter-click-interval) were extracted from 930 pulsed signals, previously categorized using a traditional approach. Discriminant function analysis revealed a high reliability of the traditional classification approach (93.5% of pulsed signals were consistently assigned to their aurally based categories). According to the discriminant function analysis (Wilk's Λ = 0.11, F3, 2.41 = 282.75, P < 0.001), repetition rate is the feature that best enables the discrimination of different pulsed signals (structure coefficient = 0.98). Classification using hierarchical cluster analysis led to a similar categorization pattern: two main signal types with distinct magnitudes of repetition rate were clustered into five groups. The pulsed signals, here described, present significant differences in their time-frequency features, especially repetition rate (P < 0.001), inter-click-interval (P < 0.001) and duration (P < 0.001). We document the occurrence of a distinct signal type-short burst-pulses, and highlight the existence of a diverse repertoire of pulsed vocalizations emitted in graded sequences. The use of quantitative analysis of pulsed signals is essential to improve classifications and to better assess the contexts of emission, geographic variation and the functional significance of pulsed signals.

A Risk Analysis Method to Support Virtual Organization Partners’ Selection

Part 17: Risk Analysis

Understanding import diversification: an empirical analysis

This paper analyzes import diversification in an aggregated perspective -- Using a dataset for 60 countries covering the period 1995-2010, we study the main determinants of import diversification -- We expect to contribute to the current literature, taking into account that there have been few empirical studies addressing import diversification and more specifically, at the cross-country level -- We take into account variables classified into four categories: Structural factors, macroeconomic factors, international trade factors and political factors -- We find robust evidence that total factor productivity (TFP), capital stock, real Exchange rates and terms of trade are key drivers of import diversification -- On the other hand, domestic consumption and trade openness exert an effect leading to import concentration -- We interpret this finding, taking into account the theoretical framework provided by the international trade and growth theories

PCA 4 DCA: the application of principal component analysis to the Dendritic Cell Algorithm

As one of the newest members in the field of articial immune systems (AIS), the Dendritic Cell Algorithm (DCA) is based on behavioural models of natural dendritic cells (DCs). Unlike other AIS, the DCA does not rely on training data, instead domain or expert knowledge is required to predetermine the mapping between input signals from a particular instance to the three categories used by the DCA. This data preprocessing phase has received the criticism of having manually over-fitted the data to the algorithm, which is undesirable. Therefore, in this paper we have attempted to ascertain if it is possible to use principal component analysis (PCA) techniques to automatically categorise input data while still generating useful and accurate classication results. The integrated system is tested with a biometrics dataset for the stress recognition of automobile drivers. The experimental results have shown the application of PCA to the DCA for the purpose of automated data preprocessing is successful.

Kinetic analysis of metal uptake by dry and gel alginate particles

The kinetics of metal uptake by gel and dry calcium alginate beads was analysed using solutions of copper or lead ions. Gel beads sorbed metal ions faster than the dry ones and larger diffusivities of metal ions were calculated for gel beads: approximately 10−4 cm2/min vs. 10−6 cm2/min for dry beads. In accordance, scanning electron microscopy and nitrogen adsorption data revealed a low porosity of dry alginate particles. However, dry beads showed higher sorption capacities and a mechanical stability more suitable for large-scale use. Two sorption models were fitted to the kinetic results: the Lagergren pseudo-first order and the Ho and McKay pseudo-second order equations. The former was found to be the most adequate to model metal uptake by dry alginate beads and kinetic constants in the orders of 10−3 and 10−2 min−1 were obtained for lead solutions with concentrations up to 100 g/m3. The pseudo-first order model was also found to be valid to describe biosorbent operation with a real wastewater indicating that it can be used to design processes of metal sorption with alginate-based materials.

Code pattern analysis of object-oriented programming languages

Code patterns, including programming patterns and design patterns, are good references for programming language feature improvement and software re-engineering. However, to our knowledge, no existing research has attempted to detect code patterns based on code clone detection technology. In this study, we build upon the previous work and propose to detect and analyze code patterns from a collection of open source projects using NiPAT technology. Because design patterns are most closely associated with object-oriented languages, we choose Java and Python projects to conduct our study. The tool we use for detecting patterns is NiPAT, a pattern detecting tool originally developed for the TXL programming language based on the NiCad clone detector. We extend NiPAT for the Java and Python programming languages. Then, we try to identify all the patterns from the pattern report and classify them into several different categories. In the end of the study, we analyze all the patterns and compare the differences between Java and Python patterns.

Raman microscopy of formamide-intercalated kaolinites treated by controlled-rate thermal analysis technology

Raman spectroscopy of formamide-intercalated kaolinites treated using controlled-rate thermal analysis technology (CRTA), allowing the separation of adsorbed formamide from intercalated formamide in formamide-intercalated kaolinites, is reported. The Raman spectra of the CRTA-treated formamide-intercalated kaolinites are significantly different from those of the intercalated kaolinites, which display a combination of both intercalated and adsorbed formamide. An intense band is observed at 3629 cm-1, attributed to the inner surface hydroxyls hydrogen bonded to the formamide. Broad bands are observed at 3600 and 3639 cm-1, assigned to the inner surface hydroxyls, which are hydrogen bonded to the adsorbed water molecules. The hydroxyl-stretching band of the inner hydroxyl is observed at 3621 cm-1 in the Raman spectra of the CRTA-treated formamide-intercalated kaolinites. The results of thermal analysis show that the amount of intercalated formamide between the kaolinite layers is independent of the presence of water. Significant differences are observed in the CO stretching region between the adsorbed and intercalated formamide.

Detailed analysis of a conservative difference approximation for the time fractional diffusion equation

Diffusion equations that use time fractional derivatives are attractive because they describe a wealth of problems involving non-Markovian Random walks. The time fractional diffusion equation (TFDE) is obtained from the standard diffusion equation by replacing the first-order time derivative with a fractional derivative of order α ∈ (0, 1). Developing numerical methods for solving fractional partial differential equations is a new research field and the theoretical analysis of the numerical methods associated with them is not fully developed. In this paper an explicit conservative difference approximation (ECDA) for TFDE is proposed. We give a detailed analysis for this ECDA and generate discrete models of random walk suitable for simulating random variables whose spatial probability density evolves in time according to this fractional diffusion equation. The stability and convergence of the ECDA for TFDE in a bounded domain are discussed. Finally, some numerical examples are presented to show the application of the present technique.

Determination of preventive maintenance lead time using hybrid analysis

The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.