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How Potential Federal Cuts to Medicaid and SNAP Could Trigger the Loss of a Million-Plus Jobs, Reduced Economic Activity, and Less State Revenue | Commonwealth Fund
https://www.commonwealthfund.org/publications/issue-briefs/2025/mar/how-cuts-medicaid-snap-could-trigger-job-loss-state-revenue

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Mangled State:
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Spatiotemporal Maps for Dynamic MRI Reconstruction
Rodrigo A. Lobos, Xiaokai Wang, Rex T. L. Fung, Yongli He, David Frey, Dinank Gupta, Zhongming Liu, Jeffrey A. Fessler, Douglas C. Noll
https://arxiv.org/abs/2507.14429

Spatiotemporal Maps for Dynamic MRI Reconstruction
The partially separable functions (PSF) model is commonly adopted in dynamic MRI reconstruction, as is the underlying signal model in many reconstruction methods including the ones relying on low-rank assumptions. Even though the PSF model offers a parsimonious representation of the dynamic MRI signal in several applications, its representation capabilities tend to decrease in scenarios where voxels present different temporal/spectral characteristics at different spatial locations. In this work…

Error Correcting Codes for Segmented Burst-Deletion Channels
Yajuan Liu, Tolga M. Duman
https://arxiv.org/abs/2507.14070 https://arxi…

Error Correcting Codes for Segmented Burst-Deletion Channels
We study segmented burst-deletion channels motivated by the observation that synchronization errors commonly occur in a bursty manner in real-world settings. In this channel model, transmitted sequences are implicitly divided into non-overlapping segments, each of which may experience at most one burst of deletions. In this paper, we develop error correction codes for segmented burst-deletion channels over arbitrary alphabets under the assumption that each segment may contain only one burst of …

A regression-based approach for bidirectional proximal causal inference in the presence of unmeasured confounding
Jiaqi Min, Xueyue Zhang, Shanshan Luo
https://arxiv.org/abs/2507.13965

A regression-based approach for bidirectional proximal causal inference in the presence of unmeasured confounding
Proxy variables are commonly used in causal inference when unmeasured confounding exists. While most existing proximal methods assume a unidirectional causal relationship between two primary variables, many social and biological systems exhibit complex feedback mechanisms that imply bidirectional causality. In this paper, using regression-based models, we extend the proximal framework to identify bidirectional causal effects in the presence of unmeasured confounding. We establish the identifica…

Magnetically Driven Retrograde Precession in Misaligned Black Hole Accretion Flows
Hong-Xuan Jiang, Yosuke Mizuno, Dong Lai, Indu K. Dihingia, Christian M. Fromm
https://arxiv.org/abs/2507.13680

Magnetically Driven Retrograde Precession in Misaligned Black Hole Accretion Flows
Observations of accreting black hole (BH) systems, such as microquasars and supermassive black holes, often reveal a precessing jet with changing directions, indicating a misaligned accretion flow relative to the BH spin. The precession is commonly attributed to the Lense-Thirring (LT) effect, which arises from the BH's rotation twisting the surrounding spacetime and accretion flow. In the strongly magnetized regime, which is preferred accretion flow conditions for M~87$^*$ and likely other jet…

Distributed Acoustic Sensing for Environmental Monitoring, and Newtonian Noise Mitigation:Comparable Sensitivity to Seismometers
Reinhardt Rading, Fracensca Badaracco, Spiridon Beis, Katharina Sophie Isleif, Paul Ophardt, Wanda Vossius, the WAVE Collaboration
https://arxiv.org/abs/2507.13523…

Distributed Acoustic Sensing for Environmental Monitoring, and Newtonian Noise Mitigation:Comparable Sensitivity to Seismometers
Newtonian noise limits the low-frequency sensitivity of ground-based gravitational wave detectors. While seismometers and geophones are commonly employed to monitor ground motion for Newtonian noise cancellation, their limited spatial coverage and high deployment costs hinder scalability. In this study, we demonstrate that distributed acoustic sensing offers a viable and scalable alternative, providing performance comparable to that of conventional seismic instruments. Using data from acoustic …

OrthoInsight: Rib Fracture Diagnosis and Report Generation Based on Multi-Modal Large Models
Ningyong Wu, Jinzhi Wang, Wenhong Zhao, Chenzhan Yu, Zhigang Xiu, Duwei Dai
https://arxiv.org/abs/2507.13993

OrthoInsight: Rib Fracture Diagnosis and Report Generation Based on Multi-Modal Large Models
The growing volume of medical imaging data has increased the need for automated diagnostic tools, especially for musculoskeletal injuries like rib fractures, commonly detected via CT scans. Manual interpretation is time-consuming and error-prone. We propose OrthoInsight, a multi-modal deep learning framework for rib fracture diagnosis and report generation. It integrates a YOLOv9 model for fracture detection, a medical knowledge graph for retrieving clinical context, and a fine-tuned LLaVA lang…

Empirical likelihood meta analysis with publication bias correction under Copas-like selection model
Mengke Li, Yukun Liu, Pengfei Li, Jing Qin
https://arxiv.org/abs/2507.13615

Empirical likelihood meta analysis with publication bias correction under Copas-like selection model
Meta analysis is commonly-used to synthesize multiple results from individual studies. However, its validation is usually threatened by publication bias and between-study heterogeneity, which can be captured by the Copas selection model. Existing inference methods under this model are all based on conditional likelihood and may not be fully efficient. In this paper, we propose a full likelihood approach to meta analysis by integrating the conditional likelihood and a marginal semi-parametric em…

Intellectual Up-streams of Percentage Scale ($ps$) and Percentage Coefficient ($b_p$) -- Effect Size Analysis (Theory Paper 2)
Xinshu Zhao, Qinru Ruby Ju, Piper Liping Liu, Dianshi Moses Li, Luxi Zhang, Jizhou Francis Ye, Song Harris Ao, Ming Milano Li
https://arxiv.org/abs/2507.13695

Intellectual Up-streams of Percentage Scale ($ps$) and Percentage Coefficient ($b_p$) -- Effect Size Analysis (Theory Paper 2)
Percentage thinking, i.e., assessing quantities as parts per hundred, has traveled widely from Roman tax ledgers to modern algorithms. Building on early decimalization by Simon Stevin in La Thiende (1585) and the 19th-century metrication movement that institutionalized base-10 measurement worldwide (Cajori, 1925), this article traces the intellectual trails through which base-10 normalization, especially 0~1 percentage scale. We discuss commonalities between those Wisconsin-Carolina experiments…