Translocality and a Duality Principle in Generally Covariant Quantum Field Theory

It is argued that the formal rules of correspondence between local observation procedures and observables do not exhaust the entire physical content of generally covariant quantum field theory. This result is obtained by expressing the distinguishing features of the local kinematical structure of quantum field theory in the generally covariant context in terms of a translocal structure which carries the totality of the nonlocal kinematical informations in a local region. This gives rise to a duality principle at the dynamical level which emphasizes the significance of the underlying translocal structure for modelling a minimal algebra around a given point. We discuss the emergence of classical properties from this point of view.Comment: 12 pages. To appear in Classical Quantum Gravit

Self-esteem, general and sexual self-concepts in blind people

Background: People with visual disability have lower self-esteem and social skills than sighted people. This study was designed to describe self-esteem and general and sexual self-concepts in blind people. Materials and Methods: This was a cross-sectional study, conducted in the Isfahan University of Medical Sciences in 2013-2014. In this study, 138 visually impaired people participated from Isfahan Province Welfare Organization and were interviewed for measuring of self-esteem and self-concept using Eysenck self-esteem and Rogers’ self-concept questionnaires. The correlation between above two variables was measured using Statistical Package for the Social Sciences (SPSS) software by Pearson correlation test. Results: Mean [± standard deviation (SD)] age of patients was 30.9 ± 8 years. The mean (±SD) of general self-concept score was 11 ± 5.83. The mean (±SD) of self-esteem score was 16.62 ± 2.85. Pearson correlation results showed a significant positive correlation between self-esteem and general self-concept (r = 0.19, P = 0.025). The mean of sexual self-concept scores in five subscales (sexual anxiety, sexual self-efficacy, sexual self-esteem, sexual fear, and sexual depression) were correspondingly 11 ± 4.41, 19.53 ± 4.53, 12.96 ± 4.19, 13.48 ± 1.76, and 5.38 ± 2.36. Self-esteem and self-concept had significant positive correlation with sexual anxiety (r = 0.49; P < 0.001) (r =-.23; P < 0.001) and sexual fear (r = 0.25; P = 0.003) (r = 0.18; P = 0.02) and negative correlation with sexual self-efficacy (r =-0.26; P = 0.002) (r =-0.28; P = 0.001) and sexual-esteem (r =-0.34; P < 0.001) (r =-0.34; P < 0.001). Conclusion: Self-esteem and self-concept had significant correlation with sexual anxiety and sexual fear; and negative correlation with sexual self-efficacy and sexual-esteem. © 2015 Journal of Research in Medical Sciences

Critical thinking and clinical decision making in nurse‏

BACKGROUND: Today, nurses are exposed to everchanging complicated conditions in health care services, they provide. To be able to cope with these conditions effectively, they should be competent decision makers. Besides, as decision making conditions get more complicated, using critical thinking is a need. The current study was carried out to evaluate the relationship between critical thinking and clinical decision making, in nurses of critical and general care units of hospitals in Isfahan. In addition, it is also aimed to compare the nurses of critical and general units in critical thinking and clinical decision making. METHODS: This is a correlation, descriptive study of cross-sectional type. The participants are 140 nurses; 70 working in critical care unit and 70, working in general units. Sampling method was random stratified sampling and the data was collected using a questionnaire with three sections; containing items on demographic data, clinical decision making and California critical thinking skills test. The validity and reliability of the questionnaire was approved using content validity, test-retest method and internal correlation test. The data was analyzed using variance analysis, Pearson correlation and t-test. RESULTS: The mean score of critical thinking and clinical decision making was 10.61, 63.27 and 10.67, 61.66 for nurses of critical care and general units, respectively. No statistical significant difference between two groups was observed in the area of clinical decision making and critical thinking. In addition, no statistical correlation was observed between the clinical decision making and critical thinking. CONCLUSIONS: The findings of the study demonstrated that the mean score of critical thinking was low in nurses. Probably, it originates from the educational system shortages and also, the professional environment problems. Some experts believe that the reason for lack of correlation between critical thinking and clinical decision making goes back to the absence of appropriate tool to measure the correlatio

Designing and Psychometric Assessment of the Questionnaire for Artificial Airway Patients’ Satisfaction with Nurse's Non-verbal Communication during Nursing Cares

Background & Aim: Verbal communication disorder is one of the most important problems of mechanically ventilated patients which can lead to anxiety and decrease satisfaction. The purpose of this study is designing and psychometric assessment of the questionnaire for artificial airway patients’ satisfaction with nurses nonverbal communication during nursing cares. Materials & Methods: This is a methodological study which was performed using Waltz 2010 method in 4 steps, namely conceptual model definition, determination of goals and tools design, compiling initial plan, and determining reliability and validity in 2016. The study population includes all patients with artificial airway in 3 hospitals under the supervision of Shiraz University of Medical Sciences. Totally, 240 patients were selected for the study, using convenience sampling. The questionnaire validity was evaluated using face, construct, and content validities. Pearson correlation coefficient and Cronbach's alpha were used to evaluate the external and internal reliabilities. SPSS Software V.19 was used for data analysis. Results: The initial version of questionnaire was designed with 27 items. After face and content validation process, the second version was designed in 24 items. The maximum score for all items was 1.5. The values of CVI and CVR were obtained at 0.89 and 0.88, respectively. For construct validity, the items were reduced to 12, based on explanatory factor analysis. The final questionnaire was obtained in 3 satisfaction dimensions namely providing physiologic, social, and emotional-psychological needs with predictive power of 47.706. The Cronbach's alpha value was calculated at 0.67. Pearson correlation coefficient was calculated at 0.67, which suggests the validity and reliability of the questionnaire. Conclusion: Considering the limitation of data availability for evaluating the satisfaction of artificial airway patients with nursing communication, the questionnaire can be an efficient tool for detecting the patient-nurse communicational challenges and patients’ needs in different areas as well as improving care services quality

Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning

Brain segmentation is a fundamental first step in neuroimage analysis. In the case of fetal MRI, it is particularly challenging and important due to the arbitrary orientation of the fetus, organs that surround the fetal head, and intermittent fetal motion. Several promising methods have been proposed but are limited in their performance in challenging cases and in real-time segmentation. We aimed to develop a fully automatic segmentation method that independently segments sections of the fetal brain in 2D fetal MRI slices in real-time. To this end, we developed and evaluated a deep fully convolutional neural network based on 2D U-net and autocontext, and compared it to two alternative fast methods based on 1) a voxelwise fully convolutional network and 2) a method based on SIFT features, random forest and conditional random field. We trained the networks with manual brain masks on 250 stacks of training images, and tested on 17 stacks of normal fetal brain images as well as 18 stacks of extremely challenging cases based on extreme motion, noise, and severely abnormal brain shape. Experimental results show that our U-net approach outperformed the other methods and achieved average Dice metrics of 96.52% and 78.83% in the normal and challenging test sets, respectively. With an unprecedented performance and a test run time of about 1 second, our network can be used to segment the fetal brain in real-time while fetal MRI slices are being acquired. This can enable real-time motion tracking, motion detection, and 3D reconstruction of fetal brain MRI.Comment: This work has been submitted to ISBI 201