Development of a curriculum for endoscopy nurse education in Iran

Abstract Introduction: Nursing as a discipline and a profession is following to meet the needs of clients in clinical settings. The nurse participation and cooperation in the programs of diagnostic and therapeutic endoscopy has not been recorded in Iran. On the other hand, health care system needs to provide specialized care for patients under endoscopy. The aim of this study was to develop a professional curriculum for endoscopy nurse education in Iran. Method: This was a study to approve the content and curriculum for endoscopy nurse education in Iran using the Delphi method. This study carried out in three phases; a review of the literature on endoscopy nursing courses and training program in the world; assessment of expert groups and individuals associated with gastrointestinal endoscopy; and finally, a consensus on the curriculum of nursing endoscopy and its implementation. Results: Based on the endoscopy nurse training needs, eight priorities for education endoscopy nurse including theory, practical, and clinical professional was determined. Total hours of training were 210 hours, including 140 hours for theoretical and practical courses and 70 hours of clinical training. Different strategies were used to teach the theoretical and practical subjects. For theoretical teaching, lectures, group work, and self-learning were applied. Role Playing and simulation were used for practical training; and for clinical training, endoscopy clinical practice settings were determined. Conclusion: This training program was based on a participant survey on the digestive endoscopy and educational needs. This educational curriculum involved learning different areas of knowledge, attitudes, and skills for nurses to train caring of patients undergoing gastrointestinal endoscopy through an inter-professional education program. These special nursing educational programs can be contributed to the professional development of Iranian nurses

Classical Analogue of the Ionic Hubbard Model

In our earlier work [M. Hafez, {\em et al.}, Phys. Lett. A {\bf 373} (2009) 4479] we employed the flow equation method to obtain a classic effective model from a quantum mechanical parent Hamiltonian called, the ionic Hubbard model (IHM). The classical ionic Hubbard model (CIHM) obtained in this way contains solely Fermionic occupation numbers of two species corresponding to particles with \up and \down spin, respectively. In this paper, we employ the transfer matrix method to analytically solve the CIHM at finite temperature in one dimension. In the limit of zero temperature, we find two insulating phases at large and small Coulomb interaction strength, $U$, mediated with a gap-less metallic phase, resulting in two continuous metal-insulator transitions. Our results are further supported with Monte Carlo simulations.Comment: 12 figure

The Effects of Cognitive – Behavior Therapy and Drug Therapy on Quality of Life and Symptoms of Patients with Irritable Bowel Syndrome

Abstract: Background & Aims: Psychological treatment and the efficacy of drug therapy are considered to be useful in quality of life and symptoms of patients with irritable bowel syndrome. The aim of this study was to examine the effects of cognitive-behavior therapy associated with drug therapy in comparison to drug therapy alone on the quality of life and symptoms of IBS patients with diarrhea predominance. Method: This study was a randomized clinical trial on 64 IBS patients. The patients were selected according to Rome-III criteria, and were divided into the two groups. Bowel Symptoms Severity and Frequency Scale (BSS-FS) and Quality Of Life (QOL-IBS) were used for evaluation of patients’ symptoms. The first group underwent cognitive-behavior therapy with medication therapy, and the second group only received medication. Data were analyzed using analysis of multiple covariances (MANCOVA). Results: The two groups showed significant difference in the QOL-IBS in post treatment and follow-up stages (P 0.05). Conclusion: Cognitive-behavior therapy associated with drug therapy can be useful in IBS patients with diarrhea predominance. However, stopping this treatment may lead to recurrence of the symptoms. Keywords: Neck muscles, Forward head posture, Craniovertebral angle, Electromyography, Pressure Bio-feedback devic

A dish-based semi-quantitative food frequency questionnaire for assessment of dietary intakes in epidemiologic studies in Iran: design and development

BACKGROUND: Earlier forms of food frequency questionnaire (FFQ) used in Iran have extensive lists of foods, traditional categories and food-based design, mostly with the interviewer-administered approach. The aim of the current paper is to describe the development of a dish-based, machine-readable, semi-quantitative food frequency questionnaire (DFQ). METHODS: Within the framework of the Study on the Epidemiology of Psychological, Alimentary Health and Nutrition project, we created a novel FFQ using Harvard FFQ as a model. RESULTS: THE FOLLOWING STEPS WERE TAKEN TO DEVELOP THE QUESTIONNAIRE: Construction of a list of commonly consumed Iranian foods, definition of portion sizes, design of response options for consumption frequency of each food item and finally a pilot test of the preliminary DFQ. From a comprehensive list of foods and mixed dishes, we included those that were nutrient-rich, consumed reasonably often or contributed to between-person variations. We focused on mixed dishes, rather than their ingredients, along with foods. To shorten the list, the related food items or mixed dishes were categorized together in one food group. These exclusions resulted in a list of 106 foods or dishes in the questionnaire. The portion sizes used in the FFQ were obtained from our earlier studies that used dietary recalls and food records. The frequency response options for the food list varied from 6-9 choices from "never or less than once a month" to "12 or more times per day". CONCLUSIONS: The DFQ could be a reasonable dietary assessment tool for future epidemiological studies in the country. Validation studies are required to assess the validity and reliability of this newly developed questionnaire.AH Keshteli, Ahmad Esmaillzadeh, Somayeh Rajaie, Gholamreza Askari, Christine Feinle-Bisset and Peyman Adib

2D Dimensionality Reduction Methods without Loss

In this paper, several two-dimensional extensions of principal component analysis (PCA) and linear discriminant analysis (LDA) techniques has been applied in a lossless dimensionality reduction framework, for face recognition application. In this framework, the benefits of dimensionality reduction were used to improve the performance of its predictive model, which was a support vector machine (SVM) classifier. At the same time, the loss of the useful information was minimized using the projection penalty idea. The well-known face databases were used to train and evaluate the proposed methods. The experimental results indicated that the proposed methods had a higher average classification accuracy in general compared to the classification based on Euclidean distance, and also compared to the methods which first extracted features based on dimensionality reduction technics, and then used SVM classifier as the predictive model

Machine learning for Internet of Things data analysis: A survey

Rapid developments in hardware, software, and communication technologies have allowed the emergence of Internet-connected sensory devices that provide observation and data measurement from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As the numbers grow and technologies become more mature, the volume of data published will increase. Internet-connected devices technology, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interaction between the physical and cyber worlds. In addition to increased volume, the IoT generates Big Data characterized by velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this Big Data is the key to developing smart IoT applications. This article assesses the different machine learning methods that deal with the challenges in IoT data by considering smart cities as the main use case. The key contribution of this study is presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying Support Vector Machine (SVM) on Aarhus Smart City traffic data is presented for a more detailed exploration.Comment: Digital Communications and Networks (2017

Pimpinella anisum in the treatment of functional dyspepsia: A double-blind, randomized clinical trial

Background: We aimed to evaluate the effects of Pimpinella anisum (anise) from Apiaceae family on relieving the symptoms of postprandial distress syndrome (PDS) in this double-blind randomized clinical trial. Materials and Methods: Totally, 107 patients attending the gastroenterology clinic, aged 18-65 years, diagnosed with PDS according to ROME III criteria and signed a written consent form were enrolled. They were randomized to receive either anise or placebo, blindly, for 4 weeks. Anise group included 47 patients and received anise powders, 3 g after each meal (3 times/day). Control group involved 60 patients and received placebo powders (corn starch), 3 gafter each meal (3 times/day). The severity of Functional dyspepsia (FD) symptoms was assessed by FD severity scale. Assessments were done at baseline and by the end of weeks 2, 4 and 12. Mean scores of severity of FD symptoms and the frequency distribution of patients across the study period were compared. Results: The age, sex, body mass index, smoking history, and coffee drinking pattern of the intervention and control groups were not significantly different. Mean (standard deviation) total scores of FD severity scale before intervention in the anise and control groups were 10.6 (4.1) and 10.96 (4.1), respectively (P = 0.6). They were 7.04 (4.1) and 12.30 (4.3) by week 2, respectively (P = 0.0001), 2.44 (4.2) and 13.05 (5.2) by week 4, respectively (P = 0.0001), and 1.08 (3.8) and 13.30 (6.2) by week 12, respectively (P = 0.0001). Conclusion: This study showed the effectiveness of anise in relieving the symptoms of postpartum depression. The findings were consistent across the study period at weeks 2, 4 and 12. © 2015, Isfahan University of Medical Sciences(IUMS). All rights reserved

Life cycle in practice: capacity building aiming European SME’s

The application of life cycle approaches – including life cycle assessment, ecodesign and environmental labelling – is becoming an increasing reality for business, and a growing challenge in many economic sectors. Businesses are facing increasing legal and market requirements to enhance resource efficiency and reduce the environmental impact of their products & services. To significantly address this challenge, the Life Cycle in Practice (LCiP) project was conceived, aiming to promote the uptake of LC approaches particularly in SMEs. The LCiP project helps SMEs in France, Belgium, Portugal and Spain reduce the environmental impacts of their products and services across the entire Life Cycle in three sectors: Buildings & Construction, Waste Management and Energy Equipment. LCiP’s specific objectives are to foster the widespread uptake of these approaches by SMEs beyond the duration of the project, by (i) Demonstrating the environmental and business benefits of applying LC Approaches through practical application in 32 businesses; (ii) Providing physical and online resource centres to support regional application of LC approaches; (iii) Building capacity for on-going implementation of LC approaches through a network of Life Cycle Champions and (iv) (Re)designing practical tools & methods tailored to the needs of the three industrial sectors. This paper presents the project's activities and expected results, as well as the conclusions of a maturity assessment on life cycle approaches that has been performed in the three sectors and four partner regions, as a means to identify needs and gaps that LCiP should fulfil

Study of Inertia and Compressibility Effects on the Density Wave Oscillations of Two-Phase Boiling Flows in Parallel Channels

In this research, a theoretical model is presented to investigate the density wave oscillations (DWOs), in two horizontal parallel channels with lumped parameter model based on two phase homogeneous hypothesis. The parallel channel is composed of the entrance section, heating section and outlet section and the model consists of the boiling channel model, pressure drop model, parallel channel model, constructive model and inertia and compressibility effects, while subcooled boiling effect is neglected and the governing equations are solved by Gear method. The model is validated with experimental data of a single channel flow instability experiment. Then the flow instability in twin channel system is studied under different conditions. This model can analyze the effects of external parameters, such as fluid inertia and compressible gases on the stability margins of density wave oscillations. The results show that, the fluid inertia and compressible gases can significantly change the stability margins of two parallel channels; in fact, the stability behavior of two parallel channel system improves with increasing the inlet inertia and outlet compressibility but, increasing the outlet inertia and inlet compressibility have negative effects the system stability