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Functional Magnetic Resonance Imaging of Spatiotemporal Brain Dynamics in Patients with Schizophrenia
No full textBrain connectivity reflects the functional organization of the brain and serves as a critical indicator for evaluating neuropsychiatric disorders and treatment outcomes. Schizophrenia, marked by impaired functional connectivity, presents challenges in identifying and characterizing complex patterns of abnormal brain networks. Auditory hallucinations, a hallmark symptom, involve false perceptions without external stimuli, and cognitive models suggest that multiple processes contribute to their emergence. This study uses resting-state and task-based functional magnetic resonance imaging (fMRI) to assess connectivity in schizophrenia patients and healthy controls, applying CONN imaging software and energy landscape analysis (ELA) to identify disease-related connectivity patterns. The results of the resting-state fMRI show that abnormal energy landscape characteristics are significantly correlated with the severity of auditory and visual perceptual disturbances in schizophrenia. Task-based fMRI supports these findings, revealing reduced connectivity in patients with auditory verbal hallucinations (AVH+) compared to healthy controls, and in AVH+ patients compared to those without hallucinations (AVH-). The study also incorporates large language models (LLM) to examine the relationship between impaired brain connectivity and hallucination generation, proposing that degradation in the generative process corresponds to altered brain networks. These impairments manifest as altered auditory and visual production. By analyzing connectivity in regions of interest (ROI) that differ between patients and controls, the study offers insight into memory storage and retrieval mechanisms. Advanced electrical engineering techniques, including signal processing, computational modeling, and machine learning, underpin the analysis. ELA models dynamic brain states and transitions, quantifies network stability, and identifies biomarkers linked to perceptual disturbances. Hierarchical clustering further helps to classify connectivity patterns. By integrating engineering methodologies with cognitive neuroscience, the study provides new insights into the relationship between functional connectivity and cognitive dysfunction in schizophrenia. The proposed imaging workflow shows promise for identifying biomarkers associated with specific clinical symptoms and may guide future treatment development and understanding of the underlying mechanisms of the disorder
XRISM/Xtend Transient Search (XTS) detected an X-ray flare from TWA 11
No full textAuthors: H. Sugai (Chuo U.), K. Fukushima, Y. Kanemaru, S. Ogawa (JAXA), M. Audard (U. de Geneve), E. Behar (Technion), T. Hakamata (Osaka U.), S. Inoue (Kyoto U.), Y. Ishihara (Chuo U.), C. Kang (Ehime U.), T. Kiyomoto (Saitama U.), T. Kohmura (TUS), H. Kuramoto (Osaka U.), J. Kurashima (U. of Miyazaki), Y. Maeda (JAXA), H. Matsumoto (Osaka U.), T. Matsushima (U. of Miyazaki), A. Miyamoto (Osaka U.), M. Mizumoto (UTEF), K. Mori (U. of Miyazaki), Y. Motogami (Saitama U.), N. Nagashima (Chuo U.), T. Narita (Kyoto U.), M. Nobukawa (NUE), H. Noda (Tohoku U.), K. Pottschmidt (UMBC, NASA GSFC, CRESST), Y. Sakamoto (Tohoku U.), M. Shidatsu (Ehime U.), H. Takahashi (Hiroshima U.), T. Takagi (Ehime U.), S. Takatuska (Osaka U.), R. Takemoto (U. of Miyazaki), Y. Terada (Saitama U.), Y. Terashima (Ehime U.), Y. Tsuboi (Chuo U.), H. Uchida (Kyoto U.), T. Yoneyama (Chuo U.), M. Yoshimoto (Ehime U.)XRISM/Xtend Transient Search (XTS) detected an X-ray flare from an X-ray source XRISM J1236-3952 on 2025-06-22 TT. The source position is determined to be (R.A., Dec.) = (189.005, -39.874), with a systematic error of ∼ 40 arcsec. A plausible counterpart is a Young Stellar Object Candidate TWA 11 (HD 109573). TWA 11 is located ∼ 13 arcsec apart from the position of XRISM J1236-3952 All statistical uncertainties in this report are provided as a 90% confidence level unless stated otherwise.
The flare started at 2025-06-22 at ∼ 04:16 TT. The flare reached its peak on 2025-06-22 at ∼ 05:09. The flare exponentially decayed in 4 × 10³ sec. This source also showed fluctuations in flux within a range of ∼ 10 times during the observation conducted the day before. The peak flux is calculated as 1 × 10⁻¹¹ erg s⁻¹ cm⁻² (0.4 – 10.0 keV). A systematic error of roughly 20% should be added to the statistical error. The corresponding luminosity is 8 × D₇₀ₚ꜀ × 10³⁰ erg s⁻¹ by assuming the distance to XRISM J1236-3952 of D₆₇ₚ꜀.
We derived the above systematic error for the flux by comparing our derived values for the sources detected with XTS in several observations with those for the corresponding X-ray counterparts. We estimated the systematic error for the source position from the separations between the detected sources with the corresponding counterparts in the same field of view.https://www.astronomerstelegram.org/?read=1724
Understanding children’s spirituality: conceptualisations by Chilean in-service early childhood educators
No full textThis study examines how Chilean in-service early childhood educators conceptualise children’s spirituality building on a larger U.S. mixed-methods project. It analyzes the responses of 87 educators to Q7 of the Early Childhood Educator’s Spiritual Practices in the Classroom (ECE-SPC) instrument, utilising NVivo 14 for coding. Three key dimensions of children’s spirituality emerged: Personal, Interpersonal, and Intangible-Immaterial. The Personal Dimension views children’s spirituality as essential and innate, fostering emotional expression, self-awareness, and connection. The Interpersonal Dimension frames it as a learned capacity for relationships shaped by external values. The Intangible-Immaterial Dimension defines children’s spirituality as a connection with the immaterial, encompassing perceptions, feelings, or beliefs in a spiritual being that supports moral growth. These findings underscore a multilayered understanding of spirituality and offer insights for teacher education and professional development. Recognising spirituality as integral to holistic child development encourages educators to incorporate the spiritual domain into early childhood classrooms, fostering inclusive and comprehensive learning environments.This study was completed with funding provided by the Agencia Nacional de Investigacióny Desarrollo of the Ministry of Education of Chile through research project FONDECYT n°[11230211] (2023-2025), awarded to PI Francisco Javier Vargas Herrerahttps://www.tandfonline.com/doi/full/10.1080/1364436X.2025.255996
Towards gridded nighttime aerosol optical thickness retrievals using VIIRS day–night band observations over regions with artificial light sources
No full textUsing observations from the Visible Infrared Imaging Radiometer Suite (VIIRS) day–night band (DNB), we examined the feasibility of developing a gridded nighttime aerosol optical thickness (AOT) data set based on the spatial derivative of measured top-of-atmosphere attenuated upwelling artificial lights at night (ALAN) over the US, Middle East, and Indian Subcontinent regions for 2017. We also studied the potential of using NASA's standard operational Black Marble nighttime lights product suite (VNP46) for estimating the spatial derivatives of surface artificial-light emissions, which is one of the key lower boundary conditions for the retrieval process. The sensitivity of nighttime aerosol retrievals to observing conditions and different methods of estimating the spatial derivative of surface artificial-light emissions were also explored. Root-mean-square errors (RMSEs) of ∼0.15 and ∼0.18 and correlations of ∼0.8 and ∼0.6 were found between VIIRS nighttime AOT and Aerosol Robotic Network (AERONET) nighttime and daytime data, respectively, suggesting that the proposed gridded nighttime AOT retrievals have reasonable skill levels for potential data assimilation, air quality, and climate studies of significant events. We also found that NASA Black Marble products can be used to estimate the spatial derivative of surface artificial-light emissions for nighttime AOT retrievals over regions that are not frequently contaminated by aerosol plumes, such as the USA. This study demonstrated the feasibility of constructing a gridded nighttime AOT data, using artificial lights, for monitoring of nighttime aerosol events over large spatial and temporal domains. Given the deployment of VIIRS instruments (currently in orbit and forthcoming) aboard the NOAA Joint Polar Satellite System (JPSS) series satellites, this study can be viewed as a precursor for gridded nighttime AOT retrievals at both regional and global scales in the future. We also show that the use of the NASA Black Marble products, which would greatly save the processing time of this method, is challenging over regions with frequent aerosol pollution, such as the Indian Subcontinent, and further exploration is required.This research has been supported by the National Aeronautics and Space Administration (grant no. 80NSSC20K1748). Jeffrey S. Reid and Juli I. Rubin were supported by the Office of Naval Research, Code 322. Zhuosen Wang and Miguel O. Román were also supported by NASA's Suomi National Polar-orbiting Partnership (Suomi-NPP) and Joint Polar Satellite System (JPSS) program under grant no. 80NSSC22K0199. Financial support was also provided by the University of North Dakota Chester Fritz Library Open Access Fund.https://amt.copernicus.org/articles/18/1787/2025
Deriving New Two-Dimensional (2D) Layered Materials Using First-Principles Combined with Thermodynamics and Periodic Trends
No full textThe emergence of two-dimensional (2D) layered materials has reshaped the design space for next-generation electronics, energy devices, and low-dimensional quantum systems. While exfoliation of known layered compounds has expanded this library, predictive strategies for discovering entirely new 2D systems remain limited. This dissertation presents a methodology for 2D materials discovery rooted in firstprinciples density functional theory (DFT), thermodynamic analysis, and periodic trends of basic chemical descriptors. At the core of this approach is the integration of electronic structure analysis with additional considerations to guide experimental efforts. The first half of this dissertation discusses how the addition of thermodynamic modeling methods to first-principles can approximate surface reactivity at the solid– liquid interface. This includes both pedagogical and technical contributions to the interpretation of band structure and bonding behavior through projected density of states (PDOS), and the adaptation of the DFT + Solvent Ion Model (DSIM) to study surface transformations under aqueous conditions. These methods are applied to examine how surface chemistry governs exfoliation stability in ABX-type 2D layered materials. A quantitative workflow is developed for evaluating surface exchange reactions and stability under redox-active conditions in layered pnictides, enabling predictions of 2D monolayer formation pathways that are determined using both electronic and thermodynamic descriptors. The second half of this dissertation details the compositional tuning of bulk 2D van der Waals ferroelectrics such as CuInP₂X₆ (X = S, Se), where DFT is used to examine how isovalent substitution at the P and In sites modifies polarization and band gap through bonding asymmetry and lattice flexibility. Cation ordering, host lattice stiffness, and ionic radii/electronegativity mismatches are evaluated to derive design rules linking structural distortion to functional response. Finally, a data-guided study combines structural mining of the Inorganic Crystal Structure Database with quantum structural diagram analysis to identify 83 new quaternary phosphochalcogenides as promising 2D candidates. These compounds are mapped by symmetry type and atomic coordination, allowing the construction of Villars-style design maps to highlight trends in stability and dimensional reduction. These efforts establish a transferable computational strategy for predicting 2D materials beyond known structure types. The findings offer guidance for experimental synthesis, enable structural prediction strategies linked to chemical and electronic descriptors, and contribute to a broader translation of solid-state physics concepts into chemically driven materials discovery
XRISM/Xtend Transient Search (XTS) detected an X-ray flare from High Proper Motion Star UCAC4 661-042690
No full textAuthors: H. Sugai (Chuo U.), K. Fukushima, K. Hayashi, Y. Kanemaru, S. Ogawa, T. Yoshida (JAXA), M. Audard (U. de Geneve), E. Behar (Technion), S. Inoue (Kyoto U.), Y. Ishihara (Chuo U.), T. Kohmura (TUS), Y. Maeda (JAXA), M. Mizumoto (UTEF), N. Nagashima (Chuo U.), M. Nobukawa (NUE), K. Pottschmidt (UMBC, NASA GSFC, CRESST), M. Shidatsu (Ehime U.), Y. Terada (Saitama U.), Y. Terashima (Ehime U.), Y. Tsuboi (Chuo U.), H. Uchida (Kyoto U.), T. Yanagi (Chuo U.), T. Yoneyama (Chuo U.), M. Yoshimoto (Osaka U.)XRISM/Xtend Transient Search (XTS) detected an X-ray flare from an X-ray source XRISM J0604+4209 on 2025-02-23 TT. The source position is determined to be (R.A., Dec.) = (90.974, 42.144), with a systematic error of ∼ 40 arcsec. A plausible counterpart is M2 dwarf high proper motion star UCAC4 661-042690 which corresponds to the X-ray source 4XMM J060352.2+420833. UCAC4 661-042690 is located ∼ 17 arcsec apart from the position of XRISM J0604+4209.
The flare started at 2025-02-23 at ∼ 01:00 with the flux of 7 × 10⁻¹⁴ erg s⁻¹ cm⁻² and reached its peak on 2025-02-23 at ∼ 01:35 with the flux of 4 × 10⁻¹³ erg s⁻¹ cm⁻². The flare exponentially decayed in 3 × 10³ sec. The above fluxes are in the 0.4 – 2.0 keV. The corresponding peak luminosity is 4 × 10²⁹ erg s⁻¹ cm⁻² when we assume the distance to XRISM J0604+4209 of D₉₆ ₚ꜀. We estimated the systematic error for the source position from the separations between the detected sources with the corresponding counterparts in the same field of view.https://www.astronomerstelegram.org/?read=1704
Comparing XRISM cluster velocity dispersions with predictions from cosmological simulations: are feedback models too ejective?
No full textThe dynamics of the intra-cluster medium (ICM), the hot plasma that fills galaxy clusters, are shaped by gravity-driven cluster mergers and feedback from supermassive black holes (SMBH) in the cluster cores. XRISM measurements of ICM velocities in several clusters offer insights into these processes. We compare XRISM measurements for nine galaxy clusters (Virgo, Perseus, Centaurus, Hydra A, PKS\,0745--19, A2029, Coma, A2319, Ophiuchus) with predictions from three state-of-the-art cosmological simulation suites, TNG-Cluster, The Three Hundred Project GADGET-X, and GIZMO-SIMBA, that employ different models of feedback. In cool cores, XRISM reveals systematically lower velocity dispersions than the simulations predict, with all ten measurements below the median simulated values by a factor 1.5-1.7 on average and all falling within the bottom 10% of the predicted distributions. The observed kinetic-to-total pressure ratio is also lower, with a median value of 2.2%, compared to the predicted 5.0-6.5% for the three simulations. Outside the cool cores and in non-cool-core clusters, simulations show better agreement with XRISM measurements, except for the outskirts of the relaxed, cool-core cluster A2029, which exhibits an exceptionally low kinetic pressure support (<1%), with none of the simulated systems in either of the three suites reaching such low levels. The non-cool-core Coma and A2319 exhibit dispersions at the lower end but within the simulated spread. Our comparison suggests that the three numerical models may overestimate the kinetic effects of SMBH feedback in cluster cores. Additional XRISM observations of non-cool-core clusters will clarify if there is a systematic tension in the gravity-dominated regime as well.The findings reported here reflect more than thirty years of work by scientists and engineers who developed an X-ray microcalorimeter array and overcame major setbacks. We thank the entire XRISM team for their work in building, launching, calibrating, and operating the observatory. Our thanks also go to the referee for helpful comments. Part of this work was supported by the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, and by NASA under contracts 80GSFC21M0002 and 80GSFC24M0006 and grants 80NSSC20K0733, 80NSSC18K0978, 80NSSC20K0883, 80NSSC20K0737, 80NSSC23K0646, 80NSSC24K0678, 80NSSC18K1684, 80NSSC23K0650, and 80NNSC22K1922. Support was provided by JSPS KAKENHI grant numbers JP23H00121, JP22H00158, JP23H04899, JP21K13963, JP24K00638, JP24K17105, JP21K13958, JP21H01095, JP23K20850, JP24H00253, JP21K03615, JP24K00677, JP20K14491, JP23H00151, JP19K21884, JP20H01947, JP20KK0071, JP23K20239, JP24K00672, JP24K17104, JP24K17093, JP20K04009, JP21H04493, JP20H01946, JP23K13154, JP19K14762, JP20H05857, JP23K03459, and JP25H00672, the JSPS Core-to-Core Program, JPJSCCA20220002, and the Strategic Research Center of Saitama University. This work has been made possible by the The Three Hundred collaboration. We acknowledge The Red Española de Supercomputación for granting computing time for running the hydrodynamic simulations of The Three Hundred galaxy cluster project in the Marenostrum supercomputer at the Barcelona Supercomputing Center. We would like to thank Arif Babul, Elena Rasia, Thomas Hough, and Annalisa Pillepich for their helpful discussions during the development of this work. SG acknowledges support from NSF award 2233001. LC acknowledges support from NSF award 2205918. CD acknowledges support from STFC through grant ST/T000244/1. LG acknowledges support from Canadian Space Agency grant 18XARMSTMA. NO acknowledges partial support by the Organization for the Promotion of Gender Equality at Nara Women’s University. MS acknowledges support by the RIKEN Pioneering Project Evolution of Matter in the Universe (r-EMU) and Rikkyo University Special Fund for Research (Rikkyo SFR). AT acknowledges support from the Kagoshima University postdoctoral research program (KU-DREAM). SY acknowledges support by the RIKEN SPDR Program. IZ acknowledges partial support from the Alfred P. Sloan Foundation through the Sloan Research Fellowship. DN acknowledges funding from the Deutsche Forschungsgemeinschaft (DFG) through an Emmy Noether Research Group (grant number NE 2441/1-1). CZ was supported by the GACR grant 21- 13491X. S.E. acknowledges the financial contribution from the contracts Prin-MUR 2022 supported by Next Generation EU (M4.C2.1.1, n.20227RNLY3 The concordance cosmological model: stress-tests with galaxy clusters), and from the Bando INAF per la Ricerca Fondamentale 2024 with a Theory Grant on “Constraining the non-thermal pressure in galaxy clusters with high-resolution X-ray spectroscopy” (1.05.24.05.10). WC is supported by Atracción de Talento Contract no. 2020-T1/TIC19882 granted by the Comunidad de Madrid and by the Consolidación Investigadora grant no. CNS2024-154838 granted by the Agencia Estatal de Investigación (AEI) in Spain. He also thanks the Ministerio de Ciencia e Innovación (Spain) for financial support under Project grant PID2021-122603NB-C21, ERC: HORIZONTMA-MSCA-SE for supporting the LACEGAL-III Latin American Chinese European Galaxy Formation Network) project with grant number 101086388, and the science research grants from the China Manned Space Project, CMS-CSST-2025-A04.http://arxiv.org/abs/2510.0632
A Benchmark Dataset for Satellite-Based Estimation and Detection of Rain
No full textAccurately tracking the global distribution and evolution of precipitation is essential for both research and operational meteorology. Satellite observations remain the only means of achieving consistent, global-scale precipitation monitoring. While machine learning has long been applied to satellite-based precipitation retrieval, the absence of a standardized benchmark dataset has hindered fair comparisons between methods and limited progress in algorithm development. To address this gap, the International Precipitation Working Group has developed SatRain, the first AI-ready benchmark dataset for satellite-based detection and estimation of rain, snow, graupel, and hail. SatRain includes multi-sensor satellite observations representative of the major platforms currently used in precipitation remote sensing, paired with high-quality reference estimates from ground-based radars corrected using rain gauge measurements. It offers a standardized evaluation protocol to enable robust and reproducible comparisons across machine learning approaches. In addition to supporting algorithm evaluation, the diversity of sensors and inclusion of time-resolved geostationary observations make SatRain a valuable foundation for developing next-generation AI models to deliver more accurate, detailed, and globally consistent precipitation estimates.The work of Simon Pfreundschuh work has been supported by NASA grant 80NSSC22K0604http://arxiv.org/abs/2509.0881
Spatiotemporal Gap-Filling of NASA Deep Blue Satellite Aerosol Optical Depth Over the Contiguous United States (CONUS) Using the UNet 3+ Architecture
No full textDue to sensor and algorithmic constraints, satellite aerosol optical depth (AOD) retrievals are spatially incomplete and have gaps caused by clouds and bright surfaces. These gaps represent a barrier in characterizing daily aerosol loadings, which is important for air quality applications. In particular, recent studies in aerosol studies have shown satellite AOD to be a useful predictor of particulate matter, but are often limited to monthly or longer temporal resolution because of missing AOD retrievals. In this study, we propose using a UNet 3+ to fill gaps in satellite AOD retrievals. We tested the hypothesis that UNet 3+ trained on deep blue (DB) AOD and supplemental data sets (e.g., Modern-Era Retrospective analysis for Research and Applications, Version 2 reanalysis AOD, meteorological and land-use variables from North American Mesoscale Forecast System, and Hazard Mapping System smoke polygons) will improve the availability of AOD data accurately. We created spatiotemporal data sets of daily, gap-filled DB AOD from 2012 to 2023 over the CONtinental United States (CONUS) at a 12 × 12 km² resolution. We were able to train the model and perform the gap-filling in ∼10 hr, resulting in an increase of AOD data availability by 281%. We demonstrated that our approach is feasible over CONUS through quantitative and qualitative evaluations against AERONET and DB AOD. In statistical evaluations, our gap-filled AOD data set attained an RMSE ∼ 0.09 and a r ∼ 0.87 against collocated AERONET retrievals, compared to an RMSE ∼ 0.11 and a r ∼ 0.86 that the original DB AOD retrievals scored against AERONET. We plan to use this data set for future air quality and health investigations.Funding for H.A. Holmes was supportedby the National Science Foundation (NSF)CAREER Chemical, Bioengineering,Environmental, and Transport Systems(CBET) (2048423) and the NIH NationalInstitute of Environmental Health Sciences(NIEHS) (R01ES029528). The supportand resources from the Center for High?Performance Computing at the Universityof Utah (https://www.chpc.utah.edu) aregratefully acknowledged. The AERONETteam, PIs, and site managers are thankedfor the ongoing generation and stewardshipof these data records. Deep blue retrievalalgorithm development has been supportedthrough multiple NASA ROSES fundingopportunities. This material is partiallybased upon work supported by theNational Aeronautics and SpaceAdministration under Grant80NSSCM0029 issued through OklahomaNASA EPSCoRhttps://agupubs.onlinelibrary.wiley.com/doi/10.1029/2025EA00433
XRISM constraints on unidentified X-ray emission lines, including the 3.5 keV line, in the stacked spectrum of ten galaxy clusters
No full textWe stack 3.75 Megaseconds of early XRISM Resolve observations of ten galaxy clusters to search for unidentified spectral lines in the E = 2.5-15 keV band (rest frame), including the E = 3.5 keVline reported in earlier, low spectral resolution studies of cluster samples. Such an emission line mayoriginate from the decay of the sterile neutrino, a warm dark matter (DM) candidate. No unidentified
lines are detected in our stacked cluster spectrum, with the 3σ upper limit on the mₛ ∼ 7.1 keV DM particle decay rate (which corresponds to a E = 3.55 keV emission line) of Γ ∼ 1.0 × 10⁻²⁷ s⁻¹. This upper limit is 3 − 4 times lower than the one derived by Hitomi Collaboration et al. (2017) from the Perseus observation, but still 5 times higher than the XMM-Newton detection reported by Bulbul et al.(2014) in the stacked cluster sample. XRISM Resolve, with its high spectral resolution but a small field of view, may reach the sensitivity needed to test the XMM-Newton cluster sample detection by combining several years worth of future cluster observations.We thank the referee for the prompt review and helpful comments. We gratefully acknowledge the hard work over many years of all of the engineers and scientists who made the XRISM mission possible. Part of this work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The material is based upon work supported by NASA under award numbers 80GSFC21M0002 and 80GSFC24M0006. This work was supported by JSPS KAKENHI grant numbers JP22H00158, JP22H01268, JP22K03624, JP23H04899, JP21K13963, JP24K00638, JP24K17105, JP21K13958, JP21H01095, JP23K20850, JP24H00253, JP21K03615, JP24K00677, JP20K14491, JP23H00151, JP19K21884, JP20H01947, JP20KK0071, JP23K20239, JP24K00672, JP24K17104, JP24K17093, JP20K04009, JP21H04493, JP20H01946, JP23K13154, JP19K14762, JP20H05857, JP23K03459, and JP25K23398. This work was supported by NASA grant numbers 80NSSC20K0733, 80NSSC18K0978, 80NSSC20K0883, 80NSSC20K0737, 80NSSC24K0678, 80NSSC18K1684, 80NSSC23K0650, and 80NNSC22K1922. LC acknowledges support from NSF award 2205918. CD acknowledges support from STFC through grant ST/T000244/1. LG acknowledges financial support from Canadian Space Agency grant 18XARMSTMA. MS acknowledges the support by the RIKEN Pioneering Project Evolution of Matter in the Universe (r-EMU) and Rikkyo University Special Fund for Research (Rikkyo SFR). AT and the present research are in part supported by the Kagoshima University postdoctoral research program (KU-DREAM). S.U. acknowledges support by Program for Forming Japan’s Peak Research Universities (J-PEAKS). SY acknowledges support by the RIKEN SPDR Program. IZ acknowledges partial support from the Alfred P. Sloan Foundation through the Sloan Research Fellowship. SE acknowledges the financial contribution from the Bando INAF per la Ricerca Fondamentale 2024 with a Theory Grant on “Constraining the non-thermal pressure in galaxy clusters with high-resolution X-ray spectroscopy” (1.05.24.05.10). HRR acknowledges support from an Anne McLaren Fellowship from the University of Nottingham. NW and CZ are supported by the GACR grant 21-13491X. This work was supported by the JSPS Coreto-Core Program, JPJSCCA20220002. The material is based on work supported by the Strategic Research Center of Saitama University.http://arxiv.org/abs/2510.2456