What is Salience?

A commonly used concept in linguistics is salience. Oftentimes it is used without definition, and the meaning of the concept is repeatedly assumed to be self-explanatory. The definitions that are provided may vary greatly from one operationalization of salience to the next. In order to find out whether it is possible to postulate an overarching working definition of linguistic salience that subsumes usage across linguistic subdomains, we review these different operationalizations of linguistic salience. This article focuses on salience in sociolinguistics, cognitive linguistics, second-language acquisition (SLA), and semantics. In this article, we give an overview of how these fields operationalize salience. Finally, we discuss correlations and contradictions between the different operationalizations

Use My Digital Forensics Tool...It’s Shiny!

The tendency to use technologies without fully understanding the potential ramifications extends to all reaches of our lives. Digital forensics is not immune from this phenomenon. This paper discusses some past scenarios in which conclusions were drawn before all of the testing was complete. Digital forensics tools are then discussed including tool capabilities, tool analysis, and associated challenges. It identifies some potential issues and ramifications that may not be given appropriate consideration by digital forensic examiners or those who rely on these tools when weighing evidence. It concludes with some suggestions for future research directions that could answer some important questions about using digital forensics tools effectively

Untangling Linguistic Salience

The concept of linguistic salience is broadly used within sociolinguistics to account for processes as diverse as language change (Kerswill & Williams, 2002) and language acquisition (Ellis, 2016) in that salient forms are e.g. more likely to undergo change, or are often acquired earlier than other features. However, the meaning of salience is “notoriously difficult to quantify” (Hickey, 2000, p. 57) and definitions of the term given in the literature often differ to such a degree that one could dispute whether the concept of salience has explanatory value (cf. Rácz, 2013). Accordingly, what makes a particular linguistic feature salient is contested: some argue that salience can be defined by linguistic traits such as loudness, high word-frequency, or a greater articulatory effort, whereas others argue that salience is a result of associations with social factors (cf. Kerswill & Williams, 2002). In a pilot study, we used eye-tracking to collect pupil dilation data while participants listened to spoken samples that were hypothesized to be either salient or not. These differences in salience were based on notions taken from the literature and included traits such as acoustical prominence, gender violations, loudness and differing realizations of the consonants /r/ and /v/. We were able to show that pupil size increased significantly for salient variables in the categories acoustic prominence, gender and loudness, pointing towards an increase in brain activity for these variables. In this poster, we propose to untangle how the concept is used. To those ends, we conducted a review of the literature on salience and identified different ways of operationalizing it. We conclude by discussing how salience could be decomposed in terms of other notions such as frequency, surprisal and markedness. We then propose a series of experiments using eye-tracking and ERP experiments

The Bird’s-Eye View Education Program: Using Bird Research To Educate The Public On The Importance Of Healthy Riparian Systems

The Upper Clark Fork River Basin (UCFRB) has been degraded by over 100 yrs of mining and smelting activities. The UCFRB is the largest contiguous complex of federal Superfund sites in the nation. Restoration and remediation efforts were initiated in the late 1980s and will continue, at a minimum, through 2030. Any restoration activity should include public education and outreach so that land-use decisions in the future do not compromise the integrity of the ecosystems that support the region. We have developed a program, the Bird’s-eye View Education Program, which integrates public education and research on the ecological health of the UCFRB. Specifically we focus on birds, inviting the public to observe research at songbird banding stations and Osprey (Pandion haliaetus) nests. Riparian-associated birds are likely to respond positively to riparian restoration activities and can be used as bio-indicators to measure success. In 2010 we operated three bird banding stations and monitored 19 Osprey nests. We captured 595 songbirds, collected 43 blood and feather samples from Osprey chicks, and served nearly 1000 participants. The program was an outstanding success and results from an assessment show that participants leave with a positive attitude toward the outdoor science experience and a general knowledge of Upper Clark Fork restoration, history, and its riparian ecosystems

Many-body renormalization of forces in f-electron materials

We present the implementation of dynamical mean-field theory (DMFT) in the CASTEP ab initio code. We explain in detail the theoretical framework for DFT+DMFT and we demonstrate our implementation for three strongly-correlated systems with f -shell electrons: γ -cerium, cerium sesquioxide Ce2O3, and samarium telluride SmTe by using a Hubbard I solver. We find very good agreement with previous benchmark DFT+DMFT calculations of cerium compounds, while for SmTe we show the improved agreement with the experimental structural parameters as compared with LDA. Our implementation works equally well for both norm-conserving and ultrasoft pseudopotentials, and we apply it to the calculation of total energy, bulk modulus, equilibrium volumes, and internal forces in the two cerium compounds. In Ce2O3 we report a dramatic reduction of the internal forces acting on coordinates not constrained by unit cell symmetries. This reduction is induced by the many-body effects, which can only be captured at the DMFT level. In addition, we derive an alternative form for treating the high-frequency tails of the Green function in Matsubara frequency summations. Our treatment allows a reduction in the bias when calculating the correlation energies and occupation matrices to high precision

No Pain No Gain: Standards mapping in Latimer Core development

Latimer Core (LtC) is a new proposed Biodiversity Information Standards (TDWG) data standard that supports the representation and discovery of natural science collections by structuring data about the groups of objects that those collections and their subcomponents encompass (Woodburn et al. 2022). It is designed to be applicable to a range of use cases that include high level collection registries, rich textual narratives and semantic networks of collections, as well as more granular, quantitative breakdowns of collections to aid collection discovery and digitisation planning.As a standard that is (in this first version) focused on natural science collections, LtC has significant intersections with existing data standards and models (Fig. 1) that represent individual natural science objects and occurrences and their associated data (e.g., Darwin Core (DwC), Access to Biological Collection Data (ABCD), Conceptual Reference Model of the International Committee on Documentation (CIDOC-CRM)). LtC's scope also overlaps with standards for more generic concepts like metadata, organisations, people and activities (i.e., Dublin Core, World Wide Web Consortium (W3C) ORG Ontology and PROV Ontology, Schema.org). LtC represents just an element of this extended network of data standards for the natural sciences and related concepts. Mapping between LtC and intersecting standards is therefore crucial for avoiding duplication of effort in the standard development process, and ensuring that data stored using the different standards are as interoperable as possible in alignment with FAIR (Findable, Accessible, Interoperable, Reusable) principles. In particular, it is vital to make robust associations between records representing groups of objects in LtC and records (where available) that represent the objects within those groups.During LtC development, efforts were made to identify and align with relevant standards and vocabularies, and adopt existing terms from them where possible. During expert review, a more structured approach was proposed and implemented using the Simple Knowledge Organization System (SKOS) mappingRelation vocabulary. This exercise helped to better describe the nature of the mappings between new LtC terms and related terms in other standards, and to validate decisions around the borrowing of existing terms for LtC. A further exercise also used elements of the Simple Standard for Sharing Ontological Mappings (SSSOM) to start to develop a more comprehensive set of metadata around these mappings. At present, these mappings (Suppl. material 1 and Suppl. material 2) are provisional and not considered to be comprehensive, but should be further refined and expanded over time.Even with the support provided by the SKOS and SSSOM standards, the LtC experience has proven the mapping process to be far from straightforward. Different standards vary in how they are structured, for example, DwC is a 'bag of terms', with informal classes and no structural constraints, while more structured standards and ontologies like ABCD and PROV employ different approaches to how structure is defined and documented. The various standards use different metadata schemas and serialisations (e.g., Resource Description Framework (RDF), XML) for their documentation, and different approaches to providing persistent, resolvable identifiers for their terms. There are also many subtle nuances involved in assessing the alignment between the concepts that the source and target terms represent, particularly when assessing whether a match is exact enough to allow the existing term to be adopted. These factors make the mapping process quite manual and labour-intensive. Approaches and tools, such as developing decision trees (Fig. 2) to represent the logic involved and further exploration of the SSSOM standard, could help to streamline this process.In this presentation, we will discuss the LtC experience of the standard mapping process, the challenges faced and methods used, and the potential to contribute this experience to a collaborative standards mapping within the anticipated TDWG Standards Mapping Interest Group

Verifiable self-certifying autonomous systems

Autonomous systems are increasingly being used in safety-and mission-critical domains, including aviation, manufacturing, healthcare and the automotive industry. Systems for such domains are often verified with respect to essential requirements set by a regulator, as part of a process called certification. In principle, autonomous systems can be deployed if they can be certified for use. However, certification is especially challenging as the condition of both the system and its environment will surely change, limiting the effective use of the system. In this paper we discuss the technological and regulatory background for such systems, and introduce an architectural framework that supports verifiably-correct dynamic self-certification by the system, potentially allowing deployed systems to operate more safely and effectively

AudioLM: a Language Modeling Approach to Audio Generation

We introduce AudioLM, a framework for high-quality audio generation with long-term consistency. AudioLM maps the input audio to a sequence of discrete tokens and casts audio generation as a language modeling task in this representation space. We show how existing audio tokenizers provide different trade-offs between reconstruction quality and long-term structure, and we propose a hybrid tokenization scheme to achieve both objectives. Namely, we leverage the discretized activations of a masked language model pre-trained on audio to capture long-term structure and the discrete codes produced by a neural audio codec to achieve high-quality synthesis. By training on large corpora of raw audio waveforms, AudioLM learns to generate natural and coherent continuations given short prompts. When trained on speech, and without any transcript or annotation, AudioLM generates syntactically and semantically plausible speech continuations while also maintaining speaker identity and prosody for unseen speakers. Furthermore, we demonstrate how our approach extends beyond speech by generating coherent piano music continuations, despite being trained without any symbolic representation of music

Towards the Determination of Safe Operating Envelopes for Autonomous UAS in Offshore Inspection Missions

From MDPI via Jisc Publications RouterHistory: accepted 2021-07-21, pub-electronic 2021-07-28Publication status: PublishedFunder: Engineering and Physical Sciences Research Council; Grant(s): EP/R026173/1A drive to reduce costs, carbon emissions, and the number of required personnel in the offshore energy industry has led to proposals for the increased use of autonomous/robotic systems for many maintenance tasks. There are questions over how such missions can be shown to be safe. A corollary exists in the manned aviation world for helicopter–ship operations where a test pilot attempts to operate from a ship under a range of wind conditions and provides subjective feedback on the level of difficulty encountered. This defines the ship–helicopter operating limit envelope (SHOL). Due to the cost of creating a SHOL there has been considerable research activity to demonstrate that much of this process can be performed virtually. Unmanned vehicles, however, have no test pilot to provide feedback. This paper therefore explores the possibility of adapting manned simulation techniques to the unmanned world to demonstrate that a mission is safe. Through flight modelling and simulation techniques it is shown that operating envelopes can be created for an oil rig inspection task and that, by using variable performance specifications, these can be tailored to suit the level of acceptable risk. The operating envelopes produced provide condensed and intelligible information regarding the environmental conditions under which the UAS can perform the task