Alien Registration- Peters, Alexandra (Westbrook, Cumberland County)

https://digitalmaine.com/alien_docs/20096/thumbnail.jp

Efficient regular path query evaluation using path indexes

We demonstrate the use of localized path indexes in generating efficient execution plans for regular path queries. This study is motivated by both the practicality of this class of queries and by the current dearth of scalable solutions for their evaluation. Our proposed solution leverages widely available relational database technology and is often orders of magnitude faster than currently known approaches. We aim in this hands-on demonstration to both highlight the promise of our approach and to stimulate further discussion and study of engineering solutions for this practical yet challenging class of graph queries

Efficient Hierarchical Domain Adaptation for Pretrained Language Models

The remarkable success of large language models has been driven by dense models trained on massive unlabeled, unstructured corpora. These corpora typically contain text from diverse, heterogeneous sources, but information about the source of the text is rarely used during training. Transferring their knowledge to a target domain is typically done by continuing training in-domain. In this paper, we introduce a method to permit domain adaptation to many diverse domains using a computationally efficient adapter approach. Our method is based on the observation that textual domains are partially overlapping, and we represent domains as a hierarchical tree structure where each node in the tree is associated with a set of adapter weights. When combined with a frozen pretrained language model, this approach enables parameter sharing among related domains, while avoiding negative interference between unrelated ones. Experimental results with GPT-2 and a large fraction of the 100 most represented websites in C4 show across-the-board improvements in-domain. We additionally provide an inference time algorithm for a held-out domain and show that averaging over multiple paths through the tree enables further gains in generalization, while adding only a marginal cost to inference.Comment: NAACL 2022 accepted paper camera ready versio

Air temperature and inflammatory and coagulation responses in men with coronary or pulmonary disease during the winter season

Background and Objective Air temperature changes are associated with increased cardiovascular and respiratory risk, but the roles of inflammatory and coagulation markers are not well understood. We investigated the associations between temperature and several blood markers in patients with coronary heart disease (CHD) and pulmonary disease (PD). Methods Two studies were conducted in Erfurt, Germany, over two successive winters. 578 and 381 repeated blood measurements were collected from 57 CHD and 38 PD patients, respectively. Data on patient characteristics and disease history were gathered at baseline. Meteorological data were collected from existing networks. Associations were analysed using additive mixed models with random patient effects. Effect modification by diabetes status was investigated only in CHD patients, as only two PD patients had diabetes. Results Mean daily air temperature varied between -13 degrees C and 16 degrees C in both study periods. A 10 degrees C decrease in the 5-day temperature average before blood withdrawal led to an increase in platelet counts (% change from the mean: 3.0%, 95% CI 0.6% to 5.5%) and fibrinogen (5.5%, 1.3% to 9.7%), no change in C-reactive protein in PD patients, and a decrease in C-reactive protein in CHD patients. A 2-day delayed increase in factor VII associated with temperature decrease was seen in CHD patients (4.9%; 0.7% to 9.2%), while PD patients showed no effect. `Effects in CHD patients without diabetes' into `Effects on factor VII in CHD patients without diabetes'. Conclusions This study suggests that temperature decrease is associated with change in several blood parameters. The complex interplay of blood markers at low temperature may contribute to the observed association between cold and cardiovascular mortality and morbidity

AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models

Pretrained language models (PLMs) are trained on massive corpora, but often need to specialize to specific domains. A parameter-efficient adaptation method suggests training an adapter for each domain on the task of language modeling. This leads to good in-domain scores but can be impractical for domain- or resource-restricted settings. A solution is to use a related-domain adapter for the novel domain at test time. In this paper, we introduce AdapterSoup, an approach that performs weight-space averaging of adapters trained on different domains. Our approach is embarrassingly parallel: first, we train a set of domain-specific adapters; then, for each novel domain, we determine which adapters should be averaged at test time. We present extensive experiments showing that AdapterSoup consistently improves performance to new domains without extra training. We also explore weight averaging of adapters trained on the same domain with different hyper-parameters, and show that it preserves the performance of a PLM on new domains while obtaining strong in-domain results. We explore various approaches for choosing which adapters to combine, such as text clustering and semantic similarity. We find that using clustering leads to the most competitive results on novel domains.Comment: Accepted at EACL 2023; camera-ready versio

Educators' experiences and perspectives of child weight discussions with parents in primary school settings.

From Europe PMC via Jisc Publications RouterHistory: ppub 2022-04-01, epub 2022-04-22Publication status: PublishedFunder: Academy of Medical Sciences; Grant(s): HOP001\1062BackgroundThe role of schools in addressing rising childhood obesity levels has been acknowledged, and numerous diet- and physical activity-related interventions exist. Aside from formal interventions, opportunistic parent-educator conversations about child weight can arise, particularly in primary school settings, yet little is known about how useful these are. This study aimed to understand the utility of child weight related conversations with parents through exploring educators' experiences and perspectives.MethodsThis qualitative study consisted of semi-structured interviews conducted with primary school teaching staff in the United Kingdom (N = 23), recruited through purposive and subsequent snowball sampling. Interviews were audio-recorded, transcribed, and analysed using thematic analysis.ResultsParticipants identified opportunities and need for child weight discussions in schools. However, conversations were prevented by the indirect and sensitive nature of conversations, and educators' professional identity beliefs. Using pre-existing face-to-face opportunities, good parent-teacher relationships and holistic approaches to child health and wellbeing were reported as important in optimising these conversations.ConclusionsWhilst educator-parent child weight discussions are necessary, discussions are highly challenging, with contradictory views on responsibility sometimes resulting in avoidance. Educators' roles should be clarified, and communication training tailored to increase teacher confidence and skills. Current social distancing will likely reduce opportunistic encounters, highlighting a need to further improve communication routes

Rich-club structure contributes to individual variance of reading skills via feeder connections in children with reading disabilities

The present work considers how connectome-wide differences in brain organization might distinguish good and poor readers. The connectome comprises a ‘rich-club’ organization in which a small number of hub regions play a focal role in assisting global communication across the whole brain. Prior work indicates that this rich-club structure is associated with typical and impaired cognitive function although no work so far has examined how this relates to skilled reading or its disorders. Here we investigated the rich-club structure of brain\u27s white matter connectome and its relationship to reading subskills in 64 children with and without reading disabilities. Among three types of white matter connections, the strength of feeder connections that connect hub and non-hub nodes was significantly correlated with word reading efficiency and phonemic decoding. Phonemic decoding was also positively correlated with connectivity between connectome-wide hubs and nodes within the left-hemisphere reading network, as well as the local efficiency of the reading network. Exploratory analyses also identified sex differences indicating these effects were stronger in girls. This work highlights the independent roles of connectome-wide structure and the more narrowly-defined reading network in understanding the neural bases of skilled and impaired reading in children