An archaeological dig on Naxos is overturning our assumptions about who Neanderthals were — and how they differed from Homo sapiens.
The Indo-European Cognate Relationships (IE-CoR) dataset is a comprehensive, open-access relational database detailing cognates—inherited related words—across 160 Indo-European languages. Developed by a consortium of 89 linguists, it aims to serve as a benchmark for computational research into the evolution of this vast language family, encompassing 25,731 lexeme entries grouped into 4,981 cognate sets based on 170 core meanings. The dataset incorporates time calibration data, geographical/social metadata, and a novel structure for coding horizontal transfer, adhering to the Cross-Linguistic Data Format (CLDF) for interoperability and long-term accessibility. IE-CoR addresses limitations of previous datasets through improved coverage, rigorous coding protocols, and a focus on the primary cognate state of root morphemes, offering a valuable resource for phylogenetic and quantitative linguistic research.
Fernando J. Corbató was a Professor Emeritus at MIT, renowned for his pioneering work in the development of time-sharing and resource-sharing computer systems. He was instrumental in creating the Compatible Time-Sharing System (CTSS) and Multics, both influential systems that laid the groundwork for modern operating systems. Corbató's contributions have been widely recognized through numerous awards and fellowships, including the Turing Award (1990) and the Computer Pioneer Award (1982). He was a long-time member of the MIT Computation Center and the Laboratory for Computer Science, and held leadership positions within the department. His work significantly impacted the field of computer science and the evolution of computing technology.
The story of ERNIE, a computer built by Thomas Flowers to generate random numbers for the UK's Premium Bonds lottery, evolving from neon-lamp based randomness to quantum technology.
The article argues that the perception of C as a “low‑level” language has become outdated.
- **Historical context** – In the early 1970s, C on the PDP‑11 was literally close to the metal: each statement mapped to one or two machine instructions, memory was flat, and the execution model was straightforward.
- **Modern hardware** – Today’s CPUs are far more complex (multi‑core, deep pipelines, out‑of‑order execution, vector units, large caches, speculative execution). They are designed to run legacy C code efficiently, but the underlying reality is far removed from the simple model that early C programmers relied on.
- **The illusion** – Modern processors adapt to preserve the old C abstract machine, giving developers the impression that C is still “low‑level.” This illusion hides a mismatch between what C promises (predictable, simple mapping to hardware) and what the hardware actually does.
- **Historical context** – In the early 1970s, C on the PDP‑11 was literally close to the metal: each statement mapped to one or two machine instructions, memory was flat, and the execution model was straightforward.
- **Modern hardware** – Today’s CPUs are far more complex (multi‑core, deep pipelines, out‑of‑order execution, vector units, large caches, speculative execution). They are designed to run legacy C code efficiently, but the underlying reality is far removed from the simple model that early C programmers relied on.
- **The illusion** – Modern processors adapt to preserve the old C abstract machine, giving developers the impression that C is still “low‑level.” This illusion hides a mismatch between what C promises (predictable, simple mapping to hardware) and what the hardware actually does.
An international team analyzed ancient DNA from 230 individuals in Georgia and Armenia, revealing a largely stable local gene pool from the Bronze Age to 500 CE, with some migration from Anatolia and the Eurasian steppe. The study also found that cranial deformation, initially introduced by migrants, became a local tradition.
The Keeladi archaeological site in Tamil Nadu, India, is revealing ancient artefacts that challenge existing historical narratives and has become a symbol of state pride and identity, sparking political debate.
An article discussing the Carthaginian empire, highlighting its history, culture, and influence, arguing it was more impactful than ancient Rome. It focuses on Hannibal, Carthaginian society, and the historical bias towards Roman accounts.
Introducing Aeneas, the first AI model for contextualizing ancient inscriptions, designed to help historians better interpret, attribute, and restore fragmentary texts. It reasons across thousands of Latin inscriptions, retrieving textual and contextual parallels to aid in historical research.
Journal of Mississippi History
Volume 82 Number 3 Article 4
2020
Volume 82 Number 3 Article 4
2020
