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Infectious laryngotracheitis virus (ILTV) is a cause of main respiratory disease of chickens controlled through live attenuated vaccines. To reduce the risk of adverse effects associated with live vaccines, a recombinant vaccine expressing PH-1 domain of viral glycoprotein B was constructed using the pET expression system under isopropylthiogalactoside (IPTG) induction. The potential immunogenicity of recombinant PH-1 (rPH-1) was evaluated in chickens. Eight-week-old specific-pathogen-free chickens were intramuscularly administered two doses of rPH-1, 25 and 50 μg, alone or with a combination of ISA70 adjuvant. The humoral immune responses were determined up to 3 months postvaccination at 2 weeks apart. The T cell proliferation response was determined on day 28 after primary immunization. The vaccinated birds with rPH-1/ISA70 developed higher and constant-specific anti-ILTV enzyme-linked immunosorbent assay (ELISA) antibodies than in those vaccinated with rPH-1 alone. Coinjection of rPH-1 and adjuvant significantly (

Natural disasters play a main role in human life. It should be taken into consideration that it is impossible to predict these disasters from happening, but preparation for a good response for these disasters can be a good solution to decrease post-damage casualties in the cities. Herein, Disaster Management Bases in terms of prevention, preparation and dealing with the crisis play a key role, especially in Tehran and in times of natural disasters. There is no doubt that a high level and efficient function of these bases has a striking correlation with the way they are located in both an urban and regional level in a way that in addition to providing security of the bases against disasters, based on the service area they could be able to provide good services for the areas of crisis. This paper tries to use Multi Criteria Decision Making (MCDM) techniques and spatial analysis method in order to assess the effectiveness of these bases. Based on assessments Disaster Management Bases have spontaneously distributed in Tehran and have located in inappropriate places. Thus using MCDM with GIS analysis, the best locations in case study area was proposed.

Additional file 1.

Satar Rezaei,1 Mohammad Hajizadeh,2 Sina Ahmadi,3 Mohammad Ebrahimi,4 Behzad Karami Matin1 1Research Center for Environmental Determinants of Health, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran; 2School of Health Administration, Faculty of Health, Dalhousie University, Halifax, NS, Canada; 3Department of Social Welfare Management, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran; 4Student Research Committee, Kermanshah University of Medical Sciences, Kermanshah, IranCorrespondence: Behzad Karami Matin Research Center for Environmental Determinants of HealthHealth Institute, Kermanshah University of Medical Sciences, Kermanshah, IranTel +98 83 38264164Postal code +98- 6719851351 Email bkmatin1344@gmail.comBackground: Self-medication (SM) is a public health concern globally. This study aimed to measure socioeconomic inequality in SM and identify its main determinants among Iranian households.Methods: A total of 38,859 households from the 2018 Household Income and Expenditure Survey (HIES) were included in the study. Data on SM, household size, age, gender and education status of the head of household, monthly household’s expenditures (as a proxy for socioeconomic status), health insurance coverage and living areas and provinces were obtained for the survey. The concentration curve and the normalized concentration index (Cn) were used to quantify the magnitude of socioeconomic inequality in SM among Iranian households. The Cn was decomposed to identify the main determinants of socioeconomic inequality in SM in Iran.Results: The results indicated that 18.2% (95% confidence interval [CI]: 17.7% to 18.5%) of households in Iran had SM practice in the past month. The results suggested a higher concentration of SM among the rich households (Cn= 0.0466; 95% CI= 0.0321 to 0.0612) in Iran. The concentration of SM among high SES households was also found in urban (0.0311; 95% CI=0.0112 to 0.0510) and rural (= 0.0513; 95% CI=0.0301 to 0.0726) areas. SM was concentrated among the rich households in Tehran, Qom, Esfahan, Ardebil, Golestan, and Sistan and Baluchestan provinces. In contrast, a higher concentration of SM was found among the poor households in Semnan, North Khorasan, Kerman, Bushehr, and South Khorasan provinces. The decomposition revealed SES of household, itself, as the main contributing factor to the concentration of SM among the wealthy households.Conclusion: This study demonstrated that SM is more concentrated among socioeconomically advantaged households in Iran. Thus, effective evidence-based interventions should be implemented to improve awareness about SM and its negative consequences. Further studies are required to investigate the consequences of SM practice among people.Keywords: self-medication, inequality, socioeconomic status, Iran

Additional file 1. Proportion of households with positive tobacco expenditure in the past month by province in Iran, 2018. The proportion of households with tobacco expenditure more than zero in the last month was about 20%. These proportions for provinces based on their Human Development Index (HDI) were 18.7%, 22.9, and 18.8% (high, middle, and low, correspondingly).

While physical sensing has been used for a long time to observe events and natural phenomena, social sensing has emerged as a new paradigm that uses humans as “sensors” (also known as social sensors) to report their observations about the physical world. Social sensing transforms how we sense the world and complements physical sensing by substantially extending the horizon we know about the world in real time. This thesis addresses two main challenges in the sensing area: (1) Proposing a scalable framework for searching physical sensors; and (2) Enabling social sensing through efficient methods for predicting the geolocation of social sensors. While the number of physical sensors deployed around the world is growing at a rapid pace, an important challenge is to determine which physical sensors should be selected to retrieve the desired data for monitoring, detecting or discovering a phenomenon. Considering the Internet of Things (IoT) as an enabler for physical sensing, we proposed a scalable context-aware sensor search framework to deal with the dramatic increase of sensors and consequently the data collected by those sensors in the future IoT. We also perform novel adjustments to increase the efficiency of our system and maintain its accuracy against dynamic nature of IoT environment. Experimental results over large scale datasets show the efficiency and scalability of our proposed framework. Social sensors, which are social media users, can react to phenomena and events of many kinds such as earthquake by making posts about it. Consequently, social sensing enables a wide range of new applications and services such as rapid disaster response and opinion analysis. Social media users should provide their locations to be useful as social sensors, however, majority of them do not declare their locations. To address this issue, we have focused on user geolocation which is the task of predicting the location of a user from available sources of information, such as text posted by that individual, or network relationships with other individuals. To this end, we propose novel predictive models based on the following intuitions: 1) People who are well-known in their local communities (local celebrities) can be used as important clues to geolocate their followers; 2) Users who live nearby are more likely to influence each other and discuss more local topics; hence, semantic similarity between users' posts can predict their geographic proximity. Moreover, we present an efficient joint model based on the fusion of neural networks to incorporate different types of available information including text, users' social relationships, and metadata fields ebmeded in tweets and profiles such as time zone and user language. We have utilized four standard Twitter geolocation benchmark datasets to evaluate our methods. The results indicate that the proposed methods significantly improve the performance of user geolocation in terms of accuracy and mean/median error distances, and yield state-of-the-art results over all datasets.

This work is organized as follows. In the first section we review the prior work and we have obtained our data. Next, we will look at address reuse in the Bitcoin network. We show that a great portion of users reuse their addresses which could enable us to cluster the addresses and attribute them to single users. Next, we will categorize the nodes based on their role in the network as a customer or seller. Finally, we do a study of nodes and network performance., Comment: 8 pages, 7 figures

Background and Aims: A multiplex transcription-polymerase chain reaction (m-PCR) was developed for direct detection and discrimination between canarypox virus (CPV) and other avian poxvirus (APV). Materials and Methods: Three compatible primer sets were designed for m-PCR amplification of different loci; fpv126, fpv140, and fpv167 located at highly conserved APV genes. Results: Results showed that m-PCR products of the expected sizes were obtained for all of the primer sets when they were tested either alone or in combination with an artificial mixture of positive controls. Based on the better amplification of fpv167 than other loci, the locus primer set was used to examine tissue samples from canaries clinically diagnosed as AVPinfected. Conclusion: All canary samples were positive for CPV by the m-PCR and virus isolation. The results of the present study indicate the m-PCR assay holds potential to be versatile, rapid, and sensitive for detection of CPV and differentiation of the virus from the other APVs.

The most important of Land-consolidation programs is to decrease consumption of chemical inputs (fertilizer and toxins) in paddy fields, thus enhancing sustainability. This study compares the consumption of inputs in traditional and developed paddy fields in Iran, based on a case study of Gilan province. The research was conducted in the form of a sur- vey study. The data for this research was collected from 176 farmers who work traditional rice fields and 188 farmers who are part of a farm-development program in Gilan province, who were selected using a stratified random sampling procedure. Data was collected through a questionnaire. The reliability of questionnaire was determined by calculating the Cronbach's alpha coefficient (0.75) after conducting a pilot study. Analysis of the survey results showed that the average consumption of chemical fertilizer in developed paddy fields (363 kg of fertilizers per hectare) was greater than that in traditional paddy fields (308 kg/ha). In contrast, developed paddy fields used less toxins (6.4 kg/ha) than traditional paddy fields (8.3 kg/ha). The t-test showed that in two groups of farmers, the farmers of developed paddy lands used significantly more chemical toxins and manure, and significantly less chemical fertilizer, than farmers of traditional paddy lands.

In this paper we prove that the entropy of a fuzzy measure preserving transformationwith respect to a sub-σ-algebra having finite atoms is affine and then we extendthe method of computing the entropy of a finite sub-σ-algebra to a sub-σ-algebra havingcountable atoms, and we investigate the ergodic properties of fuzzy probability dynamicalsystems. At the end by using this notion, a version of Kolmogorov-Sinai proposition [6, 9,10] is given.

Land consolidation is a strategy for the development of Iranian rice-growing regions. The most important targets of the program are reducing rice farmers' expenses and increasing their income. The object of this article is to conduct a factor analysis of Iranian paddy-field consolidation. The research was conducted in the form of a survey study. The data was collected from188 farmers participating in a farm-development program in Guilan province, sampled using a stratified random sampling method. The reliability of the questionnaire was calculated using a Cronbach alpha coefficient (alpha >0.78) for different sections after conducting a pilot study. Factor analysis for farmers with rice fields in projects showed that five factors explained 63.92% of total variance. These factors were: 1) social, 2) instructional, 3) environmental, 4) economic and 5) institutional effects. Social effects alone, the factor with the greatest effect, explained 34.84% of total variance.

Introduction: Chronic occupational noise exposure may constitute a risk factor for cardiovascular disease for workers. The aim of this study was to investigate the relationship between occupational noise exposure and noise annoyance with blood pressure, serum cholesterol and triglyceride levels in workers of a textile industry. Material and Method: This cross-sectional study was carried out among 220 employees of Savadkouh textile industry complex in Mazandaran province, Iran in 2017. To achieve the study objectives, the 8 -hour equivalent sound exposure level was measured and the cumulative noise exposure was calculated. Based on noise exposure level, workers were divided into control and case groups. Then, blood pressure was measured and blood samples were collected from each individual for determination of the serum cholesterol and triglyceride levels and they were transfered to the laboratory for further analysis. The noise annoyance scale and socio-demographic questionnaire were used to collect noise annoyance and other background and demographic information, respectively. Finally, Paired t-test, one-way ANOVA and multivariate regression were used to study the relationship between variables using SPSS Version 20. Result: In total, 159 workers participated in this study considering the inclusion and exclusion criteria. Eighty-three participants were exposed to more than or equal to 85 dBA, and 76 person were exposed to less than 85 dBA noise level, respectively. The results showed that mean blood pressure and cholesterol were significantly different between the control and case groups (P-value< 0.05). Based on multivariate regression results, noise exposure, cumulative noise exposure (CNE) and noise annoyance had a significant effect on blood pressure (P-value< 0.001). Cholesterol was also significantly affected by noise exposure and noise annoyance (P-value< 0.005). Conclusion: Based on the results of current study, noise can be considered as a risk factor for cardiovascular disease ampong workers. Actually, high intensity noise affect serum cholesterol and blood pressure directly, and may do indirectly by causing noise annoyance which acts as a mediator. Therefore, it seems necessary to conduct a controlled cohort study to investigating the interactions among whole variables of interest.

Logistics planning (LP) is the process of integrating and utilizing suppliers, manufacturers, warehouses, and retailers so that products are produced and delivered at the right quantities and at the right time while minimizing costs and satisfying customer requirements. Implementation of LS has crucial impacts on a company's financial performance and LP optimization is essential to achieve globally optimized operations. The six major cost components that form the overall logistics costs are raw material costs, costs of raw material transportation from vendors to manufacturing plants, production costs at manufacturing plants, transportation costs from plants to warehouses, inventory or storage costs at warehouses, and transportation costs from warehouses to end users. In a logistics optimization model, the overall systemwide costs are to be minimized through effective procurement, production, distribution, and inventory management. It is widely acknowledged that many benefits can be achieved by treating a logistics network as a whole (integration in LS) for optimization purposes, which requires the simultaneous minimization of all systemwide costs. © 2011 Elsevier Inc. All rights reserved.