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Resource Efficient Framework for Remote Sensing Visual Recognition
No full textIn the rapidly evolving field of remote sensing (RS), the need for efficient and accurate scene classification is paramount. RS imagery comprising satellite and aerial imagery often faces challenges such as varying scales and diverse environmental conditions, which can significantly affect the discernibility of important features. To address these challenges, this article introduces a light-weight dual-branch network architecture that adequately handles scale variations and complex scene compositions. The first branch, Progressive Feature Processing Branch (PFPB), of the proposed framework is engineered to extract rich multiple scale features through collaborative parallel stages and intra and inter branch connectivity with optimized computational resources. The second branch, InXformer (IXB) enhances the system's capability to assimilate global context and long-range dependencies essential for comprehensive scene analysis utilizing involution-based transformer approach. Experimental validation in three challenging datasets sourced from diverse aerial platforms demonstrates the greater effectiveness of the proposed network. The proposed network achieves a weighted F1 of 97.15% in the AIDERSv2 dataset, surpassing other methods such as DecoupleNet by more than 2%, while maintaining high efficiency with 0.41M parameters, lower computational overhead with 0.96 GFLOPs and a higher processing speed of 4616 FPS. With regards to WHU-RS19 and UCM datasets, the devised network achieves 93.69% and 94.57% weighted-F1 score respectively. These results underscore the ability of the proposed network to efficiently handle diverse scene compositions by delivering state-of-the-art performance. © 2025 Elsevier B.V., All rights reserved.FALSEsciescopu
Photon energy-dependent ultrafast magnetization dynamics in magnetic heterostructures
No full textLaser-induced ultrafast demagnetization has traditionally been understood as a process in which photon absorption excites nonequilibrium electrons, leading to demagnetization followed by magnetization recovery. It has been widely assumed that the time scale of these dynamics is governed primarily by the total absorbed laser power rather than the specific photon energy. In this study, we challenge this assumption by employing spintronic terahertz emission spectroscopy, a technique primarily sensitive to spin transport rather than local magnetization changes. We reveal that the time scales of both demagnetization and recovery systematically vary with laser wavelength. Specifically, magnetization dynamics induced by shorter-wavelength optical pulses evolve over significantly longer time scales than those triggered by longer-wavelength infrared pulses, even at constant absorbed power. Our findings suggest that higher-energy (shorter-wavelength) photons enhance magnon excitation, which drives spin transport across the magnet/nonmagnet interface, thereby modifying the magnetization dynamics. These results highlight the direct influence of photon energy on ultrafast demagnetization, building upon and complementing earlier studies from various perspectives, while also offering new opportunities for optical control of spintronic phenomena.TRUEscopu
AttCORAL: Domain-Adaptive Attention Networks for Early Alzheimers Disease Diagnosis
No full textAlzheimer's disease (AD) is one of the most common neurodegenerative disorders characterized by the progressive accumulation of amyloid-beta plaques and tau protein tangles in the brain. Due to the lack of a cure for Alzheimer's disease, early and accurate diagnosis of AD is crucial for effective early interventions to slow disease progression. Magnetic Resonance Imaging (MRI) has emerged as a promising modality for early diagnosis, providing detailed insights into brain structure alterations associated with AD. However, domain shift due to variations in imaging protocols and data distribution among national cohorts remains a challenge for the application of MRI in clinical diagnosis. To address this issue, we propose AttCORAL, a novel Domain-Adaptive Attention Network for Early Alzheimer's Disease Diagnosis, integrating attention mechanisms with Correlation Alignment (CORAL) loss to effectively mitigate domain discrepancy, enhancing the model's robustness and generalization. We evaluate AttCORAL on two large-scale MRI datasets-Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Australian Imaging, Biomarkers, and Lifestyle Study (AIBL)-which differ in acquisition protocols and demographics. While these datasets provide a valuable basis for cross-cohort validation, we acknowledge that further multi-cohort studies are necessary to fully assess global generalizability. To ensure the reliability of our approach, we apply Grad-CAM to visualize the pathological brain regions most informative for our model's predictions. Experimental results demonstrate that AttCORAL significantly outperforms current state-of-the-art studies, highlighting its effectiveness in early diagnosis of AD across diverse imaging domains.TRUEsciescopu
Inhibition of Structural Degradation in Silicon Anodes of Lithium-Ion Batteries Using a Supramolecular Self-Healing Binders based on a Host-Guest System
No full textSilicon (Si) is a promising anode material for lithium-ion batteries (LIBs) due to its high theoretical capacity. However, it suffers from severe volume expansion during cycling, leading to particle pulverization and unstable solid electrolyte interphase (SEI), which result in rapid capacity fading. Conventional binders such as PVDF and PAA have weak interactions with Si and cannot effectively suppress such degradation. In this study, we propose a novel self-healing polymeric binder based on supramolecular host–guest interactions to address this issue. The dynamic reversible bonds allow the binder to dissipate mechanical stress and autonomously heal cracks formed during cycling. As a result, the Si electrode maintains its structural integrity and electrochemical performance over extended cycles. Our findings demonstrate that supramolecular self-healing binders are a promising strategy for enhancing the durability of Si anodes and advancing high-capacity next-generation LIBs
Higher serum resistin levels and increased frailty risk in older adults: Implications beyond metabolic function
No full textBackground: Despite the pleiotropic role of resistin as an adipokine, its association with frailty—an indicator of biologic age and overall well-being in humans—remains largely unexplored. This study aims to investigate the potential of circulating resistin as a biomarker for frailty. Methods: The study included 228 older adults aged 65 years or older who underwent a comprehensive geriatric assessment. Frailty was evaluated using both the phenotypic frailty model by Fried and the deficit-accumulation frailty index (FI) by Rockwood. Serum resistin levels were measured using a competitive enzyme-linked immunosorbent assay. Results: After adjusting for sex, age, body mass index, smoking, alcohol, exercise, diabetes, and serum creatinine, serum resistin levels were 52.2% higher in individuals with phenotypic frailty than in robust controls (P = 0.001) and showed a positive correlation with the Rockwood FI (P = 0.015). Furthermore, for every 1 standard deviation increase in serum resistin levels, the risk of frailty increased by 67% (P = 0.021). When participants were divided into four groups based on serum resistin levels, individuals in the highest quartile had a 38% higher FI and exhibited a 12.5-fold higher odds ratio for frailty compared to those in the lowest quartile (P = 0.016 and 0.024, respectively). Conclusion: These findings suggest that circulating resistin may serve as a candidate blood-based biomarker for frailty, encompassing the multifaceted physical, cognitive, and social dimensions, extending beyond its well-established role in metabolic regulation. © 2025TRUEsciescopu
Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble results
Get PDFThe international field campaign, GMAP/SIJAQ 2021, was conducted in Korea from October 18th to November 25th to enhance the performance and validation of the Geostationary Environment Monitoring Spectrometer (GEMS) products algorithm and obtain a better understanding of the current air pollution status of the Korean Peninsula. Five chemical transport models (CTMs), including CMAQ, CMAQ-GIST, CAMx, WRF-Chem, and WRF GEOS-Chem, were utilized during the campaign to assist in organizing the observation plan and identifying changes in pollutant concentrations and their spatiotemporal distribution in Korea following the Korea–United States Air Quality (KORUS-AQ) 2016. In this study, we evaluated the forecasting performance, strengths, and limitations of these five CTMs and their ensemble in simulating air quality. Intensive measurement data and intercomparisons were employed to explain discrepancies between observed and simulated results. A comparison of the CTM ensemble results for PM2.5 and various gaseous pollutants between the current GMAP/SIJAQ 2021 and previous KORUS-AQ 2016 campaigns showed the R-value for the total mass PM2.5 concentration increased from 0.88 to 0.94. This improvement is related to CTM updates, including the emission inventory and better reproductions of the concentrations of gaseous species. However, the models consistently underestimated carbon monoxide (CO) concentrations, similar to the results from KORUS-AQ. This finding still suggests a further challenge that requires consideration of missing anthropogenic sources. The results of the ensemble model agreed well with the chemical composition of PM2.5 observed at the intensive monitoring station. However, for NO3− and NH4+, discrepancies were primarily due to inaccuracies in the meteorological inputs, such as precipitation, relative humidity (RH), and nighttime planetary boundary layer height (PBLH) in the CTMs. Hence, all models overestimated the concentration of elemental carbon (EC), therefore, it is necessary to revise EC emissions in the SIJAQv2 inventory, as these apply to unusual levels recorded in Seoul during the reference year of 2018. © 2024 The AuthorsTRUEsciescopu
A superresolution-enhanced spectrometer beyond the Cramer–Rao bound in phase sensitivity
No full textPrecision measurement has been an important research area in sensing and metrology. In classical physics, the Fisher information determines the maximum extractable information from statistically unknown signals, based on a joint probability density function of independently and identically distributed random variables. The Cramer–Rao lower bound (CRLB) indicates the minimum error of the Fisher information, generally known as the shot-noise limit. On the other hand, coherence has pushed the resolution limit further overcoming the diffraction limit using many-wave interference strictly confined to the first-order intensity correlation. However, practical implementation is limited by the lithographic constraints in, e.g., optical gratings. Recently, a coherence technique of superresolution has been introduced to overcome the diffraction limit in phase sensitivity using higher-order intensity correlations of a phase-controlled output field from an interferometer. Here, the superresolution is adopted for precision metrology in an optical spectrometer, whose enhanced frequency resolution is linearly proportional to the intensity-product order, overcoming CRLB. Unlike quantum sensing using entangled photons, this technique is purely classical and offers robust performance against environmental noises, benefiting from the interferometer’s scanning mode for fringe counting. © The Author(s) 2025.TRUEsciescopu
Deciphering Catalyst-Support Interaction via Doping for Highly Active and Durable Oxygen Evolution Catalysis
No full textThe design of oxygen evolution reaction (OER) electrocatalysts demands a delicate balance between activity and stability. In this study, we present a rational design approach that leverages catalyst-support interactions to enhance both the intrinsic activity and durability of Ir-based catalysts. Our study reveals that while Mo doping energetically promotes the formation of high-valent Ir species, enhancing intrinsic catalytic activity, it also leads to a reduction in electrical conductivity. These findings emphasize that supporting doping can introduce both beneficial and limiting effects, highlighting the need for a carefully balanced design strategy to optimize the overall OER performance. Simultaneously, in situ analytical techniques and comparative evaluation reveal the crucial role of oxide supports in stabilizing the catalyst. These findings highlight the pivotal role of interface engineering in maintaining catalyst integrity and the need for support materials that balance dopant-driven electronic promotion with structural and electrochemical robustness. These interconnected degradation pathways highlight the need to move beyond a catalyst-centric view and instead adopt a system-level understanding of the stability. Our approach offers a strong foundation for the rational design and evaluation of high-performance OER electrocatalysts for electrochemical energy applications.FALSEsciescopu
Improving object density determination in coherent diffraction imaging by preprocessing truncated discrete diffraction amplitudes
No full textWe investigated the consequences of discrete Fourier transformation in coherent diffraction imaging (CDI). The object density reconstructed from the discretely sampled diffraction data within a truncated range is inherently aliased, blurred, and further aggravated in phase retrieval process. We devised a preprocessing procedure to correct input Fourier constraints using a convolution kernel and to exclude erroneous Fourier constraints. By applying the proposed preprocessing to both simulated and experimental data, we demonstrated that image reconstruction was substantially improved, effectively suppressing physically unsound fluctuations in the retrieved images. This procedure could improve the fidelity of the quantitative object density retrieved by CDI.FALSEsciescopuskc