El Trastorno por Déficit de Atención (TDA) afecta aproximadamente del 3 al 5% de la población escolar mundial. Se caracteriza por causar problemas relativos con la atención, impulsividad e hiperactividad, ocasionando un mayor riesgo de que el estudiante tenga un pobre rendimiento académico. Por lo que es necesario utilizar estrategias adecuadas para que estos alumnos adquieran aprendizajes significativos y que pueden ser evaluados con instrumentos específicamente diseñados para ello. El objetivo de esta investigación es identificar qué estrategias son aplicables para alumnos con TDA y favorecer la adquisición de aprendizaje significativo. Este trabajo se fundamentó en una muestra de 30 profesores y 90 alumnos de nivel secundaria. Se eligieron las estrategias de activación de conocimientos previos, orientación de la información relevante, codificación de la información y organización de la información nueva que se consideraron adecuadas para alumnos con el padecimiento y se evaluó la funcionalidad de las mismas. Dadas las características de este tipo de alumnos, las estrategias propuestas resultaron ser adecuadas para lograr aprendizajes.

Background: Osteoporosis is a widespread metabolic bone disease that leads to an increased frequency of fractures. It is a global public health problem currently affecting millions of people, worldwide and Saudi Arabia is not an exception.Awareness and perceptions of susceptibility and belief in the seriousness of a disease can help in its prevention and control. Aim: We aimed to assess knowledge, attitude and practices for osteoporosis among Saudi general population and to identify its determining factors. Design and Setting: the survey was a cross-sectional survey of people aged ≥ 18 years, representing every region in the KSA. Method: We used self-administered questionnaire to identify the levels of KAP. Means, standard deviations and percentages along with the 95% CI were calculated. Univariate significance test have been used for the analysis. Results and Conclusion: Responses were obtained from 1830 person (42% female, 58% male). The majority of the sample heard about osteoporosis (78%). There were significant associations between level of awareness and socio-demographics of the participants. Regular practice of the main preventive behaviors was correlated with an increase in the level of awareness. The study proposed that better involvement of health authorities and physicians in patient education efforts in order to improve knowledge as well as maintain the quality and reliability of information provided regarding osteoporosis, especially for the regions with lower levels of awareness.

Three reliable, rapid and selective methods have been developed and validated for the determination of mebeverine hydrochloride and chlordiazepoxide in pharmaceutical dosage forms. The first method is first order derivative spectrophotometric method All variables affecting the reaction have been investigated and the conditions were optimized. The second method is based on separation of the cited drugs (mebeverine hydrochloride Rf =0.72 ± 0.02 and chlordiazepoxide Rf = 0.43 ± 0.04) followed by densitometric measurement of the intact drug spots at 220 nm by HPTLC. The separation was carried on silica gel plates using chloroform: methanol: ammonia (9.5: 0.5: 0.1, (v/v/v) as a mobile phase. The linearity range was 200-1200 ng/spot for mebeverine hydrochloride and 100-600 for chlordiazepoxide. The third method is accurate and sensitive HPLC method based on separation of mebeverine hydrochloride and chlordiazepoxide on a reversed phase C18 column, using a mobile phase of potassium dihydrogen phosphate buffer (0.05 M, pH 4.0 adjusted with 0.5% orthophosphoric acid)-methanol- water (30:50:20, v/v/v) and UV detection at 260 nm in an overall analysis time of about 5 min., based on peak area. The accuracy and precision of the methods were confirmed when the standard addition technique was applied. The validation was performed according to ICH guidelines. The results obtained by applying the proposed methods were statistically analyzed.

Nowadays the companies which make a business in area of development of surface technology commonly present results in which pretend that new developed products, has the highest achievement, with higher parameters and lower costs than competition. In this time many research and development companies are focus on special surface technologies which are based on creation of layers and coatings. Very useful technology seems to be plasma nitriding. This technology allows creating diffusion layers which are suitable as a substrate for coating deposition [1,2]. One of the effective methods how to reach better parameters of real surface is sandblasting. Sandblasting is a generic term for the process of smoothing, shaping and cleaning a hard surface by forcing solid particles across that surface at high speeds; the effect is similar to that of using sandpaper, but provides a more even finish with no problems at corners or crannies. Sandblasting is one of the most effective methods to modify a metal surface and improve its properties for application. Sandblasting is an integral part of a complex process of coatings. The paper deals with comparison of coating surface texture with coating surface texture after µLap polishing. The paper describes changes of the surface textures of the HS6-5-2-5 steel CSN EN ISO 4957 with coating nACo®. Coating nACo® was applied by PVD method and surface of the coating samples was subsequently polished by µLap appliance. Surface textures together with properties of the coating are decisive factors for their lifetime and durability of the cutting tools. The qualitative assessment of the changes surface texture was carried out by the 3D topography measurement of the surface by using Talysurf CCI Lite. TalyMap software was used to evaluation of the changes surface texture. For evaluation of the surface were used parameters: Sa - arithmetic mean deviation of the surface [μm], Sdq - root mean square slope of the surface.The results in this paper are showing positive influence of the polishing on the surface texture of the coating samples.

In current article, the role of emotional intelligence on transformational leadership was surveyed. Emotional intelligence has 5 dimensions include: self-awareness, self-regulation, motivating oneself, empathy and social skills which considered as 5 secondary hypotheses. First of all by applying Pearson and Regression test, correlationship and the influence of emotional intelligence on transformational leadership was surveyed which results show that there are positive and meaningful correlationship between emotional intelligence and its indices with transformational leadership. Going on, by using Average test, the levels of each variable was tested that just transformational leadership wasn\'t placed in a suitable situation. Also the results of using AHP technique, show empathy is the most important dimension of emotional intelligence and after that, social skills, self regulation, motivating oneself and self awareness were placed in other places in direct order. Finally the correlations between demographic characteristics with emotional intelligence and transformational leadership was studied that there were no relationship between them.

The Backpropagation algorithm is a well-known al-\ngorithm used to train the multilayer neural net-\nworks. In the same time, it suffers from some differ-\nent difficulties; such as the slow convergence and\nconvergence to local minima. So many improve-\nments and modification have been reported to beat\nthose limitations. The Extended Optical Backpropa-\ngation is one of the modifications that had been\ndone on the Backpropagation algorithm to enhance\nits performance.\nIn this paper, the Extended Optical Backpropagation\nalgorithm will be used to adapt the learning rate us-\ning Bold Driver algorithm. The determined learning\nrate is different for each epoch and depends on the\nweights and gradient values of the previous one.\nThe experimental results showed that using the Ex-\ntended Optical Backpropagation algorithm with\nadaptive learning rate reduced the number of itera-\ntions needed to train the network and thus enhanced\nits performance.

As a representation of dynamism of human thought, organizations try to use IT tools to improve their performance and survive in competitive arena. Variable tastes of the customers have created markets in which prompt response to consumers\' needs is an accepted principle. The success condition is such an environment is to possess complete, due and accurate information to be a base for the organization\'s decision-making and response to market demands. Using modern IT systems is considered as the pre-condition of gaining and processing the information. One of the most important tools of information and communication technologies that play a vital role in integration of information and operation of the institutes and can makes the grounds for any organization to join global markets is to use Enterprise Resource Planning systems (ERP). ERP is currently considered as one of the newest management and planning tools. Using and implementing the process of ERP systems is a technical-social challenge that affects the strategic and operational levels of any company and whose implementation will not necessarily lead to expected outputs. Thus it is necessary to evaluate the key influencing factors on the readiness of the organization in successful implementation of ERP. Unfortunately, there has not been enough attention to localizing the factors of the readiness of Iranian organizations in implementing ERP. The main objective of this research is to identify and evaluate the key effective factors on implementing ERP strategy in ApadanaCeram Company that is an important manufacturer in tile and ceramic industry. Studying the literature review and related studies and researches led us to identify 36 factors. These factors were classified in 4 groups: organizational factors, process factors, technology-related factors, and human resource-related factors. Then the most important factors were identified regarding the special conditions of tile and ceramic industry in general and Apadana Ceram Company in particular. Beside to the main objective of the research, we followed some subsidiary objectives to be used as a guide to successful implementation of the project in similar companies. This research is a practical-descriptive one. The theoretical data were collected in library method, and the needed data were collected from a questionnaire that was presented to 52 employees of ERP project in Apadana Ceram. Totally 46 employees completed the questionnaire.

One of the solutions for securing the systems and computer networks is the set of intrusion detecting systems. These systems that are analogous to burglar alarms detect the suspicious events and intrusions in their supervising environment and alarm against such suspicious events. The objective of the security solutions such as encoding, shield, ID detection systems, etc. are to secure the systems and preventing any intrusion event. Since the complete security is an expensive process and it cannot be provided in practice, we will need a system for reporting the event and even find its roots and reasons instead of preventing such events. Intrusion detecting systems are designed and used for this reason. In this research we present a new method for designing the abnormality detection using neural networks. In this method, training the neural network of system is being done in a two-step and sequential form. We have tested this new model on five different neural systems and we have compared its efficiency with the models in which the training process is single-step. The five types of our used neural networks include PCA -based Neural Network, SOFM -based Neural Network, MLP neural network, GFF Neural Network, and Jordan- Elman Neural Network. Our tests and evaluations have been done using KDD CUP 99 database and we have used all network records for training and testing the network. The Results show that our offered model leads to a significant improvement in its detection scale and positive error scale in comparison with the simple system, so that our system has the same efficiency in comparison with its similar systems and even in some cases its efficiency is better than the similar systems.