Search Results (6,131)

Background: Drug shortages represent a growing challenge to healthcare systems worldwide, affecting treatment continuity and patient outcomes. This study assessed the burden and perceived impact of drug shortages from both healthcare professionals’ and patients’ perspectives in a Saudi tertiary hospital. Methods: A cross-sectional survey was conducted in April 2025 at King Abdulaziz Medical City, Riyadh, Saudi Arabia. Convenience sampling was used to recruit healthcare professionals with at least two years of experience and adult outpatients. Structured questionnaires assessed shortage frequency, affected drug classes, perceived impacts, and management practices. The findings were descriptively analyzed and compared with the Saudi Food and Drug Authority (SFDA) national shortage data for the corresponding 12-month period. Results: A total of 230 healthcare professionals and 243 patients participated. Among healthcare professionals, 89.1% reported experiencing at least one drug shortage, with 38.3% encountering shortages more than ten times annually. Anti-infectives (36.5%) and analgesics (35.7%) were the most frequently reported classes. The most common response was prescribing alternative medications (77.4%), with 55.3% perceived as adequately effective and 30.8% as less effective. Delayed care was the most frequently reported consequence (44.0%). Among patients, 30.9% reported experiencing shortages, 46.7% reported some degree of health impact, and 28.1% incurred additional costs. Awareness and utilization of the SFDA reporting system were low in both groups. Comparison with SFDA data revealed discrepancies between hospital-reported and nationally reported shortages. Conclusions: Drug shortages were frequently reported and associated with perceived clinical and economic consequences. Gaps between hospital experiences and national reporting highlight limitations in current surveillance systems. Strengthening reporting mechanisms, communication, and supply chain coordination may improve the management of drug shortages. Full article

The study of genetic effects induced by low-dose alpha radiation associated with radon and its decay progeny is critically important for assessing radiation risks in regions with elevated natural background levels. The aim of this study was to evaluate the mutagenic effects (in germline cells) and teratogenic effects (in somatic tissues) of alpha radiation using the D. melanogaster model. To differentiate between these effects, teratogenic outcomes were analyzed in directly exposed individuals (phenotypic analysis of adults that developed from irradiated larvae), whereas mutagenic effects were assessed in the progeny of irradiated flies. Larvae and adult flies were exposed to calibrated alpha-particle sources with energies ranging from 4.8 to 7.7 MeV and absorbed doses of 1.90–44.96 mGy. The results demonstrated a statistically significant increase in the frequency of morphological abnormalities in the exposed groups, including melanotic masses and deformities of the wings, thorax, and tergites. Under 72 h exposure, a strong correlation between absorbed dose and abnormality frequency was observed (r = 0.98). In the reporter system, induction of GFP expression was detected in imaginal discs at doses above 10 mGy, indicating threshold activation of the cellular stress response. The obtained data demonstrate that chronic low-dose α-irradiation leads to an increased frequency of morphological abnormalities (indirect phenotypic manifestations of compromised genetic stability) in D. melanogaster, with the most pronounced effects observed at the level of morphogenesis. The high sensitivity of the applied test systems was confirmed, supporting the use of D. melanogaster as a bioindicator for ecogenetic monitoring of radon-prone areas, including regions of Kazakhstan. Full article

Sweeping jet (SWJ) actuators are widely used in active flow control, but explicitly resolving actuator-scale unsteadiness in full-configuration computational fluid dynamics (CFD) remains prohibitively expensive because of the small geometric scales and high-frequency oscillations involved. Existing reduced-order boundary-condition models constructed from exit-plane data alone can reproduce the observed switching waveform, but they treat the actuator as an input–output black box and provide limited insight into the internal dynamics that generate the response. This work develops a causal state-space reduced-order modeling framework that links internal mixing-chamber dynamics to time-resolved exit-plane boundary conditions. Proper orthogonal decomposition (POD) is used to obtain a low-dimensional representation of the internal flow, and a data-driven linear evolution operator is identified in the reduced space by least-squares regression of successive snapshot pairs. A POD truncation rank of $r=60$ is selected from cumulative-energy and validation-error sensitivity analyses, capturing well above 99% of the fluctuation energy while lying within the converged performance regime. A corresponding reduced operator is identified for the exit plane, and spectral comparison reveals near-neutrally stable oscillatory modes in both regions. Using a $\pm 1\%$ relative frequency-matching tolerance, the dominant reduced-operator modes exhibit a 28.3% frequency overlap, providing operator-level evidence that exit-plane oscillations are dynamically linked to internal coherent structures. This correspondence is further supported by cross-spectral coherence analysis between representative internal and exit-plane probe signals, which shows strong coherence at dynamically relevant frequencies. A delayed causal output mapping is then formulated in which the internal reduced state drives the exit-plane response after an identified lag of 149 time steps, corresponding to $2.98\times {10}^{-3}$ s. This delay provides a physically interpretable convective transport timescale from the mixing chamber to the actuator exit. Over the validation interval, the model maintains a mean relative $L_2$ error below 0.02, with maximum normalized errors below 0.04 for most of the prediction horizon, and localized increases are confined to rapid jet-switching events. Field-level reconstructions of streamwise velocity and total pressure show that the model captures both phases of the jet-switching cycle, with errors concentrated primarily in high-gradient shear-layer regions. Compared with exit-only reduced-order models, the proposed internal-driven formulation improves amplitude and phase fidelity over extended prediction horizons. The resulting framework provides a compact, interpretable, operator-based representation of SWJ actuator dynamics suitable for use as a CFD-embeddable dynamic boundary condition. Full article

Styrene, a constituent of polystyrene food-contact materials, can migrate into hot beverages, but data on short-term consumer exposure and associated biological responses remain limited. In this single-arm longitudinal human biomonitoring pilot study, 40 healthy adults consumed tea or coffee daily in Styrofoam cups for approximately two weeks. Biomarkers were measured at baseline, day 6, and day 11, including urinary mandelic acid (MA) and phenylglyoxylic acid (PGA), salivary malondialdehyde (MDA), comet assay parameters in peripheral blood lymphocytes, and micronucleus (MN) frequency in buccal cells. Measured styrene migration into beverages ranged from 3.3 to 7.1 μg/L, below the World Health Organization guideline value. Urinary metabolites and salivary MDA showed substantial interindividual variability and no consistent temporal pattern. In contrast, generalized estimating equation models showed progressive increases in comet assay indicators over the exposure period. Tail intensity and tail moment increased over time, with stronger changes among participants consuming two cups daily. MN frequency did not change significantly. These findings suggest that repeated short-term consumption of hot beverages in polystyrene cups was associated with modest changes in selected early biomarkers of biological effect under consumer-use conditions. The results should be interpreted cautiously in light of the modest sample size, short follow-up, and absence of more specific mechanistic endpoints, but they support further study of repeated low-level exposure to food-contact materials. Full article

With the continuous development of complex marine hydrocarbon reservoirs, broadband seismic data have shown growing advantages in revealing abundant stratigraphic information. Affected by acquisition conditions and stratigraphic attenuation, the acquired seismic data commonly suffer from narrow bandwidth, and conventional broadband processing techniques are incapable of optimizing the overall frequency band. This study proposes a coordinated high- and low-frequency broadband compensation method based on adaptive weight fusion to effectively extend the frequency bandwidth of seismic data. Firstly, wavefield separation is used to suppress ghost reflections, compensate low-frequency effective signals, and restore the continuity of the low-frequency spectrum. Then, based on the spectrum extrapolation method of maximum entropy spectrum estimation, a spectrum prediction model is established to achieve the continuation of high-frequency effective signals. Finally, in combination with the signal-to-noise ratio of each frequency band, the adaptive weight fusion algorithm is applied for weighted summation. The acquired broadband seismic data feature a continuous spectrum and balanced energy, greatly improving seismic imaging quality. Comparative results obtained using conventional processing methods verify that the proposed method can significantly improve stratigraphic continuity and wave group characteristics. Full article

In recent decades, intensified temperature variability has increased the likelihood of abrupt transitions between anomalously cold and warm conditions, exerting substantial ecological and societal impacts. This study identifies rapid temperature flip events (RTFEs), including cold-to-warm transition events (C2Ws) and warm-to-cold transition events (W2Cs), across China using the CN05.1 gridded daily mean temperature data for 1961–2022, and further reveals their regional heterogeneity and long-term changes. Eastern China represents a hotspot of RTFEs, exhibiting higher frequencies and stronger intensities compared with western China. RTFEs are most frequent in spring, followed by summer. Over the period 1961–2022, both C2W and W2C became more frequent and more intense, with W2C showing a larger increase in frequency of 0.54 events century⁻¹ and a larger increase in intensity of 0.29 s.d. century⁻¹, compared with increases of 0.01 events century⁻¹ and 0.11 s.d. century⁻¹, respectively, for C2W. In addition, significant decadal changes in both types of events were observed across large areas of China during the 1990s–2000s and 2010s, following a high–low–high pattern. Analysis across the seven natural sub-regions reveals distinct high-hazard areas where RTFE hotspots coincide with increasing frequency and intensity: the eastern monsoonal regions of China for W2Cs and Inner Mongolia for both event types. These findings contribute to addressing climate change and mitigating the risk of RTFEs. Full article

Magnetic resonance techniques have evolved beyond conventional proton-based imaging, enabling access to a broader range of nuclei that provide complementary structural, functional, and molecular information. This review presents a comprehensive overview of multinuclear NMR and MRI in solid and soft materials as well as in biomedical applications, with particular emphasis on ¹H, ¹³C, ³¹P, ²³Na, and ¹⁹F nuclei. Proton-based methods remain the foundation of magnetic resonance due to their high sensitivity and widespread applicability, offering insights into molecular mobility, hydration, and microstructural heterogeneity. In contrast, heteronuclear approaches enable more specific characterization of chemical structure (¹³C), phosphorus-containing functional groups and membranes (³¹P), ionic homeostasis and transport (²³Na), and exogenous tracers with negligible biological background (¹⁹F). Together, these techniques extend magnetic resonance from primarily anatomical imaging toward functional, metabolic, and molecular-level analysis. The review further discusses key hardware aspects, including magnetic field strength and radiofrequency coil design, highlighting the trade-offs between low- and high-field systems and the growing importance of multinuclear coil architectures. For example, because ¹H, ²³Na, ³¹P, and ¹⁹F resonate at different Larmor frequencies, multinuclear experiments require dedicated or multi-tuned RF coils that balance sensitivity, field homogeneity, and decoupling between channels. Mechanisms of contrast generation are examined in detail, distinguishing between endogenous sources—such as water, ions, and metabolites—and exogenous contrast agents, including gadolinium-, manganese-, and fluorine-based compounds, as well as targeted and theranostic platforms. A comparative framework of endogenous and exogenous signals is presented, emphasizing their complementary roles in balancing safety, specificity, and sensitivity. Finally, the opportunities and challenges of multinuclear magnetic resonance are critically evaluated, including limitations in sensitivity, signal-to-noise ratio, data interpretation in heterogeneous systems, and technical complexity. Emerging directions such as ultrahigh-field imaging, advanced RF technologies, hyperpolarization, and artificial intelligence-assisted reconstruction are discussed as key drivers for future development. Overall, multinuclear NMR and MRI represent a powerful and expanding toolbox for probing complex material and biological systems, with the potential to significantly enhance diagnostic capabilities and deepen our understanding of structure–function relationships across multiple scales. Full article

Drought–flood abrupt alternation (DFAA) is a typical compound hydroclimatic extreme process and has important implications for regional water resources regulation, agricultural production, and ecological stability. However, existing studies have mainly focused on event identification and frequency variation, while lacking a systematic investigation of the directional differences between drought-to-flood (DF) and flood-to-drought (FD) events in terms of process structure, cumulative effects, and spatial hazard patterns. Based on daily precipitation data from 1960 to 2024, this study identified DFAA events in the Yellow River Basin by combining the standardized weighted average precipitation (SWAP) index with run theory, and analyzed the asymmetric characteristics of DF and FD events from the perspectives of event frequency, phase duration, abrupt-transition characteristics, cumulative severity, and integrated hazard. The results show that: (1) the frequency of DFAA events in the Yellow River Basin exhibited pronounced spatial heterogeneity, with an overall pattern of being higher in the middle reaches and lower in the upper and lower reaches. The frequency of DF events was generally higher than that of FD events, and their spatial distribution was also more continuous. No significant long-term trend was detected in the annual frequency, although clear interdecadal variability was observed, characterized by a transition from relatively low-frequency periods to medium- and high-frequency periods. (2) DF and FD events exhibited stable asymmetry in process structure. The abrupt-transition duration of DF events was mainly concentrated within 1–2 days, whereas that of FD events was mainly concentrated within 3–5 days. The two event types had comparable pre-transition durations, but DF events tended to shift more rapidly and were followed by a longer-lasting flood phase. (3) The differences between the two event types in terms of instantaneous intensity were relatively limited, whereas clearer divergence was observed in cumulative severity, with DF events showing greater overall severity than FD events. This indicates that the directional difference is manifested primarily in cumulative process effects rather than in the magnitude at a single moment. (4) The comprehensive hazard index (CHI) revealed that the northern and central-eastern parts of the middle reaches of the Yellow River Basin were the main hotspots of DFAA hazard. Among them, high-hazard areas of DF events were more extensive, whereas FD hazards were characterized more by localized intensification. These findings indicate that within the identification framework adopted here, DFAA in the Yellow River Basin is characterized not only by rapid dry–wet transitions, but also by clear directional differences between DF and FD in process structure and hazard pattern. This study can provide a scientific reference for the monitoring, early warning, and zonal hazard prevention of DFAA in the basin. Full article

Synthetic Aperture Radar (SAR) is one of mainstream remote sensing techniques, offering all-weather, day-and-night operational capabilities. However, throughout the processes of signal transmission, propagation, and reception, it is difficult to ensure that the amplitude and phase of the SAR signal strictly follow a linear frequency modulation (LFM) characteristic. The resulting signal distortion often leads to main lobe broadening and sidelobe elevation, degrading the focusing performance of SAR images. Traditionally, this issue has been addressed primarily through SAR system internal calibration and pre-distortion compensation, which makes it challenging to maintain the signal in an ideal state over the long term. At the same time, many simplified SAR systems also lack an internal calibration design, such as low-cost UAV-borne SAR payloads. In this paper, we propose a novel signal distortion compensation method based on SAR image data. Without relying on SAR system calibration signals, this method estimates and compensates for signal distortion directly using SAR image data, thereby improving SAR image focusing performance, achieving a resolution closer to the theoretical bandwidth and lower sidelobe. The processing and analysis of both manned and unmanned airborne SAR image data and calibration signals demonstrate that the proposed method effectively compensates for signal distortion phases, achieving performance comparable to that of real-time calibration-signal-based methods. Full article

This work presents a noninvasive imaging method to locate veins using a tuned microwave loop resonator. It offers a low-cost, fast, and effective solution to the challenges in venipuncture. The sensor features a loop resonator with a 5.2 mm radius, incorporating a self-tuning mechanism, and operates at 2.408 GHz with a reflection coefficient of −48.77 dB. It generates localized high-intensity electric fields that penetrate tissues to sufficient depths, enabling the detection of veins based on shifts in resonant frequencies that are induced by the varied dielectric properties of blood vessels. Two-dimensional raster scan simulations of the cephalic and median cubital veins yielded a ∼25 MHz downward resonant-frequency shift between vein and non-vein positions, with the median cubital vein still detectable at depths up to 6 mm. To quantify generalization to real tissues, a decision tree classifier trained on 63 simulation samples and evaluated on 335 in vivo measurements achieved 82.09% classification accuracy (sensitivity 81.25%, specificity 83.02%), demonstrating that the simulation-derived frequency contrast transfers reliably to experimental data despite inter-subject tissue variability. Extensive tests conducted demonstrate the sensor’s effectiveness, producing consistent and distinguishable frequency shifts when the sensor moves on the skin across veins. This technology holds significant promise for improving venipuncture accuracy, minimizing complications, and enhancing patient comfort. Full article

Continuous monitoring and nowcasting of tornadic near-storm environments remain challenging, particularly in regions with limited ground-based weather radar coverage. High-spatiotemporal-resolution geostationary satellite remote sensing offers a valuable approach to track the evolution of severe convective storms. Combining 10 min cloud-top brightness temperature (TBB) data from the Himawari-8 satellite and ERA5 reanalysis, this study investigates the atmospheric environments of 177 documented tornadoes in China from 2016 to 2023. Tracking storm convective centers using TBB minima reveals clear regional differences in tornadogenesis paradigms. Southern China tornadoes exhibit a “dynamically driven” pattern within quasi-steady, warm, and moist environments. These environments feature low Lifted Condensation Levels (LCL; ~790 m) and weak Convective Inhibition (CIN). Intense low-level wind shear and storm-relative helicity (SRH) dominate the convective triggering. Northern China tornadoes follow a “coupled thermodynamic-kinematic” paradigm under relatively drier and cooler backgrounds. Their initiation relies on the rapid, synchronized accumulation of Mixed-Layer convective available potential energy (MLCAPE) and deep-layer SRH. Furthermore, intensity-based comparative analysis indicates that significant tornadoes (Enhanced Fujita [EF] scale, EF ≥ 2) are favored by higher MLCAPE, deep-layer shear, and lower LCLs compared to weak ones (EF ≤ 1). Himawari-8 TBB data capture a more rapid pre-storm convective cloud-top cooling for strong tornadoes, with medians reaching −73 °C. This study demonstrates that combining high-frequency satellite observations with reanalysis data provides quantitative precursor signals for regional severe tornado nowcasting. Full article

Background/Objectives: The use of nonsteroidal anti-inflammatory drugs (NSAIDs) is common in dentistry, mainly for pain and inflammation. However, their coadministration with warfarin may lead to serious potential drug-drug interactions (PDDIs), increasing the risk of bleeding. This study aimed to identify and describe the frequency of PDDIs between warfarin and NSAIDs prescribed by dentists and dispensed by the Unified Health System (SUS) in Minas Gerais, Brazil, from January 2011 to December 2021. Methods: A descriptive analysis was conducted using data from Integrated Pharmaceutical Services Management System (Sigaf), considering prescriptions of warfarin and NSAIDs issued during the same period. Results: The prescribed NSAIDs were diclofenac sodium 50 mg, diclofenac potassium 50 mg, ibuprofen 600 mg, nimesulide 100 mg, and nimesulide 50 mg/mL oral suspension. Warfarin sodium 5 mg is the prescribed oral anticoagulants. The results showed a marked increase in both warfarin (from 6017 to 59,945 prescriptions; +896%) and NSAID use (from 2644 to 84,408 prescriptions; +3093%), paralleling the rise in PDDIs, which grew from 2 in 2011 to 62 in 2021. Despite this 3000% relative increase, the absolute frequency of PDDIs remained low, corresponding to approximately 0.7 interactions per 1000 NSAID prescriptions in 2021. Conclusions: Although these PDDIs are low, they are clinically significant and may have important implications for patients and the healthcare system. In conclusion, PDDIs between NSAIDs and warfarin, though low in absolute numbers, have increased over the years, reinforcing the need for greater awareness among dental professionals and for the implementation of clinical decision support strategies to promote safe care. Full article

This paper presents a comprehensive investigation of the impact of I/Q (In-phase/Quadrature) imbalance on the performance of a six-port receiver operating in the millimeter-wave band, specifically in the 60–65 GHz frequency range. Unlike traditional heterodyne architectures, the six-port junction offers a low-cost and low-power alternative for direct conversion; however, it is highly sensitive to hardware imperfections. This study demonstrates that manufacturing tolerances in passive components, such as 90° hybrid couplers and power dividers, introduce significant amplitude and phase disparities. These imbalances geometrically distort the ideal QPSK constellation, transforming the circular decision boundaries into an elliptical profile. The research methodology employs a robust co-simulation approach in Advanced Design System (ADS), integrating measured S-parameters with mathematical analysis to quantify signal degradation. Performance is evaluated using the Error Vector Magnitude (EVM) metric. The experimental findings reveal that even at the higher end of the spectrum (65 GHz), where the amplitude imbalance reaches 0.7 dB and the phase error is approximately 5°, the six-port QPSK receiver maintains an EVM of 8.7%. This result is comfortably below the 17.5% limit mandated by modern wireless communication standards, such as LTE and 5G. These results confirm the architectural resilience of the six-port receiver, validating its effectiveness as a reliable solution for high-speed, short-range data transmission in future ultra-wideband telecommunication infrastructures. Full article

To tackle issues such as high data volatility, temporal dependencies, complex feature extraction, and low parameter tuning efficiency in wind power forecasting, this paper proposes a dual-optimization model for short-term wind power forecasting based on RIME-VMD and MSSA-CNN-BiLSTM. First, the Rime Optimization Algorithm (RIME) is employed to adaptively refine the key parameters of Variational Mode Decomposition (VMD), decomposing wind power into intrinsic modal functions (IMFs) of different frequencies to reduce signal complexity. Second, by integrating the local feature extraction capabilities of Convolutional Neural Network (CNN) with the bidirectional temporal dependency capture capabilities of Bidirectional Long Short-Term Memory Network (BiLSTM), a hybrid deep learning architecture is constructed. Additionally, the Multi-strategy Sparrow Search Algorithm (MSSA) is introduced to perform global hyperparameter optimization, thereby addressing the shortcomings of manual parameter tuning. The final power forecast is obtained through the prediction of each IMF component and the reconstruction of the results. Experiments demonstrate that the presented prediction model attains a root mean square error (RMSE) of 0.0333, a mean absolute error (MAE) of 0.0265, and a coefficient of determination (R²) of 0.9901. Seasonal validation shows that the model’s R² exceeds 0.983 in all four seasons—spring, summer, autumn, and winter—demonstrating good generalization capability. Relative to the BiLSTM model, its RMSE and MAE are reduced by 50.52% and 46.57%, respectively, while R² increases by 3.36%, effectively addressing the issue of insufficient accuracy in short-term wind power forecasting. Full article

Introduction: Syphilis is a preventable sexually transmitted infection (STI) with severe health outcomes, yet it is not included in Saudi Arabia’s national premarital and antenatal STI screening programs. This study assessed knowledge, attitudes, and practices (KAP) toward syphilis in Saudi Arabia and identified predictors of acceptance for including syphilis testing in such programs. Methods: A cross-sectional online survey was conducted among 935 participants aged ≥20 years. Data included sociodemographic characteristics and measures of KAP and screening acceptance. Continuous variables were summarized as medians (IQR) and categorical variables as frequencies and percentages, with bivariate and multivariate logistic regression used to identify predictors of screening acceptance. Results: Knowledge and preventive practices were low, while attitudes were predominantly neutral (median attitude score: 34 IQR 32–38). Although intentions for personal testing were low (17%), support for syphilis testing in premarital (60.8%) and antenatal (48.9%) programs was considerable. Employment in the health sector, older age, and positive attitudes predicted acceptance of screening policies. Knowledge and practice showed a weak correlation (r = 0.14), whereas knowledge and attitude were moderately correlated (r = 0.55). Conclusion: KAP toward syphilis is influenced by specific sociodemographic factors. Although acceptance of screening is high at the policy level, individual-level preventive behaviors remain low. Full article