Efficient filtration system for paraffin-catalyst slurry separation

The filtration efficiency for separating liquid paraffin (or water) from a slurry consisting of 25 weight% spherical alumina in a Slurry Bubble Column Reactor (SBCR) comprised of a cylindrical tube of 10 cm diameter and 150 cm length was studied. Various differential pressures (ΔP) were applied to two separate tubular sintered metal stainless steel filter elements with nominal pore size of 4 and 16μm. The experimental results disclosed that the rate of filtrations increased on applying higher differential pressure to the filter element. Albeit this phenomenon is limited to moderate ΔPs and for ΔP more than 1 bar is neither harmful nor helpful. The highest filtration rates at ΔPs higher than 1 bar were 170 and 248 ml/minute for 4 and 16μm respectively. Using water as the liquid in slurry the rate of filtration enhanced to 4 folds, and this issue reveals impact of viscosity on filtration efficiency clearly. In all situations, the total amount of particles present in the filtrate part never exceeded a few parts per million (ppm). The statistical analysis of the SEM image of the filtrate indicated that by applying higher pressure difference to the filter element the frequency percent of larger particle size increases. The operation of filter cake removing was performed with back flashing of 300 ml of clean liquid with pressures of 3-5 bar of N2 gas

Neurological Manifestations of an Old Disease: A Case Report

How to Cite This Article: Islami Z, Ataee Nakhaei MH. Neurological Manifestations of An Old Disease: A Case Report. Iran J Child Neurol. 2013 Summer; 7(3): 55-57. ObjectiveNeurological manifestations of neonatal disorders have various causes, among them neonatal tetanus, albeit rare, is a potentially fatal and preventable disease, which is seen in underdeveloped and developing countries. Although thedisease has been eradicated from I.R. Iran, pregnant women immigrating to Iran from neighboring countries, especially from eastern border, may carry a risk of neonatal tetanus to the child due to inadequate tetanus immunization and inappropriate post-delivery care. It is then important to maintain a high index of suspicion for early diagnosis and prompt treatment, when infants present with poor feeding and abnormal behavior.Case presentation Here, we report the clinical course of a newborn with neonatal tetanus, who was admitted with complaints of poor feeding and muscle rigidity, more than a decade after eradication of the disorder. References1. WHO. Immunization, Vaccines and Biologicals. Availablefrom: http://www.who.int/immunization/topics/tetanus/en/; 2008 [Access 25.10.2011].2. Lum SH, Chew MF. Neonatal Tetanus: A Study of Five Cases in Sandakan, Sabah. Med J Malaysia 2009;64(1):80-2.3. Ilic M, Pejcic L, Tiodorovic B, Hasani B, Stankovic S, Milojevic D, et al. Neonatal tetanus – report of a case. Turk J pediatr 2010;52:404-8.4. Chang SC, Wang CL. Neonatal tetanus after home delivery:report of one case. Pediatr Neonatol 2010;51(3):182-5.5. Cook TM, Protheroe RT, Handel JM. Tetanus: a review ofthe literature. Br J Anaesth 2001;87(3):477-87.6. Richard F. Edlich, MD, PhD, Lisa G. Hill, Chandra A.Mahler, et al. Management and Prevention of Tetanus.Long Term Eff Med Implants 2003;13(3)139–54.7. Ministry of Health and Medical Education. Pediatricimmunization. Available from: http://behdasht.gov.ir/index.aspx?siteid=1&pageid=24979&newsvie=11776&pro=nobak;2011 [Access 28.10.2011].8. S. Beheshti MD, A. Khajehdehi MD, G-R. Rezaian MD,P. Khajehdehi MD. CURRENT STATUS OF TETANUS IN IRAN. Arch Iranian Med 2002;5(4):216-18.9. World Health Organization. WHO-Recommended standards for surveillance of selected vaccinepreventable diseases. Available from: http://www.who.int/vaccines-documents/DocsPDF06/843.pdfdate; 2003[Access 25.10.2011].10. World Health Organization. Immunization surveillance,assessment and monitoring. Available from: http://www.who.int/immunization _ monitoring/ diseases/ MNTE_initiative/en/index.html; 2011 [Access 25.10.2011].

Evaluation of the correlation between serum lipid characteristics of obese subjects and ADIPOQ gene rs266729 polymorphism in Chaharmahal and Bakhtiari Province of Iran

Obesity is a multifactorial disorder that is influenced by various factors such as behavior, diet, environment, metabolic and genetic. This disease is the result of an imbalance between energy absorption and expenditure. Mutations in genes that are responsible for appetite control and metabolism are considered as the genetic component of obesity. Adiponectin protein is one of the most effective adipokines in regulating the body's energy homeostasis and fat storage, which is expressed by the ADIPOQ gene and secreted from white adipose tissue. The concentration of this protein in the blood decreases in obesity. In this study, the relationship between rs266729 polymorphism in the ADIPOQ gene with the level of biochemical parameters such as total cholesterol and triglyceride and HDL and LDL in the blood of obese people in Borujen (a city in Iran) was investigated. This study was performed on 100 people who referred to the Tamin Ejtemaee clinic due to obesity problems in Borujen. In this study, the ARMS-PCR method was used to determine the genotype of individuals. Based on the results of this study, no significant relationship was found between biochemical parameters including total cholesterol, triglyceride, and LDL with rs266729 polymorphism genotypes in ADIPOQ gene in obese subjects. We concluded that rs266729 polymorphism cannot be useful as an index parameter for predispose genotype for imbalance in total cholesterol, triglyceride, and LDL levels in a person

To Reduce the Effects of Experimental Aflatoxicosis in Broiler Chicks Using Specific Egg Yolk Immunoglobulin (IgY)

Background: This experiment was conducted to evaluate the effects of the specific egg yolk immunoglobulin (IgY) on reducing the defects of experimental aflatoxicosis in broilers.Materials and Methods: In a completely randomized design, a total of 128 Ross 308 broiler chicks were used in 4 treatments, 4 replicates and 8 observations (chicks) for 42 days.  Treatments were: 1) control; 2) diet containing 1 ppm aflatoxin B1; 3) diet contaminated with 1 ppm aflatoxin B1 + 0.75 % of egg yolk containing IgY; 4) diet contaminated with 1 ppm aflatoxin B1 + 1.5 % of egg yolk containing IgY.Results: The results showed that the use of aflatoxin containing diet significantly increased the feed conversion ratio, serum cholesterol concentration, serum gamma-glutamyl transferase (GGT), and aspartate aminotransferase (AST). Also, experimental aflatoxicosis resulted in reduced feed intake, weight gain, serum total protein and albumin concentrations (p<0.05); as well as the liver histopathologic lesions. IgY containing egg yolk (0.75% and 1.5%) added to the contaminated ration improved feed intake, weight gain and feed conversion ratio compared to treatment 2 (p<0.05). Compared to treatment 2, serum cholesterol concentration decreased while total protein concentration increased in treatments 3 and 4 (p<0.05). Liver tissue was approximately normal with mild effects on hepatocytes and mild cytoplasmic changes in chicks receiving treatments 3 and 4. Conclusion: It can be concluded that specific IgY is effective in reducing the defects of experimental aflatoxicosis as well as improving performance in broilers.

The Effect Of High-Intensity Exercise Training On Serum Calcium Of Female Combat Athletes

Purpose: Cell homeostasis is an essential factor in maintaining cellular health and intracellular mechanisms, which can also be associated with inflammatory factors and increased stress for muscle cell health. Calcium is also a necessary factor in cell health and is to establish homeostasis in the body. This study aimed to investigate the effect of high-intensity training on serum calcium levels in combat women. Method: For this purpose, 18 women karateka in the age range of 17 to 23 years were randomly divided into 2 groups: control (n=7) and exercise ((n=11). The exercise group performed proper exercises to improve karate and aerobic techniques for 6 weeks in the intensities of more than 80% of the maximum heart rate reserve.   Physiological   indices   and   blood   samples were measured 24 hours before and 48 hours after the training protocol. To measure calcium cell biomarker, the Pars Azmoon calcium kit was used. Research data were analysed by covariance test at the significant level (P≤0.05) using SPSS software version 25. Results: After six weeks of high-intensity training, there was a significant difference in serum calcium levels in the exercise group compared to the control group (P = 0.002). Also, the results within the group showed a significant increase in serum calcium (P = 0.016) in the exercise group compared to baseline conditions. Conclusions: High intensity training seems to increase serum calcium in female athletes, and this can lead to precursors to cellular disorders, muscle damage and increase inflammatory factors and ultimately decrease the performance of female athletes. However, more research is essential in this regard

Outsourcing or Insourcing of Transportation System Evaluation Using Intelligent Agents Approach

Nowadays, outsourcing is viewed as a trade strategy and organizations tend to adopt new strategies to achieve competitive advantages in the current world of business. focusing on main copmpetencies, and transferring most of activities to outside resources of organization( outsourcing) is one such strategy is. In this paper, we aim to decide on decision maker agent of transportation system, by applying intelligent agent technology and using learning model which is modeled as a reinforcement learning problem. A Q-learning algorithm is proposed to solve the RL model. Results show that the proposed model given its ability to communicate with environment, adaptability with environment and correcting itself based on learnt data ,the prposed model can be applied as a better and quicker learning model in comparison with other ways of solving of decision making problems

Enhancing wind direction prediction of South Africa wind energy hotspots with Bayesian mixture modeling

Wind energy production depends not only on wind speed but also on wind direction. Thus, predicting and estimating the wind direction for sites accurately will enhance measuring the wind energy potential. The uncertain nature of wind direction can be presented through probability distributions and Bayesian analysis can improve the modeling of the wind direction using the contribution of the prior knowledge to update the empirical shreds of evidence. This must align with the nature of the empirical evidence as to whether the data are skew or multimodal or not. So far mixtures of von Mises within the directional statistics domain, are used for modeling wind direction to capture the multimodality nature present in the data. In this paper, due to the skewed and multimodal patterns of wind direction on diferent sites of the locations understudy, a mixture of multimodal skewed von Mises is proposed for wind direction. Furthermore, a Bayesian analysis is presented to take into account the uncertainty inherent in the proposed wind direction model. A simulation study is conducted to evaluate the performance of the proposed Bayesian model. This proposed model is ftted to datasets of wind direction of Marion island and two wind farms in South Africa and show the superiority of the approach. The posterior predictive distribution is applied to forecast the wind direction on a wind farm. It is concluded that the proposed model ofers an accurate prediction by means of credible intervals. The mean wind direction of Marion island in 2017 obtained from 1079 observations was 5.0242 (in radian) while using our proposed method the predicted mean wind direction and its corresponding 95% credible interval based on 100 generated samples from the posterior predictive distribution are obtained 5.0171 and (4.7442, 5.2900). Therefore, our results open a new approach for accurate prediction of wind direction implementing a Bayesian approach via mixture of skew circular distributions.https://www.nature.com/srepStatistic

Comparative Evaluation of Deep Learning Techniques in Streamflow Monthly Prediction of the Zarrine River Basin

Predicting monthly streamflow is essential for hydrological analysis and water resource management. Recent advancements in deep learning, particularly long short-term memory (LSTM) and recurrent neural networks (RNN), exhibit extraordinary efficacy in streamflow forecasting. This study employs RNN and LSTM to construct data-driven streamflow forecasting models. Sensitivity analysis, utilizing the analysis of variance (ANOVA) method, also is crucial for model refinement and identification of critical variables. This study covers monthly streamflow data from 1979 to 2014, employing five distinct model structures to ascertain the most optimal configuration. Application of the models to the Zarrine River basin in northwest Iran, a major sub-basin of Lake Urmia, demonstrates the superior accuracy of the RNN algorithm over LSTM. At the outlet of the basin, quantitative evaluations demonstrate that the RNN model outperforms the LSTM model across all model structures. The S3 model, characterized by its inclusion of all input variable values and a four-month delay, exhibits notably exceptional performance in this aspect. The accuracy measures applicable in this particular context were RMSE (22.8), R2 (0.84), and NSE (0.8). This study highlights the Zarrine River’s substantial impact on variations in Lake Urmia’s water level. Furthermore, the ANOVA method demonstrates exceptional performance in discerning the relevance of input factors. ANOVA underscores the key role of station streamflow, upstream station streamflow, and maximum temperature in influencing the model’s output. Notably, the RNN model, surpassing LSTM and traditional artificial neural network (ANN) models, excels in accurately mimicking rainfall–runoff processes. This emphasizes the potential of RNN networks to filter redundant information, distinguishing them as valuable tools in monthly streamflow forecasting

Coming together of Bayesian inference and skew spherical data

This paper presents Bayesian directional data modeling via the skew-rotationally-symmetric Fisher-von Mises-Langevin (FvML) distribution. The prior distributions for the parameters are a pivotal building block in Bayesian analysis, therefore, the impact of the proposed priors will be quantified using the Wasserstein Impact Measure (WIM) to guide the practitioner in the implementation process. For the computation of the posterior, modifications of Gibbs and slice samplings are applied for generating samples. We demonstrate the applicability of our contribution via synthetic and real data analyses. Our investigation paves the way for Bayesian analysis of skew circular and spherical data.The Visiting Professor programme, University of Pretoria and the National Research Foundation (NRF) of South Africa, SARChI Research Chair and DSINRF Centre of Excellence in Mathematical and Statistical Sciences (CoE-MaSS), South Africa.https://www.frontiersin.org/journals/big-datadm2022Statistic