"Shami" A Public Life Narrator

The public life of people in most cases are among forgotten parts of the Persian literature; in other words, most of the poets because of their too much attention to the kings and their actions and behaviors, followed by their disconnection with the inferior class of the society, have rarely composed poems on the public life of the people. The constitutional revolution to a great extent shifted this balance in favor of the public. In this paper, the anthology of the Kurdish blind poet “Shami” - which deals with the poor class of the society and the issues relating to it from a linguistic and thematic perspective - has been investigated and on the basis of the issues that embody most in the anthology, the poems relating to the public life have been categorized into four groups: 1. Life appliances and equipment, 2.Number of people, 3. Speech and 4. Customs and etiquette. This investigation showed that Shami is a poet that understands the pains and woes of the people and tries through an eloquent language to express pains and sufferings of his own class in a poetic form, offering it to the public. Hence, he can be called a social poet as suc

Application of Wavelet Decomposition and Phase Space Reconstruction in Urban Water Consumption Forecasting: Chaotic Approach (Case Study)

The forecasting of future value of water consumption in an urban area is highly complex and nonlinear. It often exhibits a high degree of spatial and temporal variability. It is a crucial factor for long-term sustainable management and improvement of the operation of urban water allocation system. This chapter will study the application of two pre-processing phase space reconstruction (PSR) and wavelet decomposition transform (WDT) methods to investigate the behavior of time series to forecast short-term water demand value of Kelowna City (BC, Canada). The research proposes two pre-process technique to improve the accuracy of the models. Artificial neural networks (ANNs), gene expression programming (GEP) and multilinear regression (MLR) methods are the tools that considered for forecasting the demand values. Evaluation of the tools is based on two steps with and without applying the pre-processing methods. Moreover, autocorrelation function (ACF) is used to calculate the lag time. Correlation dimension is used to study the chaotic behavior of the dataset. The models’ relative performance is compared using three different fitness indexes; coefficient of determination (CD), root mean square error (RMSE) and mean absolute error (MAE). The results showed how pre-processing combination of WDT and PSR improved the performance of the models in forecasting short-term demand values

Intelligent Energy Management with IoT Framework in Smart Cities Using Intelligent Analysis: An Application of Machine Learning Methods for Complex Networks and Systems

Smart buildings are increasingly using Internet of Things (IoT)-based wireless sensing systems to reduce their energy consumption and environmental impact. As a result of their compact size and ability to sense, measure, and compute all electrical properties, Internet of Things devices have become increasingly important in our society. A major contribution of this study is the development of a comprehensive IoT-based framework for smart city energy management, incorporating multiple components of IoT architecture and framework. An IoT framework for intelligent energy management applications that employ intelligent analysis is an essential system component that collects and stores information. Additionally, it serves as a platform for the development of applications by other companies. Furthermore, we have studied intelligent energy management solutions based on intelligent mechanisms. The depletion of energy resources and the increase in energy demand have led to an increase in energy consumption and building maintenance. The data collected is used to monitor, control, and enhance the efficiency of the system

An adversarial approach for intrusion detection systems using Jacobian Saliency Map Attacks (JSMA) Algorithm

In today’s digital world, the information systems are revolutionizing the way we connect. As the people are trying to adopt and integrate intelligent systems into daily lives, the risks around cyberattacks on user-specific information have significantly grown. To ensure safe communication, the Intrusion Detection Systems (IDS) were developed often by using machine learning (ML) algorithms that have the unique ability to detect malware against network security violations. Recently, it was reported that the IDS are prone to carefully crafted perturbations known as adversaries. With the aim to understand the impact of such attacks, in this paper, we have proposed a novel random neural network-based adversarial intrusion detection system (RNN-ADV). The NSL-KDD dataset is utilized for training. For adversarial attack crafting, the Jacobian Saliency Map Attack (JSMA) algorithm is used, which identifies the feature which can cause maximum change to the benign samples with minimum added perturbation. To check the effectiveness of the proposed adversarial scheme, the results are compared with a deep neural network which indicates that RNN-ADV performs better in terms of accuracy, precision, recall, F1 score and training epochs

Effect of Instructing Care Program Through Group Discussion on the Quality of Life of the Parents of the Children Afflicted With Leukemia

Purpose: Children long-term involvement with cancer may have a negative impact on the quality of life their parents. Design and implementation of training programs for parents whose children have been diagnosed with leukemia, as the primary caregivers of children, will have a special significance and can contribute to better taking care of such children. The main purpose of the present study was to examine the impact of conducting group discussion, as care program training, on the quality of life parents whose children were suffering from leukemia. Methods: This quasi-experimental before-after intervention study encompassed two groups of parents (in total 41) of leukemia children. To collect data, a demographic questionnaire and the shortened version of SF-36 questionnaire were used to determine the quality of life of parents. Both groups completed the quality of life questionnaires before and two months after the intervention. Results: Comparison of the parents’ quality of life mean scores, obtained before and two months after training, showed that promotion in 6 domains of bodily pain, general health, emotional health, role limitation due to emotional problems, social functioning, and vitality were occurred. (P <0.05) Conclusions: Considering the important role of parents in taking care of children suffering from leukemia, introduction of care program training can be a positive step to help these parents and empower them to manage their children’s problems more systematically and will ultimately lead to improved quality of life of parents

Designing and construction a DNA vaccine encoding the fusion fragment of cfp10 and Ag85A immunodominant genes of Mycobacterium tuberculosis

Background: Pathogenic mycobacteria are one of major causes of human morbidity and mortality. Mycobacterium tuberculosis (M. tuberculosis) is an etiological agent of human tuberculosis. Designing new vaccines including DNA vaccines may be considered as new approaches for preventing of TB.Materials and Methods: M. tuberculosis H37Rv was grown on Lowenstein Jensen medium for 4 weeks at 37ºC and then DNA was extracted. The cfp10 gene was amplified by PCR. After digesting the PCR product and the plasmid, cfp10 fragment was ligated into the vector using T4 DNA ligase. Then, Ag85A was subcloned into pcDNA/cfp10. Escherichia coli strain JM109 bacteria were transformed by the desired construct. Clone confirmations were performed by colony PCR, restriction enzyme digestion and DNA sequencing. Recombinant vector was transfected into HeLa cells and total RNA was extracted, then cDNA was synthesized using oligo-dT. Finally PCR was performed by cfp10 primers.Results: The cfp10 was amplified by PCR method and the PCR products were visualized by agarose gel electrophoresis. The cfp10 fragments showed 303 bp in length. The cfp10 cloned into pcDNA. Then, Ag85Awas ligated into pcDNA/cfp10 after digestion correctly. Colony-PCR and restriction enzyme digestion and sequencing confirmed the cloning the fusion Ag85A/cfp10 fragment. Finally, after cDNA synthesis, expression of vector was confirmed in eukaryotic system.Conclusion: Cloning of Ag85A/cfp10 genes of M. tuberculosis were performed correctly. It can use as a DNA vaccine for investigation the immune responses in animal models in future studies

Selecting the best supply chain by goal programming and network data envelopment analysis

Today, one of the most important problems of decision makers in most organizations is to choose the best supply chain. The main objective of this paper is to choose the best supply chain. To select the best supply chain this paper presents a model based on goal programming and network data envelopment analysis (NDEA). The proposed model enables decision makers to compare supply chains with predetermined goals. A case study is presented to validate the proposed model

Effects of genistein and swimming exercise on spatial memory and expression of microRNA 132, BDNF, and IGF-1 genes in the hippocampus of ovariectomized rats

Objective(s): The aim of the present study was to investigate the effects of genistein and exercise on the spatial memory and expression of microRNA-132, BDNF, and IGF-1 in the hippocampus of ovariectomized rats. Materials and Methods: Sixty animals were divided into six groups of control, sham, ovariectomy (OVX), ovariectomized with 8 weeks of genistein administration (OVX.G), with 8 weeks of swimming training (OVX.E), and with 8 weeks of both of them (OVX.G.E). The effect of genistein and/or exercise was evaluated by measuring microRNA-132, BDNF, and IGF-1 expression levels in the hippocampus tissue. Grafts were analyzed using Real-time polymerase chain reaction for microRNA-132, BDNF, IGF-1, and spatial memory via a Morris water maze (MWM).  Results: Our findings showed that ovariectomy decreased the expression of microRNA-132, BDNF, and IGF-1 in the hippocampus (

Mass transfer in medium density fiberboard (MDF) modified by NA+ montmorillonite (NA+MMT) nanoclay

The potential use of nanoclay was examined to modify fluid transfer properties of medium density fiberboard (MDF). For this, Na+ montmorillonite (Na+MMT) nanoclay was added to urea formaldehyde resin to produce MDF. Then, the air permeability and mass diffusivity of MDF were evaluated. Scanning electron microscope (SEM) images and X-ray diffraction (XRD) confirmed a dispersion and exfoliation of Na+MMT in the modified MDF. The air permeability presented a systematic decrease with increasing nanoclay amount. This reduction agreed with the simple "tortuous path" model. The nanoclay had no effect on the mass diffusivity

Antidepressant Potential of Ferula gummosa Essential Oil in Mouse Models

Background and objectives: Earlier researches have exhibited the antioxidant, antinociceptive, and antiepileptic effects of Ferula gummosa. Considering that antioxidants play a key role in the pathogenesis of depression, the antidepressant potential of the F. gummosa essential oil was assessed by using a mouse models. Methods:Lorke’s method was used to access the acute toxicity of the F. gummosa essential oil. The F. gummosa essential oil (5-40 mg/kg), standard agents, and vehicle were administered to animals. The forced-swimming test (FST), tail suspension test (TST), and open-field test (OFT) were used for the evaluation of depression. Results: The F. gummosa essential oil LD50 was found to be 316.22 mg/Kg b.w. β-Pinene, α-pinene, guaiol, δ-3-carene, bulnesol, α-Bisabolol, and β-myrcenewere the major components of the F. gummosaessential oil, respectively. In both FST and TST, 10-40 mg/kg of the essential oil decreased the duration of immobility. Furthermore, 10-40mg/kg of the F. gummosa essential oil enhanced the duration of swimming with no significant effect on the duration of climbing in FST. The F. gummosaessential oil did not change the animal locomotion in the OFT. Conclusion: According to the results, the F. gummosa essential oil showed antidepressant activity similar to fluoxetine which may have a potential clinical value for the treatment of depression