A mathematical model of dispersed bioparticle-blood flow through the stenosed coronary artery under the pulsatile boundary conditions is proposed. Blood is assumed to be an incompressible non-Newtonian fluid and its flow is considered as turbulence described by the Reynolds-averaged Navier-Stokes equations. Bioparticles are assumed to be spherical shape with the same density as blood, and their translation and rotational motions are governed by Newtonian equations. Impact of particle movement on the blood velocity, the pressure distribution, and the wall shear stress distribution in three different severity degrees of stenosis including 25%, 50%, and 75% are investigated through the numerical simulation using ANSYS 18.2. Increasing degree of stenosis severity results in higher values of the pressure drop and wall shear stresses. The higher level of bioparticle motion directly varies with the pressure drop and wall shear stress. The area of coronary artery with higher density of bioparticles also presents the higher wall shear stress.
This paper aims to present an SIS-SEIQR network model for pandemic influenza. We propose a network algorithm to generate an adaptive social network with dynamic hub nodes to capture the disease transmission in a human community. Effects of visiting probability on the spread of the disease are investigated. The results indicate that high visiting probability increases the transmission rate of the disease.
This research aims to study the effect of the days in week on the return of the stock price index, particularly in the Stock Exchange of Thailand (SET). The daily closing prices of SET50 index from June 2, 2003 to June 2, 2017 are taken into account, i.e., there are totally 3,425 days. The stock returns of the 50 companies are calculated according to the daily historical stock prices of companies. Both descriptive and inferential statistics are employed in data analysis including average, standard deviation, multiple comparisons and multiple regression analysis. Applying ordinary least square method, the linear equation with five dummy variables is formulated for multiple regression analysis. The results show that the means of daily return rate of SET50 index are significantly different. Monday has a negative influence on the return rate of SET50 index whereas Friday has a positive influence at the significance level of 0.05. The return rate of SET50 index on Monday is lowest whilst Friday is highest during the week.
In this paper, we propose an SEIQR-SIS epidemic network model to study pandemic influenza and derive the approximate threshold condition (basis reproductive number) to examine the stability of the model. The numerical simulation of the disease transmission in the adaptive social network with people nodes and hub nodes is presented. The network parameters including visiting probability, hub radius and contact radius are used to investigate their impacts on the disease transmission. Our results show that these network parameters have a significant effect on the disease spread. Keywords—Adaptive network, Stability analysis, SEIQR- SIS epidemic model, Pandemic influenza, Reproductive number
This paper aims to introduce how ambulatory ventilator is effectively designed and economically constructed for the use in ambulance and homecare. The operating principle and system design including gas mixer, microcontroller and safety were proposed. Unlike the general ambulatory ventilator, the microcontroller of the proposed prototype systematically integrates tidal volume, respiratory rate, pressure profile and patient safety. Whenever there is below or over pressure, low oxygen supply or leak of breathing tube, the microcontroller is programmed to notify by alarming and displaying on monitor. The implementation and testing method including the performance, accuracy of data transmission and patient safety have a good agreement with the safety standard of lung ventilator (IEC 60601-2-12). Comparing the means of tidal volume, respiratory rate, and pressure from the developed prototype to the standard at the significance level of 0.05, it was found that the means are indifferent, i.e., the developed prototyping model of ambulatory ventilator satisfied the standard of ventilator. Continuous mandatory ventilation and continuous positive airway pressure were investigated and they were in line with the function testing. Setting 10 trials of each irregular situations, the below or over pressure and low oxygen supply were successfully detected and notified. Therefore, our developed prototyping model of ambulatory ventilator can be considered as an economical alternative for ambulance and homecare, especially in Thailand.
Erythemato-squamous diseases (ESD) are dermatological diseases that significantly impact the quality of life of an increasing number of patients worldwide. This study used a publicly available clinical dataset of 366 patients from the Department of Computer Engineering and Information Science, Bilkent University with 34 predictors contributing to the classification of ESDs. The data was curated to ensure unbiasedness and accuracy before applying principal component analysis and machine learning models to identify crucial factors in classifying the six main types of ESDs. 31 different machine learning models, including Tree, Linear Discriminant, Quadratic Discriminant, Naïve Bayes, SVM, KNN, Ensemble, Neural Network, and Kernel were trained, validated, and the classification accuracy was compared. The model that is the most adequate is the Fine KNN, which has the highest cross-validation classification accuracy at 100%. This model requires only eight predictors: itching, the Koebner phenomenon, follicular papules, fibrosis of the papillary dermis, spongiosis, inflammatory mononuclear infiltrate, bandlike infiltrate, and age.
This study evaluated the efficacy and safety of a topical botanical cream containing a combination of herbs for the treatment of psoriasis, a chronic inflammatory skin disease that can considerably diminish the quality of life of a patient. Although numerous topical therapies are available, the majority rely on potentially dangerous steroid creams or coal tar ointments that require a doctor's prescription. In this setting, safe and effective alternative treatments are required. The purpose of this study was to evaluate the efficacy and safety of a topical botanical cream containing a combination of herbs for the treatment of psoriasis.A randomized controlled trial including 51 patients with plaque psoriasis was done. Patients were administered the topical cream for eight consecutive weeks, with the dosage decided by the afflicted skin area. Patients' quality of life was measured using the Psoriasis Disability Index (PDI) and Dermatology Life Quality Index (DLQI).The patients in the therapy group reported a significant reduction in psoriasis severity, as judged by the PASI, according to the study results. The symptoms began to ease as early as the second week of cream use. In addition, as measured by the PDI and DLQI, the patients' quality of life increased. By the sixth week, the DLQI score reduced from a high impact to a moderate impact, while the PDI improved in all categories.The topical botanical cream was proven to be safe and effective in treating psoriasis, hence improving the quality of life of patients. The herbal mixture is a viable alternative to steroid creams and coal tar ointments, which can be used as a substitute or supplement to other standard treatments for psoriasis. To corroborate the outcomes of this trial and determine the long-term safety and efficacy of the botanical cream, however, additional studies with bigger sample sizes are required. This study gives crucial insights into the possible use of herbal formulations in the treatment of psoriasis and highlights the need for additional research in this area.
The aim of this study is to investigate the potential therapeutic benefits of using cannabis-enriched topical cream containing of delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), either alone (THC:CBD) or in combination with a polyherbal formulation for treating psoriasis. To evaluate the efficacy and safety of both formulations, a crossover, randomized, single-blinded study was conducted on 20 volunteers who were monitored for key indicators such as PASI score, PDI, DLQI, and blood profile. The present study involved two eight-week treatment periods with each formulation, separated by a two-week washout period. The results showed that the group using the cannabis cream comprising of THC:CBD alone experienced a significant reduction in PASI score after four weeks over the course of the 8-week study. Furthermore, the combination of THC:CBD and the polyherbal formulation was found to be more effective in reducing disease severity and improving patient quality of life. No significant adverse reactions were observed, and there was no difference in blood profile before and after treatment. These findings indicate that both topical formulations are safe and effective for treating psoriasis, with the combined formulation showing greater potential than using topical cannabis alone.
The paper aims to present mathematical model and numerical simulation of a granular material flow during a silo discharge process. The material flow in the silo is a form of two-phase flow consisting of particulates and an interstitial fluid. These two phases are soybeans and air. The homogeneous flow is assumed. The effect of the bottom design of the silo on the two- phase flow is investigated. The bottom shape including flat shape and cone shape and the diameter of outlet width including 0.08 m and 0.12 m are chosen for this investigation. The results show that the mathematical model can capture the granular material flow in the silo. The bottom design has significant effect on the velocity, pressure and shear rate in the granular material during the silo discharge process.
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