NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 14: An analysis of the technical communications practices reported by Israeli and US aerospace engineers and scientists

As part of Phase 4 of the NASA/DoD Aerospace Knowledge Diffusion Research Project, two pilot studies were conducted that investigated the technical communications practices of Israeli and U.S. aerospace engineers and scientists. Both studies had the same five objectives: first, to solicit the opinions of aerospace engineers and scientists regarding the importance of technical communications to their profession; second, to determine the use and production of technical communications by aerospace engineers and scientists; third, to seek their view about the appropriate content of an undergraduate course in technical communications; fourth, to determine aerospace engineers' and scientists' use of libraries, technical information centers, and on-line databases; and fifth, to determine the use and importance of computer and information technology to them. A self-administered questionnaire was mailed to randomly selected U.S. aerospace engineers and scientists who are working in cryogenics, adaptive walls, and magnetic suspension. A slightly modified version was sent to Israeli aerospace engineers and scientists working at Israel Aircraft Industries, LTD. Responses of the Israeli and U.S. aerospace engineers and scientists to selected questions are presented in this paper

Late Cenozoic geology of the Central Persian (Arabian) Gulf from industry well data and seismic profiles

Industry seismic reflection profiles shot in the 60's and early 70's in the central Persian (Arabian) Gulf are used to map two late Tertiary unconformities, and velocity data from a centrally located well is used to convert travel time to depth to the unconformities. The deeper horizon correlates with a regional unconformity at the end of the Eocene in most wells and dips monotonically to the northeast, whereas the shallower horizon is flatter and correlates with the mid-upper Miocene section in one well. Isopach maps based on wells indicate that sedimentation was relatively uniform across the region until the middle to late Miocene. Sediments deposited since the late Miocene thicken from 100-200 m on the Arabian side of the Gulf to >1000 m near Iran reflecting deposition of sediments eroded from the rapidly uplifting Zagros fold-belt. As a result of the rapid deposition, the velocity gradient in the upper 1 km decreases from ~4 km/sec per km near Arabia to about 2 km/sec per km on the Iranian side of the Gulf.This research was jointly supported by the Office of Naval Research, though grants N00014-96-1-0548 and 96PR04120-00, and by the Naval Oceanographic Offic

Estimating the Causal Effect of Early ArXiving on Paper Acceptance

What is the effect of releasing a preprint of a paper before it is submitted for peer review? No randomized controlled trial has been conducted, so we turn to observational data to answer this question. We use data from the ICLR conference (2018--2022) and apply methods from causal inference to estimate the effect of arXiving a paper before the reviewing period (early arXiving) on its acceptance to the conference. Adjusting for confounders such as topic, authors, and quality, we may estimate the causal effect. However, since quality is a challenging construct to estimate, we use the negative outcome control method, using paper citation count as a control variable to debias the quality confounding effect. Our results suggest that early arXiving may have a small effect on a paper's chances of acceptance. However, this effect (when existing) does not differ significantly across different groups of authors, as grouped by author citation count and institute rank. This suggests that early arXiving does not provide an advantage to any particular group.Comment: Published at CLeaR 202

Sequential SNARE disassembly and GATE-16–GOS-28 complex assembly mediated by distinct NSF activities drives Golgi membrane fusion

Characterization of mammalian NSF (G274E) and Drosophila NSF (comatose) mutants revealed an evolutionarily conserved NSF activity distinct from ATPase-dependent SNARE disassembly that was essential for Golgi membrane fusion. Analysis of mammalian NSF function during cell-free assembly of Golgi cisternae from mitotic Golgi fragments revealed that NSF disassembles Golgi SNAREs during mitotic Golgi fragmentation. A subsequent ATPase-independent NSF activity restricted to the reassembly phase is essential for membrane fusion. NSF/α-SNAP catalyze the binding of GATE-16 to GOS-28, a Golgi v-SNARE, in a manner that requires ATP but not ATP hydrolysis. GATE-16 is essential for NSF-driven Golgi reassembly and precludes GOS-28 from binding to its cognate t-SNARE, syntaxin-5. We suggest that this occurs at the inception of Golgi reassembly to protect the v-SNARE and regulate SNARE function

Naming Names: The Impact of Supreme Court Opinion Attribution on Citizen Assessment of Policy Outcomes

The manner in which political institutions convey their policy outcomes can have important implications for how the public views institutions\u27 policy decisions. This paper explores whether the way in which the U.S. Supreme Court communicates its policy decrees affects how favorably members of the public assess its decisions. Specifically, we investigate whether attributing a decision to the nation\u27s High Court or to an individual justice influences the public\u27s agreement with the Court\u27s rulings. Using an experimental design, we find that when a Supreme Court outcome is ascribed to the institution as a whole, rather than to a particular justice, people are more apt to agree with the policy decision. We also find that identifying the gender of the opinion author affects public agreement under certain conditions. Our findings have important implications for how public support for institutional policymaking operates, as well as the dynamics of how the Supreme Court manages to accumulate and maintain public goodwill

The Impact of Advocacy Organizations on Low-Income Housing Policy in U.S. Cities

Financial support for affordable housing competes with many other municipal priorities. This work seeks to explain the variation in support for affordable housing among U.S. cities with populations of 100,000 or more. Using multivariate statistical analysis, this research investigates political explanations for the level of city expenditures on housing and community with a particular interest in the influence of housing advocacy organizations (AOs). Data for the model were gathered from secondary sources, including the U.S. Census and the National Center for Charitable Statistics. Among other results, the analysis indicates that, on average, the political maturity of AOs has a statistically significant, positive effect on local housing and community development expenditures

Data Contamination Report from the 2024 CONDA Shared Task

The 1st Workshop on Data Contamination (CONDA 2024) focuses on all relevant aspects of data contamination in natural language processing, where data contamination is understood as situations where evaluation data is included in pre-training corpora used to train large scale models, compromising evaluation results. The workshop fostered a shared task to collect evidence on data contamination in current available datasets and models. The goal of the shared task and associated database is to assist the community in understanding the extent of the problem and to assist researchers in avoiding reporting evaluation results on known contaminated resources. The shared task provides a structured, centralized public database for the collection of contamination evidence, open to contributions from the community via GitHub pool requests. This first compilation paper is based on 566 reported entries over 91 contaminated sources from a total of 23 contributors. The details of the individual contamination events are available in the platform. The platform continues to be online, open to contributions from the community.Comment: https://huggingface.co/spaces/CONDA-Workshop/Data-Contamination-Databas

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Information about pretraining corpora used to train the current best-performing language models is seldom discussed: commercial models rarely detail their data, and even open models are often released without accompanying training data or recipes to reproduce them. As a result, it is challenging to conduct and advance scientific research on language modeling, such as understanding how training data impacts model capabilities and limitations. To facilitate scientific research on language model pretraining, we curate and release Dolma, a three-trillion-token English corpus, built from a diverse mixture of web content, scientific papers, code, public-domain books, social media, and encyclopedic materials. We extensively document Dolma, including its design principles, details about its construction, and a summary of its contents. We present analyses and experimental results on intermediate states of Dolma to share what we have learned about important data curation practices. Finally, we open-source our data curation toolkit to enable reproduction of our work as well as support further research in large-scale data curation.Comment: Accepted at ACL 2024; Dataset: https://hf.co/datasets/allenai/dolma; Code: https://github.com/allenai/dolm

OLMo: Accelerating the Science of Language Models

Language models (LMs) have become ubiquitous in both NLP research and in commercial product offerings. As their commercial importance has surged, the most powerful models have become closed off, gated behind proprietary interfaces, with important details of their training data, architectures, and development undisclosed. Given the importance of these details in scientifically studying these models, including their biases and potential risks, we believe it is essential for the research community to have access to powerful, truly open LMs. To this end, we have built OLMo, a competitive, truly Open Language Model, to enable the scientific study of language models. Unlike most prior efforts that have only released model weights and inference code, we release OLMo alongside open training data and training and evaluation code. We hope this release will empower the open research community and inspire a new wave of innovation