Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of the study is the generated data sets obtained on the basis of theoretical stress relaxation curves. Tables of initial data for training models for all samples are presented, a statistical analysis of the characteristics of the initial data sets is carried out. The total number of numerical experiments for all samples was 346020 variations. When developing the models, CatBoost artificial intelligence methods were used, regularization methods (Weight Decay, Decoupled Weight Decay Regularization, Augmentation) were used to improve the accuracy of the model, and the Z-Score method was used to normalize the data. As a result of the study, intelligent models were developed to determine the rheological parameters of polymers included in the generalized non-linear Maxwell-Gurevich equation (initial relaxation viscosity, velocity modulus) using generated data sets for the EDT-10 epoxy binder as an example. Based on the results of testing the models, the quality of the models was assessed, graphs of forecasts for trainees and test samples, graphs of forecast errors were plotted. Intelligent models are based on the CatBoost algorithm and implemented in the Jupyter Notebook environment in Python. The constructed models have passed the quality assessment according to the following metrics: MAE, MSE, RMSE, MAPE. The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. Model performance estimates obtained during testing are valid.
Staphylococcus aureus and Pseudomonas aeruginosa are the major globally distributed pathogens, which causes chronic and recalcitrant infections due to their capacity to produce biofilms in large part. Biofilm production represents a survival strategy in these species, allowing them to endure environmental stress by altering their gene expression to match their own survival needs. In this study, we co-cultured different clinical isolates of S. aureus and P. aeruginosa as mono- and mixed-species biofilms in a full-strength Brain Heart Infusion Broth (BHI) and in a 1000-fold diluted Brain Heart Infusion Broth (BHI/1000) using Microtiter plate assay and determination of colony-forming units. Furthermore, the effect of starvation stress on the e
... Show MoreThe present study analyzes the effect of couple stress fluid (CSF) with the activity of connected inclined magnetic field (IMF) of a non-uniform channel (NUC) through a porous medium (PM), taking into account the sliding speed effect on channel walls and the effect of nonlinear particle size, applying long wavelength and low Reynolds count estimates. The mathematical expressions of axial velocity, stream function, mechanical effect and increase in pressure have been analytically determined. The effect of the physical parameter is included in the present model in the computational results. The results of this algorithm have been presented in chart form by applying the mathematical program.
The Coronavirus Disease 2019 (COVID-19) pandemic has caused an unprecedented disruption in medical education and healthcare systems worldwide. The disease can cause life-threatening conditions and it presents challenges for medical education, as instructors must deliver lectures safely, while ensuring the integrity and continuity of the medical education process. It is therefore important to assess the usability of online learning methods, and to determine their feasibility and adequacy for medical students. We aimed to provide an overview of the situation experienced by medical students during the COVID-19 pandemic, and to determine the knowledge, attitudes, and practices of medical students regarding electronic medical education.
... Show MoreTraumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
... Show MoreThe wastewater arising from pulp and paper mills is highly polluted and has to be treated before discharged into rivers. Coagulation-flocculation process using natural polymers has grown rapidly in wastewater treatment. In this work, the performance of alum and Polyaluminum Chloride (PACl) when used alone and when coupled with Fenugreek mucilage on the treatment of pulp and paper mill wastewater were studied. The experiments were carried out in jar tests with alum, PACl and Fenugreek mucilage dosages range of 50-2000 mg/L, rapid mixing at 200 rpm for 2 min, followed by slow mixing at 40 rpm for 15 min and settling time of 30 min. The effectiveness of Fenugreek mucilage was measured by the reduction of turbidity and Chemical Oxygen Demand
... Show MoreEducation around the world has been negatively affected by the new coronavirus disease (COVID-19) pandemic. Many institutions had to transition to distance learning in compliance with the enforced safety measures. Distance learning might work well for settings with stable internet connections, professional technical teams, and basic implementation of technology in education. In contrast, distance learning faces serious challenges in less fortunate settings with inferior infrastructure. This report aims to shed light on the immediate action steps taken at a leading pharmacy school in Iraq to accommodate for the enforced changes in pharmacy education. The University of Baghdad College of Pharmacy went from less than minimal technology impl
... Show MoreObjective: To assess knowledge and skills level regarding oxygen administration methods at p
ediatric teaching hospitals in Mosul City.
Methodology: A descriptive study was applied at pediatric teaching hospitals (Al-Kansaa, and Ibn Al-Atheer) in Mosul City from 8 of October / 2018 till 29 of May / 2019. The selection of the sample was non- probability (Purposive). This sample involved of (52) nurses. The questionnaire was constructed which consists of three parts and provided for nurses. The questionnaire validity was carried out through a panel of experts. To evaluate statistically the reliability of instruments, the pilot study was applied through period from 20– till –31 of January / 2019. Non-randomly (6) nurses from Ibn S
The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.