Developing thermal prediction models for the elderly under temperature step changes

Funding Information: This work was funded by the National Key R&D Program of China [Grant No: 2022YFC3801504 ]; the Natural Science Foundation of Chongqing , China [Grant No: cstc2021ycjh-bgzxm0156 ]; and the 111 Project (Grant No. B13041 ). The author acknowledges financial support from the Chinese Scholarship Council [No: 202206050102 ]. Publisher Copyright: © 2023 Elsevier LtdDaily transitions between indoor and outdoor environments involving temperature step changes have been extensively studied in young people, but little attention has been given to age-related differences and the development of thermal prediction models specifically for the elderly. To address this knowledge gap, a study was conducted in a climate chamber using warm-neutral-warm experimental sessions. Twenty-four elderly participants were selected from volunteers who met the health and body shape requirements. Thermal sensation vote (TSV) and mean skin temperature (MST) responses of the elderly were collected and analyzed. The results demonstrate that temperature step changes (3–9 °C) and neutral thermal experiences significantly influence the thermal responses of the elderly. Compared to the young, the elderly exhibit lower TSV, lower MST, lower skin heat loss, and different associations between TSV and skin heat loss. Leveraging these age-related differences, an MST prediction model was established for the elderly. The predicted MST can also serve as an input for the TSV prediction model established in this study. The TSV prediction model is based on skin heat loss and applicable to both transient and steady-state conditions. This study introduces a new approach for predicting the thermal responses of the elderly and enhances understanding of age-related differences in thermal responses.Peer reviewe

Self-Regulation and Code of Conduct in the Community : Four Pilots on Utilising Decentralisation Technologies for Improving Sustainability and Collective Governance

Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.Decentralisation technologies, such as those based on blockchain, provide exciting possibilities to coordinate cooperative actions and contributions of independent actors in favour of more sustainable operations. These technologies offer means to operationalise and define rules for the code of conduct for community members and create incentive mechanisms to motivate self-regulation among individuals. However, while such technologies add ways to increase alignment and avoid selfish actions, they are often perceived as technologically complex and challenging to comprehend and rarely utilised in solving collective, practical problems. We challenge this notion based on four practical pilot experiments utilising novel decentralisation technology to engage community members toward more sustainable operations for collective benefits. The four pilots demonstrate how decentralisation technology can support highly different communities to better attain their goals: “Tracey” provides reliable catch and trade data on tuna fishing; “Barcelona Green Shops” encourages more sustainable shopping behaviour; “Food Futures” measures the environmental sustainability of meal choices; “Streamr Community” incentivises open-source software development. All the pilots have made the solution easy to approach for the intended audience, greatly simplifying the complexity related to the technological protocols. These successes illustrate how translation practices facilitate self-regulation and a shared code of conduct for the community. The evidence and insights drawn from these pilots pave the way toward more sustainable and inclusive business models. We explain how effective translation of digital solutions is highly impactful in reducing social struggles on a global scale. We highlight why the formalised protocols enable effective self-regulation and align actions to benefit the community. Our work illustrates how decentralisation technologies can foster sustainable, collective governance for a more prosperous future for partnerships, people, and the planet.Peer reviewe

Identifying stigmatizing and positive/preferred language in obstetric clinical notes using natural language processing

Objective To identify stigmatizing language in obstetric clinical notes using natural language processing (NLP). Materials and Methods We analyzed electronic health records from birth admissions in the Northeast United States in 2017. We annotated 1771 clinical notes to generate the initial gold standard dataset. Annotators labeled for exemplars of 5 stigmatizing and 1 positive/preferred language categories. We used a semantic similarity-based search approach to expand the initial dataset by adding additional exemplars, composing an enhanced dataset. We employed traditional classifiers (Support Vector Machine, Decision Trees, and Random Forest) and a transformer-based model, ClinicalBERT (Bidirectional Encoder Representations from Transformers) and BERT base. Models were trained and validated on initial and enhanced datasets and were tested on enhanced testing dataset. Results: In the initial dataset, we annotated 963 exemplars as stigmatizing or positive/preferred. The most frequently identified category was marginalized language/identities (n = 397, 41%), and the least frequent was questioning patient credibility (n = 51, 5%). After employing a semantic similarity-based search approach, 502 additional exemplars were added, increasing the number of low-frequency categories. All NLP models also showed improved performance, with Decision Trees demonstrating the greatest improvement (21%). ClinicalBERT outperformed other models, with the highest average F1-score of 0.78. Discussion Clinical BERT seems to most effectively capture the nuanced and context-dependent stigmatizing language found in obstetric clinical notes, demonstrating its potential clinical applications for real-time monitoring and alerts to prevent usages of stigmatizing language use and reduce healthcare bias. Future research should explore stigmatizing language in diverse geographic locations and clinical settings to further contribute to high-quality and equitable perinatal care. Conclusion ClinicalBERT effectively captures the nuanced stigmatizing language in obstetric clinical notes. Our semantic similarity-based search approach to rapidly extract additional exemplars enhanced the performances while reducing the need for labor-intensive annotation.Peer reviewe

1D Crystallographic Etching of Few-Layer WS2

Publisher Copyright: © 2024 Wiley-VCH GmbH.Layer number-dependent band structures and symmetry are vital for the electrical and optical characteristics of 2D transition metal dichalcogenides (TMDCs). Harvesting 2D TMDCs with tunable thickness and properties can be achieved through top-down etching and bottom-up growth strategies. In this study, a pioneering technique that utilizes the migration of in situ generated Na-W-S-O droplets to etch out 1D nanotrenches in few-layer WS2 is reported. 1D WS2 nanotrenches are successfully fabricated on the optically inert bilayer WS2, showing pronounced photoluminescence and second harmonic generation signals. Additionally, the modulation of inkjet-printed Na2WO4-Na2SO4 particles to switch between the etching and growth modes by manipulating the sulfur supply is demonstrated. This versatile approach enables the creation of 1D nanochannels on 2D TMDCs. The research presents exciting prospects for the top-down and bottom-up fabrication of 1D-2D mixed-dimensional TMDC nanostructures, expanding their use for electronic and optoelectronic applications.Peer reviewe

Pixel and Feature Transfer Fusion for Unsupervised Cross-Dataset Person Reidentification

| openaire: EC/H2020/101016775/EU//INTERVENERecently, unsupervised cross-dataset person reidentification (Re-ID) has attracted more and more attention, which aims to transfer knowledge of a labeled source domain to an unlabeled target domain. There are two common frameworks: one is pixel-alignment of transferring low-level knowledge, and the other is feature-alignment of transferring high-level knowledge. In this article, we propose a novel recurrent autoencoder (RAE) framework to unify these two kinds of methods and inherit their merits. Specifically, the proposed RAE includes three modules, i.e., a feature-transfer (FT) module, a pixel-transfer (PT) module, and a fusion module. The FT module utilizes an encoder to map source and target images to a shared feature space. In the space, not only features are identity-discriminative but also the gap between source and target features is reduced. The PT module takes a decoder to reconstruct original images with its features. Here, we hope that the images reconstructed from target features are in the source style. Thus, the low-level knowledge can be propagated to the target domain. After transferring both high- and low-level knowledge with the two proposed modules above, we design another bilinear pooling layer to fuse both kinds of knowledge. Extensive experiments on Market-1501, DukeMTMC-ReID, and MSMT17 datasets show that our method significantly outperforms either pixel-alignment or feature-alignment Re-ID methods and achieves new state-of-the-art results.Peer reviewe

IFRS 16 -standardin vaikutukset leasingin käyttöön ja investointeihin: Empiirinen tarkastelu eurooppalaisissa pörssiyrityksissä vuosina 2020–2023

This thesis examines the impact of IFRS 16 on corporate leasing practices and investment behavior. The aim is to investigate whether the balance sheet recognition of lease contracts has affected firms’ capital structure and investment decisions. The analysis is based on a panel dataset of European listed companies from 2019 to 2023. The data was collected from the Refinitiv database in March 2025. The study seeks to answer whether the adoption of IFRS 16 has reduced the use of leasing once the standard had been established, and whether the role of leasing as a means of financing investments has declined after its implementation. The analysis compares firms with high leasing intensity in 2019 to other firms. The empirical methods applied are Difference-in-Differences (DiD) and fixed effects panel regression. The results show that the volume of leasing decreased during 2021–2023 compared to 2020. Although leasing usage declined in general, the change was not clearly associated with firms’ prior dependence on leasing. Furthermore, the analysis found no statistically significant evidence that firms with high leasing intensity shifted notably from leasing to acquiring owned assets.Tässä tutkielmassa tarkastellaan IFRS 16 -standardin vaikutusta leasingin käyttöön ja investointikäyttäytymiseen. Tutkimuksen tavoitteena on selvittää, onko vuokrasopimusten käsittely taseessa muuttanut yritysten rahoitusrakennetta ja investointeja. Tutkimuksessa hyödynnetään eurooppalaisista pörssiyhtiöistä koostuvaa paneeliaineistoa vuosilta 2019–2023. Käytetty data on kerätty Refinitiv-tietokannasta maaliskuussa 2025. Tutkielma pyrkii vastaamaan siihen, onko IFRS 16- standardi vähentänyt yritysten leasingin käyttöä standardin vakiinnuttua ja onko vakiintumisen jälkeen leasingin käyttö investointien rahoitukseen vähentynyt. Tutkielmassa vertaillaan yrityksiä, joilla oli korkea leasingriippuvuus vuonna 2019, muihin yrityksiin. Tutkielman analyysit on tehty käyttäen erojen erotus (DiD – Difference-in-Differences) -menetelmää sekä kiinteiden vaikutusten paneeliregressiota. Tutkielman tulokset osoittavat, että leasingin määrä väheni vuosina 2021–2023 verrattuna vuoteen 2020. Vaikka leasing käyttö yleisesti väheni, muutos ei ollut selvästi sidoksissa yritysten aiempaan leasingriippuvuuteen. Tutkimuksen tuloksissa ei myöskään havaittu tilastollisesti merkitsevää näyttöä siitä, että korkean leasingriippuvuuden yritykset olisivat siirtyneet selvästi leasing sijaan omistetun omaisuuden hankkimiseen

Shrinkflaatio muotoilun inspiraationa materiaalitehokkuudelle

This thesis reinterprets shrinkflation as a design strategy to reduce material usage in plastic products while preserving their usability. Using a kitchen-knife handle as the case study, the work examines what level of material reduction can be achieved through geometric surface structuring without compromising usability. The study uses a multi-method approach that combines a literature review, computer-aided modelling, prototyping, life cycle assessment, and user testing. Twelve handle redesigns are made by nesting three indentation geometries (round, hexagonal, and linear) at two depths and two pattern densities on a constant baseline form. Material removal for each redesign is quantified in 3D-modelling and analytics software SolidWorks and translated into CO2-equivalent values with an Eco Audit tool. Usability is evaluated with user testing consisting of 20 participants who test the 3D-printed prototypes and rate comfort, control, and perceived cleanability. Collected data is visualized to see correlations and outliers. Results show that surface structuring removes 6 % of handle mass without largely affecting usability and cuts production-phase emissions by an identical proportion. This is achieved by a sparsely spaced, 1.5 mm-deep groove that provided a firm grip, use comfort and ease of cleaning. While deeper hexagonal textures improved control, they provoked discomfort and cleanability concerns. Life cycle assessment in a cradle-to-grave scope reveals that depending on the use case, the use phase emissions can overshadow the reductions, although the aggregated benefit of lightweighting scales linearly with high-volume manufacturing. The thesis demonstrates that mold-integrated textures can act as a disguised material-efficiency lever, delivering measurable environmental gains without compromising usability. The study recommends that designers should treat blank plastic surfaces as opportunities for emission savings; integrate hygiene constraints early in pattern selection; and combine material reduction with user-focused design strategies that reduce environmental impacts during the use phase. The findings extend resource-aware form-giving by contributing to the discussion with an example of a lightweighting system for solid plastic parts while maintaining usability.

AcademicRAG: Knowledge Graph Enhanced Retrieval-Augmented Generation for Academic Resource Discovery

This thesis presents AcademicRAG, a novel knowledge graph-enhanced framework for academic resource discovery that addresses critical limitations in traditional information retrieval systems. By integrating graph-based retrieval mechanisms with large language models, the framework significantly improves the capture, representation, and utilization of complex semantic relationships inherent in academic knowledge. The research introduces two key technical innovations: clue-guided keyword generation and subgraph-based retrieval, which together enhance query performance across diverse academic domains. Comprehensive evaluations demonstrate that AcademicRAG consistently outperforms existing state-of-the-art approaches in response comprehensiveness, diversity, and user empowerment. The practical implementation of a Course Discovery System validates the framework's utility in educational contexts, effectively addressing distinct information needs for both students and faculty. For students, the system provides personalized learning pathways and prerequisite analyses; for faculty, it offers curriculum optimization insights by identifying content overlaps and progression patterns across departmental boundaries. Despite notable achievements, AcademicRAG and its application acknowledges limitations in entity extraction consistency and relationship standardization, suggesting future work in hybrid extraction approaches and multimodal content integration. AcademicRAG represents a significant advancement toward more intuitive, context-aware academic information systems, enabling richer exploration of educational resources and more informed academic decision-making

Immersive VR-Driven Landscapes: Exploring Climate-Adaptive Ecosystem Design

This paper investigates the Icelandic turf house as a conceptual model for adaptive, climateresponsive design strategies explored through immersive narratives. The research integrates Virtual Reality (VR), point cloud technology, and diverse ecological datasets to establish a speculative framework for understanding and designing symbiotic systems. Leveraging the Terraforming Interface – a computational framework tailored for cross-scalar ecological exploration – this research transforms VR into an interactive medium for engaging with dynamic, multi-layered processes. High-resolution point clouds enriched with microbial, vegetative, and behavioral data allow for real-time exploration of ecological interdependencies within immersive environments. Narrative-driven VR scenarios visualize speculative futures, reimagining architecture as an active participant in ecological networks. By advancing a more-than-human perspective, this approach challenges static design paradigms, emphasizing resilience, cohabitation, and adaptive strategies for addressing climate change. The findings demonstrate the potential of architecture as a living, responsive system that bridges the divide between the built and unbuilt, offering pathways for innovation in sustainable and climate-adaptive design.Peer reviewe

Taiteen kandidaatin opinnäyte

Tässä opinnäytetyössä tarkastelen ja reflektoin omaa suhdettani vaatesuunnitteluun ja tekijyyteen miestenvaatemalliston kautta. Työn ytimessä on kysymys: miksi teen vaatteita? Vastausta haen tutkimalla omaa historiaani, arvojani ja työskentelytapojani suunnittelijana. Lähestyn aihetta intuitiivisen tekemisen, käsityöperinteen ja materiaalilähtöisen suunnittelun näkökulmasta. Taustatutkimuksessa syvennyn erityisesti suvun käsityöperinteeseen, jossa korostuvat niukkuuden aikojen kekseliäisyys, käytännöllisyys ja vaatteiden pitkä käyttöikä. Mummuni ja isomummuni rooli käsityötaitojen siirtäjinä on ollut ratkaiseva omaa kehitystäni ajatellen. Itseopiskelun, kokeilujen ja virheiden kautta olen kehittänyt oman käsitykseni merkityksellisestä tekemisestä. Opinnäytetyön produktiivinen osuus koostuu seitsemästä asukokonaisuudesta, joiden suunnittelussa hyödynnän itse valmistamiani kankaita, neuloksia ja perinteisiä räätälitekniikoita. Käsin tekeminen tarjoaa potentiaalin antaa vaatteille inhimillistä syvyyttä, mitä on mahdoton toistaa koneellisesti. Kirjallisessa osuudessa pohdin myös taiteen muodon ja sisällön välistä suhdetta, tekijyyden rehellisyyttä ja käsityön merkitystä nykyajan kulutuksellisen moraalirappion keskellä. Hyvä vaate ei ole minulle pelkkä käyttöesine vaan merkityksellinen objekti, jossa näkyy ja tuntuu ihmisen työ, ajattelu ja aika. Pyrin vaatteissani yksinkertaiseen rehelliseen ilmaisuun – vaatteisiin, jotka kantavat mukanaan sekä tarinaa että inhimillisyyttä