University of Baghdad
  • Baghdad, Baghdad, Iraq
Recent publications
Any solid, unprotected, and undefended surface in the aquatic environment will be fouled. Fouling, on the other hand, can affect a wide range of species that can tolerate some epibiosis. Several others, on the other hand, aggressively keep the epibionts off their body surface (antifouling). Antifouling defenses are built into marine plants like seaweed and seagrass. They do have a distinctive surface structure with tightly packed needle-like peaks and antifouling coverings, which may hinder settling bacteria's ability to cling. Chemical antifouling resistance is most probably a biological reaction to epibiosis' ecological drawbacks, especially for organisms capable of performing photosynthesis. The goal of this study was to see how effective natural compounds derived from littoral seaweeds were in preventing fouling. The brown mussel, an important fouling organism, was evaluated in laboratory bioassays against fifty-one populations' crude organic extracts including fort-two macroalgae species. Antifouling activity, exhibited a distinct phylogenetic pattern, with red macroalgae having the largest share of active species, subsequently brown macroalgae. Antifouling action in green seaweeds has never been significant. Seven species showed some level of induced antifouling defense. Our findings appear to back up previous findings about secondary metabolite synthesis in seaweeds, indicating that in the hunt for novel antifoulants, researchers should concentrate their efforts on tropical red macroalgae.
In the present work, we introduce new transition metal complexes. The complexes are designed to have 3,4,5-trimethoxyphenyl and 2‑hydroxy-4-methoxyphenyl groups connected by 1,2,4-triazole ring and imine linkage to be proper analogues for the anti-tubulin agent combretastatin A-4. FT-IR, ¹H NMR, ¹³C NMR, mass spectrometry, CHNS, thermal gravimetric analysis (TGA-DSC), magnetic susceptibility, conductivity measurements, UV–Vis spectrophotometry, and flame atomic absorption spectroscopy have been used for the characterization of the synthesized compounds. The observed analytical and spectral data confirmed the octahedral environment around cobalt(II), platinum(IV) and square planar around nickel(II), copper(II) and palladium(II) ions. The antioxidant activity of the synthesized complexes was assessed by the DPPH assay, the obtained results showed that C4 is the most active one, with a scavenging capacity of 87.6% in comparison with ascorbic acid as a reference antioxidant agent at 50 µg/mL. The new metal complexes were screened for anticancer activity by the MTT assay against the breast cancer cell line MCF-7 and normal cell line WRL-68. The obtained results revealed that the lowest IC50 24.38 µM was recorded for palladium complex (C4) against the cancer cell line MCF-7,and an IC50 value of 90.2 µM against the normal cell line WRL-68. The synthesized compounds were also subjected to theoretical DFT studies, the obtained results came in agreement with the experimental results. The new ligand and its metal complexes were subjected to molecular docking studies, the structures were docked with the colchicine binding site (PDB: 1SA0), and good docking scores were recorded.
In this research, the SAFT-VR Morse has been extended to polar system by considering the dipolar interactions between non-spherical molecules. The second order derivative thermodynamic properties of refrigerants such as speed of sound, specific heat capacity and Joule-Thomson coefficient have been predicted and compared to PPC-SAFT EoS. The model parameters have been obtained using vapor pressure and saturated liquid density data of pure refrigerants. Using obtained model parameters the aforementioned properties have been predicted in the vapor, liquid, saturation and supercritical phases. The effect of polar contribution on model prediction performance has been studied. The results show that, the polar contribution can be neglected without losing model accuracy. The obtained average error of the polar PC-SAFT and polar SAFT-VR Morse is very close to their original versions. As well, the PPC-SAFT EoS gives accurate results compared to SAFT-VR Morse and its polar version, especially in the case of Joule-Thomson coefficient prediction.
To improve the turnover of thermodynamic cycles, combined cycles have gained a great deal of interest today. The primary objective of these systems is to maximize the utilization of wasted energy from power cycles to initiate cooling, heating, and desalination cycles. In the context of this project, the general cycle comprises a primary portion of power generation, the generation of freshwater, and cooling along with the essential heating of water. Additionally, compressed air energy storage was utilized to lower the expense of the complete cycle. Because of this, we should switch to using compressed air during the off-peak hours of the day and night when the power demand is at its highest. This article also includes a simulation of the gasification process, in which the higher temperature of the generated products is utilized to pre-heat the air. Considering each set of decision variables, the duration of each simulation ranges from 10 to 15 s. It is vital to utilize machine learning techniques to decrease the time needed for optimization to discover the ideal points. In conclusion, the genetic algorithm demonstrated that the exergy turnover and economic cost of the optimal point of the newly introduced cycle are equivalent to 36.21% and 6.56 $/h, respectively.
In the present work, the dual S-scheme heterojunction (g-C3N4/Fe3O4/Bi2WO6/Bi2S3) was constructed with high superparamagnetic properties using an in-situ growth approach. The states of elements, chemical composition, optical properties, and nanostructure morphology were detailed using different characterization techniques (XRD, FTIR, BET, VSM, TEM, SEM, PL, DRS, EDS, and elemental mapping). The photodegradation performance of g-C3N4/Fe3O4/Bi2WO6/Bi2S3 heterojunction was investigated against MB dye under visible-light irradiation (140 W, LED). The g-C3N4/Fe3O4/Bi2WO6/Bi2S3 heterojunction exhibited complete MB degradation in 90 min, as well as 68% of total organic carbon (TOC) was eliminated. The synergistic interaction between the three effective photocatalysts in the g-C3N4/Fe3O4/Bi2WO6/Bi2S3 heterojunction can efficiently inhibit the recombination rate and provide a good path for electron and hole migration. The kinetic studies revealed that the degradation constant of g-C3N4/Fe3O4/Bi2WO6/Bi2S3 was 6.76, 3.4, and 3.2 times greater than that of pristine Bi2S3, Bi2WO6, and g-C3N4, respectively. The radical experiments showed that •OH is the main reactive species. The g-C3N4/Fe3O4/Bi2WO6/Bi2S3 exhibited simple marantic separation and efficient stability in six degradation cycles. The dual S-scheme mechanism was well explained depending on the trapping experiments and photoelectrochemical measurements. This work provides an efficient and simple method for preparing bismuth-rich photocatalysts in a solid solution. This work may have broad application potential in wastewater treatment and environmental pollution control.
The current pandemic (COVID-19) currently is great importance at all levels due to its comprehensiveness in its impact on the global economy, as well as it has displaced a number of companies from positions that have always occupied this decline as a result of improper practices and poor management, and the pandemic was the main driver of the market in financial fluctuations. It is expected that it will affect production and sales and, as a result, the expected profits, and then on the credibility of the financial statements and the exposure of companies to bankruptcy, and it will be the opposite of what was disclosed in those statements. Therefore, some accounting treatments should be carried out and some financial instruments derived therefrom, and working on finding an accounting framework that uses some types of contracts The research aims to analyze the risks facing companies, exposure to different and appropriate accounting approaches and treatments, and knowledge search to carry out reforms in accordance with international financial reporting standards and enable it to control risks effectively and successfully, and that the application of the framework helps to Risk Management and Reducing its Consequences The researchers followed the case study on a sample of service companies (Baghdad Transport and Real Estate Investment Company). It was reached to strengthen the financial position by acquiring financial assets as a result of accounting treatments for derivatives and employing gains with hedged financial assets that enhance their ability to continue and address risks before they occur. Controlling risks using these modern derivative tools is an essential issue for companies based on the returns of these tools, such as controlling regular financial flows, achieving capital gains and reducing risks. Risk and ensure its continuity and then rise to competition.
Based on the architectural approach of Human Acceptability towards built environments, the functionalization of advanced and renewable materials through part-autonomy to general systemization and structure-making could be considered as one of “the key factors” in sustainability. The contemporary states of material automation and autonomy methods are passed through several featuring orders, but in general, they are still not qualified to be considered as domesticated aspects of dealing with the natural resources through the build and construction orders in “the 4th industrial revolution”. This is the main problem of this paper and so, it will clarify the modeling, individual processing, and the emergence of such issues to rich the humanistic acceptability and interaction “as supportive aspects”. Towards that, this paper approaches some of the basic methods of contemporary facilitation, formulation, and reformulation of enhanced materials and natural resources through the architectural domains to clarify the role of industry-architecture relation, which at the first look of the human-centered set make challenges for active/operative systemization. So, such a procedure also needs to provide a better understanding of the contemporary potentials of sustainable applied practices furthermore. In addition, the embodied intelligence of respondent materials would be characterized as a cornerstone of structural control and micro/nanoelectromechanical systems of the upcoming era of individual autonomy, which would be covered in this paper as a new method of nature-based logics classification. Through four featural points of modeling technics, beauty characterization state in sustainable applications of post-digitalism, bio-based logic as the principle of additive design, and the smart processing as basic of functionalization of additive design, this paper provides a primary insight towards the faster, more efficient and effective solutions of fully autonomous driven of sustainable actuation and design prospects architecturally.
In this research, we try to investigate a solar-geothermal energy system. This system includes three turbines for power production, a PEM electrolyzer for hydrogen production, and a thermoelectric for generating electricity from excess heat. In addition, the seawater will be passed through the osmotic cycle to gain fresh water. The required power for this osmotic cycle will be obtained through the energy produced by the main turbines. The generated load, hydrogen production flow rate, purified water flow rate, and heating consumption are assessed in this study. The results showed that this system can produce 3.8 megawatts of electricity as well as 8 g per second of hydrogen fuel at the operating point. Also, the energy efficiency of this system is estimated to be 19%. Afterward, machine learning methods are used to optimize designing parameters, and the optimum operating point in terms of useful power and stored fuel flow rate is obtained by a genetic algorithm. The optimum operating point of this energy system has a useful power output of 4.099 megawatts and a hydrogen flow rate of 29 g per second. In the end, the distribution of the design parameters is displayed for points of the beam curve.
In the present study, magnet silica-coated Ag 2 WO 4 /Ag 2 S nanocomposites (FOSOAWAS) were fabricated via a multistep method to address the drawbacks related to single photocatalysts (pure Ag 2 WO 4 and pure Ag 2 S) and to clarify the significant influence of semiconductor heterojunction on the enhancement of visible-light-driven organic degradation. Different techniques were performed to investigate the elemental composition, morphology, magnetic and photoelectrochemical properties of the fabricated FOSOAWAS photocatalyst. The FOSOAWAS photocatalyst (1 g/L) exhibited excellent photodegradation efficiency (99.5%) against Congo red dye (CR = 20 ppm) after 140 min of visible-light illumination. This result confirmed the ability of the hetero-junction between Ag 2 WO 4 and Ag 2 S species to improve the efficiency of the photogenerated electron/hole pair separation and to reduce their recombination. The kinetics studies of CR photoreaction suggested that the photodegradation rate of the FOSOAWAS photocatalyst was 3.26 and 2.94 times higher than that of pure Ag 2 WO 4 and Ag 2 S NPs, respectively. The CR dye was investigated under various operating conditions (FOSOAWAS dosage, CR concentration, and pH of solution). The trapping experiments proved the significant roles of H 2 O 2 , • OH, and h + oxidants in the photoreaction of CR dye. The proposed mechanism explains that the Type I heterojunction between Ag 2 WO 4 and Ag 2 S semiconductors was responsible for the improved photo-catalytic activity of the FOSOAWAS nanocomposite. Finally, the reusability and stability experiments proved the sufficient stability and facile separation of FOSOAWAS heterojunction, which may be employed in practical applications.
In this study, the numerical analysis of the radiant floor system was investigated for a building in the presence of PCM inside the external walls as well as the roof at a thickness of 2 cm. By injecting cold/warm fluid into the radiant tubes inside the roof, the cooling/heating requirements were met. Several PCMs with identical thermal properties (except melting point) were selected and based on numerical analysis, the energy utilization in the heating/cooling sections was evaluated by comparison with the simple building (without PCM). Four main variables were defined for the neural network, and energy consumption was trended for two climate zones, Shenyang (41.7922°N, 123.4328°E), and Zhengzhou (34.7578°N, 113.6486° E). For each region, the PCM with the best phase transition was selected and it was realized that for the first region, energy consumption was diminished by 12.6% and for the second region by 15.9%. According to the temperature conditions and radiation intensity in the environment, the ANN could forecast annual energy utilization with an error of less than 6%.
This paper examines the mixed convective heat transfer (HTR) of nanofluid (NFD) flow in a rectangular enclosure with the upper moving wall numerically. The lower wall has a high temperature and a number of semi-circular obstacles with the same temperature are installed on it. The upper moving wall has a low temperature and the other two walls are insulated. The enclosure can change from horizontal to vertical. Radiation HTR is considered in the enclosure and there is a magnetic field (MGF) that can change the angle from horizontal to vertical affecting the NFD. This study is carried out for different angles of the enclosure and MGF from horizontal to vertical for radiation parameters (RDP) of 0 to 3 and a constant MGF with Hartmann number of 20 and Richardson number of 10. The aim is to estimate the Nusselt number (Nu), entropy generation (ETG), and Bejan number (Be). The SIMPLE algorithm is utilized using FORTRAN software, and optimization is done using artificial intelligence to find the maximum and minimum output values. The results demonstrate that the maximum value of Nu and Bes corresponds to the MGF angle and enclosure angle of 90°. The minimum value of the Nu and the maximum amount of ETG corresponds to the horizontal MGF and horizontal enclosure when the RDP is 1.5. An increment in the RDP enhances the amount of Nu. The maximum amount of ETG, i.e. 12.87, corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. corresponds to the enclosure with an angle of 45° for the horizontal MGF and the absence of RDP. It was also found that most environmental impacts, and hence values for different environmental factors, arise from the production of nanoparticles; thus, it is a significant contributor to environmental impacts.
This study examined the thermal stability (TS) and mechanical properties (MP) of the simulated Diethyl-toluene-diamine (DETDA) and Diglycidyl ether bisphenol A (DGEBA) matrices/graphene oxide nanosheet (GON) samples. This study was performed by molecular dynamics simulation (MDS). Physical values such as stress–strain curve, order parameter, and atomic length extension are examined at different ratios of GON and initial pressures (IP). Increasing the atomic ratio of GON increases the slope of the stress–strain curve. Thus, Young's modulus (YM) increases in atomic structures. Increasing the GON atomic ratio up to 5 % optimizes interatomic interactions and increases the order parameter. Also, by increasing the atomic ratio of GON from 1 to 5 %, the atomic length extension decreases from 11 to 8 Å. Also, the effect of the IP on the TS and MP of the sample was examined. As the IP increments, the slope of the stress–strain curve increases from 2.91 to 3.55 GPa. These studies show that the order parameter has a downward trend in increasing the IP from 1 to 5 bar and decreases from 0.48 to 0.4 as the IP increases. Also, the effects of IP on the length change of the simulated sample have a decreasing trend after 10 ns. The atomic length decreases from 11 Å to 10 Å by increasing the IP from 1 bar to 5 bar.
nowadays, image encryption is an interesting research area due to the rapid growth of communication technologies and the increasing demands for safeguarding the privacy of the transmitted images as unencrypted images are vulnerable to interception. Partial encryption is used to overcome the challenge of encryption the large size of digital images, due to the large computational overhead and long processing time needed. In this research, one level Discrete Wavelet Transform is applied to a colored image to divide the image to four sub-bands; then a texture segmentation using a Gabor filter and K-means clustering is applied to lowest frequency band. To achieve that, the texture segmentation is used as a new method for scrambling the image based on the features of another image. Finally, the scrambled segments of the image are encrypted using interchanged AES and RC4 Algorithms. Each one of the image pixels is then XORed using one of the two algorithms and the key of the other algorithm. The proposed work is evaluated using several security and performance analysis tests. The results show that the proposed work is resistant agents many kinds of attack and promising in real-time image transmission and encryption. © 2022 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.
The drag coefficient of a one-line circular patch of emergent sparse vegetation in an open-channel flow or riverbeds with varying bed roughness sizes was experimentally investigated. The total roughness of the channel was accounted for using the rate of energy dissipation that incorporated resistance by bed particles and cylinder obstacles. A total of 48 flume experiments were conducted by varying the flow rate, bed roughness, and water depth. The analysis of flow resistance due to the one-line patch of sparse vegetation and the variation in bed roughness was achieved through dimensional analysis. The results show that the drag coefficient Cd is a function of stem Reynolds number, Rd, Froude number, Fr, and the ratio between stem diameter and flow depth (d/H). Experiments showed that the drag coefficient varied with the stem Reynolds number, Froude number, and bed roughness. The Cd generally increased with decreasing stem Reynolds number and Froude number, and this increase in drag coefficient appeared significant for a rough bed of large particles. Results showed that Reynold numbers for different bed roughness had a minimal influence on the drag coefficients. The Fr increases as bed materials are smoother. Statistical regression analysis was achieved to drive the relationship between drag coefficient versus Rd, Fr, and d/H with a coefficient of determination of more than 0.97.
Four natural dyes were extracted from different fruits used in the Dye-sensitized solar cell (DSSC). It includes ber, blackberry, black grapes, and blueberry by individual dye or combined with other dyes. The dye solution's absorption spectra were extended to the whole visible region 200–750 nm. FTIR spectroscopy was employed to identify the possible functional group vibrations responsible for the dyes' chemical activity and optical behaviour. The TiO2 powder was coated on the ITO conducting surface to form a thin film. The experimental results showed that the ber dye produces the highest solar cell efficiency (η), ˜13%, among all four extracted anthocyanin studied. It also found that ber combination with other dyes is higher conversion efficiency than blackberry, black grapes, and blueberry with another and vice versa. Ber dye can be helpful in the development of more eco-friendly and cost-effective solar cells with commercially promising DSSC.
Coronavirus disease 2019 (COVID-19) emerged in late 2019, with the first case identified in Wuhan City, Hubei Province, China, on 12 December 2019. In order to perceive the comprehensive impact of this pandemic, we have to know that misinformation and denials about COVID-19 have surely exacerbated its diffusion and hindered the response against it. Turkmenistan remains one of the very few countries in the world that lacks reports about emerging cases of the novel coronavirus. Turkmen authorities claim that they have adopted all attainable measures required in order to combat the virus, asserting that COVID-19 has yet to reach their country. Despite the government’s reported absence of COVID-19 in the country, rumors, media reports and independent sources suggest the spread of the pandemic in Turkmenistan. By mid-June 2020, the outbreak was referred to as being serious with patients suffering extreme health risks, and following its state of disrepair and unethical practices, many of those anticipated to be COVID-19 infected tend to suffer at home, discouraging any interaction with the healthcare system. The civil society in Turkmenistan, for the time being, takes full part of the government’s duty in the process of informing and educating the public regarding the COVID-19 pandemic, and endeavors to keep the government and WHO accountable for behaving in such repressive ways that could lead to rather preventable loss of human life in Turkmenistan. Yet, efforts hang fire before unveiling the real situation, and Turkmenistan’s government owning up to the negations and roaming speculations, not only regarding the coronavirus crisis, but every public-related issue itself.
The role of feature extraction in electromyogram (EMG) based pattern recognition has recently been emphasized with several publications promoting deep learning (DL) solutions that outperform traditional methods. It has been shown that the ability of DL models to extract temporal, spatial, and spatio–temporal information provides significant enhancements to the performance and generalizability of myoelectric control. Despite these advancements, it can be argued that DL models are computationally very expensive, requiring long training times, increased training data, and high computational resources, yielding solutions that may not yet be feasible for clinical translation given the available technology. The aim of this paper is, therefore, to leverage the benefits of spatio–temporal DL concepts into a computationally feasible and accurate traditional feature extraction method. Specifically, the proposed novel method extracts a set of well-known time-domain features into a matrix representation, convolves them with predetermined fixed filters, and temporally evolves the resulting features over a short and long-term basis to extract the EMG temporal dynamics. The proposed method, based on Fixed Spatio–Temporal Convolutions, offers significant reductions in the computational costs, while demonstrating a solution that can compete with, and even outperform, recent DL models. Experimental tests were performed on sparse-and high-density EMG (HD-EMG) signals databases, across a total of 44 subjects performing a maximum of 53 movements. Despite the simplification compared to deep approaches, our results show that the proposed solution significantly reduces the classification error rates by 3% to 10% in comparison to recent DL models, while being efficient for real-time implementations.
Background Polycystic ovary syndrome (PCOS) became one of the main reasons for infertility in women. It has an obvious effect on phenotype represented by hirsutism, increased body mass index, obesity, and acne, while biochemical tests show adverse hormonal imbalance with hyperandrogenism as testosterone levels increases. From molecular level point of view, pathogenic SNPs may change CAG repeats number along androgen receptor (AR) resulting in altered function of the gene causing different affinity to androgen hormones. Methods Recruiting 150 patients diagnosed with PCOS for the study, genomic DNA was extracted and amplified using specifically designed exon 1 PCR primers employing gene walking technique. The resulting amplicons were sequenced and thoroughly analyzed for polymorphism and CAG repeats number. Results Data obtained from recruiting 150 patients diagnosed with PCOS showed that sequences X:67545209–67545742; X:67545503–67545739 of exon 1 harbored 7 SNPs altered secondary structure of the resulting protein and forced toward the use of CAA as synonymous codon instead of the normal CAGs stretches. This led to produced alternative mRNA that eventually changed nonsense-mediated mRNA decay mechanism. Conclusion Probability of PCOS in women with polymorphic AR gene is higher than others, especially women with high number of CAG stretches. The new finding and highlight of this study is that alternative codon usage (CAAs) to produce the same amino acid (Gln) and compensate the reduced number of CAG repeats number may be attributed to epigenetic mechanism to mitigate the adverse effect of such change and maintain a normal function of AR gene. This finding was not previously reported in former studies.
In this work magnetite/geopolymer composite (MGP) were synthesized using a chemical co-precipitation technique. The synthesized materials were characterized using several techniques such as: “X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), vibrating sample-magnetometer (VSM), field-emission scanning electron microscopy (FE-SEM), energy dispersive X-ray spectroscopy (EDS), Brunauer–Emmett–Teller (BET) and Barrentt-Joyner-Halenda (BJH)” to determine the structure and morphology of the obtained material. The analysis indicated that metal oxide predominantly appeared at the shape of the spinel structure of magnetite, and that the presence of nano-magnetite had a substantial impact on the surface area and pore structure of the geopolymer. Geopolymer and MGP specific surface areas were determined to be 26.60 and 69.04m²/g, respectively. MGP was utilized as an adsorbent for the removal of antibiotic (tetracycline) to demonstrate the role of Fe3O4 after precipitating on the geopolymer surface. It was found that a 10% Fe3O4/geopolymer mass ratio had excellent adsorption performance towards tetracycline (TC), with a removal rate of more than 90%, which was much greater than that of individual Fe3O4 and geopolymer. The Langmuir and Freundlish models provided an accurate description of the experimental data.
Background Toll-like receptors (TLRs) are a family of 10 pattern recognition receptors (TLR1–TLR10) involved in the regulation of inflammatory and immune responses besides their role in the pathogenesis of autoimmune diseases including multiple sclerosis (MS). TLR10 is the least studied TLR in MS, and data for single nucleotide polymorphisms (SNPs) of the TLR10 gene are limited. Therefore, a case–control study was performed on 85 patients with relapsing–remitting MS and 86 healthy controls (HC) to explore SNPs in the promoter region of TLR10 gene. A 927-bp region was amplified, and Sanger sequencing identified 10 SNPs with a minor allele frequency ≥ 10% (rs200395112 T/A, rs201802754 A/T, rs201228097 T/A, rs113588825 G/A, rs10004195 T/A, rs10034903 C/G, rs10012016 G/A/C, rs10012017 G/T, rs33994884 T/Deletion [Del] and rs28393318 A/G). Results Del allele and T/Del genotype of rs33994884, as well as AG genotype of rs28393318, showed significantly lower frequencies in MS patients compared to HC. Allele and genotype frequencies of the 10 SNPs showed no significant differences between MS patients classified according to the Expanded Disability Status Scale. Haplotype analysis revealed that haplotype A-T-A-G-A-G-G-T-A showed a significantly increased frequency in MS patients compared to HC (odds ratio [OR] = 9.70; 95% confidence interval [CI] = 1.28–73.31; corrected probability [ pc ] = 0.03), while frequency of A-T-A-G-T-C-A-T-G haplotype was significantly decreased (OR = 0.10; 95% CI = 0.01–0.85; pc = 0.05). Conclusions The study indicated that two SNPs may influence susceptibility to MS (rs33994884 and rs28393318), but haplotype analysis of TLR10 gene SNPs was more informative.
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9,040 members
Sinai Waleed Mohammed
  • Department of Biology
Bara'a A. Attea
  • Department of Computer Science
F. J. Al-Saffar
  • Department of Anatomy and Histology
Abdalbseet A Fatalla
  • College of Dentistry
Abbas Hamid Sulaymon
  • Department of Energy Eng.
Al-Jadriya, --10071—, Baghdad, Baghdad, Iraq
Head of institution
Qusay Abdul Wahab Al-Suhail