Search Results (3,548)

Background: Self-medication with leftover antibiotics (SMLA) drives antimicrobial resistance (AMR), particularly in developing countries. This study examined knowledge–practice gaps regarding antibiotic use and handling among individuals with prior SMLA across seven developing countries. Methods: A cross-sectional study (February 2023–February 2024) included 3191 adults from Bangladesh, Brazil, Egypt, India, Jordan, Lebanon, and Serbia who reported previous leftover antibiotic use. The questionnaires assessed knowledge of antibiotic use (15 items), resistance (12 items), and SMLA risks (15 items). Storage and disposal practices were evaluated using dichotomized correct/incorrect measures. Results: Participants demonstrated above-average knowledge scores as follows: antibiotic use (54.4 ± 8.4), resistance (43.3 ± 6.1), and SMLA risks (58.4 ± 10.3). However, substantial practice gaps emerged. Only 21.9% properly disposed of leftover antibiotics, while 47.0% used household garbage. For storage, 55.1% used appropriate methods, but 32.6% stored antibiotics inappropriately, and 12.8% lacked protocols. Serbian participants showed the highest SMLA risk knowledge (64.3 ± 10.6), Bangladeshi participants the lowest (52.0 ± 8.5, p < 0.001). Women had superior knowledge (59.6 ± 10.4 versus 56.5 ± 9.8, p < 0.001) and storage practices (56.6% versus 52.7%, p = 0.031). Paradoxically, higher AMR knowledge was associated with poorer disposal practices (OR = 0.97, p < 0.001). Conclusions: Despite extensive theoretical knowledge, unsafe medication practices persist, revealing a critical knowledge–practice gap. Our findings challenge education-focused AMR approaches, suggesting cognitive awareness alone cannot drive behavioral change. Effective interventions must address structural barriers, cultural factors, and individual health beliefs beyond traditional knowledge-deficit models. Full article

In recent years, herbal medicines (HMs) have been gaining significant attention as alternative or complementary therapeutic options. This is because synthetic drugs are expensive and have side effects, but also because herbal medicines have a rich content of effective bioactive compounds. These natural agents have been widely investigated for their potential in the prevention and management of chronic diseases including cardiovascular disorders, infections, metabolic disorders, neurological disorders, inflammatory disorders digestive diseases, oxidative stress-related diseases, and diabetes mellitus. In this review, we highlight the roles and impacts of various medicinal plants originating from diverse families, showing their bioactive characteristics, and the mechanisms through which they exert antidiabetic effects by regulating insulin secretion, oxidative stress, glucose uptake, and inflammatory pathways. In contrast to previous reviews, our study highlights the role of plants that are less explored, and integrates recent findings as well as future directions and biotechnological applications in plant-based management of diabetes. Full article

The SS Thistlegorm, a British World War II cargo vessel sunk in 1941 in the Red Sea, is one of the world’s most visited wreck dives, attracting thousands of divers annually. This popularity has accelerated structural deterioration and artefact loss through unsustainable mooring practices, looting, and unintentional diver impacts. The Thistlegorm Project—a collaboration between Alexandria University and the University of Edinburgh—conducted high-resolution underwater photogrammetric surveys in 2017 and 2022 to create the first comprehensive baseline for monitoring change. Comparative analysis revealed both subtle and significant alterations to the wreck and its debris field, including displacement of heavy structures, artefact removal, and expanded mapping of the debris field to 21.9 ha. The study demonstrates how repeat photogrammetry enables precise documentation of deterioration, informs conservation strategies, and supports heritage management in high-traffic dive sites. The Thistlegorm serves as a model for integrating digital recording, site monitoring, and collaborative stewardship of underwater cultural heritage. Full article

Background: Obesity confers substantial cardiometabolic risk. Tirzepatide, a once-weekly dual GIP/GLP-1 receptor agonist, produces dose-dependent weight loss in trials, but real-world patient-reported experiences are under-described. We evaluated real-world self-efficacy and experiences with tirzepatide in community settings. Methods: Explanatory sequential mixed-methods study of adults aged 18–59 years using tirzepatide for weight management. We collected a quantitative survey (demographics; medication use; 20-item Weight Efficacy Lifestyle Questionnaire [WEL]) followed by purposive semi-structured interviews. Associations between WEL and participant characteristics were tested a priori (two-tailed α = 0.05). Results: Among 120 participants (50.8% male; mean age 42 ± 13 years), 91.7% reported weight loss and 85.8% had <6 months’ exposure. WEL total was 91 ± 34. Higher WEL was observed in females, employed participants, those with insurance coverage versus self-pay, during early months of therapy, and among those with prior weight-loss attempts (all p < 0.05). Interviews (n = 15) indicated high satisfaction, improved sleep/energy, mood, and confidence; gastrointestinal effects were usually mild/transient. Interpretation: In routine care, tirzepatide use was associated with high eating self-efficacy and positive patient-reported outcomes. Variation by coverage and duration suggests value in pairing pharmacotherapy with behavioral support and addressing affordability to sustain benefits. Full article

Soymilk gel quality hinges on soybean protein composition and structure, yet direct comparisons linking protein traits to gel properties are limited. This study compared seven Northeast Chinese soybean varieties to identify which protein characteristics best predict tofu gel quality. Protein analysis included composition (11S/7S ratio), structure, and functional properties. Gel quality was measured through yield, water retention, texture, rheology, and microstructure imaging. Results showed substantial variation among varieties: 11S/7S ratios ranged from 1.14 to 4.10, solubility from 57.50% to 69.74%, gel yield from 193.25% to 236.12%, water-holding capacity from 42.09% to 60.23%, and gel firmness from 1520 to 1889 gf. The 11S/7S ratio emerged as the strongest quality predictor, correlating with gel firmness (R = 0.92) and elasticity (R = 0.98), while solubility correlated with yield (R = 0.79) and water retention (R = 0.83). Microscopy revealed that variety HD-1, with the highest 11S/7S ratio (4.10) and solubility (69.74%), formed dense networks with small pores (20–50 μm), whereas variety HK-60 (ratio 1.14) produced coarse structures with large pores (100–200 μm). HD-1 showed the best overall performance. Varieties with 11S/7S ratios above 3.5 and solubility above 68% consistently produced high-quality gels, while ratios below 2.5 indicated poor gel formation regardless of total protein content. These findings demonstrate that protein composition matters more than protein quantity for tofu quality. The approach enables rapid variety screening and provides practical guidelines for tofu manufacturers and soybean breeders. Full article

Failures are sometimes attributed to the deterioration of insulating oil, with contamination by cellulose particles. Such contamination lowers the dielectric strength of the oil. This study investigates the effect of cellulose contamination on the impulse breakdown voltage of transformer oil and evaluates the potential of nanofluids as a remediation strategy. A controlled amount of cellulose particles is added and dispersed into mineral oil at a concentration of 0.02 g/L to simulate a contaminated oil sample. Titanium dioxide (TiO₂) and aluminum oxide (Al₂O₃) nanoparticles are then dispersed into the contaminated oil at concentrations of 0.02 and 0.04 g/L. Impulse breakdown voltage is measured under both positive and negative polarities using electrode gaps of 1 mm and 2.5 mm, while dielectric permittivity is also measured to assess polarization effects. The influence of nanoparticle type and concentration is analyzed considering relaxation time and electron scavenging mechanisms. The results show that cellulose contamination markedly reduces dielectric strength, whereas the addition of nanoparticles effectively restores and, in several cases, enhances the insulating properties beyond those of uncontaminated oil. Full article

A manganese dioxide-modified carboxylated graphene oxide (MnO₂@CGO) nanocomposite was fabricated and utilized as a solid nanosorbent for extracting six organochlorine pesticides from environmental water samples. The target compounds, Hexachlorobenzene (HCB), β-Hexachlorocyclohexane (β-HCH), Heptachlor, Aldrin, Dieldrin, and o,p-Dichlorodiphenyltrichloroethane (o,p-DDT), were determined by micro-solid phase extraction (µ-SPE) coupled with gas chromatography–mass spectrometry (GC-MS) in selective ion monitoring mode. Key experimental factors influencing the extraction performance, such as sample pH, sorbent dosage, type and volume of eluting solvent, and time for desorption, were systematically optimized. Under the optimized conditions, the method showed good linearity (R² = 0.998–1.000) within the concentration range of 0.1–5 ng L⁻¹. The developed procedure was successfully applied to Nile River, agricultural wastewater, and groundwater samples, achieving recoveries between 87.1% and 101.2% with RSDs below 4.0%. The detection limits were 0.005–0.010 mg L⁻¹ at a signal-to-noise ratio of 3.0. Overall, the MnO₂@CGO-based µ-SPE method offers a sensitive, reliable, and straightforward approach for monitoring trace levels of organochlorine pesticides in environmental waters. Full article

This study investigates how the Egyptian stock market responded to the 2024 devaluation of the Egyptian Pound (EGP) and evaluates whether price adjustments reflect semi-strong form market efficiency. Using daily data for EGX30 firms, we estimate abnormal returns around the devaluation announcement and document largely insignificant market-wide reactions, indicating weak evidence of semi-strong efficiency. However, notable cross-firm heterogeneity emerges export-oriented and foreign-revenue-generating firms showed greater resilience, while companies dependent on imported inputs experienced sharper declines. These findings highlight how differences in currency exposure shape firms’ sensitivity to exchange rate shocks in emerging markets with recent dual-rate dynamics. From a practical perspective, the results emphasise the importance of transparent policy communication during major currency adjustments and underline the need for investors to account for firms’ FX risk profiles when constructing portfolios in devaluation-prone environments. The findings also offer insights for regulators seeking to strengthen disclosure practices and improve informational efficiency in the Egyptian capital market. Full article

In the development of quantum mechanics in the 1920s, both matrix mechanics (developed by Born, Heisenberg and Jordon) and wave mechanics (developed by Schrödinger) prevailed. These early attempts corresponded to the quantum mechanics of particles. Matrix mechanics was found to lead directly to the Schrödinger equation, and the Schrödinger equation could be used to derive the alternative problem for matrix mechanics. Later emphasis lay on the development of the dynamics of fields, where the classical field equations were quantized (see, for example, Weinberg). Today, quantum field theory is one of the most successful physical theories ever developed. The symmetry between particle and wave mechanics is exploited herein. One of the important properties of quantum mechanics is that it is linear, leading to some confusion about how to treat the problem of nonlinear classical field equations. In the present paper we address the case of classical nonlinear soliton equations which are exactly integrable in terms of the periodic/quasiperiodic inverse scattering transform. This means that all physical spectral solutions of the soliton equations can be computed exactly for these specific boundary conditions. Unfortunately, such solutions are highly nonlinear, leading to difficulties in solving the associated quantum mechanical problems. Here we find a strategy for developing the quantum mechanical solutions for soliton dynamics. To address this difficulty, we apply a recently derived result for soliton equations, i.e., that all solutions can be written as quasiperiodic Fourier series. This means that soliton equations, in spite of their nonlinear solutions, are perfectly linearizable with quasiperiodic boundary conditions, the topic of finite gap theory, i.e., the inverse scattering transform with periodic/quasiperiodic boundary conditions. We then invoke the result that soliton equations are Hamiltonian, and we are able to show that the generalized coordinates and momenta also have quasiperiodic Fourier series, a generalized linear superposition law, which is valid in the case of nonlinear, integrable classical dynamics and is here extended to quantum mechanics. Hamiltonian dynamics with the quasiperiodicity of inverse scattering theory thus leads to matrix mechanics. This completes the main theme of our paper, i.e., that classical, nonlinear soliton field equations, linearizable with quasiperiodic Fourier series, can always be quantized in terms of matrix mechanics. Thus, the solitons and their nonlinear interactions are given an explicit description in quantum mechanics. Future work will be formulated in terms of the associated Schrödinger equation. Full article

Limb amputation is a growing health concern worldwide, driven largely by the rising incidence of vascular and metabolic diseases and military conflicts. In the past two decades, remarkable advancements in surgical techniques, prosthetic technologies, and rehabilitation strategies have made a profound impact on outcomes for individuals with limb loss. In this article, we explore the evolving landscape of limb care in the United States, highlighting innovations in prosthetic technology and amputation surgery including osseointegration, neuromuscular surgeries and interfaces, artificial intelligence, sensory feedback, and the importance of prosthetic embodiment. We discuss limb care systems and the continuum of limb loss rehabilitation, focusing on the need for coordinated models of patient-centered care. We present the demographic biases and healthcare disparities related to insurance coverage and reimbursement in the United States and the explore ethics and equitability considerations pertaining to prosthetic standard of care and advanced treatments for limb loss. Finally, we lay out the systemic reform, policy advocacy, and future research needed to ensure that everyone with limb loss has equitable access to the benefits of modern amputee care. Full article

This study presents an integrated techno-economic and environmental assessment of shaft generator (SG) integration in marine propulsion systems using alternative fuels. A comprehensive numerical model is developed to simulate the operation of a bulk carrier equipped with a low-speed two-stroke main engine, comparing conventional diesel generator (DG) configurations with SG-powered alternatives under varying ship speeds and auxiliary electrical loads. Three fuel types, heavy fuel oil (HFO), fatty acid methyl esters (FAMEs), and methanol–diesel dual fuel, are analyzed to evaluate fuel consumption, exhaust emissions, and economic feasibility. The results show that SG integration consistently reduces total fuel consumption by 0.1–0.5 t/day, depending on load and fuel type, yielding annual savings of up to 150 tonnes per vessel. Carbon dioxide (CO₂), Nitrogen oxide (NO_x), and sulphur oxide (SO_x) emissions decrease proportionally with increased SG load, with annual reductions exceeding 450 tonnes of CO₂ and up to 15 tonnes of NO_x for HFO systems. Methanol–diesel operation achieves the highest relative improvement, with up to 50% lower CO₂ and near-zero SO_x emissions, despite a moderate increase in total fuel mass due to methanol’s lower calorific value. Economically, SG utilization provides daily fuel cost savings ranging from $200 to $1050, depending on the fuel and load, leading to annual reductions of up to $320,000 for high-load operations. The investment analysis confirms the financial viability of SG installations, with net present values (NPVs) up to $1.4 million, internal rates of return (IRRs) exceeding 100%, and payback periods below one year at 600 kW load. The results highlight the dual benefit of SG technology, enhancing energy efficiency and supporting IMO decarbonization goals, particularly when coupled with low-carbon fuels such as methanol. The developed computational framework provides a practical decision-support tool for ship designers and operators to quantify SG performance, optimize energy management, and evaluate the long-term economic and environmental trade-offs of fuel transition pathways. Full article

Background: Cone-beam computed tomography (CBCT) was used for a 1-year follow-up of a randomized clinical trial to compare a stainless-steel Tornado file system with OneShape and WaveOne rotary systems for biomechanical canal preparation, as indicated by radiolucency sizes of periapical lesions. Methods: Lower molars with necrotic pulps and periapical lesions were randomly divided into three groups (n = 20) according to three rotary file systems. After root canal treatment, clinical and assessment of the CBCT periapical index scores were blindly evaluated at one year using pre- and post-instrumentation CBCT images. Statistical analysis was performed to compare the three systems at a p-value of 0.05. Results: The results revealed a significant decrease in the size of apical radiolucency in each group after one-year follow-up, with no statistically significant difference among the three systems (p > 0.05). Conclusions: CBCT is a valuable biomedical imaging modality for assessing periapical lesion healing. Tornado, WaveOne, and OneShape systems can be used with similar efficacy for root canal preparation in teeth with periapical lesions. Clinical Trial Registration: The study was retrospectively registered with ClinicalTrials.gov (NCT06752837). Date of Registration: 30 December 2024. The CONSORT group has identified it as essential. Full article

Accurate, non-invasive glucose monitoring remains a major challenge in biomedical sensing. We present a high-sensitivity planar microwave biosensor that progresses from a 2-cell hexagonal array to an 8-cell hexagonal array, and finally to a 16-cell double-honeycomb (DHC-CSRR) architecture to enhance field confinement and resonance strength. Full-wave simulations using Debye-modeled glucose phantoms demonstrate that the optimized 16-cell array on a Rogers RO3210 substrate substantially increases the electric field intensity and transmission response |S₂₁| sensitivity compared with FR-4 and previous multi-CSRR designs. In vitro measurements using pharmacy-grade glucose solutions (5–25%) and saline mixtures with added glucose, delivered through an acrylic channel aligned to the sensing region, confirm the simulated trends. In vivo, vector network analyzer (VNA) tests were conducted on four human subjects (60–150 mg/dL), comparing single- and dual-finger placements. The FR-4 substrate (${\mathsf{\epsilon }}_{\mathrm{r}}$ = 4.4) provided higher frequency sensitivity (2.005 MHz/(mg/dL)), whereas the Rogers RO3210 substrate (${\mathsf{\epsilon }}_{\mathrm{r}}$ = 10.2) achieved greater amplitude sensitivity (9.35 × 10⁻² dB/(mg/dL)); dual-finger contact outperformed single-finger placement for both substrates. Repeated intra-day VNA measurements yielded narrow 95% confidence intervals on |S₂₁|, with an overall uncertainty of approximately ±0.5 dB across the tested glucose levels. Motivated by the larger |S₂₁| response on Rogers, we adopted amplitude resolution as the primary metric and built a compact prototype using the AD8302-EVALZ with a custom 3D-printed enclosure to enhance measurement precision. In a cohort of 31 participants, capillary blood glucose was obtained using a commercial glucometer, after which two fingers were placed on the sensing region; quadratic voltage-to-glucose calibration yielded R² = 0.980, root–mean–square error (RMSE) = 2.316 mg/dL, overall accuracy = 97.833%, and local sensitivity = 1.099 mg/dL per mV, with anthropometric variables (weight, height, age) showing no meaningful correlation. Clarke Error Grid Analysis placed 100% of paired measurements in Zone A, indicating clinically acceptable agreement with the reference meter. Benchmarking against commercial continuous glucose monitoring systems highlights substrate selection as a dominant lever for amplitude sensitivity and positions the proposed fully non-invasive, consumable-free architecture as a promising route toward portable RF-based glucose monitors, while underscoring the need for larger cohorts, implementation on flexible biocompatible substrates, and future regulatory pathways. Full article

Bridges are vital components of global infrastructure, with millions constructed over the years. Many of them face aging and are vulnerable to risks. Traditional bridge inspection methods are costly and time-consuming. They often rely on many manual laborers without providing system-level insights. Moreover, these outdated approaches make it difficult to obtain a clear representation of the current bridge health. This paper introduces a novel framework based on deep learning (DL) for identifying local bridge damage using acceleration data collected by Unmanned Aerial Vehicle (UAV)-mounted sensors. The framework employs WaveNet, which was designed as a generative audio DL model. Its causal dilated convolution deals with long-range temporal correlations without recurrence. Two WaveNet regressors are used to predict the damage location and its severity. The methodology is integrated with an optimized sensor spacing strategy for UAV deployments. The results demonstrate that the severity model achieved an average R² = 0.98, while the location model reached R² = 0.85. Optimal sensor spacing “S” was found at S = 1.0 m for localization and S = 0.5 m for severity. A field-simulated case was accurately identified by the two models, representing the potential of the proposed framework for more reliable bridge health monitoring. Full article