Search Results (351)

Very-high-energy electrons, coupled with ultra-high dose rates, are being explored for their potential use in radiotherapy to treat deep-seated tumours. The dose per pulse needed to achieve ultra-high dose rates far exceeds the limit of current medical linear accelerator capabilities. A high dose per pulse has been observed as the limiting factor for many existing dosimeters, resulting in saturation at doses far below what is required. The MOSkin, an existing clinical quality assurance dosimeter, has previously been demonstrated as dose rate independent but has not been subjected to a high dose per pulse. Within this study, the MOSkins dose-per-pulse response was tested for linearity, with a dose per pulse as high as 23 Gy within 200 ns at the ANSTO Australian Synchrotron’s Pulsed Energetic Electrons for Research facility. While using EBT-XD film as a reference dosimeter, a dose rate dependence of the EBT-XD was discovered. Once confirmed and a correction factor established, EBT-XD was used as an independent reference measurement. This work presents confirmation of the MOSkin suitability for ultra-high dose-rate environments with an electron energy of 100 MeV, and a theoretical discussion of its dose-rate and dose-per-pulse independence; the MOSkin is the only detector suitable for both clinical quality assurance, and ultra-high dose-rate measurements in its standard, unmodified form. Full article

Although the lattice Boltzmann method (LBM) is relatively straightforward, it demands a well-crafted framework to handle the complex partial differential equations involved in multiphase flow simulations. For the first time to our knowledge, this work proposes a novel LBM framework to solve Eulerian–Eulerian multiphase flow equations without any finite difference correction, including very-large-density ratios and also a realistic relation for the drag coefficient. The proposed methodology and all reported LBM formulas can be applied to any dimension. This opens a promising venue for simulating multiphase flows in large High Performance Computing (HPC) facilities and on novel parallel hardware. This LBM framework consists of six coupled LBM schemes—running on the same lattice—ensuring an efficient implementation in large codes with minimum effort. The preliminary numeral results agree in an excellent way with the reference numerical solution obtained by a traditional finite difference solver. Full article

Rapid urbanization and climate change pose significant challenges to air quality in arid metropolitan areas, with critical implications for public health and sustainable development. This study projects the evolution of air pollution in Riyadh, Saudi Arabia, through 2070 using an integrated modeling approach that combines CMIP6 climate projections with localized air quality data. We analyzed daily concentrations of major pollutants (SO₂, NO₂) across 15 strategically selected monitoring stations representing diverse urban environments, including traffic corridors, residential areas, healthcare facilities, and semi-natural zones. Climate data from two Earth System Models (CNRM-ESM2-1 and MPI-ESM1.2) were bias-corrected and integrated with historical pollution measurements (2000–2015) using hierarchical Bayesian statistical modeling under SSP2-4.5 and SSP5-8.5 emission scenarios. Our results revealed substantial deterioration in air quality, with projected increases of 80–130% for SO₂ and 45–55% for NO₂ concentrations by 2070 under high-emission scenarios. Spatial analysis demonstrated pronounced pollution gradients, with traffic corridors (Eastern Ring Road, Northern Ring Road, Southern Ring Road) and densely urbanized areas (King Fahad Road, Makkah Road) experiencing the most severe increases, exceeding WHO guidelines by factors of 2–3. Even semi-natural areas showed significant increases in pollution due to regional transport effects. The hierarchical Bayesian framework effectively quantified uncertainties while revealing consistent degradation trends across both climate models, with the MPI-ESM1.2 model showing a greater sensitivity to anthropogenic forcing. Future concentrations are projected to reach up to 70 μg m⁻³ for SO₂ and exceed 100 μg m⁻³ for NO₂ in heavily trafficked areas by 2070, representing 2–3 times the Traffic corridors showed concentration increases of 21–24% compared to historical baselines, with some stations (R5, R13, and R14) recording projected levels above 4.0 ppb for SO₂ under the SSP5-8.5 scenario. These findings highlight the urgent need for comprehensive emission reduction strategies, accelerated renewable energy transition, and reformed urban planning approaches in rapidly developing arid cities. Full article

Citizen science data are easily accessible, which has led to their wide use for scientific data collection such as mapping invasive plant species. However, the crowd-sourced nature of citizen science data has led to criticism over the quality of the data owing to the fragmented spatial distribution of the data collection points. Despite inherent limitations, an increasing collection of research indicates that, when appropriately corrected for data quality issues, the data collected by volunteers can serve as a reliable source for identifying and analysing biodiversity patterns. Prior to utilising citizen science data, it is essential to identify its inherent flaws and limitations to develop appropriate strategies for its effective application. One viable approach to validating such data is to compare it with datasets collected by experts, particularly in urban areas where volunteer participation is high. In our comparative analyses, we evaluated the usability of citizen science data (Global Biodiversity Information Facility (GBIF)) for mapping the occurrence density of five invasive plant species (Ailanthus altissima, Asclepias syriaca, Elaeagnus angustifolia, Robinia pseudoacacia, and Solidago spp.) in urban cores and fringes in Hungary by comparison to maps obtained from spatially homogeneous data (EUROSTAT Land Use and Coverage Area Frame Survey (LUCAS)) collected by experts. The results showed that the volunteers collected valuable data on Ailanthus altissima, which is specific to urban areas, but they underestimated Robinia pseudoacacia, which is often planted for economic benefits. In addition, the volunteers collected much more data closer to urban cores. These results suggest that citizen science data may be suitable for mapping urbanophilic species in urban environments. Our research contributes to the assessment and scientific applicability of volunteer-collected data for mapping the distribution of invasive plant species. Full article

The implementation of low-cost sensitive and selective gas sensors for monitoring fruit ripening and quality strongly depends on their long-term stability. Gas sensor drift undermines the long-term reliability of low-cost sensing platforms, particularly in precision agriculture. We present a real-time drift compensation framework based on a lightweight Temporal Convolutional Neural Network (TCNN) combined with a Hadamard spectral transform. The model operates causally on incoming sensor data, achieving a mean absolute error below 1 mV on long-term recordings (equivalent to <1 particle per million (ppm) gas concentration). Through quantization, we compress the model by over 70%, without sacrificing accuracy. Demonstrated on a combustion-type gas sensor system (dubbed GMOS) for ethylene monitoring, our approach enables continuous, drift-corrected operation without the need for recalibration or dependence on cloud-based services, offering a generalizable solution for embedded environmental sensing—in food transportation containers, cold storage facilities, de-greening rooms and directly in the field. Full article

(1) Background: Geospatial associations for COVID-19 mortality were estimated using a cohort of 28,128 hospitalized Medicaid patients identified from the 2020–2021 Kentucky Health Facility and Services administrative claims data. (2) Methods: County-level patient information (age, sex, chronic obstructive pulmonary disease [COPD], and mechanical ventilation use [96 hrs. plus]); social deprivation index (SDI) scores; physician and nurse rates per 100,000; and annual average particulate matter 2.5 (PM_2.5) were used as the predictors. Ordinary least-squares (OLS) regression and multiscale geographically weighted regression (MGWR) with the dependent variable, COVID-19 mortality per 100,000, were performed to compute global and local effects, respectively. (3) Results: MGWR (adjusted R²: 0.52; corrected Akaike information criterion [AICc]: 292.51) performed better at explaining the association between the dependent variable and predictors than the OLS regression (adjusted R²: 0.36; AICc: 301.20). The percentages of patients with COPD and who were mechanically ventilated (96 hrs. plus) were significantly associated with COVID-19 mortality, respectively (OLS standardized βCOPD: 0.22; βventilation: 0.53; MGWR mean βCOPD: 0.38; βventilation: 0.57). Other predictors were not statistically significant in both models. (4) Conclusions: A risk of COVID-19 mortality was observed among patients with COPD and prolonged mechanical ventilation use, after controlling for social determinants, the healthcare workforce, and PM_2.5 in rural and Appalachian counties of Kentucky. These counties are characterized by persistent poverty, healthcare workforce shortages, economic distress, and poor population health outcomes. Improving population health protection through multisector collaborations in rural and Appalachian counties may help reduce future health burdens. Full article

The online dynamic collection of irrigation and plant physiological information is crucial for the precise irrigation management of nutrient solutions and efficient crop cultivation in vegetable soilless substrate cultivation facilities. In this study, an intelligent weighing system was installed in a tomato substrate cultivation greenhouse. The monitored values from the intelligent weighing system’s pressure-type module were used to calculate irrigation start–stop times, frequency, volume, drainage volume, drainage rate, evapotranspiration, evapotranspiration rate, and stomatal conductance. In contrast, the monitored values of the suspension-type weighing module were used to calculate the amount of weight change in the plants, which supported the dynamic and quantitative characterization of substrate cultivation irrigation and crop growth based on an intelligent weighing system. The results showed that the monitoring curves of pressure and flow sensors based on the pressure-type module could accurately identify the irrigation start time and number of irrigations and calculate the irrigation volume, drainage volume, and drainage rate. The calculated irrigation amount was closely aligned with that determined by an integrated-water–fertilizer automatic control system (R² = 0.923; mean absolute error (MAE) = 0.105 mL; root-mean-square error (RMSE) = 0.132 mL). Furthermore, transpiration rate and leaf stomatal conductance were obtained through inversion, and the R², MAE, and RMSE of the extinction coefficient correction model were 0.820, 0.014 mol·m⁻²·s⁻¹, and 0.017 mol·m⁻²·s⁻¹, respectively. Compared to traditional estimation methods, the MAE and RMSE decreased by 12.5% and 15.0%, respectively. The measured values of fruit picking and leaf stripping linearly fitted with the calculated values of the suspended weighing module, and R², MAE, and RMSE were 0.958, 0.145 g, and 0.143 g, respectively. This indicated that data collection based on the suspension-type weighing module could allow for a dynamic analysis of plant weight changes and fruit yield. In summary, the intelligent weighing system could accurately analyze irrigation information and crop growth physiological indicators under the practical application conditions of facility vegetable substrate cultivation, providing technical support for the precise management of nutrient solutions. Full article

The multi-band atmospheric correction algorithms, now referred to as remote sensing reflectance (R_rs) algorithms, have been implemented on a NASA computing facility for global remote sensing of ocean color and atmospheric aerosol parameters from data acquired with several satellite instruments, including the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi spacecraft platform. These algorithms are based on the 2-band version of the SeaWiFS (Sea-Viewing Wide Field-of-View Sensor) algorithm. The bands centered near 0.75 and 0.865 μm are used for atmospheric corrections. In order to obtain high-quality R_rs values over Case 1 waters (deep clear ocean waters), strict masking criteria are implemented inside these algorithms to mask out thin clouds and very turbid water pixels. As a result, R_rs values are often not retrieved over bright Case 2 waters. Through our analysis of VIIRS data, we have found that spatial features of bright Case 2 waters are observed in VIIRS visible band images contaminated by thin cirrus clouds. In this article, we describe methods of combining cirrus and aerosol corrections to improve spatial coverage in R_rs retrievals over Case 2 waters. One method is to remove cirrus cloud effects using our previously developed operational VIIRS cirrus reflectance algorithm and then to perform atmospheric corrections with our updated version of the spectrum-matching algorithm, which uses shortwave IR (SWIR) bands above 1 μm for retrieving atmospheric aerosol parameters and extrapolates the aerosol parameters to the visible region to retrieve water-leaving reflectances of VIIRS visible bands. Another method is to remove the cirrus effect first and then make empirical atmospheric and sun glint corrections for water-leaving reflectance retrievals. The two methods produce comparable retrieved results, but the second method is about 20 times faster than the spectrum-matching method. We compare our retrieved results with those obtained from the NASA VIIRS R_rs algorithm. We will show that the assumption of zero water-leaving reflectance for the VIIRS band centered at 0.75 μm (M6) over Case 2 waters with the NASA R_rs algorithm can sometimes result in slight underestimates of water-leaving reflectances of visible bands over Case 2 waters, where the M6 band water-leaving reflectances are actually not equal to zero. We will also show conclusively that the assumption of thin cirrus clouds as ‘white’ aerosols during atmospheric correction processes results in overestimates of aerosol optical thicknesses and underestimates of aerosol Ångström coefficients. Full article

Background/Objectives: People living with a spinal cord injury (PwSCI) present numerous complications at a systemic level that negatively impact their physical and mental health as well as their quality of life. The purpose of this study was to describe the clinical profile of PwSCI living in nursing homes (NHs), Complex Continuing Care Systems (CCCs), home care (HC), and inpatient mental health facilities (MHs) in nine Canadian provinces and territories. Methods: We analyzed data collected with the following assessment tools: Resident Assessment Instrument (RAI) Minimum Data Set (RAI-MDS 2.0), RAI–MH, RAI-HC, Cognitive Performance Scale, Activities of Daily Living (ADL) Hierarchy Scale and impairments in instrumental ADLs (IADLs), Pain Scale, Changes in Health, End-Stage Disease, Signs, and Symptoms (CHESS) Scale, Depression Rating Scale, and Deafblind Severity Index (DBSI). We reported counts (n) and percentages (%) and performed Chi-square tests with a Bonferroni correction to determine the statistical significance of the differences in frequencies within and between care settings. Results: We identified 13,136 PwSCI, predominantly males and younger than comparison groups. PwSCI presented fewer comorbidities but reported higher pain than comparison groups. Almost all of the PwSCI in NHs (99.4%) and CCCs (98.9%) needed assistance to perform ADLs. Conclusions: The prevalence of comorbidities and impairments following SCI varies based on the clinical setting. The present clinical profile of PwSCI will inform interventions to improve health of PwSCI across the continuum of care. Full article

Background: Burns represent one of the most severe injuries encountered in the pre-hospital and ED environment, with essential features and an often negatively powerful impact on patients’ quality of life. Preventive measures can significantly reduce the number of cases presenting to medical facilities; knowledge and the correct application of first aid measures in the pre-hospital stage have a significant role in reducing the risk of complications and in obtaining optimal outcomes. Methods: This retrospective one-year single-center study analyzed 399 adult burn patients treated at the Clinical Emergency Hospital of Bucharest (CEHB) in 2023. Information concerning the main characteristics of the patients (age, sex, and residence), etiology and severity of burns, and pre-hospital management of patients was analyzed. Results: Most patients (63.41%) resided in urban areas, with a higher prevalence of males (55.89%). Thermal burns accounted for 77.69% of cases, primarily caused by water, food, oil, or flames. Burns covered ≤10% TBSA in 77.19% of cases, while 6.52% extended beyond 50% TBSA. First aid was provided to 52.63% of patients at the accident site, often by non-specialized individuals. The mean time to presentation was 34.90 h, with significant correlations between time, age, burned body surface area, and burn depth. Conclusions: There is a real need for improvements in first-aid training and health initiatives to enhance pre-hospital burn care. Better documentation of the care provided to patients before being admitted to specialized centers, as well as further studies in this field, are absolutely necessary for improving prevention programs and burn management in the acute stage. Full article

Aggression constitutes a significant behavioral issue associated with delinquent behavior, commonly observed in youth diagnosed with conduct disorder (CD) and living in correctional facilities. Catechol-o-methyl-transferase (COMT) gene variants modify the environmental sensitivity associated with the risk of aggression. This study evaluated the association of COMT rs4680 and rs4818 polymorphisms with aggressive behavior in 341 male adolescents living inside and outside a correctional facility, with or without a diagnosis of CD. Aggression was assessed using the Hare Psychopathy Checklist: Youth Version (PCL-YV), Modified Overt Aggression Scale (MOAS) and Swanson, Nolan and Pelham Questionnaire. COMT rs4680 and rs4818 polymorphisms were genotyped using TaqMan SNP Genotyping Assays. A similar prevalence of the COMT genotypes or haplotypes was found between adolescents with or without CD, suicidal behavior, or detention in correctional facility. In youth with CD, the COMT rs4680 A allele was associated with higher MOAS verbal aggression, aggression toward objects, irritability (subjective and open), and PCL-YV interpersonal domain scores compared with carriers of the COMT rs4680 G allele. COMT rs4818 GC carriers with CD had higher scores on the MOAS subjective irritability than GG heterozygotes. These novel findings revealed the association of lower COMT rs4680 and rs4818 activity alleles with aggression in detained male adolescents with CD. Full article

Non-destructive testing (NDT) plays a crucial role in ensuring the structural integrity and safety of industrial facilities and components. Long pulse thermography (LPT), a form of active thermographic testing (ATT), has gained attention for its ability to detect subsurface defects efficiently. However, non-uniform thermal excitation and environmental noise often degrade the accuracy of defect detection. This study proposes an advanced thermographic inspection technique incorporating a halogen array (HA) lamp and a compensation methodology to enhance the reliability of defect detection. Two compensation methods, namely absolute temperature compensation (ATC) and temperature rate compensation (TRC), were developed to correct non-uniform thermal loads and improve the defect contrast. Experimental validation was conducted on A-type and B-type mock-up specimens with artificial subsurface defects (10–90% depth). The results demonstrated a significant enhancement in the signal-to-noise ratio (SNR), reaching up to a 42 dB improvement in severe defects. Furthermore, a quantitative evaluation method was proposed using SNR-based defect depth estimation models, improving the accuracy of defect sizing. This approach eliminates the need for complex amplitude and phase transformations, enabling direct defect assessment from temperature thermograms. Full article