1T'-transition metal dichalcogenide monolayers stabilized on 4H-Au nanowires for ultrasensitive SERS detection.

Unconventional 1T'-phase transition metal dichalcogenides (TMDs) have aroused tremendous research interest due to their unique phase-dependent physicochemical properties and applications. However, due to the metastable nature of 1T'-TMDs, the controlled synthesis of 1T'-TMD monolayers (MLs) with high phase purity and stability still remains a challenge. Here we report that 4H-Au nanowires (NWs), when used as templates, can induce the quasi-epitaxial growth of high-phase-purity and stable 1T'-TMD MLs, including WS2, WSe2, MoS2 and MoSe2, via a facile and rapid wet-chemical method. The as-synthesized 4H-Au@1T'-TMD core-shell NWs can be used for ultrasensitive surface-enhanced Raman scattering (SERS) detection. For instance, the 4H-Au@1T'-WS2 NWs have achieved attomole-level SERS detections of Rhodamine 6G and a variety of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike proteins. This work provides insights into the preparation of high-phase-purity and stable 1T'-TMD MLs on metal substrates or templates, showing great potential in various promising applications.

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup.

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

Characteristic Plasmon Energies for 2D In2Se3 Phase Identification at Nanoscale.

Two-dimensional (2D) materials with competing polymorphs offer remarkable potential to switch the associated 2D functionalities for novel device applications. Probing their phase transition and competition mechanisms requires nanoscale characterization techniques that can sensitively detect the nucleation of secondary phases down to single-layer thickness. Here we demonstrate nanoscale phase identification on 2D In2Se3 polymorphs, utilizing their distinct plasmon energies that can be distinguished by electron energy-loss spectroscopy (EELS). The characteristic plasmon energies of In2Se3 polymorphs have been validated by first-principles calculations, and also been successfully applied to reveal phase transitions using in situ EELS. Correlating with in situ X-ray diffraction, we further derive a subtle difference in the valence electron density of In2Se3 polymorphs, consistent with their disparate electronic properties. The nanometer resolution and independence of orientation make plasmon-energy mapping a versatile technique for nanoscale phase identification on 2D materials.

Orbital-Selectivity-Induced Robust Quantum Anomalous Hall Effect in Hund's Metals MgFeP.

Ferromagnetic (FM) states with high Curie temperatures (Tc) and strong spin-orbit coupling (SOC) are indispensable for the long-sought room-temperature quantum anomalous Hall (QAH) effects. Here, we propose a two-dimensional (2D) iron-based monolayer MgFeP that exhibits a notably high FM Tc (about 1525 K) along with exceptional structural stabilities. The unique multiorbital nature in MgFeP, where localized dx2-y2 and dxz/yz orbitals coexist with itinerant dxy and dz2 orbitals, renders the monolayer a Hund's metal and in an orbital-selective Mott phase (OSMP). This OSMP triggers an FM double exchange mechanism, rationalizing the high Tc in the Hund's metal. This material transitions to a QAH insulator upon consideration of the SOC effect. By leveraging orbital selectivity, the QAH band gap can be enlarged by more than two times (to 137 meV). Our findings showcase Hund's metals as a promising material platform for realizing high-performance quantum topological electronic devices.

Imaging Anisotropic Proton Intercalation in Photochromic MoO3.

Protonation represents a fundamental chemical process with promising applications in the fields of energy, environment, and memory devices. Probing the protonation mechanism, however, presents a formidable challenge owing to the elusiveness of intercalated protons. In this work, we utilize the atomic and electronic structure changes associated with protonation to directly image the proton intercalation pathways in α-MoO3 induced by UV illumination. We reveal the anisotropic intercalation behavior which is initiated by photocatalyzed water dissociation preferentially at the (001) edges and then propagates along the c axis, transforming α-MoO3 into HxMoO3 to realize photochromism. This photochromic process can be reversed via heating in air, leading to anisotropic proton deintercalation, also preferentially along the c axis. The observed anisotropic behavior can be attributed to the intrinsically low energy barriers for both proton migration along the c axis and water dissociation/formation at (001) edges.

Happy people are always similar: The evidence from brain morphological and functional inter-subject correlations.

A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics.

Facet-Dependent Surface Restructuring on Nickel (Oxy)hydroxides: A Self-Activation Process for Enhanced Oxygen Evolution Reaction.

Unraveling the catalyst surface structure and behavior during reactions is essential for both mechanistic understanding and performance optimization. Here we report a phenomenon of facet-dependent surface restructuring intrinsic to ß-Ni(OH)2 catalysts during oxygen evolution reaction (OER), discovered by the correlative ex situ and operando characterization. The ex situ study after OER reveals ß-Ni(OH)2 restructuring at the edge facets to form nanoporous Ni1-xO, which is Ni deficient containing Ni3+ species. Operando liquid transmission electron microscopy (TEM) and Raman spectroscopy further identify the active role of the intermediate ß-NiOOH phase in both the OER catalysis and Ni1-xO formation, pinpointing the complete surface restructuring pathway. Such surface restructuring is shown to effectively increase the exposed active sites, accelerate Ni oxidation kinetics, and optimize *OH intermediate bonding energy toward fast OER kinetics, which leads to an extraordinary activity enhancement of ∼16-fold. Facilitated by such a self-activation process, the specially prepared ß-Ni(OH)2 with larger edge facets exhibits a 470-fold current enhancement than that of the benchmark IrO2, demonstrating a promising way to optimize metal-(oxy)hydroxide-based catalysts.

Facet-Controlled Synthesis of Unconventional-Phase Metal Alloys for Highly Efficient Hydrogen Oxidation.

Facet control and phase engineering of metal nanomaterials are both important strategies to regulate their physicochemical properties and improve their applications. However, it is still a challenge to tune the exposed facets of metal nanomaterials with unconventional crystal phases, hindering the exploration of the facet effects on their properties and functions. In this work, by using Pd nanoparticles with unconventional hexagonal close-packed (hcp, 2H type) phase, referred to as 2H-Pd, as seeds, a selective epitaxial growth method is developed to tune the predominant growth directions of secondary materials on 2H-Pd, forming Pd@NiRh nanoplates (NPLs) and nanorods (NRs) with 2H phase, referred to as 2H-Pd@2H-NiRh NPLs and NRs, respectively. The 2H-Pd@2H-NiRh NRs expose more (100)h and (101)h facets on the 2H-NiRh shells compared to the 2H-Pd@2H-NiRh NPLs. Impressively, when used as electrocatalysts toward hydrogen oxidation reaction (HOR), the 2H-Pd@2H-NiRh NRs show superior activity compared to the NiRh alloy with conventional face-centered cubic (fcc) phase (fcc-NiRh) and the 2H-Pd@2H-NiRh NPLs, revealing the crucial role of facet control in enhancing the catalytic performance of unconventional-phase metal nanomaterials. Density functional theory (DFT) calculations further unravel that the excellent HOR activity of 2H-Pd@2H-NiRh NRs can be attributed to the more exposed (100)h and (101)h facets on the 2H-NiRh shells, which possess high electron transfer efficiency, optimized H* binding energy, enhanced OH* binding energy, and a low energy barrier for the rate-determining step during the HOR process.

The computational and neural substrates of individual differences in impulsivity under loss framework.

Numerous neuroimaging studies have identified significant individual variability in intertemporal choice, often attributed to three neural mechanisms: (1) increased reward circuit activity, (2) decreased cognitive control, and (3) prospection ability. These mechanisms that explain impulsivity, however, have been primarily studied in the gain domain. This study extends this investigation to the loss domain. We employed a hierarchical Bayesian drift-diffusion model (DDM) and the inter-subject representational similarity approach (IS-RSA) to investigate the potential computational neural substrates underlying impulsivity in loss domain across two experiments (n = 155). These experiments utilized a revised intertemporal task that independently manipulated the amounts of immediate and delayed-loss options. Behavioral results demonstrated positive correlations between the drift rate, measured by the DDM, and the impulsivity index K in Exp. 1 (n = 97) and were replicated in Exp. 2 (n = 58). Imaging analyses further revealed that the drift rate significantly mediated the relations between brain properties (e.g., prefrontal cortex activations and gray matter volume in the orbitofrontal cortex and precuneus) and K in Exp. 1. IS-RSA analyses indicated that variability in the drift rate also mediated the associations between inter-subject variations in activation patterns and individual differences in K. These findings suggest that individuals with similar impulsivity levels are likely to exhibit similar value processing patterns, providing a potential explanation for individual differences in impulsivity within a loss framework.

Engineered bone marrow mesenchymal stem cell-derived exosomes loaded with miR302 through the cardiomyocyte specific peptide can reduce myocardial ischemia and reperfusion (I/R) injury.

BACKGROUND: MicroRNA (miRNA)-based therapies have shown great potential in myocardial repair following myocardial infarction (MI). MicroRNA-302 (miR302) has been reported to exert a protective effect on MI. However, miRNAs are easily degraded and ineffective in penetrating cells, which limit their clinical applications. Exosomes, which are small bioactive molecules, have been considered as an ideal vehicle for miRNAs delivery due to their cell penetration, low immunogenicity and excellent stability potential. Herein, we explored cardiomyocyte-targeting exosomes as vehicles for delivery of miR302 into cardiomyocyte to potentially treat MI. METHODS: To generate an efficient exosomal delivery system that can target cardiomyocytes, we engineered exosomes with cardiomyocyte specific peptide (CMP, WLSEAGPVVTVRALRGTGSW). Afterwards, the engineered exosomes were characterized and identified using transmission electron microscope (TEM) and Nanoparticle Tracking Analysis (NTA). Later on, the miR302 mimics were loaded into the engineered exosomes via electroporation technique. Subsequently, the effect of the engineered exosomes on myocardial ischemia and reperfusion (I/R) injury was evaluated in vitro and in vivo, including MTT, ELISA, real-time quantitative polymerase chain reaction (PCR), western blot, TUNNEL staining, echocardiogram and hematoxylin and eosin (HE) staining. RESULTS: Results of in vitro experimentation showed that DSPE-PEG-CMP-EXO could be more efficiently internalized by H9C2 cells than unmodified exosomes (blank-exosomes). Importantly, compared with the DSPE-PEG-CMP-EXO group, DSPE-PEG-CMP-miR302-EXO significantly upregulated the expression of miR302, while exosomes loaded with miR302 could enhance proliferation of H9C2 cells. Western blot results showed that the DSPE-PEG-CMP-miR302-EXO significantly increased the protein level of Ki67 and Yap, which suggests that DSPE-PEG-CMP-miR302-EXO enhanced the activity of Yap, the principal downstream effector of Hippo pathway. In vivo, DSPE-PEG-CMP-miR302-EXO improved cardiac function, attenuated myocardial apoptosis and inflammatory response, as well as reduced infarct size significantly. CONCLUSION: In conclusion, our findings suggest that CMP-engineered exosomes loaded with miR302 was internalized by H9C2 cells, an in vitro model for cardiomyocytes coupled with potential enhancement of the therapeutic effects on myocardial I/R injury.

FURION: modeling of FEL pulses propagation in dispersive soft X-ray beamline systems.

Modern X-ray free-electron lasers (XFELs) can generate pulses with durations ranging from femtoseconds to attoseconds. The numerical evaluation of ultra-short XFEL pulses through beamline systems is a critical process of beamline system design. However, the bandwidth of such ultra-short XFEL pulses is often non-negligible, and the propagation cannot be simply approximated using the central wavelength, especially in dispersive beamline systems. We developed a numerical model which is called Fourier optics based Ultrashort x-Ray pulse propagatION tool (FURION). This model can not only be used to simulate dispersive beamline systems but also to evaluate non-dispersive beamline systems. The FURION model utilizes Fresnel integral and angular spectrum integral to perform ultra-short XFEL pulse propagation in free space. We also present the method for XFEL pulse propagation through different types of dispersive gratings, which are commonly used in soft X-ray beamline systems. By using FURION, a start-to-end simulation of the FEL-1 beamline system at Shenzhen superconducting soft X-ray free electron laser (S3FEL) is carried out. This model can also be used to evaluate gratings-based spectrometers, beam splitters, pulse compressors, and pulse stretchers. This work provides valuable insights into the start-to-end simulation of X-ray beamline systems.

Solvent-regulated self-assembled carbon nitride for photocatalytic reduction of U(VI) in water.

Manufacturing high-performance and reusable materials from radioactive uranium-containing wastewater remains a significant challenge. Herein, a supramolecular self-assembly strategy was proposed, using melamine and cyanuric acid as precursors and using intermolecular hydrogen bond force to form carbon nitride (CN-D) in different solvents through a single thermal polymerization strategy. Supramolecular self-assembly method is a promising strategy to synthesize a novel carbon nitride with molecular regulatory properties. In addition, 98% of U(VI) in wastewater can be removed by using CN-D for 60 min under visible light. After five cycles of recycling, more than 95% of U(VI) can still be reduced, indicating that it has good recyclability and reusability. This study not only provides an efficient photocatalytic method of uranium reduction, but also provides a new method for self-assembly synthesis.

Serum alpha 1 antitrypsin potent act as an early diagnostic biomarker for cardiac amyloidosis.

Cardiac amyloidosis is a refractory cardiomyopathy with a poor prognosis and lacks effective treatments. N-terminal pro-brain natriuretic peptide (NT-proBNP) and troponin T are poor prognostic factors for myocardial amyloidosis. However, NT-proBNP and troponin also serve as markers of heart failure and myocardial infarction, lacking specificity. Whether abnormal elevation of alpha-1 antitrypsin in myocardial amyloidosis also predicts the poor prognosis of patients remains unknown. We conducted a retrospective single-center case-control study to analyze the serological and physical examination data of 83 cardiac amyloidosis patients and 68 healthy controls matched by gender and age. We aimed to explore the onset and prognostic factors of cardiac amyloidosis. The serum alpha-1 antitrypsin level (169.78 ± 39.59 mg/dl) in patients with cardiac amyloidosis was significantly higher than that in the normal control (125.92 ± 18.26 mg/dl). Logistic regression results showed that alpha-1 antitrypsin, free sialic acid, high-density lipoprotein cholesterol, apolipoprotein A/B ratio, and homocysteine were predictors of cardiac amyloidosis. Multivariable logistic regression showed that only alpha 1 antitrypsin was an independent risk factor for cardiac amyloidosis. Receiver operating characteristic curve analysis based on the Mayo stage and troponin level showed the cut-off value of 140.55 mg/dl for alpha-1 antitrypsin in predicting cardiac amyloidosis with 81.7% sensitivity and 83.9% specificity. Elevated alpha-1 antitrypsin levels may be an early diagnostic biomarker for cardiac amyloidosis.

Exploring the mechanism of dendrobine in treating metabolic associated fatty liver disease based on network pharmacology and experimental validation.

BACKGROUND: This study investigates the therapeutic mechanisms of dendrobine, a primary bioactive compound in Dendrobium nobile, for Metabolic Associated Fatty Liver Disease (MASLD) management. Utilizing network pharmacology combined with experimental validation, the clinical effectiveness of dendrobine in MASLD treatment was assessed and analyzed. RESULTS: The study demonstrates significant improvement in liver function among MASLD patients treated with Dendrobium nobile. Network pharmacology identified key targets such as Peroxisome Proliferator-Activated Receptor Gamma (PPARG), Interleukin 6 (IL6), Tumor Necrosis Factor (TNF), Interleukin 1 Beta (IL1B), and AKT Serine/Threonine Kinase 1 (AKT1), with molecular docking confirming their interactions. Additionally, dendrobine significantly reduced ALT and AST levels in palmitic acid-treated HepG2 cells, indicating hepatoprotective properties and amelioration of oxidative stress through decreased Malondialdehyde (MDA) levels and increased Superoxide Dismutase (SOD) levels. CONCLUSION: Dendrobine mitigates liver damage in MASLD through modulating inflammatory and immune responses and affecting lipid metabolism, potentially by downregulating inflammatory mediators like TNF, IL6, IL1B, and inhibiting AKT1 and Signal Transducer and Activator of Transcription 3 (STAT3). This study provides a theoretical basis for the application of dendrobine in MASLD treatment, highlighting its potential as a therapeutic agent.

Consequences of Exposure to Famine Exposure on the Later Life eGFR Decline Among Survivors of the Great Chinese Famine: A Retrospective Study.

OBJECTIVES: Chronic kidney disease (CKD) significantly contributes to the socio-economic burden both in China and worldwide. Previous research has shown that experiencing childhood famine is linked to various chronic conditions like diabetes, hypertension, and proteinuria. However, the long-term effects of early-life famine exposure on adult kidney function remain unclear. This study investigates whether exposure to the Chinese Great Famine (1959-1962) is associated with a decline in glomerular filtration rate (GFR) later in life. DESIGN AND METHODS: China Health and Retirement Longitudinal Study is a population-based observational study. We analyzed data from 8,828 participants in the 2011-2012 baseline survey, updated in 2014. Participants were categorized based on their birth year into fetal-exposed (1959-1962), childhood-exposed (1949-1958), adolescence/adult-exposed (1912-1948), and nonexposed (1963-1989) groups. The estimated GFR (eGFR) was calculated using the CKD-EPI-Cr-Cys equation (2021), with CKD defined as an eGFR below 60 mL/min/1.73 m2. RESULTS: Average eGFR values were 103.0, 96.8, 91.2, and 76.3 mL/min/1.73 m2 for the fetal-exposed, childhood-exposed, adolescence/adult-exposed, and nonexposed groups, respectively. The eGFR in the exposed groups was significantly lower compared to the nonexposed group. Specifically, famine exposure correlated with a lower eGFR (coefficient estimates [CE] -9.14, 95% confidence interval [CI] -9.46, -8.82), with the strongest association observed in the adolescence/adult-exposed group (CE -26.74, 95% CI -27.75, -25.74). Adjusting for variables such as demographics, physical and laboratory tests, complications, and personal habits like smoking and drinking did not qualitatively alter this association (CE -1.38, 95% CI -1.72, -1.04). Further stratification by sex, body mass index, alcohol consumption history, hypertension, diabetes, Center for Epidemiologic Studies Depression score, and education level showed that the association remained consistent. CONCLUSIONS: Exposure to famine during different life stages can have enduring effects on GFR decline in humans.

Enhancing Sun-Dried Kelp Detection: Introducing K-YOLO, a Lightweight Model with Improved Precision and Recall.

Kelp, often referred to as a "sea vegetable", holds substantial economic significance. Currently, the drying process for kelp in China primarily relies on outdoor sun-drying methods. Detecting kelp in the field presents challenges arising from issues such as overlapping and obstruction. To address these challenges, this study introduces a lightweight model, K-YOLOv5, specifically designed for the precise detection of sun-dried kelp. YOLOv5-n serves as the base model, with several enhancements implemented in this study: the addition of a detection head incorporating an upsampling layer and a convolution module to improve the recognition of small objects; the integration of an enhanced I-CBAM attention mechanism, focusing on key features to enhance the detection accuracy; the replacement of the CBS module in the neck network with GSConv to reduce the computational burden and accelerate the inference speed; and the optimization of the IoU algorithm to improve the identification of overlapping kelp. Utilizing drone-captured images of sun-dried kelp, a dataset comprising 2190 images is curated. Validation on this self-constructed dataset indicates that the improved K-YOLOv5 model significantly enhances the detection accuracy, achieving 88% precision and 78.4% recall. These values represent 6.8% and 8.6% improvements over the original model, respectively, meeting the requirements for the real-time recognition of sun-dried kelp.

Electromagnetic Short-Term to Imminent Forecast Indices for M ≥ 5.5 Earthquakes in the Gansu-Qinghai-Sichuan Region of China.

Electromagnetic indices play a potential role in the forecast of short-term to imminent M ≥ 5.5 earthquakes and have good application prospects. However, despite possible progress in earthquake forecasting, concerns remain because it is difficult to obtain accurate epicenter forecasts based on different forecast indices, and the forecast time span is as large as months in areas with multiple earthquakes. In this study, based on the actual demand for short-term earthquake forecasts in the Gansu-Qinghai-Sichuan region of western China, we refined the construction of earthquake forecast indicators in view of the abundant electromagnetic anomalies before moderate and strong earthquakes. We revealed the advantageous forecast indicators of each method for the three primary earthquake elements (time, epicenter, magnitude) and the spatiotemporal evolution characteristics of the anomalies. The correlations between the magnitude, time, intensity, and electromagnetic anomalies of different M ≥ 5.5 earthquakes indicate that the combination of short-term electromagnetic indices is pivotal in earthquake forecasting.

Refinement of Different Frequency Bands of Geomagnetic Vertical Intensity Polarization Anomalies before M > 5.5 Earthquakes.

Geomagnetic vertical intensity polarization is a method with a clear mechanism, mature processing methods, and a strong ability to extract anomalous information in the quantitative analysis of seismogenic geomagnetic disturbances. The existing analyses of geomagnetic vertical intensity polarization are all based on the 5~100 s frequency band without refinement of the partitioning process. Although many successful results have been obtained, there are still two problems in the process of extracting anomalies: the geomagnetic anomalies that satisfy the determination criteria are still high in occurrence frequency; and the anomalies are distributed over too large an area in space, which leads to difficulties in determining the location of the epicenter. In this study, based on observations from western China, where fluxgate observation points are positioned in areas with frequent, densely distributed medium-strength earthquakes, we refined the frequency bands of geomagnetic vertical intensity polarization, recalculated the spatial and temporal evolution characteristics of geomagnetic disturbances before earthquakes, and improved the crossover frequency anomaly prediction index while promoting the application of the method in earthquake forecasting.

Geomagnetic Disturbances and Pulse Amplitude Anomalies Preceding M > 6 Earthquakes from 2021 to 2022 in Sichuan-Yunnan, China.

Compelling evidence has shown that geomagnetic disturbances in vertical intensity polarization before great earthquakes are promising precursors across diverse rupture conditions. However, the geomagnetic vertical intensity polarization method uses the spectrum of smooth signals, and the anomalous waveforms of seismic electromagnetic radiation, which are basically nonstationary, have not been adequately considered. By combining pulse amplitude analysis and an experimental study of the cumulative frequency of anomalies, we found that the pulse amplitudes before the 2022 Luding M6.8 earthquake show characteristics of multiple synchronous anomalies, with the highest (or higher) values occurring during the analyzed period. Similar synchronous anomalies were observed before the 2021 Yangbi M6.4 earthquake, the 2022 Lushan M6.1 earthquake and the 2022 Malcolm M6.0 earthquake, and these anomalies indicate migration from the periphery toward the epicenters over time. The synchronous changes are in line with the recognition of previous geomagnetic anomalies with characteristics of high values before an earthquake and gradual recovery after the earthquake. Our study suggests that the pulse amplitude is effective for extracting anomalies in geomagnetic vertical intensity polarization, especially in the presence of nonstationary signals when utilizing observations from multiple station arrays. Our findings highlight the importance of incorporating pulse amplitude analysis into earthquake prediction research on geomagnetic disturbances.