h. parsaei

The discussion of moral values ​​has always been considered one of the most important and widespread issues in the human realm, which manifests its influence in various ways in the context of artistic and literary works and in the form of educational teachings. Poetry, as a platform for communication between the creator of the work and the audience, can be an effective source for the sustainability and growth of values ​​and instructive moral principles so that readers, by choosing it, can reach new capacities in understanding moral values. In the present study, by studying the mythological poems of the poet Malek-osh-Sho'ara Bahar, the ethical principles and values ​​that govern his poems have been reflected in order to answer the question of what ethical values ​​and principles Bahar used in his mythological poems?

It seems that the lack of teachings such as freedom, justice, and humanity are effective factors in the poet's expression of regret as a person from a constitutional society. The poet uses various ethical elements such as the effectiveness of mythological heroes and heroes and the justice in their era in order to achieve success in showing the authenticity of Iran and Iranians in the past, so that he can point out the ethical values ​​that can be expected in the present society. Truth and falsehood, goodness and badness, or the opposition of good and evil as values ​​and counter-values ​​are also reflected in his poetry by referring to mythologies such as the divine, Ahura Mazda, and, on the contrary, devil.

Divan Shams is a reflection of the opinions and thoughts of this mystic, many of its words have a positive meaning in both axes of companionship and substitution, and like a chain, it serves the thoughts of its creator, as one of the famous western psychologists, Martin Seligman He has turned himself from the symptoms of learned helplessness to the penetrating effects of positive emotions. The purpose of this essay is to analyze and analyze Ghazals and investigate the positive lexical chains of Rumi in Divan Shams according to Martin Seligman's theory of positivist psychology.

The current research is a basic research using the methods of rational reasoning and analysis and based on library studies, and it deals with the category of analysis of chains of positive words based on the positivist components of Martin Seligman and its effect on Diwan Shams of Tabrizi. The statistical community is also the statistical community of 3000 verses from the ten-volume book "Koliat Shams" by Maulana Jalaluddin Mohammad Molavi, based on the original edition of Faruzanfar with his corrections and margins.

All the components of Martin Seligman's positivist psychology have been observed in Koliat Shams. The percentage of Seligman's positive virtues in Diwan Shams is as follows: excellence has taken the first rank of virtues with 42.43%. Wisdom is in the second place with 20.61%. Shujaat ranks third with 17.28%. Altruism with 14.10%, moderation with 4.62% and seeking justice with 0.96% have taken the next ranks. The abilities of love with 74.54%, leadership with 65.38% and perfection with 53.96% are the highest, and the abilities of humor with 0.78%, seeking justice with 0.96% and stability with 7.92% are the lowest.

The use of such positive concepts and words in Diwan Shams, in addition to bringing the audience to the city of Rumi's love, is effective in creating psychological transformation and changing attitudes and improving the quality of life of the audience. The adaptation of Rumi's positive linguistic and intellectual elements in Divan Shams with the opinions of Martin Seligman; Today's psychologist and psychotherapist, these two spiritual and human capitals, with a gap of eight centuries, are the main result and product of this research. Seligman's thoughts and components as the subject and the brain-made world of Rumi in Divan Shams, as the example and the compass hand of the sublime human life, have created a wonderful and irreplaceable alliance that is reliable and fruitful from the two scientific and artistic points of view of literature and psychology.

The COVID-19 pandemic has affected people globally; nowadays several countries are facing a major change in daily life due to universal quarantining, closed schools, social isolation, and shelter-in-place orders. In addition, this pandemic caused an economic crisis. International Labour Organization (ILO) reported that not only COVID-19 is a serious threat to public health but also the economic and social disruption of this crisis threatens the long-term livelihoods and wellbeing of millions of people. In this short paper, we introduce our hypothesis on using artificial intelligence (AI) technology to predict which employees are most vulnerable to the infections caused by the novel coronavirus (SARS-CoV-2). Such a system can be used in a wide variety of work places such as libraries, banks, drugstores, and hotel receptions to reduce the risk of severe infections in employees as well as to ensure the safety of labor force and the sustainability of businesses and jobs.

Electromyographic (EMG) signals obtained from a contracted muscle contain valuable information on its activity and health status. Much of this information lies in motor unit potentials (MUPs) of its motor units (MUs), collected during the muscle contraction. Hence, accurate estimation of a MUP template for each MU is crucial.

To investigate the possibility of improving MUP template estimation using the wavelet denoising technique.

In this analytical study, several MUP template estimators were developed by combining conventional estimation methods and wavelet denoising techniques. A MUP template was initially estimated using conventional methods such as mean, median, median-trimmed mean, or mode. Thereafter, it was post-processed using the wavelet denoising technique.

Evaluation results of the studied estimators using 40 simulated EMG signals with a true template for each constituent MUP train showed that augmented wavelet- based template estimation methods are more reliable than conventional methods. However, on average, wavelet denoising was not much effective. Around 40 MUPs of a MU is sufficient to estimate its MUP template.

Although wavelet techniques are effective in EMG signal analysis, here wavelet denoising did not practically improve MUP template estimation. Considering computational simplicity and estimation error, the two methods median and median-trimmed mean are practical estimators that can provide a good estimation of a MUP template for a MU when approximately 40 MUPs are available. Nevertheless, the baseline noise level in the MUP templates estimated using the median-trimmed mean method is slightly lower than that in the templates estimated using the median method.

Scoliosis is the most common type of spinal deformity. A universal and standard method for evaluating scoliosis is Cobb angle measurement, but several studies have shown that there is intra- and inter- observer variation in measuring cobb angle manually. Develop a computer- assisted system to decrease operator-dependent errors in Cobb angle measurement. The spinal cord in the given x-ray image of the spine is highlighted using contract-stretching technique. The overall structural curvature of the spine is determined by a semi-automatic algorithm aided by the operator. Once the morphologic curve of the spine is determined, in the last step the cobb-angle is estimated by calculating the angle between two normal lines to the spinal curve at the inflection points of the curve. Evaluation results of the developed algorithms using 14 radiographs of patients ( 4 - 40 years old) with cobb angle ranges from 34 - 82 degrees, revealed that the developed algorithm accurately estimated cobb angle. Statistical analysis showed that average angle values estimated using the developed method and that provided by experts are statistically equal. The correlation coefficient between the angle values estimated using the developed algorithm and those provided by the expert is 0.81. Compared with previous algorithms, the developed system is easy to use, less operator-dependent, accurate, and reliable. The obtained results are promising and show that the developed computer-based system could be used to quantify scoliosis by measuring Cobb angle.

Electromyography (EMG) signal processing and Muscle Onset Latency (MOL) are widely used in rehabilitation sciences and nerve conduction studies. The majority of existing software packages provided for estimating MOL via analyzing EMG signal are computerized, desktop based and not portable; therefore, experiments and signal analyzes using them should be completed locally. Moreover, a desktop or laptop is required to complete experiments using these packages, which costs. Develop a non-expensive and portable Android application (app) for estimating MOL via analyzing surface EMG. A multi-layer architecture model was designed for implementing the MOL estimation app. Several Android-based algorithms for analyzing a recorded EMG signal and estimating MOL was implemented. A graphical user interface (GUI) that simplifies analyzing a given EMG signal using the presented app was developed too. Evaluation results of the developed app using 10 EMG signals showed promising performance; the MOL values estimated using the presented app are statistically equal to those estimated using a commercial Windows-based surface EMG analysis software (MegaWin 3.0). For the majority of cases relative error <10%. MOL values estimated by these two systems are linearly related, the correlation coefficient value ~ 0.93. These evaluations revealed that the presented app performed as well as MegaWin 3.0 software in estimating MOL. Recent advances in smart portable devices such as mobile phones have shown the great capability of facilitating and decreasing the cost of analyzing biomedical signals, particularly in academic environments. Here, we developed an Android app for estimating MOL via analyzing the surface EMG signal. Performance is promising to use the app for teaching or research purposes.