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The Prime Focus Infrared Microlensing Experiment (PRIME): First Results
No full textWe present the description of the instruments and the first results of the PRime-focus Infrared Microlensing Experiment (PRIME). PRIME is the first dedicated near-infrared (NIR) microlensing survey telescope located at the South African Astronomical Observatory (SAAO) in Sutherland, South Africa. Among its class, it offers one of the widest fields of view in the NIR regime. PRIME's main goals are (1) To study planetary formation by measuring the frequency and mass function of planets. In particular, we compare results from the central Galactic bulge (GB), accessible only in the NIR by PRIME, with those from the outer GB by optical surveys. (2) To conduct concurrent observations with NASA's Nancy Grace Roman Space telescope. Due to the different lines of sight between the ground and space, we detect slight variations in light curves, known as ``Space-based parallax." This effect allows us to measure the mass of lens systems and their distance from the Earth. It is the only method to measure the mass of the free-floating planets down to Earth-mass. We begin the GB survey in February 2024 and analyzed images through June 1, 2025, identifying 486 microlensing candidates and over a thousand variable stars, including Mira variables, which are useful to study the Galactic structure. We issue real-time alerts for follow-up observations, supporting exoplanet searches, and the chemical evolution studies in the GB. During the off-bulge season, we conduct an all-sky grid survey and Target of Opportunity (ToO) observations of transients, including gravitational wave events, gamma-ray bursts, and other science.The PRIME project is supported by JSPS KAKENHI Grant Number JP16H06287, JP22H00153, JP25H00668, JP19KK0082, JP20H04754, JP24H01811 and JPJSCCA20210003. We acknowledge a financial support by Astrobiology Center. M.T. is supported by JSPS KAKENHI grant No.24H00242. DPB acknowledges support from NASA grants 80NSSC20K0886 and 80NSSC18K0793.http://arxiv.org/abs/2508.1447
Loneliness in Resettlement Among Multi-Ethnic Resettled Refugees in Ohio
No full textBackground
This study assessed the prevalence and factors associated with loneliness among five resettled communities in Ohio: Afghan, Bhutanese, Congolese, Ethiopi an/Eritrean, and Somali.
Methods
A cross-sectional online survey of 572 participants was conducted with the help of local community organizations. Loneliness was measured using the three-item UCLA Loneliness Scale and categorized into two groups: “not lonely” and “lonely.” The final analytic sample comprised 458 participants. Binary logistic regression was used to analyze key predictors, including healthcare access, mental and physical health, social support, and resilience.
Results
Of the participants, 29% reported loneliness. Participants with regular access to a doctor were 56% less likely to experience loneliness than those without access [adjusted odds ratio (aOR) = 0.44, 95% CI: 0.29–0.69], while fair/poor self-rated health tripled the experience (aOR = 3.07, 95% CI: 1.42–6.63). Mental health was the strongest predictor, with anxiety increasing the odds of loneliness by over eight times (aOR = 8.43, 95% CI: 4.46–15.93) and depression by more than three times (aOR = 3.53, 95% CI: 1.99–6.26). Experiencing racial discrimination increased the odds of loneliness by 73% (aOR = 1.73, 95% CI: 1.10–2.74). Low resilience quintupled the odds of loneliness (aOR = 5.07, 95% CI: 2.79–9.20), while low social support doubled such odds (aOR = 2.50, 95% CI: 1.04–6.03).
Conclusion
The study found a high prevalence of loneliness among adults in resettled communities, which underscores the need to address physical and mental health, healthcare access, and social support. Especially, it is critical to develop and implement culturally tailored interventions to reduce loneliness and improve the well-being of these communities.This work was supported by the Ohio Department of Mental Health and Addiction Services (Grant number 2300903).https://link.springer.com/article/10.1007/s40615-025-02614-
Internet of Vehicles Security Threats, Countermeasures, Open Challenges With Future Research Directions
No full textInternet of Vehicles (IoV) is growing rapidly with the potential to revolutionize transportation systems. Considering the promising future and potential contributions of IoV’s technology, it has attracted the attention of researchers, industry stakeholders, and potential intruders. However, the IoV’s network topological infrastructure faces several connectivity and communication challenges, along with security issues that are beyond the scope of current literature. Although each aspect and challenge has its own consequences, this work focuses on Physical Layer Security (PhyLaySec) threats, which are the most devastating because they undermine the trust of all stakeholders associated with this technology. In the literature, this topic is bearly focused, which demonstrates that the existing PhyLaySec countermeasures would not be able to counter future security challenges in IoV in terms of vehicle-to-vehicle (V2V) authentication, vehicle-to-infrastructure (V2I) authentication, vehicles-to-everything (V2X) authentication, etc., due to factors such as high vehicle mobility, dynamic network topologies, limited bandwidth, and ultra-fast communication. Therefore, this paper aims to provide a systematic review of state-of-the-art PhyLaySec techniques from 2017 to 2025, with a focus on their strengths and weaknesses. Through our review, we identify key open research questions that require further investigation to enhance the security of IoV’s technologies. Moreover, we highlight potential future research directions that aim to ensure the foolproof security of IoV technology with respect to underlined challenges. Finally, we acknowledge that this is the first paper to comprehensively address the topic of PhyLaySec of IoV technology, which makes it a valuable resource for researchers and professionals working in this field.This research was partially supported by the U.S. National Science Foundation through Grant Nos. 2317117 and 2309760https://ieeexplore.ieee.org/abstract/document/11146540
A Global and Some National Perspectives on the Current Evidence of Interventions on Fruit and Vegetable Intake in Low-, Middle-, and High-Income Countries
No full textAdequate amounts of fruit and vegetables (F&V) are an important part of a healthy diet, yet intake is suboptimal in most population groups worldwide. To better understand the evidence of strategies aiming to improve F&V intake, we conducted a scoping review of interventions assessing the impact on F&V intake, including those aiming to improve F&V intake explicitly and those targeting diet, health, lifestyle, or food environment generally. Among all eligible interventions reviewed, most of which were implemented in high-income countries, about half reported a significant positive impact on fruit and/or vegetable intake. Interventions that used a multicomponent strategy (61%) and those that focused on F&V specifically (72%) were most likely to find a significant increase in fruit and/or vegetable intake. Detailed summaries are provided in 2 accompanying articles. In the present article, we put these findings into perspective. Specifically, we considered the evidence for 4 target countries of the Fruit and Vegetables for Sustainable Healthy Diets Initiative: Benin, the Philippines, Sri Lanka, and Tanzania. When considering available evidence at the national level, there is a paucity of information from intervention trials despite evidence of inadequate F&V intakes in each of these countries. When considering available evidence at the global level, and especially for low-and-middle income countries, there is a critical need to strengthen the evidence across various intervention strategies, particularly related to targeting, timing, intensity, duration, frequency, and other key characteristics, to better understand how to enhance their impact on F&V intake in various population groups and contexts.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: We would like to thank all funders who supported this research through their contributions to the CGIAR Trust Fund: https://www.cgiar.org/funders.https://journals.sagepub.com/doi/10.1177/0379572125135738
Conceptualizing Black Feminist Womanist Gerontology: Applying a Critical Framework for Research on Black Women in Menopause
No full textRecent scholarship has questioned the lack of culturally responsive, theory-guided research addressing the connections between aging, minority communities, and what is needed to advance health equity. Models that utilize traditional theories of aging often do not account for cultural context that undergirds the aging experience, and this is especially the case for older Black women. To understand the ways in which Black women thrive, we must consider various approaches that define their well-being. Dichotomizing aging into concrete categories as healthy/unhealthy may unintentionally isolate this group where aging successfully presents as a contradiction, thus perpetuating further marginalization. It is important that scholarship and intervention projects reflect cultural humility in dissemination. Therefore, we propose Black-Feminist-Womanist Gerontology, a curation of thought that creates a foundation by which Black women survive, live, and age, despite the ‘gold standard’ of aging being dominated by white ethnocentric context that pathologizes older Black women’s lived experiences. In this forum article, we summarize the principles of Black Feminist-Womanist Gerontology, a culturally relevant model for studying Black women’s health as they age. Factors of the model and recommendations of its use will be discussed and applied to the study of Black women in menopause.https://academic.oup.com/gerontologist/advance-article/doi/10.1093/geront/gnaf209/825671
Dust Optical Centroid Height (AOCH) over bright surface: first retrieval from TROPOMI oxygen A and B absorption bands
No full textThe vertical distribution of dust layers can influence dust transport, radiative forcing, deposition and ultimately, surface particulate matter mass concentration. Although many dust layer height (ALH) products from passive satellite measurements have been developed, most of them are applicable on dark surfaces only. Here, building on the absorbing aerosol optical centroid height (AOCH) retrieval from hyperspectral O₂ A and B absorption band measurements of TROPOspheric Monitoring Instrument (TROPOMI) for dark target, we further develop dust AOCH retrieval over bright surfaces. Key updates include: 1) the thresholds in cloud mask tests are refined with consideration of the different spectral characteristics of bright surface reflectance; and 2) the assumption of Lambertian surface is modified to the Ross-Li Bidirectional Reflectance Distribution Function (BRDF) model to consider the angular dependence of surface reflectance. The validation against the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) for several dust plumes over Saharan Desert illustrates that TROPOMI AOCH has ~1 km uncertainty and ~0.1 km mean bias, better than ~1 km underestimated dust layer mean altitude (ALT) from the Infrared Atmospheric Sounder Interferometer (IASI). With this implement of bright surfaces, our algorithm is ready for global retrieval and will be applicable for similar hyperspectral instrument in the future.https://ieeexplore.ieee.org/document/1113113
Towards Closing the Hydroxyl Radical (OH) Budget: Assessing the Feasibility and Uncertainties in Constraining Primary OH Production From Space
No full textRecent progress in constraining the atmosphere’s primary oxidant, the hydroxyl radical (OH), with machine learning (ML) and satellite data raises the intriguing possibility of also constraining individual OH chemical production and loss terms. Here, we present a methodology to constrain primary OH production (i.e., OH production from the reaction of water vapor with O¹D) from 60°S – 60°N at 500m above ground level (magl) (Pₒₕ_500) using a combination of ML, satellite observations, and meteorological data. The aim of this work is to establish methodological feasibility and to assess and quantify the uncertainties of that methodology. This methodology produces geophysically-credible distributions of Pₒₕ_500 across all seasons, with seasonal variability being driven primarily by changes in water vapor and ozone photolysis rates. Regions with quantifiable 1σ uncertainties of 25% or less comprise approximately 68% - 73% of global Pₒₕ_500, suggesting the product is of sufficient quality to inform the relationship between Pₒₕ and trends and variability in OH. The incorporation of additional satellite retrievals into the machine learning model as well as increased spatial and temporal averaging could reduce errors in regions with higher uncertainties, such as those areas with frequent clouds or biomass burning. Ultimately, the results presented here can provide a blueprint to observationally constrain other production and loss terms within the OH budget.This work is part of the FETCH4 project and is supported in part by Schmidt Sciences through the VESRI program. We would like to thank the NASA Goddard Space Flight Center’s Earth Sciences Division for supporting NASA personnel for this effort with Strategic Science funding.https://ntrs.nasa.gov/citations/2025000952
Enhanced self-directed training (ESDT): dynamic data balancing in regression models
No full textSPIE Defense + Commercial Sensing, April 13-17, 2025, Orlando, FloridaEnhanced Self-Directed Training (ESDT) is a novel framework designed to enhance regression-based Multilayer Perceptron (MLP) models through strategic synthetic data augmentation. Unlike traditional methods that rely on random data generation, ESDT focuses on high-loss validation cases, applying Synthetic Data Extension (SDE) techniques, such as SMOTE-based interpolation for continuous data and time-based translation for discontinuous events. This strategy significantly improves model generalization, reduces overfitting, and boosts performance in unbalanced datasets. By tailoring data augmentation efforts to specific areas where the model encounters challenges, ESDT effectively increases data diversity and resilience, ensuring robust predictive modeling across various complex domains. This research establishes ESDT as a robust, adaptive training methodology, promising advancements in scalability and efficiency for future machine learning applications.https://www.spiedigitallibrary.org/conference-proceedings-of-spie/13459/134590J/Enhanced-self-directed-training-ESDT--dynamic-data-balancing-in/10.1117/12.3066302.ful
HAWC, VERITAS, Fermi-LAT and XMM-Newton follow-up observations of the unidentified ultra-high-energy gamma-ray source LHAASO J2108+5157
No full textAuthors at The VERITAS collaboration : C. B. Adams, P. Bangale, W. Benbow, J. H. Buckley, Y. Chen, J. L. Christiansen, A. J. Chromey, M. Escobar Godoy, S. Feldman, Q. Feng, J. Foote, L. Fortson, A. Furniss, W. Hanlon, O. Hervet, C. E. Hinrichs, J. Holder, Z. Hughes, T. B. Humensky, W. Jin, P. Kaaret, M. Kertzman, M. Kherlakian, D. Kieda, T. K. Kleiner, N. Korzoun, S. Kumar, M. J. Lang, M. Lundy, G. Maier, M. J. Millard, P. Moriarty, R. Mukherjee, W. Ning, R. A. Ong, M. Pohl, E. Pueschel, J. Quinn, P. L. Rabinowitz, K. Ragan, P. T. Reynolds, D. Ribeiro, E. Roache, I. Sadeh, L. Saha, G. H. Sembroski, R. Shang, D. Tak, A. K. Talluri, J. V. Tucci, J. Valverde, D. A. Williams, S. L. Wong, and J. Woo.
Authors at The HAWC collaboration: R. Alfaro, C. Alvarez, J.C. Arteaga-Velazquez, D. Avila Rojas, R. Babu, E. Belmont-Moreno, A. Bernal, K.S. Caballero-Mora, A. Carraminana, S. Casanova, U. Cotti, J. Cotzomi, E. De la Fuente, C. de Leon, D. Depaoli, P. Desiati, N. Di Lalla, R. Diaz Hernandez, M.A. DuVernois, K. Engel, T. Ergin, C. Espinoza, K.L. Fan, N. Fraija, S. Fraija, J.A. García-Gonzalez, F. Garfias, A. Gonzalez Munoz, M.M. Gonzalez, J.A. Goodman, S. Groetsch, J.P. Harding, S. Hernandez-Cadena, I. Herzog, D. Huang, F. Hueyotl-Zahuantitla, P. Huntemeyer, A. Iriarte, S. Kaufmann, A. Lara, J. Lee, H. Leon Vargas, A.L. Longinotti, and G. Luis-Raya. K. Malone, O. Martinez, J. Martínez-Castro, J.A. Matthews, P. Miranda-Romagnoli, J.A. Morales-Soto, E. Moreno, M. Araya, M. Mostafá, M. Najafi, A. Nayerhoda, L. Nellen, N. Omodei, E. Ponce, E.G. Pérez-Pérez, C.D. Rho, D. Rosa-Gonzalez, M. Roth, H. Salazar, A. Sandoval, M. Schneider, J. Serna-Franco, A.J. Smith, Y. Son, R.W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Ureña-Mena, E. Varela, L. Villaseñor, X. Wang, Z. Wang, I.J. Watson, H. Wu, S. Yu, S. Yun-Carcamo, and H. Zhou. Authors at The XMM-Newton collaboration: Kaya Mori, Charles J. Hailey, Samar Safi-Harb, and Shuo Zhang.We report observations of the ultra-high-energy gamma-ray source LHAASO J2108+5157, utilizing VERITAS, HAWC, Fermi-LAT, and XMM-Newton. VERITAS has collected ∼ 40 hours of data that we used to set ULs to the emission above 200 GeV. The HAWC data, collected over ∼ 2400 days, reveal emission between 3 and 146 TeV, with a significance of 7.5 σ, favoring an extended source model. The best-fit spectrum measured by HAWC is characterized by a simple power-law with a spectral index of 2.45 ± 0.11ₛₜₐₜ. Fermi-LAT analysis finds a point source with a very soft spectrum in the LHAASO J2108+5157 region, consistent with the 4FGL-DR3 catalog results. The XMM-Newton analysis yields a null detection of the source in the 2 - 7 keV band. The broadband spectrum can be interpreted as a pulsar and a pulsar wind nebula system, where the GeV gamma-ray emission originates from an unidentified pulsar, and the X-ray and TeV emission is attributed to synchrotron radiation and inverse Compton scattering of electrons accelerated within a pulsar wind nebula. In this leptonic scenario, our X-ray upper limit provides a stringent constraint on the magnetic field, which is ≲ 1.5 µG.This research is supported by grants from the U.S. Department of Energy Office of Science, the U.S. National Science Foundation and the Smithsonian Institution, by NSERC in Canada, and by the Helmholtz Association in Germany. This research used resources provided by the Open Science Grid, which is supported by the National Science Foundation and the U.S. Department of Energy’s Office of Science, and resources of the National Energy Research Scientific Computing Center (NERSC), a U.S. Department of Energy Office of Science User Facility operated under Contract No. DE-AC02-05CH11231. We acknowledge the excellent work of the technical support staff at the Fred Lawrence Whipple Observatory and at the collaborating institutions in the construction and operation of the instrument. We acknowledge the support from: the US National Science Foundation (NSF); the US Department of Energy Office of High-Energy Physics; the Laboratory Directed Research and Development (LDRD) program of Los Alamos National Laboratory; Consejo Nacional de Ciencia y Tecnolog´a (CONACyT), M´exico, grants LNC-2023-117, 271051, 232656, 260378, 179588, 254964, 258865, 243290, 132197, A1-S-46288, A1-S22784, CF-2023-I-645, c´atedras 873, 1563, 341, 323, Red HAWC, M´exico; DGAPA-UNAM grants IG101323, IN111716-3, IN111419, IA102019, IN106521, IN114924, IN110521 , IN102223; VIEP-BUAP; PIFI 2012, 2013, PROFOCIE 2014, 2015; the University of Wisconsin Alumni Research Foundation; the Institute of Geophysics, Planetary Physics, and Signatures at Los Alamos National Laboratory; Polish Science Centre grant, 2024/53/B/ST9/02671; Coordinaci´on de la Investigaci´on Cient´fica de la Universidad Michoacana; Royal Society - Newton Advanced Fellowship 180385; Gobierno de Espa˜na and European Union - NextGenerationEU, grant CNS2023- 144099; The Program Management Unit for Human Resources & Institutional Development, Research and Innovation, NXPO (grant number B16F630069); Coordinaci´on General Acad´emica e Innovaci´on (CGAI-UdeG), PRODEP-SEP UDG-CA499; Institute of Cosmic Ray Research (ICRR), University of Tokyo. H.F. acknowledges support by NASA under award number 80GSFC21M0002. C.R. acknowledges support from National Research Foundation of Korea (RS-2023-00280210). We also acknowledge the 11 significant contributions over many years of Stefan Westerhoff, Gaurang Yodh and Arnulfo Zepeda Dom´nguez, all deceased members of the HAWC collaboration. Thanks to Scott Delay, Luciano D´az and Eduardo Murrieta for technical support. The XMM-Newton observation and data analysis are supported by NASA grant XMMNC22.http://arxiv.org/abs/2508.0193
XRISM/Xtend Transient Search (XTS) detected an X-ray flare from a spectroscopic binary
No full textAuthors: 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.), H. Sugai (Chuo 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 J1911+0509, on 2025-03-27 TT. The source position is determined to be (R.A., Dec.) = (287.733, 5.150), with a systematic error of ∼ 40 arcsec. A plausible counterpart is an X-ray source 2E 1908.4+0503, which may correspond to a spectroscopic binary UCAC4 476-091023 at 259 pc. UCAC4 476-091023 is located ∼ 5 arcsec apart from the position of XRISM J1911+0509. All statistical uncertainties in this report will be provided at a 90% confidence level unless stated otherwise.
The flare started around 2025-03-27 at 20:00 TT, peaked on 2025-03-27 at 20:54 TT, and then, exponentially decayed in 2 × 10³ sec, which is derived by fitting the 0.4 – 2.0 keV light curve with a constant + burst model in the QDP software package.
In order to estimate the source flux, we fit the spectrum in the flare phase with an absorbed APEC model with a temperature of kT = 1.3 (+0.4/-0.2) keV and a hydrogen column density NH < 4 × 10²¹ cm⁻². Then, the model flux is calculated as (6.5 +1.5/- 1.3) × 10⁻¹³ erg s⁻¹ cm⁻² (0.4 – 10.0 keV). A systematic error of roughly 20% should be added to the statistical error. Corresponding luminosity is (5.2 +1.2/-1.1) D²₂₅₉ ₚ꜀ × 10³⁰ erg s⁻¹.
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 and their corresponding counterparts in the same field of view.
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