Bioinformatics and Classical Literary Study

This paper describes the Quantitative Criticism Lab, a collaborative initiative between classicists, quantitative biologists, and computer scientists to apply ideas and methods drawn from the sciences to the study of literature. A core goal of the project is the use of computational biology, natural language processing, and machine learning techniques to investigate authorial style, intertextuality, and related phenomena of literary significance. As a case study in our approach, here we review the use of sequence alignment, a common technique in genomics and computational linguistics, to detect intertextuality in Latin literature. Sequence alignment is distinguished by its ability to find inexact verbal similarities, which makes it ideal for identifying phonetic echoes in large corpora of Latin texts. Although especially suited to Latin, sequence alignment in principle can be extended to many other languages

A Complex Hierarchy of Avoidance Behaviors in a Single-Cell Eukaryote.

Complex behavior is associated with animals with nervous systems, but decision-making and learning also occur in non-neural organisms [1], including singly nucleated cells [2-5] and multi-nucleate synctia [6-8]. Ciliates are single-cell eukaryotes, widely dispersed in aquatic habitats [9], with an extensive behavioral repertoire [10-13]. In 1906, Herbert Spencer Jennings [14, 15] described in the sessile ciliate Stentor roeseli a hierarchy of responses to repeated stimulation, which are among the most complex behaviors reported for a singly nucleated cell [16, 17]. These results attracted widespread interest [18, 19] and exert continuing fascination [7, 20-22] but were discredited during the behaviorist orthodoxy by claims of non-reproducibility [23]. These claims were based on experiments with the motile ciliate Stentor coeruleus. We acquired and maintained the correct organism in laboratory culture and used micromanipulation and video microscopy to confirm Jennings' observations. Despite significant individual variation, not addressed by Jennings, S. roeseli exhibits avoidance behaviors in a characteristic hierarchy of bending, ciliary alteration, contractions, and detachment, which is distinct from habituation or conditioning. Remarkably, the choice of contraction versus detachment is consistent with a fair coin toss. Such behavioral complexity may have had an evolutionary advantage in protist ecosystems, and the ciliate cortex may have provided mechanisms for implementing such behavior prior to the emergence of multicellularity. Our work resurrects Jennings' pioneering insights and adds to the list of exceptional features, including regeneration [24], genome rearrangement [25], codon reassignment [26], and cortical inheritance [27], for which the ciliate clade is renowned.DBT-Cambridge Lectureshi

An investigation into commercial aspects of the hard clam fishery and development of commercial gear for the harvest of molluscs : final contract report for the period 1 July, 1970 through 30 June, 1973

Because of the volumes of data presented in the final report on An Investigation into Commercial Aspects of the Hard Clam Fishery and Development of Gear for the Harvest of Oysters , we are presenting here a brief summary of the results along with conclusions and recommendations

Strings, Triangles, and Go-betweens: Intertextual Approaches to Silius’ Carthaginian Debates

This article examines a case study in Silius Italicus’ Punica using two distinct but complementary approaches to Flavian epic intertextuality: a methodological move to expand and further incorporate computational tools within philology, and a literary theoretical move to combine intertextuality and thematic interpretation. The case study focuses on the debates in the Carthaginian senate described in Punica 2 and 11, both of which Silius adapts from similar scenes in Livy while also drawing on Vergil’s Aeneid. Part 1 of the essay introduces a new tool for finding a range of inexact verbal parallels based on a bioinformatics technique known as sequence alignment. After comparing the method with two other computational tools, Diogenes and Tesserae, we assess our tool’s ability to detect intertexts in the Punica already noted in traditional scholarship. We then analyse a series of computationally identified parallels that have not been commented on previously and find that all three tools can reveal morphologically and syntactically similar phrases of apparent literary interest. Part 2 focuses on a feature of Silius’ triangulation of Livy and Vergil, the characterisation of the Carthaginian senator Hanno. Through allusions to Vergil’s Drances, Silius turns Hanno from a shrewd judge of Roman character and strength, as he appears in Livy, into a far more ambivalent, Quisling-like figure. Moreover, the effect of blending the two sources is to make more porous the distinctions between nationalities and other categories that structure the reader’s response to Hanno and to the Punica as a whole. In concluding, we suggest that the context in which these literary interactions take place - diplomacy and debate - itself figures the kind of negotiation taking place at a textual level between the various works and their worldviews. The conclusion unifies the methodological and theoretical parts of the essay under the rubric of “triangulation”, in part by drawing on the application of the term in the philosophy of Donald Davidson

Statistics of X-ray flares of Sagittarius A*: evidence for solar-like self-organized criticality phenomenon

X-ray flares have routinely been observed from the supermassive black hole, Sagittarius A$^\star$ (Sgr A$^\star$), at our Galactic center. The nature of these flares remains largely unclear, despite of many theoretical models. In this paper, we study the statistical properties of the Sgr A$^\star$ X-ray flares, by fitting the count rate (CR) distribution and the structure function (SF) of the light curve with a Markov Chain Monte Carlo (MCMC) method. With the 3 million second \textit{Chandra} observations accumulated in the Sgr A$^\star$ X-ray Visionary Project, we construct the theoretical light curves through Monte Carlo simulations. We find that the $2-8$ keV X-ray light curve can be decomposed into a quiescent component with a constant count rate of $\sim6\times10^{-3}~$count s$^{-1}$ and a flare component with a power-law fluence distribution $dN/dE\propto E^{-\alpha_{\rm E}}$ with $\alpha_{\rm E}=1.65\pm0.17$. The duration-fluence correlation can also be modelled as a power-law $T\propto E^{\alpha_{\rm ET}}$ with $\alpha_{\rm ET} < 0.55$ ($95\%$ confidence). These statistical properties are consistent with the theoretical prediction of the self-organized criticality (SOC) system with the spatial dimension $S = 3$. We suggest that the X-ray flares represent plasmoid ejections driven by magnetic reconnection (similar to solar flares) in the accretion flow onto the black hole.Comment: to appear in Ap

Quantitative Criticism of Literary Relationships

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships (“intertextuality”) and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term “quantitative criticism,” focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca’s main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions

Quantitative Criticism of Literary Relationships

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships (“intertextuality”) and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term “quantitative criticism,” focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca’s main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions

Quantitative criticism of literary relationships

Authors often convey meaning by referring to or imitating prior works of literature, a process that creates complex networks of literary relationships ("intertextuality") and contributes to cultural evolution. In this paper, we use techniques from stylometry and machine learning to address subjective literary critical questions about Latin literature, a corpus marked by an extraordinary concentration of intertextuality. Our work, which we term "quantitative criticism," focuses on case studies involving two influential Roman authors, the playwright Seneca and the historian Livy. We find that four plays related to but distinct from Seneca's main writings are differentiated from the rest of the corpus by subtle but important stylistic features. We offer literary interpretations of the significance of these anomalies, providing quantitative data in support of hypotheses about the use of unusual formal features and the interplay between sound and meaning. The second part of the paper describes a machine-learning approach to the identification and analysis of citational material that Livy loosely appropriated from earlier sources. We extend our approach to map the stylistic topography of Latin prose, identifying the writings of Caesar and his near-contemporary Livy as an inflection point in the development of Latin prose style. In total, our results reflect the integration of computational and humanistic methods to investigate a diverse range of literary questions