AI as Collaborative Muse: Enhancing Pre-Writing for Academic Authors

AI writing tools raise concerns of misuse in academics. However, AI can aid, not automate, pre-writing. The author shows how AI can assist scholarly writing through activities like organizing freewriting notes into outlines, recommending titles and journals, and summarizing/comparing literature. AI expedites idea generation, focus, literature review and positioning - serving as a collaborative muse, not replacement, for human creativity

The Idea of a Writing Center in Brazil: A Different Beat

This article explores the emergence and development of writing centers in Brazil, using the author’s experience founding the Centro de Assessoria de Publicação Acadêmica (CAPA) at the Universidade Federal do Paraná as a case study. The author provides some historical context about Brazilian education and its traditional “banking model” of education (Paulo Freire) that did not value individual expression—including through writing. This model persisted even as composition studies evolved elsewhere. Academic literacy development in Brazil is thus a relatively recent phenomenon, and the effects of that paucity are felt among scholars in higher education settings. This motivated the author’s research into publication challenges faced by Brazilian faculty and graduate students, which revealed a need for more institutional support. This inspired the idea for CAPA, conceived as a space promoting dialogue around writing, not just language editing. In establishing CAPA, critical considerations were the use of a public call mechanism familiar to Brazilians (“o edital”) to make consultations part of the writing process, offering translation to draw more people from around campus, and conducting outreach that stressed writing over “English.” CAPA’s mission to foster academic identities and combat epistemicide makes it unique, but also gives it a very Brazilian flavor. Unlike some writing centers in other global contexts, CAPA was not an imported idea but emerged from local needs, fully integrated with Brazilian higher education culture, compatible with Brazilian understandings like critical pedagogy. CAPA represents a Brazilian innovation contributing original knowledge to international writing center conversations

Waverider, volume 2

The results of a study concerning a High-Speed Civilian Transport Aircraft are discussed. An evaluation of the viability of four configurations is presented. One design considered in the Waverider configuration. The Waverider creates lift at high speeds through the use of shock waves. This shocklift when combined with conventionally created lift provides high lift/drag values at higher speeds than conventional configurations. The Waverider cruises at Mach 5.5, has a range of 6,500 nautical miles, and seats 250 passengers. The aircraft is operable from existing airfields and does not require any special traffic control considerations when operating in controlled airspace

The development of a corpus-informed list of formulaic sequences for language pedagogy

Discussion around the importance and prevalence of multiword expressions in the lexicon and the teaching of vocabulary has existed for a number of years in applied linguistics (e. g. lrujo, 1986; Pawley and Syder, 1983; Sinclair, 1987; Wray, 2002). While there seems to be a general agreement among scholars that formulaic language should feature in language learning and, perhaps to a lesser extent, language testing, there appears to be rather less agreement when it comes to how to select and/or prioritize specific items for inclusion. One criterion for selection which has been used often for vocabulary items of single words is frequency (i.e. how relatively common a word is), data for which can be consulted using various frequency lists that have long existed and are in the public domain, such as the General Service List (West, 1953). However, to date, no list of formulaic language that could be considered comparable to the General Service List in terms of intended use and relevance to language instruction has been attempted. The work presented in the present thesis aims to address this lack. The thesis first presents the need for such a list, and then describes the methodology employed by the researcher to ultimately produce a frequency-informed and pedagogically-relevant list of multiword expressions that can be used in conjunction with existing lists single orthographic words to help inform such instruments of L2 pedagogy as language textbooks and language tests, entitled the PHRASal Expressions List, or PHRASE List. To that end, two projects are also presented in the thesis which exemplify ways in which the list may be usefully employed. The first is a research validation exercise carried out in collaboration with the English Profile project in order to compare the phraseological component of the English Profile Wordlist to the expressions in the PHRASE List. The second project presents the development and validation of a kind of vocabulary test that samples from the PHRASE List, and which is intended to be used to supplement knowledge assessed in existing tests of single orthographic words, such as the Vocabulary Size Test (Nation & Beglar, 2007)

Improved control strategies for the environment within cell culture bioreactors

This paper describes the development of improved control strategies for the standard environmental conditions in a fed-batch bioreactor used for monoclonal antibody cell culture. The consequences of relying on fixed parameter PID based controllers are considered and poor performance is demonstrated as a consequence of non-linearity and loop interactions. The benefits from adopting a more sophisticated control strategy are considered. Model Predictive Control (MPC) relies on a process model that can be identified from small system perturbations. It considers the predicted longer-term response and consequently can deliver improved control and satisfy user defined constraints. Results from experimental trials demonstrate the capability of MPC and the merits are discussed with regards to industrial application

Competition-based model of pheromone component ratio detection in the moth

For some moth species, especially those closely interrelated and sympatric, recognizing a specific pheromone component concentration ratio is essential for males to successfully locate conspecific females. We propose and determine the properties of a minimalist competition-based feed-forward neuronal model capable of detecting a certain ratio of pheromone components independently of overall concentration. This model represents an elementary recognition unit for the ratio of binary mixtures which we propose is entirely contained in the macroglomerular complex (MGC) of the male moth. A set of such units, along with projection neurons (PNs), can provide the input to higher brain centres. We found that (1) accuracy is mainly achieved by maintaining a certain ratio of connection strengths between olfactory receptor neurons (ORN) and local neurons (LN), much less by properties of the interconnections between the competing LNs proper. An exception to this rule is that it is beneficial if connections between generalist LNs (i.e. excited by either pheromone component) and specialist LNs (i.e. excited by one component only) have the same strength as the reciprocal specialist to generalist connections. (2) successful ratio recognition is achieved using latency-to-first-spike in the LN populations which, in contrast to expectations with a population rate code, leads to a broadening of responses for higher overall concentrations consistent with experimental observations. (3) when longer durations of the competition between LNs were observed it did not lead to higher recognition accuracy

Instability in clinical risk stratification models using deep learning

While it has been well known in the ML community that deep learning models suffer from instability, the consequences for healthcare deployments are under characterised. We study the stability of different model architectures trained on electronic health records, using a set of outpatient prediction tasks as a case study. We show that repeated training runs of the same deep learning model on the same training data can result in significantly different outcomes at a patient level even though global performance metrics remain stable. We propose two stability metrics for measuring the effect of randomness of model training, as well as mitigation strategies for improving model stability.Comment: Accepted for publication in Machine Learning for Health (ML4H) 202

D-(+)-Pinitol, a Component of the Heartwood of Enterolobium cyclocarpum (Jacq.) Griseb

d-(+)-Pinitol, a natural product of the group of cyclitols, was purified for the first time from an aqueous extract of the heartwood of Enterolobium cyclocarpum, and its chemical structure was determined