Salahaddin University - Erbil

Blade design for a solar chimney power plant turbine is modeled geometrically. NACA 4412 blade is selected for its favorable lift to drag characteristics in the considered diameter range. The constructed model is integrated into a solar chimney plant and validated against existing examples in literature. A similar process is applied using a reverse fan model. Margins of discrepancies obtained from the turbine and reverse fan models are used as indicators for the total deviation expected from using the reverse fan model with a sloped collector plant. Here, the effect of turbine pressure change on the temperature rise and air flow are examined to set the upper limit of pressure drop and check the capacity of the system for power generation. The maximum air flow velocity at the center of the sloped collector reached 9.8 m/s. The highest achievable temperature difference was 37 °C. The favorable working zone for turbine operation inside the tower of a sloped collector solar chimney in terms of pressure drop and air flow rate is marked based on a constant efficiency.

In this paper, integrability and the global dynamics of two chaotic systems, Coullet and Malasoma systems, are studied. We mainly use the contradiction technique to show that both systems have no polynomial, Darboux and rational first integrals. Moreover, it is proved that the Cullet system has no analytic first integrals if some conditions on the parameters are satisfied. We also give a complete description of the dynamics at infinity by Poincaré compactification technique for both aforementioned systems.

In the present study, a novel series of azo-thiazole derivatives (3a–c) containing a thiazole moiety was successfully synthesized. The structure of these derivatives was examined by spectroscopic techniques, including 1H NMR, 13C NMR, FT-IR, and HRMS. Further, the novel synthesized compounds were evaluated for their in vitro biological activities, such as antibacterial and anti-inflammatory activities, and an in silico study was performed. The antibacterial results demonstrated that compounds 3a and 3c (MIC = 10 mg mL−1) have a notable potency against Staphylococcus aureus compared to azithromycin (MIC = 40 mg mL− 1). Alternatively, compound 3b displayed a four-fold higher potency (24 recovery days, 1.83 mg day−1) than Hamazine (28 recovery days, 4.14 mg day−1) in promoting burn wound healing, and it also exhibited a comparable inhibitory activity against screened bacterial pathogens compared to the reference drug. Docking on 1KZN, considering the excellent impact of compounds on the crystal structure of E. coli 1KZN, a 24 kDa domain, in complex with clorobiocin, indicated the close binding of compounds 3a–c with the active site of the 1KZN protein, which is consistent with their observed biological activity. Additionally, we conducted molecular dynamics simulations on the docked complexes of compounds 3a–c with 1KZN retrieved from the PDB to assess their stability and molecular interactions. Furthermore, we assessed their electrochemical characteristics via DFT calculations. Employing PASS and pkCSM platforms, we gained insights into controlling the bioactivity and physicochemical features of these compounds, highlighting their potential as new active agents.

This article focuses to extract the optical solitons in fiber optics modeled by (1 + 1)-dimensional coupled nonlinear Schrödinger equation (NLSE) by the assistance of truncated M-fractional derivative. Circularly polarized waves in fiber optics are described by the studied equation. The NLSEs have attracted greater attention due to their ability to effectively elucidate a diverse array of intricate physical phenomena and their capacity to exhibit deeper dynamical patterns through localised wave solutions. The solutions are obtained using the modified Sardar sub-equation method (MSSEM), which is a recently developed integration technique. Various types of optical pulses, including bright, dark, combo, and singular soliton solutions, are obtained. Considering appropriate parameters, a variety of graph shapes are sketched to describe the graphical presentation of the calculated outcomes. The findings indicate that the chosen technique is effective in improving nonlinear dynamical behaviour. We anticipate that many engineers who use engineering models will find this study to be of interest. The results validate the simplicity, effectiveness, and universality of the selected computational approach, even when applied to complex systems.

In this paper, we examine the optical solitons for the nonlinear doubly dispersive equation and the modified Boussinesq equation, which explain the flow of shallow water in a small-amplitude surface system. We realize a variety of solitons using the Sardar sub-equation approach, including bright solitons, dark solitons, singular solitons, mixed bright-singular solitons, periodic, exponential, and rational solutions. The generated optical solutions can be used to simulate water waves and the free movement of a fluid surface, both of which are important in computing models of nonlinear partial differential equations in science, engineering, and mathematical physics. For the physical interpretation of the data, the well-known symbolic software Mathematica 12 was employed.

In this research, it was proposed to create three new robust multivariate charts corresponding to the |S|‐ chart, which are robust to outliers, using three methods, an algorithm, namely the Rousseuw and Leroy algorithm, Maronna and Zamar, and the family of ‘concentration algorithms’ by Olive and Hawkins. Then the comparison between the proposed and classical method of the researcher Shewhart depends on the total variance (trace variance matrix), the general variance (determinant of the variance matrix), and the difference between the upper and lower control limits to obtain the most efficient charts against outliers through simulation and real data and using a program in the MATLAB language designed for this purpose. The study concluded that the proposed charts dealt with the problem of the influence of outliers and were more efficient than the classical method, in addition, the proposed robust chart (Orthogonalized Gnanadesikan‐Kettenring) was more efficient than the rest of the proposed charts.

Moringa leaves contain a proper amount of antioxidants, amino acids, vitamins, hormones, macronutrients, and micronutrients. Terefore, it is applied as a natural, inexpensive, and simple-to-make biostimulant to boost nutritional value and growth parameters in a variety of plants. Te main purpose of this study is to determine the optimal concentration of Moringa oleifera L. leaf extract (MLE) as an efective biostimulant to improve nutritional and physical quality in cabbage (Brassica oleracea var. capitata). To do this, three concentrations of MLE (6, 8, and 10%) were foliar sprayed to the plant leaves at a rate of 25 mL plant −1 for every two weeks from transplantation till harvest, while control plants (Ø) were sprayed with distilled water only. Our results show that MLE greatly increased cabbage growth, nutrient content, pigment content, and nutrient absorption, while a high concentration of 10% MLE could also signifcantly reduce nitrate content in cabbage leaves. In comparison to the control plants, sprays of 6%, 8%, and 10% MLE reduced nitrate content by 23%, 14%, and 12%, respectively. However, the lowest nitrate content was found for the plants sprayed with 6% MLE. Except for the dry matter, all the growth parameters, mineral content, and pigment content were signifcantly higher after spraying with 10% MLE, while better vitamin C and lower nitrate were found in the plants treated with 6% MLE. A Pearson correlation reveals that head weight has a positive correlation with head diameter, head height, chlorophyll a, and carotenoids at p levels of 0.01 and a positive correlation with chlorophyll b and vitamin C at p levels of 0.05. Vitamin C and dry matter, on the other hand, had a negative connection with nitrate content.

We have investigated the potential energy curves (PECs) of the LiN heteronuclear diatomic molecule, including its ionic species LiN+ and LiN−, using explicitly correlated multi-reference configuration interaction (MRCI-F12) calculations in conjunction with the correlation consistent quintuple-𝜁 basis set. The effect of core–valence correlation, scalar relativistic effects, and the size of the basis sets has been investigated. A comprehensive set of spectroscopic constants determined based on the above-mentioned calculations are also reported for the lowest electronic states and all systems, including dissociation energies, harmonic and anharmonic vibrational frequencies, and rotational constants. Additional parameters, such as the dipole moments, equilibrium spin-orbit constants, excitation energies, and rovibrational energy levels, are also documented. We found that the three triplet states of LiN, namely, X 3Σ−, A 3Π, and 2 3Σ−, exhibit substantial potential wells in the PEC diagrams, while the quintet states are repulsive in nature. The ground state of the anion also shows a deep potential well in the vicinity of its equilibrium geometry. In contrast, the ground and excited states of the cation are very loosely bound. Charge transfer properties of each of these states are also analyzed to obtain an in-depth understanding of the interatomic interactions. We found that the core–valence correlation has a substantial effect on the calculated spectroscopic constants.

This study involves a simulation-based optimization of a wavelength division multiplexing (WDM) in a passive optical network system, and an RZ modulator, with incorporating a vertical cavity surface emitting laser (VCSEL) and an edge-emitting (CW) laser alternately. Two scenarios have been proposed. First, 8 VCSEL/CW lasers, having distinctive frequency, are assigned for each user in the WDM PON. In the second scenario, only one optical source (193.1 THz) is employed to share among the eight users of the PON. The first scenario supports 5 Gbps up to 150 km fiber length, and comparably, the VCSEL-based system provides a better Q-factor performance comparable with the CW laser-based system. The second scenario confirmed the transmission of 20 Gbps up to 150 km by the VCSEL-based system, while the CW laser system allowed 20 Gbps up to only 100 km, while demonstrating a lower Q-factor.

The purpose of this review is to summarize the current literature on reductive C–N coupling of nitro compounds and boronic acids, with special emphasis on the mechanistic features of the reactions. The metal-catalyzed reactions are discussed first. This is followed by electro-synthesis and organophosphorus-catalyzed reactions. Finally, the available examples of catalyst-free reactions will be covered at the end of this review.

Many diseases and pests affect cucumber leaves as they grow. A lack of prompt control may result in reduced yields or crop failure. Early and correct detection of cucumber leaf diseases and pests is essential to prevent cucumber yield reduction. Manual detection consumes a large amount of human resources and exhibits poor real-time performance. In addition, there is a lack of public datasets for cucumber leaf disease images in real-world scenarios. To this end, firstly, this study collected and established a new cucumber leaf pest and disease dataset in a real-world scenario. Secondly, to accurately detect cucumber leaf diseases and pests, an improved cucumber leaf disease and pest detection model was proposed from scratch based on the original YOLOv5l model. To reduce the model size, the Bottleneck CSP module was used instead of C3 as the backbone and neck network section. Owing to the reduction in the number of parameters, number of layers, and calculations, the detection impact was significantly improved, in addition to that, the improved model able to detect even a small leaf spot of disease. Finally, the authenticity of the proposed model is demonstrated by incorporating the convolutional block attention module (CBAM) into both the improved and original YOLOv5l model. The experimental results showed that the mean average precision (mAP) of the improved model was 80.10%; whereas, the precision and recall were 73.8%, 73.9%, respectively. The improved model weight occupies only 13.6 MB of the memory. The overall improved model performance outperformed that of the original YOLOv5 model.

In this research the goal was to produce novel pyrimidine triazole compounds in high yields using triethylamin as an efficient catalyst. These new compounds were synthesized by using multicomponent reaction of aldehydes, guanidine, electron deficient acetylenic compounds, tert-butyl isocyanide and hydrazonoyle chloride in aqueous media. Due to the presence of an NH group, which was assessed using two different methodologies, newly synthesized pyrimidine triazoles have antioxidant properties. Additionally, the antibacterial activity of newly created pyrimidine triazoles was assessed using the disk distribution method with two different types of Gram-positive bacteria and Gram-negative bacteria, demonstrating that the use of these compounds prevented the growth of bacteria. Applied to the preparation of pyrimidine triazole derivatives, this method has short reaction times, high product yields, and the ability to separate catalyst and product using simple procedures.

The current research study includes a process of green safety method for synthesizing zinc oxide nanoparticles (ZnO NPs) from Musa paradisiaca L. leaf plant extract as an efficient chelating and capping agent for ZnO NPs from Zinc acetate dihydrate salt, and use with vinegar as a substitute of Carbaryl insecticide on Vicia faba plant. UV-Vis and FTIR studies of Musa paradisiaca L. leaf extract and ZnO NPs demonstrated that this plant is an excellent candidate for the green synthesis of ZnO NPs. From using various characterization techniques of XRD, FTIR, UV-Vis. spectroscopy and TEM, the structure, morphology, chemical composition and crystallinity of ZnO NPs were investigated. The XRD pattern spectrum and TEM, and FTIR confirmed the pure crystallinity and the spherical-shape of the hexagonal wurtzite ZnO NP structure with an average size 47 nm and with the measurement results of ZnO NPs band gap was around 4.52 eV. Seven treatments each with three replications were sprayed by the leaves including: 100 ppm ZnO NPs, 200 ppm ZnO NPs, 1% vinegar, 10% vinegar, recommended dose (1X) of Carbaryl, double dose (2X) of Carbaryl and a control (without any treatment). Following Carbaryl (2X) spraying, 100 ppm of ZnO NPs has shown the greatest effects on death rate and corrected mortality rate (Mc %) of Aphis fabae by values of 87.5% and 5.15% respectively. Moreover, 200 ppm ZnO NPs increased soil TDS and EC to 270.65 ± 0.029 ppm and 189.49 ± 0.003 µS.cm− 1 respectively. Thus, it can be concluded that the biosynthesized ZnO NPs and vinegar are good and natural substitutes of chemical pesticides.

Er + 3 doped lead-bismuth tellurite glasses with the composition (75-x) TeO 2 − 15 PbO – 10 Bi 2 O 3 - xEr 2 O 3 where (x = 0, 0.5, 1, 1.5, 2 and 2.5 mole%) were synthesized by using melt quenching technique. The influence of Er ³⁺ doping was evaluated through physical and optical properties. The non-crystalline nature of the samples was analyzed by XRD. The density of the samples was increased from 6.387 to 6.528 g.cm − 3 . The absorption spectra show eight transition bands corresponding to the transitions from ⁴ I 15/2 to ⁴ I 13/2, ⁴ I 11/2, ⁴ I 9/2, ⁴ F 9/2, ⁴ S 3/2, ⁴ H 11/2, ⁴ F 7/2 and ⁴ F 5/2, respectively. The experimental and calculated oscillator strengths were calculated based on the Judd-Ofelt theory. The intensity parameters follow the trend Ω 2 > Ω 6 > Ω 4 . Three emission bands were observed from the fluorescence spectra. The green transition ⁴ S 3/2 → ⁴ I 15/2 is the strongest among other transitions. The color coordinates were determined by using CIE 1931 chromaticity diagram. The highest quantum efficiency was 95.11% for the transition ⁴ S 3/2 → ⁴ I 15/2 . The results suggest that the TPBE2 glass is a great promising candidate for photonic applications and fabrication of laser optical devices.

In recent years, due to the dramatic increase of the bacteria resistance to antibiotics and chemotherapeutic drugs, an increasing importance is given to the discovery of novel bioactive molecules, more potent than those in use. In this contest, methanol extracts of different parts of the medicinal plant Limoniastrum monopetalum (L.) Boiss. (Plumbaginaceae), widely occurring in Tunisia, were prepared to evaluate the antimicrobial and antiproliferative activities. The methanol extract of the roots showed the highest antibacterial activity against E. coli, S. aureus and E. faecalis, whereas the stem extract exhibited the highest antiproliferative effects towards a Hela cell line. Analysis of volatile fractions, using gas chromatography–mass spectrometry (GC–MS) and gas chromatography–flame ionization detector (GC–FID) techniques, led to the identification of camphor as the most abundant constituent, which represented from 84.85 to 99.48% of the methanol extracts. Multiple chromatographic separation of the methanol leaf extract afforded the flavonoid maeopsin-6-O-glucoside (S1) and a few fractions that were subjected to biological activity assays. One fraction exhibited interesting antibacterial activity against E. coli and E. faecalis (MIC values of 62.5 and 78.12 µg/mL, respectively), and antiproliferative effects against Hela and A549 cells (IC50 = 226 and 242.52 μg/mL, respectively). In addition, in silico studies indicated that maesopsin-6-O-glucoside, which was moderately active against Staphylococcus aureus, strongly interacted with the active site of the accessory gene regulator protein A (AgrA) of Staphylococcus aureus.

Gastric cancer, particularly adenocarcinoma, is a significant global health concern. Environmental risk factors, such as Helicobacter pylori infection and diet, play a role in its development. This study aimed to characterize the chemical composition and evaluate the in vitro antibacterial and antitumor activities of an Aristolochia olivieri Colleg. ex Boiss. Leaves’ methanolic extract (AOME). Additionally, morphological changes in gastric cancer cell lines were analyzed. AOME was analyzed using HPLC-MS/MS, and its antibacterial activity against H. pylori was assessed using the broth microdilution method. MIC and MBC values were determined, and positive and negative controls were included in the evaluation. Anticancer effects were assessed through in vitro experiments using AGS, KATO-III, and SNU-1 cancer cell lines. The morphological changes were examined through SEM and TEM analyses. AOME contained several compounds, including caffeic acid, rutin, and hyperoside. The extract displayed significant antimicrobial effects against H. pylori, with consistent MIC and MBC values of 3.70 ± 0.09 mg/mL. AOME reduced cell viability in all gastric cancer cells in a dose- and time-dependent manner. Morphological analyses revealed significant ultrastructural changes in all tumor cell lines, suggesting the occurrence of cellular apoptosis. This study demonstrated that AOME possesses antimicrobial activity against H. pylori and potent antineoplastic properties in gastric cancer cell lines. AOME holds promise as a natural resource for innovative nutraceutical approaches in gastric cancer management. Further research and in vivo studies are warranted to validate its potential clinical applications.

Four novel seconeodolastane diterpenoids, named tricholomalides D–G, were isolated, together with the known tricholomalide C, from the fruiting bodies of Tricholoma ustaloides Romagn., a species belonging to the large Tricholoma genus of higher mushrooms (Basidiomycota, family Tricholomataceae). They were isolated through multiple chromatographic separations, and the structures, including the absolute configuration, were established through a detailed analysis of MS, NMR, and CD spectral data and comparison with related compounds reported in the literature, which has been thoroughly revised.

Radiogenomics is a newly emerging field that integrates genomics with medical imaging data. The aim of this field is to elucidate the associations between gene expression data and imaging phenotypes, especially in cancer. However, radiogenomics is hindered by the expensive cost of genetic screening tests which leads to the unavailability of numerous big datasets for paired imaging and genetic data. Big data is crucial for training machine learning-based techniques for analysis relating to radiogenic studies. Currently, fake data is generated on only one of the two radiogenomic types; genomic or medical imaging data are generated separately. In this paper, we propose a deepfake approach implemented by combining two Generative Adversarial Networks (GANs) to create fake image data that are hardly differentiable from the original to improve Breast cancer diagnosis. To evaluate the model, a survey is developed and distributed among the participants to measure their ability to differentiate the original from the Deepfakes images. The results showed that the model-generated fake images cannot be distinguished from the authentic images and are relatively satisfying using the PyTorch framework.