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The ongoing global public health challenge posed by the COVID-19 pandemic necessitates continuous research and surveillance efforts. In this study, we comprehensively analyzed over 1000 COVID-19 RT-PCR tests conducted on a cohort of 1200 patients in Saudi Arabia. Our primary goal was to investigate mutations in specific genes RdRp, N, and E different infection and recovery stages in Saudi patients with SARS-CoV-2. We also extended our analysis to include patients of various nationalities residing in Saudi Arabia, with the overarching objective of assessing these genes as markers for COVID-19 presence and progression. To diagnose and investigate potential genetic variations in COVID-19, we engaged RT-PCR. Our study primarily focused on detecting mutations in the RdRp, N, and E genes in Saudi patients with SARS-CoV-2, as well as individuals from various national residing in Saudi Arabia. This molecular technique provided valuable insights into the virus’s genetic makeup during infection and recovery. In our analysis of 671 positive COVID-19 cases, diverse gene involvement patterns were observed. Specifically, 55.91% had mutations in all three genes (RdRp, N, and E), 62.33% in both N and E genes, and 67.16% in RdRp and N genes. Additionally, 30.75% exhibited mutations exclusively in the RdRp gene, and 51.58% had mutations in the N gene. The N gene, in particular, showed high sensitivity as a marker for identifying active viral circulation. Regarding the temporal dynamics of the disease, the median duration between a positive and a subsequent negative COVID-19 RT-PCR test result was approximately 33.86 days for 44% of cases, 14.31 days for 30%, and 22.67 days for 4%. The insights from this study hold significant implications for managing COVID-19 patients during the ongoing pandemic. The N gene shows promise as a marker for detecting active viral circulation, potentially improving patient care and containment strategies. Establishing a defined positive threshold for diagnostic methods and correlating it with a low risk of infection remains a challenge. Further research is needed to address these complexities and enhance our understanding of COVID-19 epidemiology and diagnostics.

Background: Lower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorly understood. Objectives: We aim to evaluate (i) microstructural WM differences across MS patients (pwMS) with OAB symptoms, patients without LUT symptoms, and healthy subjects using diffusion tensor imaging (DTI), and (ii) associations between clinical OAB symptom scores and DTI indices. Methods: Twenty-nine female pwMS [mean age (SD) 43.3 years (9.4)], including seventeen with OAB [mean age (SD) 46.1 years (8.6)] and nine without LUT symptoms [mean age (SD) 37.5 years (8.9)], and fourteen healthy controls (HCs) [mean age (SD) 48.5 years (20)] were scanned in a 3T MRI with a DTI protocol. Additionally, clinical scans were performed for WM lesion segmentation. Group differences in fractional anisotropy (FA) were evaluated using tract-based spatial statistics. The Urinary Symptom Profile questionnaire assessed OAB severity. Results: A statistically significant reduction in FA (p = 0.004) was identified in microstructural WM in pwMS, compared with HCs. An inverse correlation was found between FA in frontal and parietal WM lobes and OAB scores (p = 0.021) in pwMS. Areas of lower FA, although this did not reach statistical significance, were found in both frontal lobes and the rest of the non-dominant hemisphere in pwMS with OAB compared with pwMS without LUT symptoms (p = 0.072). Conclusions: This study identified that lesions affecting different WM tracts in MS can result in OAB symptoms and demonstrated the role of the WM in the neural control of LUT functions. By using DTI, the association between OAB symptom severity and WM changes were identified, adding knowledge to the current LUT working model. As MS is predominantly a WM disease, these findings suggest that regional WM involvement, including of the anterior corona radiata, anterior thalamic radiation, superior longitudinal fasciculus, and superior frontal-occipital fasciculus and a non-dominant prevalence in WM, can result in OAB symptoms. OAB symptoms in MS correlate with anisotropy changes in different white matter tracts as demonstrated by DTI. Structural impairment in WM tracts plays an important role in LUT symptoms in MS.

The interest in hydrogen is rapidly expanding because of rising greenhouse gas emissions and the depletion of fossil resources. The current work focuses on employing affordable Al alloys for hydrogen production and storage to identify the most efficient alloy that performs best in each situation. In the first part of this work, hydrogen was generated from water electrolysis. The Al alloys that are being examined as electrodes in a water electrolyzer are 1050-T0, 5052-T0, 6061-T0, 6061-T6, 7075-T0, 7075-T6, and 7075-T7. The flow rate of hydrogen produced, energy consumption, and electrolyzer efficiency were measured at a constant voltage of 9 volts to identify the Al alloy that produces a greater hydrogen flow rate at higher process efficiency. The influence of the electrode surface area and water electrolysis temperature were also studied. The second part of this study examines these Al alloys’ resistance to hydrogen embrittlement for applications involving compressed hydrogen gas storage, whether they are utilized as the primary vessel in Type 1 pressure vessels or as liners in Type 2 or Type 3 pressure vessels. Al alloys underwent electrochemical charging by hydrogen and Charpy impact testing, after which a scanning electron microscope (SEM) was used to investigate the fracture surfaces of both uncharged and H-charged specimens. The structural constituents of the studied alloys were examined using X-ray diffraction analysis and were correlated to the alloys’ performance. Sensitivity analysis revealed that the water electrolysis temperature, electrode surface area, and electrode material type ranked from the highest to lowest in terms of their influence on improving the efficiency of the hydrogen production process. The 6061-T0 Al alloy demonstrated the best performance in both hydrogen production and storage applications at a reasonable material cost.

Reliability assessments are pivotal in evaluating system quality and have found extensive application in manufacturing. This research delves into a system comprising five components, one of which is a bridge network. The components are presumed to follow a Bilal lifetime distribution with a failure rate that changes over time. Four distinct methods are employed to enhance the components within the system. This study involves the computation of δ-fractiles and reliability equivalence factors (REFs). Additionally, a numerical case study is provided to elucidate the theoretical findings.

The particle swarm optimization (PSO) algorithm is widely used for optimization purposes across various domains, such as in precision agriculture, vehicular ad hoc networks, path planning, and for the assessment of mathematical test functions towards benchmarking different optimization algorithms. However, because of the inherent limitations in the velocity update mechanism of the algorithm, PSO often converges to suboptimal solutions. Thus, this paper aims to enhance the convergence rate and accuracy of the PSO algorithm by introducing a modified variant, which is based on a hybrid of the PSO and the smell agent optimization (SAO), termed the PSO-SAO algorithm. Our specific objective involves the incorporation of the trailing mode of the SAO algorithm into the PSO framework, with the goal of effectively regulating the velocity updates of the original PSO, thus improving its overall performance. By using the trailing mode, agents are continuously introduced to track molecules with higher concentrations, thus guiding the PSO’s particles towards optimal fitness locations. We evaluated the performance of the PSO-SAO, PSO, and SAO algorithms using a set of 37 benchmark functions categorized into unimodal and non-separable (UN), multimodal and non-separable (MS), and unimodal and separable (US) classes. The PSO-SAO achieved better convergence towards global solutions, performing better than the original PSO in 76% of the assessed functions. Specifically, it achieved a faster convergence rate and achieved a maximum fitness value of −2.02180678324 when tested on the Adjiman test function at a hopping frequency of 9. Consequently, these results underscore the potential of PSO-SAO for solving engineering problems effectively, such as in vehicle routing, network design, and energy system optimization. These findings serve as an initial stride towards the formulation of a robust hyperparameter tuning strategy applicable to supervised machine learning and deep learning models, particularly in the domains of natural language processing and path-loss modeling.

Historically, the photocatalytic efficacy of graphitic carbon nitride (g-C3N4) has been constrained by a rapid charge recombination rate and restricted sensitivity to visible light. To overcome these limitations and enhance the performance of g-C3N4, the strategic formation of heterojunctions with semiconductor materials is deemed the optimal approach. The present study employed a facile sonication-assisted pyrolysis method to synthesize a g-C3N4@ZrO2 nanocomposite photocatalyst. This hybrid material was characterized extensively using a comprehensive suite of analytical techniques, including XRD, SEM, EDX, FTIR, and UV-Vis DRS. A comparative analysis of photocatalytic applications under identical conditions was conducted for all synthesized materials, wherein they were subjected to UVc light irradiation. The photocatalytic degradation of various dye models, such as MB, EY, and a combination of dyes, was assessed using the prepared nanocomposites. The g-C3N4@ZrO2 photocatalysts showcased superior photocatalytic performance, with a particular variant, g-CNZ6, exhibiting remarkable activity. With a bandgap energy of 2.57 eV, g-CNZ6 achieved impressive degradation efficiencies of 96.5% for MB and 95.6% for EY within 40 min. Following previous studies, the superoxide radical anions (O2−. and h+) were largely accountable for the degradation of MB. Therefore, the observed efficacy of the g-C3N4@ZrO2 nanocomposite photocatalyst can be attributed to the increased generation of these reactive species.

Thiazole and thiazolidinone recur in a wide range of biologically active compounds that reach different targets within the context of tumors and represent a promising starting point to access potential candidates for treating metastatic cancer. Therefore, searching for new lead compounds that show the highest anticancer potency with the fewest adverse effects is a major drug-discovery challenge. Because the thiazole ring is present in dasatinib, which is currently used in anticancer therapy, it is important to highlight the ring. In this study, cycloalkylidenehydrazinecarbothioamides (cyclopentyl, cyclohexyl, cyclooctyl, dihydronapthalenylidene, flurine-9-ylidene, and indolinonyl) reacted with 2-bromoacetophenone and diethylacetylenedicarboxylate to yield thiazole and 4-thiazolidinone derivatives. The structure of the products was confirmed by using infrared (IR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and single-crystal X-ray analyses. The antiproliferative activity of the newly synthesized compounds was evaluated. The most effective inhibitory compounds were further tested in vitro against both epidermal growth factor receptor (EGFR) and B-Raf proto-oncogene, serine/threonine kinase (BRAFV600E) targets. Additionally, molecular docking analysis examined how these molecules bind to the active sites of EGFR and BRAFV600E.

According to data provided by the World Health Organization (WHO), a total of 2.3 million women across the globe received a diagnosis of breast cancer in the year 2020, and among these cases, 685,000 resulted in fatalities. As the incidence of breast cancer statistics continues to rise, it is imperative to explore new avenues in the ongoing battle against this disease. Therefore, a number of new indolyl-hydrazones were synthesized by reacting the ethyl 3-formyl-1H-indole-2-carboxylate 1 with thiosemicarbazide, semicarbazide.HCl, 4-nitrophenyl hydrazine, 2,4-dinitrophenyl hydrazine, and 4-amino-5-(1H-indol-2-yl)-1,2,4-triazole-3-thione to afford the new hit compounds, which were assigned chemical structures as thiosemicarbazone 3, bis(hydrazine derivative) 5, semicarbzone 6, Schiff base 8, and the corresponding hydrazones 10 and 12 by NMR, elemental analysis, and X-ray single-crystal analysis. The MTT assay was employed to investigate the compounds’ cytotoxicity against breast cancer cells (MCF-7). Cytotoxicity results disclosed potent IC50 values against MCF-7, especially compounds 5, 8, and 12, with IC50 values of 2.73 ± 0.14, 4.38 ± 0.23, and 7.03 ± 0.37 μM, respectively, compared to staurosproine (IC50 = 8.32 ± 0.43 μM). Consequently, the activities of compounds 5, 8, and 12 in relation to cell migration were investigated using the wound-healing test. The findings revealed notable wound-healing efficacy, with respective percentages of wound closure measured at 48.8%, 60.7%, and 51.8%. The impact of the hit compounds on cell proliferation was assessed by examining their apoptosis-inducing properties. Intriguingly, compound 5 exhibited a significant enhancement in cell death within MCF-7 cells, registering a notable increase of 39.26% in comparison to the untreated control group, which demonstrated only 1.27% cell death. Furthermore, the mechanism of action of compound 5 was scrutinized through testing against kinase receptors. The results revealed significant kinase inhibition, particularly against PI3K-α, PI3K-β, PI3K-δ, CDK2, AKT-1, and EGFR, showcasing promising activity, compared to standard drugs targeting these receptors. In the conclusive phase, through in vivo assay, compound 5 demonstrated a substantial reduction in tumor volume, decreasing from 106 mm³ in the untreated control to 56.4 mm³. Moreover, it significantly attenuated tumor proliferation by 46.9%. In view of these findings, the identified leads exhibit promises for potential development into future medications for the treatment of breast cancer, as they effectively hinder both cell migration and proliferation.

The area coverage problem solution is one of the vital research areas which can benefit from swarm robotics. The greatest challenge to the swarm robotics system is to complete the task of covering an area effectively. Many domains where area coverage is essential include exploration, surveillance, mapping, foraging, and several other applications. This paper introduces a survey of swarm robotics in area coverage research papers from 2015 to 2022 regarding the algorithms and methods used, hardware, and applications in this domain. Different types of algorithms and hardware were dealt with and analysed; according to the analysis, the characteristics and advantages of each of them were identified, and we determined their suitability for different applications in covering the area for many goals. This study demonstrates that naturally inspired algorithms have the most significant role in swarm robotics for area coverage compared to other techniques. In addition, modern hardware has more capabilities suitable for supporting swarm robotics to cover an area, even if the environment is complex and contains static or dynamic obstacles.

The synthesis of 4-methyl/phenyl-1,2,5,6-tetraazafluoranthen-3(2H)-one 4 and 7 has been reported with ninhydrin via a reaction first with ethyl acetoacetate or ethyl benzoylacetate and then a reaction of the resultant esters with hydrazine hydrate. The mechanism of hydrazinolysis and cyclization to obtain tetraazafluoranthen-3(2H)-ones is ambiguous, and the previously proposed mechanism was not based on facts because the actual intermediates were not isolated. Herein, the important intermediates involved in the hydrazinolysis–cyclization mechanistic pathway were isolated and characterized using NMR and X-ray single-crystal analysis. The intermediates demonstrate that the reaction carried out via two hydrazinolysis–cyclization reactions, the first of which includes the condensation of one hydrazine molecule with two ketone groups and the second of which includes the reaction of another hydrazine molecule with the ester and then condensation with the other ketone group. The stability of hydrazide 11 enabled the hydrazine to reduce the carbonyl of the ketone group to form 12 via a Wolff–Kishner-like reduction. The structure of the three intermediates was confirmed using X-ray crystallographic analysis. It was found that the three fused ring systems deviated from planarity to different extents, with their deviation from being coplanar reaching up to 5.3°. The possible non-covalent interactions which control the molecular packing of these intermediates were elucidated with the aid of Hirshfeld analysis.

The treatment of N-Phenylmorpholine-4-carbothioamide (HPMCT) with bivalent metal ions in a 2:1 mol ratio without a base present affords [MCl2(κ1S-HPMCT)2] {M = Cu(1), Pd(2), Pt(3), and Hg(4)} in a good yield. Furthermore, the reaction of two equivalents of HPMCT and one equivalent of bivalent metal ions in the presence of Et3N has afforded [M(κ2S,N-PMCT)2] {M = Ni(5), Cu(6), Pd(7), Pt(8), Zn(9), Cd(10), and Hg(11)}. Infrared, 1H, 13C Nuclear Magnetic Resonance molar conductivity, and elemental analysis were used to characterize the synthesized complexes. The results suggest that HPMCT is bonded as monodentate via an S atom in Complexes (1–4), whereas linkage as a bidentate chelating ligand via S and N atoms gives two chelate rings. Moreover, the synthesized ligand and the complexes were screened for antibacterial activity, which displayed that the very best antibacterial activities for Complexes (1), (6), and (3). In addition, the cytotoxic activity of the HPMCT ligand, [PdCl2(HPMCT)2] (2), and [PtCl2(HPMCT)2] (3) were screened on breast cancer cell lines (MCF-7), and Complex (3) reveals the most promising activity with an IC50 value 12.72 ± 0.4 μM. Using the B3LYP method and 6-311++G(d,p) basis sets for the ligand and the SDD basis set for the central metal, the synthesized complexes utilizing the prepared ligand were optimized. Various quantum parameters such as hardness, electron affinity, dipole moment, vibrational frequencies, and ionization energy for the ligand and its complexes have been calculated. In general, a favorable agreement was found between the experimental results and the obtained theoretical results.

The regiospecific S-benzylation/allylation of two 4-aryl-5-indolyl-1,2,4-triazole-3-thione precursors was carried out using Et3N as a base. Allyl group migration from exocyclic sulfur to the triazole nitrogen (N3) was successfully achieved in a short time via thermal fusion without the need for any catalyst. The allylation of indole nitrogen, along with exocyclic sulfur or triazole nitrogen (N3), was carried out using K2CO3 as stronger base. S,N-Diallylated products were converted to N,N-diallylated analogues using a simple fusion approach. Structural analyses of the two newly synthesized hybrids 2b and 5b investigated via the X-ray diffraction of a single crystal combined with Hirshfeld calculations. The compound 5b was crystallized in a monoclinic crystal system and the P21/c space group, whereas in compound 2b, the crystal system comprises the less symmetric triclinic and P − 1 space group. The asymmetric unit contains one and two molecules of 5b and 2b, respectively, while the unit cell contains four molecules in both cases. Hirshfeld analysis was performed in both systems to analyze the non-covalent interactions that control molecular packing. For 5b, C…H, N…H, S…H, Cl…N and H…H interactions are the most significant. Their percentages are 23.7, 8.8, 4.5, 1.2 and 48.2, respectively. In the case of 2b, the Cl…C, S…N, C…H, H…H and N…H interactions have the upper hand in molecular packing. In one unit, the percentages of these contacts are 2.3, 0.9, 26.8, 38.7 and 9.3%, while in the other unit, the corresponding values are 4.4, 1.3, 22.1, 43.6 and 9.0%, respectively.

The hit compound 1,2,4-triazolo[4’,3’:2,3]pyridazino[4,5-b]indole 3 was synthesized from the reflux of 4-amino-5-indolyl-1,2,4-triazole-3-thione 1 with 4′-bromoacetophenone 2 in methanol catalyzed by concentrated HCl and the desired final molecule was obtained by recrystallization from methanol. The suggested structures of compounds 1 and 3 based on the spectral characterizations were confirmed by X-ray single crystal diffraction analysis. Compound 3 crystallized in the triclinic crystal system and P-1 space group with a = 5.9308(2) Å, b = 10.9695(3) Å, c = 14.7966(4) Å, α = 100.5010(10)°, β = 98.6180(10)°, and γ = 103.8180(10)°. On the other hand, the crystal system of 1 is monoclinic, where a = 6.23510(10) Å, b = 26.0156(4) Å, c = 12.4864(2) Å, β = 93.243(2)° and the space group is P21. The triazole and indole rings are found twisted from each other in both compounds. The twist angle is higher in 3 (12.65°) than 1 (4.94–7.22°). In the case of the former, the H…H (39.6%), H…C (22.0%), N…H (12.8%) and Br…H (13.2%) contacts are the most dominant while the C…C, C…H, Br…H, N…H and S…S contacts have the characteristics of strong interactions. In the latter, the C…H, N…H, S…H, S…S, and C…C contacts are the most important. In this case, the percentages of the H…H, C…H, N…H and S…H contacts are in the range of 34.9–37.4, 20.5–24.0, 12.2–13.6, 14.0–15.8, respectively. In both systems, the shape index and curvedness of surfaces confirmed the presence of π–π stacking interactions.

The transition to Electric Vehicles (EV) in place of traditional internal combustion engines is increasing societal demand for electricity. The ability to integrate the additional demand from EV charging into forecasting electricity demand is critical for maintaining the reliability of electricity generation and distribution. Load forecasting studies typically exclude households with home EV charging, focusing on offices, schools, and public charging stations. Moreover, they provide point forecasts which do not offer information about prediction uncertainty. Consequently, this paper proposes the Long Short-Term Memory Bayesian Neural Networks (LSTM-BNNs) for household load forecasting in presence of EV charging. The approach takes advantage of the LSTM model to capture the time dependencies and uses the dropout layer with Bayesian inference to generate prediction intervals. Results show that the proposed LSTM-BNNs achieve accuracy similar to point forecasts with the advantage of prediction intervals. Moreover, the impact of lockdowns related to the COVID-19 pandemic on the load forecasting model is examined, and the analysis shows that there is no major change in the model performance as, for the considered households, the randomness of the EV charging outweighs the change due to pandemic.

Permanent magnet (PM) machines with fractional slot concentrated windings (FSCW) constitute a notably remarkable proposition for electric vehicles. Additionally, an integrated onboard battery charger (IOBC) provides another superiority as it exploits the components of the powertrain to charge the battery without any additional components. Interior permanent magnet (IPM) motor arises as a credible choice due to its high torque density, resulting from the high saliency ratio. The optimal design of an IPM motor has been extensively presented from different perspectives, but the optimal design of a motor employed for IOBC application for both propulsion and charging modes has not been studied extensively. In this paper, the design and optimization of a 12-slot/10-pole IPM motor with IOBC are studied under both propulsion and charging modes. A finite-element-based optimization with the aid of a genetic algorithm technique is proposed to obtain the optimal machine by maximizing the average torque and minimizing the torque ripple, core losses, and magnet size.

5-(1H-Indol-2-yl)-4-phenyl-2,4-dihydro-3H-1,2,4-triazole-3-thione 1a and 4-(4-chlorophenyl)-5-(1H-indol-2-yl)-2,4-dihydro-3H-1,2,4-triazole-3-thione 1b were galactosylated in the presence of NaHCO3 in ethanol to produce S-galactosides 3,4, whereas, in the presence of K2CO3 in acetone they produced a mixture of S- and N-galactosides 3-6 with a higher yield of S-galactosides over the respective N-galactosides. Improvement in the yields of N-galactosides was produced by thermal migration of the galactosyl moiety from sulfur to nitrogen using fusion. β-Stereoselectivity of galactosylation was determined using the coupling constant value 3J1,2, which exceeded 9.0 Hz in all prepared galactosides. The precursors 1a and 1b alkylated with 3-bromopropan-1-ol 7 in K2CO3 and acetone produced the S-alkylated products 8 and 9, respectively. Structural determinations of new compounds 5 and 9 are presented. The phenyl and indole moieties were found to be twisted from the triazole ring mean in both compounds. For compound 5, the twist angles were 66.24° and 18.86°, respectively, while the corresponding values for 9 were in the ranges of 73.15–77.29° and 13.96–20.70°, respectively. Hence, the crystal system of 9 is triclinic while the space group is P-1. Detailed analysis of the intermolecular interactions in the crystal structure of 5 is presented using Hirshfeld calculations. The O…H, N…H, C…H, and S…H contacts appeared as red spots in the dnorm Hirshfeld surface indicating short distance intermolecular interactions. Their percentages were estimated based on the decomposition of the fingerprint plot to be 25.6, 2.4, 14.0, and 6.3%, respectively.

Wound healing is regulated by complex crosstalk between keratinocytes and other cell types, including stem cells. In this study, a 7-day direct co-culture model of human keratinocytes and adipose-derived stem cells (ADSCs) was proposed to study the interaction between the two cell types, in order to identify regulators of ADSCs differentiation toward the epidermal lineage. As major mediators of cell communication, miRNome and proteome profiles in cell lysates of cultured human keratinocytes and ADSCs were explored through experimental and computational analyses. GeneChip® miRNA microarray, identified 378 differentially expressed miRNAs; of these, 114 miRNAs were upregulated and 264 miRNAs were downregulated in keratinocytes. According to miRNA target prediction databases and the Expression Atlas database, 109 skin-related genes were obtained. Pathway enrichment analysis revealed 14 pathways including vesicle-mediated transport, signaling by interleukin, and others. Proteome profiling showed a significant upregulation of the epidermal growth factor (EGF) and Interleukin 1-alpha (IL-1α) compared to ADSCs. Integrated analysis through cross-matching the differentially expressed miRNA and proteins suggested two potential pathways for regulations of epidermal differentiation; the first is EGF-based through the downregulation of miR-485-5p and miR-6765-5p and/or the upregulation of miR-4459. The second is mediated by IL-1α overexpression through four isomers of miR-30-5p and miR-181a-5p.

Recently, deep learning and the Internet of Things (IoT) have been widely used in the healthcare monitoring system for decision making. Disease prediction is one of the emerging applications in current practices. In the method described in this paper, lung cancer prediction is implemented using deep learning and IoT, which is a challenging task in computer-aided diagnosis (CAD). Because lung cancer is a dangerous medical disease that must be identified at a higher detection rate, disease-related information is obtained from IoT medical devices and transmitted to the server. The medical data are then processed and classified into two categories, benign and malignant, using a multi-layer CNN (ML-CNN) model. In addition, a particle swarm optimization method is used to improve the learning ability (loss and accuracy). This step uses medical data (CT scan and sensor information) based on the Internet of Medical Things (IoMT). For this purpose, sensor information and image information from IoMT devices and sensors are gathered, and then classification actions are taken. The performance of the proposed technique is compared with well-known existing methods, such as the Support Vector Machine (SVM), probabilistic neural network (PNN), and conventional CNN, in terms of accuracy, precision, sensitivity, specificity, F-score, and computation time. For this purpose, two lung datasets were tested to evaluate the performance: Lung Image Database Consortium (LIDC) and Linear Imaging and Self-Scanning Sensor (LISS) datasets. Compared to alternative methods, the trial outcomes showed that the suggested technique has the potential to help the radiologist make an accurate and efficient early lung cancer diagnosis. The performance of the proposed ML-CNN was analyzed using Python, where the accuracy (2.5–10.5%) was high when compared to the number of instances, precision (2.3–9.5%) was high when compared to the number of instances, sensitivity (2.4–12.5%) was high when compared to several instances, the F-score (2–30%) was high when compared to the number of cases, the error rate (0.7–11.5%) was low compared to the number of cases, and the computation time (170 ms to 400 ms) was low compared to how many cases were computed for the proposed work, including previous known methods. The proposed ML-CNN architecture shows that this technique outperforms previous works.

The present synthetic strategy involves the synthesis of indolyl-triazolo-thiadiazole heterocyclic ring systems 8–13 from the condensation of 4-amino-5-(1H-indol-2-yl)-3H-1,2,4-triazole-3-thione 1 with the aromatic carboxylic acid derivatives 2–7 in presence of POCl3 for 1 h. All compounds were obtained in very good yields and have been well-characterized using spectroscopic techniques. Exclusively, good quality crystals from the target organic hybrid 8-(1H-indol-2-yl)-5-(p-tolyl)-[1,2,4]triazolo [3,4-b][1,3,4]thiadiazole 9 were obtained and found suitable for X-ray single crystal diffraction measurement, which is used to confirm and analyze the molecular and supramolecular structure aspects of 9. The solid-state structure of the synthesized molecule 9 agrees very well with other characterizations. The packing of 9 is dominated by the N…H, S…H, C…C and S…C non-covalent interactions, which agree with the Hirshfeld surface analysis. The percentages of these contacts are calculated to be 20.3%, 5.4%, 9.4% and 4.3%, respectively.

The novel hydrazone-containing thieno[2,3-d]pyrimidine, namely, N′-(1,3-dioxo-1,3-dihydro-2H-inden-2-ylidene)-2-(4-oxo-5,6,7,8-tetrahydrobenzo[4,5]thieno[2,3-d]pyrimidin-3(4H)-yl)acetohydrazide 4 was synthesized in a very good yield from the reaction of the triketoester 1 or ninhydrin 2 with the exocyclic acetohydrazide 3 in methanol. Good-quality crystals of 4 were obtained by recrystallization of the compound from the DMF/MeOH solvent mixture. The target product 4 crystallized in the triclinic crystal system and P-1 space group. The topology analysis of molecular packing indicated that the H…H (30.4%), O…H (22.0%) and H…C (17.0%) contacts are the most dominant intermolecular interactions in the crystal of 4, while the O…H, N…H, H…C, N…C, O…C, C…C and O…O are the only contacts which have shorter interaction distances than the vdWs radii sum of the interacting atoms. The structure of 4 is optimized and the calculated structure showed good agreement with the experimental one. Additionally, MEP, HOMO, LUMO and the reactivity descriptors were calculated.

The Internet of Things (IoT) has been influential in predicting major diseases in current practice. The deep learning (DL) technique is vital in monitoring and controlling the functioning of the healthcare system and ensuring an effective decision-making process. In this study, we aimed to develop a framework implementing the IoT and DL to identify lung cancer. The accurate and efficient prediction of disease is a challenging task. The proposed model deploys a DL process with a multi-layered non-local Bayes (NL Bayes) model to manage the process of early diagnosis. The Internet of Medical Things (IoMT) could be useful in determining factors that could enable the effective sorting of quality values through the use of sensors and image processing techniques. We studied the proposed model by analyzing its results with regard to specific attributes such as accuracy, quality, and system process efficiency. In this study, we aimed to overcome problems in the existing process through the practical results of a computational comparison process. The proposed model provided a low error rate (2%, 5%) and an increase in the number of instance values. The experimental results led us to conclude that the proposed model can make predictions based on images with high sensitivity and better precision values compared to other specific results. The proposed model achieved the expected accuracy (81%, 95%), the expected specificity (80%, 98%), and the expected sensitivity (80%, 99%). This model is adequate for real-time health monitoring systems in the prediction of lung cancer and can enable effective decision-making with the use of DL techniques.

This study introduces a step-by-step, summarized overview of direct methanol fuel cell (DMFC) fundamentals, thermodynamic–electrochemical principles, and system evaluation factors. In addition, a parametric investigation of a JENNY 600S DMFC is conducted to simulate cell performance behavior under varying operating conditions. The system is mathematically modeled and solved in MATLAB and accounts for multi-irreversibilities such as the activation and ohmic and concentration overpotentials. The performance of the modeled system was validated against theoretical and experimental results from the literature. The results indicated that increasing the fuel cell’s operating temperature yields enhanced output cell voltages due to enhanced methanol oxidation reactions. Nevertheless, the maximum efficiency limits of the fuel cell tend to decrease with an increase in temperature. In addition, the model has also depicted that enhanced output cell voltages are associated with increased oxygen consumption, resulting in the lower exit flowrates of the reactants.

A new one parameter distribution recently was proposed for modelling lifetime data called half logistic-geometric (HLG) distribution. In this paper, appropriate transformation is considered for HLG distribution and a new distribution is derived called unit half logistic-geometric (UHLG) distribution for modelling bounded data in the interval (0, 1). Some important statistical properties are investigated with a closed form quantile function. Some methods of parameter estimation are introduced to evaluate the distribution parameter and a simulation study is introduced to compare these different methods. A real data application in the insurance field is introduced to show the flexibility of the new distribution modelling such data comparing with other distributions.

Transforming Growth Factor- β Receptor type 1 (TGF-βR1) is an important anticancer target involved in promoting cell proliferation, progression, and metastasis through the induction of angiogenesis and suppression of immunological responses during the late stage of malignancy. Tranilast was initially approved for the treatment of bronchial asthma and allergic conditions in 1982. Later, it was revealed that Tranilast had numerous effects on cancer hallmarks, including immune evasion and sustained proliferation via the inhibition of TGF-βR1. This research describes the design of a novel series of anthranilate derivatives having various modes of interactions with TGF-βR1 compared with Tranilast. A database of novel Tranilast analogues was generated using Molecular Operating Environment Software (MOE 2020.09, Chemical Computing Group CCG, Montréal, Canada) using fragment-based drug design. Representative compounds were selected from the database and docked in the identified binding site of TGF-βR1. Several compounds showed higher binding affinity for TGF-βR1 compared with the lead compound in this work, Tranilast. Compounds with high docking scores contained a positively charged amine group that interacted with Asp290 or a negatively charged carboxylate group with Lys 335 in the TGF-βR1 ATP binding site. Additionally, compounds containing an aromatic group showed high docking scores through interacting with Ser287, Lys337, or Ile 211. Compounds A11, A14, A16, and B5 which had the best poses in terms of binding interactions and docking scores to the binding site will be considered for further synthesis and biological evaluation.

Environment-friendly materials (e.g., Honey and Mint) are used as corrosion inhibitors for aluminum in hydrochloric acid (HCl) using both the density functional theory (DFT) at the B3LYP/6–31G* basis set level and semi-empirical methods (AM1, PM3, MINDO, and RM1). The aim of this study is to investigate the inhibition efficiency (%IE) in terms of their molecular structure. The quantum chemical parameters such as the highest occupied molecular orbital energy (EHOMO), the lowest unoccupied molecular orbital energy (ELUMO), the energy gap (ΔE), the charge on the reactive core, the hardness (η), and the total energy have all been computed. The MINDO method was used to measure the electronic energies and charge densities of the inhibitors that were used. Theoretical calculations were also carried out, with the findings correlating well with the experimental data. Gravimetry and gasometry measurements were used to investigate the effects of honey and mint on aluminum corrosion in a 1.0 M hydrochloric acid (HCl) solution. In acid solutions, honey and mint were found to be effective inhibitors of aluminum corrosion, with honey being the better option. Because of the adsorption of its components on aluminum surfaces, the inhibitory effect of the used inhibitors was addressed. The higher dipole moment of honey than that of mint caused the adsorption of honey on the aluminum surface better. The IEs measured by gravimetry and gasometry are almost identical.

Cell regenerative therapy is a modern solution for difficult-to-heal wounds. Keratinocytes, the most common cell type in the skin, are difficult to obtain without the creation of another wound. Stem cell differentiation towards keratinocytes is a challenging process, and it is difficult to reproduce in chemically defined media. Nevertheless, a co-culture of keratinocytes with stem cells usually achieves efficient differentiation. This systematic review aims to identify the secretions of normal human keratinocytes reported in the literature and correlate them with the differentiation process. An online search revealed 338 references, of which 100 met the selection criteria. A total of 80 different keratinocyte secretions were reported, which can be grouped mainly into cytokines, growth factors, and antimicrobial peptides. The growth-factor group mostly affects stem cell differentiation into keratinocytes, especially epidermal growth factor and members of the transforming growth factor family. Nevertheless, the reported secretions reflected the nature of the involved studies, as most of them focused on keratinocyte interaction with inflammation. This review highlights the secretory function of keratinocytes, as well as the need for intense investigation to characterize these secretions and evaluate their regenerative capacities.

The alkylation of 3,5-dihydro-4H-pyridazino[4,5-b]indole-4-thione with benzyl bromide, ethyl chloroacetate, and allyl bromide in the presence of potassium carbonate (K2CO3) yielded new alkylsulfanylpyridazino[4,5-b]indole derivatives (i.e., compounds 4–6). Hydrazinolysis of ester 6 resulted in hydrazide 7. The structure of compound 6 was verified by X-ray single-crystal analysis. Among the synthesized compounds, compound 6 exhibited the most promising cytotoxicity toward MCF-7 cells with an IC50 value of 12 µM. It showed potential inhibition activity toward EGFR, PI3K, and AKT in MCF-7 cells, with 0.26-, 0.49-, and 0.31-fold reductions in concentration compared to an untreated control. Additionally, it showed apoptosis-inducing activity in MCF-7 cells (47.98-fold); overall apoptosis increased to 38.87% compared to 0.81% in the untreated control, which disrupted the cell cycle at pre-G1 and S phases. Moreover, compound 6 exhibited good binding affinities toward the tested proteins (EGFR, PI3K, and AKT) and had binding energies ranging from −15.87 to −24.87 Kcal/mol. It also formed good interactions with essential amino acids inside the binding sites. Hence, compound 6 is recommended as an anti-breast cancer chemotherapeutic due to its effects on the EGFR-PI3K-AKT pathway.

A straightforward one-pot route for the synthesis of a new 4-phenyl-1,2,5,6-tetraazafluoranthen-3(2H)-one is reported form the direct hydrazinolysis of triketo ester and hydrazine hydrate in ethanol. 4-Phenyl-1,2,5,6-tetraazafluoranthen-3(2H)-one was subjected to aza-Michael addition and N-alkylation on reaction with a set of alkylating agents in the presence of K2CO3. Hydrazinolysis of 4-phenyl-1,2,5,6-tetraazafluoranthen-3(2H)-one ester to hydrazide and conversion of hydrazide to thiosemicarbazide were successful. X-Ray single crystals analysis and 1H, 13C NMR were used for unambiguous structure confirmation. The O…H, N…H, C…N and C…C in 2, and the N…H, C…N, C…C, C…O and H…H interactions in 6 are the most important in the molecular packing based on Hirshfled analysis. Moreover, the presence of short C…C and C…N contacts in both compounds revealed the presence of π–π stacking interactions.

Introduction: Despite global efforts to contain the illness, COVID-19 continues to have severe health, life, and economic repercussions; thus, maintaining vaccine development is mandatory. Different directions concerning COVID-19 vaccines have emerged as a result of the vaccine’s unpredictability. Aims: To study the determinants of the attitudes of healthcare workers (HCWs) to receiving or refusing to receive the vaccine. Methods: The current study adopted an interviewed questionnaire between June and August 2021. A total of 341 HCWs currently working at Assiut University hospitals offered to receive the vaccine were included. Results: Only half of the HCWs (42%) accepted the COVID-19 vaccine. The most common reason that motivated the HCWs was being more susceptible than others to infection (71.8%). On other hand, the common reasons for refusing included: previously contracted the virus (64.8%); did not have time (58.8%); warned by a doctor not to take it (53.8%). Nearly one-third of nonaccepting HCWs depended on television, the Internet, and friends who refused the vaccine for information (p < 0.05). In the final multivariate regression model, there were six significant predictors: sex, job category, chronic disease, being vaccinated for influenza, and using Assiut University hospital staff and the Ministry of Health as sources of information (p < 0.05). Conclusion: Misinformation and negative conceptions are still barriers against achieving the desired rate of vaccination, especially for vulnerable groups such as HCWs.

Multilevel thresholding is one of the most effective image segmentation methods, due to its efficiency and easy implementation. This study presents a new multilevel thresholding method based on a modified artificial ecosystem-based optimization (AEO). The differential evolution (DE) is applied to overcome the shortcomings of the original AEO. The main idea of the proposed method, artificial ecosystem-based optimization differential evolution (AEODE), is to employ the operators of the DE as a local search of the AEO to improve the ecosystem of solutions. We used benchmark images to test the performance of the AEODE, and we compared it to several existing approaches. The proposed AEODE achieved a high performance when evaluated by the structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and fitness values. Moreover, the AEODE outperformed the basic version of the AEO concerning SSIM and PSNR by 78% and 82%, respectively, which reserves the best features for each of AEO and DE.

The synthesis of C2-symmetrical bis(β-enamino-pyran-2,4-dione) derivative 3 connected via 1,6-hexylene linker was reported for the first time. X-ray structures and Hirshfeld studies of the new bis- β-enamino-pyran-2,4-dione derivative 3 along with two structurally related pyran-2,4-dione derivatives 2a,b were discussed. A comparative analysis of the different intermolecular contacts affecting the crystal stability was presented. Generally, the H…H, O…H, and H…C interactions are common in all compounds and are considered the most abundant contacts. In addition, DFT calculations were used to compute the electronic properties as well as the 1H and 13C NMR spectra of the studied systems. All compounds (except 3) are polar where 2a (3.540 Debye) has a higher dipole moment than 2b (2.110 Debye). The NMR chemical shifts were calculated and excellent correlations between the calculated and experimental data were obtained (R2 = 0.93–0.94).

A new compounds named 3-4′-bipyrazoles 2 and 3 were synthesized in high chemical yield from a reaction of pyran-2,4-diketone 1 with aryl hydrazines under thermal conditions in MeOH. Compound 2 was unambiguously confirmed by single-crystal X-ray analysis. It crystalizes in a triclinic crystal system and space group P-1. Its crystal structure was found to be in good agreement with the spectral characterizations. With the aid of Hirshfeld calculations, the H…H (54.8–55.3%) and H…C (28.3–29.2%) intermolecular contacts are the most dominant, while the O…H (5.8–6.5%), N…H (3.8–4.6%) and C…C (3.0–4.9%) are less dominant. The compound has a polar nature with a net dipole moment of 6.388 Debye. The BD(2)C31-C32→BD*(2)N4-C34 (27.10 kcal/mol), LP(1)N5→BD*(2)C31-C32 (36.90 kcal/mol), BD(1)C32-C34→BD*(1)C18-C31 (6.78 kcal/mol) and LP(1)N4→BD*(1)N5-C31 (7.25 kcal/mol) are the strongest π→π*, n→π*, σ-σ* and n→σ* intramolecular charge transfer processes, respectively.

Four different new Schiff basses tethered indolyl-triazole-3-thione hybrid were designed and synthesized. X-ray single crystal structure, tautomerism, DFT, NBO and Hirshfeld analysis were explored. X-ray crystallographic investigations with the aid of Hirshfeld calculations were used to analyze the molecular packing of the studied systems. The H···H, H···C, S···H, Br···C, O···H, C···C and N···H interactions are the most important in the molecular packing of 3. In case of 4, the S···H, N···H, S···C and C···C contacts are the most significant. The results obtained from the DFT calculations indicated that the thione tautomer is energetically lower than the thiol one by 13.9545 and 13.7464 kcal/mol for 3 and 4, respectively. Hence, the thione tautomer is the most stable one which agree with the reported X-ray structure. In addition, DFT calculations were used to compute the electronic properties while natural bond orbital calculations were used to predict the stabilization energies due to conjugation effects. Both compounds are polar where 4 (3.348 Debye) has a higher dipole moment than 3 (2.430 Debye).

Intra and intermolecular interactions found in the developed crystals of the synthesized py-ron-2,4-dione derivatives play crucial rules in the molecular conformations and crystal stabili-ties, respectively. In this regard, Hirshfeld calculations were used to quantitatively analyze the different intermolecular interactions in the crystal structures of some functionalized py-ran-2,4-dione derivatives. The X-ray structure of pyran-2,4-dione derivative namely (3E,3′E)-3,3′-((ethane-1,2-diylbis(azanediyl))bis(phenylmethanylylidene))bis(6-phenyl-2H-pyran-2,4(3H)-dione) was determined. It crystallized in the monoclinic crystal system and C2/c space group with unit cell parameters: a = 14.0869(4) Å, b = 20.9041(5) Å, c = 10.1444(2) Å and β = 99.687(2)°. Generally, the H…H, H…C, O…H and C…C contacts are the most important interactions in the molecular packing of the studied pyran-2,4-diones. The molecular structure of these compounds is stabilized by intramolecular O…H hydrogen bond. The nature and strength of the O…H hy-drogen bonds were analyzed using atoms in molecules calculations. In all compounds, the O…H hydrogen bond belongs to closed-shell interactions where the interaction energies are higher at the optimized geometry than the X-ray one due to the shortening in the A…H distance as a con-sequence of the geometry optimization. These compounds have polar characters with different charged regions which explored using molecular electrostatic potential map. Their natural charges, reactivity descriptors and NMR chemical shifts were computed, discussed and compared.

Soil loss is one of the most important causes of land degradation. It is an inevitable environmental and socio-economic problem that exists in many physiographic regions of the world, which, besides other impacts, has a direct bearing on agricultural productivity. A reliable estimate of soil loss is critical for designing and implementing any mitigation measures. We applied the widely used Revised Universal Soil Loss Equation (RUSLE) in the Khabur River Basin (KhRB) within the NW part of the Zagros Fold and Thrust Belt (ZFTB). The areas such as the NW Zagros range, characterized by rugged topography, steep slope, high rainfall, and sparse vegetation, are most susceptible to soil erosion. We used the Digital Elevation Model (DEM) of the Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), Harmonized World Soil Database (HWSD), and Landsat imagery to estimate annual soil loss using the RUSLE model. In addition, we estimated sediment yield (SY) at sub-basin scale, in the KhRB where a number of dams are planned, and where basic studies on soil erosion are lacking. Estimation of SY will be useful in mitigation of excessive sedimentation affecting dam performance and watershed management in this region. We determined the average annual soil loss and the SY in the KhRB to be 11.16 t.ha−1.y−1 and 57.79 t.ha−1.y−1, respectively. The rainfall and runoff erosivity (R factor), slope length (L factor), and slope steepness (S factor), are the three main factors controlling soil loss in the region. This is the first study to determine soil loss at the sub-basin scale along with identifying suitable locations for check dams to trap the sediment before it enters downstream reservoirs. The study provides valuable input data for design of the dams to prevent excessive siltation. This study also aims at offering a new approach in relating potential soil erosion to the actual erosion and hypsometric integrals.

NO formation, which is one of the main disadvantages of ammonia combustion, was studied during the isochoric, adiabatic autoignition of ammonia/air mixtures using the algorithm of Computational Singular Perturbation (CSP). The chemical reactions supporting the action of the mode relating the most to NO were shown to be essentially the ones of the extended Zeldovich mechanism, thus indicating that NO formation is mainly thermal and not due to fuel-bound nitrogen. Because of this, addition of water vapor reduced NO formation, because of its action as a thermal buffer, but increased ignition delay, thus exacerbating the second important caveat of ammonia combustion, which is unrealistically long ignition delay. However, it was also shown that further addition of just 2% molar of H2O2 does not only reduce the ignition delay by a factor of 30, but also reverses the way water vapor affects ignition delay. Specifically, in the ternary mixture NH3/H2O/H2O2, addition of water vapor does not prolong but rather shortens ignition delay because it increases OH radicals. At the same time, the presence of H2O2 does not affect the influence of H2O in suppressing NO generation. In this manner, we were able to show that NH3/H2O/H2O2 mixtures offer a way to use ammonia as carbon-less fuel with acceptable NOx emissions and realistic ignition delay.