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Abstract In order to maximize the electricity supply from clean energy sources, the goal of the smart power system is to unite all renewable energy sources. The goal of the present study is to use three optimization techniques, artificial rabbits optimization algorithm (ARO), grey wolf optimizer (GWO), and whale optimization algorithm (WOA), to reduce the cost of electricity (COE) while improving the reliability of the power supply for rural areas. While using the same control variables for the optimization methods and load profile, various hybrid system configurations are explored. Photovoltaic, wind turbine, fuel cell, and electrolyser systems are all involved in the proposed hybrid renewable system. The ARO methodology is more effective than the GWO, WOA, and PSO procedures in terms of net present cost (NPC) and cost of energy (COE) generation, according to data comparing the three optimization techniques with the traditional Particle Swarm Optimization (PSO) method. The proposed ARO reached a value of COE of 0.4412$/kWh compared to 0.4438$/kWh for GWO, 0.4443$/kWh for WOA, and 0.44378$/kWh for PSO.

Abstract Groundwater levels vary from region to another and sometimes in different zones in the same country due to different boundary conditions and extraction rates. Therefore, understanding intricate aquifer systems and predicting how they will react to hydrological changes require the use of groundwater models. In Egypt, the groundwater levels in the Nile Delta aquifer decrease causing problems to the delta ecosystem while it is rising in Aswan area due to the presence of Nasser Lake causing several damages to the city’s buildings and infrastructures. In order to maximize its benefits and lessen the harm brought on by inadequate groundwater management in the city of Aswan, the height of the groundwater level in that city was examined, appraised, and groundwater management scenarios were established in this study. To achieve the objectives of the study, a simulation of Aswan aquifer’s groundwater system is built based on a quasi-three-dimensional transient groundwater flow model using MODFLOW. The model was calibrated and verified. Four management scenarios are tested. The fifth scenario, in this scenario, the four scenarios combined together at the same time and with the same conditions and ratios were proposed to be implemented. The results of the proposal to implement the four scenarios together showed that the rates of decline in groundwater levels in the last stage will be 12.44%. The study results reveal that a better understanding of the simulated long-term average spatial distribution of water balance components is useful for managing and planning the available water resources in the Aswan aquifer.

Abstract Electrocardiography (ECG) and photoplethysmography (PPG) are non-invasive methods used to quantify signals originating from the cardiovascular system. Although there is a strong correlation between the cycles of the two measures, the correlation between the waveforms has received little attention in research. Measuring the PPG is significantly simpler and more convenient compared to the ECG measure. Recent research has demonstrated that PPG signals can be utilized to rebuild the ECG signals, suggesting that healthcare professionals might acquire a comprehensive comprehension of patients' cardiovascular well-being by only measuring PPG. With the advancement of artificial intelligence, the deep learning model has made significant progress in reconstructing ECG signals from PPG signals. However, the quality of the reconstructed ECG signal is still in need of more enhancement. In order to enhance the quality of the reconstructed ECG signal, we propose an innovative hybrid attention-based bidirectional recurrent neural network (Bi-RNN) that incorporates a dilated convolutional neural network technique for the purpose of reconstructing ECG signals from PPG signals. This addresses issues that occur when standard dilated CNN (DCNN) models neglect the link between circumstances and dispersion of gradients. The suggested approach maximizes the utilization of the DCNN and Bi-RNN unit design to provide fusion features. In order to ensure the model's resilience to deformation, it is imperative to initially extract spatial properties utilizing convolutional neural networks (CNNs). Once we have obtained geographic data, we employ BiLSTM to extract temporal features. The proposed model is so-called hybrid attention-based CNN and BiLSTM (HA-CNN-BiLSTM). BiLSTM mitigates the issues of gradient vanishing and exploding while maintaining accuracy. To showcase the advantages of the suggested model, we conduct a comparison between HA-CNN-BiLSTM and each separate state-of-the-art method. The simulation results indicated that the proposed method yielded superior root mean square error (RMSE) when reconstructing the ECG signal across different optimizers. The results also demonstrated that the proposed method results in the lowest RMSE with SGDM optimizer which is 0.031.

Background: Endophytic fungi produce biologically robust metabolites suitable for diverse applications, which support the increasing exploration of these fungi. The study aimed to investigate the in vitro antimicrobial properties of the metabolites of endophytic fungus Aspergillus terreus which isolated from the leaves of Psidium guajava plants while the acute oral toxicity was assessed in vivo. Results: A. terreus (OR125572) was successfully isolated for the first time from P. guajava. The ethyl acetate extract of A. terreus exhibited antibactericidal effects against Enterobacter aerogenes with a minimum inhibitory concentration of 18.75 mg/ml in contrast to 75.00 ± 0.0, 37.50, and 37.50 mg/ml, respectively against Staphylococcus aureus, Escherichia coli, and Bacillus sphaericus were 75.00 ± 0.0, 37.50, and 37.50 mg/ml, respectively. Analysis of the crude extract obtained from A. terreus by GC-MS revealed a total of 32 distinct compounds. The major components included 1,2-benzenedicarboxylic acid, di-iso-octyl ester; hexyl oxecan-2-one and phenol. The acute oral toxicity study found no symptoms of toxicity and no mortality until the 14th d, suggesting that the LD50 value of A. terreus extract might exceed 1 ml/kg. The group receiving 0.5 ml/kg of A. terreus extract experienced a 42.9% increase in body weight, while administration of varying dosages resulted in a significant reduction in MCV levels. There was also a significant increase in the proportion of monocytes across all treated groups. Conclusions: The study demonstrated the potential of A. terreus as a source of antimicrobial and other bioactive compounds, with relatively low acute toxicity.How to cite: Shehabeldine AM, Abdelaziz AM, Abdel-Maksoud MA, et al. Antimicrobial characteristics of endophytic Aspergillus terreus and acute oral toxicity analysis. Electron J Biotechnol 2024;72. https://doi.org/10.1016/j.ejbt.2024.07.003.

Abstract Catalytic methane decomposition is a promising technology for reducing the reliance on fossil fuels and mitigating the effects of climate change by producing clean hydrogen and value‐added carbon without the emission of greenhouse gases. The aim of the study was to investigate the use of Al2O3‐modified MgO doped iron‐based catalysts for the catalytic decomposition of methane. The catalysts were synthesized using the impregnation method and characterized using various analysis techniques, including Brunauer, Emmett, and Teller, temperature programmed reduction, temperature programmed oxidation, X‐ray diffraction, thermal gravimetric analysis, Raman, scanning electron microscopy, and transmission electron microscopy. The activity of the synthesized catalysts was tested in a packed‐bed reactor with a gas flow rate of 20 mL/min at a temperature of 800°C. The investigation focuses on the influence of incorporating magnesium into alumina catalysts with MgO concentration ranging from (20%–70%), where higher magnesium levels improve catalytic activity by creating more active sites, positively impacting methane decomposition. Enhanced catalyst reducibility and increased particle dispersion lead to improved catalytic properties despite the reduced surface area. The FA70M and FA63M catalysts exhibited almost the same catalytic characteristics and the highest stability and methane conversion among the catalysts investigated, reaching 87% and 85% at 800°C for 120 min. Moreover, both catalysts showed hydrogen yields of 86% and 85%, respectively. The introduction of MgO further increased the total carbon yield from 103% with FA and 39% for FM to 114% and 120% for the respective catalysts (FA70M and FA63M). During the methane decomposition reaction, carbon nanotubes of varying diameters were produced. Higher iron loading resulted in a positive trend.

Abstract Ionic driving forces provide the net electromotive force for ion movement across receptors, channels, and transporters, and are a fundamental property of all cells. In the nervous system, fast synaptic inhibition is mediated by chloride permeable GABAA and glycine receptors, and single-cell intracellular recordings have been the only method for estimating driving forces across these receptors (DFGABAA). Here we present a tool for quantifying inhibitory receptor driving force named ORCHID: all-Optical Reporting of CHloride Ion Driving force. We demonstrate ORCHID’s ability to provide accurate, high-throughput measurements of resting and dynamic DFGABAA from genetically targeted cell types over multiple timescales. ORCHID confirms theoretical predictions about the biophysical mechanisms that establish DFGABAA, reveals differences in DFGABAA between neurons and astrocytes, and affords the first in vivo measurements of intact DFGABAA. This work extends our understanding of inhibitory synaptic transmission and demonstrates the potential for all-optical methods to assess ionic driving forces.

Abstract Background Diabetic peripheral neuropathy (DPN) in children and adolescents with type 1 diabetes mellitus (T1DM) is a growing issue, with controversial data in the terms of prevalence and evaluation timelines. Currently, there are no clear standards for its early detection. Therefore, our aim was to assess the contribution of the Michigan neuropathy screening instrument (MNSI), lipid profile, serum neuron specific enolase (NSE), and serum heat shock protein 27 (HSP 27) to the prediction of DPN in children and adolescents with T1DM. Methods In this case-control study, fifty children diagnosed with T1DM for at least five years were enrolled and evaluated through complete neurological examination, MNSI, and nerve conduction study (NCS). Additionally, HbA1c, lipid profile, serum NSE, and serum HSP 27 levels were measured for patients and controls. Results The prevalence of DPN in our study was 24% by NCS, and electrophysiological changes showed a statistically significant lower conduction velocity for the posterior tibial and sural nerves, as well as a prolonged latency period for the common peroneal and sural nerves in neuropathic patients. In these patients, older age, earlier age of diabetes onset, longer disease duration, higher total cholesterol, triglycerides, low density lipoprotein cholesterol, HbA1c, serum NSE, and HSP27 levels were observed. The MNSI examination score ≥ 1.5 cutoff point had an area under the curve (AUC) of 0.955, with 75% sensitivity and 94.74% specificity, according to receiver operating characteristic curve analysis. However, the questionnaire’s cutoff point of ≥ 5 had an AUC of 0.720, 75% sensitivity, and 63% specificity, with improved overall instrument performance when combining both scores. Regarding blood biomarkers, serum NSE had greater sensitivity and specificity in discriminating neuropathic patients than HSP27 (92% and 74% versus 75% and 71%, respectively). Regression analysis revealed a substantial dependency for MNSI and serum NSE in predicting DPN in patients. Conclusions Despite limited research in pediatrics, MNSI and serum NSE are promising predictive tools for DPN in children and adolescents with T1DM, even when they are asymptomatic. Poor glycemic control and lipid profile changes may play a critical role in the development of DPN in these patients, despite conflicting results in various studies.

Serratiopeptidase is a zinc-containing metalloprotease primarily obtained from Serratia marcescens isolated from the silkworm guts. This study aimed to assess the antinociceptive, anti inflammatory, and antipyretic effects of serratiopeptidase in hen chicks. It included 104 hen chicks weighing 70-90 g. The antinociception efficacy was assessed by electricalstimulation and hot water test. Anti-inflammatory efficacy was assessed by formalin test. Assessment of therapeutic and antipyretic efficacy was determined by Baker’s yeast-induced pyrexia test. In the electrical stimulation test, 20 and 40 mg/kg of serratiopeptidase induced an antinociceptive effect in 15% and 18%, respectively. In the hot-water test, this effect was observed in 31 and 82%, respectively. In the first phase of the formalin test, an antinociceptive effect was observed for both doses, whereas in the second stage, an anti-inflammatory effect was observed in 56% and 62%, respectively. Serratiopeptidase produced a novel antipyretic effect for both doses on the Baker’s-yeast test, pre- and post-injection of the yeast. It was concluded that serratiopeptidase had good activity against pain and acute inflammation, and for the first time, it was demonstrated that serratiopeptidase ameliorated and prevented hyperthermia.

Abstract Background Sleep distrurbances involves daytime preoccupation about sleep, which plays a critical role in perpetuating sleep disturbances. Recent cognitive models highlight the importance of daytime processes, like processing sleep-related information and interpretations during waking hours, in influencing sleep quality and quantity. The Sleep Preoccupation Scale (SPS) quantifies this daytime cognitive activity related to sleep. This study aimed to translate and validate an Arabic version of the SPS for assessing sleep preoccupation among Arabic speakers. Methods 523 Arabic speakers (mean age 23.6 years, 75% female) from four countries completed the Arabic SPS alongside the Athens Insomnia Scale, Generalized Anxiety Disorder-7 Scale, and the Anxiety and Preoccupation about Sleep Questionnaire (APSQ). The sample repeated the SPS after two weeks for test-retest reliability. Confirmatory factor analysis evaluated the SPS’s two-factor structure. Internal consistency, item response theory, and convergent validity with the other scales were examined. Results Confirmatory factor analysis supported the two-factor model’s fit. Measurement invariance results suggest that the SPS exhibits a similar basic factor structure across both insomnia and non-insomnia groups. The Arabic SPS demonstrated good internal consistency (Cronbach’s α = 0.92, McDonald’s ω = 0.92) and two-way mixed effects, consistency, single rater/measurement intraclass correlation coefficient (ICC) test-retest reliability (ICC = 0.95). Most items exhibited satisfactory item response theory fit statistics and discrimination. The SPS total score showed strong positive correlations with insomnia severity (r = 0.48, p

Preanesthetic drugs play an essential role in general anesthesia for smooth induction and recovery and have multiple pharmacodynamic properties; however, they are considered blockers of histamine receptor type 1. The fundamental goal was to determine the properties of orphenadrine as a pre-anesthetic in a chick model. Healthy, unsexed chicks were used. Up-and-down methods determined the safety profile of orphenadrine for the average lethal dose and the average analgesic dose. We administered orphenadrine at different doses and times. We then calculated the onset, duration, and recovery of anesthesia using xylazine and ketamine, as well as the body temperature and breathing rate of the chicks that had undergone general anesthesia. The median lethal dose was 121.10±8.49 mg/kg, intraperitoneal (IP), and the median analgesic dose was 2.49±0.21 mg/kg IP. Orphenadrine at 2.5, 5, and 10 mg/kg produced analgesia in a dose-dependent manner. Administration of orphenadrine at 5 mg/kg and IP at different times significantly prolonged the duration of anesthesia for xylazine and ketamine in a time-dependent manner, and body temperature and breathing rate were significantly decreased in the lateral recumbency situation in comparison with pre-lateral recumbency and post-lateral recumbency (recovery). Orphenadrine at 5,10, and 20 mg/kg, IP followed by 30 minutes produced a significant decrease in the onset of anesthesia, prolonged duration, and shortened recovery time compared with ketamine and xylazine alone. Orphenadrine also made a significant decrease in body temperature before lateral recumbency compared with xylazine and ketamine. Body temperature and breathing rate were significantly lower in lateral recumbency than in pre- and post-lateral recumbency. Conclusion: Orphenadrine is a safe drug because of the wide range between the average lethal and analgesic doses. It is also a good preanesthetic drug that prolongs the duration of anesthesia and shortens the recovery time in a Chick's model. However, because it has a hypothermic property, it must be used with caution when used as a preanesthetic.

Aims of study to compare between Roux-en-Y gastric bypass and gastric sleeve surgery to reduce excess weight in dogs with less complication. The study was conducted on 12 overweight male dogs. Their weights ranged between 33 and 39 kg, while their ages ranged from 20 months to 38 months. The dogs were randomly divided in two equal groups. The first group underwent gastric sleeve surgery, while the second group underwent gastric bypass surgery. The following criteria were used to evaluate the results: Animals weights were checked every two weeks for eight weeks. Laparoscopy was also performed two and eight weeks after surgery to evaluate any complications at the surgical operation site and ensure that stomach or intestinal contents were not leaking into the abdominal cavity. A blood sample was taken from each animal before surgery (zero time) and at the 2nd, 4th, 6th, and 8th weeks after surgery to measure iron and vitamin B12 levels. The weights of the animals in both groups decreased during 2nd, 4th, 6th, and 8th weeks, but the animals in the second group lost significant weight (p≤0.05) more than the animals in the first group. The results of the laparoscopic examination showed that there was no leakage of stomach and intestinal contents into the abdominal cavity; However, adhesions to the omentum, adjacent organs, or another part of the intestine are observed at the site of the operation. These adhesions were less in the first group than in the second group. According to the result of the iron test, the iron level in the second group decreased more than in the first groups. Vitamin B12 levels in the second group were lower than in the first group. In conclusion, the study showed that gastric bypass surgery effects on iron and vitamin B12 also severe adhesion and loss body weight more than gastric sleeve surgery.

Abstract Rates of nitrogen transformations support quantitative descriptions and predictive understanding of the complex nitrogen cycle, but measuring these rates is expensive and not readily available to researchers. Here, we compiled a dataset of gross nitrogen transformation rates (GNTR) of mineralization, nitrification, ammonium immobilization, nitrate immobilization, and dissimilatory nitrate reduction to ammonium in terrestrial ecosystems. Data were extracted from 331 studies published from 1984–2022, covering 581 sites. Globally, 1552 observations were appended with standardized soil, vegetation, and climate data (49 variables in total) potentially contributing to the observed variations of GNTR. We used machine learning-based data imputation to fill in partially missing GNTR, which improved statistical relationships between theoretically correlated processes. The dataset is currently the most comprehensive overview of terrestrial ecosystem GNTR and serves as a global synthesis of the extent and variability of GNTR across a wide range of environmental conditions. Future research can utilize the dataset to identify measurement gaps with respect to climate, soil, and ecosystem types, delineate GNTR for certain ecoregions, and help validate process-based models.

Abstract The gallbladder (GB) is a small pouch and a deep tissue placed under the liver. GB Cancer (GBC) is a deadly illness that is complex to discover in an initial phase. Initial diagnosis can significantly enhance the existence rate. Non-ionizing energy, low cost, and convenience make the US a general non-invasive analytical modality for patients with GB diseases. Automatic recognition of GBC from US imagery is a significant issue that has gained much attention from researchers. Recently, machine learning (ML) techniques dependent on convolutional neural network (CNN) architectures have prepared transformational growth in radiology and medical analysis for illnesses like lung, pancreatic, breast, and melanoma. Deep learning (DL) is a region of artificial intelligence (AI), a functional medical tomography model that can help in the initial analysis of GBC. This manuscript presents an Automated Gall Bladder Cancer Detection using an Artificial Gorilla Troops Optimizer with Transfer Learning (GBCD-AGTOTL) technique on Ultrasound Images. The GBCD-AGTOTL technique examines the US images for the presence of gall bladder cancer using the DL model. In the initial stage, the GBCD-AGTOTL technique preprocesses the US images using a median filtering (MF) approach. The GBCD-AGTOTL technique applies the Inception module for feature extraction, which learns the complex and intrinsic patterns in the pre-processed image. Besides, the AGTO algorithm-based hyperparameter tuning procedure takes place, which optimally picks the hyperparameter values of the Inception technique. Lastly, the bidirectional gated recurrent unit (BiGRU) model helps classify gall bladder cancer. A series of simulation analyses were performed to ensure the performance of the GBCD-AGTOTL technique on the GBC dataset. The experimental outcomes inferred the enhanced abilities of the GBCD-AGTOTL in detecting gall bladder cancer.

Abstract The realm of self-healing materials integrates chemical and physical mechanisms that prevent wear and fracturing and extend the operational lifetime. Unlike the favorable rheology of amorphous soft materials that facilitates efficient contact between fragments, the efficiency of recovery of atomistically ordered materials is restricted by slower interfacial mass transport and the need for ideal physical alignment, which limits their real-world application. We report drastic enhancements in efficiency and recovery time in the self-healing of anilinium bromide, challenging these limitations. Crystals of this material recovered up to 49% within seconds and up to 95% after 100 min via ferroelastic detwinning. The spatial evolution of strain during cracking and healing was measured in real time using digital image correlation. Favorable alignment and strong ionic bonding across the interface of partially fractured crystals facilitate self-healing. This study elevates organic crystals close to the best-in-class self-healing polymers and sets an approach for durable crystal-based optoelectronics.

Abstract One of the core concepts of contemporary control theory is the idea that a dynamical system can be controlled. Several abstract settings have been developed to describe the distributed control systems in a domain in which the control is acted through the boundary. In this manuscript, we investigate the boundary approximate controllability (ABC) of stochastic differential inclusion (SDI) with Hilfer fractional derivative (HFD) and nonlocal condition by implementing the principle of stochastic analysis, the fixed-point theorem, fractional calculus and multi-valued map. Moreover, an example is offered to define the primary results.

Abstract The rapid uprising technologies of smartphone applications and software introduced a new era for analytical detection techniques. It has transformed bench-top laboratory methods into simpler ones depending on cost-effective, portable, and widely accessible devices. In this work, two high performance thin layer chromatographic (HPTLC) methods were developed based on smartphone’s camera detection and either ImageJ desktop software or Color-Picker smartphone’s application as alternative techniques to conventional densitometric detection. A mixture of Naltrexone hydrochloride (NAL) and Bupropion hydrochloride (BUP) was chromatographed on HPTLC- plates using ethyl acetate, methanol, acetone, and glacial acetic acid (3:6:1:0.5, by volume) as a developing system. The developed plates were scanned at 203 nm for the densitometric analysis, then visualized by modified Dragendorff’s reagent and shot by a smartphone’s camera. The captured images were uploaded to either ImageJ software or Color-Picker application to detect the separated spots. The results derived from the three detection methods were compared over the concentration range of 0.4–24 & 0.6–18 µg/band for the densitometric method, 0.4–24 & 2–24 µg/band for ImageJ built method and 0.8–20 & 5–20 µg/band for Color Picker built method for NAL and BUP, respectively. The methods were found to be appropriate for assaying both active drug substances in pure forms and combined in marketed pharmaceutical formulations. The excellent sustainability of densitometric and ImageJ-based methods enabled also the assessment of their dosage form content uniformity. The greenness and sustainability of the methods were assessed by three metric tools, namely Green Analytical Procedure Index (GAPI), Analytical GREEnness Metric Approach (AGREE), and White Analytical Chemistry (WAC). The assessments results confirmed the sustainability and superiority of the proposed methods in terms of sample treatment, waste mount, energy consumption, cost, and number of analyzed samples per an hour.

Abstract Nanoparticle-mediated drug delivery offers a promising approach to targeted cancer therapy, leveraging the ability of nanoparticles to deliver therapeutic agents directly to cancerous tissues with minimal impact on surrounding healthy cells. The presence of these nanoparticles is governed by a concentration equation, which accounts for the diffusion, convection, and reaction of the nanoparticles with the blood components. It is well-known that whenever a disease or infection occurs in a human, in 80% of cases a rise in the concentration of hydrogen peroxide in the blood occurs. This is the reason why blood is assumed to contain hydrogen peroxide (in the present study), which is a biomarker of oxidative stress and inflammation. This study explores the integration of machine learning (ML) techniques into the optimization of drug delivery processes within the human cardiovascular system, focusing on the enhancement of these processes through the application of magnetic fields. By employing ML algorithms, we analyze and predict the behavior of nanoparticles as they navigate the complex fluid dynamics of the cardiovascular system, particularly under the influence of an external magnetic field. The predictive power of ML models enables the precise control of nanoparticle trajectories, optimizing their accumulation in cancerous tissues and improving the efficacy of the drug delivery system. The findings of this study demonstrate that ML-enhanced magnetic targeting can significantly enhance the precision and effectiveness of nanoparticle-mediated drug delivery, offering a new paradigm in cancer treatment strategies. This approach has the potential to revolutionize the field by providing personalized and highly efficient therapeutic solutions for cancer patients.

Abstract Asthma and chronic obstructive pulmonary disease (COPD) are the most common diagnoses for adults and children with respiratory tract inflammation. Recently, a novel fixed dose combination consisting of Ipratropium and Fenoterol has been released for the management and control of the symptoms of such disorders. The current research has newly developed and optimized three smart, accurate, simple, cost-effective, and eco-friendly spectrophotometric methods that enabled the simultaneous determination of the drugs under study in their combined inhaler dosage form, without the need for any previous separation steps, using water as a green solvent. The strategy employed was based on calculating one or two factors as a numerical spectrum or constant, which provided the complete removal of any component in the mixture that might overlap and the mathematical filtration of the targeted analyte. The methods developed could be classified into two types of spectrophotometric windows. Window I; involved absorption spectrum in their original zero-order forms (°D), which included recently designed methods named induced concentration subtraction (ICS) and induced dual wavelength (IDW). While window III focused on the ratio spectrum as the induced amplitude modulation (IAM) method. The extremely low absorptivity and lack of distinct absorption maximum in the zero-order absorption spectrum of Ipratropium were two intrinsic challenges that were better overcome by the proposed spectrophotometric methods than by the conventionally used ones. According to ICH guidelines, the proposed methods were validated using unified regression over range 2.0–40.0 µg/mL in the ICS method, while the linearity ranges for the IDW and IAM methods were 5.0–40.0 µg/mL of Ipratropium and 2.0–40.0 µg/mL of Fenoterol. Moreover, the three proposed methods were effectively used to assay the co-formulated marketed inhaler and further expanded to confirm the delivered dose uniformity in compliance with the USP guidelines. Finally, the established methods were evaluated for their greenness and blueness, in comparison to the official and reported analysis methods, using advanced cutting edge software metrics. Furthermore, the suggested techniques adhered well to the white analytical chemistry postulates that were recently published.

Abstract The frictional properties of pavement are contingent on its surface texture, which consists of multiple scales that each contribute differently to friction generation at the tire-surface interface. Consequently, this study applied three adaptive decomposition algorithms of the Hilbert–Huang Transformation (HHT) to extract essential texture parameters from surface profiles, aiming to improve understanding of how pavement texture impacts friction properties. The decomposition algorithms used are Empirical Mode Decomposition (EMD), Ensemble EMD (EEMD) and Complete EEMD with Adaptive Noise (CEEMDAN). A Circular Track Meter (CTMeter) was used to measure the surface texture profiles of twelve asphalt mixture slabs with high macrotexture, while friction properties were assessed using a dynamic friction tester (DFT). Additionally, sixteen texture parameters related to height, spacing, and shape were computed to characterize the surface texture of both the original profile and the derived intrinsic mode functions (IMFs). The statistical analysis revealed that while the third IMF (IMF3) obtained by the EEMD exhibited the strongest correlation with the original profile, reaching up to 0.69, the IMFs obtained by EMD demonstrated the highest correlation with the DFT results. Under different polishing conditions and DFT speeds, the friction-texture correlation varied significantly, with the highest correlation observed at the peak values of DFT results and DFT values at 20 km/h (DFT20). Among the texture indicators, in addition to the mean profile depth (MPD), the root mean square (Rq), root mean square wavelength (λq), and two points slope variance (SV2) were recommended for characterizing both the original texture and IMFs profiles in the correlation analysis of the friction-texture relationship.

Abstract Kojic acid (KA) has gained significant attention due to its widespread use in the food and cosmetics industries. However, concerns about its potential carcinogenic effects have heightened the need for sensitive detection methods. This study introduces a fluorescence-based optical sensor for the quantification of KA in food samples, utilizing fluorescent carbon dots (CDs) synthesized from pomegranate peel via a hydrothermal method. The Stern–Volmer plot demonstrated a linear response for KA in the range of 120 to 1200 µM, with a Pearson correlation coefficient (r) of 0.9999 and. The sensor exhibited a detection limit of 30 ± 0.04 µM and a limit of quantification (LOQ) of 90 ± 0.14 µM. Application of the developed method to soy sauce and vinegar samples yielded accurate KA determinations, with recoveries of 103.11 ± 0.96% and 104.45 ± 2.15%, respectively. These findings highlight the potential of the proposed sensor for practical applications in food quality and safety assessment, offering valuable insights into the presence of KA in food products.

Abstract Proton exchange membrane fuel cell (PEMFC) parameter extraction is an important issue in modeling and control of renewable energies. The PEMFC problem’s main objective is to estimate the optimal value of unknown parameters of the electrochemical model. The main objective function of the optimization problem is the sum of the square errors between the measured voltages and output voltages of the proposed electrochemical optimized model at various loading conditions. Natural rabbit survival strategies such as detour foraging and random hiding are influenced by Artificial rabbit optimization (ARO). Meanwhile, rabbit energy shrink is mimicked to control the smooth switching from detour foraging to random hiding. In this work, the ARO algorithm is proposed to find the parameters of PEMFC. The ARO performance is verified using experimental results obtained from conducting laboratory tests on the fuel cell test system (SCRIBNER 850e, LLC). The simulation results are assessed with four competitive algorithms: Grey Wolf Optimization Algorithm, Particle Swarm Optimizer, Salp Swarm Algorithm, and Sine Cosine Algorithm. The comparison aims to prove the superior performance of the proposed ARO compared with the other well-known competitive algorithms.

Abstract Background Self-medication practices involve the use of medications without healthcare professional requests. The threat of coronavirus disease 2019 (COVID-19) caused the practice of a fittest to survive action, with the assumption that something is better than nothing. Moreover, owing to the lack of effective treatment for COVID-19, the general public has shifted toward self-medication and symptomatic treatment, with approximately 80% of people stockpiling medication for use during the pandemic. Thus, this study aimed to assess the factors associated with self-medication practices during the COVID-19 pandemic crisis in southwestern Ethiopia. Methods A community-based cross-sectional study design was employed at selected drug retail outlets in southwestern Ethiopia for 415 community pharmacy clients from July 1, 2021, to September 1, 2021. Purposive sampling techniques were employed to select five drug retail outlets on the basis of high patient flows, and we took the study participants until the required quota allotted to each selected drug retail outlet had been filled. Bivariable and multivariable logistic regression analyses were employed to identify factors associated with self-medication. AORs with 95% CIs were used to report associations, and the level of significance was set at P

Metamaterial absorbers (MMAs) have tremendous potential for controlling and modulating Terahertz electromagnetic (EM) waves. It is challenging to design MMAs for optimal performance using conventional methods due to their time-consuming and computationally demanding nature. Machine learning (ML) regressor approaches have emerged as potential tools for optimizing the predictive modeling of MMAs in recent years. This article examined different regression techniques, such as Decision Tree, k-Nearest Neighbors, Random Forest, Extra Trees (ET), Extreme Gradient Boosting, Bagging, and Categorical Boosting. The primary goal is to assess the effectiveness of each regressor technique in forecasting the performance of MMAs using various performance metrics. The study focuses on a representative spectrum of MMAs, chosen for its key features that are common across a wide range of MMAs. The extra tree Regressor outperforms other models in the comparative analysis due to its capacity to integrate multiple decision trees and include randomness into the feature selection process, resulting in improved predictive skills. The ET regressor forecasts MMA performance remarkably well for a 70 % test size, with a Root Mean Squared Error of 0.0251, a Mean Absolute Error of 0.0074, a Mean Squared Error of 0.006, and an Adjusted R-squared of 0.9873. These findings can assist researchers in optimizing metamaterial absorber designs for Terahertz applications using ML regressor techniques and provide insights into how these methods can be generalized to other spectra with similar characteristics.

Although the removal of colloidal particles continues to be an important reason for using coagulation, currently a newer approach, the removal of organic matter to reduce the formation of disinfection byproducts (DBPs) such as trihalomethanes (THMs) are suspected carcinogens. Inefficient removal of total organic carbon (TOC) leads to the formation of carcinogenic THMs. This motivates the research efforts to find a way to reduce them in potable water. The first objective of this research is monitoring the water quality (raw and produced) for selected three water treatment plants within Giza Governorate to reveal the most polluted site (high TOC in the raw water and THMs in the treated water) in the study areas. The second objective of this study is enhancing coagulation to reduce TOC and THMs from surface water treating. In this study, two different coagulants aluminum sulfate (alum), and ferric chloride were tested under different conditions of pH and coagulant concentration to determine their effectiveness for removal of TOC, THMs and turbidity. Optimum values for the mentioned conditions were used to achieve the maximum reduction for TOC and THMs in Al-Ayat drinking water treatment plant (DWTP) which recorded the highest concentration of TOC and THMs. Ferric chloride as a coagulant achieved the maximum removal percentage % of TOC, THMs and turbidity as 79%, 82% and 94%, respectively, at ferric chloride dose 100 mg/L, while alum as a coagulant recorded the maximum removal percentage % of TOC, THMs and turbidity as 46%, 52% and 91%, respectively, at alum dose 100 mg/L. The results indicated that ferric chloride as a coagulant has the highest efficiency reduction of TOC, THMs and turbidity if compared to alum with the same dose added.

Abstract Background PPHN is a common cause of neonatal respiratory failure and is still a serious condition and associated with high mortality. Objectives To compare the demographic variables, clinical characteristics, and treatment outcomes in neonates with PHHN who underwent ECMO and survived compared to neonates with PHHN who underwent ECMO and died. Methods We adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline and searched ProQuest, Medline, Embase, PubMed, CINAHL, Wiley online library, Scopus and Nature for studies on the development of PPHN in neonates who underwent ECMO, published from January 1, 2010 to May 31, 2023, with English language restriction. Results Of the 5689 papers that were identified, 134 articles were included in the systematic review. Studies involving 1814 neonates with PPHN who were placed on ECMO were analyzed (1218 survived and 594 died). Neonates in the PPHN group who died had lower proportion of normal spontaneous vaginal delivery (6.4% vs 1.8%; p value > 0.05) and lower Apgar scores at 1 min and 5 min [i.e., low Apgar score: 1.5% vs 0.5%, moderately abnormal Apgar score: 10.3% vs 1.2% and reassuring Apgar score: 4% vs 2.3%; p value = 0.039] compared to those who survived. Neonates who had PPHN and died had higher proportion of medical comorbidities such as omphalocele (0.7% vs 4.7%), systemic hypotension (1% vs 2.5%), infection with Herpes simplex virus (0.4% vs 2.2%) or Bordetella pertussis (0.7% vs 2%); p = 0.042. Neonates with PPHN in the death group were more likely to present due to congenital diaphragmatic hernia (25.5% vs 47.3%), neonatal respiratory distress syndrome (4.2% vs 13.5%), meconium aspiration syndrome (8% vs 12.1%), pneumonia (1.6% vs 8.4%), sepsis (1.5% vs 8.2%) and alveolar capillary dysplasia with misalignment of pulmonary veins (0.1% vs 4.4%); p = 0.019. Neonates with PPHN who died needed a longer median time of mechanical ventilation (15 days, IQR 10 to 27 vs. 10 days, IQR 7 to 28; p = 0.024) and ECMO use (9.2 days, IQR 3.9 to 13.5 vs. 6 days, IQR 3 to 12.5; p = 0.033), and a shorter median duration of hospital stay (23 days, IQR 12.5 to 46 vs. 58.5 days, IQR 28.2 to 60.7; p = 0.000) compared to the neonates with PPHN who survived. ECMO-related complications such as chylothorax (1% vs 2.7%), intracranial bleeding (1.2% vs 1.7%) and catheter-related infections (0% vs 0.3%) were more frequent in the group of neonates with PPHN who died (p = 0.031). Conclusion ECMO in the neonates with PPHN who failed supportive cardiorespiratory care and conventional therapies has been successfully utilized with a neonatal survival rate of 67.1%. Mortality in neonates with PPHN who underwent ECMO was highest in cases born via the caesarean delivery mode or neonates who had lower Apgar scores at birth. Fatality rate in neonates with PPHN who underwent ECMO was the highest in patients with higher rate of specific medical comorbidities (omphalocele, systemic hypotension and infection with Herpes simplex virus or Bordetella pertussis) or cases who had PPHN due to higher rate of specific etiologies (congenital diaphragmatic hernia, neonatal respiratory distress syndrome and meconium aspiration syndrome). Neonates with PPHN who died may need a longer time of mechanical ventilation and ECMO use and a shorter duration of hospital stay; and may experience higher frequency of ECMO-related complications (chylothorax, intracranial bleeding and catheter-related infections) in comparison with the neonates with PPHN who survived.

Tooth impaction is an abnormality that occurs when a tooth does not emerge into its place in the dental arch. Impacted permanent molar is an unusual condition that is usually detected during a routine examination. This impaction type is mostly problematic and can cause serious issues, especially when early detection and appropriate treatment are not achieved. This article highlights a case with a complaint of an ill-fitting denture, accompanied by an impacted molar that was identified during routine radiographic examination. The available treatment options include periodic follow-up, surgical exposure and orthodontic repositioning, and more invasively, surgical extraction and prosthetic replacement. The case was treated by a nonsurgical prosthodontics approach, in addition to regular follow-up, avoiding surgical interventions. This approach successfully restored both the patient’s function and esthetics. The case demonstrated the potential of prosthodontics therapy for managing impacted teeth and offering a minimally invasive and short treatment alternative to surgical and orthodontic interventions.

Abstract Background There is evidence that major depressive disorder (MDD) with its cardinal symptoms, anhedonia and suicide, are linked with raised inflammatory markers like C-reactive protein (CRP). This case–control study investigated the correlation between high sensitive CRP (Hs-CRP), anhedonia, suicidal ideation, and depression severity in MDD patients. Methods Forty-one MDD patients and 47 healthy controls were recruited. MDD diagnosis was confirmed using DSM-5 criteria. Depression severity, anhedonia, and suicidal ideation were assessed using standardized scales. Serum Hs-CRP levels were measured as an inflammatory marker. Results MDD cases had significantly greater Hs-CRP levels compared to controls. Additionally, Hs-CRP levels were positively correlated with both anhedonia and suicidal ideation in MDD cases. Depression severity was significantly linked with both anhedonia and suicidal ideation. Conclusion This study suggests a link between inflammation, anhedonia, suicidal ideation, and depression severity in MDD patients. Additional research is necessary to find out the principal mechanisms.

Abstract Ipratropium bromide (IPR) and fenoterol hydrobromide (FEN) have recently been combined in a promising inhaler to treat two prevalent inflammatory illnesses of the airways: bronchial asthma and chronic obstructive pulmonary disease (COPD). The necessity for a single, sensitive, and trustworthy analytical approach to cover the diverse and necessary tests of in-vitro and in-vivo studies is greatly grown with the rising production of new fixed combinations. Two novel, selective and environmentally friendly LC techniques were developed in order to guarantee precise measurement of IPR and FEN in their challenging formulation. The initial technique involved high-performance thin-layer chromatography (HPTLC) in conjunction with densitometric quantification. Chromatographic separation was attained on HPTLC plates utilizing ethyl acetate - ethanol - acetic acid (5.0:5.0:0.1, by volume) as a developing system. Densitometric quantification of the separated bands was carried out at 220.0 nm over concentration ranges of 0.50–15.0 µg/band for IPR and 0.50–12.0 µg/band for FEN. High-performance liquid chromatography (HPLC) paired with diode array detection (DAD) was the core of the second technique. The optimized separation was achieved on a Zorbax SB C18 (150 × 4.6 mm, 5 μm) column with a combination of 10.0 mM potassium dihydrogen orthophosphate, pH 5.0 ± 0.1, adjusted with o-phosphoric acid and methanol (70:30, v/v) as the mobile phase and pumped at flow rate of 1.0 mL/min. The peaks were monitored at 220.0 nm using diode array detection, achieving linearity range of 5.0–200.0 µg/mL for both drugs. The ICH criteria have been verified and both methods have been confirmed to be valid, and successfully applied for assay the cited drugs in the Atrovent® comp HFA metered dose inhaler as well as delivered dose uniformity testing of the final product. Finally, whiteness appraisal and several state-of-the-art green evaluation metrics were applied to evaluate the sustainability of the proposed methods. The suggested approaches produced promising results and are the first simple and sustainable methodologies for the simultaneous quantification of both drugs in different real samples, all of which strongly suggest their application in quality control laboratories.

Abstract Impaired wound healing in diabetic individuals creates huge social and financial burdens for both diabetic patients and the health system. Unfortunately, the current treatment has not resulted in consistently lower amputation rates. Quinoxalines are heterocyclic compounds with multiple important pharmacological properties. Their effect on wound healing have not been closely studied. In the current work, the wound healing effect of 3-hydrazinylquinoxaline-2-thiol hydrogel is tested topically in a full-thickness excision wound in streptozotocin-induced type 1 diabetic rats. We examined the wound closure rate, expression of inflammatory factors, growth factors in addition to the histological analysis. The results revealed a significant acceleration in wound closure in the treated group compared with the control experimental animals. Histological data demonstrated enhanced re-epithelialization and collagen disposition. The healing effect was additionally evaluated by the inhibition of the inflammatory response of interleukin (IL)—1β interleukin (IL)—6, tumor necrosis factor (TNF-α) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) with a marked improvement of the transforming growth factor beta (TGFβ-1), antioxidant markers and collagen-1. In silico study indicated a favorable drug-like properties and toxicity profile. The present work showed that 3-hydrazinylquinoxaline-2-thiol holds great potential for the treatment of diabetic wounds.

Abstract Antibiotics are among the most widely used pharmaceutically active compounds. Possessing the capability to adversely impact the ecological system, existence of antibiotics in the environment is an escalating concern. With the purpose of removing two widely used antibiotics efficiently from aqueous solutions, the competency of two biochar (BC)-based sorbents derived from spent coffee (SC) grounds was investigated. Both pristine (SCBC) and nickel (II) oxide-impregnated (Ni-SCBC) biochars were utilized as sustainable and cost-effective sorbents to remove daunorubicin (DAYN) and tigecycline (TIGY) from single synthetic aqueous solutions and binary combinations. Batch adsorption experiments were controlled implementing Box–Behnken design. The removal efficiency of Ni-SCBC was superior compared to SCBC (TIGY: 67.06%, DAYN: 94.30%). Results of characterizations showed that impregnation with NiO changed the degree of crystallization with a remarkable increase in the surface area from 49.23 m2/g in SCBC to 86.06 m2/g in Ni-SCBC. Adsorption of DAYN and TIGY (single solutions) conformed well to Freundlich, and Langmuir isotherms, respectively. A maximum adsorption capacity (q max) of 136.62 mg/g (DAYN) and 73.15 mg/g (TIGY) was reported in single solutions, compared to 23.50 mg/g (DAYN) and 58.42 mg/g (TIGY) in binary mixture. Adsorption kinetics onto Ni-SCBC fitted well with the pseudo-second-order (PSO) and Elovich models. Acquired results demonstrated that SCBC and Ni-SCBC are promising adsorbents for remedying antibiotics.

Abstract Background The epidemiology of Neisseria gonorrhoeae (NG) infection in the Middle East and North Africa (MENA) region remains poorly understood, despite the global recognition of its disease burden and the growing concern regarding antimicrobial resistance. This study aimed to systematically review the evidence on NG prevalence in MENA, estimate the pooled mean prevalence across different populations, and explore population-level associations with prevalence as well as sources of between-study heterogeneity. Methods The study conducted a systematic review, risk of bias assessment, meta-analyses, and meta-regressions, utilizing both published and unpublished evidence sourced from international, regional, and national databases, in adherence to PRISMA guidelines. Random-effects meta-analyses and meta-regressions were employed to analyze the data. Results The study identified 341 NG prevalence measures from 21 countries in MENA. The pooled mean prevalence of current urogenital infection was 1.9% (95% confidence interval (CI) 1.1–2.8%) in the general population, with a higher pooled prevalence in studies with sample sizes

Abstract The catalytic partial oxidation of methane (POM) is aimed at the mitigation of CH4 (a highly potent greenhouse gas) from the environment and the synthesis of syngas with a high H2/CO ratio. Herein, to enhance the POM reaction, Ni‐supported phosphate‐modified‐zirconia were synthesized with promotor “Ce” to achieve high H2/CO ratio (2.4–3.2). The catalysts were characterized by surface area and porosity, X‐ray diffraction, RAMAN, temperature‐programmed experiments (TPR, CO2‐TPD, and TPO), and TEM. Increasing the ceria addition over 10Ni/PO4 + ZrO2 resulted in lower crystallinity, higher dispersion of active sites, and enhanced the surface area of catalyst. The unique and prominent reducibility and basicity of NiO‐species and surface oxide ions, respectively, are particularly notable at 4 wt.% ceria loading. At a reaction temperature of 600°C, the highest concentration of active sites and a unique concentration of moderate strength basic sites can be achieved with 4 wt.% ceria loading over 10Ni/PO4 + ZrO2. This leads to 44% conversion of CH4, 36% yield of H2, 35% yield of CO2, and H2/CO ratio of 3.16 for the POM reaction. The cyclic H2TPR‐O2TPO‐H2TPR experiment confirms the reorganization of the active site towards high temperature under oxidizing gas O2 and reducing gas H2 gas stream during the POM reaction.

Abstract Cell adhesion to the extracellular matrix and its natural outcome of cell spreading, along with the maintenance of barrier activity, are essential behaviors of epithelial cells, including retinal pigment epithelium (RPE). Disruptions in these characteristics can result in severe vision-threatening diseases such as diabetic macular edema and age-related macular degeneration. However, the precise mechanisms underlying how RPE cells regulate their barrier integrity and cell spreading are not fully understood. This study aims to elucidate the relative importance of upper glycolytic components in governing these cellular behaviors of RPE cells. Electric Cell-Substrate Impedance Sensing (ECIS) technology was utilized to assess in real-time the effects of targeting various upper glycolytic enzymes on RPE barrier function and cell spreading by measuring cell resistance and capacitance, respectively. Specific inhibitors used included WZB117 for Glut1 inhibition, Lonidamine for Hexokinase inhibition, PFK158 for PFKFB3/PFK axis inhibition, and TDZD-8 for Aldolase inhibition. Additionally, the viability of RPE cells was evaluated using a lactate dehydrogenase (LDH) cytotoxicity assay. The most significant decrease in electrical resistance and increase in capacitance of RPE cells were observed due to dose-dependent inhibition of Glut1 using WZB117, as well as Aldolase inhibition with TDZD-8. LDH level analysis at 24–72 h post-treatment with WZB117 (1 and 10 μM) or TDZD-8 (1 μM) showed no significant difference compared to the control, indicating that the disruption of RPE functionality was not attributed to cell death. Lastly, inhibition of other upper glycolytic components, including PFKFB3/PFK with PFK158 or Hexokinase with Lonidamine, did not significantly affect RPE cell behavior. This study provides insights into the varied roles of upper glycolytic components in regulating the functionality of RPE cells. Specifically, it highlights the critical roles of Glut1 and Aldolase in preserving barrier integrity and promoting RPE cell adhesion and spreading. Such understanding will guide the development of safe interventions to treat RPE cell dysfunction in various retinal disorders.

Abstract Background Nitric oxide (NO) may contribute to the persistence of high-risk human papillomavirus (hrHPV) infection, which has been linked to the development of premalignant lesions and cervical cancer. Our study aimed to examine the relationship between cervical NO metabolite (NOx) levels, hrHPV infection, and cytopathological findings. Additionally, we assessed cervical NOx levels as a biomarker for predicting hrHPV infection and epithelial atypia. Methods The study involved 74 women who attended the Gynecology and Obstetrics outpatient clinics at Cairo University Hospitals between November 2021 and August 2022. Cervical samples were subjected to Pap testing, assessment of NOx levels by the Griess method, and detection of hrHPV DNA by real-time polymerase chain reaction. Results High-risk HPV was detected in 37.8% of women. EA was found in 17.1% of cases, with a higher percentage among hrHPV-positive than negative cases (35.7% vs. 4.3%, p = 0.001). The most prevalent hrHPV genotype was HPV 16 (89.3%). The cervical NOx level in hrHPV-positive cases was significantly higher (37.4 µmol/mL, IQR: 34.5–45.8) compared to negative cases (2.3 µmol/mL, IQR: 1.2–9.8) (p = 23.61 µmol/mL and > 11.35 µmol/mL exhibited good diagnostic accuracy for the prediction of hrHPV infection and EA, respectively. Conclusions The high prevalence of hrHPV infection, particularly HPV 16, in our hospital warrants targeted treatment and comprehensive screening. Elevated cervical NOx levels are associated with hrHPV infection and high-grade atypia, suggesting their potential use as biomarkers for predicting the presence of hrHPV and abnormal cytological changes.

This paper represents a wide incident angle-polarization insensitive, stable in results, and compact-sized metamaterial absorber that can be used for Doppler navigation aids and remote sensing applications in Earth Exploration Satellite Services. The unit cell dimension was subwavelength-sized of 0.112λ X 0.112λ, with a good effective medium ratio (8.9), and achieved polarization insensitivity at a maximum incident angle up to 180°, making it more effective for proposed applications. The absorber resonated at 3.855 GHz, 5.13 GHz, 9.855 GHz, 13.335 GHz, and 16.02 GHz with single negative metamaterial properties due to negative permeability and absorptions of 99.7 %, 99.2 %, 98.6 %, 98.1 %, and 97.9 %, respectively. An RLC equivalent circuit on ADS was analyzed to validate the simulated results using the dipoles created by the surface currents. The absorber is cost-effective as no lumped elements or multilayer substrate materials were used, making fabricating less time-consuming and simple. The simulated results were validated by measuring data from a vector network analyzer after fabricating it. The proposed metamaterial absorber is suitable for use in Doppler navigation and Earth Exploration Satellite Services, and this research can further be extended to beamforming and sensing applications in the future.

Abstract Background Incorporating video as a tool for education offers a multitude of advantages. However, it is unknown what is the best educational tool to use for increasing public awareness, consequently reducing fear about root canal treatment. For this reason, this study aimed to compare the effectiveness of educational animation and leaflets as delivery methods for providing information on root canal treatment to patients and to assess their ability to retain the information. Methods One hundred fifty adult volunteers were recruited via social media and Umm Al-Qura University Dental Hospital to participate in this randomized control trial study. The volunteers were divided into the study group (SG) and the control group (CG). The SG was provided with information through animations created by the research team, while the CG received the same information through a leaflet. Pre-intervention (T1), immediate post-intervention (T2), and one-month post-intervention (T3) validated questionnaires were completed by the participants to assess the changes in their knowledge. To evaluate the impact of the information delivery method, the knowledge scores of T2 and T3 were compared to T1 within each group using Paired T-tests. Additionally, the study compared the knowledge scores of the two groups using unpaired T-tests. The significance level was set at a P-value of less than 0.05. Results A significant improvement in endodontic therapy knowledge among the participants in both groups (T1 compared to T2 in the same group) was noted (P

Abstract Conscious sedation is widely considered one of the techniques most commonly used to manage anxiety in both children and adults during dental procedures. The application of procedural sedation exhibits considerable variation globally. The purpose of the study was to determine the prevalence of conscious sedation in the current situation in the dental healthcare sector in Egypt and to identify the factors influencing it. An online cross-sectional analytical survey, consisting of nine multiple choice questions, was distributed through the contact lists of national dentists and social media platforms. 163 respondents completed the survey. Regarding the use of conscious sedation, only 25 (15.3%),95% confidence interval (10–21) utilized it. The percentage of participants who used conscious sedation was higher among dentists practicing pediatric dental specialists (n = 19, 76%). Academic qualification correlates significantly with the practice of conscious sedation (P = 0.002), but this was not reflected in multiple logistic regression. Indeed, while conscious sedation is part of the dental study curriculum in Egypt, its application rate is relatively low compared to other countries. This discrepancy could be attributed to a variety of factors, including resource availability, lack of training, reflecting the need to develop strategies to improve the implementation of conscious sedation in Egyptian dental practices.

Abstract Background The nutritional status and growth of children with Autism spectrum disorders (ASD) is influenced significantly by two factors; food selectivity behaviors due to their consumption of a limited variety of food and the high incidence of gastrointestinal (GIT) disorders. Aim This study aimed to assess the nutritional adequacy and growth pattern of ASD children aged three to twelve years compared to their healthy developing peers. Methods A national comparative, facility-based cross-sectional study was conducted in eight Egyptian governorates on 285 Egyptian children diagnosed with ASD and 224 children who are their relatives as healthy developing peers. Anthropometric measurements were obtained, including weight, height, head circumference, and mid-upper arm circumference. Body Mass Index (BMI) was calculated and all numbers were plotted on WHO growth charts. Assessment of food preferences, and nutrient intake adequacy of children was done using the Food preference questionnaire, and the Dietary Reference Intakes (DRIs) of Egyptian children. Results Calorie-dense food and sugar intake were higher among ASD children than their healthy developing peers. ASD children omit some important protein sources such as dairy (COR = 5.2, 95% CI:2.7–9.9), meat, and poultry (COR = 2.7, 95% CI: 1.6–4.7), and a lower intake of fruits and vegetables than their healthy developing peers. For children with ASD in all age groups, a deficiency in the range of 50–60% was detected for vitamins (C, D, B6, thiamine, riboflavin, niacin) and minerals (iron). A deficiency in the range of 60–70% was detected for folate and calcium. A deficiency of vitamin C calcium and iron was also detected for both children with ASD and their healthy developing relatives aged 6 to 12 years. GIT disorders were common among ASD children compared to healthy developing peers (COR = 2.8 to 10.3). Children with ASD had four-fold higher odds of stunting (COR = 4.1, CI: 1.7–10.1), threefold higher odds of being overweight (COR = 3.3, CI: 1.48–7.32), and nearly eleven-fold higher odds of obesity (COR = 11.4, CI: 4.05–32.17) compared to their healthy developing peers. Conclusion ASD children are prone to overweight and protein malnutrition. Their intake of fruits and vegetables is inadequate and hence their intake of vitamins and minerals is insufficient, contributing to stunting.

This innovative study investigates the flow of ternary hybrid nanofluid containing gyrotactic microorganisms in microchannel. The magnetic field, thermophoresis, and Brownian motion effects are analyzed. The transformation of the PDEs system into ODEs is carried out by using the group transformation method. The innovative findings examine the Newtonian and non-Newtonian models derived from the system of ODEs. Several graphs illustrate how different parameters affect the velocity profile, temperature, concentration, and microorganisms. The power-law index value increases the fluid flow velocity by about 9% at n = 3, 36% at n = 4 relative to the case of n = 2.5 at the center of the boundary layer. Moreover, the ternary hybrid nanofluid exhibits a greater temperature compared to the nanofluid. The current results are compared to the researchers' findings to confirm the validity of the obtained results. When the Prandtl number is between 6 and 10, the Nusselt number reaches 45.49%.

Abstract This article presents a novel approach for parameters estimation of photovoltaic cells/modules using a recent optimization algorithm called quadratic interpolation optimization algorithm (QIOA). The proposed formula is dependent on variable voltage resistances (VVR) implementation of the series and shunt resistances. The variable resistances reduced from the effect of the electric field on the semiconductor conductivity should be included to get more accurate representation. Minimizing the mean root square error (MRSE) between the measured (I–V) dataset and the extracted (V–I) curve from the proposed electrical model is the main goal of the current optimization problem. The unknown parameters of the proposed PV models under the considered operating conditions are identified and optimally extracted using the proposed QIOA. Two distinct PV types are employed with normal and low radiation conditions. The VVR TDM is proposed for (R.T.C. France) silicon PV operating at normal radiation, and eleven unknown parameters are optimized. Additionally, twelve unknown parameters are optimized for a Q6-1380 multi-crystalline silicon (MCS) (area 7.7 cm2) operating under low radiation. The efficacy of the QIOA is demonstrated through comparison with four established optimizers: Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Salp Swarm Algorithm (SSA), and Sine Cosine Algorithm (SCA). The proposed QIO method achieves the lowest absolute current error values in both cases, highlighting its superiority and efficiency in extracting optimal parameters for both Single-Crystalline Silicon (SCS) and MCS cells under varying irradiance levels. Furthermore, simulation results emphasize the effectiveness of QIO compared to other algorithms in terms of convergence speed and robustness, making it a promising tool for accurate and efficient PV parameter estimation.

Abstract Municipal wastewater treatment systems use the chemical oxygen demand test (COD) to identify organic contaminants in industrial effluents that impede treatment due to their high concentration. This study reduced the COD levels in tannery wastewater using a multistage treatment process that included Fenton oxidation, chemical coagulation, and nanotechnology based on a synthetic soluble COD standard solution. At an acidic pH of 5, Fenton oxidation reduces the COD concentration by approximately 79%. It achieves this by combining 10 mL/L of H2O2 and 0.1 g/L of FeCl2. Furthermore, the author selected the FeCl3 coagulant for the coagulation process based on the best results of comparisons between different coagulants. At pH 8.5, the coagulation dose of 0.15 g/L achieved the maximum COD removal efficiency of approximately 56.7%. Finally, nano bimetallic Fe/Cu was used to complete the degradation and adsorption of the remaining organic pollutants. The XRD, SEM, and EDX analyses proved the formation of Fe/Cu nanoparticles. A dose of 0.09 g/L Fe/Cu NPs, 30 min of contact time, and a stirring rate of 200 rpm achieve a maximum removal efficiency of about 93% of COD at pH 7.5. The kinetics studies were analyzed using pseudo-first-order P.F.O., pseudo-second-order P.S.O., and intraparticle diffusion models. The P.S.O. showed the best fit among the kinetic models, with an R2 of 0.998. Finally, the authors recommended that technique for highly contaminated industrial effluents treatment for agriculture or industrial purposes.

Abstract Porous asphalt mixture is conventional hot mix asphalt (HMA) with substantially decreased fines, which produces an open-graded mixture that enables the water to flow through an interconnected void space. Porous asphalt is a permeable system that has a lot of benefits. However, because of its open structure, the durability of this mixture decreases, and both its stability and resilient modulus are much lower compared to the dense conventional asphalt mixtures. Also, the high void percentage may lead to an increase in the draindown proportion. Fibers (cellulose or mineral) and polymer-modified binders are recommended for porous asphalt mixtures, especially in hot and moderate climates. The objective of this study is to improve the porous asphalt mixture's performance by using ethylene–vinyl acetate (EVA) polymer-modified bitumen. Two types of fibers (cellulose fibers and glass wool fibers) were used, separately to determine the control mixture. Four different proportions of EVA polymer were added to the bitumen (1%, 2%, 3%, and 4%) and Scanning Electron Microscopy (SEM) was used for better investigating of the bitumen microstructure, then The Marshall mix design was used to determine the optimum EVA content (OEC) for the porous asphalt mixture. Several performance tests were conducted to investigate the characteristics of the porous asphalt mixture, such as the infiltration rate, binder draindown, the wheel track and the cantabro abrasion tests. The findings of the study conclude that the addition of EVA polymer to the porous asphalt mixtures enhances the performance as it increases stability by 20.8% and the infiltration rate by 20.6%. It decreases binder draindown proportion by 33.3%, cantabro abrasion loss by 25.1% and the rut depth at 5,000 cycles and 10,000 cycles by 29.8% and 19.7%, respectively.

This research was designed to study the effect of silymarin dosage on the histological structure of the testicle in rabbits and the impact it has on the level of sperm production in these animals. Thirty adult male rabbits were used to complete this work. Their ages ranged between 5 to 6 months, while their weight ranged between 1,500 to 1,700 grams. The animals were divided into three groups based on the amount of dose of silymarin given as follows (C- 10 rabbits given free diet served as a control group: T1-10 rabbits treated with an oral daily dose of 0.5 ml per kg B.W. T2-10 rabbits treated with orally daily dose 1 ml per kg B.W.). The various types of cells were identified in this study based on several criteria, the most important of which are the external appearance of these cells during the series of divisions, the size of the cell, and the shape of the nucleus. The results showed an improvement in the architecture of seminiferous tubule epithelium, the disappearance of vacuolar degenerations in more than 95% of this epithelium, and an increase in the number of mature sperm in the center of each tubule in addition to increasing all parameters of Leydig cells. In conclusion, the testicles in rabbits exposed to silymarin are positively affected, leading to improved sperm production.

The Covid-19 virus first discovered in February 2020 has defied borders by domesticating itself in all countries around the globe. Like in all other countries, the Covid-19 pandemic even though at first a health crisis has impacted all spheres of social life in the UAE from the economy to education as well as professions and their practices. The spread of infectious diseases is also known to live behind anxiety, fear, and general psychological distress among people. Government and health agencies in the UAE have embarked on public education and engagement to curb the spread of the virus as well as mitigate some of its adverse psychological consequences including anxiety and fear. The development of the Internet and new media has provided health authorities with channels for reaching out to the public on desirable health behavior. The discourse on digital divide for instance, has, among others, questioned technologically deterministic views about the novelty of the Internet by pointing at the divides or barriers it has created in society. While the UAE is reported to be the most digitally connected country in the MENA region in terms of the spread and access to Internet and broadband facilities thus overcoming the first level of digital divide, this study uses both focus group discussions and in-depth interviews to explore Internet and social media use patterns, and extent of reproduction of the second and third levels of digital divide among communities in the country during Covid-19 pandemic.

Background: Bariatric surgery in Saudi Arabia has become one of the most performed surgical procedures for weight loss surgery (WLS). The aim of this survey is to highlight the importance of education and training in bariatric anesthesia (BA). Methods: An Internet-based cross-sectional survey was conducted to examine the percentages of general anesthesiologists among respondents who supported the need for formal structured training in BA as the primary outcome. A 41 items questionnaire on different aspects of BA included in this survey. All anesthesiologists in KSA participated in this survey. Results: 42% responded giving anesthesia for bariatric surgery/year between 25 and 50% of cases/year. 22% responded performing 25–50 cases/month, 21% from 10–25 cases, and 14% from 50–100 cases. Compared with how many elective bariatric surgical procedures performed in your center/month revealed significant differences (P < 0.05), 39% responded with no dedicated team in their center, 14% for 0.05), upon asking on how many trained/skilled anesthesiologists in bariatric anesthesia in your center, 24% reported none, 4% only one, 21% 2–5 anesthesiologists, 12% 5–10 anesthesiologists, and 19% of the respondents reported more than 10 anesthesiologists specialized in BA. Conclusion: We believe in education and training in bariatric anesthesia. Residents’ rotation in BA should be included in their curriculum. A dedicated fellowship program to be developed at a national level as well as courses and workshops.

Abstract Acetamiprid (ACDP) is a widely used neonicotinoid insecticide that is popular for its efficacy in controlling fleas in domestic settings and for pets. Our study aims to offer a comprehensive examination of the toxicological impacts of ACDP and the prophylactic effects of cinnamon nanoemulsions (CMNEs) on the pathological, immunohistochemical, and hematological analyses induced by taking ACDP twice a ‎week for 28 days. Forty healthy rats were divided into four groups (n = 10) at random; the first group served as control rats; the second received CMNEs (2 mg/Kg body weight); the third group received acetamiprid (ACDP group; 21.7 mg/Kg body weight), and the fourth group was given both ACDP and CMNEs by oral gavage. Following the study period, tissue and blood samples were extracted and prepared for analysis. According to a GC-MS analysis, CMNEs had several bioactive ingredients that protected the liver from oxidative stress by upregulating antioxidant and anti-inflammatory agents. Our findings demonstrated that whereas ACDP treatment considerably boosted white blood cells (WBCs) and lymphocytes, it significantly lowered body weight gain (BWG), red blood cells (RBCs), hemoglobin (Hb), hematocrit (HCT), and platelets (PLT). ACDP notably reduced antioxidant enzyme activities: superoxide dismutase (SOD), glutathione peroxidase (GPx), and catalase (CAT) and elevated hydrogen peroxide and malondialdehyde levels compared with other groups. ACDP remarkably raised alanine aminotransferase (ALT), aspartate amino transaminase (AST), and alkaline phosphatase (ALP) levels. Moreover, the histopathological and immunohistochemistry assays discovered a severe toxic effect on the liver and kidney following ACDP delivery. Furthermore, cyclooxygenase 2 (COX-2) + immunoexpression was enhanced after treatment with CMNEs. All of the parameters above were returned to nearly normal levels by the coadministration of CMNEs. The molecular docking of cinnamaldehyde with COX-2 also confirmed the protective potential of CMNEs against ACDP toxicity. Our findings highlighted that the coadministration of CMNEs along with ACDP diminished its toxicity by cutting down oxidative stress and enhancing antioxidant capacity, demonstrating the effectiveness of CMNEs in lessening ACDP toxicity.

Abstract Background Cardiovascular magnetic resonance-feature tracking (CMR-FT) is a novel quantitative objective noninvasive technique in the assessment of myocardial deformation. The purpose of that study was to assess the capability of the CMR-FT in the detection of myocardial ischemia and viability. We investigated 30 patients (n = 480 myocardial segments), with known or suspected coronary artery disease (CAD). Dobutamine stress cardiovascular magnetic resonance (DS-CMR) and late gadolinium enhancement (LGE) were used to identify the viable non-ischemic, ischemic, and non-viable myocardial segments. Cine images at rest were used to calculate the segmental radial (Err), circumferential (Ecc), and longitudinal (Ell) strain parameters by manual contouring of endocardial and epicardial borders using Segment Software. Results Of the 480 myocardial segments and based on the DS-CMR and LGE results, 338 segments were defined as viable non-ischemic (remote), 101 segments were viable ischemic, and 41 segments were non-viable. Rest segmental Ecc, Err, and Ell values were significantly impaired in the non-viable (mean ± SD = − 3.94 ± 4.99%, 11.81 ± 12.55%, and − 7.50 ± 6.96%, respectively) compared to both viable groups, p