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Wildfires have become increasingly prevalent worldwide due to climate change, posing significant threats to human lives, property, and natural ecosystems. The rapid progression of wildfires necessitates predictive computational models to assist firefighters in effectively developing strategies to control firefronts. However, existing models often face challenges in computational complexity as the firefront expands. This study aims to develop a faster, more computationally efficient, deep-learning-based model for predicting wildfire spread. We hypothesise that firefront propagation can be modelled using stochastic cellular automata and that a deep-learning model can mimic this approach. With this in mind, we will first introduce our in-house stochastic cellular automata model, which is being validated with data from a known Finnish wildfire. After that, we propose a novel deep-learning model which uses the data generated by our cellular automata. The deep-learning-based model was based on Unet architecture, and it is capable of predicting firefront progression accurately and efficiently one time-step at a time. The model provided realistic simulations of firefronts with high computational efficiency, leaving future development needs to longer time series. One potential application of the developed model is in UAV-based real-time wildfire management systems.

An educator's competence influences the implementation of evidence-based education and the overall quality of social and health care. This study aimed to identify distinct competence profiles from Finnish social, health and rehabilitative care educators, as well as describe which personal and professional characteristics influenced belonging to a certain profile. Data were collected from 28 educational organizations located throughout Finland using the Health and Social Care Educators' Competence instrument. The survey was answered by 422 educators. The performed K-means cluster analysis identified three distinct educator competence profiles, which differed in terms of self-assessed expertise in various competence areas and certain background characteristics. The results highlight that educational institutions should concentrate on refining the digital competence of educators, which requires networking, collaboration, and work-related pedagogical competence. The differences in evaluation identified for the three profiles demonstrates that more experienced educators should mentor their less experienced counterparts to ensure a high quality of education.

The mixing ratios of highly volatile organic compounds (VOCs) were studied on Utö Island in the Baltic Sea. Measurements of non-methane hydrocarbons (NMHCs) and methanethiol (unexpectedly found during the experiment) were conducted using an in situ thermal desorption–gas chromatography–flame ionization detector/mass spectrometer (TD-GC-FID/MS) from March 2018 until March 2019. The mean mixing ratios of NMHCs (alkanes, alkenes, alkynes, and aromatic hydrocarbons) were at the typical levels for rural/remote sites in Europe, and, as expected, the highest mixing ratios were measured in winter, while in the summertime, the mixing ratios remained close to or below detection limits for most of the studied compounds. Sources of NMHCs during wintertime were studied using positive matrix factorization (PMF) together with wind direction analyses and source area estimates. Shipping was found to be a major local anthropogenic source of NMHCs with a 21 % contribution. It especially contributed to ethene, propene, and ethyne mixing ratios. Other identified sources were petrol fuel (15 %), traffic exhaust (14 %), local solvents (6 %), and long-range-transported background (42 %). Contrary to NMHCs, high mixing ratios of methanethiol were detected in summertime (July mean of 1000 pptv). The mixing ratios followed the variations in seawater temperatures and sea level height and were highest during the daytime. Biogenic phytoplankton or macroalgae emissions were expected to be the main source of methanethiol.

The effect of helium plasma operation on the erosion of plasma-facing components at the low-field side divertor of ASDEX Upgrade was investigated during the 2022 helium experimental campaign. A set of tungsten-covered graphite samples with small platinum marker spots was exposed to both L-mode and H-mode plasma discharges. The highest net erosion of over 1.1 nm/s was observed around the H-mode strike point similar to the case in deuterium plasma. Significant helium inventories of about 6 × 1016 He/cm2 were measured in the scrape-off layer region of the divertor. Impurity deposition including boron and deuterium showed a distinct peak up to 2.4 × 1017 B/cm2 and 1.0 × 1016 D/cm2 between the strike points, and significant boron inventories up to 5.9 × 1016 B/cm2 were also measured on the scrape-off layer side of the H-mode strike point. Platinum re-deposition was not detected between the marker spots, suggesting that it occurs only very locally within the markers. Overall erosion was, as expected, higher than in deuterium discharges, and it also remained comparatively high towards the scrape-off layer, unlike with deuterium.

Laser Induced Breakdown Spectroscopy (LIBS) method is considered to be a promising tool for analyzing the retention of hydrogen isotopes (D and T) and helium (He) on the first walls and divertor regions of future fusion reactors. Helium will be produced in DT reactions but could also be used in the initial non-nuclear phases of DEMO concepts. The present study investigates the He detection by LIBS method in the Be coatings simulating the deposits on the divertor plasma-facing components of JET while the results are also relevant for He detection in the deposits of other wall materials. The study was carried out in a vacuum vessel filled with 2–40 mbar argon background gas. It was shown that 2.8 at. % of He was confidently detectable by LIBS at optimized measurement conditions and the estimated limit of detection at used experimental conditions is approximately 0.7 at. %. The intensity of the He emission line at 587.56 nm was the strongest at the center of the laser-induced plasma plume. The He line intensity increased with the pressure of Ar gas but the broadening of the He line and the increase of the background emission and noise set an upper limit to the Ar background pressure usable for He detection. The application of the calibration-free LIBS procedure resulted in the overestimation of the He/Be ratio by several orders of magnitude. The overestimation can be explained by the deviation of LIBS plasma from the local thermodynamic equilibrium, which is caused by the very high excitation energy of He atoms.

Wildfires present severe threats to various aspects of ecosystems, human settlements, and the environment. Early detection plays a critical role in minimizing the destructive consequences of wildfires. This study introduces an innovative approach for smoke-based wildfire detection in Boreal forests by combining the YOLO V5 algorithm and transfer learning. YOLO V5 is renowned for its real-time performance and accuracy in object detection. Given the scarcity of labelled smoke images specific to wildfire scenes, transfer learning techniques are employed to address this limitation. Initially, the generalisability of smoke as an object is examined by utilising wildfire data collected from diverse environments for fine-tuning and testing purposes in Boreal forest scenarios. Subsequently, Boreal forest fire data is employed for training and fine-tuning to achieve high detection accuracy and explore benchmarks for effective local training data. This approach minimises extensive manual labelling efforts while enhancing the accuracy of smoke-based wildfire detection in Boreal forest environments. Experimental results validate the efficacy of the proposed approach. The combined YOLO V5 and transfer learning framework demonstrates a high detection accuracy, making it a promising solution for automated wildfire detection systems. Implementing this methodology can potentially enhance early detection and response to wildfires in Boreal forest regions, thereby contributing to improved disaster management and mitigation strategies.

The pre-fusion power operation (PFPO) phase of ITER, as described in the ITER research plan with Staged Approach,22 ITER Organization, “ITER Research Plan within the Staged Approach,” ITR-18–003, Aug. 2018. includes both hydrogen (H) and helium (He) plasma operations. In preparation for PFPO, both WEST and JET ran He plasma campaigns to study plasma-wall interactions in a tungsten environment. The campaigns included a back-and-forth transition between H or deuterium (D) and He plasma operation allowing the assessment of the achievable plasma content as well as the accessible wall reservoirs for respective species. The WEST changeovers included tokamak pulses with a fixed divertor configuration. The JET changeovers applied ion cyclotron wall conditioning (ICWC) and tokamak pulses including limiter phases and four different divertor configurations. Glow discharge conditioning (GDC) was applied to complete the changeovers. The results are characterized by subdivertor optical and mass spectrometric gas analyzers and spatially resolved optical emission spectroscopy. A He content of 96–97 % after H operations is achieved by tens of ICWC pulses (JET) and several dedicated diverted plasmas (WEST and JET), while a fivefold is estimated to be required for the back transition. Effective pumping of the wall released species is a key parameter for a fast changeover. Upon applying higher heating power, the relative content of the fueled plasma species decreases. The JET gas balance analysis indicates that He operation may increase H retention. WEST divertor spectroscopy indicates a larger He inventory near the inner divertor strike line. He GDC has a clear effect on the He recycling light at the WEST divertor while D GDC did not reduce the long lasting He content observed in D pulses after the JET He campaign.

Understanding the interaction between the fusion plasma and the plasma-facing materials (PFMs) is crucial for achieving the optimal performance, safety, and lifetime of the fusion devices. Relevant materials have been intensely studied to determine fuel retention and the composition of the co-deposited layers on the PFMs by depth profile analysis using Laser-Induced Breakdown Spectroscopy (LIBS) and Calibration-Free (CF)-LIBS. However, the comparison between the layers containing a mixture of different (seeding) gases using LIBS, has not been studied systematically. Consequently, the aim of this work is the LIBS depth profile analysis of Be-based samples containing the fuel (D) and one of the seeding gases (N, Ne, He) with variable concentrations to study the potential impact on fuel retention in the PFMs. The LIBS measurements were performed using Nd:YAG laser (1064 nm) under Ar atmosphere (at 2 and 100 mbar). In LIBS the ablation rate was evaluated, spectral lines of all relevant elements except N and Ne were detected and compared with the SIMS depth profiles. The reasons for the non-detectability of Ne are discussed in detail.

Tungsten (W) is the prime candidate for the plasma facing material in present and future fusion devices. When exposed to a plasma containing He ions, W can exhibit creation of sub-surface nano-bubbles leading to formation of nano-tendrils called fuzz. Formation of W fuzz was confirmed by many laboratory experiments including He loading in linear plasma devices. There is, however, limited experience related to the parameter space for fuzz formation and re-erosion in a tokamak environment. For this reason, a dedicated experiment was carried out in ASDEX Upgrade (AUG) during its 2022 He campaign to study the evolution of fuzz-like W structures.Twelve tungsten samples were mechanically polished to a mirror-like surface finish. Six of them were subsequently exposed to a He plasma in the PSI-2 linear device in order to establish a fuzz layer with a thickness of 600 – 800 nm. Before exposure in AUG, all samples were pre-characterized by Focused Ion Beam (FIB) cross-sectioning. In total 48 FIB cross-sections with line markings for quantification of local erosion, deposition and fuzz formation were prepared – 4 on each sample. The samples were placed in two parallel poloidal rows spanning a range of 20 cm around the outer strike line position (OSP). They were subsequently exposed in AUG to a series of 14 consecutive discharges, 8 in H-mode and 6 in L-mode.Detailed analysis by means of electron microscopy revealed on the samples regions of erosion, deposition and fuzz formation. Below the H-mode OSP, homogeneous co-deposits containing W and O, with a thickness up to 400 nm, were found. In the close vicinity of the H-mode OSP, significant erosion of pre-exposure PSI-2 fuzz was observed. The erosion reached up to 100 – 250 nm, depending on the location. In addition, the initially polished samples did not show any newly formed fuzz in that zone. Above the H-mode OSP, new fuzz was formed with a thickness of up to 1 μm. There was no Mo found in the newly formed fuzz. Pre-exposure PSI-2 fuzz was either removed or modified.

This paper explores the plasma parameters of helium and hydrogen Ion Cyclotron Wall Conditioning (ICWC) discharges performed in JET as part of a He/H fuelling changeover experiment. The conducted study shows that plasma with a higher density is formed in helium than in hydrogen. A distinct glow in the ion cyclotron resonance zone is observed throughout the discharge in He. In H-ICWC discharges, a lower radio-frequency coupling efficiency and coupled power was observed than in He-ICWC discharges. While the helium concentration decreased with the number of H-ICWC pulses and the same for hydrogen in He-ICWC, which is the intended result of the plasma wall interaction in the ICWC changeover procedure, the main features of hydrogen as well as the helium IC discharge do not change dramatically.

BackgroundOral health is a significant part of general health. Poor oral health can influence an individual’s appearance, self-esteem, eating, and speaking. The use of mobile phone apps has been growing in the field of medicine, including dentistry. However, to date, there is no evidence related to the availability of mobile apps focusing on various branches of dentistry. ObjectiveThe aim of this study was to review the scientific literature on the use of patient-oriented mobile phone apps in oral health and summarize the key findings. MethodsA scoping review of published scientific literature on the use of patient-oriented mobile phone apps in oral health was conducted in accordance with the Joanna Briggs Institute. A search was performed in PubMed and Scopus for studies published between January 2000 and June 2021 that were written in English. All study types except for those reporting developmental protocols were included in this review. In total, 2 reviewers independently screened the studies using the eligibility criteria. The study protocol was registered in the Open Science Framework registries in June 2021. ResultsThe initial search yielded a total of 977 studies, 45 (4.6%) of which met the inclusion criteria. All the studies (45/45, 100%) were published after 2009. Most studies (31/45, 69%) concerned oral health promotion using mobile phone apps, followed by behavior management (5/45, 11%). More than half (23/45, 51%) of the included studies were conducted in Asian countries. Overall, 31% (14/45) of the studies focused on adolescents. A total of 51% (23/45) of the studies were randomized controlled trials (RCTs). Approximately 39% (9/23) of the included RCT studies reported a substantial reduction in dental plaque, and 26% (6/23) of the studies reported significant improvement in gingival health. Regarding dental anxiety management, 13% (3/23) of the RCT studies reported a significant decrease in mean heart rate and lower Facial Image Scale scores. ConclusionsAccording to the literature, the use of mobile apps in oral health is increasing among patients, mainly children and adolescents. Many studies that have used mobile apps have focused on promoting oral health. However, other areas such as diagnostic and remote consultations (teledentistry) have until recently been neglected despite their great potential.

Different kinds of W layers resembling the ones found after campaigns in tokamak were produced by Pulsed Laser Deposition: namely nanocrystalline, amorphous and porous W layers. Films were exposed to divertor relevant D plasma, in PSI-2; D retention as well as nanostructure formation were investigated. For nanocrystalline W films we found lamellar structures that coalesce with increasing D fluence. Instead, on amorphous W no lamellas were formed but a new random string-like shape. A higher oxygen content in the W layer results in an evolution of the shape of the nanostructures in straight parallel lines with acute angles. The presence of a porous structure morphology hinders the formation of surface nanostructures. Reviewing results from different linear devices including also bulk W, we observe that, when formed, nanostructures appear in general with a fluence threshold of 3–5 × 1025 D/m2 regardless the impinging D flux. D retention shows an unusual trend increasing fluence and is enhanced by the presence of amorphous structure and open morphology. Amorphous W films exhibit higher D retention (3 orders of magnitude) compared to crystalline W. When the amorphous W is annealed, retention returns to the standard values of bulk W regardless the presence of a layered structure parallel to the substrate. Porous W, thanks to the high surface to volume ratio and the presence of void distribution along the growth direction, favors higher recycling and thus limits the D uptake during exposure. The presence of O, in the investigated coatings, seems to have little effect on D retention.

Children at increased genetic risk for type 1 diabetes (T1D) after environmental exposures may develop pancreatic islet autoantibodies (IA) at a very young age. Metabolic profile changes over time may imply responses to exposures and signal development of the first IA. Our present research in The Environmental Determinants of Diabetes in the Young (TEDDY) study aimed to identify metabolome-wide signals preceding the first IA against GAD (GADA-first) or against insulin (IAA-first). We profiled metabolomes by mass spectrometry from children's plasma at 3-month intervals after birth until appearance of the first IA. A trajectory analysis discovered each first IA preceded by reduced amino acid proline and branched-chain amino acids (BCAAs), respectively. With independent time point analysis following birth, we discovered dehydroascorbic acid (DHAA) contributing to the risk of each first IA, and γ-aminobutyric acid (GABAs) associated with the first autoantibody against insulin (IAA-first). Methionine and alanine, compounds produced in BCAA metabolism and fatty acids, also preceded IA at different time points. Unsaturated triglycerides and phosphatidylethanolamines decreased in abundance before appearance of either autoantibody. Our findings suggest that IAA-first and GADA-first are heralded by different patterns of DHAA, GABA, multiple amino acids, and fatty acids, which may be important to primary prevention of T1D.

Fuel retention monitoring in tokamak walls requires the development of remote composition analysis methods such as laser-induced breakdown spectroscopy (LIBS). The present study investigates the feasibility of the LIBS method to analyse the composition and fuel retention in three samples from WEST divertor erosion marker tiles after the experimental campaign C3. The investigated samples originated from tile regions outside of strong erosion and deposition regions, where the variation of thin deposit layers is relatively small and facilitates cross-comparison between different analysis methods. The depth profiles of main constituents W, Mo and C were consistent with depth profiles determined by other composition analysis methods, such as glow-discharge optical emission spectroscopy (GDOES) and secondary ion mass spectrometry (SIMS). The average LIBS depth resolution determined from depth profiles was 100 nm/shot. The averaging of the spectra collected from multiple spots of a same sample allowed us to improve the signal-to-noise ratio, investigate the presence of fuel D and trace impurities such as O and B. In the investigated tile regions with negligible erosion and deposition, these impurities were clearly detectable during the first laser shot, while the signal decreased to noise level after a few subsequent laser shots at the same spot. LIBS investigation of samples originating from the deposition regions of tiles may further clarify LIBS’ ability to investigate trace impurities.