A study on the ethical components of nursing practice (moral distress, ethical sensitivity, ethical decision)

This paper is an applied research in terms of objective and a descriptive research in terms of method. Having prepared the research plan, a questionnaire was designed based on goals and hypotheses of the research and was sent to the statistical universe. Also this paper is a field research in terms of data collection. As regards theoretical bases of the research, library data collection method has been applied. So, the required data has been gathered by referring to the related references, books, libraries and so on. To design a questionnaire and gather the opinions of the statistical universe members, field study method and researcher-made questionnaire have been used. The statistical universe comprises nurses and head of ICU and head nurses of Najmieh Hospital in Tehran. The respondents were selected by random sampling method. Also to estimate sample size, Morgan table was applied. The statistical universe consists of 65 members and according to the table, 56 questionnaires were determined for the research. So 60 questionnaires were sent and 58 ones were returned. Face and content validity of the research tool were approved by experts. The test reliability was estimated 0.777 by calculating Cronbach's alpha coefficient. In this paper, factor analysis based on partial least squares structural equations method has been applied to analyze more important factors and coefficients, estimate independent variables coefficients and even determine effectiveness of each independent variable on each other and determine appropriateness of the questions and their coefficients in explaining the related index. The main result of this paper presents a proper model for the relation of effective variables on nurse performance by using regression model. © IDOSI Publications, 2014

Visualization of clinical teaching citations using social network analysis

Background: Analyzing the previous research literature in the field of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA). Methods: We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. Results: Based on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills. Conclusions: In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects. © 2021, The Author(s)

Effect of Al2O3 and Cr2O3 on loquidus temperatures in the cristobalite and tridymite primary phase fields of the MgO-"FeO"-SiO2 ststem in equilibrium with metallic iron

The effects of alumina and chromite impurities on the liquidus temperatures in the cristobalite/tridymite (SiO2) primary phase fields in the MgO-FeO-SiO, system in equilibrium with metallic iron have been investigated experimentally. Using high temperature equilibration and quenching followed by electron probe X-ray microanalysis (EPMA), liquiclus isotherms have been determined in the temperatures range 1 673 to 1 898 K. The results are presented in the form of pseudo-ternary sections of the MgO-FeO-SiO, system at 2, 3 and 5 wt% Al2O3, 2 wt% Cr2O3, and 2 wt% Cr2O3+2 wt% Al2O3. The study enables the liquidus to be described for a range of SiO2/MgO and MgO/FeO ratios. It was found that liquiclus temperatures in the cristobalite and tridymite primary phase fields, decrease significantly with the addition of Al2O3 and Cr2O3

Dendritic cells from aged subjects contribute to chronic airway inflammation by activating bronchial epithelial cells under steady state

The mechanisms underlying the increased susceptibility of the elderly to respiratory infections are not well understood. The crosstalk between the dendritic cells (DCs) and epithelial cells is essential in maintaining tolerance as well as in generating immunity in the respiratory mucosa. DCs from aged subjects display an enhanced basal level of activation, which can affect the function of epithelial cells. Our results suggest that this is indeed the scenario as exposure of primary bronchial epithelial cells (PBECs) to supernatants from unstimulated DCs of aged subjects resulted in activation of PBECs. The expression of CCL20, CCL26, CXCL10, mucin, and CD54 was significantly increased in the PBECs exposed to aged DC supernatants, but not to young DC supernatants. Furthermore, aged DC supernatants also enhanced the permeability of the PBEC barrier. We also found that DCs from aged subjects spontaneously secreted increased levels of pro-inflammatory mediators, interleukin-6, tumor necrosis factor (TNF)-α, and metalloproteinase A disintegrin family of metalloproteinase 10, which can affect the functions of PBECs. Finally, we demonstrated that TNF-α, present in the supernatant of DCs from aged subjects, was the primary pro-inflammatory mediator that affected PBEC functions. Thus, age-associated alterations in DC–epithelial interactions contribute to chronic airway inflammation in the elderly, increasing their susceptibility to respiratory diseases

Low-energy switch based on a cavity soliton laser

We show that the position of a soliton in a cavity soliton laser can be controlled by injecting incoherent or coherent beams close to the soliton. The interaction between the CS and the injected beam can be attractive or repulsive depending on the type of injection. The energy necessary to drift the soliton can be very small if the injected beam is frequency matched with the soliton and the laser operates near the drift instability threshold of the soliton. In this way an optical switch at very low energy in a miniaturized device can be realized

Soil type identification for autonomous excavation based on dissipation energy

Abstract: Knowledge of soil properties and identifying worked soil type are critical for optimized control strategies of an autonomous excavator. The current paper presents an online soil type identification based on real-time measuring of energy components for horizontal dragging tasks. The online energy measurement, calculated by integration of the force acting on an object along a displacement, makes the resulting data robust to noise. Analysis of the energy measurement reveals that the correlation between potential–dissipation energy and displacement has unique characteristics for any given soil, independently of the amount of applied force. This leads to the creation of a new soil ‘energy map ’ with respect to various soil types. A mathematical model has been developed for each soil’s ‘energy map’. An identification algorithm has been developed to utilize these prior mathematical models for cross-referencing with online total energy of the currently worked soil to identify soil type online. The overall approach has been validated experimentally on a laboratory test-rig using mulch, gravel, sand, and clay soils