Baghdad Science Journal

A group of divalent complexes was prepared in the formula [M( L)Cl2] when M=Co+2, Ni+2, Cu+2, Zn+2, and Cd+2 L= (Z)-4-((1-(H-indol-3-yl)ethylidene)amino)1,5-dimethyl-2-phenyl-1,2-dihydro-3H-pyrazol-3-one. The Schiff base ligand is prepared by reacting 4-aminoantipyrine with 3-acetylindol. The prepared ligand and complexes were identified by elemental analysis, an infrared spectrometer, the nuclear magnetic resonance spectrum, molar electrical conductivity, electronic spectra, magnetic susceptibility, atomic absorption of the elements, and biological efficiencies. The measurements showed that the synthesized ligand interacts with the central metal ion through the oxygen carbonyl group and nitrogen azomethine atoms, that the coordination of the prepared complexes has a square planar nickel complex and the tetrahedral geometry of other complexes, and that these complexes are non-electrolytic.The synthesized compounds have good antibacterial activity against Gram-negative bacteria, represented by Pseudomonas savastanoi, and Gram-positive bacteria, represented by Bacillus subtilis.

The general formula of new complexes [M2(BDS)Cl4] are resulting from the reaction of a new ligand [N1, N4- bis (1H- benzo [d] imidazol- ‎‎2- yl) -N1, N4 -bis(4-(dimethyl amino) benzyl) succinimide] (BDS) with metal ions M(II)= ‎Cd, Co, Hg, Cu and Ni. This ligand was derived from the reaction of the three substances 4-(Dimethyl amino) ‎benzaldehyde, 2-amino benzimidazole, and succinyl chloride. The compounds are characterized by FT-IR, NMR, UV-Vis and Mass spectroscopy. The serine protease SplB of Staphylococcus aureus and the A chain of Rhomboid-protease-GLPG of Escherichia coli were chosen to study the binding strength of the ligand and the copper complex prepared by molecular docking method.
The gold nano−[Cu2(BDS)Cl4] was also prepared from mixing the copper complex solution with the gold nano solution, and the diagnosis was carried out using different methods, including FTIR, UV-Vis and SEM. The inhibition ability of the prepared compounds, including the nanocomplex, was tested against two types of selected bacteria (G-) Escherichia coli & (G+) Staphylococcus aureus, where the results showed that the ability of the nanocomplex to inhibit both types of bacteria was greater than the ligand and the free copper complex. The free copper complex and the nanocomplex were studied to inhibit human lung adenocarcinoma cell line (A549) and compare it with normal cell line rat embryonic fibroblasts ‎‎(REF). The results showed a high ability of the nanocomplex to inhibit cancer cells, and this confirms the possibility of using it as an anticancer in the future.

This study aims to synthesize a new class of silicon polymers P1-P4 were synthesized based on dichlorodimethylsilane (DCDMS) with some organic compounds containing terminal hydroxyl groups were synthesized for the first time[M1-M4] via condensation polymerization .Also, their nanocomposites P′1-P′4 were prepared in the presence of 0.7% the silver nanoparticles (Ag-NPs) using the solution casting method. The structures of all monomers and polymers were characterized by FTIR and 1H-NMR spectroscopy, which allowed to identify functional groups of monomers and silicone polymers. Thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) test were performed to analyze thermal behavior and effect of the presence of silver nanoparticles. The results of thermal analysis showed that the presence of phenyl rings demonstrated the thermal stability of pure silicon polymers, and the introduction of silver nanoparticles of 7% weight showed an improvement in the thermal performance of nanocomposites P′1-P′4 compared to pure silicon polymers. Which means that the temperature for weight loss (TGA) was higher for the most nanocomposite P′1-P′4, where the TGA for polymers increased from 127 for polymer P2 to 196 for its nanocomposite P′2, this may be due to filling the free voids between the Polymerized chains by silver nanoparticles. The silver nanoparticles were characterized and analyzed using X-ray diffraction XRD and scanning electron microscopy. The X-ray study showed the presence of silver nanoparticles and the average size of nanoparticles ranged from 20 -30 nanometers. The surface study was performed using scanning electron microscopy which showed a fairly uniform shape for the silver nanocomposites.

This study aims to create an easy method for simultaneously measuring nimesulide and flurbiprofen in pharmaceutical formulations. This research provides insight into how variations in buffer concentration, pH levels, and acetonitrile content influence the separation mechanism of two non-steroidal anti-inflammatory drugs (NSAIDs). The retention time of two NSAIDs was increased with an increase of eluent pH value from 3 to 5.5. When acetonitrile content increased from 5 % to 50 %, the retention of two target drugs decreased, indicating hydrophobic and ionic interactions. The RP - HPLC system with UV detection accomplished separation (250 x 4.60 mm, 130Å, and 5) using a C8 Hyper Clone BDS column. The acetonitrile and acetate buffer mixture is used as the mobile phase gradient elution at a detection wavelength of 254 nm and a 1 mL/min flow rate. The linear ranges were 0.05-12.50 and 0.03-17.35 µg.ml-1 for nimesulide and flurbiprofen, respectively. LOD 0.030, 0. 020µg.ml-1 and LOQ 0.091, 0.060µg.ml-1 for nimesulide and flurbiprofen, respectively. The verification findings demonstrate the suitability of the proposed methods for quantifying NSAIDs in pharmaceutical formulations.

In the present investigation, the simultaneous determination of lisinopril and amlodipine in their pure forms and in pharmaceutical formulations were determined using third derivative spectrophotometry. The process is easy, precise, accurate, and economical. The medications in the combined formulation were analyzed using the zero-crossing point method. Lisinopril and amlodipine were discovered to have wavelengths of (204 and 240 nm) and (248 and 272 nm), respectively, in solvent medium in a concentration range of 5–45 µg mL-1 for lisinopril and 5–40 µg mL-1 for amlodipine. The results were much in line with the accepted methodology. Common tablet excipients showed no interference. the recovery rate of lisinopril dihydrate was 98.57 to 103.42% and amlodipine 95.14 to 102.80%. Amlodipine besylate and lisinopril dihydrate were satisfactorily measured using this technique in tablet forms.

In this research, two dyes of p-amino phenol were synthesized by reacting the diazonium salt of p-amino phenol with aromatic compounds, including 1-naphthol and p-amino phenol. The new dyes (a and b) were identified by FT-IR, 1H-NMR, and measurements of some physical properties. The inhibitory activity of the prepared azo compounds against corrosion of carbon steel type C45 in HCl (0.1 M) medium was investigated experimentally by electrochemical measurements. The quantum mechanical method was used to calculate the geometrical structure and physical properties using the Gaussian 09 W program and the density functional theory (DFT) of B3LYP at the 6-311+G (2d, 2p) level. The DFT was utilized for the calculation of inhibition efficiency parameters for dyes that were at equilibrium geometry in vacuum media. The resulting theoretical data revealed that the optimum corrosion inhibitor was compound a.

Rheumatoid Arthritis (RA) is a chronic, systemic autoimmune disease associated with synovial tissue proliferation, cartilage destruction and pannus formation. The study aimed to determine the link among each anticyvlic anti-citrullinated peptide antibody (ACPA), lactate dehydrogenase (LDH), zinc (Zn), and copper (Cu) levels in rheumatoid arthritis (RA) patients and healthy control. Across sectional study was carried out at the Baghdad Teaching Hospital in Baghdad Iraq, and involved 110 patients (95 females and 15 men), who were matched for age and sex with 40 healthy controls (28 females and 12 males). Patients with RA were diagnosed by a specialist rheumatologist utilizing ACR/EULAR criteria in 2010. According to the type of disease-modifying anti-rheumatic drug therapy used—biologic (bDMARDs), conventional (cDMARDs), and combined (DMARDs)—patients in this study were split into three subgroups. Zn, Cu, and LDH were quantified using a spectrophotometer (AAS), whilst serum ACPA was assessed using an enzyme-linked immunosorbent assay (ELISA). The results showed that there was a significant rise in all subgroups of ACPAs (p<0.001), Zn (p<0.001), and Cu (p<0.001) when compared to the healthy control, but no significant differences across subgroups. LDH levels increased significantly in the chemotherapy and bio-chemotherapy subgroups as compared to healthy controls, but LDH levels decreased significantly in the biology subgroup when compared to the chemotherapy and bio-chemotherapy subgroups. Changing therapy types has no effect on raising levels of ACPA, Zn, and Cu, however, it has an effect on LDH levels. The Biology subgroup showed no significant difference among RA patients subgroup and healthy control.

Thyme oil contains thymol (2-isopropyl-5-methylphenol), a naturally occurring, colorless crystalline phenolic compound with a characteristic odor. It is considered an antioxidant. Thymol has low solubility in water and good solubility in oil. Thymol nanoemulsion, dissolved in sesame oil, was prepared by converting it into nanodroplets. From a biological perspective, biological surfaces can effectively adsorb nanoemulsion droplets for more efficient biological activities. Nanoemulsions are spherical particles that act as a carrier for drug molecules, and range in size from 10-1000 nanometers. Because of the anticancer effect of thymol, it can be used as a suitable treatment to prevent angiogenesis in hepatocellular carcinoma. performed a cytotoxicity investigation using the MTT assay, in which a human hepatocellular carcinoma cell line was treated with different concentrations of thymol nanoemulsion. The results indicated that as the concentration increased, cell viability decreased. RNA was then extracted and C-DNA was synthesized. The expression levels of VEGFR and VEGF genes in nanothymol- and free-thymol-treated cells and in untreated cells were then examined. The results showed that the expression of this gene in cells treated with free thymol decreased by 5.33 times compared to untreated cells, but when the cells were treated with nanothymol, the level of gene expression decreased by about 10.02 times.

Activated carbon is highly valued for its versatility and extensive industrial use. Walnut (Canarium vulgare Leech), an indigenous Indonesian plant primarily found in Eastern regions like Maluku and Tidore islands, produces shells that can be converted into activated carbon. This study involved obtaining carbon from walnut shells through pyrolysis at 360°C for 6 hours, followed by activation in a 3M KCl solution for 24 hours. The activated carbon was analyzed using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy-Energy Dispersive X-ray (SEM-EDX), and X-ray Diffraction (XRD). FTIR analysis revealed functional groups including N-H, Ar-H (aromatic), C≡N, carbonyl CO, and ester CO. SEM images showed a non-homogeneous structure in pyrolyzed and KCl-activated carbon. After activation, the pore diameter distribution increased significantly from 496.2 nm to 1,226 µm. EDX analysis indicated a rise in carbon content from 85.40% after pyrolysis to 86.50% post-KCl activation. XRD diffractograms suggested amorphous structures in both forms of carbon, as indicated by loose peaks and broad diffraction patterns. This research introduces the novel use of KCl as an activator to enhance the porosity of walnut shell-derived activated carbon. The KCl-activated carbon demonstrated an ability to remove 0.122 mg/L of Fe(III), achieving 16.78% Fe(III) absorption in 150 minutes. These findings suggest that KCl-activated walnut shell carbon could be an effective alternative absorbent for clean water treatment in the future.

Food waste has accounted for 44% of the total amount of waste produced in Indonesia. From that total, fruits and vegetables waste constitute the main dominant contributors. Production of ecoenzyme has the potential to reduce the environmental waste problem and convert as well the waste into valuable products. This study was employed to characterize and evaluate the enzymatic activity of ecoenzymes produced from the fruit and vegetable waste. The fruits used to produce these ecoenzymes were pineapple, avocado, and orange, while the vegetables-ecoenzymes were generated from lettuce, Chinese cabbage, and broccoli. The ecoenzyme was produced through a fermentation process for up to 3 months with the formulation of the ecoenzyme is molasses, fruit or vegetable waste, and water in a ratio of 1:3:10. Characteristics of the ecoenzyme products were determined by observing the pH, color, odor, and enzymatic activities. The results showed both fruit- and vegetable-ecoenzyme has decreasing acidic pH compared to the initial fermentation, except for avocado-ecoenzyme. The color of ecoenzymes was turned to reddish-brown after 6-12 weeks of fermentations. The sour and fresh smells were detected for ecoenzyme derived from vegetables and fruit, respectively. Enzyme activity assay revealed that all generated ecoenzymes contain protease, amylase, and lipase. The highest enzymatic activity was displayed for avocado-ecoenzyme with protease 0.38 U/mL, amylase activity of 8.30 U/mL, and lipase 3.16 U/mL. The results indicated that the fermentation process from fruit and vegetables was successful. Recycle and reusing natural waste for ecoenzyme productions provide eco-friendly and economical multi-purpose application products.

Toxoplasma gondii was widely spread in humans and other animals, including domestic poultry, worldwide and depends on a unique collection of secretory and cytoskeletal organelles for host cell invasion. The meat of T. gondii infected poultry which includes chickens and ducks was widely consumed in most countries and was known as a primary source of human infection. In Iraq generally and in Basrah province especially, the prevalence of T. gondii in local ducks (Anas platyrhynchos domesticus) and domestic chicken (Gallus gallus) was scarcely known. In the current study, the Latex Agglutination Test (LAT) and (TOX) Toxoplasma IgM/IgG Antibody Rapid Test Kit (Immunochromatography) were used to examine antibodies to T. gondii in 40 local duck birds and 62 domestic chickens from different regions in Basrah Province. Antibodies to T. gondii (LAT) were found in 14 (35%) of 40 local duck birds, and 23 (37.09%) of 62 domestic chickens. While the T. gondii antibodies (Rapid Test) were detected in 10 (25%) of 40 local duck birds and 17 (27.41%) of 62 domestic chicken. The findings showed that the soil was contaminated by T. gondii oocysts represented a food source for domestic chicken and local duck birds due to the birds feeding on the ground. It suggested that the meat from domestic poultry may be an important source of human T. gondii infection in Iraq. This study was the first study in Basrah province to detect toxoplasmosis in domestic chicken and local duck birds.

In Baghdad, the site of Jadriyah and Umm Al-Khanazeer Island (JUKI) was the only IBA nominated by the Birdlife International in 1994 (based on data from 1984). Unfortunately, the JUKI site was deleted from the IBA list in 2017 without proper investigation. We compared our 2022 data with two previous surveys and successfully calculated the trend of the site for the first time. JUKI, as compared to 1984 as baseline data, has currently a medium level of threats (land use change and climate change). Status assessment shows that the site in 2022 has 58.9 % of its 1984 potential habitat remaining (poor habitat status). JUKI still has 84 % of its 2011 potential bird population (moderate bird status), keeping 3 of the 6 original key species; half of the key bird species is kept (indicating continuous eligibility as IBA site). The site needs the immediate activation of absent proper site management (response measures) based on the IUCN and Birdlife International criteria. The newly added trend parameter indicated a trend of no change–small deterioration. Our conclusion is that the JUKI site is still eligible as an IBA site and its removal from the IBA list was not based on scientific evidence.

Neural tube defects (NTDs) are complex structural deformities in newborn infants. These defects are caused by a blend of genetic and environmental factors in the abnormal phenotype. The current study aims to determine the genetic variation polymorphism for methylenetetrahydrofolate reductase (MTHFR) C677T rs180133 genotyping and to detect single nucleotide polymorphisms (SNPs) in a DNA sample of Spinal Bifida (SB) and compare it with control newborn children. Blood samples were collected from newborns (50 children under one year old) (25 cases of spinal bifida (SB) and 25 controls). The DNA was extracted and amplified by the tetra ARMS-PCR technique (Amplification Refractory Mutation System Polymerase Chain Reaction). ARMS-PCR technique consists of four primers (two outer and two inner) to amplify target DNA sequences for different genotypes for the distribution of the genetic variation of MTHFR genotyping of different genotypes (wild-type (CC) and mutant-type (TT) alleles). The results indicate that the genetic mutation of the enzyme tetrahydrofolate reductase was associated with spina bifida in newborns and could serve as a biomarker to detect the development of spina bifida in newborns.

Standard treatments for ischemic stroke are intravenous thrombolysis and endovascular recanalization. In the acute phase (<4.5 hours) only 3.2% to 5.2% of ischemic stroke patients are eligible for intravenous thrombolysis. Mesenchymal stem cells (MSCs) are multipotent cells that can differentiate into different types of cells that produce potential regenerative therapeutics in stroke patients. MSCs will secrete secretomes that contain growth factors, chemokines, cytokines, metabolites and bioactive lipids. Secretome promote production of CD31 and Vascular Endothelial Growth Factor (VEGF). Neurogenesis and angiogenesis effect from CD31 and VEGF cause brain cell regeneration and neurological improvement. This study analyzes the effect of 150 l SH-MSCs injection toward CD31 and VEGF expression in rats with ischemic stroke. The method used was laboratory true experimental post-test with only control group design and sample was taken with consecutive sampling. It uses 18 Rattus norvegicus and divided into sham, control and P1 (MCAO + 150 ul secretome) groups. Control and P1 group were made in stroke condition with Middle Cerebral Artery Occlusion methods by clamping Common Carotid Artery. Modified Neurological Severity Score (mNSS) used to measure neurological function improvement. Mean value of VEGF and CD31 expression in P1 higher than control group and mNSS in P1 lower than control group. Through the increases of VEGF and CD31 expressions, SH-MSCs can drive cell proliferation, neuron cell survival, angiogenesis, neurogenesis and blood-brain-barrier integrity recovery in the rats’ brains, so it improves clinical outcomes and neurological function in rats with ischemic stroke.

Irrigation practices on agricultural fields use more water than any other human activity. As a result, the sustainability of water use and food output is intimately tied to how fields are managed. This research was conducted to enhance the long-term viability of water and agricultural production. Soil amendments of compost and perlite were applied in an experiment to investigate the possibility of enhancing soil textures (sandy clay and silty clay) and, consequently, improving the production of crops and water sustainably. The Root Zone Water Quality Model (RZWQM2) was utilized to simulate the water dynamics and water requirement for wheat production under the combination of soil amendments and soil textures. Applied compost produced the highest crop yield, compared to the control treatment, with an increase of 6 - 21% and 2 - 9% in the sandy clay and silty clay, respectively. The interaction between sandy clay and compost treatment yielded the highest crop evapotranspiration of 508 and 375 mm per season for the first and second crop growing seasons, respectively. Using soil amendments decreased water leakage out of the root zone and improved water/wheat productivity. In addition, soil nitrate leaching away from the root zone was reduced by applying soil amendments. According to the findings, soil amendments successfully improved the productivity of both soil textures. Moreover, the compost treatment delivered superior outcomes, mainly when applied to sandy clay. Hence, evaluating other applications of soil amendments concerning soil texture types is recommended to improve the sustainable productivity of water and crops.

Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real time polymerase chain reaction (qRT-PCR). The low concentrations of the plant extracts did not affect neither on the bacterial growth, nor on the viability of K. pneumoniae, supported with growth curves. Additionally, the biofilm production was inhibited even by lower plant concentrations, and both cinnamon and clove extracts were able to render the MDR bacteria to be more susceptible to antibiotics. At the molecular levels, the bacterium treated with either clove or cinnamon or in combination showed under expression of the biofilm formation regulation gene (bssS), the carbapenem resistance gene (bla), as well as the QS target gene (LuxS). Both clove and cinnamon ethanolic extracts exerted potent impacts on reducing pathogenic traits regulated by QS in K. pneumoniae. Finally, the study recommends further exploration of clove and cinnamon extracts separately or in combination to develop alternative therapies against MDR K. pneumoniae infections.

Cadmium telluride (CdTe) nanocrystals (NCs) have generated the interest of researchers as an electrode material in lithium-ion batteries (LIBs) due to a potentially high capacity. CdTe nanocrystals or quantum dots (QDs) were synthesized using laser ablation (Nd: YAG laser at energy 600 mJ by 150 pulse number) to be utilized to form a nanobattery device out of ITO/CdTe/Li: graphene/TPD/Ni. The spectra of the CdTe NCs were assessed using ultraviolet-visible (UV-VIS) and photoluminescence (PL) spectrometers, and the outcomes proved that the CdTe NCs synthesized were nanocrystalline structures. The energy gap (Eg) within CdTe NCs regarded as PL has been identified to be close to 2.33 eV. CdTe NCs produced via laser ablation enhance the functionality of the nanobattery by increasing the carrier's charge mobility and, as a further benefit, by facilitating recombination processes inside CdTe NCs with Li ions. In addition to lighting at (3V), current-voltage (I-V) specifications establish a suitable environment as well as formation. CdTe NCs increased the capability of the nanobattery by increasing the charge mobility of the carrier and, as a result, the interactions between CdTe NCs ions and TPD conductive polymer. Similarly, combining TPD conductive polymers with CdTe NCs semiconductor layers in nanobattery resulted in a complex creation of conductive polymers and semiconductor nanomaterials, resulting in high-performance nanobattery efficiency. The nanobattery mechanism built using materials for semiconductors (CdTe NCs) and (Li-graphene) has successfully run the nanobattery at low voltages while supplying a large current.

Metal ferrite nanomaterials have emerged as promising materials for gas sensor fabrication due to their high surface area, which provides a large number of adsorption sites for gas molecules. In this research, a zinc ferrite nanoparticle-based gas sensor was prepared using the solid-state reaction method to achieve high sensitivity and a fast response time. The powder zinc ferrite was annealed at different temperatures within the range (500-700) °C for six hours. The optimum temperature for synthesis was 675°C. The structural properties of the prepared compound were studied using X-ray diffraction. The results showed that the compound crystallizes in a cubic crystal structure and belongs to the space group Fd3m. The lattice constant was a = 8.3856 Å. The theoretical density of ZnFe2O4 has been calculated. The average crystallite size of the ZnFe2O4 compound was calculated using Scherrer’s formula. The average crystallite size was 29.5 nm. The morphology of the ZnFe2O4 nanoparticles was observed by scanning electron microscopy. The electrical resistance variations of the ZnFe2O4 compound were studied as a function of temperature. The electrical resistance values decreased with increasing temperature, indicating semiconducting behavior. The sensing properties of ZnFe2O4-based sensors were studied. The sensing results showed that the compound is a good sensor for ethanol vapor, where the response and recovery times were 10.115 s and 81.351 s at an operating temperature of 275 °C for a 100 ppm concentration of ethanol. For acetone vapor, the response and recovery times were 10.978 and 102.543 s at an operating temperature of 300 °C for a 100 ppm concentration. Findings indicate that the gas sensor based on zinc ferrite nanoparticles exhibited a high sensitivity and fast response time to ethanol vapor at a relatively low operating temperature 275 °C. These findings suggest future work on the nanostructure of zinc ferrite for its potential use in gas sensing applications.

Nanoparticle biogenic synthesis (NP) has attained widespread interest due to its benefits such as simplicity, environmental friendliness, rapidity and cost-effectiveness. Selenium nanoparticles (SeO2NPs) were synthesized utilizing Cinnamomum verum bark extracts (CVBE) and selenium tetrachloride. In this study. XRD, TEM, UV and FTIR techniques were used to characterize the biosynthesized SeO2 NPs. The crystal structure of SeO2-NPs is hexagonal as evidenced by XRD results. The crystalline size was achieved at about 24.5 nm and the TEM image showed that the diameter of SeO2 was less than 100 nm with spherical and semi-spherical shapes. The effect of SeO2 on antifungal and diverse types of bacteria was the subject of this investigation. SeO2 inhibited Staphylococcus epidermidis activity against 23 mm and staphylococcus aureus activity against 21 mm, as well as antifungal isolates 18 mm, which was more effective than bacterial Klebsiella Sp. and Escherichia coli.

The study prepared new Copper sodium borate oxide CSmBO nanocomposite thin films using a solvothermal synthesis method and the annealing process occurred at 350°C for 3 hours. The study characterized the films using FESEM, EDX, and UV spectroscopy. Based on the FESEM analysis, the films were uniform and dense, with nanoparticles which range from 21.49 to 96.51 nm in size. EDX confirmed the elemental composition of the CSmBO nanostructures, validating the successful incorporation of copper, samarium, and boron. (XRD) diffraction patterns show up that forming a Crystal phase with high levels of strain and blemish is due to nanoparticle gathering. The synthesized nanocomposites exhibited a remarkable tunability in morphology and structure. UV-Vis spectroscopy revealed a broad optical absorption spectrum with a maximum absorbance peak at 600 nm, demonstrating the potential of the CSmBO nanocomposite thin films for optoelectronic applications. The band gap (Eg) was 2.03 eV and the Urbach energy (Eu) 0.15 eV which indicates a relatively lower degree of localise band tail states. Successfully fabricating CSMBO nanocomposite thin films with tunable features highlights the potential of this composite for many optoelectronic implementation, inclusively solar energy harvesting, light-emitting and diodes photo catalysis.

The current study presents an experimental attempt to enhance the thermal performance of a parabolic solar collector, which is a tube made of copper, by using four different types of receiver coatings. The experiments were conducted with a mass flow rate of 1 L/min, utilizing deionized water as the heat transfer fluid, and a single-axis tracking system (north-south orientation). The experimental tests were carried out in Mosul, Iraq, during selected days of the months (May, June, July) in the year 2023, from 9 AM to 4 PM. The results indicated that when air was used as a type of receiver coating, the highest useful thermal energy value reached 557 watts, the lowest 69 watts, with an average of 335 watts. When using black chrome-coated glass with aluminum fiber that is evacuated of air, the highest useful thermal energy value was 1247 watts, the lowest 146 watts, with an average of 335 watts. As black chrome-coated glass with PCM was used, the highest useful thermal energy value was 620 watts, the lowest 69 watts, with an average of 324 watts. Finally, when transparent white glass was used, the highest useful thermal energy value was 759 watts, the lowest 97 watts, with an average of 427 watts. These results demonstrate that the utilization of black chrome-coated glass with evacuated aluminum fiber provides the best thermal performance compared to the other types of receiver coatings investigated in this study.

Scheduling involves assigning resources to jobs within specified constraints over time. Traditionally, the processing time for each job was considered a constant value. However, in practical scenarios, job processing times can dynamically fluctuate based on prevailing circumstances. In this article, a novel approach is presented for the two-machine fuzzy Flow-Shop Scheduling Problem (FSSP) in a fuzzy environment, where job processing times are represented by trapezoidal fuzzy numbers. Additionally, a novel algorithm based on Goyal's approach for the two-machine FSSP with fuzzy processing times has been proposed and developed. Simultaneously, an existing algorithm has been enhanced to improve its performance in this specific context. The study aims to minimize the total waiting time for jobs. A defuzzification function is employed to rank fuzzy numbers, with the ultimate goal of minimizing the total waiting time. Furthermore, the article evaluates the performance of these methods in terms of solution quality, using test problems with 10, 20, 30, 40, 50, 60, 80, 90, 100, 120, 200, 250, 300, and 500 jobs, along with 2 machines. The mean total waiting time is compared to existing algorithms, including the NEH algorithm, Palmer’s method, Johnson’s method, B. Goyal and B. Kaur, and the proposed algorithm. Additionally, the obtained results, along with a well-structured ANOVA test, highlight the effectiveness of the proposed method in addressing the scheduling problem under investigation. The experimental results showcase that the proposed algorithm can effectively minimize the waiting time in fuzzy two-machine FSSP and achieve superior results when compared to various existing algorithms.

In general, the exponential average of two positive numbers does not have to be an integer. Because of this, the exponential average needs to be an integer that takes into consideration the flooring or ceiling function. It has been defined that graphs can be labeled with an exponential average, where the flooring function or the ceiling function can apply labels to the edges. To establish the exponential average assignment on graphs, consider the edge labels that arise from the ceiling function alone. The vertex assignment function δ and edge assignment function δ^* are called a Cexp average assignment of the graph G with p vertices and q edges if δ is injective and δ^*is bijective and the corresponding relations are δ:V→Ν-{q+2,⋯,∞},δ^*:E→Ν-{1,q+2,⋯,∞} and is defined by edge label 〖 δ〗^* is 〖 δ〗^* (uv)=⌈1/e ((X(v))/(X(u)))^(1/(Y(u,v))) ⌉ where X(u)=〖δ(u)〗^(δ(u)),Y(u,v)=δ(v)-δ(u) and N is the set of all natural numbers. If the graph accepts a Cexp average assignment then it is called a Cexp average assignment graph. The Cexp average assignment of graphs is proposed in this paper, and its characteristics are explored on the cycle, the union of path and cycle, the union of T- graph and cycle, the graph G*, the graph G^', the graph G ̂and tadpole.

The oxidation ability of cold plasma is a major influence on bacterial inactivation, lipid oxidation, medical equipment sterilization, and applications in air and wastewater purification, for this reason, the ability of cold plasma to oxidize materials is an important factor that must be studied. In this study, the ability of cold plasma generated by a dielectric barrier discharge (DBD) to oxidize materials was revealed and proven by using different exposure times (5, 10, 15, 20 min) and several measurements: the decolonization of indigo carmine from dark blue to yellow, the significant reduction in pH, and the increase in oxidation reduction potential (ORP) and electrical conductivity (EC), Proven spectrophotometrically in the presence of nitrogen and its oxide ions. It was observed that the exposure time of 15 min is the maximum period during which oxidation occurs, after which saturation occurs. Numerous reactive oxygen and nitrogen species are created upon the interaction of gas phase plasma and water vapor (supported by excited species, energies and plasma electrons).

Here the notion of convex fuzzy absolute value space is represented with an example which shows that the existence of such space. The reason behind introducing the definition of convex fuzzy absolute value and does not using the ordinary absolute value is the main definition in this paper will be not correct with ordinary absolute value. After that the main definition of convex fuzzy normed space is recalled with example which shows that the existence of such space. Then other definitions and theorems is recalled that will be used later in the section of main results such as the convex fuzzy norm is convex fuzzy continuous function. So our goal in the section of results and discussion is to prove some properties of finite dimensional convex fuzzy normed space which not true ingeneral for convex fuzzy normed space. Thus the last section contains the following results with proofs if D is a subspace of the convex fuzzy normed space U with dimD <∞ then D is convex fuzzy complete subspace of U. Moreover when Y is a convex fuzzy bounded as well as convex fuzzy closed subspace of the c-FNS, U also dim U <∞ then Y is convex fuzzy compact. As well as if dimU <∞ for a linear space U then there is a unique convex fuzzy norm on U. Finally if W={w∈U: the convex fuzzy norm of w belongs to I } a convex fuzzy closed subset of U as well as convex fuzzy compact this implies that dimU<∞ where U is convex fuzzy normed space.

Carbon dioxide is the main greenhouse gas contributing to global warming risk. Forest biomass is crucial for the sequestration of atmospheric carbon dioxide; however, the rate of decline in worldwide forest biomass is concerning and can be attributed to anthropogenic activities. Reforestation is essential in this situation to decrease the amount of CO_2 in the atmosphere. Efforts at reforestation can be evaluated according to the financial investment required for their execution. This work presents a nonlinear mathematical model that examines the impact of reforestation and the implementation of reforestation initiatives on regulating atmospheric CO_2 levels. The critical values of the model and their stability are found analytically. The occurrence of transcritical bifurcation around the possible critical points is performed using the Sotomayor theorem. Based on the numerical simulations, the model in the absence of reforestation would put some aspects at risk of extinction. Further, the level of CO_2 in the atmosphere would decrease due to reforestation. Moreover, the numerical analysis indicates that the system experiences a loss of stability without reforestation activities. The system maintains oscillation through Hopf-bifurcation while engaging in reforestation activities.

The study of medical image-based disease detection has witnessed a notable surge in interest and success with computational methods. This work proposes a novel framework to detect diseases at earlier stages from medical images, using mathematical model and Machine Learning. Introduce two new quantitative measures for COVID-19 and Tumor disease detection: image uncertainty based on Shannon entropy and image complexity based on fractal dimension. Our result demonstrated that in COVID-19 positive images exhibited skewed pixel distribution due to the hazy regions resulting in lower entropy values for diseased cases compared to healthy ones. The second quantity, fractal dimension was measured by box counting method determines the image's complexity. The outcomes of both techniques were applied to the classification of images using the Machine Learning (ML) model k-NN (k-nearest neighbor). This complete framework provides a new and unique approach to identify and classify diverse types of images with a classification accuracy of 90% for Covid and 70% for Tumor achieved. Our work shows that Entropy and fractal dimensions can distinguish between COVID-19 and healthy patients, making them promise for early diagnosis. This manuscript presents a novel, computationally efficient and explainable methodology for disease classification that provides early-stage disease detection.

People's need for food is increasing day after day due to the large population increase that has occurred in human society, which has led to a significant increase in the activity of food product manufacturing companies in the world. Hence the necessary need to evaluate the performance of food production companies. We found that the best way to evaluate the performance of these companies is through social media comments, because it is the newest and most common method among people. In this paper, 4 machine learning techniques were relied upon to evaluate participants’ comments in evaluating food production companies after using a lexicon of Arabic language terms in general and the Iraqi dialect in particular. These terms relate to positive and negative words and expressions. Then training through machine learning algorithms. Random Forest (RF), Naive Bayes (NB), Rough Set Theory (RST), and Support Vector Machine (SVM) algorithms were tested. Experiments have shown that RST is superior to the other three. RST achieved (96.13%), SVM achieved (95.75%), although RF achieved (94.1%) and NB achieved (87.1%).

High-security cryptography algorithms like AES require high computational capabilities to achieve information security. Therefore, it is necessary to use parallel computing architectures that exploit modern technologies in spatial parallelisms to obtain the most conceivable computational power. Various technologies have been introduced to achieve parallel processing. One of them is field-programmable gate arrays (FPGAs), which have good characteristics suitable for implementing parallel architectures with lower power consumption. The paper aims to design and implement an embedded computing processing engine architecture transceiver with high performance to obtain better throughput on FPGA technology to encrypt and decrypt images. In this design, two boards are used, "DE1_Soc and NEEK board" with Altera Quartus prime 18.1, cyclone V 5CSEMA5F31C6 FPGA device for synthesis and simulation. The implementation results show that the proposed architecture has an efficient performance in terms of an operating frequency is 600 MHZ and a throughput is 76.8 GHZ.

The social media platforms have been generating an enormous amount of data for every second. Twitter, in practice by the individuals is producing more than six hundred tweets in each second. While freely posting opinions and expressions by users, it is very difficult to confine the hate speech shared against any individual, religion or any ethnic group. Consequently, the persons targeted by such hateful content get frustrated. In this regard the different approaches have been solving this serious problem but, sometimes unable to achieve satisfactory results. Therefore, we propose different Machine Learning models to classify given data in two categories, offensive or non-offensive. The experiments were conducted on Twitter data generated by ourselves using Twitter API and Tweepy library by Python. The generated results were evaluated based upon various metrics such as accuracy, precision, recall, F1-measure and MCNEMAR test. Compared to the different machine learning algorithms, random forest ensemble classifier outperformed against other algorithms, the novelty and contribution of our research paper is: The development of Twitter dataset that consists of several tweets containing 11 object variables with four different class variables showing the different offensive levels, Machine Learning algorithms’ application to detect the hate speech, Comparative analysis of different Machine Learning algorithms against different evaluating metrics including McNemar Test. The significance of proposed technique is well explained by the Twitter datasets generated through Twitter API and Tweepy library by Python.