Benjamin D. Goffin, Alfonso Fernandez, Jordi Etchanchu
et al.
Wildfires, exacerbated by climate change, land-use alterations, and extreme weather conditions, can have catastrophic impacts on both people and ecosystems. Recent research highlights the role of Soil Moisture (SM) as a predisposing factor to large fires, yet critical thresholds remain poorly characterized across different data sources. Volumetric SM measurements differ in magnitude and dynamic range across large spatial extents and satellite products, making direct comparisons challenging. To address this, we calculated the Fraction of Available Water (FAW), which ranges from 0 to 1 as SM varies from wilting point to field capacity. Using satellite observations from the Soil Moisture and Ocean Salinity (SMOS), Advanced Microwave Scanning Radiometer 2 (AMSR2), Soil Moisture Active Passive (SMAP), and the Climate Change Initiative (CCI) programs, we explored antecedent conditions in south-central Chile that favored an extreme fire spread in early February 2023, when over 240 000 ha burned in just four days. Our analysis showed that FAW was low—not only in the days immediately before the fires, but throughout the preceding month. Critical thresholds emerged across multiple satellite products, revealing plant stress (FAW < 0.50) and extreme drought (FAW < 0.20). Even drier conditions (FAW < 0.10) were widespread, affecting both burned and nonburned areas and reducing moisture constraints across the region. Our findings demonstrate that FAW thresholds derived from multiple satellite products, including SMOS, SMAP, and CCI, provide a robust framework for identifying SM levels that may predispose areas to wildfire danger.
Several solutions have been proposed to explain the dark matter (DM) component, but two explanations stand out. The most widely accepted is the assumption of the existence of exotic matter, and the second is the assumption of a modification of gravitation called MOND. We show in this article that the solutions of exotic matter and MOND are particular cases of a more general solution of pure general relativity that explains DM with only baryonic matter and without modifying gravity. Within the framework of general relativity linearization (GRL), we first demonstrate that these two explanations (exotic matter and GRL solution) are so close that all explanations within the framework of the exotic matter assumption can be translated within the GRL solution. Conversely, certain effects appear in this alternative that should not be observed in the hypothesis of exotic matter. Different types of alignments (about axes of rotation or planar trajectories) should appear on different types of objects (dwarf satellite galaxies, galaxies, or clusters of galaxies). Observational monitoring of the dynamics of S-2 stars close to our Galactic Center in the future should reveal (due to greater precision) discrepancies from the theory, explainable by the lower mass of SgrA* compensated by a stronger-than-expected GRL field (instead of exotic matter). The implementation of simulations to explain the structuring of the universe on a large scale should be able to reveal filaments or walls and large voids, thanks to a stronger-than-expected GRL field (explaining the DM component instead of exotic matter). The size of these structures would be correlated with the intensity of this GRL field. We show that this solution responds to the points addressed to all alternatives to exotic matter. Conversely, we propose points challenging the exotic matter assumption that are naturally explained in this DM component alternative explanation.
Haley Svadlenak, Ross Parnell‐Turner, Margaret Morris
Abstract Tectonic subsidence, sea level, and paleoclimate reconstructions using marine records rely on accurate decompaction of the sediment column. Over time, increased overburden pressure from burial decreases sediment porosity with depth. The porosity‐depth relationship is lithology‐dependent and can be represented by an exponential function determined by initial porosity at the seafloor and compaction decay length. While site‐specific compaction parameters are useful for most studies, these are often unrepresentative due to an insufficient number of measurements. Existing, commonly applied parameter estimates are based upon a handful of spatially restricted sites and lack meaningful uncertainty constraints. We compiled a global porosity data set consisting of 31,808 moisture and density measurements from 280 scientific ocean drilling sites visited during 60 Integrated Ocean Drilling Program and International Ocean Discovery Program (IODP) expeditions between 2009 and 2024. Using bootstrapping techniques, we resampled and fit porosity measurements 10,000 times using nonlinear least squares to obtain compaction parameters and uncertainties both globally and independently for sites in the Pacific, Atlantic, Indian, and Southern Oceans. Measurements from samples dominated by a single lithology (>75%) were used to obtain lithology‐dependent parameters. Average compaction behavior for marine sediments can be described with an initial porosity of 66.3±2.0% and a decay length of 1399±120 m. Our results confirm the lithology‐dependence of these parameters and indicate that sediment compaction behavior is consistent across ocean basins. These globally‐applicable parameters and uncertainties are a valuable resource for evaluating sediment decompaction and will enable error quantification in subsequent analyses of basin evolution and sedimentation.
Astronomical imaging data frequently exhibit low signal-to-noise ratios (SNRs), especially for observations obtained from small-aperture, wide-field survey instruments, in which the detected signals are inherently faint and dominated by noise. Such characteristics pose a substantial technical challenge for subsequent target detection and quantitative measurement tasks. This challenge is particularly pronounced for faint astronomical targets with SNRs ranging from 1 to 10. When the SNR decreases below approximately 5, the useful signal approaches or falls beneath the detection threshold imposed by background noise, leading to a pronounced degradation in the performance of traditional threshold-based detection algorithms, such as Sextractor. Furthermore, astronomical imaging data are typically characterized by a high 16-bit dynamic range. This wide dynamic range results in the intensities of faint targets being compressed into a narrow interval of low pixel values. Standard global normalization strategies employed in deep learning models further compress this narrow intensity band, thereby suppressing and obscuring discriminative target features. To address these challenges, we propose ATD-DL, a deep learning–based framework specifically designed for faint astronomical target detection. The core of the proposed framework is an enhanced U-Net–based segmentation architecture. This architecture is integrated with a multi-stage image preprocessing pipeline, target separation, and centroid extraction modules to enable efficient and robust detection of astronomical objects. Experimental results demonstrate that the proposed method achieves excellent performance in detecting extremely faint targets with SNRs in the range 2 ≤ SNR < 5. Compared with traditional approaches, including SExtractor and DAOPHOT, the proposed framework exhibits a markedly superior detection capability under low-SNR conditions near the detection limit. In future applications, ATD-DL may be extended to space object detection tasks, where it has the potential to substantially improve the identification of extremely faint targets.
Abstract This paper presents a case study on the digital transformation of the Timber Buyers Program within the Illinois Department of Natural Resources (IDNR). The initiative replaced outdated, paper-based systems for timber buyer licensing and harvest fee tracking with a modern, GIS-integrated web ap- plication. This transformation not only improved operational efficiency and significantly boosted harvest fee revenue, but also established a strategic roadmap to strengthen enforcement against illegal timber activities, directly supporting the efforts of District Forest Officers and Conservation Police Officers. By integrating ArcGIS, the solution enabled precise geolocation of timber harvest sites—a capability previously unavailable to the agency. The case highlights how the strategic application of geospatial and IT expertise can deliver measurable improvements in public-sector forest management, offering a scalable model for environmental conservation agencies across the United States. The study adopts a mixed-method approach, combining spatial analysis and operational data from 2023 to 2024 to evaluate the measurable impact of GIS integration on efficiency and revenue. Quantitative validation demonstrates improved data accuracy and enforcement outcomes, reinforcing the significance of GIS as an evidence-based governance tool.
Sergey Shuvalov, Laila Andersson, Jasper S. Halekas
et al.
Abstract Heavy cold ions at Mars are gravitationally bound to the planet unless some process provides energy to them. Observations show that cold (<20 eV) and dense (∼>1 cm−3) O+/O2+ ions with bulk velocities equal to energies ∼1 keV can reach deep into the nightside Martian magnetosheath. These ions are co‐located with a change of the sign of the sunward component of the magnetic field. This magnetic field topology implies the persistence of a localized planetary ions escape channel associated with draped magnetic field lines that are convecting tailward. The observed ion populations propagate approximately in the same direction as surrounding magnetosheath flow and are likely to be almost unheated ionospheric ions from low altitudes. The paper discusses planetary ion energization via Hall electric field originated from ions and electron separation associated with magnetic field curvature.
Abstract Freezing temperature parameterization significantly impacts the heat balance at sea‐ice bottom and, consequently, the simulated sea‐ice thickness. Here, the single‐column model ICEPACK was used to investigate the impact of the freezing temperature parameterization on the simulated sea‐ice thermodynamic growth during the MOSAiC expedition from October 2019 to September 2020. It is shown that large model errors exist with the standard parameterization and that different formulations for calculating the freezing temperature impact the simulated sea‐ice thickness significantly. Considering the winter mixed layer temperature, a modified parameterization of the freezing point temperature based on Mushy scheme was developed. The mean absolute error (ratio) of simulating sea‐ice thickness for all buoys reduces from 7.4 cm (4.9%) with the “Millero” scheme, which performs the best among the existing schemes in the ICEPACK model, to 4.2 cm (2.9%) with the new developed scheme.
Abstract Recent studies have demonstrated great values of deep‐learning (DL) methods for improving El Niño‐Southern Oscillation (ENSO) predictions. However, the black‐box nature of DL makes it challenging to physically interpret mechanisms responsible for successful ENSO predictions. Here, we demonstrate an interpretable method by performing perturbation experiments to predictors and quantifying input‐output relationships in predictions by using a transformer‐based model; ENSO‐related thermal precursors serving as initial conditions during multi‐month time intervals (TIs) are identified in the equatorial‐northern Pacific, acting to precondition input predictors to provide for long‐lead ENSO predictability. Results reveal the existence of upper‐ocean temperature anomaly pathways and consistent phase propagations of thermal precursors around the tropical Pacific. It is illustrated that three‐dimensional thermal fields and their basinwide evolution during long TIs act to enhance long‐lead prediction skills of ENSO. These physically explainable results indicate that neural networks can adequately represent predictable precursors in the input predictors for successful ENSO predictions.
Quantum nonlocality would naturally fit into a version of relativity with a preferred reference system. However, acceptance of this idea has traditionally required experimental evidence. Namely, detecting in laboratory a small angular dependence of the velocity of light correlated to the cosmic motion of the Earth. Here, we summarize a new theoretical framework where the tiny, irregular residuals observed so far, from Michelson-Morley to current experiments of laser interferometry, can indeed be understood in terms of the Earth motion in the Cosmic Microwave Background observed directly with satellites in space. Our results, challenging the usual null interpretation, emphasize the central role of 'ether-drift' experiments for Relativity, Cosmology and Quantum Physics.
Mercedes E. Paoletti, Oscar Mogollon-Gutierrez, Sergio Moreno-Alvarez
et al.
Land-cover classification is an important topic for remotely sensed hyperspectral (HS) data exploitation. In this regard, HS classifiers have to face important challenges, such as the high spectral redundancy, as well as noise, present in the data, and the fact that obtaining accurate labeled training data for supervised classification is expensive and time-consuming. As a result, the availability of large amounts of training samples, needed to alleviate the so-called Hughes phenomenon, is often unfeasible in practice. The class-imbalance problem, which results from the uneven distribution of labeled samples per class, is also a very challenging factor for HS classifiers. In this article, a comprehensive review of oversampling techniques is provided, which mitigate the aforementioned issues by generating new samples for the minority classes. More specifically, this article pursues a twofold objective. First, it reviews the most relevant oversampling methods that can be adopted according to the nature of HS data. Second, it provides a comprehensive experimental study and comparison, which are useful to derive practical conclusions about the performance of oversampling techniques in different HS image-based applications.
Abstract We derive the ALOS‐2 coseismic interferograms, pixel‐offsets and Sentinel‐2 sub‐pixel offsets of the 2023 Mw7.8 and Mw7.7 Kahramanmaras, Turkey earthquake sequence. Offset maps show that the sequence ruptured ∼300 km along the East Anatolian Fault (EAF) and ∼180 km along the secondary Cardak and Dogansehir faults. We infer the coseismic slip distribution and interseismic fault motion by inverting the co‐ and inter‐seismic observations. Inversion results show that the coseismic slip (∼8.0 m) and interseismic strike‐slip rate (∼4.6 mm/yr) on the main rupture of the Mw7.8 event are basically consistent with the ∼8.4 m and ∼3.9 mm/yr of the Mw7.7 event. Most coseismic slips of the Mw7.8 and Mw7.7 events occur within 10 and 12 km at depth, respectively, in keeping with the interseismic locking depth of 10.4 ± 3.3 km and 11.1 ± 3.1 km. This implies that the coseismic rupture kinematics correlate with the interseismic strain accumulation. Moreover, static stress changes show that the Mw7.7 event is likely promoted by ∼2 bar stress increase from the Mw7.8 event on the central section of its main rupture.
This volume presents, with some amplification, the notes on the lectures on nuclear physics given by Enrico Fermi at the University of Chicago in 1949 "The compilers of this publication may be warmly congratulated The scope of this course is amazing: within 240 pages it ranges from the general properties of atomic nuclei and nuclear forces to mesons and cosmic raysThis volume presents, with some amplification, the notes on the lectures on nuclear physics given by Enrico Fermi at the University of Chicago in 1949 "The compilers of this publication may be warmly congratulated The scope of this course is amazing: within 240 pages it ranges from the general properties of atomic nuclei and nuclear forces to mesons and cosmic rays, and includes an account of fission and elementary pile theory The course addresses itself to experimenters rather than to specialists in nuclear theory, although the latter will also greatly profit from its study on account of the sound emphasis laid everywhere on the experimental approach to problems There is a copious supply of problems "—Proceedings of the Physical Society "Only a relatively few students are privileged to attend Professor Fermi's brilliant lectures at the University of Chicago; it is therefore a distinct contribution to the followers of nuclear science that his lecture material has been systematically organized in a publication and made available to a much wider audience "—Nucelonics
String theory always comes with heavy mathematical rigor as it questions the most significant and impossible attempt to make a scale-invariant phenomenology between general relativity and quantum theory. Thus, steps have been taken to simplify the theory a bit thereby making it accessible to general yet enthusiastic readers of physics. However, as there is numerous mathematics involved in the modeling of this theory, thus, any chance to make a purely non-mathematical approach towards strings would prove vacuous and intimidating making the pathway of this marvelous theory chocked with unnecessary assumptions resulting in false analogies (or hopes) relating to this theory. Thus, where it’s almost impossible to proceed without any equations, we have given a few just to wipe out some logical confusion arising to the first readers of strings. Few necessary diagrams are included along with intense theory and least mathematics for making this significant approach of theoretical physicists accessible to general learners or readers. Topics: Bosonic string theory, supersymmetric string theory, M – theory, F – theory, dualities and interconnectedness, viability, Randall – Sundrum model for tackling the hierarchy problem of particle physics, conifold singularities, Branes, Bulks, Extremal black holes, Ekpyrotic cosmology, topological aspects of Calabi – Yau (CY) manifolds, A and B models, Mirror Symmetries; AdS/CFT, cosmic strings, all in a way accessible to every reader. Methods: Theoretical analogies, deductions, principles behind the origin, development along with the probable conclusion of this theory, the roots of its origin, the necessary difficulty for detecting those strings, and approaches done by theorists to work out the pathway of achieving Einstein’s dream of unification irrespective of several hindrances. Results: String theory itself is not a complete theory. Rather it’s in the process of further development through the increment of time resulting in more applications of mathematics by developing or incorporating them in due needs. Thus, without stating any concrete results, the theory has been tackled in this paper with a viable hypothesis based on the current understanding, and previous attempts are stated to have been made for its success.
nanomaterials, and the use of computational modeling to collect microscopic information of nano-oxide materials. The amazing thing revealed in the discussion in each chapter of the book is the discovery of new properties frommetal oxides when they turn into nanomaterials as it changes in properties or unusual crystal structures that produce amazing functions. Synthesized metal oxides sometimes have some drawbacks such as the lack of stability of a material when it undergoes a phase transition. So research emerged that then decided to couple metal oxides with carbon nanotubes (CNT) with a hybrid system design to produce controlled nanostructures. Chapters 7 to 13 also impressed us because they presented various applications of nanomaterials in life, such as for NO (Nitrogen Oxides) removal, air and water cleaning, CO2 reduction, photoelectrochemical fuel production, electrochemical energy storage, and gas-sensing. It reveals that nanomaterial is one of the great discoveries to make this world better. This complete and complex material on the basics of nanomaterials and their applications can be a very useful reading resource for readers. The preface of this book presents us with an overview of the contents of the entire book as well as the key features contained. Hence, readers can easily find out the topic of discussion before reading the entire book. The part that we like about this book is that each chapter always begins with an introduction by mentioning existing phenomena and problems so that readers can find out firsthand the reasons for studying and using nanomaterials. Research from previous to recent research is also explained in each chapter so that readers get clear information about improvements in the synthesis, methods, and application of nanomaterials from time to time. Researchers who are interested in developing it for the better will be able to get a clear picture of the shortcomings of previous research and get an idea of which aspects of this nanomaterial need improvement. We are very impressed with this book because the material is presented in a clear, detailed, and well-structured manner. How each author explains the synthesis, method, and application of nanomaterials is very easy to understand. Each chapter also presents curves, graphs, pictures, and tables that can help readers understand the results of the research that has been done. However, unfortunately, for general readers or non-expert readers, it will be difficult to understand the pictures coupledwith themany terms commonly used in the fields of physics and chemistry. We strongly recommend this book as the best resource for students at the advanced undergraduate and graduate level, specifically in fields related to physics, chemistry, natural science, and environmental development, as well as researchers who have an interest in nanomaterial research, environmental research, chemical-physics, or similar. The authors have successfully presented this comprehensive book through their great explanation. We are convinced that this book will get full consideration as their ultimate resource among the intended readers. Nonetheless, someone who does not have the basic science knowledge may be quite hard-pushed to understand this book. Acknowledgements
A recent example of successful technology transition from high energy physics to practical engineering applications is cosmic ray muon tomography. Cosmic ray muon tomography, is a promising non-destructive technique that has been recently utilized to monitor or image the contents of dense or well shielded objects, typically not feasible with conventional radiography techniques, e.g., x-ray or neutron. Cosmic ray muon tomography has been used with various levels of success in spent nuclear fuel monitoring, volcano imaging, and cargo container imaging. Further, knowledge of cosmic ray muon momentum spectrum has the potential to significantly improve and expand the use of a variety of recently developed muon-based radiographic techniques. However, existing muon tomography systems rely only on muon tracking and have no momentum measurement capabilities which reduces the image resolution and requires longer measurement times. A fieldable cosmic ray muon spectrometer with momentum measurement capabilities for use in muon tomography is currently missing. In this paper, we will discuss and explore recent advances in cosmic ray muon computed tomography and spectroscopy and their applications to engineering including a new concept for measuring muon momentum using multiple gaseous Cherenkov radiators. By varying the pressure of multiple gas Cherenkov radiators, a set of muon momentum threshold levels can be selected that are triggered only when the incoming muon momentum exceeds that level. As a result, depending on the incoming muon momentum, none to all Cherenkov radiators can be triggered. By analyzing the signals from each radiator, we can estimate the actual muon momentum.
Digital radio detection of cosmic-ray air showers has emerged as an alternative technique in high-energy astroparticle physics. Estimation of the detection efficiency of cosmic-ray radio arrays is one of the few remaining challenges regarding this technique. To address this problem, we developed a new approach to model the efficiency based on the explicit probabilistic treatment of key elements of the radio technique for air showers: the footprint of the radio signal on ground, the detection of the signal in an individual antenna, and the detection criterion on the level of the entire array. The model allows for estimation of sky regions of full efficiency and can be used to compute the aperture of the array, which is essential to measure the absolute flux of cosmic rays. We also present a semi-analytical method that we apply to the generic model, to calculate the efficiency and aperture with high accuracy and reasonable calculation time. The model in this paper is applied to the Tunka-Rex array as example instrument and validated against Monte Carlo simulations. The validation shows that the model performs well, in particular, in the prediction of regions with full efficiency. It can thus be applied to other antenna arrays to facilitate the measurement of absolute cosmic-ray fluxes and to minimize a selection bias in cosmic-ray studies.