The excessive and rapid urban growth witnessed by most cities in the world can be a cause of diseases and epidemics, especially those problems related to population, which include problems of transportation and increase in density in the centers, in addition to the lack of interest in planning and designing those cities to take into account the health aspect of the city and obtain The health well-being of the population, and each of these problems has negative effects on health in general and on human health in particular through its prevalence. Therefore, many concepts that serve as a tool for achieving public health and the physical health of the population have emerged, including the concept of city health, which is defined as cities

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

In This research a Spectroscopic complement and Thermodynamic properties for molecule PO2 were studied . That included a calculation of potential energy . From the curve of total energy for molecule at equilibrium distance , for bond (P-O), the degenerated of bond energy was (4.332eV) instate of the vibration modes of ( PO2 ) molecule and frequency that was found active in IR spectra because variable inpolarization and dipole moment for molecule. Also we calculate some thermodynamic parameters of ( PO2 ) such as heat of formation , enthalpy , heat Of capacity , entropy and gibb's free energy Were ( -54.16 kcal/mol , 2366.45 kcal/mol , 10.06 kcal /k/mol , 59.52 k

The main objective of this study was to evaluate the adsorptionefficiency of two adsorbent materials, Iraqi chicken eggshells (ESh)and activated carbon (AC) derived from ESh powder for theremoval of a cationic dye (Janus green B; JGD) from aqueoussolution. Activated carbon was synthesised from ESh usinga simple chemical activation method using phosphoric acid asthe activating agent. The physicochemical properties of the adsor-bents were characterised by the Brunauer–Emmett–Teller (BET)method, FT-IR spectroscopy, scanning electron microscopy(SEM), energy-dispersive X-ray spectroscopy (EDS), inductivelycoupled plasma optical emission spectroscopy (ICP-OES), andpoint of zero charge (pHpzc). The results of BET analysis confirmedthat AC has

The best optimum temperature for the isolate was 30○C while the pH for the maximum mineral removal was 6. The best primary mineral removal was 100mg/L, while the maximum removal for all minerals was obtained after 8 hrs, and the maximum removal efficiency was obtained after 24 hrs. The results have proved that the best aeration for maximum removal was obtained at rotation speed of 150 rpm/ minute. Inoculums of 5ml/ 100ml which contained 106 cell/ ml showed maximum removal for the isolate.

The isomerization of n-hexane on platinum loaded acidic zeolite was studied at atmospheric pressure, H2/nC6 molar ratios of 1-4 and temperature range of 240-270ºC. The measured kinetic data were fitted to an equation based on the bifunctional mechanism and by using independently obtained dehydrogenation and adsorption data. The activation energies of protonation (ΔHpro) and the elementary isomerization step (Eact,iso) and as well as the corresponding preexponential factor were simultaneously determined. The observed values of both ΔHpro and Eact,iso are in agreement with the results of quantum-chemical calculations.

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima