Hypertension Prediction in Primary School Students Using an Ensemble Machine Learning Method

Introduction: The prevalence of hypertension in children is increasing, and this complication is considered the most important risk factor for cardiovascular diseases in older age. Early detection and control of hypertension can prevent its progress and reduce its consequences. Machine learning methods can help predict this complication promptly and reduce cost and time. This study aimed to provide a model based on ensemble machine learning methods to more accurately predict the hypertension of primary school children. Method: This is an applied developmental study that was conducted using the information of 1287 primary school children aged 7-13 years in Kashmar city. After data preprocessing, to achieve a more accurate diagnosis of hypertension in children, the output results of five common machine learning methods in disease diagnosis including decision tree, naive Bayesian, nearest neighbors, artificial neural network, and support vector machine using weighted majority voting method were combined. Results: The results showed that the accuracy, sensitivity, and specificity of the proposed model were 90.31%, 80.65%, and 93.54%, respectively, and compared to similar studies it performed better. Conclusion: The proposed model can better predict and diagnose hypertension in children and improve accuracy and reduce the error rate. This model can be a useful and early tool in the diagnosis of hypertension in children, reducing the consequences and costs of this complication and being a big step in the fight against hypertension

SYNTHESIS AND CHARACTERIZATION OF BIOACTIVE GLASS/FORSTERITE NANOCOMPOSITES FOR BONE AND DENTAL IMPLANTS

In this research, bioactive glass (BG) of the type CaO–P2O5–SiO2 and nanocrystalline forsterite (NF) bioceramic were successfully synthesized via sol–gel processing method. Heat-treatment process was done to obtain phase-pure nanopowders. After characterization of each sample, the nanocomposite samples were prepared by cold pressing method and sintered at 1000°C. The samples were fully characterized by X-ray powder diffraction (XRD), scanning electron microscope (SEM), energy dispersive spectroscopy (EDX), Fourier transform infrared spectroscopy (FTIR) analyses. The average nanocrystallite size was determined using the Debye-Scherrer’s formula 19.6 nm. The bioactivity was examined in vitro with respect to the ability of hydroxyapatite (HAp) layer to form on the surfaces as a result of contact with simulated body fluid (SBF). According to the obtained results, the prepared nanocomposite enhances the fracture toughness of the BG matrix without deteriorating its intrinsic properties as bioactivity

Advancing Multilingual Handwritten Numeral Recognition with Attention-driven Transfer Learning

As deep learning continues to evolve, we have observed huge breakthroughs in the fields of medical imaging, video and frame generation, optical character recognition (OCR), and other domains. In the field of data analysis and document processing, the recognition of handwritten numerals plays a crucial role. This work has led to remarkable changes in OCR, historical handwritten document analysis, and postal automation. In this study, we present a novel framework to overcome this challenge, going beyond digit recognition in only one language. Unlike common methods that focus on a limited set of languages, our method provides a comprehensive solution for recognition of handwritten digit images in 12 different languages. These specific languages are chosen because most of them have fairly distant representations in latent space. We utilize transfer learning, as it reduces the computational cost and maintains the quality of enhanced images and the models’ recognition accuracy. Another strength of our approach is the innovative attention-based module called the MRA module. Our experiments confirm that by applying this module, major progress is made in both image quality and the accuracy of handwritten digit recognition. Notably, we reached high precisions, surpassing nearly 2% improvement in specific languages compared to earlier techniques. In this work, we present a robust and cost-effective approach that handles multilingual handwritten numeral recognition across a wide range of languages. The code and further implementation details are available at https://github.com/CVLab-SHUT/HandWrittenDigitRecognition

Downregulated regulatory T cell function is associated with increased peptic ulcer in Helicobacter pylori-infection

Background: Helicobacter pylori (H. pylori) chronically colonizes gastric/duodenal mucosa and induces gastroduodenal disease such as gastritis and peptic ulcer and induces vigorous innate and specific immune responses; however, the infection is not removed, a state of chronic active gastritis persists for life if untreated. The objective of this study was to determine the number of regulatory T cells (Tregs) in gastric mucosa of patients with gastritis and peptic ulcer and determined the relationship between main virulence factor of H. pylori and Tregs. Methods and materials: A total of 89 patients with gastritis, 63 patients with peptic ulcer and 40 healthy, H. pylori-negative subjects were enrolled in this study. Expression of CD4 and Foxp3 was determined by immunohistochemistry. Antrum biopsy was obtained for detection of H. pylori, bacterial virulence factors and histopathological assessments. TGF-b1, IL-10 and FOXP3 expressions were determined by real-time polymerase chain reaction (qPCR). Results: The numbers of CD4þ and Foxp3þ T cells as well as the expression of IL-10, TGF-b1, FOXP3, INF-g and IL-17A in infected patients were significantly higher than the ones in uninfected patients. Also, the number of CD4þ T cells was independent on the vacuolating cytotoxin A (vacA) and outer inflammatory protein A (oipA), but it was positively correlated with cytotoxin-associated gene A (cagA). Instead, the number of Foxp3þ T cells was dependent on the vacA and oipA, but it was independent on cagA. The number of Foxp3þ T cells and the expression of IL-10, TGF-b1 and FOXP3 in infected patients with gastritis were significantly higher than the ones in infected patients with peptic ulcer. Moreover, the number of CD4þ T cells and the expression of IL-17A and INF-g was the lowest in the gastritis patients, however, increased progressively in the peptic ulcer patients. Additionally, the numbers of CD4þ and Foxp3þ T cells as well as the expression of IL-10, TGF-b1, FOXP3 and INF-g were positively correlated with the degree of H. pylori density and chronic inflammation. Conclusion: Tregs are positively associated with vacA alleles and oipA status of H. pylori and histological grade but negatively associated with peptic ulcer disease

Biological control of bloom algae in the southern of Caspian Sea

In recent years the incidence of algal blooms caused by Nodularia to become one of the serious problems and is threated life of aquatic organisms in the southern Caspian Sea. Nodularia is a Blue-green algae (cyanobacteria group) and due to production of nodularin toxin is importance. In this study, the first, three species of Pseudomonas including aeruginosa, putida and fluorescens were isolated from Tajan river estuary and identified using biochemical tests and compared to standard species. The trend of Nodularia spumigena biomass (log 5) and pseudomonas species (log 7 and 8) were examined in 30 treatments for 10 days in aquarium scale. Parameters such as chlorophyll a, dissolved oxygen, phosphate and nitrate were tested at different time the same time. The results showed that the decline trend of nodularia in aeruginosa and mixed species treatments were better than other treatments and log 8 of bacterium was also more inhibitory effect than to log 7. Similar results were observed in double layer on agar medium and latter treatments had algaecide effect on nodularia. However, putida and fluorescens treatments had algaestatic properties. Concentration of chlorophyll a, dissolved oxygen and nitrate in all treatments, especially aeruginosa and mixed bacteria have been often decreased (p<0.05). Changes of latter factors in control treatment have been relatively consistent. Although the phosphate changes at different time of relative decline, but nevertheless significant differences were observed. The parameters examined in this study were in direct contact with the algae population and decrease or increase of these factors cause significant change in algae biomass. The conclusion showed that different strains of pseudomonas are able to reduce the population of algae N. spumigena in aquarium scale and the results observed in combination treatment were better than other treatments. The challenge examination of pseudomonas and nodularia in mesocosm scale, evaluation of bacterial metabolites, and also quality and quantity analysis of chemical and biological factors involved in the process is recommended and with achieve reasonable results can be made from this indicator bacteria during algal bloom in the larger ecosystem

A study on water quality and physio- chemicals parameters in surface water, underground water and wastewater of Mangol dam basin (Mazandaran province)

This study was conducted to determine water quality of surface water (7 stations), ground water (5 stations) and wastewater (4 stations) at Haraz River during instruction of Mangol Dam in 2009-2010. This study is to follow physico-chemical fluctuation of waters and compared the data obtained with previous studies and standard levels. Results of current study showed that annual mean with standard error of temperature, DO, BOD_5, COD, HCO^3-, CO_3^2-, TA, Ca^2+, Mg^2+, TH, TSS, TDS, Cl^-, PO_4^3-, NH^4+, NO2- and NO3- were observed 12.7 (±0.61) centigrade, 10.13 (±0.12), 2.1 (±0.1), 7.71 (±0.99), 28.1 (±6.1), 14.34 (±1.64), 36.30 (±2.33), 64.66 (±2.34), 28.84 (±1.52), 271.62 (±8.41), 0.37 (±0.03), 0.30 (±0.02), 28.02 (±1.96), 0.06 (±0.01), 0.010 (±0.001) and 0.94 (±0.03) mg/l, pH was 8.00 (±0.02) and EC 0.50 (±0.02) ms/cm in surface water. The annual mean with standard error of temperature, HCO^3-, CO_3^2-, TA, Ca^2+, Mg^2+, TH, TSS, TDS, Cl^-, PO4^3-, NH^4+, NO^2- and NO^3- were observed 21.62 (±1.03) centigrade, 54 (±5), 11 (±5), 57 (±5), 208.6 (±42.5), 109 (±23), 1088 (±165), 0.065 (±0.017), 0.97 (±0.11), 317.8 (±76.2), 0.25 (±0.06), 0.06 (±0.01), 0.0007 (±0.0001) and 0.78 (±0.05) mg/l, pH was 7.37 (±0.07) and EC 1.98 (±0.23) ms/cm in underground water. In addition, the annual mean with standard error of temperatute, DO, BOD5, COD, TSS, TDS, and NO3- were observed 12.7 (±0.61) centigrade, 13.59 (±0.87), 9.80 (±0.12), 2.22 (±0.18), 7.54 (±1.02), 0.50 (±0.03), 0.320 (±0.008) and 0.990 (±0.016) mg/l, pH was 7.95 (±0.02) and EC 0.64 (±0.01) ms/cm in wastewater. Quality of surface water of Haraz River and its branches were almost contained suitable for usual applications, but sometimes the quality of surface water based on BOD5 need to more attention for man uses (such as supply of drinking water). In addition, the quality of surface water was relatively suitable for aquatic based on the aquatic standard levels. Results also showed that water quality index (WQI) was declined from upstream to downstream and some parameters were not in standard ranges. The quality of surface water classified in group II at all stations based on water classification rules which it shows serious water quality changes due to environmental destroyed and domestic, agriculture sewage pollutions. Groundwater were affected by different springs at middle and downstream which they caused change physico-chemical characteristics and water quality. Wastewater was classified from good to moderate based on BOD5. The quality of wastewater was declined at downstream with decreasing DO and pH and increasing BOD5 and pollutants

Development of Private-Public Participation in Iranian Water Resources to Boost the Tourism Industry

Nowadays, tourism is one of the fastest growing industries in the world. It plays a prominent role in countries’ economies since not only it directly contributes to the national income, but it also indirectly benefits adjacent industries through spillovers. Tourism has been the primary source of income for many emerging countries. Unfortunately, Iran has not been taking advantage of this industry since 1979 due to its reliance on revenues from the oil industry. However, due to rapidly declining oil revenues in the recent past, Iran’s economic cycle has been interrupted, resulting in a recession. During a recession, a significant portion of the government’s projected resources for keeping the country up and running will not be realized. In such situations, Public-Private Partnership (PPP) could boost the economy by expanding the adjacent businesses. In this paper, we demonstrate a PPP plan which leverages water resources and facilities to boost the tourism industry in Iran. In particular, we study in detail the partnership evolution in Iran, and propose appropriate PPP implementation mechanisms by defining autonomous projects. We show that our proposed approach could boost Iran’s economy. As a byproduct, it could also enhance the outlook of Iran’s tourism industry

Manganese–methionine chelate improves antioxidant activity, immune system and egg manganese enrichment in the aged laying hens

Abstract Background It has been reported that supplementation of manganese (Mn) could alleviate the negative effects of age on egg quality in laying hens. However, limited information is available on compensatory ways in order to reduce the adverse effects of hen age on health and Mn deposition in the body. Objectives The objectives were to investigate the effect of organic and inorganic sources of Mn on antioxidant activity, immune system, liver enzymes, shell quality and Mn deposition in the tissues of older laying hens. Methods A total of 250, 80‐week‐old Leghorn laying hens (w36) were allocated into five treatment groups with five replications in a completely randomised design. Treatments were control (without Mn supplementation), 100% Mn sulphate, 75% Mn sulphate + 25% organic Mn chelate, 50% Mn sulphate + 50% organic Mn chelate and 25% Mn sulphate + 75% organic Mn chelate. Results The groups fed 50 and 75% organic Mn chelate exhibited the lowest feed conversion ratio, as well as the maximum laying percentage, and egg weight and mass. Except to those fed 75% Mn sulphate, the hens received Mn supplements either as organic or inorganic, had higher immunoglobulin G and M compared with the control (p < 0.05). A significant elevation in the values of superoxide dismutase was observed in the hens receiving 50 and 75% organic Mn chelate when compared with the other treatments. The ALP activity decreased with increasing organic Mn chelate. Mn supplementation, either as organic or inorganic, increased Mn deposition in bone, egg yolk and shell, serum and liver. Conclusion Dietary supplementation with 50–75% Mn–methionine has the potential to replace Mn‐sulphate in laying hens’ diet for improving eggshell quality, Mn deposition in the eggshell, antioxidant capacity and immune response, as well as improving laying performance, egg weight and feed conversion ratio

Q-learning based control for energy management of series-parallel hybrid vehicles with balanced fuel consumption and battery life

The present study investigates an energy management strategy based on reinforcement learning for series-parallel hybrid vehicles. Hybrid electric vehicles allow using more advanced power management policies because of their complexity of power management. Towards this feature, a Q-Learning algorithm is proposed to design an energy management strategy. Compared to previous studies, an online reward function is defined to optimize fuel consumption and battery life cycle. Moreover, in the provided method, prior knowledge of the cycle and exact modeling of the vehicle are not required. The introduced strategy is simulated for four driving cycles in MATLAB software linked with ADVISOR. The simulation results show that in the HWFET cycle, the fuel consumption decreases by 1.25 %, and battery life increases by 65% compared to the rule-based method implemented in ADVISOR. Also, the results for the other driving cycles confirm the self-improvement property. In addition, it has been depicted that in the case of change in the driving cycle, the method performance has been maintained and gained better performance than the rule-based controller

An efficient method for a class of integro-differential equations with a weakly singular kernel

In this work, a class of volterra integro-differential equation with a weakly singular kernel is discussed. The shifted Legendre Tau method is introduced for finding the unknown function. The proposed method is based on expanding the approximate solution as the elements of a shifted Legendre polynomials. We reduce the problem to a set of algebraic equations by using operational matrices. Also the convergence analysis and error estimation have been discussed and approved with the exact solution. Finally, several numerical examples are given to demonstrate the high accuracy of the method.Publisher's Versio