Nonthermal Effects of Radar Exposure on Human: A Review Article

ABSTRACT Microwave is part of the electromagnetic spectrum that has different application such as communications, military, air-traffic Control and etc... Previous studies showed that radar frequency could be a health hazard agent. This review article mentioned some of the studies that investigated non-thermal effects of radar frequencies. Reproductive effects, cancers, blood effects, genetic, adverse immune effects and mental effects are non-thermal effects that presented in this report. There are many unknown aspects of the biological effects and many of them did not determined very well such as oxidative stress and mental effects. Compliance with permissible exposure limits, reduction in exposure, and shielding are some of the controlling methods to protect workers from the exposure of microwave and among them, The use of shielding is a superior method for prevention of microwave exposure and among them, electromagnetic Nano composites shields is appropriate for protection of workers from radar exposure

An attenuation Layer for Electromagnetic Shielding in X- Band Frequency

Uncontrolled exposure to X-band frequency leads to health damage. One of the principles of radiation protection is shielding. But, conventional shielding materials have disadvantages. Therefore, studies of novel materials, as an alternative to conventional shielding materials, are required to obtain new electromagnetic shielding material. Therefore, this study investigated the electromagnetic shielding of two component epoxy thermosetting resin for the X - band frequency with workplace approach. Two components of epoxy resin mixed according to manufacturing instruction with the weight ratio that was 100:10 .Epoxy plates fabricated in three different thicknesses (2, 4 and 6mm) and shielding effectiveness measured by Vector Network Analyzer. Then, shielding effectiveness measured by the scattering parameters.The results showed that 6mm thickness of epoxy had the highest and 2mm had the lowest average of shielding effectiveness in X-band frequency that is 4.48 and 1.9 dB, respectively. Also, shielding effectiveness increased by increasing the thickness. But this increasing is useful up to 4mm. Percentage shielding effectiveness of attenuation for 6, 4 and 2mm thicknesses is 64.35%, 63.31% and 35.40%. Also, attenuation values for 4mm and 6mm thicknesses at 8.53 GHz and 8.52 GHz frequency are 77.15% and 82.95%, respectively, and can be used as favourite shields for the above frequency. 4mm-Epoxy is a suitable candidate for shielding application in X-band frequency range but, in the lower section, 6mm thickness is recommended. Finely, the shielding matrix can be used for selecting the proper thickness for electromagnetic shielding in X- Band frequency

The Impacts of Water Pricing and Non-Pricing Policies on Sustainable Water Resources Management: A Case of Ghorveh Plain at Kurdistan Province, Iran

As with other regions of Iran, due to excessive extraction of groundwater for intense agricultural activity, Ghorveh plain, a water-scarce irrigation district in the west of Iran, has faced a serious water crisis during the last decade. The present study investigates the impacts of two scenario policies, namely, non-price policy (as a supply-oriented policy) and water pricing policies (as a demand-oriented policy) on agricultural sector of Ghorveh Plain, using positive mathematical programming (PMP). The model was calibrated by using farm-level data for the crop years in 2016–2017. Our findings indicate that applying water supply constraint policy will change the land use and cropping pattern to the crops with higher water productivity. The increase of water resource constraints can lead to the increase of water economic return which indicates a rising value of water resources shortage, warning the producers of the agriculture sector to allocate water to the crops with higher economic value under the water resources shortage conditions. In addition, the findings underline that in a situation where the price of irrigation water is low due to the low elasticity of water demand in the agriculture sector, formulating the economic instruments such as rising water prices does not solely suffice to achieve sustainable water resource management. However, mixed scenarios emphasized that the water distribution policies should be aligned with the increases in water cost. © 2019 by the authors

Antimicrobial effects of Kelussia odoratissima extracts against food borne and food spoilage bacteria "in vitro"

The aim of this paper was to investigate the antibacterial potential of Kelussia odoratissima Mozff extract against Gram-negative and Gram-positive bacteria. Karafs-eKoohi with the scientific name of Kelussia odoratissima is an Iranian endemic edible plant in the middle region of Iran with enormous use as food, spice and medicinal herb. The antibacterial effect of the extracts was investigated using pour plate and disk diffusion methods. Minimum Inhibitory Concentration (MIC( and Minimum Bactericidal Concentration (MBC) were also studied using the dilution method. Repeated measure ANOVA was used for data analysis. The results showed that in disk diffusion method all concentrations of ethanolic extract had inhibitory effect against Bacillus subtilis and Staphylococcus aureus. Minimum Inhibitory Concentration (MIC( of Kelussia odoratissima leaves of aqueous and ethanolic extracts for Bacillus subtilis and Staphylococcus aureus were 16 and 8 mg/ml, and for Enterobacter aerogenes were 32 and 16 mg/ml, respectively. Minimum Bactericidal Concentration (MBC) of Kelussia odoratissima leaves of aqueous and ethanolic extracts for Bacillus subtilis and Staphylococcus aureus were 32 and 16 mg/ml, and for Enterobacter aerogenes were 64 and 32mg/ml, respectively. The results showed that the extract of Kelussia odoratissima had a satisfactory antimicrobial activity and the ethanolic extract of Kelussia odoratissima leaves had greater inhibitory effects on the strains studied compared to aqueous extract in vitro. A significant correlation was also observed between zone of inhibition and concentration of extracts

An investigation on the effect of alcoholic and aqueous extracts of Dorema aucheri (Bilhar) on some pathogenic bacteria in vitro

       Dorema aucheri is a plant that grows in Iran. In Persian it is called (Bilhar). This experimental study was carried out at Ferdowsi University of Mashhad in 2014. After collection and preparation of aqueous and ethanolic extracts of Dorema aucheri (Bilhar), The antibacterial activity of ethanolic and aqueous extracts of Bilhar was evaluated against 7 laboratory strains of microorganisms, including 4 Gram positive (Staphylococcus aureus, Streptococcus pyogenes, Bacillus cereus and Bacillus subtilis) and 3 Gram negative bacteria (Escherichia coli, Pseudomonas aeruginosa and Proteus vulgaris). Its effects against human pathogen microorganism were determined using “Spreading of the Extract on Medium Surface” and “Disk Agar Diffusion Method”, Minimal Inhibitory Concentration (MIC) and Minimum Lethal Concentration (MLC) were determined for this extract. Collected data were analyzed by SPSS software using one-way ANOVA. The zone of inhibition for the ethanolic extract varied from 8 mm for P. aeruginosa to 24 mm for S. pyogenes and from 7 mm for P. aeruginosa to 19 mm for S.pyogenes in the aqueous extract. The minimum inhibitory concentration (MIC) of the extracts ranged between 2 mg/ml and 64 mg/ml while the minimum lethal concentration (MLC) ranged between 4 mg/ml and 256 mg/ml. Among of tested strains, P. aeruginosa has maximum MIC and MBC. 30 and 40 mg/mL Concentrations of Redcurrant have significant antimicrobial effect on bacteria. Antibacterial effect of extracts was decreased with decrease of extract concentration in disk. According to result, ethanolic extract of Dorema aucheri have antimicrobial effect on growth of all of the strains exposed analyzes and antimicrobial effect of that was maximum on Gram-positive bacterum of S. pyogenes. P. aeruginosa showed the highest level of resistance against the aqueous and ethanolic Bilhar extracts. The present study demonstrated that the ethanol leaf extract of Dorema aucheri hold an excellent potential as an antibacterial agent.

Family History of Alzheimer’s Disease Increases the Risk of COVID-19 Positivity: A SUMS Employees Cohort-based Study

Background: Substantial data indicate that genetic and environmental factors play a key role in determining the risk of Alzheimer’s disease (AD). Moreover, it is known that having relatives with AD increases the risk of developing this disease.Objective: This study is aimed at investigating whether having a family history of AD, may increase the risk of COVID-19 in a cohort-based study.Material and Methods: Participants of this retrospective cohort study were previously enrolled in the SUMS Employees Cohort (SUMSEC). All participants including those whose SARS-CoV-2 infection was confirmed by positive PCR test and chest CT scan were requested to respond to interviewer-administered questionnaires. Moreover, AD was diagnosed via memory and thinking impairment, concentration problems, confusion with location, and problems in finishing daily tasks.Results: The total numbers of female and male participants with a family history of AD were 463 and 222 individuals, respectively. When all types of family history of AD were considered, a 51.3% increase was found in the relative frequency of the participants with both family history of AD and confirmed COVID-19 compared with those only with a family history of AD. Conclusion: Despite the limitations of our study, and from a broader perspective, our findings can further support the concept that AD risk haplotypes including APOE are linked to the same morbidities from cardiovascular disease and obesity that increase vulnerability to COVID-19. Given this consideration, millions of APOE ε4 carriers around the globe should be advised to take additional precautions to prevent life-threatening diseases such as COVID-19

Analysis of different signal peptides for the secretory production of Ama r 2 in gram-positive systems (Lactococcus lactis)

Prokaryotic systems have been considered the most affordable and simplest hosts which are being employed to express recombinant proteins such as allergens; nevertheless, without appropriate signal peptide (SP), these systems cannot be used for secretory proteins. Recently, a lot of effort has been put into assessing the potential of gram-positive strains such as lactic acid bacteria for new applications in the production of heterologous proteins. Ama r 2 is a respiratory allergen from Amaranthus retroflexus, whose recombinant production in the probiotic host could be introduced as a specific and effective way to rapid diagnosis and immunotherapy of this allergy. Consequently, the production of this recombinant protein using the prokaryotic system, requires a suitable SP to protect disulfide bonds and to prevent misfolding. This study was designed to predict the best SPs for the expression of Ama r 2 protein in Lactococcus lactis as the host. In this study, 42 signal sequences were selected from SP databases and the most important features of them were evaluated. First, n, h and c regions of the SPs and their probabilities were investigated by signalP software version 4.1. Then, their physicochemical properties were evaluated by Portparam and SOLpro. Moreover, the secretion sorting and sub-cellular localization sites were evaluated by PRED-TAT and ProtcompB software programs. The results revealed that yjgB, entC2 (Entrotoxine type C-2), ent B (Entrotoxine type), blaZ (Beta lactamase), dex (number 21), blm (Beta lactamase 2), dex (Dextranase; number 20) and number 26 were introduced theatrically as the best SPs to express Ama r 2 in Lactococcus lactis

Machine Learning Models for Predicting Breast Cancer Risk in Women Exposed to Blue Light from Digital Screens

Background: Nowadays, there is a growing global concern over rapidly increasing screen time (smartphones, tablets, and computers). An accumulating body of evidence indicates that prolonged exposure to short-wavelength visible light (blue component) emitted from digital screens may cause cancer. The application of machine learning (ML) methods has significantly improved the accuracy of predictions in fields such as cancer susceptibility, recurrence, and survival. Objective: To develop an ML model for predicting the risk of breast cancer in women via several parameters related to exposure to ionizing and non-ionizing radiation.Material and Methods: In this analytical study, three ML models Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron Neural Network (MLPNN) were used to analyze data collected from 603 cases, including 309 breast cancer cases and 294 gender and age-matched controls. Standard face-to-face interviews were performed using a standard questionnaire for data collection. Results: The examined models RF, SVM, and MLPNN performed well for correctly classifying cases with breast cancer and the healthy ones (mean sensitivity> 97.2%, mean specificity >96.4%, and average accuracy >97.1%).  Conclusion: Machine learning models can be used to effectively predict the risk of breast cancer via the history of exposure to ionizing and non-ionizing radiation (including blue light and screen time issues) parameters. The performance of the developed methods is encouraging; nevertheless, further investigation is required to confirm that machine learning techniques can diagnose breast cancer with relatively high accuracies automatically