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Importance of New Use of Concrete in Iraq Analysis of Development And Use of Concrete in Architecture
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Since its invention by the Ancient Romans and later developed during the mid-18th century, the concrete structure and finish, has been considered as the most powerful, practical, economic and constructional material that meets the building’s architectural and aesthetical requirements. By creating unique architectural forms, the pioneer architects used concrete widely to shape up their innovative designs and buildings.

The pre-mixed ultra-high performance concrete which manufactured by Lafarge.

The transparent concrete and cement that allow the light beams to pass through them, introduces remarkable well-lit architectural spaces within the same structural criteria. This product is a recyclable, sustainable, friendly environmental and cost efficient back up.

Due to its characteristics, strength, flexibility, affordability and long term performance, the concert integrated and contributed in modern architecture, urbanism and civil developments. Apparently, most of the 20th Century architects employed high-tech concrete method to deliver Iconic and bespoke architectural monuments world-wide. The interaction between the architectural form and the concrete as a buildable, executable, structural and constructional material has been always the main concern for architects over generations.

The formalism in architecture was first identified by the Art-Nouveau movement during the early 20 century in Europe as well as in Northern America. It formed, utilized and sculptured the concert to meet the use, function, aesthetical and spatial needs of spaces. This wave generated series of most significant, outstanding and impressive buildings in the architectural symbolized record.

This was followed by the Brutalism architecture presented by Alison and Peter Smithson in England and also by Le Corbusier works in Marseille and India. However, Alvar Alto and Louis Khan have participated and established a tremendous use of concrete to erect public interest developments on the same era

The concert as a structural element dominated the Metabolism architecture that represented by the Japanese architects like Kiyonori Kikutake, Kisho Kurokawa, Noboru Kawazoe, Masato Otakaand and Fumihiko Maki. They visualized the city of the future to be viable, evaluable, expandable, flexible structures that evoked the processes of organic growth as it is in nature. Their developments are often called technocratic and described as avant-garde with a rhetorical character. The Metabolist mega structures heavily relied on advanced technology and adaptable plug-in building techniques in using this material.

The research concluded the influences of the concrete as a building material upon the modern and building forms from the outsets. By exploring the history of the material, expanding its characteristics and specifications and later demonstrating the modern architecture movements and architects, this research has achieved its targets to acknowledge the importance of concrete in the current construction market and architectural developments.

 

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Publication Date
Tue Jul 26 2022
Journal Name
Frontiers In Veterinary Science
Berbamine and thymoquinone exert protective effects against immune-mediated liver injury via NF-κB dependent pathway
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Background

Immune-mediated hepatitis is a severe impendence to human health, and no effective treatment is currently available. Therefore, new, safe, low-cost therapies are desperately required. Berbamine (BE), a natural substance obtained primarily from Berberis vulgaris L, is a traditional herbal medicine with several bioactivities, such as antimicrobial and anticancer activities. Thymoquinone (TQ), a phytochemical molecule derived from the Nigella sativa plant's black cumin seeds, has attracted interest owing to itsanti-inflammatory, antioxidant, and anticancer properties.

Aim

This c

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
COMPARATIVE STUDY BETWEEN A NOVEL DETERMINISTIC TEST FOR MERSENNE PRIMES AND THE WELL-KNOWN PRIMALITY TESTS
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In this article, a new deterministic primality test for Mersenne primes is presented. It also includes a comparative study between well-known primality tests in order to identify the best test. Moreover, new modifications are suggested in order to eliminate pseudoprimes. The study covers random primes such as Mersenne primes and Proth primes. Finally, these tests are arranged from the best to the worst according to strength, speed, and effectiveness based on the results obtained through programs prepared and operated by Mathematica, and the results are presented through tables and graphs.

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison Between Classic Local Least Estimatop And Bayesian Methoid For Estimating Semiparametric Logistic Regression Model
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Semi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.

We compare two methods Bayesian and . Then the results were compared using MSe criteria.

A simulation had been used to study the empirical behavior for the Logistic model , with  different sample sizes and variances. The results using represent that the Bayesian method is better than the   at small samples sizes.

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparison between Linear and Non-linear ANN Models for Predicting Water Quality Parameters at Tigris River
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.

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Publication Date
Thu Jun 01 2017
Journal Name
Nuclear Physics A
Alpha-cluster preformation factor within cluster-formation model for odd-A and odd–odd heavy nuclei
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Wrapper and Hybrid Feature Selection Methods Using Metaheuristic Algorithms for English Text Classification: A Systematic Review
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Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

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Publication Date
Thu Aug 04 2022
Journal Name
Contemporary Nurse
ICU nurses’ safety performance related to respect for safety and management commitment: A cross-sectional study
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Polluted Water Sensor Based on Carbon Quantum Dots/Alq3 Using Drop Casting and Spin Coating Techniques
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Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of

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Publication Date
Wed Apr 25 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using Approximation Non-Bayesian Computation with Fuzzy Data to Estimation Inverse Weibull Parameters and Reliability Function
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        In real situations all observations and measurements are not exact numbers but more or less non-exact, also called fuzzy. So, in this paper, we use approximate non-Bayesian computational methods to estimate inverse Weibull parameters and reliability function with fuzzy data. The maximum likelihood and moment estimations are obtained as non-Bayesian estimation. The maximum likelihood estimators have been derived numerically based on two iterative techniques namely “Newton-Raphson” and the “Expectation-Maximization” techniques. In addition, we provide compared numerically through Monte-Carlo simulation study to obtained estimates of the parameters and reliability function i

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