The cyanobacterial neurotoxinβ-N-methylamino-L-alanine (BMAA) is considered to be an “excitotoxin,” and its suggested mechanism of action is killing neurons. Long-term exposure to L-BMAA is believed to lead to neurodegenerative diseases including Parkinson’s and Alzheimer’s diseases and amyotrophic lateral sclerosis (Lou Gehrig’s disease). Objectives of this study were to determine the presumptive median lethal dose (LD₅₀), the Lowest-Observed-Adverse-Effect Level (LOAEL), and histopathologic lesions caused by the naturally occurring BMAA isomer, L-BMAA, in mice. Seventy NIH Swiss Outbred mice (35 male and 35 female) were used. Treatment group mice

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Theoretical trends have appeared Which posed the concept of biological structures in contemporary architecture concept, Spread through the emergence of architectural production that reflect and indicate the nature of the construction structures based on the ideas and principles of biological structures in biological science: Despite the emergence of many architectural proposals that tried to explain the concept in the field of architecture, but it is not dealt with in depth and not given a comprehensive definition: So there was need to search for the concept and its beginning in the biological field as a general framework down to the field of architecture for the purpose of reducing the limits of their search framework T

The topic of context is one of the important topics, which was mentioned as a concept in several fields and different fields, and there were many points of view that defined that concept.
He specified the title of the research (design contexts in the design of the interior space), as the research sought to identify the concept of context in the interior design of the spaces of sewing workshops. The research was divided into four chapters:
The first chapter, which consists of the methodological framework, the problem of research and the need for it, the importance of research, the goal and limits of research for sewing workshops for vocational schools from (2020-2021).
The second chapter: consists of previous studies and the theo

A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

The purchase of a home and access to housing is one of the most important requirements for the life of the individual and the stability of living and the development of the prices of houses in general and in Baghdad in particular affected by several factors, including the basic area of the house, the age of the house, the neighborhood in which the housing is available and the basic services, Where the statistical model SSM model was used to model house prices over a period of time from 2000 to 2018 and forecast until 2025 The research is concerned with enhancing the importance of this model and describing it as a standard and important compared to the models used in the analysis of time series after obtaining the

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat