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An exploratory study on expectations from AI-based automated scheduling
Get PDFScheduling is a complex process that requires information from several sources,
coordination between teams, and experience of using various methods and tools.
Automated scheduling (AS) may facilitate the process and provide a potential solution
for the skills gap experienced in the construction industry. In this paper, we will
present initial findings from a funded research project about development of an AIbased AS tool for building projects. As a part of the needs analysis, semi-structured
interviews were conducted with 12 construction professionals to identify challenges
with the traditional scheduling process, requirements from, and potential concerns
about an AI-based AS tool. Unavailability of data, procedural difficulties such as
extracting information from several documents and poor communication between
different disciplines were highlighted as the current challenges. Major expectations
from the tool are primarily about automated analysis of various documents and better
coordination of information exchange. Judgemental reasoning required for
scheduling tasks and limited explainability of AI raise concerns about the
performance of a fully automated tool and decreases trust
Cognitive mechanisms explaining the relationship between post-traumatic stress and post-traumatic growth in survivors of breast cancer
Get PDFBackground: The ability to derive growth from a traumatic event, such as a cancer diagnosis, can facilitate effective adaptation to the challenges associated with cancer survivorship. Objective: In two studies, we investigated the possible cognitive mechanisms explaining the relationship between post-traumatic stress and post-traumatic growth in female survivors of breast cancer. Specifically, Study 1 examined the role of interpretation bias, and Study 2 examined the role of cognitive restructuring of trauma. Methods: In Study 1, 113 participants completed questionnaires assessing stress- and anxiety-related symptomatology, post-traumatic stress and growth, perceived cognitive functioning, and positive interpretation bias. In Study 2, 117 participants completed questionnaires assessing stress and anxiety-related symptoms, rumination, perceived cognitive functioning, cognitive restructuring of trauma, and post-traumatic stress and growth. Results: In both studies, post-traumatic stress was negatively related to post-traumatic growth. In Study 1, positive interpretation bias explained a significant amount of variance in the relationship between post-traumatic stress and post-traumatic growth, with perceived cognitive functioning moderating the relationship between interpretation bias and post-traumatic growth. In Study 2, cognitive restructuring explained a significant amount of variance in the relationship between post-traumatic stress and post-traumatic growth, with deliberate rumination moderating the effects of cognitive restructuring on post-traumatic growth. Conclusions: Cognitive mechanisms are key to understanding the relationship between post-traumatic stress and growth and should be targeted in interventions to improve cognitive flexibility and resilience among breast cancer survivors
Edge-guided cross-modal fusion network for multi-resolution breast cancer segmentation in smart digital pathology
Get PDFAccurate segmentation of carcinoma in situ and invasive carcinoma in Whole Slide Images (WSIs) is crucial for improving breast cancer diagnostics in smart healthcare systems. Existing methods that rely solely on Hematoxylin and Eosin (H&E) staining lack molecular boundary-specific markers and struggle with resolution limitations. To address these challenges, we propose a breast cancer segmentation framework that fuses multi-resolution semantic features from H&E images with edge information from Cytokeratin 5/6 (CK5/6) immunohistochemical staining. The model integrates three modules: a multi-resolution semantic segmentation branch, an edge detection module aligned with H&E images, and a multi-scale fusion module. By combining multi-modal information and selectively zooming in on key regions, the method enhances the diagnostic process of medical practitioners, making the system more accurate and suitable for deployment in an Internet of Medical Things (IoMT) platform. Evaluations on the Breast Cancer Semantic Segmentation (BCSS) and the Chinese People's Liberation Army (PLA) General Hospital datasets show segmentation similarity coefficients of 81.28% and 93.16%, respectively. This approach offers an effective solution for user-facing digital pathology systems and supports clinical decision-making in consumer-centric smart healthcare
Mapping the impact of climate change on the quality potential of UK still Chardonnay wine production: using the Chablis region as an analogous model
Get PDFIn recent decades, the UK (especially Southern and Eastern England) has developed a
reputation for quality sparkling wine production. The potential for high quality still
white wine from Chardonnay grapes grown in the UK was investigated using the
Chablis region in Burgundy, France, as an analogy for UK viticulture. Weather data and
Chablis vintage quality scores from 1963 to 2018 were analysed to model the response
of vintage score to weather (key variables: mean temperature, April to September; mean
minimum temperature, September; total rainfall, June to September). This weather
model was applied to the UK for 1981–2000, 2010–2019 and, with climate change
projections, to 2040–2059. Only 0.2% to 1.8% of UK land was found suitable in recent
climatic conditions for reliable production of high-quality still Chardonnay wine, but
under median and 95th percentile projections for 2040–2059 SE and E England will
have the potential for high-quality still Chardonnay wine production in an average year.
This analysis was extended to include the effects of topography and soils to map
suitable sites for Chardonnay vineyards in the UK, evaluated against 35 wine experts’
scores of current English still Chardonnay wines. Minerality, often associated with
cooler regions’ high-quality still white wines, was studied by analysing Chablis Premier
Cru tasting notes entered into CellarTracker between 2003 and 2022. Use of the
descriptor minerality was correlated with growing season temperature, sunshine hours,
and vineyard aspect whereas soils and geology were not a principal source of minerality
in Chablis wine. Overall, the results show that reliable production of premium quality
still Chardonnay wine is likely to be possible by mid-Century in SE, S, and E England -
and possibly also the Midlands and SW England under more extreme climate change
Quantitative-genetic analysis of directional adaptation suggests low maximum sustainable rates of change in agreement with data from field populations
No full textWhat rates of directional change are species likely to be capable of sustaining indefinitely such as in response to a warming climate? We derive estimates of the maximum rates of phenotypic change that populations can sustain in response to a directionally changing environment, using a quantitative genetics simulation model whose parameters are calibrated with data from natural populations. Sustainable directional change is largely limited to
2–4% of a trait standard deviation per generation, in agreement with an estimate derived from quantitative-genetic theory and with published field studies. Data from thirty-seven longitudinal field-studies of species’ phenological responses to a warming climate yield rates of change that fall in the 68th–86th percentiles of our predictions for what populations can sustain, and there are suggestions that the rate of climate change may already have diminished their capacities to maintain these rates. Given the pace of climate change, species with generation times greater than four years may be especially at risk
A Paley-Wiener theorem for the Mehler-Fock transform
Get PDFIn this note, we prove a Paley–Wiener Theorem for the Mehler–Fock transform. In
particular, we show that it induces an isometric isomorphism from the Hardy space
H2(C+) onto L2(R+, (2π )−1t sinh(πt) dt). The proof we provide here is very simple
and is based on an old idea that seems to be due to G. R. Hardy. As a consequence of
this Paley–Wiener theorem we also prove a Parseval’s theorem. In the course of the
proof, we find a formula for the Mehler–Fock transform of some particular functions
How do teachers view multilingualism in education? Evidence from Greece, Italy, and the Netherlands
Get PDFAs an increasing number of multilingual children are enrolled in European schools, it is important to gain more insight into teachers’ attitudes towards multilingual approaches in education. The goal of this study is to investigate the attitudes of primary school teachers in Greece, Italy, and the Netherlands, three countries that have a highly multilingual student population but differ with respect to the migration context and language policies. Using an online questionnaire, we assessed teachers’ attitudes towards multilingualism in the school environment and their adherence to monolingual ideals. We aimed to compare the three countries and investigate which factors related to the teachers’ background and school characteristics predict teachers’ beliefs. The results suggest that teachers in Greece are significantly more positive towards multilingualism than teachers in Italy and the Netherlands, despite great individual variation. Moreover, for all three countries, we found that having received training on multilingualism had a positive effect on teachers’ attitudes. In the Netherlands, we found that teachers who taught a greater proportion of multilingual students on average showed more positive attitudes towards multilingualism. We discuss the implications of these findings for educational language policy, highlighting the importance of evidence-based training on multilingualism for all teachers
A novel explainable deep learning framework for reconstructing South Asian palaeomonsoons
Get PDFWe present novel explainable deep learning techniques for reconstructing South Asian palaeomonsoon rainfall over the last 500 years, leveraging long instrumental precipitation records and palaeoenvironmental datasets from South and East Asia to build two types of model: dense neural networks ('regional models') and convolutional neural networks (CNNs). The regional models are trained individually on seven regional rainfall datasets and while they capture decadal-scale variability and significant droughts, they underestimate interannual variability. The CNNs, designed to account for spatial relationships in both predictor and target, demonstrate higher skill in reconstructing rainfall patterns and produce robust spatiotemporal reconstructions. The 19th and 20th centuries were characterised by marked inter-annual variability in the monsoon, but earlier periods were characterised by more decadal- to centennial-scale oscillations. Multidecadal droughts occurred in the mid-seventeenth and nineteenth centuries, while much of the eighteenth century (particularly the early part of the century) was characterised by above-average monsoon precipitation. Extreme droughts tend to be concentrated in south and west India and often coincide with recorded famines. The years following large volcanic eruptions are typically marked by significantly weaker monsoons, but the sign and strength of the relationship with ENSO varies on centennial timescales.
By applying explainability techniques, we show that the models make use of both local hydroclimate and synoptic-scale dynamical relationships. Our findings offer insights into the historical variability of the Indian summer monsoon and highlight the potential of deep learning techniques in palaeoclimate reconstruction