¿Cómo afecta la inteligencia emocional de los profesores de la Universidad de Teherán a su autoconfianza?

Some studies have indicated the relationship between Emotional Intelligence (EI) and self-efficacy beliefs at schools or language institutes. This study, sought to investigate this association among university teachers. 105 university teachers participated in the present study. The participants were required to complete the “Teachers’ Sense of Efficacy Scale” and the “Emotional Intelligence Questionnaire”. Correlation and regression analysis were conducted on the data. The results of data analysis revealed that there was a strong positive relationship between EI and self-efficacy beliefs. Furthermore, it was found that among the fifteen components of EI, three subscales of Flexibility, Optimism and Interpersonal Relationship were positive predictors of Efficacy beliefs.Algunos estudios dan pruebas de la existencia de una relación entre la inteligencia emocional (EI, siglas en inglés) y la auto-confianza en las escuelas o institutos de lenguas. Este estudio tiene como objetivo, estudiar esta relación entre los profesores universitarios. Por ello se ha solicitado la participación de 105 profesores y se les pidió que respondan a las preguntas respecto a “El sentido de los profesores sobre la gradación de eficacia” así como “el cuestionario de la inteligencia emocional”. En los datos obtenidos se analizó tanto la correlación como la regresión. El resultado del análisis de los datos muestra que existe una relación positiva muy destacada entre EI y el auto-confianza. Además, se observó que tres factores subescalas de los quince componentes, es decir: la flexibilidad, el optimismo y la relación interpersonal eran considerados como los predicadores positivos de la eficacia

The status quo of teacher-training courses in the Iranian EFL context: a focus on models of professional education and dynamic assessment

Given that Teacher-Training Courses (TTC’s) have responsibility for assisting prospective teachers with building up a repertoire of technical & pedagogic knowledge, the systematically evaluation of such courses is regarded as seminal (Lynch, 2003 and Peacock, 2009). Therefore, the present study is an attempt to (a) probe into the way professional expertise is acquired by preservice Iranian EFL teachers, (b) analyze the instructional content of TTC’s currently held in Iran, with a focus on teachings on Dynamic Assessment (DA), and (c) examine preservice teachers’ and TTC trainers’ opinions about the TTC’s. To this end, 9 purposefully selected TTC’s were observed, employing participant observation, and content analyses were carried out on their syllabi. Also, 107 TTC participants filled out a questionnaire, and 14 TTC instructors were interviewed; the sampling of the TTC participants and instructors was nonprobability convenient. Results of descriptive statistics showed that accounting for 84.73% of all the instructional attempts, the craft model was the most frequently prevalent model of teacher learning. Content analyses and preservice teacher questionnaire results signified that writing skill was marginalized in all the courses, and none of them included instructions on DA in their syllabi. Open, selective, and axial coding as well as content analyses of the collected data gave rise to eight themes delineating major areas fueling the current research-practice divide in the TTC syllabi. Findings of the study provide an opportunity to examine the status quo, strengths, and weaknesses of the TTC’s. The eight identified impediments to the employment of research in pedagogy could help reach a framework for factors that might induce TTC organizers to disregard the implication of relevant research findings for the courses they run

Intelligent sequence stratigraphy through a wavelet-based decomposition of well log data

Identification of sequence boundaries is an important task in geological characterization of gas reservoirs. In this study, a continuous wavelet transform (CWT) approach is applied to decompose gamma ray and porosity logs into a set of wavelet coefficients at varying scales. A discrete wavelet transform (DWT) is utilized to decompose well logs into smaller frequency bandwidths called Approximations (A) and Details (D). The methodology is illustrated by using a case study from the Ilam and upper Sarvak formations in the Dezful embayment, southwestern Iran. Different graphical visualization techniques of the continuous wavelet transform results allowed a better understanding of the main sequence boundaries. Using the DWT, maximum flooding surface was successfully recognised from both highest frequency and low frequency contents of signals. There is a sharp peak in all A&D corresponding to the maximum flooding surface (MFS), which can specifically be seen in fifth Approximation (a5), fifth Detail (d5), fourth Detail (d4) and third Detail (d3) coefficients. Sequence boundaries were best recognised from the low frequency contents of signals, especially the fifth Approximation (a5). Normally, the troughs of the fifth Approximation correspond to sequence boundaries where higher porosities developed in the Ilam and upper Sarvak carbonate rocks. Through hybridizing both CWT and DWT coefficient a more effective discrimination of sequence boundaries was achieved. The results of this study show that wavelet transform is a successful, fast and easy approach for identification of the main sequence boundaries from well log data. There is a good agreement between core derived system tracts and those derived from decomposition of well logs by using the wavelet transform approach

Estimation of vitrinite reflectance from well log data

Vitrinite reflectance (VR) data provide important information for thermal maturity assessment and source rock evaluation. The current study introduces a practical method for vitrinite reflectance determination from sonic and resistivity logs. The main determinant factor of the method is ΔRRS which is defined as the separation between cumulative frequency values of resistivity ratio (RR) and sonic log data. The values of ΔRRS range from −1 at ground level to +1 at bottom hole. The crossing point depth of the DT and RR cumulative frequency curves, where ΔRRS=0, indicates the onset of oil generation window. From the surface (ground level) to the crossing point depth ΔRRS takes negative values indicating organic material diagenesis window. Below the crossing point depth ΔRRS turns into positive values showing thermally-mature organic matter within the catagenesis window. Vitrinite reflectance measurements revealed strong exponential relationships with the calculated ΔRRS data. Accordingly, a new calibration chart was proposed for VR estimation based on ΔRRS data. Finally, an equation is derived for vitrinite reflectance estimation from ΔRRS and geothermal gradient. The proposed equation works well in the event of having limited VR calibration data

Tight gas sands permeability estimation from mercury injection capillary pressure and nuclear magnetic resonance data

There are several methods to estimate permeability from pore throat sizes and NMR T2 relaxation time. Although most of the methods are well-established and work well for conventional reservoirs they fail to estimate permeability for tight gas sands. The aim of this study was to establish relationships between permeability and pore throat sizes, derived from mercury injection analysis, and NMR T2 relaxation time. Regression analysis was used to achieve a set of relationships between dry gas permeability, porosity and pore throat sizes for 50 tight gas sand samples. Unlike for normal sandstone, pore throat radii corresponding to a mercury saturation of 10% (r10) is the best permeability predictor for tight gas sands. For tight gas sands, NMR T2 relaxation spectra fall on the shorter values corresponding to the smaller pores. This is because pore spaces are significantly reduced both in size and volume due to extensive compaction and cementation. This study shows that using NMR T2peak and multi-regression analysis, permeability can be estimated with high accuracy even in rocks with substantially constricted pore throats

Single Intense Microsecond Electric Pulse Induces Radiosensitization to Ionizing Radiation: Effects of Time Intervals Between Electric Pulse and Ionizing Irradiation

Background and Objective: Recent studies have shown the potential of electroporation (EP) as a physical radiosensitizer for ionizing radiation (IR). The amount of sensitizing effect depends on some factors the most important of them is the time interval between the EP and IR. This experimental in vitro study aims to investigate the radiosensitizing effect of EP exposure prior to IR and also evaluate the effects of EP-IR time intervals on the amount of radiosensitizing effects.Methods: Chinese hamster ovary (CHO) cell lines were cultured in vitro. The cells were divided into 10 groups including one untreated or control group, IR, and EP treatment alone groups, and seven combined EP-IR groups with 10, 20, 30, 40, 50, 60, and 70 min intervals. The dose enhancement factors (DEFs) for 6 MV X-rays IR were comparatively investigated between the groups using MTT assay.Results: The EP significantly induced radiosensitizing effect and its amount depends on the time intervals. The viability rate of the cells in the combined EP-IR treatment groups for intervals of 10, 20, 30, 40, and 50 min was significantly lower than the IR alone group. The highest DEF (1.18) was observed 10 min time interval between EP and IR.Conclusion: The radiosensitizing effects of EP persist long enough, 10–50 min, which allows safe application of EP as a radiosensitizer before IR in clinical setting

Relay X Channels without Channel State Information at the Transmit Sides: Degrees of Freedom

This paper focuses on the two-user relay-assisted X channel with no channel state information (CSI) available at the transmitter side. Two relaying modes, namely half-duplex decode-and-forward (DF) and cognitive relays, are considered and the degrees of freedom (DoF) are characterized. It is shown that assisted by a half-duplex DF relay that is equipped with 2M antennas, the X channel with two M-antenna users has 4M/3 DoF, which is achievable through interference alignment (IA). Furthermore, it is shown that in this channel, an M-antenna cognitive relay (with non-causal access to information streams) provides 2M DoF using interference cancellation (IC) technique. In this setting, IC outperforms interference alignment in the cognitive relay mode, since the latter achieves 4M/3 DoF

Homeopathy in Dentistry and Oral Medicine: A review

Objectives: Homeopathy is the most important field of alternative medicine. At present, over 3000 organic medications have been registered in the homeopathy pharmacopeia; out of which, 70% have herbal, 20% have mineral and the remaining have animal origins. Evidence shows that homeopathy may be beneficial in dentistry and oral medicine. However, this is a less known field for dentists. Therefore, this study aimed to do a review on the most common homeopathy medicines used for oral and dental problfems and to present it in a simple and practical way for general dental practitioners.Review of Literature: Google Scholar and PubMed data bases were searched for any article related to both homeopathy and dentistry. Several recent meta-analyses, randomized control trials, animal and laboratory trials, and other interventional papers were studied.Homeopathy drugs are basically produced from natural origin; they have less side effects in comparison with chemical drugs. In this method, only small doses of medications with low cost are used. The positive effects of homeopathy drugs on several oral conditions have been emphasized.Conclusion: Homeopathy may be a suitable adjunct to conventional medicine for management of many conditions since it is affordable, effective and uplifting for patients

Hadoop-Oriented SVM-LRU (H-SVM-LRU): An Intelligent Cache Replacement Algorithm to Improve MapReduce Performance

Modern applications can generate a large amount of data from different sources with high velocity, a combination that is difficult to store and process via traditional tools. Hadoop is one framework that is used for the parallel processing of a large amount of data in a distributed environment, however, various challenges can lead to poor performance. Two particular issues that can limit performance are the high access time for I/O operations and the recomputation of intermediate data. The combination of these two issues can result in resource wastage. In recent years, there have been attempts to overcome these problems by using caching mechanisms. Due to cache space limitations, it is crucial to use this space efficiently and avoid cache pollution (the cache contains data that is not used in the future). We propose Hadoop-oriented SVM-LRU (HSVM- LRU) to improve Hadoop performance. For this purpose, we use an intelligent cache replacement algorithm, SVM-LRU, that combines the well-known LRU mechanism with a machine learning algorithm, SVM, to classify cached data into two groups based on their future usage. Experimental results show a significant decrease in execution time as a result of an increased cache hit ratio, leading to a positive impact on Hadoop performance