Abstract We studied the characteristics of ultra‐low‐frequency (ULF) waves associated with dipolarization in the near‐Earth plasma sheet for substorms and pseudosubstorms, employing superposed epoch analysis of data from the Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft. We find exponential intensification of ULF waves before dipolarization for both substorms and pseudosubstorms, highlighting Pi2 waves' appearance before Pi1 waves. After rapid growth, the high‐frequency portion of the Pi2 waves and the Pi1 waves in a tailward region for pseudosubstorms are notably weaker and decrease faster than those for substorms. These results suggest that instabilities related to high‐frequency Pi2 and Pi1 waves are essential for a full‐fledged substorm and auroral poleward expansion.
Ayan Sar, Tanupriya Choudhury, Sampurna Roy
et al.
Few-shot multispectral object detection remains a formidable challenge in remote sensing, constrained by the scarcity of annotated data across heterogeneous modalities and environmental conditions. Existing transformer-based detectors, while powerful, often exhibit overfitting in low-sample regimes and fail to preserve cross-spectral consistency between visible and infrared channels. To address these limitations, this article presents few-shot spatial–spectral prototype calibration network (Few-SSPC-Net), a spatial–spectral prototype calibration network designed for efficient and adaptive few-shot multispectral object detection. Unlike conventional transformer-driven pipelines, this framework employs a transformer-free dual-branch convolutional architecture—one branch emphasizing spatial semantics and the other spectral correlations—bridged by a Cross-Scale Interaction Module for fine-grained feature alignment across modalities. Central to this framework is the proposed Spatial–Spectral Prototype Calibration Module, which dynamically refines class prototypes through spectral correlation-guided calibration between support and query samples. This mechanism mitigates prototype drift and enhances generalization by enforcing spectral angular consistency within the embedding space. The entire architecture is trained under an episodic meta-learning paradigm, optimizing a joint objective of classification, localization, and spectral calibration regularization. Extensive experiments on benchmark datasets demonstrate that Few-SSPC-Net achieves consistent gains over state-of-the-art few-shot detectors, with up to +4.7% mAP improvement under five-shot settings, while maintaining competitive inference efficiency. The results affirm the positioning of Few-SSPC-Net as a robust framework for multispectral object detection in complex, data-limited remote sensing scenarios.
Abstract The Siwalik Group is a key laboratory for the study of the Neogene environment. The lower unit of the Siwalik Group was deposited in a meandering river system (between ~ 16 and 10 Ma) that changed to braided during the deposition of the Middle Siwalik (at ~ 10 Ma). The vegetation shifted from C3 to C4 in the central Himalaya, Nepal at ~ 7.4 Ma (Surai Khola) and ~ 6.6–5.9 Ma (Bakiya Khola), in contrast to that in the western Himalaya at ~ 8.8–8.6 Ma (Potwar Basin, Pakistan). Additionally, the Indian Summer Monsoon (ISM) was active in the central Himalaya as early as ~ 10.7 Ma, remaining steady until 9.5 Ma, and then decreased by 7.5 Ma, i.e., 0.5 million years later than in the western Himalaya. Not only the uplift of the Himalaya due to the activation of the Main Boundary Thrust, but the rise of the proto-Tibetan Plateau could be a possible reason behind the intensification of the Asian Summer Monsoon (ASM) at ~ 10 Ma. There was an enrichment of δ18O, and a decrease in thickness of the leaching zones, which is most likely associated with the intensification of the monsoon. The rate of weathering and erosion was also higher during 10–8 Ma, coinciding with the rapid sedimentation rate in the Ganga Basin at ~ 10 Ma. Furthermore, geochronological studies indicate that the Tethyan Himalayan and Greater Himalayan sediments were a prominent source of sediments till ~ 10 Ma, while subsequent detritus was sourced from the Lesser Himalaya. However, in the eastern Himalaya, the presence of dominant numbers of the Cretaceous and younger detritus highlights the uneven pattern of Himalayan exhumation. The condition and formation of paleosols in Lower Siwalik in the central Himalaya indicate a decrease in ASM. The present study compares and summarizes the climatic conditions in the western and eastern Himalaya during the Neogene.
Tomohiro Ohuchi, Yuji Higo, Noriyoshi Tsujino
et al.
Abstract Transient creep in olivine aggregates has been studied by stress‐relaxation experiments at pressures of 1.7–3.6 GPa and at temperatures of ≤1020 K in a DIA apparatus. Time‐dependent deformation of olivine at small strains (<0.07) was monitored with an ∼1 s of time resolution using a combination of a high‐flux synchrotron X‐ray and a cadmium telluride imaging detector. The observed deformation was found to follow the Burgers creep function with the transient relaxation time ranging from 50 (±20) to 1,880 (±750) s. We show that the Burgers creep for olivine cannot account for the low viscosities in early post‐seismic deformation reported by geodetic observations (<7 × 1017 Pa·s). In contrast, the time‐dependent increase in viscosity observed in late post‐seismic deformation (1018−1020 Pa·s) is explained by the Burgers rheology, suggesting that the combination of the Burgers model and another model is needed for the interpretation of post‐seismic deformation.
Semantic segmentation models experience a significant performance degradation due to domain shifts between the source and target domains. This issue is particularly prevalent in remote sensing imagery, where a semantic segmentation model trained on images from one satellite is tested on images from another. Previous research has often overlooked the role of data augmentation in enhancing a model's adaptability to target domains. In contrast, this article proposes a novel self-training framework that incorporates data augmentation at both the input and feature levels, yielding excellent results. Specifically, we introduce a regularized online self-training framework that effectively addresses the challenges of overconfidence and class imbalance inherent in self-training. Based on this framework, we implement two robust data augmentation strategies at the input and feature levels to facilitate the learning of cross-domain invariant knowledge. At the input level, we employ a large-scale domain mixing strategy, termed multidomain mixing, to enhance the model's generalization capability. At the feature level, we introduce masked feature augmentation, a masking-based perturbation technique applied to the semantic features of the target domain. This approach enhances the consistency of teacher–student network predictions in the target domain feature space, thereby improving the robustness of the model's recognition of target domain features. The integration of the proposed self-training framework with dual-level data augmentation culminates in our innovative self-training-based dual-level data augmentation (STDA) method. Extensive experimental results on the ISPRS semantic segmentation benchmark demonstrate that STDA outperforms existing state-of-the-art methods, showcasing its effectiveness.
Jennifer Günther, Dejan Prelević, Dieter F. Mertz
et al.
Abstract The origin of Italian kamafugites and lamproites is a matter of debate, not least due to their “crustal signature” displayed by trace element compositions and isotopic ratios, but also due to puzzling geodynamic significance. We combine in situ EMPA and LA‐ICP‐MS analyses with in situ analyses of oxygen isotopes (SIMS) on olivine from the Pleistocene San Venanzo kamafugites and Torre Alfina lamproites. Lamproitic olivine shows extremely high Mg# and Ni concentrations whereas Ca and Mn concentrations are low. Their δ18OV‐SMOW values are very high up to +11.5 ‰. In kamafugites we recognize three genetically different olivine groups: (a) phenocrystic one with high Mg#, very low Ni, high Ca and Mn. Values of δ18OV‐SMOW are up to +10.9 ‰; (b) melt‐related xenocrystic grains that compositionally resemble lamproitic olivine; (c) skarn‐related almost pure forsterite of extreme δ18OV‐SMOW ∼27 ‰, with negligible amounts of minor and trace elements. The melting and crystallization conditions of Italian kamafugites and lamproites indicate compositionally heterogeneous mantle sources on very small scales. Distinct geochemical features of the olivine macrocryst populations observed in kamafugite point to a range of processes occurring both within the magma storage and transport system. We suggest that the diversity of metasomatic agents was involved in mantle processes on local scales, coupled with magma mixing and/or the uptake of xenocrysts during magma ascend.
This study presents a highly accurate range and Doppler-velocity extraction scheme for millimeter-wave (MMW) short-range sensing using the Doppler-velocity and <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>-space decomposition in a weighted kernel density (WKD) scheme. The WKD method has been developed as one of the most promising micro-Doppler analysis methods for human motion; however, an original WKD method requires a highly decomposed range profile to achieve its maximum performance. As the main contribution of this article, the proposed method introduces the Doppler velocity and k-space decomposition via the 4-D fast Fourier-transform process, which significantly improves the range resolution and reduces computational complexity. The numerical and experimental results show that the proposed method achieves significantly higher range and velocity accuracy and resolution, as well as higher noise-robustness at a lower computational cost.
Hyperspectral anomaly detection (HAD) is an important hyperspectral image application. HAD can find pixels with anomalous spectral signatures compared with their neighbor background without any prior information. While most of the existed researches are related to statistic-based and distance-based techniques, by summarizing the background samples with certain models, and then, finding the very few outliers by various distance metrics, this review focuses on the HAD based on machine learning methods, which have witnessed remarkable progress in the recent years. In particular, these studies can generally be grouped into the traditional machine learning and deep-learning-based methods. Several representative HAD methods, including both traditional machine and deep-learning-based methods, are then conducted on four real HSIs in the experiments. Finally, conclusions regarding HAD are summarized, and prospects and future development direction are discussed.
Representation-based target detectors for hyperspectral imagery have attracted considerable attention in recent years. However, their detection performance is still unsatisfactory due to the independent manner of the recovery process on each test pixel. Moreover, the background dictionary generated through the dual windows is susceptible to target contamination. Aiming to address these issues, in this article, we propose a decomposition model (DM) with background dictionary learning (BDL) for hyperspectral target detection. The observed data are decomposed into three parts: background, target, and noise. The background and target dictionaries are utilized to represent the background and target components, respectively. In order to achieve a satisfactory recovery of the background and target components, the proposed DM exploits the spatial smoothness of background pixels and the scarcity of the targets of interest in the whole scene via the total variation and the sparsity, respectively. Then, the separated target image is directly used for the detection purpose. Furthermore, a novel BDL method based on the locality-constrained linear coding is presented, and a complete and compact background dictionary can be learned with a low computational cost. Meanwhile, the a priori target dictionary is also incorporated into the learning process in order to suppress the contamination of the target signal on the learned background spectra. Extensive experiments on both simulated and real hyperspectral datasets demonstrate the superiority of the proposed detector in comparison with several conventional and state-of-the-art target detectors.
Abstract In this study, we investigate the drivers of observed multi‐decadal fluctuations in Arctic and Antarctic surface temperatures using multiple large ensembles of climate simulations and single‐forcing ensembles. We find that the observed oscillation in Arctic surface temperature around a linear trend since 1920 is a forced response to emissions of anthropogenic aerosols and greenhouse gases. In contrast, we show that observed multi‐decadal Antarctic surface temperature fluctuations are partially related to Pacific decadal variability which influences the climate of West Antarctica. Lastly, we demonstrate that internally driven multi‐decadal fluctuations at the two poles are not systematically correlated in any climate model examined here, as had been previously suggested. We conclude by discussing the implications of these results for understanding projections of Arctic and Antarctic surface climate of the coming decades.
<p>Planetary and gravity waves play an important role in the dynamics of the atmosphere. They are present in the atmospheric distribution of temperature, wind, and ozone content. These waves are detectable also in the vertical profile of ozone and they cause its undulation. One of the structures occurring in the vertical ozone profile is laminae, which are narrow layers of enhanced or depleted ozone concentrations in the vertical ozone profile. They are connected with the total amount of ozone in the atmosphere and with the activity of the planetary and gravity waves. The aim of this paper is to quantify these processes in midlatitudinal Europe. We compare the occurrence of laminae induced by planetary waves (PL) with the occurrence of these induced by gravity waves (GL). We show that the PL are 10–20 times more frequent than that of GL. There is a strong annual variation of PL, while GL exhibit only a very weak variation. With the increasing lamina size the share of GL decreases and the share of PL increases. The vertical profile of lamina occurrence is different for PL and GL smaller than 2 mPa. For laminae greater than 2 mPa this difference is smaller.</p>
B. Rojo-Garibaldi, D. A. Salas-de-León, M. A. Monreal-Gómez
et al.
Hurricanes are complex systems that carry large amounts of energy. Their
impact often produces natural disasters involving the loss of human lives and
materials, such as infrastructure, valued at billions of US dollars. However,
not everything about hurricanes is negative, as hurricanes are the main
source of rainwater for the regions where they develop. This study shows a
nonlinear analysis of the time series of the occurrence of hurricanes in the
Gulf of Mexico and the Caribbean Sea obtained from 1749 to 2012. The
construction of the hurricane time series was carried out based on the
hurricane database of the North Atlantic basin hurricane database (HURDAT)
and the published historical information. The hurricane time series provides
a unique historical record on information about ocean–atmosphere
interactions. The Lyapunov exponent indicated that the system presented
chaotic dynamics, and the spectral analysis and nonlinear analyses of the
time series of the hurricanes showed chaotic edge behavior. One possible
explanation for this chaotic edge is the individual chaotic behavior of
hurricanes, either by category or individually regardless of their category
and their behavior on a regular basis.
Abstract. Cosmic noise at 40 MHz is measured at Ny-Ålesund (79° N, 12° E) using a relative ionospheric opacity meter ("riometer"). A riometer is normally used to determine the degree to which cosmic noise is absorbed by the intervening ionosphere, giving an indication of ionisation of the atmosphere at altitudes lower than generally monitored by other instruments. The usual course is to determine a "quiet-day" variation, this representing the galactic noise signal itself in the absence of absorption; the current signal is then subtracted from this to arrive at absorption expressed in decibels (dB). By a variety of means and assumptions, it is thereafter possible to estimate electron density profiles in the very lowest reaches of the ionosphere. Here however, the entire signal, i.e. including the cosmic noise itself, will be examined and spectral characteristics identified. It will be seen that distinct spectral subranges are evident which can, in turn, be identified with non-Gaussian processes characterised by generalised Hurst exponents, α. Considering all periods greater than 1 h, α ≈ 24, an indication of fractional Brownian motion, whereas for periods greater than 1 day α ≈ 0.9 – approximately pink noise and just in the domain of fractional Gaussian noise. The results are compared with other physical processes, suggesting that absorption of cosmic noise is characterised by a generalised Hurst exponent ≈ 1.24 and thus non-persistent fractional Brownian motion, whereas generation of cosmic noise is characterised by a generalised Hurst exponent ≈ 1. The technique unfortunately did not result in clear physical understanding of the ionospheric phenomena, and thus, in this respect, the application was not successful; the analysis could, however, be used as a tool for instrument validation.
A. J. Komkoua Mbienda, C. Tchawoua, D. A. Vondou
et al.
The modified Mackay (mM), the Grain-Watson (GW), Myrdal and Yalkovsky (MY),
Lee and Kesler (LK), and Ambrose-Walton (AW) methods for estimating vapor pressures () are tested against experimental data for a set of volatile organic compounds (VOC). required to determine gas-particle partitioning of such organic compounds is used as a parameter for simulating the dynamic of atmospheric aerosols. Here, we use the structure-property relationships of VOC to estimate . The accuracy of each of the aforementioned methods is also assessed for each class of compounds (hydrocarbons, monofunctionalized, difunctionalized, and tri- and more functionalized volatile organic species). It is found that the best method for each VOC depends on its functionality.
N. F. Blagoveshchenskaya, H. C. Carlson, V. A. Kornienko
et al.
Multi-instrument observational data from an experiment on
13 October 2006 at the EISCAT/HEATING facility at Tromsø, Norway are
analysed. The experiment was carried out in the evening hours when the
electron density in the F-region dropped, and the HF pump frequency <I>f<sub>H</sub></I>
was near and then above the critical frequency of the F2 layer. The
distinctive feature of this experiment is that the pump frequency was just
below the third electron gyro harmonic frequency, while both the HF pump
beam and UHF radar beam were directed towards the magnetic zenith (MZ). The
HF pump-induced phenomena were diagnosed with several instruments: the
bi-static HF radio scatter on the London-Tromsø-St. Petersburg path,
the CUTLASS radar in Hankasalmi (Finland), the European Incoherent Scatter
(EISCAT) UHF radar at Tromsø and the Tromsø ionosonde (dynasonde). The
results show thermal electron excitation of the HF-induced striations seen
simultaneously from HF bi-static scatter and CUTLASS radar observations,
accompanied by increases of electron temperature when the heater frequency
was near and then above the critical frequency of the F2 layer by up to 0.4 MHz.
An increase of the electron density up to 25% accompanied by strong
HF-induced electron heating was observed, only when the heater frequency was
near the critical frequency and just below the third electron gyro harmonic
frequency. It is concluded that the combined effect of upper hybrid
resonance and gyro resonance at the same altitude gives rise to strong
electron heating, the excitation of striations, HF ray trapping and
extension of HF waves to altitudes where they can excite Langmuir turbulence
and fluxes of electrons accelerated to energies that produce ionization.
Luca Cocchi, Paolo Stefanelli, Fabio Caratori Tontini
et al.
<p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px Times;">We describe a magneto-gradiometric survey performed in the «Mar Piccolo» of Taranto, Italy in May 2005 for</p> <p style="margin: 0.0px 0.0px 0.0px 0.0px; font: 9.0px Times;">environmental purposes. This region, which is a noisy harbour environment, provides a challenging test for magnetic methods. To reduce spurious noise signals, with both temporal and spatial origins, we used two Geometrics G880 model caesium magnetometers towed in a transverse gradient configuration. We show how, in shallow waters, this gradiometric configuration allows us to distinguish anomalies due to small metallic bodies near the seabed from the induced noise due to the anthropic contribution and geomagnetic field variations. A direct visual inspection confirmed that the peculiarities highlighted in the gradient anomaly map were due to abandoned metallic objects found on the seabed.</p> <br />