A Coverage Monitoring algorithm based on Learning Automata for Wireless Sensor Networks

To cover a set of targets with known locations within an area with limited or prohibited ground access using a wireless sensor network, one approach is to deploy the sensors remotely, from an aircraft. In this approach, the lack of precise sensor placement is compensated by redundant de-ployment of sensor nodes. This redundancy can also be used for extending the lifetime of the network, if a proper scheduling mechanism is available for scheduling the active and sleep times of sensor nodes in such a way that each node is in active mode only if it is required to. In this pa-per, we propose an efficient scheduling method based on learning automata and we called it LAML, in which each node is equipped with a learning automaton, which helps the node to select its proper state (active or sleep), at any given time. To study the performance of the proposed method, computer simulations are conducted. Results of these simulations show that the pro-posed scheduling method can better prolong the lifetime of the network in comparison to similar existing method

TEL: Low-Latency Failover Traffic Engineering in Data Plane

Modern network applications demand low-latency traffic engineering in the presence of network failure while preserving the quality of service constraints like delay and capacity. Fast Re-Route (FRR) mechanisms are widely used for traffic re-routing purposes in failure scenarios. Control plane FRR typically computes the backup forwarding rules to detour the traffic in the data plane when the failure occurs. This mechanism could be computed in the data plane with the emergence of programmable data planes. In this paper, we propose a system (called TEL) that contains two FRR mechanisms, namely, TEL-C and TEL-D. The first one computes backup forwarding rules in the control plane, satisfying max-min fair allocation. The second mechanism provides FRR in the data plane. Both algorithms require minimal memory on programmable data planes and are well-suited with modern line rate match-action forwarding architectures (e.g., PISA). We implement both mechanisms on P4 programmable software switches (e.g., BMv2 and Tofino) and measure their performance on various topologies. The obtained results from a datacenter topology show that our FRR mechanism can improve the flow completion time up to 4.6x$-$7.3x (i.e., small flows) and 3.1x$-$12x (i.e., large flows) compared to recirculation-based mechanisms, such as F10, respectively

Detecting the adulteration in apple vinegar using olfactory machine coupled PCA and ANN methods

Nowadays, the number of food adulteration cases is increasing sharply for reasons such as population growth, increasing demand and profitability of suppliers. Mixing apple vinegar with white vinegar and acetic acid are the most common methods of cheating on the market in Iran. In this study, an electrical olfactory system was used to detect pure apple vinegar from acetic acid and white vinegar. The data obtained from the sensors were analyzed by PCA and ANN methods after preprocessing. Based on the results, TGS822 and MQ136 sensors showed the highest response to odor of samples of vinegar mixed with acetic acid and white vinegar, respectively. Also, the confusion matrix obtained from ANN analysis for different levels of adulteration with acetic acid and white vinegar showed correct classification rate of 93.3% and 94.7%, respectively

Low-dose subconjunctival bevacizumab to augment trabeculectomy for glaucoma

Mohammad-Reza Sedghipour, Ali Mostafaei, Yousef TaghaviNikoukari Ophthalmology University Hospital, Tabriz University of Medical Sciences, Tabriz, IranBackground: The purpose of this study was to assess the effect of bevacizumab in maintaining intraocular pressure lowered by trabeculectomy in refractory open-angle glaucoma.Methods: Thirty-seven eyes from 37 patients referring to Nikoukari Ophthalmology University Hospital in Tabriz were enrolled in this randomized clinical trial. Seventeen patients were randomly assigned to receive bevacizumab augmentation after trabeculectomy, and 20 patients were assigned to a control group receiving a placebo injection of normal saline. Bevacizumab was injected subconjunctivally at a dose of 0.2 mg. Intraocular pressure was measured on eight occasions, ie, at baseline, 24 hours, 3 days, 7 days, 2 weeks, 1 month, 2 months, and 3 months after treatment.Results: Men constituted 81% of the participants, who were of mean age 67.5 years. Twenty-nine patients had secondary open-angle glaucoma, while eight patients had primary open-angle glaucoma. Intraocular pressure decreased from a mean of 28.4 mmHg at baseline to a mean of 12.1 mmHg during the first day and to 15.1 mmHg after 3 months. Adding bevacizumab to trabeculectomy was not found to affect intraocular pressure differently to placebo. Neither the results of repeated measurements analysis nor single comparison statistical tests were significant for a difference in efficacy of bevacizumab versus placebo.Conclusion: Subconjunctival bevacizumab 0.2 mg was not found to affect the trend in intraocular pressure more than placebo after trabeculectomy for open-angle glaucoma.Keywords: glaucoma, trabeculectomy, bevacizumab, antivascular endothelial growth factor agent

Evaluating the CDMA System Using Hidden Markov and Semi Hidden Markov Models

CDMA is an important and basic part of today’s communications technologies. This technology can be analyzed efficiently by reducing the time, computation burden, and cost by characterizing the physical layer with a Markov Model. Waveform level simulation is generally used for simulating different parts of a digital communication system. In this paper, we introduce two different mathematical methods to model digital communication channels. Hidden Markov and Semi Hidden Markov models’ applications have been investigated for evaluating the DS-CDMA link performance with different parameters. Hidden Markov Models have been a powerful mathematical tool that can be applied as models of discrete-time series in many fields successfully. A semi-hidden Markov model as a stochastic process is a modification of hidden Markov models with states that are no longer unobservable and less hidden. A principal characteristic of this mathematical model is statistical inertia, which admits the generation, and analysis of observation symbol contains frequent runs. The SHMMs cause a substantial reduction in the model parameter set. Therefore in most cases, these models are computationally more efficient models compared to HMMs. After 30 iterations for different Number of Interferers, all parameters have been estimated as the likelihood become constant by the Baum Welch algorithm. It has been demonstrated that by employing these two models for different Numbers of Interferers and Number of symbols, Error sequences can be generated, which are statistically the same as the sequences derived from the CDMA simulation. An excellent match confirms both models’ reliability to those of the underlying CDMA-based physical layer

Relationships between the Salivary Microbial Composition and Gastrointestinal Diseases

Abstract   Background and Objective: Salivary microbiota, including bacteria shed from oral surfaces, is individualized, temporally stable and affected by the environmental factors such as diet, lifestyle and oral hygiene. Salivary microbiota is nonpathogenic and commensal; however, if microbiota colonizes into the intestines, they could alter gastrointestinal microbiota and result in development of several chronic inflammatory diseases, foremost autoimmune diseases and gastrointestinal cancers. There are few studies that assessed salivary microbiota in autoimmune gastrointestinal disorders. This may help researchers find novel personalized therapeutic approaches for the gastrointestinal diseases. Therefore, the aim of this review was to discuss alterations of salivary microbiota composition in gastrointestinal disease progress, including celiac disease, inflammatory bowel disease and gastrointestinal cancers. Results and Conclusion: This study suggested that oral microbiota composition is linked to chronic inflammatory diseases by changing the immune system responses through increasing the production of inflammatory cytokines and mediators. Investigation of saliva microbiota is becoming an important part of diagnosing gastrointestinal diseases and changes in the composition of oral microbiota can predict risks of disorder progression in high-risk individuals. Conflict of interest: The authors declare no conflict of interest

EFL Learning, EFL Motivation Types, and National Identity: In Conflict or in Coalition

The present study was aimed at examining concerns about the social effects of EFL learning, a challenging area of research which has not been discussed sufficiently. It tried to investigate the relationship between EFL learning and national identity. In addition, attempt was made to find a relationship between language motivation types and national identity. Furthermore, the role of two demographic variables, gender and age was examined. To this end, a sample consisting of 350 undergraduates studying at Allameh Tabataba'i University in Tehran took part in the study. A questionnaire on national identity and another one on language motivation types followed by an interview were the instruments used. The questionnaires had already been developed. However, there were some major modifications for the former which consisted of 30 items measuring national identity for all participants. The latter contained 42 items measuring language motivation types for only EFL learners. The Regression analysis,  independent samples t-tests and a one-way ANOVA were run. The results revealed that claims over the harmful social effects of EFL learning were not arguably significant and it was found that among the eight language motivation types, going abroad and social responsibility were correlated with national identity. Furthermore, gender and age indicated significant differences among the participants' tendencies. The findings indicated that the social concerns about EFL learning are too pessimistic. So, materials developers, syllabus designers and teachers might consider the potentiality of some social elementsand demographic variables for the development of EFL learning

Seroepidemiology of Toxocariasis in Children (5-15 yr Old) Referred to the Pediatric Clinic of Imam Hossein Hospital, Isfahan, Iran.

BACKGROUND: Human toxocariasis, a helminthozoonosis, is due to the migration of Toxocara species larvae into human organisms. Humans, especially children become infected by ingesting of embryonated eggs from soil, dirty hands, and raw vegetables. Seroprevalence of this infection is high in developed countries, especially in rural areas. The aim of this study was to investigate the seroepidemiology of Toxocariasis in children referred to the pediatric clinic of Imam Hossein hospital, Isfahan, Iran. METHODS: In this cross sectional study the sera of children aged 5 to 15 years old, admitted to Imam Hossein Pediatric Hospital were collected during 2013-14. Then the sera were examined for anti Toxocara canis antibodies using commercial ELISA kit. RESULTS: From 427 children, 196 (45.9%) were female and 231(54.1%) were male. 107(25.1%) were from rural and 320 (74.9%) were from urban area. Of them 129 (30.2%) were contacted with dog. One child (0.2%) had hypereosinophilia, 33 (7.7%) eosinophlia, and 6 (1.39%) were positive for T. canis IgG (two male and four female). Four of infected children with T. canis were from urban (1.25%) and two from rural areas (1.9%). There was no significant correlation between education of parents, gender, age, place of living and contact with dog with ELISA results test. CONCLUSION: Toxocariasis is prevalent in the children of Isfahan region. Results suggest a low Toxocara exposure in children in this area. Therefore, more risk factors associated with Toxocara exposure should be identified in the further investigatio

Extension of the Theory of Planned Behavior (TPB) to Predict Patterns of Marijuana Use among Young Iranian Adults

Background; : Marijuana use is increasing among adolescents and young adults. Long-term marijuana use magnifies the risk of a wide variety of behavioral, cognitive-emotional, and neurological problems, and can be a gateway to use of other drugs. In the present study, we investigated the cognitive-emotional and behavioral predictors of marijuana use. To this end, young Iranian adults answered questions based on an extended Theory of Planned Behavior (TPB) and related it to marijuana use. We hypothesized that cognitive-emotional and behavioral factors would predict intention to use marijuana, and that this, in turn, would predict actual consumption.; Methods; : A total of 166 young Iranian adults (mean age: 20.51 years; 15.7% females) attending a walk-in center for drug use took part in this cross-sectional study. Participants completed questionnaires covering sociodemographic information, frequency of marijuana use per week, along with questionnaires assessing the following dimensions of the TPB: attitude towards marijuana use, subjective norms, self-efficacy to resist marijuana use, environmental constraints, problem-solving skills, and behavioral intention for marijuana use.; Results; : Mean marijuana use was found to be 4.6 times/week. Attitude towards marijuana use, subjective norms, environmental constraints, and behavioral intention to use marijuana were positively correlated to each other and with marijuana use/week. In contrast, higher self-efficacy and problem-solving skills were associated with lower marijuana use/week. The multiple regression analysis showed that a positive attitude to marijuana use, lower self-efficacy in resisting its use, higher behavioral intention, and poorer problem-solving skills predicted actual use.; Conclusion; : The pattern of results suggests that dimensions of TPB can explain marijuana use among young Iranian adults self-admitted to a walk-in center for drug use. Specifically, poor problem-solving skills, low self-efficacy in resisting marijuana use, and positive labelling of its use appeared to be the best predictors of actual use. It follows that prevention programs aimed at improving problem-solving skills and raising self-efficacy, along with educational interventions aimed at highlighting the negative effects of marijuana might decrease the risk of its use among young adults in Iran

Downregulation of Autophagy-related Genes in Macrophages from Patients with Behcet's Disease

Objective: Overwhelming inflammatory chemokines and cytokines characterize the immunological profile and inflammatory settings of Behcet disease (BD). The connection between autophagy-related genes (ATGs) and various perspectives of innate and adaptive immunobiology such as antigen presentation, immune tolerance, lymphocyte development and differentiation, cytokine signaling, and inflammation have been implicated. The aim of this study was to evaluate the mRNA expression profile of ATGs in macrophages of patients with BD. Materials and Methods: Whole blood samples were obtained from 10 BD patients and 10 healthy controls. Monocytes were isolated from the blood samples and then differentiated to macrophages using macrophage colony-stimulating factor (M-CSF). After total RNA extraction and cDNA synthesis, quantitative analysis of ATGs including ATG5, ATG7, ATG12, LC3b, mTOR, RAPTOR, and RICTOR was conducted by SYBR Green master mix and real-time polymerase chain reaction (PCR). Results: mRNA expression of all ATGs was downregulated in macrophages of BD patients compared with healthy controls. It is worth to note that the downregulation of ATG12 and LC3b mRNAs in macrophages of BD patients was statistically significant in comparison to that of healthy control group (P = 0.007 and 0.021, respectively). Conclusion: Considering the role of autophagy in initiation of immune responses and then clearance of dead cells as well as its participation in the development and differentiation of immune cells, downregulation of ATGs in macrophages of BD patients may be involved in uncontrolled immune response and overproduction of inflammatory cytokines