Cervical cancer is the fourth common cancer among women worldwide. Pap smear screening has resulted in deceasing incidence of cervical cancer in developed countries but low uptake of Pap smear ...screening among women in developing countries is still a public health challenge. The aim of this cross-sectional study was to assess the relationship between self-efficacy and timely uptake of Pap smear among Iranian women. A total of 580 married women referred to primary health care centers covered administratively by Shahid Beheshti University of Medical Sciences in Tehran were administered a questionnaire by trained staff. Data were analyzed with SPSS (version 16) software, using univariate and multivariate logistic regression. The mean age for participants was 33.1±8.8 years. There was a significant association between self-efficacy and Pap smear screening (P<0.01). There was also a positive correlation between duration of marriage and husband's education with Pap smear uptake (P<0.01). In univariate analysis, there was a significant association between Pap smear uptake and level of self-efficacy (OR = 15.3 for intermediate and OR=7.4 for good level), duration of marriage (OR = 5.7 for 5-14 years and OR=10.4 for more than 15), age (OR =2.7 for 27-34 years and OR=7.4 for more than 35 years) and husband education level (OR=2.3 for more than 12 years of education). In multivariate analysis, significant associations persisted between Pap smear uptake and self-efficacy (OR = 23.8; 95% CI: 8.7, 65.5), duration of marriage (OR = 5.9; 95% CI: 2.8, 12.2), age (OR = 3.9; 95% CI: 1.2, 12.9) and husband's education (OR = 2.5; 95% CI: 2.0, 10.3). Efforts are needed to increase women's knowledge about cervical cancer and improve their self-efficacy and perceptions of the Pap smear screening in order to reduce cervical cancer incidence and mortality rates.
Background
Pollen is one of the most common allergens that cause respiratory allergies worldwide. Pollen grains from poplars have been reported as important sources of pollinosis in many countries.
...Objective
The aim of the present study was to determine the molecular and immunochemical characterization of Pop n 2, a novel allergen of Populus nigra (P nigra) pollen extract.
Methods
In this study, the pollen extract of P nigra was analysed by SDS‐PAGE, and the allergenic profile was determined by IgE immunoblotting and specific ELISA using the sera of twenty allergic patients. The coding sequence of Pop n 2 was cloned and expressed in the Escherichia coli BL21 (DE3) using plasmid the pET‐21b (+). Finally, the expressed recombinant Pop n 2 was purified by affinity chromatography.
Results
Pop n 2 belongs to the profilin family with a molecular weight of approximately 14 kDa. Pop n 2 is the most IgE‐reactive protein (about 65%) in the P nigra pollen extract. The cDNA sequencing results indicated an open reading frame 396 bp that encodes 131 amino acid residues. The results of ELISA and Immunoblotting assays showed that recombinant Pop n 2 could react with the IgE antibody in patients' sera, like its natural counterpart.
Conclusion
Our data revealed that Pop n 2 is a significant allergen in the P nigra pollen extract. Moreover, we observed that the recombinant Pop n 2 produced by the pET‐21b (+) vector in the E colisystem acts as its natural counterpart.
PurposeThis research aims to monitor vegetation indices to assess drought in paddy rice fields in Mazandaran, Iran, and propose the best index to predict rice yield.Design/methodology/approachA ...three-step methodology is applied. First, the paddy rice fields are mapped by using three satellite-based datasets, namely SRTM DEM, Landsat8 TOA and MYD11A2. Second, the maps of indices are extracted using MODIS. And finally, the trend of indices over rice-growing seasons is extracted and compared with the rice yield data.FindingsRice paddies maps and vegetation indices maps are provided. Vegetation Health Index (VHI) combining average Temperature Condition Index (TCI) and minimum Vegetation Condition Index (VCI), and also VHI combining TCImin and VCImin are found to be the most proper indices to predict rice yield.Practical implicationsThe results serve as a guideline for policy-makers and practitioners in the agro-food industry to (1) support sustainable agriculture and food safety in terms of rice production; (2) help balance the supply and demand sides of the rice market and move towards SDG2; (3) use yield prediction in the rice supply chain management, pricing and trade flows management; and (4) assess drought risk in index-based insurances.Originality/valueThis study, as one of the first research assessing and mapping vegetation indices for rice paddies in northern Iran, particularly contributes to (1) extracting the map of paddy rice fields in Mazandaran Province by using satellite-based data on cloud-computing technology in the Google Earth Engine platform; (2) providing the map of VCI and TCI for the period 2010–2019 based on MODIS data and (3) specifying the best index to describe rice yield through proposing different calculation methods for VHI.
This study was aimed at developing a type of slow‐release progesterone micro‐particles useable in a single intramuscular injection for estrus synchronization in non‐breeding season ewes. A total of ...66 ewes were randomly assigned into four groups: CIDR (n = 16): exposed to intravaginal CIDR for 12 days, and three experimental groups, i.e., T100 (n = 16), T150 (n = 17) and T200 (n = 17), receiving a single intramuscular injection of 100, 150 and 200 mg slow‐release progesterone, respectively. Blood sampling was performed on all ewes at five different times, and the ELISA method measured progesterone levels. No significant differences were observed in progesterone levels among the groups in each sampling time. More than 90% of ewes in the CIDR, T100 and T150 groups and all those in T200 showed estrus behaviour, and the rate was not significantly different between groups. The difference in the mean interval from progesterone treatment to estrus was also insignificant. The parturition rate declined by increasing the dose of injected progesterone; although it was similar in CIDR and T100 groups, it decreased significantly in T150 and T200. Since our injectable progesterone formulation was successful in the induction and synchronization of estrus in ewes out of the breeding season, it can be applied as an alternative to the conventional progesterone containing intravaginal devices.
•Consumption of vitamin E (Vit E) may reduce inflammation which improve allergy symptoms.•The Inhibition of cell proliferation could be induced by Vit E through Protein phosphatase 2 (PP2A).•Vit E ...inhibits Eosinophilic and Neutrophilic inflammation via STAT6 inhibition.•The production of inflammatory cytokines, and ROS as well as the Th2 response are inhibited by Vit E.
Allergic diseases are caused by the immune system's response to innocent antigens called allergens. Recent decades have seen a significant increase in the prevalence of allergic diseases worldwide, which has imposed various socio-economic effects in different countries. Various factors, including genetic factors, industrialization, improved hygiene, and climate change contribute to the development of allergic diseases in many parts of the world. Moreover, changes in lifestyle and diet habits play pivotal roles in the prevalence of allergic diseases. Dietary changes caused by decreased intake of antioxidants such as vitamin E lead to the generation of oxidative stress, which is central to the development of allergic diseases. It has been reported in many articles that oxidative stress diverts immune responses to the cells associated with the pathogenesis of allergic diseases. The aim of this short review was to summarize current knowledge about the anti-allergic properties of vitamin E.
Continuous exposure to preservatives such as nitrite salts has deleterious effects on different organs. Meanwhile, Nigella sativa oil can remediate such organ dysfunction. Here, we studied the effect ...of consumption of thymoquinone (TQ); the main component of Nigella sativa oil on the brain damage induced by sodium nitrite. Forty adult male rats were daily given oral gavage of sodium nitrite (80 mg/kg) with or without thymoquinone (50 mg/kg). Oxidative stress, cytokines of inflammation, fibrotic elements and apoptotic markers in brain tissue were measured. Exposure to sodium nitrite (SN) resulted in increased levels of malondialdehyde, TGF-β, c-reactive protein, NF-κB, TNF-α, IL-1β and caspase-3 associated with reduced levels of glutathione, cytochrome c oxidase, Nrf2 and IL-10. However, exposure of rats' brain tissues to thymoquinone resulted ameliorated all these effects. In conclusion, thymoquinone remediates sodium nitrite-induced brain impairment through several mechanisms including attenuation of oxidative stress, retrieving the reduced concentration of glutathione, blocks elevated levels of pro-inflammatory cytokines, restores cytochrome c oxidase activity, and reducing the apoptosis markers in the brain tissues of rats.
Power transformers play a critical role in the performance of power systems. This equipment is costly due to significant copper and iron prices and manufacturing costs. Therefore, maintenance and ...protection of such equipment is essential. Despite its robust performance, maloperation of differential protection (DP) in transformers may cause operational challenges to power system operators. The differential relay may operate incorrectly after the transformer energization leads to an inrush current (IC) and the relay identifies the event as an internal fault, and consequently issues the trip command. The other case of maloperation includes, but not limited to, a moment when the current transformer saturates due to an external fault. In this paper, a novel approach for DP is proposed, that is based on signal processing methods. In this paper, variational mode decomposition (VMD) and the deep neural network are implemented by using the convolutional neural network (CNN) and bi‐directional long short‐term memory (BiLSTM) models. The VMD decomposes differential current signal (DCS) to intrinsic mode functions with corresponding narrow‐band property frequency spectrums, which provides more detailed information about signal characteristics in different frequency bands. At the next stage, an effective feature for the BiLSTM is extracted by the CNN with the convolutional layers to classify events and proper discrimination. Extensive simulations on a 500 MVA transformer in MATLAB demonstrate the effectiveness of the proposed protection approach to differentiate ICs from internal and external faults with 99.8% accuracy in less than 1/8th of a power cycle.
In this paper, a novel approach for differential protection is proposed, that is based on signal processing methods. To this end, variational mode decomposition and the deep neural network are implemented by using the convolutional neural network and bi‐directional long short‐term memory models.
•Combination of Conditional GAN with Convolutional classifier is proposed for fault detection.•Third Harmonic Angel (THA) of fault current is used as an effective feature.•Little amount of training ...data is used to train CGAN.•High performance of the CGAN in generation of pseudo-real data in large scale.
Low level current and similarity of High Impedance Faults (HIF) in respect of characteristics to other transient events have posed a critical challenge to the protection of distribution systems. In addition, the dependency of previous methods on large amounts of training data increases the simulation error rate, and preparing this amount of data is time-consuming. In this paper, a novel scheme based on conditional generative adversarial network (CGAN) and convolutional neural network (CNN) classifier techniques is proposed, that reduces this dependency and leads to acceptable classification accuracy. In the proposed method, a small amount of data is extracted from the under-study network as the real data. Then, the third harmonic angle of the current is extracted from the real data by an adaptive linear neuron (ADALINE) as an effective feature. The CGAN is performed to produce a large amount of pseudo data. At last, the fault data is separated from other transient network events via the CNN classifier. Five different scenarios are used to evaluate the proposed method on a 13-bus IEEE network. The simulation results show that the Precision and Recall of distinguishing HIFs from other transient events is greater than 98% in all the scenarios. These results verify that the proposed scheme is very accurate despite the low dependency on input training data.
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•A differential protection algorithm based on MRA and BIGRU is proposed.•The proposed method accurately classifies inrush current and the internal faults.•The events are classified in less than ...one-eighth of the power cycle.•The proposed method does not depend on a threshold value, and.•The proposed method is evaluated in different situations of the power transformer.
Power transformer protection performs an essential role in power systems, ensuring a reliable power supply to the customers. One of the main challenges in differential protection of the transformers is to correctly discriminate inrush currents from internal faults and prevent the maloperation of the differential relay. In this regard, a novel differential protection method is proposed, which decomposes the differential current signal to multiple energy levels through the multi-resolution analysis (MRA) and selects the most useful feature to feed to the bidirectional gated recurrent unit (BIGRU) to classify the events. The use of the BIGRU results in the high accuracy and low implementation complexity of the proposed approach. Various simulations carried out on a 70 MVA transformer demonstrate that the proposed approach has an accuracy of 99.70% in discriminating inrush currents from internal faults in less than one-eighth of the power cycle.
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