Search Results (68)

Focused ultrasound (FU) technology is extensively employed in clinical applications such as tumor ablation, Parkinson’s disease treatment, and neuropathic pain management. The safety and efficacy of FU therapy critically depend on the accurate quantification of the acoustic field, particularly the high-pressure distribution in focal region. To address the limitations of existing acoustic measurement techniques—including invasiveness, inability to measure high sound pressure, and system complexity—this study proposes a non-invasive method termed Laser Deflection Acoustic Field Quantification (LDAQ), based on the laser deflection principle. An experimental system was constructed utilizing the acousto-optic deflection effect, which incorporates precision displacement control, rotational scanning, and synchronized triggering. Through tomographic scanning, laser deflection images of the acoustic field were acquired at multiple orientations. An inversion algorithm using Radon transforms was proposed to reconstruct the refractive index gradient distributions from the variations of light intensity and spot displacement. An adaptive weighted fusion strategy was then employed to map these optical signals to the sound pressure field. To validate the LDAQ technique, an acoustic field generated by an FU transducer operating at 0.84 MHz was measured. The reconstructed results were compared with both hydrophone measurements and numerical simulations. The findings demonstrated high consistency among all three results within the focal zone. Full-field analysis yielded a root mean square error (RMSE) of 0.1102 between LDAQ and simulation, and an RMSE of 0.1422 between LDAQ and hydrophone measurements. These results confirm that LDAQ enables non-invasive and high-precision quantification of megapascal-level focused acoustic fields, offering a reliable methodology for acoustic field characterization to support FU treatment optimization and device standardization. Full article

Recent advances in forward-looking sonar (FLS) have enabled the acquisition of high-resolution acoustic images. However, the accuracy of image-based rotation estimation remains limited owing to speckle noise, perceptual ambiguity, and shadows. In recent years, object-based path reconstruction has become increasingly important for underwater inspection tasks, and in such scenarios, reliably estimating rotation from static seabed objects is essential for ensuring the robustness of autonomous underwater vehicle (AUV) missions. Accordingly, we present a rotation estimation method that adaptively extracts a region of interest (ROI) and applies the Radon transform. The proposed approach automatically selects sonar image regions containing objects and emphasizes high projection values in the resulting sinogram. By computing the shift between the high projection values of two sinograms, the method achieves robust rotation estimation even under low contrast and severe speckle noise. Experimental results demonstrate that our method consistently achieves lower estimation errors than existing approaches, particularly in scenarios involving static seabed objects. These findings highlight its practical value for object-based path reconstruction, high-precision mapping, and other underwater navigation tasks. Full article

Measuring indoor radon concentrations is essential for ensuring good air quality in buildings and protecting public health, but significant regulatory and methodological fragmentation still exists at the international level. This study analysed scientific articles published in the last five years, aiming to critically map the technical choices adopted in measuring radon in different indoor environments. The results show that regulatory fragmentation continues to generate inconsistent practices with regard to measurement protocols, sampling durations, devices used, and normative references used to interpret the results. In many cases, the protocols cannot be readily classified according to major technical standards as specific interpretation criteria are required, such as the sampling frequency and the overall duration of the strategy. These results highlight the importance of standardising measurement methods in order to improve the accuracy of exposure assessments and enable comparisons between studies. Full article

The Shizhuyuan polymetallic deposit in Hunan Province, China, is a world-class ore field rich in tungsten (W), tin (Sn), molybdenum (Mo), and bismuth (Bi), now facing resource depletion due to prolonged exploitation. This study addresses the limitations of traditional geological prediction methods in complex terrain by integrating multi-source datasets—including γ-ray spectrometry, high-precision magnetometry, induced polarization (IP), and soil radon measurements—across 5049 samples. Unsupervised factor analysis was employed to extract five key ore-indicating factors, explaining 82.78% of data variance. Based on these geological features, predictive models including Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were constructed and compared. SHAP values were employed to quantify the contribution of each geological feature to the prediction outcomes, thereby transforming the machine learning “black-box models” into an interpretable geological decision-making basis. The results demonstrate that machine learning, particularly when integrated with multi-source data, provides a powerful and interpretable approach for deep mineral prospectivity mapping in concealed terrains. Full article

This study presents the results of preliminary documentation and radon tracer investigations conducted at the “Aurelia” Mine in Złotoryja. Measurements of ²²²Rn activity concentrations were carried out between 17 March and 26 August 2023, while terrestrial laser scanning (TLS) for mapping purposes was performed on 16 November 2024. The radon data exhibited a consistently right-skewed distribution, with skewness coefficients ranging from 0.9 to 8.2 and substantial standard deviations, indicating significant data dispersion. Outliers and extreme outliers were identified as key factors influencing average radon activity concentrations from April through August, whereas data from March displayed homogeneity, with no detected anomalies. The average ²²²Rn activity concentrations recorded from March to July ranged from 51.4 Bq/m³ to 65.9 Bq/m³. In contrast, July and August showed elevated average values (75.8 Bq/m³ and 5784.8 Bq/m³, respectively) due to the presence of outliers and extreme values. Upon removal of these anomalies, the adjusted means were 73.8 Bq/m³ and 1003.6 Bq/m³, respectively, resulting in reduced skewness and improved representativeness. These findings suggest that the annual average radon concentrations at the “Aurelia” Mine remain compliant with the regulatory threshold of 300 Bq/m³ set by the Atomic Law Act, with exceedances likely related to atypical or rare geophysical phenomena requiring further statistical validation. August exhibited a significant occurrence of outliers and extreme outliers in ²²²Rn activity concentration data, particularly concentrated between the 13th and 17th days of the month. This anomaly is hypothesized to be associated with geological processes, notably mining-induced seismic events within the LGOM (Legnica–Głogów Copper District) region. It is proposed that periodic transitions between tensional and compressional phases within the rock mass, triggered by mining activity, may lead to abrupt increases in radon exhalation, potentially occurring before or after seismic events with a magnitude exceeding 2.5. Although the presented data provide preliminary evidence supporting the influence of tectonic kinematic changes on subsurface radon dynamics, further systematic observations are required to confirm this relationship. At the current stage, the hypothesis remains speculative but may contribute to the broader understanding of radon behavior in geologically active underground environments. Complementing the geochemical analysis, TLS enabled detailed geological mapping and 3D spatial modeling of the mine’s underground tourist infrastructure. The resulting simplified linked data model—integrating radon activity concentrations, geological structures, and spatial parameters—provides a foundational framework for developing a comprehensive GIS database. This integrative approach highlights the feasibility of combining tracer studies with spatial and cartographic data to improve radon risk assessment models and ensure regulatory compliance in underground occupational settings. Full article

A new generation of compact radon detectors with high sensitivity and fine spatial resolution (1–2 cm scale) was used to investigate indoor radon distribution and identify potential entry pathways. Solid-state nuclear track detectors (Kodak-Pathe LR-115 type II, Dosirad, France), combined with activated carbon fabric (ACC-5092-10), enabled sensitive, spatially resolved radon measurements. Two case studies were conducted: Case 1 involves a room with elevated radon levels suspected to originate from the floor. Case 2 involves a house with persistently high indoor radon concentrations despite active basement ventilation. In the first case, radon emission from the floor was found to be highly inhomogeneous, with concentrations varying by more than a factor of four. In the second, unexpectedly high radon levels were detected at electrical switches and outlets on walls in the living space, suggesting radon transport through wall voids and entry via non-hermetic electrical fittings. These novel detectors facilitate fine-scale mapping of indoor radon concentrations, revealing ingress routes that were previously undetectable. Their use can significantly enhance radon diagnostics and support the development of more effective mitigation strategies. Full article

Radon anomalies have long been explored as potential geochemical precursors to seismic activity due to their responsiveness to subsurface stress variations. However, before this study, the scientific progression of this research domain had not been systematically examined through a quantitative lens. This study presents a comprehensive bibliometric analysis of 379 articles published between 1977 and 2025 and indexed in Scopus and Web of Science. Utilizing the Bibliometrix R-package and its Biblioshiny interface, the analysis investigates temporal publication trends, leading countries, institutions, international collaboration networks, and thematic evolution. The results reveal a marked increase in research output since 2010, with China, India, and Italy emerging as the most prolific contributors. Thematic mapping indicates a shift from conventional geochemical monitoring toward the integration of artificial intelligence techniques, such as decision trees and neural networks, for anomaly detection and predictive modeling. Notwithstanding this methodological evolution, core research themes remain centered on radon concentration monitoring and the analysis of environmental parameters. Overall, the findings highlight the coexistence of traditional and emerging approaches, emphasizing the importance of standardized methodologies and interdisciplinary collaboration. This bibliometric synthesis provides strategic insights to inform future research and strengthen the role of radon monitoring in seismic early warning systems. Full article

Radon (Rn) exposure has a strong association with lung cancer risk and is influenced by epigenetic modifications. To investigate the characterization of DNA methylation (DNAm) episignatures for radon-induced lung cancer, we detected the specific changes in DNAm in blood and lung tissues using reduced representation bisulfite sequencing (RRBS). We identified the differentially methylated regions (DMRs) induced by radon exposure. The bioinformatics analysis of the DMR-mapped genes revealed that pathways in cancer were affected by radon exposure. Among them, the DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 were repeated between lung tissue and blood, and validated by the MassArray. In addition, radon exposure promoted lung cancer development in the genetic engineering mouse model (GEMM), accompanied by decreased MAPK10 and increased PLCG1, PLCβ3, and PIK3R2 with mRNA and protein levels. Conclusively, radon exposure significantly changes the genomic DNAm patterns in lung tissue and blood. The DNAm episignatures of MAPK10, PLCG1, PLCβ3 and PIK3R2 have a significant influence on radon-induced lung cancer. This brings a new perspective to understanding the pathways involved in radon-induced lung cancer and offers potential targets for developing blood-based biomarkers and epigenetic therapeutics. Full article

This study evaluates the effectiveness of advanced statistical and geospatial methods for analyzing radon concentration distributions in indoor environments, using the district of San Martín de Porres, Lima, Peru, as a case study. Radon levels were monitored using LR-115 nuclear track detectors over three distinct measurement periods between 2015 and 2016, with 86 households participating. Detectors were randomly placed in various rooms within each household. Normality tests (Shapiro–Wilk, Anderson–Darling, and Kolmogorov–Smirnov) were applied to assess the fit of radon concentrations to a log-normal distribution. Additionally, analysis of variance (ANOVA) was used to evaluate the influence of environmental and structural factors on radon variability. Non-normally distributed data were normalized using a Box–Cox transformation to improve statistical assumptions, enabling subsequent geostatistical analyses. Geospatial interpolation methods, specifically Inverse Distance Weighting (IDW) and Kriging, were employed to map radon concentrations. The results revealed significant temporal variability in radon concentrations, with geometric means of 146.4 Bq·${\text{m}}^{-3}$, 162.3 Bq·${\text{m}}^{-3}$, and 150.8 Bq·${\text{m}}^{-3}$, respectively, across the three periods. Up to 9.5% of the monitored households recorded radon levels exceeding the safety threshold of 200 Bq·${\text{m}}^{-3}$. Among the interpolation methods, Kriging provided a more accurate spatial representation of radon concentration variability compared to IDW, allowing for the precise identification of high-risk areas. This study provides a framework for using advanced statistical and geospatial techniques in environmental risk assessment. Full article

The successful prospecting of kimberlite pipes is dependent upon a comprehensive understanding of the deep structures of the pipes and the host geological formation. This is a challenging task, given the complex nature of diamond deposits, the small size of pipes in the plan, the absence of stable features in potential fields, etc. As a consequence, the allocation of control structures is practically not used in exploration work. In this regard, the Arkhangelsk diamond province (NW Russia) is distinguished by the considerable overburden thickness, which presents a significant challenge for the application of geophysical methods. It is thus imperative to devise novel methodologies for conducting investigations. In order to achieve this, a set of methods was employed, including microseismic sounding, passive seismic interferometry, and radon emanation mapping. This set of methods has previously been tested only on a few pipes and has not previously been employed in the Griba deposit. The Volchya pipe was selected as the test object due to its proximity to the Griba pipe. The findings revealed that the pipe displayed a more complex configuration than was previously postulated. The controlling faults were found to be oriented in a southwesterly to northwesterly direction and to exhibit a contrasting narrow vertical structure at depths greater than 400 m. Further identification of control structures by the proposed set of methods can increase the efficiency of diamond prospecting. Full article

This review aimed to explore advances in radon detection methods, emphasizing cost-effectiveness and accessible techniques such as CDs, DVDs, and glass-based detectors. In this review, we compared traditional methods like alpha track detectors and continuous radon monitors with emerging innovations that leverage polycarbonate material and IoT-integrated systems. Our evaluation of the synthesis suggests that CDs and DVDs provide scalable solutions for long-term radon monitoring, while glass-based detectors like CR-39 offer high sensitivity for epidemiological studies. The integration of IoT and AI technologies further enhances real-time radon monitoring, paving the way for precise, scalable, and affordable radon mitigation strategies. This work highlights the importance of low-cost, innovative approaches in reducing radon-related lung cancer risks and informs future research on optimizing the technologies for diverse environments. Full article

Ship wake detection stands as a pivotal task in marine environment monitoring. The main challenge in ship wake detection is to improve detection accuracy and mitigate false alarms. To address this challenge, a novel procedure for ship wake detection in a single SAR image is proposed in this study. Initially, an entropy distance similarity criterion is designed to measure nonlocal image patch similarity. Based on the proposed criterion, a low-rank and sparse decomposition method is modified using nonlocal similar patch matrix construction to separate the sparse wake. Subsequently, a field-of-experts (FOE) model is introduced to generate a series of multi-view wake feature maps, which are fused to construct an enhanced feature map. The sparse wake is further enhanced in the Radon domain with the enhanced feature map. The experimental results demonstrate the effectiveness of the proposed method on real SAR ship wake images. Full article

Radon concentrations in the tourist part of the Cango cave were measured using 25 strategically placed electret ion chambers. Airflow rates were also measured and found to be less than 1 m/s throughout the cave. An IDW interpolated radon concentration overlay was constructed using QGIS and overlayed on maps of the cave. The maximum radon concentration of 2625 Bq/m³ was measured in the Grand Hall, located in the central part of the cave following a narrow passage. The initial part of the cave near the entrance exhibited normal cave breathing characteristics, with radon concentrations of less than 300 Bq/m³. The deepest section of the cave, however, demonstrated an unexpected decrease in radon levels, temperature, and humidity. The average radon concentration in the Cango cave, measured at 1265 Bq/m³, is relatively low compared to other caves worldwide that need mitigation measures according to the International Commission on Radiological Protection (ICRP). Full article

We present two magnetic particle imaging (MPI) systems with bore sizes of 75 mm and 100 mm, respectively, using three-dimensionally arranged permanent magnets for excitation and frequency mixing magnetic detection (FMMD) coils for detection. A rotational and a translational stage were combined to move the field free line (FFL) and acquire the MPI signal, thereby enabling simultaneous overall translation and rotational movement. With this concept, the complex coil system used in many MPI systems, with its high energy consumption to generate the drive field, can be replaced. The characteristic signal of superparamagnetic iron oxide (SPIO) nanoparticles was generated via movement of the FFL and acquired using the FMMD coil. The positions of the stages and the occurrence of the f₁ + 2f₂ harmonics were mapped to reconstruct the spatial location of the SPIO. Image reconstruction was performed using Radon and inverse Radon transformations. As a result, the presented method based on mechanical movement of permanent magnets can be used to measure the MPI, even for samples as large as 100 mm. Our research could pave the way for further technological developments to make the equipment human size, which is one of the ultimate goals of MPI. Full article

The objective of this work is to give a holistic overview of the groundwater quality in Qatar in terms of its radon levels and provide a radiological risk assessment of elevated radon levels on human health. This study covered the analysis of groundwater collected from various locations throughout Qatar and maps using ArcGIS followed by a radiological risk assessment of radon in Qatar. There is no extensive study reported to investigate radon activity levels in groundwater across Qatar and their health effects. The radon level measurements of the Qatari groundwater ranged between 2.7 ± 0.2 and 60.7 ± 13.4 Bq/L with a mean value of 20.6 Bq/L, which is greater than the US EPA’s maximum contamination level (11 Bq/L). About 65% of the studied samples exceeded the US EPA’s MCL guidelines. The mean total annual effective dose due to radon inhalation and ingestion was 0.056 mSv/y, which is below the WHO reference level of 0.1 mSv/y. The radon radiological risk study through inhalation and ingestion clearly revealed that the contribution of the inhalation dose was higher than the ingestion dose. Full article