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Climate change endangers the Carpathian region by increasing the risk of fires. In response, our study provides a harmonised dataset with twenty-seven variables and develops an interpretable machine learning-based framework for assessing fire susceptibility across all seven countries of the region. We applied a two-stage process: first, using various feature selection techniques to refine predictors before the modeling phase, and second, utilising the SHAP framework to interpret model predictions. Between these steps, advanced machine learning models were optimised and trained in the H2O environment, demonstrating high predictive accuracy. Our findings revealed eight fire susceptibility clusters. The resulting dataset, susceptibility maps, and detailed interpretative insights serve as a valuable resource for local communities and policy-makers in the region.

Based on the European Union Basic Safety Standards to protect people against exposure to ionizing radiation, establishing and addressing the reference levels for indoor radon concentrations is necessary. Therefore, the indoor radon concentration should be monitored and control in dwelling and workplaces. However, proper ventilation and sustainability are the major factors that influence how healthy the environment in a building is for its occupants. In this paper, the indoor radon distribution in a typical naturally ventilated room under two scenarios (when the door is closed and open) using the computational fluid dynamics (CFD) technique was studied. The CFD code ANSYS Fluent 2020 R1 based on the finite volume method was employed before the simulation results were compared with analytical calculations as well as passive and active measurements. The average radon concentration from the CFD simulation was found to be between 70.21 and 66.25 Bq m −3 under closed and open-door conditions, respectively, at the desired ventilation rate of 1 ACH (Air Changes per Hour). Moreover, the highest concentrations of radon were measured close to the floor and the lowest values were recorded near to the inlet, resulting in the airflow velocity profile. The simulation results were in good agreement with the maxima of 19% and 7% compared to analytical calculations at different indoor air velocities in the open- and closed-door scenarios, respectively. The measured radon concentrations obtained by the active measurements also fitted well with the CFD results, for example, with a relative standard deviation of around 7% and 2% when measured by AlphaGUARD and RAD7 monitors at a height of 1.0 m above the ground in the open-door scenario. From the simulation results, the effective dose received by an individual from the indoor air of the workplace was also calculated.

BackgroundThe European Union council has introduced the basic safety standards (EU-BSS) for protection against the dangers arising from exposure to ionizing radiation by laying down a new radon reference level at workplaces. In this regard, all European state members must establish a national reference level based on all pre-defined requirements. After implanting the directive 2013/59/Euratom by European state members, new challenges have been revealed to mitigate radon appropriately in underground workplaces due to the exciting limitations (e.g., ventilation system, dust dispersion, air injection, etc.). Therefore, a conceptual design of an environmental radiological survey was defined and implemented by examining the hypothesis to find practical solutions following EU-BSS. The main objectives of this study were to identify the potential radon entry paths, utilize an optimized ventilation system, and carry on long-term radon monitoring in an operational underground manganese mine.ResultsThe mullock rocks (the geological structure of the mine walls) contained a small amount of Ra-226 (2–4 Bq kg−1). On the other hand, the mine ore (black shale, underlayer black shale, and carbonate ore) has shown the highest concentration of Ra-226 (12–16 Bq kg−1) and the highest radon exhalation (1.2–1.6 mBq s−1 m−2). The surface radon exhalation from the mine walls was in the range of 0.7 ± 0.1 and 1.5 ± 0.2 mBq m−2 s−1. It was found that shortly after mining activity was undertaken, radon concentration increased dramatically with an average of about 5900 ± 420 Bq m−3 near the freshly broken walls. The optimized mobile mitigation system reduced radon concentration to 250 ± 41 Bq m−3 on average.ConclusionApart from the fact that aged walls were involved in the radon accumulation, considering the mine ventilation performance and the total active surface area, the exhaled radon from the aged walls could not be the primary potential source of high radon concentration when mining activity was undertaken. According to the obtained results, the ores, recently fragmented during the course of mining operations, were the primary path. Therefore, after successfully identifying the radon entry path, radon concentration could be reduced to meet the EU-BSS requirement by implementing the developed mitigation system.

Impact assessment of building materials is a focused topic in the field of radioecology. A radiological survey has conducted to monitor radioactivity of most common building materials in Semnan Province, Iran, and assess the radiation risk. Activity concentrations of 226 Ra, 232 Th, and 40 K were measured in 29 samples including nine commonly used building materials that were collected from local suppliers and manufacturers, using a high purity germanium gamma-ray detector. The activity concentrations of 226 Ra, 232 Th, and 40 K varied from 6.7±1 to 43.6±9, 5.9±1 to 60±11, and 28.5±3 to 1085±113 Bq kg −1 with averages of 26.8±5, 22.7±4, and 322.4±4 Bq kg −1 , respectively. By applying multivariate statistical approach (Pearson correlation, cluster, and principal component analyses (PCA)), the radiological health hazard parameters were analyzed to obtain similarities and correlations between the various samples. The Pearson correlation showed that the 226 Ra distribution in the samples is controlled by changing the 232 Th concentration. The variance of 95.58% obtained from PCA resulted that the main radiological health hazard parameters exist due to the concentration of 226 Ra and 232 Th. The resulting dendrogram of cluster analysis also shows a well coincidence with the correlation analysis.

Humans are continuously exposed to polymeric materials such as in textiles, car tires and packaging. Unfortunately, their break down products pollute our environment, leading to widespread contamination with micro- and nanoplastics (MNPs). The blood–brain barrier (BBB) is an important biological barrier that protects the brain from harmful substances. In our study we performed short term uptake studies in mice with orally administered polystyrene micro-/nanoparticles (9.55 µm, 1.14 µm, 0.293 µm). We show that nanometer sized particles—but not bigger particles—reach the brain within only 2 h after gavage. To understand the transport mechanism, we performed coarse-grained molecular dynamics simulations on the interaction of DOPC bilayers with a polystyrene nanoparticle in the presence and absence of various coronae. We found that the composition of the biomolecular corona surrounding the plastic particles was critical for passage through the BBB. Cholesterol molecules enhanced the uptake of these contaminants into the membrane of the BBB, whereas the protein model inhibited it. These opposing effects could explain the passive transport of the particles into the brain.

Previous research has not demonstrated secondary degeneration of the spinal cord (SpC) motoneurons after cerebral infarct. The aim of the present study is to investigate the involvement of the anterior horn cells (AHC) in the early post-stroke period using histomorphological and immunohistochemical methods. Post-mortem analysis of the 6th cervical segment was performed in 7 patients who had total MCA stroke within 1 month before death. Nissl-stained sections were used for morphometry, while CD68 and synaptophysin (SYP) immunohistochemistry to monitor microglial activation and synaptic changes in the anterior horn (AH), respectively. Contralateral to the cerebral lesion (contralesional side), cells were smaller after 3 days and larger after 1 week of stroke, especially regarding the large alpha motoneurons. CD68 density increased mainly on the contralesional Rexed’s IX lamina of the SpC. SYP coverage of the large motoneurons was reduced on the contralesional side. Early microglial activation in the AH and electrophysiological signs has suggested the possibility of impairment of anterior horn cells (AHC-s). Our study supported that early microglial activation in the contralesional side of the SpC may primarily affect the area corresponding to the location of large motoneurons, and is accompanied by a transient shrinkage followed by increase in size of the large AHC-s with a reduction of their synaptic coverage. After MCA stroke, early involvement of the SpC motoneurons may be suspected by their morphological and synaptic changes and by the pattern of microglial activation.

Recently, interest in measuring the concentration of 220 Rn in air has increased greatly following the development of standards and the calibration of monitoring instruments. In this study, a 220 Rn calibration chamber was designed and developed at the Institute of Radiochemistry and Radioecology (RRI) based on the computational fluid dynamics (CFD) method implemented in ANSYS Fluent 2020 R1 code at the University of Pannonia in Hungary. The behavior of 220 Rn and its spatial distribution inside the 220 Rn calibration chamber at RRI were investigated at different flow rates. The 220 Rn concentration was close to homogeneous under higher flow regimes due to thorough mixing of the gas inside the chamber. Predictions based on CFD simulations were compared with experimentally measured transmission factors (C out /C in ). The spatial distribution of 220 Rn was dependent on the flow rate and the positions of the inlet and outlet. Our results clearly demonstrate the suitability of the 220 Rn calibration chamber at RRI for calibrating monitoring instruments. Furthermore, the CFD-based predictions were in good agreement with the results obtained at higher flow rates using experimental and analytical models according to the relative deviation, with a maximum of approximately 9%.

A comprehensive study was carried out to measure indoor radon/thoron concentrations in 78 dwellings and soil-gas radon in the city of Mashhad, Iran during two seasons, using two common radon monitoring devices (NRPB and RADUET). In the winter, indoor radon concentrations measured between 75 ± 11 to 376 ± 24 Bq·m−3 (mean: 150 ± 19 Bq m−3), whereas indoor thoron concentrations ranged from below the Lower Limit of Detection (LLD) to 166 ± 10 Bq·m−3 (mean: 66 ± 8 Bq m−3), while radon and thoron concentrations in summer fell between 50 ± 11 and 305 ± 24 Bq·m−3 (mean 115 ± 18 Bq m−3) and from below the LLD to 122 ± 10 Bq m−3 (mean 48 ± 6 Bq·m−3), respectively. The annual average effective dose was estimated to be 3.7 ± 0.5 mSv yr−1. The soil-gas radon concentrations fell within the range from 1.07 ± 0.28 to 8.02 ± 0.65 kBq·m−3 (mean 3.07 ± 1.09 kBq·m−3). Finally, indoor radon maps were generated by ArcGIS software over a grid of 1 × 1 km2 using three different interpolation techniques. In grid cells where no data was observed, the arithmetic mean was used to predict a mean indoor radon concentration. Accordingly, inverse distance weighting (IDW) was proven to be more suitable for predicting mean indoor radon concentrations due to the lower mean absolute error (MAE) and root mean square error (RMSE). Meanwhile, the radiation health risk due to the residential exposure to radon and indoor gamma radiation exposure was also assessed.

Identifying investment patterns as part of customer segmentation is one of the most important tasks in retail banking. Clustering customers effectively is an important element of improving marketing policy and strategic planning. There are several methods for identifying similar groups of customers and describing their characteristics to offer them appropriate products. However, using machine learning methods is rare, and the application is limited for certain types of data. The aim of this study is to investigate the benefits of using a two-stage clustering method using neural-network-based Kohonen self-organizing maps followed by hierarchical clustering for identifying the investment patterns of potential retail banking customers. The unique benefit of this method is the ability to use both categorical and numerical variables at the same time. This research examined 1,542 responses received for an online investment survey, focusing on the questions that are related to the respondents’ investment preferences and their current financial assets. The research utilizes descriptive statistics and multiple correspondence analysis (MCA) to understand the variables and Kohonen self-organizing maps (SOMs), in combination with hierarchical clustering, to identify customer groups and describe the characteristics of these clusters. The analysis was able to identify clusters of potential customers with similar preferences and gained insights into their investment patterns related to their investment portfolio and investment behavior, including their savings profile, attitude to risk-taking, and preferences for investment advice. These findings were supported by additional insights through the application of multiple correspondence analysis (MCA) describing patterns of financial instruments and portfolios. The main contribution of the research is the combined application of the machine learning methods Kohonen SOM, hierarchical clustering, and MCA for investment pattern analysis in the retail banking business.

Mobility of transposable elements (TEs) frequently leads to insertional mutations in functional DNA regions. In the potentially immortal germline, TEs are effectively suppressed by the Piwi-piRNA pathway. However, in the genomes of ageing somatic cells lacking the effects of the pathway, TEs become increasingly mobile during the adult lifespan, and their activity is associated with genomic instability. Whether the progressively increasing mobilization of TEs is a cause or a consequence of ageing remains a fundamental problem in biology. Here we show that in the nematode Caenorhabditis elegans , the downregulation of active TE families extends lifespan. Ectopic activation of Piwi proteins in the soma also promotes longevity. Furthermore, DNA N 6 -adenine methylation at TE stretches gradually rises with age, and this epigenetic modification elevates their transcription as the animal ages. These results indicate that TEs represent a novel genetic determinant of ageing, and that N 6 -adenine methylation plays a pivotal role in ageing control. Transposable elements in somatic cells become increasingly mobile during ageing. Here, the authors show that in the nematode Caenorhabditis elegans , downregulation of transposable elements extends lifespan, and that their increases with age are coupled with progressively growing N 6 -adenine methylation in these genetic loci.