The impact of ethnic tourism on gender equality: A case study of Iran’s Baluchistan women

Ethnic tourism makes women more visible in the public sphere in traditional ethnic communities. In many ethnic traditional communities such as Iran’s Baluchistan, women see ethnic tourism as a window into other cultures. In these kinds of communities, women are often isolated from contact with outsiders because of their responsibilities, which are typically focused on managing the household, while men are responsible for trade and travel. This paper examines how ethnic tourism affects gender equality and helps women in Iran’s Baluchistan for their voices to be heard in the community. This research illustrates the potential of ethnic tourism as a vehicle for gender equality through increasing social interactions and cultural exchanges, leading women to hold greater awareness of their human rights. Thus, the idea of ethnic tourism for gender equality in ethnic communities can be seen as a new way of understanding the potential of ethnic tourism for women equality. The results of the research were gathered through fieldwork as the major methodological frame and during the fieldwork, different specific methods were used to collect empirical data: interviews and participant observation. The theoretical structure for analyzing interview data was grounded in theory. Moreover, visual data in the form of photography was collected throughout all the stages of the fieldwork

Investigation of Deep Learning-Based Filtered Density Function for Large Eddy Simulation of Turbulent Scalar Mixing

The present investigation focuses on the application of deep neural network (DNN) models to predict the filtered density function (FDF) of mixture fraction in large eddy simulation (LES) of variable density mixing layers with conserved scalar mixing. A systematic training method is proposed to select the DNN-FDF model training sample size and architecture via learning curves, thereby reducing bias and variance. Two DNN-FDF models are developed: one trained on the FDFs generated from direct numerical simulation (DNS), and another trained with low-fidelity simulations in a zero-dimensional pairwise mixing stirred reactor (PMSR). The accuracy and consistency of both DNN-FDF models are established by comparing their predicted scalar filtered moments with those of conventional LES, in which the transport equations corresponding to these moments are directly solved. Further, DNN-FDF approach is shown to perform better than the widely used $\beta$-FDF method, particularly for multi-modal FDF shapes and higher variances. Additionally, DNN-FDF results are also assessed via comparison with data obtained by DNS and the transported FDF method. The latter involves LES simulations coupled with the Monte Carlo (MC) methods which directly account for the mixture fraction FDF. The DNN-FDF results compare favorably with those of DNS and transported FDF method. Furthermore, DNN-FDF models exhibit good predictive capabilities compared to filtered DNS for filtering of highly non-linear functions, highlighting their potential for applications in turbulent reacting flow simulations. Overall, the DNN-FDF approach offers a more accurate alternative to the conventional presumed FDF method for describing turbulent scalar transport in a cost-effective manner

Large Eddy Simulation-Based Analysis of Entropy Generation in a Turbulent Nonpremixed Flame

LES (large eddy simulation) is employed for prediction and analysis of entropy generation in turbulent combustion. The entropy transport equation is considered in LES. This equation contains several unclosed entropy generation terms corresponding to irreversible processes: heat conduction, mass diffusion, chemical reaction and viscous dissipation. The SGS (subgrid scale) closure of these effects is provided by a methodology termed the En-FDF (entropy filtered density function), which contains complete statistical information about SGS variation of scalars and entropy. In the En-FDF, the effects of chemical reaction and its associated entropy generation appear in closed forms. The methodology is applied for LES of a nonpremixed jet flame. Predictions show good agreements with the experimental data. Analysis of entropy generation shows that heat conduction and chemical reaction are the main sources of irreversibility in this flame. The sensitivity of individual entropy generation effects to turbulence intensity is studied

Spiritual well-being and moral distress among Iranian nurses

Moral distress is increasingly recognized as a problem affecting healthcare professionals, especially nurses. If not addressed, it may create job dissatisfaction, withdrawal from the moral dimensions of patient care, or even encourage one to leave the profession. Spiritual well-being is a concept which is considered when dealing with problems and stress relating to a variety of issues. Objective: This research aimed to examine the relationship between spiritual well-being and moral distress among a sample of Iranian nurses and also to study the determinant factors of moral distress and spiritual well-being in nurses. Research design: A cross-sectional, correlational design was employed to collect data from 193 nurses using the Spiritual Well-Being Scale and the Moral Distress Scale-Revised. Ethical considerations: This study was approved by the Regional Committee of Medical Research Ethics. The ethical principles of voluntary participation, anonymity, and confidentiality were considered. Findings: Mean scores of spiritual well-being and moral distress were 94.73+15.89 and 109.56+58.70, respectively. There was no significant correlation between spiritual well-being and moral distress (r ¼ �.053, p ¼ .462). Marital status and job satisfaction were found to be independent predictors of spiritual well-being. However, gender and educational levels were found to be independent predictors for moral distress. Age, working in rotation shifts, and a tendency to leave the current job also became significant after adjusting other factors for moral distress. Discussion and conclusion:This study could not support the relationship between spiritual well-being and moral distress. However, the results showed that moral distress is related to many elements including individual ideals and differences as well as organizational factors. Informing nurses about moral distress an

Joint Velocity Scalar Filtered Density Function for Large Eddy Simulation of Turbulent Reacting Flows

The joint ``velocity-scalar' filtered density function (FDF) methodology is developed and implemented for large eddy simulation (LES) of turbulent reacting flows. In FDF, the effects of the unresolved subgrid scales (SGS) are taken into account by considering the joint probability density function (PDF) of the velocity and scalar fields. An exact transport equation is derived for the FDF in which the effects of SGS convection and chemical reaction are in closed forms. The unclosed terms in this equation are modeled by considering an equivalent set of stochastic differential equations (SDEs) which is similar to that typically used in Reynolds-averaged simulation (RAS) procedures. The SDEs are solved numerically by a Lagrangian Monte Carlo procedure in which the It^o-Gikhman character of the SDEs is preserved. The consistency of the proposed SDEs and the convergence of the Monte Carlo solution are assessed. It is shown that the FDF results agree well with those obtained by a ``conventional' finite-difference LES procedure in which the transport equations corresponding to the filtered quantities are solved directly. The FDF results are also compared with those obtained by the Smagorinsky closure, and all the results are assessed via comparison with data obtained by direct numerical simulation of a temporally developing mixing layer involving transport of a passive scalar. It is shown that all the first twomoments including the scalar fluxes are predicted well by FDF. The predictive capabilities of the FDF are further demonstrated by LES of reacting shear flows. The predictions show favorable agreements with laboratory data, and demonstrate several of the features as observed experimentally

Argon Plasma Coagulation in Treatment of Post Intubation Tracheal Stenosis

INTRODUCTION: Acquired tracheal stenosis can be created by various malignant or benign causes. The most common cause of acquired non-malignant tracheal stenosis is endotracheal intubation, even for a short period. Argon plasma coagulation is a non-contact method of thermal hemostasis. Argon plasma coagulation can be used easily and fast and has low depth of penetration. METHODS: This study is single blinded. Subjects are patients with tracheal stenosis after endotracheal intubation who were selected by non-probability sampling and were studied from March 2007 to November 2009 in bronchoscopy and laser center of Masih Daneshvari Hospital, Tehran. First, for each patient, a diagnostic flexible bronchoscopy was performed to identify the type, location, and severity of the stenosis. Then, under general anesthesia, patients underwent rigid bronchoscopy. Then, with Argon plasma coagulation device (ERBE VIO 200D) the stenosis was removed as possible. After two weeks, a new PFT (pulmonary function test) was done for checking the obstructive signs.RESULTS: Of these 34 patients, 24 were asymptomatic for more than 1 year and responded to treatment(70/6%), 5 were asymptomatic for more than 10 months and less than 12 months (14/7%) and 5 did not have asymptomatic periods more than 10 months, and did not respond to treatment. In PFT follow-ups, FEV1 in all patients who were asymptomatic for more than 10 months had a significant progress; therefore, in 27 out of 29 patients at the end of the study, FEV1 was more than 90% and 2 patients had FEV1 of 70-90%.CONCLUSION: In fact, although the surgical treatment remains the main treatment of tracheal stenosis after intubation (PITS), if this method is not possible for any reason, APC is very useful as a safe and effective method

Progress in the Prediction of Entropy Generation in Turbulent Reacting Flows Using Large Eddy Simulation

An overview is presented of the recent developments in the application of large eddy simulation (LES) for prediction and analysis of local entropy generation in turbulent reacting flows. A challenging issue in such LES is subgrid-scale (SGS) modeling of filtered entropy generation terms. An effective closure strategy, recently developed, is based on the filtered density function (FDF) methodology with inclusion of entropy variations. This methodology, titled entropy FDF (En-FDF), is the main focus of this article. The En-FDF has been introduced as the joint velocity-scalar-turbulent frequency-entropy FDF and the marginal scalar-entropy FDF. Both formulations contain the chemical reaction and its entropy generation effects in closed forms. The former constitutes the most comprehensive form of the En-FDF and provides closure for all of the unclosed terms in LES transport equations. The latter is the marginal En-FDF and accounts for entropy generation effects, as well as scalar-entropy statistics. The En-FDF methodologies are described, and some of their recent predictions of entropy statistics and entropy generation in turbulent shear flows are presented

The Effect of Foot Massage on the Consciousness Levels in Comatose Patients With Brain Injury Hospitalized in Intensive Care Unit (Icu): A Randomised Control Trial

Introduction: Coma results from traumatic or non-traumatic brain injuries. Foot massage can influence the level of consciousness in comatose patients. The purpose of this study was to determine the effects of foot massage on the level of consciousness in comatose patients due to brain injury who were hospitalized in the ICUs of selected hospitals in Qazvin. Methods: This study was a clinical trial which was conducted on 40 patients with coma who were hospitalized in the ICUs of Shahid Rajaee and Razi hospitals in Qazvin in 2014. Patients were assigned to case and control groups, using randomize blocked allocation. Massage of both feet was performed in a Stroke manner (5 minutes for each foot) and once a day for 14 days. Then, the level of consciousness was recorded using Glasgow Coma Scale. Statistical tests (chi-square, Independent t-test, dependent t-test and Repeated Measures variance analysis) were used for analysis. Results: The results showed that there is significant difference between the mean of consciousness level before (5.80±1.58) andafter (10.6±2.41) massage in the intervention group(P=0.001). While the mean of consciousness level was (5.3±1.72)before and (6.94±3.03)after the intervention in the control group andit was not statistically significant (P=0.06). Conclusion: Foot massage could increase the level of consciousness among patients in comatose patients due to brain injury. It is recommended to use this intervention for increasing patientsconsciousness level

The Predictive Factors of Job Performance in Nurses' Moral Distress

Introduction: Moral distress is one of the most complex ethical problems for nurses working in Intensive Care Units. Desired job performance of the nurse guarantees the quality of health care provided to patients and is an important factor in accelerating the process of treatment and recovery of patients. This study was conducted to investigate the predictive factors of job performance in nurses' moral distress. Methods: This is a descriptive cross-sectional study, in which 256 nurses working in ICU wards of private and public hospitals of Qazvin province (from January to March 2019) were selected through convenience sampling method. Demographic characteristics questionnaire, Six Dimension Scale of Nursing Performance and Modified Moral Distress Scale-Revised were used for data collection. Statistical analysis was performed using linear regression model test in SPSS 22. Results: The results showed that the mean score of nurses' moral distress was 171.37±55.63. In multivariate linear regression model, only educational dimension of job performance in both frequency (β=-26.37, P=0.001) and quality (β =-76.15, P=0.025) correlated significantly with moral distress. Conclusion: Based on the results of the present study, educational dimension of job performance is a predictive factor for moral distress. Therefore, steps can be taken to reduce moral distress inclinical settings, such as the use of nurses with specialized training in Intensive Care Units, paying special attention to teaching ethical issues in nursing centers and holding retraining courses for nurses. Keywords: Job performance, Moral distress, Nursin