Correlation between preeclampsia and season or some of its risk factor pregnant women

زمینه و هدف: پره اکلامپسی از عوارض عمده بارداری محسوب می شود و یکی از سه علل اصلی مرگ و میر مادران به شمار می رود. لذا این مطالعه با هدف بررسی رابطه پره اکلامپسی با فصل و عوامل خطر زای آن در زنان 45-15 ساله انجام شد. روش بررسی: نمونه های مورد مطالعه با بررسی پرونده های موجود در بایگانی زایشگاه قدس زاهدان طی سال های 1386-1383 تعداد 2488 زن باردار با تشخیص پره اکلامپسی که واجد شرایط پژوهش بودند (سن 45-15 سال و حاملگی اول الی سوم) انتخاب شدند. 2488 زن باردار نیز به عنوان گروه فاقد پره اکلامپسی (شاهد) انتخاب شدند که از نظر سن و تعداد حاملگی با گروه مبتلا همسان بودند. اطلاعات از طریق پرسشنامه جمع آوری و به کمک آزمون های کای دو تجزیه و تحلیل گردید. یافته ها: نتایج این مطالعه نشان داد ارتباط معنی داری بین پره اکلامپسی و فصل وجود دارد، به طوری که با شروع فصل بهار پره اکلامپسی به تدریج افزایش پیدا کرده و در پاییز به یک افزایش ناگهانی می رسد و در زمستان کاهش ناگهانی پیدا می کند (001/0

Bayesian Analysis of Doubly Inflated Poisson Regression for Correlated Count Data: Application to DMFT Data

Outcome variables in clinical studies sometimes include count data with inflation in two points (usually zero and k (k>0)). Doubly inflated models can be adopted for modeling these types of data. In statistical modeling, the association among subjects due to longitudinal or cluster study designs is considered by random effects models. In this article, we proposed a doubly inflated random effects model using the Bayesian approach for correlated count data with inflation in two values, and compared this model with Bayesian zero-inflated Poisson and Bayesian Poisson models. The parameters’ estimates by these models were obtained by Markov Chain Monte Carlo method using OpenBUGS software. Bayesian models were compared using the deviance information criterion. To this end, we utilized the total number of decayed, missed, and filled teeth of 12-year-old children and also conducted a simulation study.  Results of real data and the simulation study revealed that the proposed model is fitted better than previous models.&nbsp

Machine-Learning Algorithms for Forecast-Informed Reservoir Operation (FIRO) to Reduce Flood Damages

Water is stored in reservoirs for various purposes, including regular distribution, flood control, hydropower generation, and meeting the environmental demands of downstream habitats and ecosystems. However, these objectives are often in conflict with each other and make the operation of reservoirs a complex task, particularly during flood periods. An accurate forecast of reservoir inflows is required to evaluate water releases from a reservoir seeking to provide safe space for capturing high flows without having to resort to hazardous and damaging releases. This study aims to improve the informed decisions for reservoirs management and water prerelease before a flood occurs by means of a method for forecasting reservoirs inflow. The forecasting method applies 1- and 2-month time-lag patterns with several Machine Learning (ML) algorithms, namely Support Vector Machine (SVM), Artificial Neural Network (ANN), Regression Tree (RT), and Genetic Programming (GP). The proposed method is applied to evaluate the performance of the algorithms in forecasting inflows into the Dez, Karkheh, and Gotvand reservoirs located in Iran during the flood of 2019. Results show that RT, with an average error of 0.43% in forecasting the largest reservoirs inflows in 2019, is superior to the other algorithms, with the Dez and Karkheh reservoir inflows forecasts obtained with the 2-month time-lag pattern, and the Gotvand reservoir inflow forecasts obtained with the 1-month time-lag pattern featuring the best forecasting accuracy. The proposed method exhibits accurate inflow forecasting using SVM and RT. The development of accurate flood-forecasting capability is valuable to reservoir operators and decision-makers who must deal with streamflow forecasts in their quest to reduce flood damages

Effect of different levels of sunflower meal and multi-enzyme complex on performance, biochemical parameters and antioxidant status of laying hens

This study was designed to evaluate the effects of different sunflower meal (Helianthus annus; SFM) levels and a multi-enzyme complex (Natuzyme P50) on performance, biochemical parameters and antioxidant status of laying hens. A total of 288 Hy-Line W-36 laying hens (39-wk-old) were divided into six groups with six replicates per group (eight birds per replicate) and fed one of the six experimental diets. A corn-soybean meal-based diet was formulated and used as control diet. The experimental treatments consisted of three levels of SFM (0, 10, and 20%) and two levels of multi-enzyme complex (0 and 250g/ton). The feeding trial lasted 10 weeks. The results showed that the egg production, egg weight and mass, egg specific gravity, shell strength and thickness, Haugh unit, shape index, triglyceride content, plasma glutathione peroxidase (GSH) activity, and malondialdehyde (MDA) were not influenced by dietary treatments; however, the feed consumption, yolk cholesterol, low-density lipoprotein (LDL) and high-density lipoprotein (HDL) cholesterol were significantly affected by feeding SFM compared to the control. In conclusion, the supplementation of SFM up to 20% in diet with multi-enzyme complex in laying hens did not appear to cause any adverse effects on egg production and quality as well on antioxidant status in laying hens.Keywords: Enzymes, laying hen, performance, sunflower meal, yolk cholestero

Domestic violence and its association with domains of reproductive health in women: A systematic review

Background and purpose: Violence is one of the main aspects of gender inequality that is a major barrier to achieving the goals of global reproductive health. It is directly associated with women's access to health care and health outcomes. In a systematic review, we aimed to investigate the articles on the relationship between intimate partner violence and women's reproductive health. Materials and methods: Electronic databases including, Scopus, ProQuest, PubMed, and Google Scholar were searched for articles published in English between 2010 and 2017. Results: After evaluation, 31 articles were selected. The lowest and highest prevalence of violence was associated with physical violence (2.8) and psychological violence (75.9), respectively. Moreover, violence was found to be associated with six domains of reproductive health including, not using contraceptive methods, abortion, genital tract diseases, poor pregnancy outcomes, and not using reproductive health services. Conclusion: Systematic review of studies investigated, showed a strong relationship between domestic violence and major aspects of reproductive health. Therefore, it is necessary to prevent domestic violence in order to promote the health of whole community. © 2018, Mazandaran University of Medical Sciences. All rights reserved

Domestic violence and its association with domains of reproductive health in women: A systematic review

Background and purpose: Violence is one of the main aspects of gender inequality that is a major barrier to achieving the goals of global reproductive health. It is directly associated with women's access to health care and health outcomes. In a systematic review, we aimed to investigate the articles on the relationship between intimate partner violence and women's reproductive health. Materials and methods: Electronic databases including, Scopus, ProQuest, PubMed, and Google Scholar were searched for articles published in English between 2010 and 2017. Results: After evaluation, 31 articles were selected. The lowest and highest prevalence of violence was associated with physical violence (2.8) and psychological violence (75.9), respectively. Moreover, violence was found to be associated with six domains of reproductive health including, not using contraceptive methods, abortion, genital tract diseases, poor pregnancy outcomes, and not using reproductive health services. Conclusion: Systematic review of studies investigated, showed a strong relationship between domestic violence and major aspects of reproductive health. Therefore, it is necessary to prevent domestic violence in order to promote the health of whole community. © 2018, Mazandaran University of Medical Sciences. All rights reserved

Performance of epoxy resin polymer as self-healing cementitious materials agent in mortar

This research investigated the application of epoxy resin polymer as a self-healing strategy for improving the mechanical and durability properties of cement-based mortar. The epoxy resin was added to the concrete mix at various levels (5, 10, 15, and 20% of cement weight), and the effectiveness of healing was evaluated by microstructural analysis, compressive strength, and non-destructive (ultrasonic pulse velocity) tests. Dry and wet-dry conditions were considered for curing, and for generating artificial cracks, specimens at different curing ages (1 and 6 months) were subjected to compressive testing (50 and 80% of specimen’s ultimate compressive strength). The results indicated that the mechanical properties in the specimen prepared by 10% epoxy resin and cured under wet-dry conditions was higher compared to other specimens. The degree of damage and healing efficiency index of this particular mix design were significantly affected by the healing duration and cracking age. An optimized artificial neural network (ANN) combined with a firefly algorithm was developed to estimate these indexes over the self-healing process. Overall, it was concluded that the epoxy resin polymer has high potential as a mechanical properties self-healing agent in cement-based mortar

Gelation Time of Hexamethylenetetramine Polymer Gels Used in Water Shutoff Treatment

Among the methods available to reduce water production, injecting a gelling system composed of a polymer and a crosslinker has been widely used. In this work, a hydrogel was prepared by crosslinking of an aqueous solution containing hexamethylenetetramine (HMTA) as crosslinker, hydrochloric acid (HCl) as an activator, and the co-polymer of 2-acrylamido-2methyl-propanesulfonic-acid sodium salt (AMPS) and acrylamide (PAMPS). In order to indicate the effective factors on the gelation time and also to develop the quadratic mathematical models, central composite design (CCD) was applied. Therefore, the main purpose was to establish functional relationship between the three factors (polymer concentration, HMTA, and hydrochloric acid) and a response (gelation time) by using a statistical technique. In order to determine the optimum value of these factors for maximum gelation time, a simultaneous optimization was also applied. The results of the analysis of variance (ANOVA) of the developed model illustrated that the fitted model was significant in a 99% confidence limit. The results showed that hydrochloric acid was identified as the main factor effecting the gelation time and there was also an interaction between HMTA and hydrochloric acid. Finally, a mechanism for the reaction between PAMPS and HMTA were presented