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Mastering vocabulary is essential for language acquisition, particularly in Arabic. This study aims to develop and evaluate the feasibility and effectiveness of AVLI (Arabic Vocabulary on Lectora Inspire) for grade X students at Baitul Jannah Integrated Islamic High School. Employing a research and development approach, this study utilized the ADDIE development model, which includes analysis, design, development, implementation, and evaluation phases. Data were collected through documentation, observation, interviews, questionnaires, and tests. The findings revealed that the Lectora Inspire-based mufradat learning media is deemed feasible, achieving a feasibility test score of 75% from material expert validators and 90% from media validators. User feedback was positive, with 86% of 106 respondents finding the learning media engaging. Moreover, AVLI proved effective in enhancing mufradat learning, evidenced by an increase in average student scores from 65.5 on the pretest to 85.5 on the posttest, a rise of 30 points. Consequently, this study concludes that Lectora Inspire-based learning media is both feasible and effective for teaching mufradat to grade X students, highlighting its potential implications for Arabic language education.

Abstract Recently, low Earth orbit (LEO) satellites have emerged as key players in space information network (SIN) due to their ability to provide global coverage. However, they remain susceptible to threats such as denial of service (DoS), man-in-the-middle (MITM), and spoofing attacks. In this paper, we propose a cross-layer security framework (CLSF) to address these vulnerabilities. Our approach begins by employing a physically unclonable function (PUF) at the upper layer to establish mutual authentication between legitimate satellites and ground stations, while also securely exchanging frequency seeds for the next phase. Following this, dynamic seed frequency hopping (DSFH) is applied at the physical layer to counter DoS, MITM, and spoofing attacks. Additionally, the frequency transitions of malicious satellites are modeled using a Markov chain. Our results demonstrate that the proposed CLSF, which integrates PUF and DSFH, delivers strong security performance.

Characterizing the epidemiology of circulating respiratory pathogens during the COVID-19 pandemic could clarify the burden of acute respiratory infections and monitor outbreaks of public health and military relevance. The US Department of Defense supported 2 regions for influenza-like illness and severe acute respiratory infections surveillance, one in the Middle East through US Naval Medical Research Unit EURAFCENT, and another in Latin America through US Naval Medical Research Unit SOUTH. During 2020‒2022, coinciding with the COVID-19 pandemic, we collected a total of 16,146 nasopharyngeal and oropharyngeal swab samples from sentinel sites in Jordan (n = 11,305) and Latin America (n = 4,841). Samples were tested for SARS-CoV-2, influenza, and other respiratory pathogens. SARS-CoV-2 was the most frequently detected pathogen during 2020; other respiratory pathogens had distinct temporal and frequency distributions according to geographic location. Our findings support the need for continued sentinel surveillance as a vital tool for assessing the burden of respiratory diseases globally.

Surveillance of antimicrobial resistance in Kenya, Uganda, and Jordan identified multidrug-resistant high-risk bacterial clones: Escherichia coli sequence types 131, 1193, 69, 167, 10, 648, 410, 405 and Klebsiella pneumoniae sequence types 14, 147, 307, 258. Clones emerging in those countries exhibited high resistance mechanism diversity, highlighting a serious threat for multidrug resistance.

Abstract Background Metabolic-associated fatty liver disease (MAFLD) has emerged as the predominant form of chronic liver disease globally linked with heightened cardiovascular disease (CVD) risk, the leading cause of mortality among affected individuals. Aim This study aims to assess serum PTX3 (pentraxin 3) and platelet-derived growth factor receptor beta (PDGFRβ) as potential non-invasive biomarkers for predicting cardiovascular risk (CVR) in MAFLD patients. Method A case–control investigation encompassing 84 MAFLD patients without prior CVD history and 30 age- and gender-matched healthy controls was conducted. Both cohorts underwent comprehensive laboratory and radiological evaluations. CVR was evaluated through common carotid artery intima-media thickness (IMT), Framingham risk score, and QRISK 2 score. The efficacy of two ELISA biomarkers PTX3 and PDGFRβ was examined for correlation with CVR in MAFLD patients. Results MAFLD patients displayed significantly heightened levels of PTX3 and PDGFβ compared to healthy controls (P

Abstract Background One of the most often used bedside surgical techniques in critical care units (ICUs) for critically ill individuals who need prolonged mechanical ventilation is percutaneous dilatational tracheostomy (PDT). Numerous difficulties may arise from puncturing the esophagus or making a false passage during surgery. Objectives To compare the use of laryngeal mask airway (LMA) and endotracheal tube (ETT) during PDT guided by ultrasonography (US) or bronchoscopy. Methods Our study was a prospective cohort of 120 patients admitted to the Critical Care Department at Kasr Alainy Hospital and Damanhur Medical National Institute between March 2020 and November 2021. Hemodynamics, arterial blood gasses, complications, and outcomes of the patients were recorded. Results The studied patients were divided into the ETT and LMA groups (60 patients in each group). Then, each group was subdivided into two subgroups (ETT-US, ETT-Bronch, LMA-US, and LMA-Bronch; 30 patients in each subgroup) according to the guiding procedure used for puncturing the trachea: US-guided or bronchoscopy-guided. Regarding HR, there was no statistically significant difference between the two groups or four subgroups before, during, and after the procedure. In addition, there was no statistically significant difference between the two studied groups regarding MAP before the procedure. However, during and after the procedure, MAP was significantly higher in the ETT group. There was no discernible change in oxygen saturation or PaO2 before, during, or after the procedure. However, there was no discernible difference in PaCO2 levels before and after the procedure; it was much greater in the ETT group and ETT-Bronch subgroup during the process. Furthermore, there was no statistically significant variation in the number of punctures between the two groups or the four subgroups. The length of the process varied significantly across the two major groups and the four evaluated subgroups. The LMA group had the shortest procedure duration (5.05 ± 1.28 min), the LMA-Bronch subgroup (4.79 ± 1.42 min), and the LMA-US subgroup (5.31 ± 1.10 min), while the ETT had the longest procedure duration group (5.86 ± 1.11 min), the ETT-Bronch subgroup (6.09 ± 1.23 min), and ETT-US (5.63 ± 0.94 min). Regarding complications, there was no considerable difference between the two groups or four subgroups except aerophagia. Aerophagia was considerably more common in the LMA group (7 candidates) and was not observed in the ETT group. Conclusions Our study concluded that the laryngeal mask airway improves ventilation during percutaneous dilatation tracheostomy, especially when used with ultrasound, and thus can be used for candidates with traumatic brain injury and brain edema.

Abstract For Egypt, ethane is a vital chemical precursor, with the potential to significantly attract financial resources and drive economic growth. Enhancing its added value necessitates efficient recovery of ethane before it enters the national grid without processing. This research investigates the technical and economic feasibility of integrating natural gas liquids (NGLs) from three Egyptian NGLs plants—South Western Desert NGLs (SWD NGLs), North Western Desert NGLs (NWD NGLs), and East Mediterranean NGLs (EMD NGLs)—to improve ethane recovery from natural gas fields. The study focuses on revamping these NGLs plants using various NGLs recovery techniques, conducting a comprehensive comparison to identify the most effective methods for processing rich feed gas. Detailed design of the NGLs recovery processes was developed using HYSYS V.14 simulation software and supplementary calculation sheets. The design criteria encompass both technical and economic parameters to ensure a holistic approach in meeting project requirements. Results indicate a significant increase in ethane recovery: 16% for SWD NGLs, 10% for NWD NGLs (A, B, C), and 85% for EMD NGLs. This improvement will boost ethane feedstock for petrochemical companies from 2000 ton/day to 3500 ton/day, enabling increased polyethylene production. Economic analysis for the base case shows an expected internal rate of return (IRR) of 26%, a net present value (NPV) of USD 73 million, and a payback period of approximately 3 years. Sensitivity analysis on product prices, feed gas prices, and total capital investment confirms the project’s economic viability, with all cases showing feasibility (IRR ≥ 15%) except when product prices fall below USD 225/ton for propane, USD 215/ton for liquefied petroleum gas (LPG), and USD 25/bbl for condensate. This study highlights the potential for enhanced ethane recovery, offering substantial economic benefits and supporting the growth of Egypt’s petrochemical industry.

Introduction: Asthma is a serious disease that affects not only the respiratory system but also the brain by decreasing oxygen saturation. Despite the numerous neuroimaging studies that have shed light on the effect of asthma on brain volume, there is still a need for new studies to evaluate brain volume in asthmatic patients. Aim: To evaluate the Grey Matter Volume (GMV) of the brain in asthmatic patients using Magnetic Resonance Imaging images (MRI) to detect possible changes. Materials and Methods: This is an observational analytic case-control study carried out at Al Amal Hospital in Khartoum State, Sudan, between January 2020 and October 2022. The study included 100 adult participants (50 asthmatic patients and 50 healthy controls) using MRI and automatic brain segmentation through a software program (BrainSuite). Data were analysed using Statistical Package for Social Science (SPSS) software, version 25.0 (IBM SPSS Inc., Chicago, IL), and Microsoft Excel 2013. An independent sample T-test was used to compare the mean of the measurements between controls and asthmatics. Frequencies, means, and standard deviations were taken. A p-value of 0.05 or less was accepted as statistically significant. Results: Out of all participants, 50 were asthmatics and 50 were controls. The mean age of asthmatics was (31±8.53) years and of controls was 32±8.49 years. The mean Grey Matter Volume (GMV) of the asthmatic patients was 575.93 cm3±71.46 SD and of controls was 569.55 cm3±73.77 SD. There were no statistically significant differences between the groups depending on the GMV of asthmatic and control participants (p>0.05). The mean GMV in asthmatic males was 355.50 cm3±53.26 SD and in females 321.65 cm3±32.72 SD, while in control males it was 367.63 cm3±45.77 SD and in females 318.03 cm3±34.16 SD. GMV showed significant statistical differences between asthmatic males and females (p0.05). Asthma disease does not result in noticeable changes in GMV in either male or female brains.

6082 Al-alloy underwent a friction stir drilling (FSD) processing. Subsequently, a two-stage post-heat treatment (PHT) procedure, i.e., solution treatment at 550 °C for 2 h, followed by artificial aging at 175 °C for 18 h, was implemented to significantly enhance microstructure and mechanical performance of the alloy. The microstructure was characterized by optical, laser, scanning electron and electron backscattered diffraction microscopes, while the mechanical behavior was assessed by a micro-indentation hardness tester, employing the indentation hardness (HIT) technique. Corrosion behavior of FSD as well as PHT specimens was investigated through electrochemical techniques.The microstructure of the base metal (BM) manifested an α-Al matrix with an average grain size of approximately 50 μm. FSD resulted in the creation of stirring zone (SZ) and thermo-mechanical affected zone (TMAZ), with respective widths of 400 ± 50 and 950 ± 100 μm. The SZ exhibited a very fine structure with an average grain size of 0.5 μm, thereby displaying increased hardness. The PHT microstructure displayed the formation of fine βʹ and βʺ second phase precipitate types, whereas the HIT hardness of the PHT α-aluminum matrix in the SZ, was lower than TMAZ and BM, due to reductions of βʹ in the SZ compared to TMAZ and BM. Moreover, the corrosion rate of the SZ decreased after the heat-treatment cycle, attributed to the recovery of strain energy induced during friction drilling and the increased solubility of solute atoms within the α-Al matrix.

Antimicrobial resistance is attributed to acquiring new mechanisms by microbes to combat antimicrobial agents, highlighting the necessity to discover new antimicrobial agents to protect human health. Graphene and its derivatives have shown antimicrobial potential due to their physical and chemical distinctive features. Potent antibacterial properties were observed by decorating the surface of graphene and its derivatives with inorganic nanoparticles, such as metal and metal oxide. In an attempt to reliably overcome antimicrobial resistance, the multifunctional nanocomposites, including FeO/NiO, FeO/NiO/GO, FeO/NiO/N-GO, and FeO/NiO/S-GO, were synthesized using a wet chemical method. Accordingly, the structural analysis was performed using X-ray diffraction (XRD), infrared spectroscopy (IR), energy dispersive X-ray (EDX), ultraviolet-visible spectroscopy (UV–vis), and scanning electron microscopy (SEM). For antibacterial potential, the synthesized nanocomposites were tested against non-resistant and resistant strains of bacteria. Notably, moderate antibacterial potential was found for FeO/NiO/N-GO nanocomposite with a MIC value of 12.5 μg/mL, compared to the MIC of pure Ciprofloxacin, a positive control, with a value of 1.25 μg/mL. Toward antifungal potential, the synthesized nanocomposites were assessed against various spores of fungal strains. In this regard, the synthesized nanocomposites were demonstrated as potent antifungal agents. Among the synthesized nanocomposites, FeO/NiO and FeO/NiO/S-GO exhibited the highest ZOI against Aspergillus flavus. Additionally, the activity of these nanocomposites was evaluated by means of total reducing power (TRP), total antioxidant capacity (TAC), and free radical scavenging. Further, the antioxidant, brine shrimp lethality, and hemolytic potential of the synthesized nanocomposites were evaluated to compare their effectiveness. According to brine shrimp lethality, all synthesized nanocomposites were sufficiently active, with a calculated median lethal concentration (LC50) showing ≥ 50 % mortality. The obtained results provide a promising base for the incorporation of nanocomposites in pharmaceutical and biomedical products.

Background/objectiveTo examine the cognitive benefits of 6 months of prescribed intermittent exercise (10-min bouts totaling 150 weekly minutes) in community-dwelling older adults, comparing effects of low-intensity movement (LIM) and moderate-intensity aerobic exercise (aerobic exercise; AE) training; and exploring biological mechanisms of exercise-related cognitive improvement.MethodTwenty-five adults (>60 years old) participated in a 6-month controlled trial and were randomized into LIM or AE intermittent training. Cognition was assessed using a neuropsychological test battery including the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), California Verbal Learning Test, 2nd Edition (CVLT-II), and Delis-Kaplan Executive Function System (D-KEFS). Neuroimaging measures were collected using a 7 T human MRI scanner. Serologic neurotrophic and inflammatory factors were analyzed using Luminex multiplex assays [brain derived neurotrophic factor (BDNF); vascular endothelial growth factor (VEGF)]; interleukin-6 (IL-6), C-reactive protein (CRP), plasminogen activator inhibitor (PAI-1).ResultsLIM and AE intermittent training had dissociable effects on cognition, with LIM resulting in improved learning and memory and AE resulting in improved executive functioning. Intervention groups differed on change in cognitive performance on CVLT-II learning and D-KEFS trail making test. Increase in right dorsolateral prefrontal cortex (DLPFC) surface area was linked to executive improvement (i.e., phonemic fluency) regardless of intervention group. A decline in circulating PAI-1 was linked to learning and memory improvement in response to LIM over 6 months.ConclusionModerate-intensity AE and LIM intermittent training likely have distinct cognitive benefits, though low-intensity activity is often included as a control group in exercise trials in aging.

Flood detection in crisis and disaster management is significantly facilitated by the analysis of synthetic aperture radar (SAR) imagery. Traditional flood detection techniques focus more on SAR image pairs than on the optical level. However, the distinctive characteristics of SAR images, characterized by limited visual information, pervasive speckle noise, and analogous backscatter signals, present formidable obstacles to accurately identifying water bodies and extracting change features. Consequently, the performance of existing methods remains unsatisfactory. This paper addresses this challenge by focusing on disparities between SAR image pairs and introducing a pioneering semantic token-based transformer network, denoted as SemT-Former, to enhance flood detection accuracy. SemT-Former operates by prioritizing changes of interest rather than fully comprehending the entire image scene. This is achieved through the integration of temporal-wise feature representation and the introduction of a class token to capture high-level segmentation associated with changes in water bodies. These innovations augment the model’s capacity to discriminate between genuine changes in water bodies and spurious changes induced by similar signals or speckle noise. The effectiveness of SemT-Former is evaluated through a case study in Khartoum, Sudan, focusing on flood detection and the estimation of damaged farmland near river confluences. Experimental results demonstrate that SemT-Former outperforms existing methods, exhibiting a 90.6% improvement in F1-score and an 88.5% enhancement in IoU. This underscores SemT-Former as a promising solution for precise and effective flood mapping from SAR images.

Kafrelsheikh, situated in the middle of the Nile Delta, significantly contributes to Egypt's aquaculture and agriculture sectors. However, the local use of organochlorine pesticides (OCPs) in agriculture is often a source of OCP residues in associated drainage waters, which may threaten aquatic ecosystems. These pesticides persist in local water bodies, jeopardizing aquatic ecosystems and potentially impacting human health. This comprehensive study assessed the seasonal variations of 17 OCPs in both water sources and Nile tilapia across eight fish farming locations in Kafrelsheikh. Using gas chromatography coupled with mass spectrometry (GC-MS), we detected OCP concentrations in water that varied seasonally where winter recorded the highest levels at 22.5 ng/mL and, summer showed the lowest levels at 6.2 ng/mL. Despite water samples occasionally showing risk quotients (RQs) greater than 1, indicating a potential threat to aquatic life, the OCP levels in Nile tilapia were sufficiently low, with target hazard quotients (THQ) below 1, suggesting no significant risk for human consumption. The research highlights a pressing need for regular environmental monitoring and stricter regulatory control over pesticide use to protect aquatic life and ensure the safety of aquaculture products. These findings provide a critical basis for policy-making, aimed at balancing agricultural productivity with environmental sustainability in regions heavily dependent on both.

While recognition of sign language alphabets and isolated words has matured in recent years, recognition of sign language sentences, or continuous signing, is still a research topic of interest in computer vision, especially in signer independent mode of recognition. Existing state-of-the-art solutions in the continuous Arabic Sign Language Recognition (ArSLR) are promising; however, when implemented in signer independent mode, the accuracies drop noticeably. In this paper, we propose a solution for recognizing continuous Arabic signing in signer dependent and independent modes through the use of motion images with positioning information. Initially, sign videos are converted into several motion images, each emphasizing a different segment of the sentence. This is achieved by a weighted sum of residual images after applying optical flow and motion compensation. Each motion image is composed of the whole sentence video, hence putting the emphasized segment into context in terms of previous and successive sign words. Thereafter, hand-crafted features are calculated from each resultant image, including numerical summaries of the horizontal, vertical and diagonal profiles. With such features, the architecture used for model generation and testing is simplified, where it consists of a single Bi-LSTM layer followed by dropout, softmax, and classification layers. This paper makes use of a recent Arabic Sign Language dataset known as ArabSign. The dataset is composed of 6 signers and 93 words arranged into 50 sentences with 30 repetitions each. Experimental results revealed that the proposed solution is suitable for signer dependent and signer independent modes of continuous sign language recognition. Using a Leave-One-Signer-Out policy, the proposed solution achieved word-recognition rates of 99.8% and 75.3%, respectively. These results noticeably surpass relevant state-of-the-art solutions.

Pea is a commercially significant legume that is widely utilized worldwide and has a elevated amount of nutrition and bioactive components. Its consumption is attributed to a number of health benefits and its potential as a functional food. Fulvic acid can be used as a bio-stimulant to promote plant growth and increase nutrient availability and uptake. A field experiment was designed during two subsequent cropping seasons (i.e., 2022–23 and 2023–24) to evaluate the impact of two methods of fulvic acid application of seed priming and foliar spray on the growth, yield, antioxidant content, and nutritional value of pea (Pisum sativum L.) plants. The seeds were primed with fulvic acid at 1.5, 3 g L−1, and water, while a foliar spray of fulvic acid with the same doses was performed on the seedlings of non-primed seeds. The results obtained exhibited that the seed priming technique with fulvic acid outperformed the fulvic acid foliar applications. The increase in the fulvic acid dose to 3 g L−1 in both application techniques exhibited the highest plant growth, heaviest fresh and dry weights, and highest green seed yield. The maximum growth parameters were recorded after the foliar spray treatment at a dose of 3 g L−1, as it led to improvement in the growth parameters, leaf pigments, and total carbohydrates. The highest number of seeds per pod, number of pods per plant, 100-seed weight, and seed yield were obtained by the seed priming technique. From the results obtained, it may be concluded that the application of fulvic acid at 3 g L−1 via the seed priming technique is beneficial for enhancing the productivity of peas.

This study examines the differences in the adoption and effectiveness of artificial intelligence (AI) in language learning between Indonesia and Arab countries. Using a quantitative comparative approach, data were collected from 200 educational institutions across both regions. The findings reveal significant disparities in AI adoption, with Arab countries showing a higher level of integration and effectiveness compared to Indonesia. This is attributed to better technological infrastructure, stronger policy support, and more comprehensive teacher training programs in Arab countries. In contrast, Indonesia faces challenges such as limited access to technology and less comprehensive AI integration, which impact the effectiveness of AI in enhancing language skills. The study suggests that for AI to deliver maximum benefits in language learning, a holistic approach is necessary, including investments in infrastructure, extensive teacher training, and fostering a more innovative educational culture. The findings provide valuable insights not only for Indonesia and Arab countries but also for other nations seeking to integrate AI into their educational systems.

The development of innovative non-invasive neuroimaging methods and biomarkers is critical for studying brain disease. Imaging of cerebrospinal fluid (CSF) pulsatility may inform the brain fluid dynamics involved in clearance of cerebral metabolic waste. In this work, we developed a methodology to characterize the frequency and spatial localization of whole brain CSF pulsations in humans. Using 7 Tesla (T) human magnetic resonance imaging (MRI) and ultrafast echo-planar imaging (EPI), in-vivo images were obtained to capture pulsations of the CSF signal. Physiological data were simultaneously collected and compared with the 7 T MR data. The primary components of signal pulsations were identified using spectral analysis, with the most evident frequency bands identified around 0.3, 1.2, and 2.4 Hz. These pulsations were mapped spatially and temporally onto the MR image domain and temporally onto the physiological measures of electrocardiogram and respiration. We identified peaks in CSF pulsations that were distinct from peaks in grey matter and white matter regions. This methodology may provide novel in vivo biomarkers of disrupted brain fluid dynamics.

Introduction Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease in adults. As a social media platform, YouTube has tremendous potential to both support and hinder public health efforts. The aim of this study was to assess the reliability and quality of the most viewed English-language YouTube videos on ADPKD. Methods A YouTube search was conducted on 3 August 2023, using the keyword ADPKD disease and the top 200 videos were analyzed for relevance. Videos in the “Short” category that were duplicates, were not in English, were not audio or visual, and contained advertisements were excluded. Two reviewers divided the 159 included videos into groups based on their source and content. Results In 106 (66.7%) of the 159 videos, general information about the disease was given, 58 (36.5%) discussed medical treatment, 11 (6.9%) discussed surgical treatment, 30 (18.9%) included patient images and radiological images, and eight (5%) discussed the genetic and pathological features of the disease. Additionally, 16 (10.1%) videos fell into the “other” category. According to the Journal of the American Medical Association, Quality Criteria for Consumer Health Information and Global Quality Scale scoring systems, videos uploaded by health associations and foundations received the highest scores (3 (1–4), 54 (28–70), 4 (1–5), respectively). Conclusion Academic institutions and other official health organizations such as Health Associations/Foundations need to use YouTube more effectively to disseminate accurate, reliable and useful health-related information to society.

Avian encephalomyelitis (AE) is a disease caused by the avian encephalomyelitis virus (AEV) of the genus Tremovirus in the family Picornaviridae. Recently, cases of turkey poults showing neurological signs were submitted to the veterinary diagnostic laboratories at South Dakota State University and the University of Minnesota. The affected birds were showing nervous neurological signs such as tremors, inability to stand, torticollis, and wing drop. Clinical signs were observed by 3 weeks of age. Necropsy of birds revealed no significant gross lesions in the internal organs, including the brain. There was no significant bacterial growth in the brains. Microscopic examination of various sections of the brain revealed multifocal lymphocplasmacytic perivascular cuffs in the cerebellum and cerebral cortex. The brain samples were processed for detection and whole genome sequencing by next-generation sequencing. Three full-length polyprotein sequences (6405 nt) of AEV were assembled. All three sequences shared 99.9–100% nucleotide and 100% amino acid identities with each other. Only 77.7–78.5% of nucleotide and 90.3–92.5% of amino acid identities with AEV field strains and vaccine sequences were available in GenBank. This indicates that a new divergent variant of AEV is circulating in the field and causing AE outbreaks in the Midwest region.

This paper aims to explore the possibility of utilizing vision transformers (ViTs) for on-edge medical diagnostics by experimenting with the Kvasir-Capsule image classification dataset, a large-scale image dataset of gastrointestinal diseases. Quantization techniques made available through TensorFlow Lite (TFLite), including post-training float-16 (F16) quantization and quantization-aware training (QAT), are applied to achieve reductions in model size, without compromising performance. The seven ViT models selected for this study are EfficientFormerV2S2, EfficientViT_B0, EfficientViT_M4, MobileViT_V2_050, MobileViT_V2_100, MobileViT_V2_175, and RepViT_M11. Three metrics are considered when analyzing a model: (i) F1-score, (ii) model size, and (iii) performance-to-size ratio, where performance is the F1-score and size is the model size in megabytes (MB). In terms of F1-score, we show that MobileViT_V2_175 with F16 quantization outperforms all other models with an F1-score of 0.9534. On the other hand, MobileViT_V2_050 trained using QAT was scaled down to a model size of 1.70 MB, making it the smallest model amongst the variations this paper examined. MobileViT_V2_050 also achieved the highest performance-to-size ratio of 41.25. Despite preferring smaller models for latency and memory concerns, medical diagnostics cannot afford poor-performing models. We conclude that MobileViT_V2_175 with F16 quantization is our best-performing model, with a small size of 27.47 MB, providing a benchmark for lightweight models on the Kvasir-Capsule dataset.

Pyocyanin is considered a maker of Pseudomonas aeruginosa (P. aeruginosa) infection. Pyocyanin is among the toxins released by the P. aeruginosa bacteria. Therefore, the development of a direct detection of PYO is crucial due to its importance. Among the different optical techniques, the Raman technique showed unique advantages because of its fingerprint data, no sample preparation, and high sensitivity besides its ease of use. Noble metal nanostructures were used to improve the Raman response based on the surface-enhanced Raman scattering (SERS) technique. Anodic metal oxide attracts much interest due to its unique morphology and applications. The porous metal structure provides a large surface area that could be used as a hard template for periodic nanostructure array fabrication. Porous shapes and sizes could be controlled by controlling the anodization parameters, including the anodization voltage, current, temperature, and time, besides the metal purity and the electrolyte type/concentration. The anodization of aluminum foil results in anodic aluminum oxide (AAO) formation with different roughness. Here, we will use the roughness as hotspot centers to enhance the Raman signals. Firstly, a thin film of gold was deposited to develop gold/alumina (Au/AAO) platforms and then applied as SERS-active surfaces. The morphology and roughness of the developed substrates were investigated using scanning electron microscopy (SEM) and atomic force microscopy (AFM) techniques. The Au/AAO substrates were used for monitoring pyocyanin secreted from Pseudomonas aeruginosa microorganisms based on the SERS technique. The results showed that the roughness degree affects the enhancement efficiency of this sensor. The high enhancement was obtained in the case of depositing a 30 nm layer of gold onto the second anodized substrates. The developed sensor showed high sensitivity toward pyocyanin with a limit of detection of 96 nM with a linear response over a dynamic range from 1 µM to 9 µM.

Objectives: The aim of this study was to examine the impact of the pentraxin 3 (PTX3) serum level and angiotensin-converting enzyme (ACE) gene insertion/deletion (I/D) polymorphism on the severity of radiographic pulmonary infiltrates and the clinical outcomes of COVID-19. Methods: The severity of COVID-19 pulmonary infiltrates was evaluated within a week of admission by analyzing chest X-rays (CXR) using the modified Brixia (MBrixa) scoring system. The insertion (I)/deletion (D) polymorphism of the ACE gene and the serum levels of PTX3 were determined for all patients included in the study. Results: This study included 80 patients. Using a cut-off serum level of PTX3 ≥ 2.765 ng/mL, the ROC analysis (AUC 0.871, 95% CI 0.787–0.954, p < 0.001) showed a sensitivity of 85.7% and specificity of 78.8% in predicting severe MBrixa scores. Compared to ACE I/I polymorphism, D/D polymorphism significantly increased the risk of severe CXR infiltrates, OR 7.7 (95% CI: 1.9–30.1), and p = 0.002. Significant independent predictors of severe CXR infiltrates include hypertension (OR 7.71), PTX3 (OR 1.20), and ACE D/D polymorphism (OR 18.72). Hypertension (OR 6.91), PTX3 (OR 1.47), and ACE I/I polymorphism (OR 0.09) are significant predictors of poor outcomes. Conclusion: PTX3 and ACE D/D polymorphism are significant predictors of the severity of COVID-19 pneumonia. PTX3 is a significant predictor of death.

Key Clinical Message We are reporting a case of hypothyroidism presenting as fissured tongue, demonstrating significant resolution of fissure tongue upon thyroid hormone replacement therapy.

Mycobacterium tuberculosis is a lethal human pathogen, with the key flavoenzyme for catalyzing bacterial cell-wall biosynthesis, decaprenylphosphoryl-D-ribose oxidase (DprE1), considered an Achilles heal for tuberculosis (TB) progression. Inhibition of DprE1 blocks cell wall biosynthesis and is a highly promising antitubercular target. Macozinone (PBTZ169, a benzothiazinone (BTZ) derivative) is an irreversible DprE1 inhibitor that has attracted considerable attention because it exhibits an additive activity when combined with other anti-TB drugs. Herein, 754 BTZ analogs were assembled in a virtual library and evaluated against the DprE1 target using a covalent docking approach. After validation of the employed covalent docking approach, BTZ analogs were screened. Analogs with a docking score less than -9.0 kcal/mol were advanced for molecular dynamics (MD) simulations, followed by binding energy evaluations utilizing the MM-GBSA approach. Three BTZ analogs-namely, PubChem-155-924-621, PubChem-127-032-794, and PubChem-155-923-972- exhibited higher binding affinities against DprE1 compared to PBTZ169 with ΔGbinding values of -77.2, -74.3, and -65.4 kcal/mol, versus -49.8 kcal/mol, respectively. Structural and energetical analyses were performed for the identified analogs against DprE1 throughout the 100 ns MD simulations, and the results demonstrated the great stability of the identified BTZ analogs. Physicochemical and ADMET characteristics indicated the oral bioavailability of the identified BTZ analogs. The obtained in-silico results provide promising anti-TB inhibitors that are worth being subjected to in-vitro and in-vivo investigations.

The study of the interactions between biomolecules and nanostructures is quite fascinating. Herein, the adsorption propensity of beryllium oxide (Be12O12) nanocarrier toward nucleobases (NBs) was investigated. In terms of DFT calculations, the adsorption tendency of Be12O12 toward NBs, including cytosine (NB-C), guanine (NB-G), adenine (NB-A), thymine (NB-T), and uracil (NB-U), was unveiled through various configurations. Geometrical, electronic, and energetic features for Be12O12, NBs, and their associated complexes were thoroughly evaluated at M06-2X/6-311+G** level of theory. The potent adsorption process within NBs∙∙∙Be12O12 complexes was noticed through favorable interaction (Eint) and adsorption (Eads) energies with values up to -53.04 and -38.30 kcal/mol, respectively. Generally, a significant adsorption process was observed for all studied complexes, and the favorability followed the order: NB-C∙∙∙ > NB-G∙∙∙ > NB-A∙∙∙ > NB-T∙∙∙ > NB-U∙∙∙Be12O12 complexes. Out of all studied complexes, the most potent adsorption was found for NB-C∙∙∙Be12O12 complex within configuration A (Eint = -53.04 kcal/mol). In terms of energy decomposition, SAPT analysis revealed electrostatic (Eelst) forces to be dominant within the studied adsorption process with values up to -99.88 kcal/mol. Analyzing QTAIM and NCI, attractive intermolecular interactions within the studied complexes were affirmed. From negative values of thermodynamic parameters, the nature of the considered adsorption process was revealed to be spontaneous and exothermic. Regarding density of state, IR, and Raman analyses, the occurrence of the adsorption process within NBs∙∙∙Be12O12 complexes was confirmed. Noticeable short recovery time values were observed for all studied complexes, confirming the occurrence of the desorption process. The findings provided fundamental insights into the potential application of Be12O12 nanocarrier in drug and gene delivery processes.

[This corrects the article DOI: 10.1371/journal.pone.0253155.].

Epstein-Barr virus (EBV) was the first tumor virus identified in humans, and it is mostly linked to lymphomas and cancers of epithelial cells. Nevertheless, there is no FDA-licensed drug feasible for this ubiquitous EBV viral contagion. EBNA1 (Epstein-Barr nuclear antigen 1) plays several roles in the replication and transcriptional of latent gene expression of the EBV, making it an attractive druggable target for the treatment of EBV-related malignancies. The present study targets EBV viral reactivation and upkeep by inhibiting EBNA1 utilizing a drug-repurposing strategy. To hunt novel EBNA1 inhibitors, a SuperDRUG2 database (> 4,600 pharmaceutical ingredients) was virtually screened utilizing docking computations. In accordance with the estimated docking scores, the most promising drug candidates then underwent MDS (molecular dynamics simulations). Besides, the MM-GBSA approach was applied to estimate the binding affinities between the identified drug candidates and EBNA1. On the basis of MM-GBSA//200 ns MDS, bezitramide (SD000308), glyburide (SD001170), glisentide (SD001159), and glimepiride (SD001156) unveiled greater binding affinities towards EBNA1 compared to KWG, a reference inhibitor, with ΔGbinding values of -44.3, -44.0, -41.7, -40.2, and -32.4 kcal/mol, respectively. Per-residue decomposition analysis demonstrated that LYS477, ASN519, and LYS586 significantly interacted with the identified drug candidates within the EBNA1 binding pocket. Post-dynamic analyses also demonstrated high constancy of the identified drug candidates in complex with EBNA1 throughout 200 ns MDS. Ultimately, electrostatic potential and frontier molecular orbitals analyses were performed to estimate the chemical reactivity of the identified EBNA1 inhibitors. Considering the current outcomes, this study would be an adequate linchpin for forthcoming research associated with the inhibition of EBNA1; however, experimental assays are required to inspect the efficiency of these candidates.

BackgroundHuman biomonitoring is crucial for regulatory toxicology, yet data on biomarker concentrations in the UAE are lacking. This study addresses this gap by analyzing urinary concentrations of 16 metals in UAE young adults, assessing correlations with personal characteristics, dietary patterns, and lifestyle habits.MethodsA cross-sectional pilot study was conducted among 144 randomly selected young adults (71 males and 73 females) from Sharjah, UAE, between January and March 2023. Participants provided urine samples, which were analyzed for 16 heavy metals using ICP-OES, and completed detailed questionnaires covering sociodemographic factors, lifestyle, and dietary habits. Descriptive statistics were used to summarize participant characteristics, and linear regression analysis was applied to explore associations between metal concentrations and factors such as gender, dietary habits, and exposure to environmental risks. Non-parametric tests, including the Mann-Whitney test, were used to assess differences by gender. Statistical significance was set at p < 0.05. Ethical approval was obtained, and informed consent was secured before participation.ResultsSignificant findings include dietary influences on metal exposure, with rice consumption linked to higher metal concentrations. Sex differences were significant, with females showing elevated levels of arsenic, lead, and cadmium. Lifestyle factors, such as smoking and incense use, were correlated with increased barium and boron levels.ConclusionThis study highlights the significant role of dietary habits, especially the consumption of rice, in metal exposure among young adults in Sharjah. The findings highlight the urgent need for comprehensive human biomonitoring to understand environmental exposures and reform public health policies. The gender-specific differences in metal distribution suggest the necessity for targeted public health strategies. The study, however, is limited by its cross-sectional nature and the focus on a specific geographic area, warranting further research for broader generalizability. Future investigations, particularly on the impact of incense exposure on metal levels, are essential for developing comprehensive health interventions and preventive strategies in the UAE.

BackgroundRussian current (RC), a well-known neuromuscular electrical stimulation operating at 2500 Hz, has demonstrated significant strength improvement over traditional exercises due to its high tolerance and low pain provocation. Despite extensive NMES parameter research, the specific effects of expert modes, particularly ON2 and Rest, remain unexplored. This study investigates the direct effect of these expert modes on quadriceps muscle strength in healthy adults.MethodsThis is a single-blind, randomization-controlled trial. Forty-eight healthy university students (31 females, 17 males) were assigned in two randomized experimental groups either the ON2 or Rest mode for a 15-minute electrical stimulation session. Quadriceps maximum voluntary isokinetic contraction measurements were taken before and directly after RC application using Biodex Medical Systems 4 pro isokinetic dynamometer.ResultsBoth RC modes significantly increased the quadriceps muscle torque in healthy adults compared to baseline (pConclusionThe findings of this study align with previous research on NMES and RC supporting the idea that electrical stimulation enhances muscle strength, selecting the appropriate RC expert modes can assist physiotherapist in tailoring rehabilitation program to achieve their specific strength goals.

ObjectivesThis pilot study primarily aimed to detect the adherence as well as the effect size required to estimate the actual sample size needed for a larger scale study to compare and evaluate the effectiveness of two extracorporeal shock wave therapy (ESWT) protocols along, with a physical therapy program in reducing pain and improving function among patients suffering from plantar fasciitis. The study also aimed to report the effects of the ESWT protocols used on pain and function.MethodsA total of 26 participants took part in the study, including 17 females and 9 males. The average age of the participants was 34 years with a body mass index (BMI) of 23 kg/m2. Participants were divided into three equal groups; Group A received ESWT at a frequency of 15 Hz and intensity of 3, Group B received ESWT at a frequency of 10 Hz and intensity of 4, while Group C underwent the selected physical therapy program along with sham shock wave therapy as a control. Pain levels were assessed using the Visual Analog Scale (VAS) while functional improvements were evaluated using the Foot Function Index (FFI). Data was collected prior to treatment, after three sessions and at the end of six weeks (after six sessions).ResultsThe three groups were well matched, and the results revealed high adherence rates (90%, 90% and 80% respectively). Results also indicated reductions in pain levels and improvements in function for both intervention groups when compared to the control group. Group A demonstrated better outcomes compared to Group B while Group C showed relatively less improvement.ConclusionThe study concluded a high adherence rate for the three groups as well as a small effect size detected of 0.282 that would suggest a total of 123 participants to be required to replicate the study on a larger scale. With regards to the findings of this pilot, the combination of ESWT and a targeted physical therapy program revealed a possible effective therapeutic approach for plantar fasciitis, with a higher frequency potentially yielding more favourable results.

This study presents a comprehensive analysis of utilizing TensorFlow Lite on mobile phones for the on-edge medical diagnosis of lung diseases. This paper focuses on the technical deployment of various deep learning architectures to classify nine respiratory system diseases using X-ray imagery. We propose a simple deep learning architecture that experiments with six different convolutional neural networks. Various quantization techniques are employed to convert the classification models into TensorFlow Lite, including post-classification quantization with floating point 16 bit representation, integer quantization with representative data, and quantization-aware training. This results in a total of 18 models suitable for on-edge deployment for the classification of lung diseases. We then examine the generated models in terms of model size reduction, accuracy, and inference time. Our findings indicate that the quantization-aware training approach demonstrates superior optimization results, achieving an average model size reduction of 75.59%. Among many CNNs, MobileNetV2 exhibited the highest performance-to-size ratio, with an average accuracy loss of 4.1% across all models using the quantization-aware training approach. In terms of inference time, TensorFlow Lite with integer quantization emerged as the most efficient technique, with an average improvement of 1.4 s over other conversion approaches. Our best model, which used EfficientNetB2, achieved an F1-Score of approximately 98.58%, surpassing state-of-the-art performance on the X-ray lung diseases dataset in terms of accuracy, specificity, and sensitivity. The model experienced an F1 loss of around 1% using quantization-aware optimization. The study culminated in the development of a consumer-ready app, with TensorFlow Lite models tailored to mobile devices.

Education policies help to improve society by decreasing inequities and establishing effective learning environments. Periodic assessments can help researchers and policymakers uncover new obstacles and ensure progress on these ever-changing education policy concerns using critical theory. Bibliometric studies, a type of periodic study, emphasize the importance of data-driven approaches in the formulation and implementation of education policies. This study conducts a bibliometric analysis of education policy issues from 2000 to 2023. Based on keywords, we initially selected 931 articles from the Web of Science (WoS) database. Only articles in English were included, and we used PRISMA guidelines to reduce the number of articles to 363. We focused on citations, publication frequency, topics, trends, and issues. Two independent researchers analyzed the documents for reliability. For validity, we used transferability. We also used a content analysis of frequently cited articles. Our analysis revealed three prominent trends. The first trend pertained to controversial environmental issues and sustainability concepts in education policy. The second theme was professional development, special education, and school choice. The third one was science, vocational education, special education, and ICT. The content analysis results indicated that teaching and learning, professional development, science education, subject matter teaching, and mobile learning were the topics of the content analyzed articles. We found that relying solely on bibliometric review resulted in broad conceptualizations of educational policy issues, focusing primarily on efficiency and effectiveness. Additionally, we applied critical theoretical frameworks to conduct a more comprehensive analysis of the emergent issues identified through bibliometric analysis.

Motivational deficits and reduced goal-directed behavior for external rewards have long been considered an important features of negative symptoms in patients with schizophrenia (SCZ). Negative symptoms have also a high prevalence in bipolar disorder (BP). We used a transdiagnostic approach in order to examine association between negative symptoms and effort allocation for monetary rewards. 41 patients with SCZ and 34 patients with BP were enrolled in the study along with 41 healthy controls (HC). Effort-Expenditure for Rewards Task (EEfRT) was used to measure subjects' effort allocation for monetary rewards. Generalized estimating equation models were used to analyze EEfRT choice behavior. Negative symptoms were assessed using the Brief Negative Symptom Scale (BNSS). SCZ and BP groups expended lower effort to obtain a monetary rewards compared to HC. Severity of negative symptoms was negatively correlated with EEfRT performance in both diagnostic groups. Each diagnostic group showed lower effort allocation for monetary rewards compared to HC suggesting reduced motivation for monetary rewards. In addition, our results suggest that abnormal effort-based decision-making might be a transdiagnostic factor underlying negative symptoms., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 Elsevier B.V. All rights reserved.)