Baghdad Science Journal

This study presents a rapid, sensitive, and straightforward approach for measuring Cu(II) ions using turbidity continuous flow injection analysis (CFIA) . The method involves reacting Cu(II) ion with calcium Ferro cyanide to produce a brown-red precipitate. To detect the attenuation of incident light as a result of collision on the surfaces of the precipitate particles, the analyzer NAG-SSP-5S-1D was used to measure turbidity at an angle (0-180 ͦ).
The linear range of Cu(II) measurements extends from 0.01 to 5 mmol.L-1 with Correlation Coefficient of 0.9993 and R2 % = 99.86 .The limit of detection (LOD) was determined to be 23.829 ng/sample from diluted the lowest concentration in the calibration curve, and the repeatability of the method (RSD%) was demonstrated to be less than 0.3 % (n=6) for the selected concentration (1,5 mmol.L-1). The method was successfully applied to the determination of Cu (II) ions in a variety of alloys using the standard addition method. A comparison was made between the newly developed method analysis and the classical method ((UV Spectrophotometry, λmax=520 nm ) using t-test. It was noticed that there was no significant difference between the two methods at 95 % confidence level. Overall, the developed flow injection method offers simplicity, sensitivity, and reliable analytical performance for the determination of Cu(II) ion . Therefore the newly developed method can be used of as an alternative and an acceptable method for the analysis of Cu (II) ions in alloys compared to the reference method.

The cloud point extraction (CPE) methodology was utilized to produce a simple, highly sensitive, and environmentally friendly method for preconcentrating and evaluating salbutamol sulfate (SAL) in pharmaceutical dosage forms. Triton X-114 was used as a surfactant to recover the product result from the diazotization coupling between SAL and diazotized 2, 4-dichloroaniline (DCA) by the cloud point extraction process. The product was extracted with non-ionic surfactant micelles and then spectrophotometrically detected at a wavelength of 445 nm. Under ideal conditions, the calibration curve's linearity (r = 0.9947) ranged from 0.1 to 5.0 µg. mL-1 of SAL. The results showed that the samples had average recoveries ranging from 97.5 to 99.1%, relative standard deviation (RSD) better than 3.5%, and detection and quantification limits of 0.01 and 0.04 µg.mL-1, respectively. Both batch and cloud point extraction procedures (with and without extraction) were used to study the reaction, and a simple comparison of the two approaches was made. The recommended technique proved effective in determining the SAL in pharmaceutical applications

In this research drug polymers, have been prepared by substituting drugs to polymers backbone, which raised interest as a result of the benefits systems possesses, which includes the gradual release of the application of the drug, ease of application, delivery of the drugs in certain (specific) local, prolong the period of drug douse, reduce the potential and common side effects, and decrease the toxicity. This work included ring opening of PVP with ethylene glycol then substitution with different drugs (Salbutamol and Ribavirin, Phenylephrine, Theophylline, Sulfamethoxazole). All prepared drug polymers were identified by FT-IR ,1H-NMR, and UV. Spectroscopes, thermal analysis such as TGA . The physical properties of all polymers were measured.
The controlled release for all polymers was studied in different pH values at [30-40 0C]. The hydrolysis data showed that release rates are strongly dependent on the pH of the medium and temperature.
We concluded that the drug polymers could enhance the solubility of drug carrier polymers in water, with desirable properties, slow-release, and prolonged activity. These four methods of advanced properties and bearing of the different bioactive units, and studying Molecular Docking.

A cost-effective and efficient detector was created to conduct thorough turbidimetric measurements by reaction of Co (II) ion with calcium ferro cyanide to form bright green particulate, using the method of continuous flow injection analysis, the use of NAG-5SX1-1D-SSP Analyzer in determining cobalt (II) ion in a test for the validity of the new design. The NAG-5SX1-1D-SSP Analyzer is composed of five irradiation sources of white snow leds having the diameter of 10 mm with one solar cell of 55 mm length, 13.5 mm width. Using a selector switch to select the optimum voltage to be used which was 2.7 VDC. Under conditions of optimization, cobalt (II) ion was determined at 0.005-20 mmol. L-1(n=23) while linearity dynamic range 0.005-7 mmol. L-1 (n=20) at r=0.9981(correlation coefficient), R2%= 99.61%. The application of Co (II) ion in alloys of 94.83-103.37%, the analytical system presents a L.O.D at 7.543 ng/Sample and a L.O.Q at 14.708 µg/Sample with RSD% < 0.21% for 3 and 6.5 mmol. L-1 [Co (II) ion]. To enhance the assessment of the recently suggested approach, an analysis was carried out by combining the standard addition technique with a classical method. In general, the established flow injection procedure provides ease, precision, and consistent analytical efficacy in determining Cobalt (II) ions, indicating its potential utility for the analysis and evaluation of various important ions and pharmaceutical drugs.

In this work the precursor (W1) 2,2'-((1E,1'E)-(4,4'-diamino-5,5'-dimethyl-[1,1'-biphenyl]Diazene-2,1-diyl-3,3'-diyl)-bis((E)-pyridin-3-yldiazenyl)-[1,1'-biphenyl] or (W2) 3,3'-dimethyl-5,5'-bis((E)-pyridin-3-yldiazenyl)-[1,1'-biphenyl] -4,4'-diamine respectively were obtained from the reaction of 2-aminophenol or 2-aminopyridine with toluidine, respectively. Subsequently, these precursors were used for the synthesis of two ligands using the azo compounds (W1) or (W2) and curcumin to produce [H4L1] 4,4',4'',4'''-((1E,1'E,6E,6'E)-((3,3'-bis((E)-(2-hydroxyphenyl)diazenyl)-5,5'-dimethyl-[1,1'-bi phenyl]-4,4'-diyl)bis(azaneylylidene))bis(5-hydroxyhepta-1,6-diene-1,7-diyl-3-ylidene))bis(azaneylylidene))bis(aza -neylylidene))tetrakis(2-methoxyphenol) or [H2L2] 4,4',4'',4'''-((3,3'-dimethyl-,4,4'-diyl)bis- (azaneylylidene))bis(5-hydroxyhepta-1,6-diene-1,7-diyl-3-ylidene))tetrakis(2-methoxyphenol). The prepared ligands were characterized by F.T-I.R, U.V, 1H-NMR, 13C-NMR spectroscopy. This work also included the preparation of complexes through the reaction of ligands with the metal alts of CoII, CuII, MnII, NiII and CdII ions, under reflux, using ethanol as a solvent and KOH as a base. These complexes were characterized by (I.R., U.V-Vis. and mass) spectroscopy, atomic absorption (A.A), melting point, conductivity and magnetic susceptibility measurements along with thermal analysis. Analytical and spectroscopic methods pointed to tautomerism observed in curcumin moiety. Six and four coordination shapes were suggested based on the information gathered during the characterization procedure. Certain bacteria and fungi were tested against the ligands and their complexes. All prepared compounds appeared better inhibition against fungi compared to the four types of bacteria and the results obtained suggested different effects of the complexes, but generally, the metal complexes are more effective than the free ligands against a variety of organisms under test.

There has been an increasing interest in the chemistry of pyridazine derivatives because of their biological significance. Pyridazine has been reported to possess variety of biological activities like antidiabetic, anticancer, anti-AIDS, anti-inflammatory, anticonvulsant and antimicrobial, insecticidal etc. In our study, pyridazine derivatives were synthesized by starting with paracetamol, also known as para hydroxy acetanilide, which does not require a prescription. The reaction involved the use of metallic sodium and methanol as a solvent, resulting in the formation of para-hydroxy acetanilide sodium salt (p-hydroxy acetanilide sodium salt). Subsequently, compound p-hydroxy acetanilide sodium salt was reacted with 2-chloro ethyl acetate in Dimethylformamide (DMF) as a solvent to yield ethyl-2- (p-acetamido hydroxy) acetate. This compound ethyl-2- (p-acetamido hydroxy) acetate was further reacted with hydrazine hydrate to obtain the corresponding hydrazine -2-(4-acetyl amino phenoxy) acetyl. The acid anhydride derivatives, hydrazine -2-(4-acetyl amino phenoxy) acetyl were reacted with glacial acetic acid as a solvent, leading to the synthesis of derivatives 1,2-diazine. These newly synthesized compounds were then subjected to antimicrobial testing against various microorganisms, including bacterial strains, gram-negative bacteria, and fungal strains. The objective was to identify the most effective biologically active compounds.

The current investigation aims to display that bulk polymerization of Atenolol (Ate) can synthesize and store molecular-imprinted polymers (MIP) at room temperature. It is indicated that such an environment has various advantages, including higher sensitivity, lower costs, higher stability, and longer life. To guarantee appropriate adsorption capacity, 0.99:6:20mmol ratios of template, monomer, and cross-linking agents are employed for polymerization. To start the functional monomer styrene (C8H8) bonding Ethylene glycol dimethacrylate (EGDMA) C10H14O4, the researcher employed benzoyl peroxide (BPO). Accordingly, MIP is created for Atenolol (Ate-MIP), which can be detected for pharmaceuticals employing UV-visible spectrophotometry at 276 nm for drugs. Fourier-transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscopy (SEM) were utilized. Large cavities appear due to the elution process's application on the template (Ate) from the Ate-MIP. These cavities resulted from a porogenic mixture of solvents produced from methanol, chloroform, and acetic acid (70:20:10). The Langmuir isotherm model indicated that Ate-MIP has a maximum adsorption capacity of 2.9957 µmol/g, and the template to monomer ratio was 1:1. Molecular imprinted polymers (MIPs)-filled solid-phase extraction (SPE) syringe was used to selectively extract and pre-concentrate Ate from aqueous solutions and atenolol estimations.

Triazoles linked to carbohydrate molecules are one of the most important compounds that have wide applications in the pharmaceutical, biological, and materials science fields. Many of these compounds have been prepared and their structural, chemical, and physical properties have been studied. One of the best techniques used to study and interpret these properties is nuclear magnetic resonance NMR spectroscopy. For this purpose, the simplest glucose-based 1,2,3-triazole derivative 5 has been prepared from D-glucose in four consecutive steps. First, the reaction of glucose with acetic anhydride in the presence of sodium acetate afforded 1,2,3,4,6-penta-O-acetyl-β-D-glucopyranose (2) in 83% yield. The treatment of compound 2 with 48% HBr in glacial acetic acid gave glycosyl bromide 3 in 79% yield. This derivative was directly reacted with sodium azide in N,N-dimethylformamide DMF to produce glycosyl azide 4 in quantitative yield. Click reaction of azide 4 with propargyl alcohol in dimethyl sulfoxide DMSO gave the target triazole 5 in good yield. The 1H NMR spectra of the triazole 5 were measured in different deuterated solvents and it showed there is a complex splitting of the signals of the glucose ring in CDCl3. This splitting pattern disappeared upon decreasing of temperature, increasing of the concentration, or changing the deuterated solvent.

The Schiff base reaction between Cephalexin (CFX). (7R)-3-Methyl-7- (α- D -phenylglycylamino) -3-cephem-4-carboxylic acid (C16H17O4N3S) and vanillin C8H8O3 [ 3-methoxy -4-mydroxybenzaldehyde] was carried out resulting in ligand C26H27N3O6S (L). In turn, reacted with the next metal ions (Cobalt (II), Nickel (II), Copper (II), Zinc (II), and Cadmium (II)), forming stable complexes with unique geometries such as (Octahedral for Ni+2, Cu+2, Zn+2&Cd+2, Tetrahedral for Co+2). The complexes were identified using spectroscopic techniques such as UV-Visible, FTIR, 1H NMR, 13C NMR, mass spectrometry, magnetic moment, and molar conductivity. TGA analysis confirmed the interaction of water residues with metal ions within the coordination sphere, as supported by atomic absorption spectra obtained from C.H.N.S. AAS, which aligned with the expected results. All techniques were utilized to demonstrate the ligand's production and propose the new shape of the complexes. The result from infrared spectrum showed that the ligand behaves as bidentate with all prepared complexes with unique geometries such as (Octahedral for Ni+2, Cu+2, Zn+2&Cd+2, Tetrahedral for Co+2). Conductivity analysis revealed their electrolytic nature in Ni and Cu and ions complexes and non-electrolyte in other. The antibacterial activity of the compounds that were produced was tested using an agar-well diffusion procedure towards one strain of gram-positive as well as one strain of gram-negative bacteria

Four metal complexes of Schiff base ligand were prepared. To characterize both the ligand and the metal complexes, various techniques were employed, including elemental analysis, FT-IR spectroscopy, UV-Vis spectroscopy, molar conductivity measurements, magnetic moment determination, melting point, mass spectroscopy, 1H-NMR and 13C-NMR spectroscopy. The results showed that the metal complexes formed have the formula [M(L)2Cl2]Cl(n).H2O, where L= Schiff base ligand and M= Cr(III), Rh(III), Pt(IV) and Au(III), n= 1, 2. Based on spectroscopic analysis, coordination with metal ions involves the 'N' donor atom of N atoms of the imine and the N-H amid group, and four complexes are suggested to have a six-coordinated octahedral structure. Molar conductivity of these complexes showed that they were electrolytic in nature. In this study, the anticancer of the ligand and its metal complexes were investigated against MDA-MB-231 cell lines. Moreover, the in vitro efficacy them against Gram-negative bacteria (E. coli) and Gram-positive bacteria (S. aureus), as well as the fungal strain Candida albicans, was evaluated using the disc diffusion method. The results indicated that the complexes demonstrated the highest levels of cytotoxicity against MDA-MB-231 cell lines and antimicrobial activity more than the free ligand. These findings suggest that these metal complexes may have promising applications in the development of novel anticancer, antioxidant and antimicrobial agents.

The seasonal variation of phytoplankton and zooplankton groups in correlation with physio-chemical variables has been examined by monthly water samples from eight distinct locations in Smaquli Dam and Streams within Dolly Smaquli in Erbil city, Iraq. The sampling time spans from September 2021 to August 2022. Nineteen physical and chemical variables were examined including Air and water temperature, Electrical conductivity (EC), Total dissolved solids (TDS), Turbidity, pH, Dissolved oxygen (DO), Biochemical oxygen demand (BOD5), Total Alkalinity, Total Hardness, Nitrite (NO2), Nitrate (NO3), Reactive phosphate (PO4), Ca+2, Mg+2, Na+, K+, SO4-2 and Cl-. The findings about planktonic communities revealed a range of total zooplankton numbers, which varied from non-detectable to 17,833 individuals. l-3. The overall population of phytoplankton amounted to 2971 cells. l-1 to 3,832,590 cells. l-1. The phytoplankton productivity and zooplankton total number were higher at Dam impoundment sites compared with Stream sites. However, the direct grazing relationship of zooplankton on phytoplankton was noticed in both types of ecosystems. The observed fluctuations in plankton’s functional groups throughout different seasons underscore the significance of physical and chemical variables. Canonical Correspondence Analysis (CCA) between environmental variables and dominant groups of phytoplankton and zooplankton indicated that environmental variables such as Water temperature, pH, Turbidity, DO, BOD5 and Nutrients are important factors that influence on monthly variation of plankton functional groups in freshwater ecosystem. Nevertheless, the status of the Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) for all locations falls under the "Fair" category for drinking.

Biochar was previously confined to agriculture applications, but its utilization has since expanded across various sectors. In this case, sludge acquired from a sewage treatment facility was employed in the production of biochar. The study investigates the adsorption of cadmium in aqueous solution by both untreated biochar and biochar treated with H3PO4, examining the influence of adsorbent dosage, contact time, pH, and initial concentration. Phosphorus compounds present on the biochar surface activate it, enhancing cadmium removal compared to untreated biochar. The experimental results showed that the optimal dosage (1000 mg/l) and adsorption rate were significantly affected by pH. The Langmuir isotherm is more in accordance with the results of the experiment than other models, an indication that the majority of the adsorption is accomplished through monolayer chemical adsorption. The study determined that biochar derived from surplus sludge can be further utilized to serve as an economical adsorbent for the removal of Cadmium from wastewater.

The ability of Staphylococcus aureus enolase to cleave plasminogen has been thought to be important for bacterial virulence. The genetic variants of Eno gene sequences were investigated in the present study to assess the pattern of biological diversity of one isolate of S. aureus isolated from patients with diabetic food from Iraqi hospitals. The observed variant\'s possible impact in altering the enolase\'s binding with its receptor was assessed by docking with plasminogen before and after mutation. Within the locus 791st, two variations were identified with two different consequences since A>T791 (in S2, S3, S14, and S17) and A>C791 (in S8) had given one nonsense (p.268Kter) and one missense (p.K>Q268) variants. Furthermore, two variations were also identified in the 791st locus with two different consequences since T>G947 (in S2, S3, S17) and T>C947 (in S8) had given one missense (p.L>V320) and one silent (T>C947) variant. It was inferred from the tree that our investigated samples were positioned in two phylogenetic positions within the S. aureus sequences with a noticeable tilt from the nearest strains. While the majority of samples occupied one phylogenetic position, the mutant samples were positioned in another distant position. Docking of the S8-based enolase variant with plasminogen showed a critical alteration in the binding of both proteins compared with the wild-type interactions. Based on the identified p.K>Q268 variant, the main mechanism through which the mutant S8 variant develops to interact with the host immunity is explained. The isolates were named as S8 (∆eno1G), S2 (∆eno1L), and S5(WT).

Cytomegalovirus (CMV) is a common latent virus that can cause severe disease in immunocompromised individuals and pregnant women. Interleukins (ILs) are crucial for cell-to-cell communication and facilitate precise regulation of the immune response. The current study aimed to evaluate serum IL-35 and IL-39 levels in Iraqi women with CMV, particularly in pregnant women, and investigate their potential involvement in CMV infection and pregnancy. Serum samples were obtained from 115 women (age range:15–29 years), including CMV-infected pregnant women, uninfected pregnant women, CMV-infected non-pregnant women, and healthy non-pregnant women. IL-35 and IL-39 levels were measured using ELISA kits. Statistical analyses were performed using SPSS, and differences between groups were evaluated using t-tests, ANOVA, and correlation analyses. IL-35 levels were significantly elevated in CMV patients compared to controls (P ≤ 0.001). The mean serum IL-35 level was higher in infected non-pregnant women (8.755 ± 0.641 ng/ml) than in infected pregnant women (6.329 ± 0.649 ng/ml). IL-39 levels were significantly higher in infected non-pregnant women (37.083 ± 5.910 pg/ml) and lowest in infected pregnant women (22.296 ± 2.323 pg/ml). Age-related differences in cytokine levels were observed, and a significant negative correlation was found between IL-35 and IL-39 in infected non-pregnant women (r = -0.707, p =0.001). In conclusion, IL-35 and IL-39 may contribute to maintaining immune balance during CMV infection and pregnancy. Elevated IL-35 in CMV-infected women may reduce inflammation and promote immune tolerance, while lower IL-39 in infected pregnant women may reflect a weakened immune response and affect resistance against the virus.

Drosophila melanogaster is an agricultural insect pest. The female pierces crops and lays eggs. Then, the eggs hatch, after which the larvae begin to develop inside the tissue, feeding on it and destroying it. This study, conducted from 1/11/2023 to 15/12/2024, aims to ascertain the impact of secondary chemicals, in the wild Bacopa monnieri plant cultivated in Iraq on the development of insect life cycle stages using different concentrations (2000, 4000, 6000, 8000 ppm) under laboratory conditions. The data revealed that the eggs had the highest mortality rates at 8000 ppm for saponin and terpene 78.666% and 74% respectively. The larvae had the highest mortality rates of 59% and 78.333%, while the pupa had 79.666% and 74% mortality rates. In addition to pupae dying after being treated with saponin and terpene extracts, adults have also been seen to emerge partially. The results also exhibited abnormalities in the morphology of the D. melanogaster adults when the pupae were developed into the adult stage. Furthermore, the findings indicated that saponin and terpene exhibited a repellent impact on adult D. melanogaster, with the most potent repellent effect observed at a concentration of 8000 ppm, resulting in 76.6% and 76% repellency for saponin and terpene, respectively. This study proved that saponin and terpene significantly affected all insect stages and could play an essential role in the insect’s biological control.

The research investigates the use of silver nanoparticles (AgNPs) as a foliar spray at a concentration (50 mg/ml) on faba bean and potato plants to stimulate systemic acquired resistance (SAR) and suppress bean yellow mosaic virus (BYMV) and potato virus Y (PVY). The application of AgNPs reduced the percentage of virus reduction infection (RI) and disease severity (DS). AgNPs (50 mg/ml) was more effective on BYMV-infected faba bean (9.75 and 10.50) followed by PVY-infected potato (14.50 and 18.25) for the percentage of reduction infection and disease severity respectively. The mechanism of AgNPs involves binding to viral protein coats, aggregating virus particles, and preventing their spread in host cells. SDS-PAGE analysis revealed distinct protein patterns in AgNPs-treated plants infected with BYMV and PVY. Compared to untreated infected plants, the number of expressed proteins increased, with five bands observed in BYMV-infected plants and six bands in PVY-infected plants. RT-PCR analysis identified the transcriptional expression of pathogen-related proteins (PR-2), thereby inducing systemic resistance and indicating successful viral suppression. Infected treated plants with silver nanoparticles (50 mg/ml AgNPs) verified a reduction in photosynthetic pigments (chlorophyll and carotene), indicating a potential disruption in photosynthesis. Also, infected treated plants showed increased levels of total soluble protein (TSP), scavenging enzymes [Peroxidase (PO) and polyphenol oxidase (PPO)], proline, endogenous hormones (salicylic acid), and total phenolic compounds. The findings suggest that AgNPs, at the studied concentration, are promising multi-functional agents for inducing plant resistance, promoting growth, and generating bioactive compounds, offering an eco-friendly approach to disease control in agriculture.

Atmospheric stability is considered one of the most important factors affecting the increase or decrease in wind speed in the atmosphere and thus affecting the wind energy density. Stability conditions are classified into three categories: unstable, stable, and neutral. This study aims to analyze the stability of the atmospheric conditions in Southern Iraq, specifically in the Ali al-Gharbi region, using the Monin-Obukhov length method. Which includes field data for the wind speed at three altitudes (10m, 30m, and 50m) in 2017. The mean daily and seasonal friction velocities were calculated. Wind speed was calculated for different atmospheric stability conditions and its effect on wind power density and wind energy density for each case was studied. The monthly mean wind power density and wind energy density at heights (30 m and 50m) were estimated. The results showed that the highest values of friction velocity and wind speed were in the summer season, and the lowest values of friction velocity and wind speed were in the autumn season. The daily frictional velocity reaches its highest value at midday. The highest wind energy density was in stable conditions, followed by unstable conditions, while in neutral conditions, wind energy density was the lowest. Also, the highest values of wind power density and wind energy density were in June and July, and the lowest values of wind power density and wind energy density can be observed in January and February. From the results, conclude that the amount of wind energy production is high in stable Atmospheric conditions, and the highest wind energy density was in the summer season.

This work examines the production and analysis of electrospun fibers made from pure and CuO-doped polyvinylpyrrolidone (PVA) polymers. These fibers are then applied to glass and p-type silicon wafers. The ideal parameters for electrospinning were a flow rate of 0.5 ml/h, a voltage of 15 kV, and a distance of 16 cm between the collector and the needle. X-ray diffraction investigation determined that the PVA fibers were amorphous, but the CuO-doped samples had a tetragonal phase. Fourier Transform Infrared Spectroscopy (FTIR) was employed to examine the vibrational properties, modes, and network bonding in the 400 to 4000 cm⁻¹ spectral range. Scanning Electron Microscopy (SEM) analysis provided detailed analysis and yielded information on the structure, fibers' thickness, and CuO distribution. The UV-Vis spectral study showed that the optical band gap reduced from 2.7 eV (pure PVA) to 2.4 eV (10 wt.% CuO) as the quantity of CuO increased. Assesses the electrical behavior of the fibers by analyzing their current-voltage (I-V) characteristics in illuminated and non-illuminated circumstances. This analysis yields essential information about the fibers' response to light and their non-linear electrical properties, which are relevant for electronic and photovoltaic applications. The results emphasize the influence of CuO. The impact of doping on PVA fibers' structural, optical, and electrical properties indicates their potential for use in various electronic applications. A comprehensive approach offers fresh perspectives on the diverse capabilities and prospects of many electronic applications, highlighting the substantial influence of CuO doping in augmenting these features. Overall, the findings underscore the potential of CuO-doped PVA fibers in advancing electronic and optoelectronic technologies.

Laser-Induced Breakdown Spectroscopy (LIBS) has emerged as a powerful technique for analyzing materials through the creation of plasma by laser ablation. In this study, we present a comprehensive investigation of plasma parameters in an Fe target using LIBS spectroscopy. The experiment involved using a high-power laser to ablate the Fe target, generating a plasma plume that emitted characteristic spectral lines. By analyzing the emitted light, we extracted valuable information about the plasma parameters, including electron temperature, electron density, and ionization degrees. The LIBS setup was carefully calibrated and optimized to ensure accurate and reliable measurements. The obtained spectra were employed within the framework of the Boltzmann plot technique to determine plasma temperatures, where as the evaluation of electron density was accomplished through the utilization of Stark broadening analysis. The ascertained electron temperature values spanned from 12760 K to 13804 K for iron (Fe), accompanied by an electron density ranging between 2.72×1017 cm-3 and 3.62×1017 cm-3 for Fe. These derived electron temperature and density values subsequently served as pivotal inputs for the estimation of additional plasma parameters, including the Debye length, the particle count within the Debye sphere, and the plasma frequency.

Hilbert space has been improved by building on a fuzzy soft vector space. It is named the fuzzy soft Hilbert space. This space has been crucial to the development of functional analysis. Interest emerged in investigating fuzzy soft operators, results and other intriguing properties of quasi-hyponormal operators are obtained, as a result, circumstances surrounding the achievement of certain analytical traits are also looked at and their more general called perturbation fuzzy soft operators, many pertinent findings in the context of fuzzy soft operator theory, which we will use in our talks of certain analytical aspects pertaining to characterizations feature. This study presents perturbation fuzzy soft κ quasi hyponormal operator, referred to as the perturbation Fsκq-hyponormal operator, based on a special class of operators. Moreover, the connection of the attribute of this new operator to a class of operators which includes fuzzy soft κ quasi hyponormal operator posed on fuzzy soft vector space is examined and various theorems related to this operator have been investigated, along with some major characteristics of this operator. In addition, several algebraic attributes of this proposed operator are yielded including algebraic power, algebraic sum along with algebraic product.

The concepts of dual soft sets are introduced as general mathematical tools for transactions with a lack of confidence or certainty. This work defined the dual soft topology on a dual soft set and presented its related properties. The main goal of this research is to clarify the concepts of dense and nowhere dense sets on dual soft topological spaces as density plays a very important role in general topology for solving many mathematical and engineering problems. Our research paper presented the notions of dense, nowhere dense and somewhere dense within the dual soft set theory which in specific ways. The topological structure and the algebraic relationships between the dual soft dense sets, nowhere dense sets and somewhere dense sets have been discussed and well as their main characteristics as well as their necessary examples. A link has also been made between the concepts of the dual soft dense sets and dual soft nowhere dense sets with the dual soft super condensed sets, dual soft semi condensed sets and dual soft condensed sets. There are lots of research papers done by important mathematicians that have been published on this topic (which is density topological spaces). There were many important conclusions, results, theorems and effects about dense sets, nowhere dense sets and somewhere dense sets, so this sheet was collected and chose the most important of these results which are taken from all of these previous research papers and gave a share of our point of view in some new one in our research which affects our space which is dual soft topological space.

The finite element approach, which uses linear, quadratic, and cubic polynomials, can solve the elliptic form of the Poisson equation. This allows the method to provide a solution to the Poisson problem. This possibility arises from the structure within which the method operates. This work aims to provide an analysis of the technique in question and demonstrate its potential for applications in both square and circular dimensions. In conducting this investigation, a direct solution of the system of linear equations was used. Obtaining optimal error estimates in the L^2 and H^1 norms is possible for us if we choose to use numerical solutions and experimentation as our method of choice. This will enable us to achieve our goal. This article will present a range of examples that exemplify this concept, and its objective is to study the rates of convergence for cyclic and quadrilateral shapes. Additionally, the article will provide a variety of instances. The research presents a numerical representation of its findings. The research utilizes MATLAB R2018b to display the information in the form of graphics and tables. This has been done to provide a more realistic explanation of the facts presented.

Nonlinear analysis finds numerous applications in understanding the intricate characteristics of generalized Sierpinski graphs or chemical graphs. It aids in discerning the fractal patterns inherent in self-similar structures, deciphering the dynamic interactions within chemical bonds, and assessing the complexity of molecular arrangements. Furthermore, it plays a crucial role in unraveling the emergent behaviors of complex systems, offering insights applicable to diverse fields such as materials science, chemistry, biology, network theory, and beyond. In this paper, the complexity of generalized Sierpinski graphs and chemical graphs is analyzed using fractal-based nonlinear measures computed iteratively. Nonlinear measures assess intricate relationships within graphs by taking into account interactions that diverge from linear patterns. In particular, generalized Sierpinski graphs are derived from an increased number of iterative processes, which can also be viewed as a form of self-similar graph. The purpose of the study is to compare nonlinear measurements such as generalized fractal dimensions, Renyi entropy, and Tsallis entropy for extended Sierpinski graphs and benzenoid chemical graphs to understand the relationship among them. However, the benzenoid graph has self-similarity as a result of its chemical bonding structure. Furthermore, the paper assesses the efficacy of these methods in terms of iteration wise comparisons, employing a wide range of orders. The computational results in this paper indicate that the complexity of the representative graphs grows with the number of iterations, reflecting increased self-similarity as the values of fractal-based measures rise for both generalized Sierpinski graphs and benzenoid chemical graphs. This comparative research will enable us to quantify non-linearity and analyze self-similarity in real-time graphical networks or chemical structures.

In this study, the notion of the star operator and the class of weight functions defined on the entire natural number set N have been used to develop a version of the statistical cover of a topological space. In this version of statistical γ-cover, the pace of statistical convergence is mostly controlled by the selected weight function. A map g defined as g: N→[0,∞) such that lim┬(n→∞)⁡〖g(n)〗=∞ and lim┬(n→∞)⁡〖n/(g(n))〗≠0 is called a weight function. Relationships between several γ-cover variants have been established, and many counter instances have been offered to help differentiate between them. It has been established that every s_g-γ cover of a space is an s_g-St-γ cover for that space; every s_g-St-γcover is an s-St-γcover but the converse of these relations does not hold. The nature of weighted statistical γ-covers under various topological procedures and topological sub-spaces is investigated. The idea of an s_g-St-dense subset has been presented and it is observed that s_g-dense subset of an s_g-γ-cover is an s_g-γ-cover. An unsolved open problem is proposed to analyze the potential that an s_g-dense subset of an s_g-St-cover may not be an s_g-St- cover.

Lung diseases have newly increased, with lung cancer being the most serious, as a result of ‎the widespread use of electronic cigarettes and the high demand for them among youth. ‎Misdiagnosis of this disease has resulted in a high death rate around the world, which further ‎complicates matters. So the researchers have tended to concentrate on and study this illness. After ‎extracting the crucial characteristics for this cancer's classification, several studies implemented ‎multiple artificial intelligence algorithms with different techniques, nonetheless, the primary difference between those studies ‎persisted in the classification accuracy. In this paper, after selecting the methods of pre-processing ‎the data and extracting the critical features in addition to evaluating the strength of the associations ‎between the data variables by applying the correlation coefficient method. The K-Nearest Neighbor ‎‎(KNN) algorithm was implemented and tested after being enhanced by using the Random Forest (RF) ‎algorithm to classify lung cancer diseases. The experimental results after collecting lung cancer data set from ‎UCI's machine learning repository for diagnosing three types of cancers showed obtaining a ‎competitive classification accuracy of higher than 97.4 %. This competitive accuracy motivates us ‎and other researchers to use the proposed system to diagnose other types of diseases.

Improving the accuracy level of face recognition system is still an open research area where it consists of certain limitations to attain maximum accuracy. In earlier days, several algorithms are developed using machine learning and deep learning models, but still, they need improvement in terms of accuracy. For that purpose, in this article a novel CNN model called the optimized multi cascaded CNN (OPT-MTC-CNN) in the artificial intelligence system is developed, which helps to overcome the accuracy issues in face recognition system. The algorithms that are incorporated in this model are Fully Convolutional Network (FCN), Convolutional Neural Network (CNN), and Improved Non-Maximum Suppression (INMS). The implementation of this idea is performed in python, and the parameters that are calculated for its performance analysis are accuracy, precision, recall and f1-score. Additionally, certain parameters are measured to improve the network efficiency, such as specificity and sensitivity. The earlier methods that are utilized to perform the comparative analysis are CNN with Siamese network, pretrained CNN and Faster R-CNN. From the final obtained results, it gets proven that the proposed work attained 99% specificity, 98% sensitivity and 99.8% accuracy, which are better when compared with these earlier baseline methods.

Brain-computer interfaces (BCIs) provide direct drone control by interpreting motor imagery brain impulses. This review paper critically assesses the progress made in using hybrid neural networks and motor imagery to operate mind-controlled drones and addresses the challenges of encoding and decoding complex brain signals for precise and reliable drone control. In this review paper, the primary objective is to analyze and synthesize the latest brainwave analysis technologies, focusing on hybrid neural networks and motor imagery tasks for drone control via brain-computer interfaces. This study aims to provide insights into the effectiveness of these technologies in enhancing the accuracy and reliability of mind-controlled drone systems. The method of conducting the review process is PRSM. This review paper shows that signal analysis reliability dictates a model that accurately decodes motor imagery-related brain signals and converts them into drone control commands. The integration of machine learning algorithms with neurophysiological principles has demonstrated significant improvements in the performance of mind-controlled drone systems. In conclusion, the synergistic utilization of hybrid neural networks and motor imagery techniques holds great potential for advancing the field of mind-controlled drones. Further research and optimization of signal processing algorithms are essential for enhancing the speed, precision, and robustness of mind-controlled drone systems, ultimately leading to transformative advancements in human-machine interactions across various domains. This review paper lays the groundwork for future research endeavours aimed at unlocking the full potential of brainwave analysis for mind-controlled drones.

A region's economic activity has a significant impact on the growth of its surroundings. Adequate connectivity (e.g., toll roads, railways, airlines and others) are essential to the inter-regional economy and encourage new economic hub. Indonesia is intensively constructing toll road infrastructure and West Java province has the highest number of planned/operating it. This study aims to identify new economic hubs in West Java based on connectivity between regencies/cities with toll roads. The new hubs are identified by using a community detection approach. To support the idea, this study illustrates cities/regencies as vertices and connectivity of cities/regencies with toll roads as edges, resulting in a graph. The community detection algorithm breaks down into several sub-graphs and is evaluated using modularity. This study also presents suggestions of potential economic sectors that can be developed collaboratively among intra-cluster members. Five new economic hubs have been identified with modularity value = +0.63. The new economic hub in the northwestern part of West Java has potential in the industrial and tourism sectors. New economic hubs in central-northern West Java have potential in the industry, agriculture and tourism sectors. New economic hubs in eastern West Java have potential in the fisheries and tourism sectors. New economic hubs in western and southern West Java have potential in the agriculture and tourism sectors.

In today's globalized world, the pursuit of better opportunities has led to a significant increase in immigration and foreign labor. This trend is particularly evident in Bangladesh, where many workers migrate annually to destinations such as Malaysia, Qatar, Saudi Arabia, and the UAE. Understanding the sentiments and emotions of these workers is crucial to preventing crimes, suicides, political unrest, and other security issues in host countries. As maximum workers usually come from rural Bangladeshi communicate they use local dialect for conversations and very popular widely used local dialect known as Pabnaia. This study did not identify any prior research specifically focused on the local Bangla dialect, Pabnaia; therefore this research built new dataset. The aim of this research is to classify the sentiment of immigrants who use the Pabnaia dialect in their conversations, which may assist in mitigating the aforementioned risks of misunderstandings in immigrant-friendly countries. Pabnaia, widely used in various domains like drama and comedy in Bangladesh. Data were sourced from social media, comments, Bangla dramas, and translations from standard Bangla to Pabnaia, resulting in a dataset of over 2600 records and 22,000 unique words which was collected manually. TF-IDF vectorization was used for feature extraction, followed by basic machine learning algorithms such as Decision Tree, Support Vector Machine, and Naive Bayes. Deep learning techniques, including Deep Neural Network (DNN), Long short-term memory (LSTM), and convolutional neural network (CNN), demonstrated superior performance, where DNN achieving 83% accuracy and an 84% F1-score on the labelled dataset.

In this work, the authors introduce and study a new subclass of M_(∑_r)^(h,u) (γ,η,κ,λ), which is r-fold bi-univalent functions in open-unit disk A. Using the Rushwaya derivative operator, the study investigates the properties and behavior of an analytically generalized r-fold symmetric two-monovalent function in the open-unit disk A. The analysis calculates the Taylor-Maclarin coefficients |a_(r+1) | and |a_(2r+1) | , which represent one of its key terms these estimates M_(∑_r)^(h,u) (γ,η,κ,λ). Subclass of functions important for understanding analytical and geometric behavior they provide valuable insights into the development of these concepts and their relationship to the geometric properties of the functions. Furthermore, research goes beyond coefficient estimates to examine the significance of results. By analyzing this expression, the study highlights the circumstantial importance of the M_(∑_r)^(h,u) (γ,η,κ,λ) subclass plant. The importance of this new subclass is essentially its ability to add special information to specific operator users, as well as the inclusion of multiple values to increase its flexibility and robustness. Furthermore, by linking us to prior research in the field, the study strengthens the theoretical framework and deepens our understanding of these activities, thus contributing to extensive knowledge in this area.