Komala Subramanyam Cherukuri, Pranav Abishai Moses, Aisa Sakata
et al.
Oral histories are vital records of lived experience, particularly within communities affected by systemic injustice and historical erasure. Effective and efficient analysis of their oral history archives can promote access and understanding of the oral histories. However, Large-scale analysis of these archives remains limited due to their unstructured format, emotional complexity, and high annotation costs. This paper presents a scalable framework to automate semantic and sentiment annotation for Japanese American Incarceration Oral History. Using LLMs, we construct a high-quality dataset, evaluate multiple models, and test prompt engineering strategies in historically sensitive contexts. Our multiphase approach combines expert annotation, prompt design, and LLM evaluation with ChatGPT, Llama, and Qwen. We labeled 558 sentences from 15 narrators for sentiment and semantic classification, then evaluated zero-shot, few-shot, and RAG strategies. For semantic classification, ChatGPT achieved the highest F1 score (88.71%), followed by Llama (84.99%) and Qwen (83.72%). For sentiment analysis, Llama slightly outperformed Qwen (82.66%) and ChatGPT (82.29%), with all models showing comparable results. The best prompt configurations were used to annotate 92,191 sentences from 1,002 interviews in the JAIOH collection. Our findings show that LLMs can effectively perform semantic and sentiment annotation across large oral history collections when guided by well-designed prompts. This study provides a reusable annotation pipeline and practical guidance for applying LLMs in culturally sensitive archival analysis. By bridging archival ethics with scalable NLP techniques, this work lays the groundwork for responsible use of artificial intelligence in digital humanities and preservation of collective memory. GitHub: https://github.com/kc6699c/LLM4OralHistoryAnalysis.
Considering inflationary magnetogenesis induced by time-dependent kinetic and axial couplings of a massless Abelian vector boson field breaking the conformal invariance we show in this article that, surprisingly, the spectral shape of the large-scale primordial magnetic field power spectrum is insensitive to the post-inflationary history, namely the barotropic parameter ($w$) and the gauge coupling functions of the post-inflationary era.
Shaun de Carvalho, Robert de Mello Koch, Minkyoo Kim
The state space of excited giant graviton brane systems is given by the Gauss graph operators. After restricting to the $su(2|3)$ sector of the theory, we consider this state space. Our main result is the decomposition of this state space into irreducible representations of the $su(2|2)\ltimes\mathbb{R}$ global symmetry. Excitations of the giant graviton branes are charged under a central extension of the global symmetry. The central extension generates gauge transformations so that the action of the central extension vanishes on physical states. Indeed, we explicitly demonstrate that the central charge is set to zero by the Gauss Law of the brane world volume gauge theory.
Git metadata contains rich information for developers to understand the overall context of a large software development project. Thus it can help new developers, managers, and testers understand the history of development without needing to dig into a large pile of unfamiliar source code. However, the current tools for Git visualization are not adequate to analyze and explore the metadata: They focus mainly on improving the usability of Git commands instead of on helping users understand the development history. Furthermore, they do not scale for large and complex Git commit graphs, which can play an important role in understanding the overall development history. In this paper, we present Githru, an interactive visual analytics system that enables developers to effectively understand the context of development history through the interactive exploration of Git metadata. We design an interactive visual encoding idiom to represent a large Git graph in a scalable manner while preserving the topological structures in the Git graph. To enable scalable exploration of a large Git commit graph, we propose novel techniques (graph reconstruction, clustering, and Context-Preserving Squash Merge (CSM) methods) to abstract a large-scale Git commit graph. Based on these Git commit graph abstraction techniques, Githru provides an interactive summary view to help users gain an overview of the development history and a comparison view in which users can compare different clusters of commits. The efficacy of Githru has been demonstrated by case studies with domain experts using real-world, in-house datasets from a large software development team at a major international IT company. A controlled user study with 12 developers comparing Githru to previous tools also confirms the effectiveness of Githru in terms of task completion time.
Maude Wagner, Francine Grodstein, Karen Leffondre
et al.
Long-term behavioral and health risk factors constitute a primary focus of research on the etiology of chronic diseases. Yet, identifying critical time-windows during which risk factors have the strongest impact on disease risk is challenging. To assess the trajectory of association of an exposure history with an outcome, the weighted cumulative exposure index (WCIE) has been proposed, with weights reflecting the relative importance of exposures at different times. However, WCIE is restricted to a complete observed error-free exposure whereas exposures are often measured with intermittent missingness and error. Moreover, it rarely explores exposure history that is very distant from the outcome as usually sought in life-course epidemiology. We extend the WCIE methodology to (i) exposures that are intermittently measured with error, and (ii) contexts where the exposure time-window precedes the outcome time-window using a landmark approach. First, the individual exposure history up to the landmark time is estimated using a mixed model that handles missing data and error in exposure measurement, and the predicted complete error-free exposure history is derived. Then the WCIE methodology is applied to assess the trajectory of association between the predicted exposure history and the health outcome collected after the landmark time. In our context, the health outcome is a longitudinal marker analyzed using a mixed model. A simulation study first demonstrates the correct inference obtained with this approach. Then, applied to the Nurses' Health Study (19,415 women) to investigate the association between BMI history (collected from midlife) and subsequent cognitive decline after age 70. In conclusion, this approach, easy to implement, provides a flexible tool for studying complex dynamic relationships and identifying critical time windows while accounting for exposure measurement errors.
The radius of the L chondrite parent body, its formation time, and its evolution history are determined by fitting theoretical models to empirical data of radioisotopic chronometers for L chondrites. A simplified evolution model for the L chondrite parent body is constructed considering sintering of the initially porous material, temperature dependent heat conductivity, and an insulating regolith layer. Such models are fitted to thermochronological data of five meteorites for which precise data for the Hf-W and U-Pb-Pb thermochronometers have been published. A set of parameters for the L chondrite parent body is found that yields excellent agreement (within error bounds) between a thermal evolution model and thermochonological data. Empirical cooling rate data also agree with the model results within error bounds such that there is no conflict between cooling rate data and the onion-shell model. Two models are found to be compatible with the presently available empirical data: One model with a radius of 115 km and a formation time of 1.89 Ma after CAI formation, another model with 160 km radius and formation time of 1.835 Ma. The central temperature of the smaller body remains well below the Ni,Fe-FeS eutectic melting temperature and is consistent with the apparent non-existence of primitive achondrites related to the L chondrites. For the bigger model incipient melting in the central core region is predicted which opens the possibility that primitive achondrites related to L chondrites could be found.
Galaxy mass assembly is an end product of structure formation in the $Λ$CDM cosmology. As an extension of Lee \& Yi (2013), we investigate the assembly history of stellar components in galaxies as a function of halo environments and stellar mass using semi-analytic approaches. In our fiducial model, halo mass intrinsically determines the formation and assembly of the stellar mass. Overall, the ex situ fraction slowly increases in central galaxies with increasing halo mass but sharply increases for $\log M_{*}/M_{\odot}\gtrsim11$. A similar trend is also found in satellite galaxies, which implies that mergers are essential to build stellar masses above $\log M_{*}/M_{\odot}\sim11$. We also examine the time evolution of the contribution of mass growth channels. Mergers become the primary channel in the mass growth of central galaxies when their host halo mass begins to exceed $\log M_{200}/M_{\odot}\sim13$. However, satellite galaxies seldom reach the merger-dominant phase despite their reduced star formation activities due to environmental effects.
The limitations of demographic models as well as the opportunities of evolutionary models are reviewed. Flaws associated with demographic models include the confounding effects of plant architecture, representation of heterogeneous individuals in populations, and changes in deme membership confounding covariance structure. Trait-based evolutionary models include FoxPatch which represents weedy Setaria spp. seed behavior with explicit life history process prediction rules and algorithms.
Using dynamics, Furstenberg defined the concept of a central subset of positive integers and proved several powerful combinatorial properties of central sets. Later using the algebraic structure of the Stone-Čech compactification, Bergelson and Hindman, with the assistance of B. Weiss, generalized the notion of a central set to any semigroup and extended the most important combinatorial property of central sets to the central sets theorem. Currently the most powerful formulation of the central sets theorem is due to De, Hindman, and Strauss in [3, Corollary 3.10]. However their formulation of the central sets theorem for noncommutative semigroups is, compared to their formulation for commutative semigroups, complicated. In this paper I prove a simpler (but still equally strong) version of the noncommutative central sets theorem in Corollary 3.3.
Mahboubeh Sanaei, Shervin Sahebi, Hamid H. S. Javadi
For a ring endomirphism, we introduce the central skew Armendariz rings, which are a generalization of skew Armendariz rings and central Armendariz rings, and investigate their properties.
J. J. Walmswell, J. J. Eldridge, B. J. Brewer
et al.
We propose a new method to infer the star formation histories of resolved stellar populations. With photometry one may plot observed stars on a colour-magnitude diagram (CMD) and then compare with synthetic CMDs representing different star formation histories. This has been accomplished hitherto by parametrising the model star formation history as a histogram, usually with the bin widths set by fixed increases in the logarithm of time. A best fit is then found with maximum likelihood methods and we consider the different means by which a likelihood can be calculated. We then apply Bayesian methods by parametrising the star formation history as an unknown number of Gaussian bursts with unknown parameters. This parametrisation automatically provides a smooth function of time. A Reversal Jump Markov Chain Monte Carlo method is then used to find both the most appropriate number of Gaussians, thus avoiding avoid overfitting, and the posterior probability distribution of the star formation rate. We apply our method to artificial populations and to observed data. We discuss the other advantages of the method: direct comparison of different parametrisations and the ability to calculate the probability that a given star is from a given Gaussian. This allows the investigation of possible sub-populations.
Motivated by the advances of quantum Darwinism and recognizing the role played by redundancy in identifying the small subset of quantum states with resilience characteristic of objective classical reality, we explore the implications of redundant records for consistent histories. The consistent histories formalism is a tool for describing sequences of events taking place in an evolving closed quantum system. A set of histories is consistent when one can reason about them using Boolean logic, i.e., when probabilities of sequences of events that define histories are additive. However, the vast majority of the sets of histories that are merely consistent are flagrantly non-classical in other respects. This embarras de richesses (known as the set selection problem) suggests that one must go beyond consistency to identify how the classical past arises in our quantum Universe. The key intuition we follow is that the records of events that define the familiar objective past are inscribed in many distinct systems, e.g., subsystems of the environment, and are accessible locally in space and time to observers. We identify histories that are not just consistent but redundantly consistent using the partial-trace condition introduced by Finkelstein as a bridge between histories and decoherence. The existence of redundant records is a sufficient condition for redundant consistency. It selects, from the multitude of the alternative sets of consistent histories, a small subset endowed with redundant records characteristic of the objective classical past. The information about an objective history of the past is then simultaneously within reach of many, who can independently reconstruct it and arrive at compatible conclusions in the present.