Distinct Hot Spots Research Articles

Accelerated Historical and Future Warming in the Middle East and North Africa

AbstractThe present study assesses the climate of the Middle East and North Africa (MENA) in detail, focusing on the historical and future warming trends in the region. The assessment incorporates data from observations, reanalyses, and statistically downscaled climate models from the Coupled Model Intercomparison Project Phases 5 and 6. Since the pre‐industrial era, the observed average climate in the MENA has warmed by 1.5°C and is on the brink of exceeding 2°C. The reanalysis data suggest that the regional warming over some MENA sub‐regions is three times faster than the global average. By the end of the 21st century, the Arabian Peninsula is projected to warm to 2.6°C ± 0.57°C and 7.6°C ± 1.53°C under low and high greenhouse gas emission scenarios, respectively. Distinct warming hotspots emerge over the Arabian Peninsula and Algeria in summer and over Mauritania in West Africa and the Elburz Mountains in Iran in winter. The summer hotspot over the Arabian Peninsula has already warmed by more than 2°C and can potentially warm to approximately 9°C under the high‐emission scenario. As global warming progresses to 1.5, 2.0, 3.0, and 4.0°C, the average temperature over the MENA land is projected to increase by 2.3°C ± 0.18°C, 3.0°C ± 0.22°C, 4.6°C ± 0.26°C, and 6.1°C ± 0.31°C, respectively. The 1.5, 2.0, 3.0, and 4.0°C warming levels over the MENA are expected to predate those of the global mean by two or three decades. Natural climate fluctuations also significantly influence the region's warming, contributing to temperature extremes.

Tracing the Propagation of Shocks in the Equatorial Ring of SN 1987A over Decades with the Hubble Space Telescope

The nearby SN 1987A offers a unique opportunity to investigate the complex shock interaction between the ejecta and circumstellar medium. We track the evolution of the optical hot spots within the equatorial ring (ER) by analyzing 33 Hubble Space Telescope imaging observations between 1994 and 2022. By fitting the ER with an elliptical model, we determine its inclination to be 42.°85 ± 0.°50 with its major axis oriented −6.°24 ± 0.°31 from the west. We identify 26 distinct hot spots across the ER, with additional ones emerging over time, particularly on the western side. The hot spots initially show high velocities ranging from 390 to 1660 km s−1, followed by a deceleration phase around day ∼ 8000. Subsequent velocities vary from 40 to 660 km s−1. The light curves of the hot spots reach maxima between 7000 and 9000 days, suggesting a connection with the deceleration. Many spots are spatially resolved and show elongation perpendicular to the direction of motion, indicative of a short cooling time. To explain these results, we propose that each hot spot comprises dense substructures embedded in less dense gas. The initial velocities are then phase velocities, where the break occurs when the blast wave leaves the ER, while the late velocities reflect the propagation of radiative shocks in the dense substructures. We estimate that the dense substructures have a volumetric filling factor of ∼0.3ne/106cm−3−2% and a total mass of ∼0.24ne/106cm−3−1×10−2M⊙ .

Biosensor-based growth-coupling as an evolutionary strategy to improve heme export in Corynebacterium glutamicum

The iron-containing porphyrin heme is of high interest for the food industry for the production of artificial meat as well as for medical applications. Recently, the biotechnological platform strain Corynebacterium glutamicum has emerged as a promising host for animal-free heme production. Beyond engineering of complex heme biosynthetic pathways, improving heme export offers significant yet untapped potential for enhancing production strains. In this study, a growth-coupled biosensor was designed to impose a selection pressure on the increased expression of the hrtBA operon encoding an ABC-type heme exporter in C. glutamicum. For this purpose, the promoter region of the growth-regulating genes pfkA (phosphofructokinase) and aceE (pyruvate dehydrogenase) was replaced with that of PhrtB, creating biosensor strains with a selection pressure for hrtBA activation. Resulting sensor strains were used for plate-based selections and for a repetitive batch f(luorescent)ALE using a fully automated laboratory platform. Genome sequencing of isolated clones featuring increased hrtBA expression revealed three distinct mutational hotspots: (i) chrS, (ii) chrA, and (iii) cydD. Mutations in the genes of the ChrSA two-component system, which regulates hrtBA in response to heme levels, were identified as a promising target to enhance export activity. Furthermore, causal mutations within cydD, encoding an ABC-transporter essential for cytochrome bd oxidase assembly, were confirmed by the construction of a deletion mutant. Reversely engineered strains showed strongly increased hrtBA expression as well as increased cellular heme levels. These results further support the proposed role of CydDC as a heme transporter in bacteria. Mutations identified in this study therefore underline the potential of biosensor-based growth coupling and provide promising engineering targets to improve microbial heme production.

Global landmark: 2023 marks the worst year for dengue cases with millions infected and thousands of deaths reported

ObjectivesIn 2023, the world experienced the worst dengue virus (DENV) outbreak on record. The study aimed to identify global regions and continents with high burden of dengue in 2023. DesignWe collected data on the number of DENV cases and deaths reported by various countries to the World Health Organization and World Health Organization regional offices. We estimated DENV cases per million population and case fatality ratio (CFR) among the confirmed cases reported by each country. ResultsOverall, in 2023 more than 6.5 million cases and over 6,800 deaths attributed to DENV were recorded globally, marking a historic milestone. Two distinct hotspots of DENV circulation emerged: South America and South and Southeast Asian regions. South America reported the highest number of cases (3,924,992), and 1,946 deaths, with a CFR of 0.05. In Asia, 1,622,405 cases and 3,637 deaths were reported, with a CFR of 0.22. We observed a statistically significant difference in the number of cases and deaths per million across different continents (P-value <0.001). However, the CFR did not differ significantly across continents (P-value = 0.123). ConclusionsThe increased cases and mortality highlight the urgent need for a comprehensive global approach aimed at DENV infection control, including vaccine development, vector control, public health initiatives, and improved clinical management.

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer for which few effective therapies exist. Immunotherapies specifically are ineffective in pancreatic cancer, in part due to its unique stromal and immune microenvironment. Pancreatic intraepithelial neoplasia, or PanIN, is the main precursor lesion to PDAC. Recently it was discovered that PanINs are remarkably abundant in the grossly normal pancreas, suggesting that the vast majority will never progress to cancer. Here, through construction of 48 samples of cm3-sized human pancreas tissue, we profiled the immune microenvironment of 1,476 PanINs in 3D and at single-cell resolution to better understand the early evolution of the pancreatic tumor microenvironment and to determine how inflammation may play a role in cancer progression. We found that bulk pancreatic inflammation strongly correlates to PanIN cell fraction. We found that the immune response around PanINs is highly heterogeneous, with distinct immune hotspots and cold spots that appear and disappear in a span of tens of microns. Immune hotspots generally mark locations of higher grade of dysplasia or locations near acinar atrophy. The immune composition at these hotspots is dominated by naïve, cytotoxic, and regulatory T cells, cancer associated fibroblasts, and tumor associated macrophages, with little similarity to the immune composition around less-inflamed PanINs. By mapping FOXP3+ cells in 3D, we found that regulatory T cells are present at higher density in larger PanIN lesions compared to smaller PanINs, suggesting that the early initiation of PanINs may not exhibit an immunosuppressive response. This analysis demonstrates that while PanINs are common in the pancreases of most individuals, inflammation may play a pivotal role, both at the bulk and the microscopic scale, in demarcating regions of significance in cancer progression.

RhizoMAP: a comprehensive, nondestructive, and sensitive platform for metabolic imaging of the rhizosphere

BackgroundElucidating the intricate structural organization and spatial gradients of biomolecular composition within the rhizosphere is critical to understanding important biogeochemical processes, which include the mechanisms of root-microbe interactions for maintaining sustainable plant ecosystem services. While various analytical methods have been developed to assess the spatial heterogeneity within the rhizosphere, a comprehensive view of the fine distribution of metabolites within the root-soil interface has remained a significant challenge. This is primarily due to the difficulty of maintaining the original spatial organization during sample preparation without compromising its molecular content.ResultsIn this study, we present a novel approach, RhizoMAP, in which the rhizosphere molecules are imprinted on selected polymer membranes and then spatially profiled using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). We enhanced the performance of RhizoMAP by combining the use of two thin (< 20 μm) membranes (polyester and polycarbonate) with distinct MALDI sample preparations. This optimization allowed us to gain insight into the distribution of over 500 different molecules within the rhizosphere of poplar (Populus trichocarpa) grown in rhizoboxes filled with mycorrhizae soil. These two membranes, coupled with three different sample preparation conditions, enabled us to capture the distribution of a wide variety of molecules that included phytohormones, amino acids, sugars, sugar glycosides, polycarboxylic acids components of the Krebs cycle, fatty acids, short aldehydes and ketones, terpenes, volatile organic compounds, fertilizers from the soil, and others. Their spatial distribution varies greatly, with some following root traces, others showing diffusion from roots, some associated with soil particles, and many having distinct hot spots along the plant root or surrounding soil. Moreover, we showed how RhizoMAP can be used to localize the origin of the molecules and molecular transformation during root growth. Finally, we demonstrated the power of RhizoMAP to capture molecular distributions of key metabolites throughout a 20 cm deep rhizosphere.ConclusionsRhizoMAP is a method that provides nondestructive, untargeted, broad, and sensitive metabolite imaging of root-associated molecules, exudates, and soil organic matter throughout the rhizosphere, as demonstrated in a lab-controlled native soil environment.

Distinct binding hotspots for natural and synthetic agonists of FFA4 from in silico approaches.

FFA4 has gained interest in recent years since its deorphanization in 2005 and the characterization of the Free Fatty Acids receptors family for their therapeutic potential in metabolic disorders. The expression of FFA4 (also known as GPR120) in numerous organs throughout the human body makes this receptor a highly potent target, particularly in fat sensing and diet preference. This offers an attractive approach to tackle obesity and related metabolic diseases. Recent cryo-EM structures of the receptor have provided valuable information for a potential active state although the previous studies of FFA4 presented diverging information. We performed molecular docking and molecular dynamics simulations of four agonist ligands, TUG-891, Linoleic acid, α-Linolenic acid, and Oleic acid, based on a homology model. Our simulations, which accumulated a total of 2 μs of simulation, highlighted two binding hotspots at Arg992.64 and Lys293 (ECL3). The results indicate that the residues are located in separate areas of the binding pocket and interact with various types of ligands, implying different potential active states of FFA4 and a highly adaptable binding intra-receptor pocket. This article proposes additional structural characteristics and mechanisms for agonist binding that complement the experimental structures.

Understanding Key Stressors for Marine and Coastal Biodiversity Loss: An Overview

Biodiversity hotspots are the regions with high levels of endemic species and significant habitat loss. Coastal areas can exhibit distinct biodiversity hotspots due to their diverse habitats, such as coral reefs, mangrove forests, and intertidal zones. These hotspots often support unique assemblages of species adapted to specific coastal conditions. Ecosystem services provided by marine biodiversity include provisioning services (seafood, resources for medicine); regulating services (stable climate and clean water); cultural services (recreational and mental benefits: sea bathing); and supporting services (nutrient circulation and photosynthesis). Despite some successful conservation efforts, biodiversity continues to decline. Marine ecosystems are vulnerable to rapid changes in diversity and function. Major pressures and threats causing increasing pressure on coastal and marine biodiversity include climate change, ocean acidification, habitat destruction and changes in sea use, invasive species, overexploitation, and pollution. Preservation of coastal biodiversity is of prime importance for human wellbeing. The coastal ecosystems sustain diverse life forms and also safeguard essential ecological services. Therefore conservation and restoration of coastal biodiversity is a timeless responsibility for sustainable development. In light of these observations, this review aims to update recent information from the available literature on the key stressors of marine and coastal biodiversity loss. This study also suggests the strategies to be implemented for successful conservation and restoration of coastal and marine biodiversity.

Complete Chloroplast Genome of Megacarpaea megalocarpa and Comparative Analysis with Related Species from Brassicaceae.

Megacarpaea megalocarpa, a perennial herbaceous species belonging to the Brassicaceae family, has potential medicinal value. We isolated and characterized the chloroplast (cp) genome of M. megalocarpa and compared it with closely related species. The chloroplast genome displayed a typical quadripartite structure, spanning 154,877 bp, with an overall guanine-cytosine (GC) content of 36.20%. Additionally, this genome contained 129 genes, 105 simple sequence repeats (SSRs), and 48 long repeat sequences. Significantly, the ycf1 gene exhibited a high degree of polymorphism at the small single copy (SSC) region and the inverted repeat a (IRa) boundary. Despite this polymorphism, relative synonymous codon usage (RSCU) values were found to be similar across species, and no large segment rearrangements or inversions were detected. The large single copy (LSC) and SSC regions showed higher sequence variations and nucleotide polymorphisms compared to the IR region. Thirteen distinct hotspot regions were identified as potential molecular markers. Our selection pressure analysis revealed that the protein-coding gene rpl20 is subjected to different selection pressures in various species. Phylogenetic analysis positioned M. megalocarpa within the expanded lineage II of the Brassicaceae family. The estimated divergence time suggests that M. megalocarpa diverged approximately 4.97 million years ago. In summary, this study provides crucial baseline information for the molecular identification, phylogenetic relationships, conservation efforts, and utilization of wild resources in Megacarpaea.

Modeling Habitat Suitability of Snow Leopards in Yanchiwan National Reserve, China.

Snow leopards (Panthera uncia) are elusive predators inhabiting high-altitude and mountainous rugged habitats. The current study was conducted in the Yanchiwan National Nature Reserve, Gansu Province, China, to assess the habitat suitability of snow leopards and identify key environmental factors inducing their distribution. Field data collected between 2019 and 2022 through scat sampling and camera trapping techniques provided insights into snow leopard habitat preferences. Spatial distribution and cluster analyses show distinct hotspots of high habitat suitability, mostly concentrated near mountainous landscapes. While altitude remains a critical determinant, with places above 3300 m showing increased habitat suitability, other factors such as soil type, human footprint, forest cover, prey availability, and human disturbance also play important roles. These variables influence ecological dynamics and are required to assess and manage snow leopard habitats. The MaxEnt model has helped us to better grasp these issues, particularly the enormous impact of human activities on habitat suitability. The current study highlights the importance of altitude in determining snow leopard habitat preferences and distribution patterns in the reserve. Furthermore, the study underscores the significance of considering elevation in conservation planning and management strategies for snow leopards, particularly in mountainous regions. By combining complete environmental data with innovative modeling tools, this study not only improves local conservation efforts but also serves as a model for similar wildlife conservation initiatives around the world. By understanding the environmental factors driving snow leopard distribution, conservation efforts can be more efficiently directed to ensure the long-term survival of this endangered species. This study provides valuable insights for evidence-based conservation efforts to safeguard the habitats of snow leopards amidst emerging anthropogenic pressure and environmental fluctuations.

Genetic characterization and phylogenetic analysis of the Nigella sativa (black seed) plastome

In this study, the complete plastome sequence of Nigella sativa (black seed), was analyzed for the first time. The plastome spans approximately 154,120 bp, comprising four sections: the Large Single-Copy (LSC) (85,538 bp), the Small Single-Copy (SSC) (17,984 bp), and two Inverted Repeat (IR) regions (25,299 bp). A comparative study of N. sativa’s plastome with ten other species from various genera in the Ranunculaceae family reveals substantial structural variations. The contraction of the inverted repeat region in N. sativa influences the boundaries of single-copy regions, resulting in a shorter plastome size than other species. When comparing the plastome of N. sativa with those of its related species, significant divergence is observed, particularly except for N. damascena. Among these, the plastome of A. glaucifolium displays the highest average pairwise sequence divergence (0.2851) with N. sativa, followed by A. raddeana (0.2290) and A. coerulea (0.1222). Furthermore, the study identified 12 distinct hotspot regions characterized by elevated Pi values (> 0.1). These regions include trnH-GUG-psbA, matK-trnQ-UUG, psbK-trnR-UCU, atpF-atpI, rpoB-psbD, ycf3-ndhJ, ndhC-cemA, petA-psaJ, trnN-GUU-ndhF, trnV-GAC-rps12, ycf2-trnI-CAU, and ndhA-ycf1. Approximately, 24 tandem and 48 palindromic and forward repeats were detected in N. sativa plastome. The analysis revealed 32 microsatellites with the majority being mononucleotide repeats. In the N. sativa plastome, phenylalanine had the highest number of codons (1982 codons), while alanine was the least common amino acid with 260 codons. A phylogenetic tree, constructed using protein-coding genes, revealed a distinct monophyletic clade comprising N. sativa and N. damascene, closely aligned with the Cimicifugeae tribe and exhibiting robust support. This plastome provides valuable genetic information for precise species identification, phylogenetic resolution, and evolutionary studies of N. sativa.

Influence of climate variability and land cover dynamics on the spatio-temporal NDVI patterns in western hydrological regions of Bangladesh

Analyzing vegetation greenness considering climate and land cover changes is crucial for Bangladesh given the historically drier North-West and South-West regions of Bangladesh have shown prominent climatic and hydrological variations. Therefore, this study assessed the spatial and temporal variation of NDVI and its relationship with climate and land cover changes from 2000 to 2022 for these regions. In this study, Moran's I and Getis Ord Gi* were employed for spatial autocorrelation and Mann-Kendall, Sen's slope test along with Innovative Trend Analysis were deployed to identify temporal trends of NDVI. RMSE, MAE and R-squared values were assessed between computed and observed PET. Correlation of NDVI with climate variables were assessed through multivariate correlation analysis and correlation mapping. Additionally, Pearson product moment correlation was applied between different types of land cover and NDVI. Spatial autocorrelation outcomes showed that NDVI values have been clustered in distinct hotspots and cold-spots over the years. Temporal trend detection results indicate that NDVI values are rising significantly all over the regions. Multivariate correlation analysis identified no climate variable to be the limiting factor for NDVI changes. Similarly, the precipitation-NDVI correlation map displayed no significant correlation. Nonetheless, temperature-NDVI correlation map illustrated varying degrees of mostly moderate and strong positive correlations with distinct negative correlation results in the Sundarbans of South-West region. Land cover pattern analysis with NDVI showed a positive correlation to forest, cropland and vegetation area increasing and negative correlation to grassland and barren area decreasing. In this regard, Rangpur division exhibited stronger correlations than Rajshahi division in North-West. The findings indicate that NDVI changes in the regions are largely dependent on land cover changes in comparison to climate trends. This can instigate further research in other hydrological regions to explore the natural and man-made factors that can affect the greenery and vegetation density in specific regions.

Genomic dissection and mutation-specific target discovery for breast cancer PIK3CA hotspot mutations

BackgroundRecent advancements in high-throughput genomics and targeted therapies have provided tremendous potential to identify and therapeutically target distinct mutations associated with cancers. However, to date the majority of targeted therapies are used to treat all functional mutations within the same gene, regardless of affected codon or phenotype.ResultsIn this study, we developed a functional genomic analysis workflow with a unique isogenic cell line panel bearing two distinct hotspot PIK3CA mutations, E545K and H1047R, to accurately identify targetable differences between mutations within the same gene. We performed RNA-seq and ATAC-seq and identified distinct transcriptomic and epigenomic differences associated with each PIK3CA hotspot mutation. We used this data to curate a select CRISPR knock out screen to identify mutation-specific gene pathway vulnerabilities. These data revealed AREG as a E545K-preferential target that was further validated through in vitro analysis and publicly available patient databases.ConclusionsUsing our multi-modal genomics framework, we discover distinct differences in genomic regulation between PIK3CA hotspot mutations, suggesting the PIK3CA mutations have different regulatory effects on the function and downstream signaling of the PI3K complex. Our results demonstrate the potential to rapidly uncover mutation specific molecular targets, specifically AREG and a proximal gene regulatory region, that may provide clinically relevant therapeutic targets. The methods outlined provide investigators with an integrative strategy to identify mutation-specific targets for the treatment of other oncogenic mutations in an isogenic system.

The E592K variant of SF3B1 creates unique RNA missplicing and associates with high-risk MDS without ring sideroblasts

AbstractAmong the most common genetic alterations in myelodysplastic syndromes (MDS) are mutations in the spliceosome gene SF3B1. Such mutations induce specific RNA missplicing events, directly promote ring sideroblast (RS) formation, and generally associate with a more favorable prognosis. However, not all SF3B1 mutations are the same, and little is known about how distinct hotspots influence disease. Here, we report that the E592K variant of SF3B1 associates with high-risk disease features in MDS, including a lack of RS, increased myeloblasts, a distinct comutation pattern, and a lack of favorable survival seen with other SF3B1 mutations. Moreover, compared with other hot spot SF3B1 mutations, E592K induces a unique RNA missplicing pattern, retains an interaction with the splicing factor SUGP1, and preserves normal RNA splicing of the sideroblastic anemia genes TMEM14C and ABCB7. These data have implications for our understanding of the functional diversity of spliceosome mutations, as well as the pathobiology, classification, prognosis, and management of SF3B1-mutant MDS.

MR Safety of Inductively Coupled and Conventional Intraoral Coils.

Intraoral coils (IOCs) in magnetic resonance imaging (MRI) significantly improve the signal-to-noise ratio compared with conventional extraoral coils. To assess the safety of IOCs, we propose a 2-step procedure to evaluate radiofrequency-induced heating of IOCs and compare maximum temperature increases in 3 different types of IOCs. The 2-step safety assessment consists of electric field measurements and simulations to identify local hotspots followed by temperature measurements during MRI. With this method, 3 different coil types (inductively coupled IFC, transmit/receive tLoop, and receive-only tLoopRx) were tested at 1.5 T and 3 T for both tuned and detuned coil states. High SAR and regular MRI protocols were applied for 2 coil positions. The measured E field maps display distinct hotspots for all tuned IOCs, which were reduced by at least 40-fold when the IOCs were detuned. Maximum temperature rise was higher when the coils were positioned at the periphery of the phantom with the coil planes parallel to B 0 . When neither active nor passive detuning was applied, maximum temperature increase of ΔT = 1.3/0.5/1.8 K was found for IFC/tLoop/tLoopRx coils. Hotspots detected by E field measurements, and simulations were consistent. In the simulations, the results were different for homogeneous phantoms compared with full anatomical models. The 2-step test procedure is applicable to different coil types. The results indicate that a risk for radiofrequency-induced heating exists for tuned IOCs, so that adequate detuning circuits need to be integrated in the coils to ensure safe operation.

Unveiling the Distinct Structure of the Upper Mantle Beneath the Canary and Madeira Hotspots, as Depicted by the 660, 410, and X Discontinuities

AbstractThe Canary and Madeira Islands are two distinct hotspots in the Central‐East Atlantic that are close to each other. Their volcanism is generally attributed to underlying mantle plumes, but the detailed structure of these plumes is still not well understood. The thermal and compositional structure of the plume introduces complexities in the phase transitions of the mantle, which impact the depth and magnitude of seismic discontinuities. We use 1,268 high‐quality receiver functions from stations located at the two hotspots to detect P‐to‐s converted phases through a common‐conversion point stacking approach and conduct a detailed analysis of mantle seismic discontinuities. The results show that both hotspots are characterized by a thin mantle transition zone (MTZ), with sharp 410 and 660 discontinuities at depths of 428–421 km and 647–664 km, beneath the Canaries and Madeira respectively. The results indicate that the Canary plume crosses the MTZ, whereas the Madeira plume mainly influences the upper portion of the MTZ. Furthermore, we find reliable detections of a sharp X discontinuity beneath the Canaries at 287 km. Its presence suggests the accumulation of silica‐rich recycled eclogite at these depths. We also use the amplitudes of P410s and PXs to derive velocity jumps at corresponding discontinuities. Based on these measurements, we estimate that the basalt proportion is 60%–80%, with accumulation being more significant in the Canaries than in Madeira. The MTZ thickness, the presence of the X discontinuity, and the high basalt proportion provide compelling evidence for a deep‐rooted thermochemical plume beneath the study area.

Drone-based monitoring of intertidal blue mussel beds in the Wadden Sea – comparison of a threshold and two machine learning approaches

In the Wadden Sea, intertidal mussel beds of the blue mussel (Mytilus edulis) and the Pacific oyster (Magallana gigas) form distinct epibenthic communities and local hotspots of high biomass and biodiversity. To detect and evaluate natural and anthropogenic processes, a ground-based monitoring program started over 25 years ago in the German Wadden Sea. In this study, we describe the potential of drones and machine learning approaches for a remote sensing-based integration into an existing monitoring program of intertidal mussel beds. A fixed wing drone was used to cover an area of up to 39ha in a single flight, with an overall time saving potential of 50%. Applying machine learning approaches, a detailed extraction of the intertidal blue mussel bed coverage with an overall accuracy (OA) up to 95.6% was reached, applying a Support Vector Machine (SVM). The application of a multispectral sensor improved the classification performance. Compared to ground-based monitoring, the drone-based method provided significantly more information on the area extension, coverage, and associated algae of the mussel beds. The results show that drones can provide a non-invasive way to survey large and difficult to access areas providing detailed maps of mussel beds and their internal structures.

An integrated approach for understanding global earthquake patterns and enhancing seismic risk assessment

Earthquakes, as intricate natural phenomena, profoundly impact lives, infrastructure, and the environment. While previous research has explored earthquake patterns through data analysis methods, there has been a gap in examining the time intervals between consecutive earthquakes across various magnitude categories. Given the complexity and vastness of seismic data, this study aims to provide comprehensive insights into global seismic activity by employing sophisticated data analysis methodologies on a century-long dataset of seismic events. The four-phase methodology encompasses exploratory data analysis (EDA), temporal dynamics exploration, spatial pattern analysis, and cluster analysis. The EDA serves as the foundational step, providing fundamental insights into the dataset's attributes and laying the groundwork for subsequent analyses. Temporal dynamics exploration focuses on discerning variations in earthquake occurrences over time. Spatial analysis identifies geographic regions with heightened earthquake activity and uncovers patterns of seismic clustering. K-means clustering is employed to delineate distinct earthquake occurrence clusters or hotspots based on geographical coordinates. The study's findings reveal a notable increase in recorded earthquakes since the 1960s, peaking in 2018. Distinct patterns in seismic activity are linked to factors such as time, human activities, and plate boundaries. The integrated approach enriches understanding of global earthquake trends and patterns, contributing to improved seismic hazard assessments, early warning systems, and risk mitigation efforts.

Investigating the spatiotemporal associations between meteorological conditions and air pollution in the federal state Baden-Württemberg (Germany)

When analyzing health data in relation to environmental stressors, it is crucial to identify which variables to include in the statistical model to exclude dependencies among the variables. Four meteorological parameters: temperature, ultraviolet radiation, precipitation, and vapor pressure and four outdoor air pollution parameters: ozone (O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{O}_3$$\\end{document}), nitrogen dioxide (NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{NO}_2$$\\end{document}), particulate matter (PM2.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{2.5}$$\\end{document}, PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document}) were studied on a daily basis for Baden-Württemberg (Germany). This federal state covers urban and rural compartments including mountainous and river areas. A temporal and spatial analysis of the internal relationships was performed among the variables using (a) cross-correlations, both on the grand ensemble of data as well as within subsets, and (b) the Local Indications of Spatial Association (LISA) method. Meteorological and air pollution variables were strongly correlated within and among themselves in time and space. We found a strong interaction between nitrogen dioxide and ozone, with correlation coefficients varying over time. The coefficients ranged from negative correlations in January (−0.84), April (−0.47), and October (−0.54) to a positive correlation in July (0.45). The cross-correlation plot showed a noticeable change in the correlation direction for O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{O}_3$$\\end{document} and NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{NO}_2$$\\end{document}. Spatially, NO2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{NO}_2$$\\end{document}, PM2.5\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{2.5}$$\\end{document}, and PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} concentrations were significantly higher in urban than rural regions. For O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{O}_3$$\\end{document}, this effect was reversed. A LISA analysis confirmed distinct hot and cold spots of environmental stressors. This work examined and quantified the spatio-temporal relationship between air pollution and meteorological conditions and recommended which variables to prioritize for future health impact analyses. The results found are in line with the underlying physico-chemical atmospheric processes. It also identified postal code areas with dominant environmental stressors for further studies.

Voxel-wise dose rate calculation in clinical pencil beam scanning proton therapy

Objective. Clinical outcomes after proton therapy have shown some variability that is not fully understood. Different approaches have been suggested to explain the biological outcome, but none has yet provided a comprehensive and satisfactory rationale for observed toxicities. The relatively recent transition from passive scattering (PS) to pencil beam scanning (PBS) treatments has significantly increased the voxel-wise dose rate in proton therapy. In addition, the dose rate distribution is no longer uniform along the cross section of the target but rather highly heterogeneous, following the spot placement. We suggest investigating dose rate as potential contributor to a more complex proton RBE model. Approach. Due to the time structure of the PBS beam delivery the instantaneous dose rate is highly variable voxel by voxel. Several possible parameters to represent voxel-wise dose rate for a given clinical PBS treatment plan are detailed. These quantities were implemented in the scripting environment of our treatment planning system, and computations experimentally verified. Sample applications to treated patient plans are shown. Main results. Computed dose rates we experimentally confirmed. Dose rate maps vary depending on which method is used to represent them. Mainly, the underlying time and dose intervals chosen determine the topography of the resultant distributions. The maximum dose rates experienced by any target voxel in a given PBS treatment plan in our system range from ∼100 to ∼450 Gy(RBE)/min, a factor of 10–100 increase compared to PS. These dose rate distributions are very heterogeneous, with distinct hot spots. Significance. Voxel-wise dose rates for current clinical PBS treatment plans vary greatly from clinically established practice with PS. The exploration of different dose rate measures to evaluate potential correlations with observed clinical outcomes is suggested, potentially adding a missing component in the understanding of proton relative biological effectiveness (RBE).