This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6^th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time

Semiconductor-based photocatalytic processes are widely applied as ecofriendly technology for degrading organic pollutants. Establishing photocatalytic heterojunctions with Z-type photocarriers transfer pathways is projected to be a superb strategy to enhance photocatalytic behavior. In this paper, novel and stable (0D/2D) heterojunctions of CoS-embedded boron-doped g-C3N4 (CoS/BCN) with a high rate of charges transfer/separation were assembled for degradation of malachite green dye (MG). The CoS/BCN photocatalyst achieves a photodegradation efficiency of 96.9 % within 1 h of LED illumination, which is 2.5 and 1.4-fold enhancement compared with bare g-C3N4 and BCN, respectively. Besides, the results of species-trapping trials exhibited that

Type 2 diabetes mellitus (T2DM) is a chronic disorder that is a serious health concern all over the globe, it is linked to Interleukin-10 (IL-10) single nucleotide polymorphisms (SNPs) at the promoter region. On the other hand, diabetes influences the cellular and humoral immunity predisposing the patient to a variety of opportunistic parasites one of them is Toxoplasma gondii (T. gondii), which may infect any nucleated cell, including pancreatic cells. The purpose of this research was to explore the association of IL-10 genetic polymorphisms with T2DM and latent toxoplasmosis among Iraqi patients with T2DM. Fifty-five and fifty-eight venous blood samples were taken from T2DM patients and age-matched non-diabetic person

The importance of this topic may not be overlooked by many of the specialists, because it is one the sciences of the Arabic language, but it is an important method in the field of influencing the recipient and his aesthetic ability to create influential images as well.
The talking about Semantic (Badi'iyah)is as old as the Arabic age, so it may be talking about it not the new thing because the people who specialized have preceded us and exhausted all the talk .

Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

True random number generators are essential components for communications to be conconfidentially secured. In this paper a new method is proposed to generate random sequences of numbers based on the difference of the arrival times of photons detected in a coincidence window between two single-photon counting modules

The present paper describes a static model of malware detection and employs a tri-class prevention policy that operates on the EMBER 2024 Win64 partition. A LightGBM classifier trained on 1,040,000 samples and 804 static PE features achieves AUC-ROC = 0.9979, precision = 98.7%, recall = 97.4%, and F1 = 0.9805 on the temporally-split 240,000-sample test set. An innovative Tri-class Threshold Scheme (BLOCK/SUSPICIOUS/ALLOW) obtained by constrained F2-score optimisation on a separate validation set obtains 97.9% malware detection with 98.1% benign pass rate. Efficient model scoring is verified by mean per-sample model inference latency of 2.30 ms (P99: 2.70 ms) measured on pre-extracted EMBER features, future work is characterized by a complet