760 research outputs found
Assessment of the Nexus between Groundwater Extraction and Greenhouse Gas Emissions Employing Aquifer Modelling
AbstractOne of the main sources of Greenhouse Gas Emissions (GHG) is electricity consumption which is getting used for different purposes.Water pumping, especially, pumping from deep groundwater resources consumes a lot of energy. In arid and semi-arid areas, in which groundwater is the only source of water, water pumping is done for different purposes such as agricultural, industrial and urban uses. Kerman plain is one of these arid and semi-arid areas which is located in South East of Iran. Groundwater reliance and aquifer decline are the most prominent challenges that this area is faced with in recent years. This challenges increase the demand for more electricity consumption to pump water from the aquifer so that CO2 emissions will be increased. A large percentage of water extraction from the aquifer is used for agricultural purposes. In this paper, by modelling Kerman plain aquifer with MODFLOW software by using Geographical Information System (GIS) database and also studying height of groundwater table from 1999 to 2012, electricity energy consumption of groundwater extraction for agricultural, industrial and urban water supply is calculated and the CO2 emissions trends resulted from electricity energy consumption is evaluated. Then model results are examined for a business as usual (BAU) scenario of changes in water resources. As a result the amount of CO2 emitted from groundwater abstraction by three mentioned sectors is calculated for specified time horizon. Finally, some suggestions are presented for reducing greenhouse gas emissions for the time horizon
Phase mixing of standing Alfven waves with shear flows in solar spicules
Alfvenic waves are thought to play an important role in coronal heating and
solar wind acceleration. Here we investigate the dissipation of such waves due
to phase mixing at the presence of shear flow and field in the stratified
atmosphere of solar spicules. The initial flow is assumed to be directed along
spicule axis and to vary linearly in the x direction and the equilibrium
magnetic field is taken 2-dimensional and divergence-free. It is determined
that the shear flow and field can fasten the damping of standing Alfven waves.
In spite of propagating Alfven waves, standing Alfven waves in Solar spicules
dissipate in a few periods. As height increases, the perturbed velocity
amplitude does increase in contrast to the behavior of perturbed magnetic
field. Moreover, it should be emphasized that the stratification due to
gravity, shear flow and field are the facts that should be considered in MHD
models in spicules.Comment: Accepted for publication in Astrophysics & Space Scienc
Human Rights, Women and Islam
The ISIM invited 2003 Nobel Peace Prize winner Shirin Ebadi for her first formal visit to the Netherlands where she met with members of NGOs, government officials, scholars, students, and activists from 15-17 April 2004. On 16 April she gave a lecture at the Nieuwe of Littéraire Sociëteit de Witte in The Hague entitled, Human Rights, Women and Islam which is presented below in abridged form with some audience questions
Implications of surface noise for the motional coherence of trapped ions
Electric noise from metallic surfaces is a major obstacle towards quantum
applications with trapped ions due to motional heating of the ions. Here, we
discuss how the same noise source can also lead to pure dephasing of motional
quantum states. The mechanism is particularly relevant at small ion-surface
distances, thus imposing a new constraint on trap miniaturization. By means of
a free induction decay experiment, we measure the dephasing time of the motion
of a single ion trapped 50~m above a Cu-Al surface. From the dephasing
times we extract the integrated noise below the secular frequency of the ion.
We find that none of the most commonly discussed surface noise models for ion
traps describes both, the observed heating as well as the measured dephasing,
satisfactorily. Thus, our measurements provide a benchmark for future models
for the electric noise emitted by metallic surfaces.Comment: (5 pages, 4 figures
Designing and Psychometric Evaluation of the Competency Inventory for Postgraduate Students of Intensive Care Nursing
Background: Today, the role of expert clinical nurses is highlighted because their presence is necessary for guaranteeing the quality of nursing care provided for the patients. However, there are no proper instruments for measuring the clinical competence of postgraduate students in intensive care nursing.
Objectives: The present study aimed at development and psychometric evaluation of the clinical-competence inventory for postgraduate students of intensive care nursing.
Patients and Methods: A methodological study was conducted at state nursing schools of Iran. The participants were postgraduate students of intensive care nursing, who were being trained at 16 nursing schools throughout Iran, during year 2014. After examining some relevant texts, the first draft of the inventory was designed with 60 items. In order to confirm its face and content validity, a panel of experts and students examined the inventory. The final draft, which contained 44 items, was distributed among postgraduate students of intensive care nursing, and 217 students answered the inventory. The construct validity was verified using exploratory factor analysis. The reliability of the inventory was verified using consistency tests.
Results: Firstly an instrument with 60 items was developed. Next, the face and content validity of the instrument was assessed by 15 students and 11 experts. Overall, 16 items were removed through validity assessment and 44 items remained in the final draft. The content validity index of the final draft was 0.90. Moreover, the content validity ration of 44 items ranged between 0.75 and 1. The Cronbach’s alpha coefficient of the inventory was 0.95 and the intraclass correlation coefficient (ICC) of the test-retest results was 0.96. To examine the construct validity of the final draft, it was administered for 217 postgraduate students of intensive care nursing and five factors, with Eigenvalues above one and loading level equal to or above 0.4, were extracted through exploratory factor analysis.
Conclusions: The inventory developed in this study is a suitable index for evaluating the efficacy of postgraduate students in the field of intensive care nursing
Development and psychometric evaluation of the patient safety violation scale in medical oncology units in Iran
Background: Patient safety is one of the key components of nursing care for cancer cases. Valid and reliable context-based instruments are necessary for accurate evaluation of patient safety in oncology units. The aim of the present study was to develop and evaluate the psychometric properties of the Patient Safety Violation Scale in medical oncology units in Iran. Materials and Methods: In this methodological study, a pool of 58 items was generated through reviewing the existing literature. The validity of the 58-item scale was assessed through calculating impact score, content validity ratio, and content validity index for its items as well as conducting exploratory factor analysis. The reliability of the scale was evaluated by assessing its internal consistency and testretest stability. Study sample consisted of 300 oncology nurses who were recruited from thirteen teaching hospitals affiliated to Tehran University of Medical Sciences, Tehran, Iran. Results: Sixteen items were excluded from the scale due to having low impact scores, content validity ratios, or content validity indices. In exploratory factor analysis, the remaining 42 items were loaded on five factors including patient fall, verification of patientidentity, harm during care delivery, delay in care delivery, and medication errors. These five factors explained 62 of the total variance. The Cronbach's alpha of the scale and the test-retest interclass correlation coefficient were equal to 0.933 and 0.92, respectively. Conclusions: The 42-item Patient Safety Violation Scale is a simple and short scale which has acceptable validity and reliability. Consequently, it can be used for assessing patient safety in clinical settings such as medical oncology units and for research projects
Psychometric properties of the king spiritual intelligence questionnaire (KSIQ) in physical veterans of Iran-Iraq warfare
Aims: The study's purpose was to determine reliability and validity of the King spiritual intelligence questionnaires in veterans of Iran-Iraq Warfare. Methods: In this cross sectional study, 300 veterans of the Iran-Iraq war completed the King spiritual intelligence questionnaires. Principal components analysis (PCA) with varimax rotation was used to assess domain structure of the King spiritual intelligence questionnaires. Internal and external consistency reliability was assessed with Cronbach's alpha and intra-class correlation coefficient (ICC). Results: Internal consistency of King spiritual intelligence questions estimated with Cronbach's alpha, 0.872 and intra-class correlation coefficient (ICC).872 (CI 95%: 0.84 -0.89). The construct validity of the questionnaire was calculated using exploratory factor analysis that showed 3 factors with Eigen values of greater than one, which explained in total 44.7% of the variance. (1, 8 items, α= 0.87; 2, 5. items; α = 0.89; 3, 2 items, α= 0.51). Conclusion: The Persian version of King spiritual intelligence questionnaire demonstrated suitable validity and reliability among the Veterans of Iran-Iraq Warfare. With the consideration of the proper psychometric characteristics, this questionnaire can be used to further research spiritual intelligence in this population
Study of chemical and physical behavior cotton fabrics treated by corona discharge after several laundering
Cotton fabric because of finishing process has shrinkage behavior after laundering and for improving this problem, chemical agents utilize for anti-shrinkage. This temporary finishing can reduce shrinkagebut has many environmental problems. Corona discharge treatment has been used for cotton fabric, other fibers and polymers. This treatment can reduce costs and environmental impacts. In this study, cotton fabric was treated by corona discharge instrument at 2 - 40 passages and fabrics were washed with laundering method. After four times laundering, shrinkage behavior of corona discharge treated fabric as compared with un-treated fabric decrease. After 10 passages of corona discharge treatment,water, dye absorption and shrinkage are modified but after 14 passages, despite of shrinkage improvement, dyeing properties decrease
Solving an Optimal Control Problem of Cancer Treatment by Artificial Neural Networks
Cancer is an uncontrollable growth of abnormal cells in any tissue of the body. Many researchers have focused on machine learning and artificial intelligence (AI) based on approaches for cancer treatment. Dissimilar to traditional methods, these approaches are efficient and are able to find the optimal solutions of cancer chemotherapy problems. In this paper, a system of ordinary differential equations (ODEs) with the state variables of immune cells, tumor cells, healthy cells and drug concentration is proposed to anticipate the tumor growth and to show their interactions in the body. Then, an artificial neural network (ANN) is applied to solve the ODEs system through minimizing the error function and modifying the parameters consisting of weights and biases. The mean square errors (MSEs) between the analytical and ANN results corresponding to four state variables are 1.54e-06, 6.43e-07, 6.61e-06, and 3.99e-07, respectively. These results show the good performance and efficiency of the proposed method. Moreover, the optimal dose of chemotherapy drug and the amount of drug needed to continue the treatment process are achieved
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