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Methodologism as a Philosophy of Knowing
No full textAbstract
Methodologism outlines a new pragmatist approach to knowing and meaning. While knowing is typically defined as a state of some kind, such as possessing a true justified belief, I shall propose that knowing can, in general, be defined as a correct way of doing. This view applies to both the sciences and more mundane ways of knowing in our various forms of life. Also in historiography, knowing is understood as doing. The main focus in the methodologist philosophy of historiography should be to identify good and responsible ways of maintaining and advancing the conversation about the past, without an expectation of a settlement to any one view about the past. We need to ask: What are epistemologically responsible ways of practicing historiography? More specifically, what are the conditions and rules under which claims in historiography may be made, accepted, or rejected.Abstract
Methodologism outlines a new pragmatist approach to knowing and meaning. While knowing is typically defined as a state of some kind, such as possessing a true justified belief, I shall propose that knowing can, in general, be defined as a correct way of doing. This view applies to both the sciences and more mundane ways of knowing in our various forms of life. Also in historiography, knowing is understood as doing. The main focus in the methodologist philosophy of historiography should be to identify good and responsible ways of maintaining and advancing the conversation about the past, without an expectation of a settlement to any one view about the past. We need to ask: What are epistemologically responsible ways of practicing historiography? More specifically, what are the conditions and rules under which claims in historiography may be made, accepted, or rejected
Multimodal data fusion for unobtrusive human physiological sensing
No full textAbstract
The increasing demand for continuous health monitoring, particularly in home environments, is driven by the demographic shift toward aging populations and the growing prevalence of individuals living alone. Traditional monitoring systems, often reliant on wearable devices or user-initiated actions, are limited by compliance, comfort, and accessibility. Unobtrusive technologies offer a solution by enabling remote sensing of physiological signals without requiring active user participation, providing continuous and passive monitoring while preserving comfort and autonomy.
This dissertation investigates unobtrusive physiological sensing for reliable human monitoring, focusing on multiple non-contact technologies, including RGB-D cameras, thermal imaging, and millimeter-wave radar. It proposes novel methods for fusing multimodal data to improve accuracy and robustness. To support this research, a multimodal dataset, OMuSense-23, was established, capturing respiratory and cardiac activities across different poses. This dataset serves both as a benchmark and as a foundation to evaluate challenges such as synchronization complexity, scalability, and ecological validity.
Findings demonstrate that combining multiple sensing modalities enhances monitoring performance, while they introduce challenges in data alignment, processing, and generalization to real-world conditions. The dissertation provides insights into designing and leveraging multimodal sensing frameworks, highlighting strategies for integrating handcrafted and learned features, self-supervised representation learning, and robust fusion techniques. This work contributes to scalable, interpretable, and reliable systems for unobtrusive physiological monitoring in home and assistive living environments. Original papers Lage Cañellas, M., Álvarez Casado, C., Nguyen, L., & Bordallo López, M. (2023). Depression recognition from facial videos: Preprocessing and scheduling choices hide the architectural contributions. Electronics Letters, 59(20), e12992. https://doi.org/10.1049/ell2.12992 https://doi.org/10.1049/ell2.12992 Self-archived version Cañellas, M. L., Álvarez Casado, C., Nguyen, L., & López, M. B. (2024). Estimating exercise-induced fatigue from thermal facial images. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2800–2804. https://doi.org/10.1109/ICASSP48485.2024.10447613 https://doi.org/10.1109/ICASSP48485.2024.10447613 Self-archived version Cañellas, M. L., Nguyen, L., Mukherjee, A., Casado, C. Á., Wu, X., Susarla, P., Sharifipour, S., Jayagopi, D. B., & López, M. B. (2024). Omusense-23: A multimodal dataset for contactless breathing pattern recognition and biometric analysis. arXiv. https://doi.org/10.48550/ARXIV.2407.06137 https://doi.org/10.48550/ARXIV.2407.06137 Lage Cañellas, M., Álvarez Casado, C., Nguyen, L., & Bordallo López, M. (2025). A self-supervised multimodal framework for 1D physiological data fusion in remote health monitoring. Information Fusion, 124, 103397. https://doi.org/10.1016/j.inffus.2025.103397 https://doi.org/10.1016/j.inffus.2025.103397 Self-archived version Cañellas, M. L., Casado, C. Á., Malin, M., Prencipe, N., Sharifipour, S., & López, M. B. (2025). Fusion of handcrafted and deep-learned cardiorespiratory features for breathing pattern classification. 2025 33rd European Signal Processing Conference (EUSIPCO), 1627–1631. https://doi.org/10.23919/EUSIPCO63237.2025.11226671 https://doi.org/10.23919/EUSIPCO63237.2025.11226671 Tiivistelmä
Kasvava tarve jatkuvalle terveydentilan seurannalle erityisesti kotiympäristöissä johtuu väestön ikääntymisestä sekä yksin asumisen yleistymisestä. Perinteiset seurantajärjestelmät, jotka usein perustuvat joko puettaviin laitteisiin tai käyttäjän tekemiin toimenpiteisiin, ovat rajoittuneita muun muassa vaatimustenmukaisuuden, mukavuuden ja saatavuuden näkökulmista. Huomaamattomat teknologiat tarjoavat ratkaisun mahdollistamalla fysiologisten signaalien etähavainnoinnin ilman käyttäjän aktiivista osallistumista ja tarjoavat näin jatkuvaa ja passiivista seurantaa säilyttäen samalla mukavuuden ja autonomian.
Tämä väitöskirja tutkii huomaamatonta fysiologista havainnointia osana ihmisten luotettavaa seurantaa keskittyen useisiin kosketuksettoman havainnoinnin teknologioihin, kuten RGB-D-kameroihin, lämpökamerakuvantamiseen ja millimetriaaltotutkaan. Tässä väitöskirjassa esitetään uusia menetelmiä multimodaalisen datan yhdistämiseen tarkkuuden ja luotettavuuden parantamiseksi. Tutkimusta varten on koottu multimodaalinen OMuSense-23-aineisto, joka sisältää hengitys- ja sydäntoiminnan mittauksia kehon eri asennoissa. Tämä aineisto toimii sekä vertailukohtana että perustana haasteiden, esimerkiksi synkronoinnin monimutkaisuuden, skaalautuvuuden ja ekologisen validiteetin, arvioinnille.
Tulokset osoittavat, että useiden havainnointi-tekniikoiden yhdistäminen parantaa seurantatarkkuutta, mutta tuo mukanaan haasteita liittyen datan kohdistukseen, prosessointiin ja yleistettävyyteen todellisissa olosuhteissa. Väitöskirja tarjoaa näkemyksiä multimodaalisten havainnointi-järjestelmien suunnitteluun ja hyödyntämiseen korostaen strategioita, jotka liittyvät käsin tehtyjen ja opittujen ominaisuuksien integroimiseen, itseohjautuvaan oppimiseen sekä kestäviin fuusiotekniikoihin. Tämä väitöskirja edistää skaalautuvien, tulkittavien ja luotettavien järjestelmien kehittämistä kodeissa ja avustetun asumisen ympäristöissä tehtävään huomaamattomaan seurantaan. Osajulkaisut Lage Cañellas, M., Álvarez Casado, C., Nguyen, L., & Bordallo López, M. (2023). Depression recognition from facial videos: Preprocessing and scheduling choices hide the architectural contributions. Electronics Letters, 59(20), e12992. https://doi.org/10.1049/ell2.12992 https://doi.org/10.1049/ell2.12992 Rinnakkaistallennettu versio Cañellas, M. L., Álvarez Casado, C., Nguyen, L., & López, M. B. (2024). Estimating exercise-induced fatigue from thermal facial images. ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2800–2804. https://doi.org/10.1109/ICASSP48485.2024.10447613 https://doi.org/10.1109/ICASSP48485.2024.10447613 Rinnakkaistallennettu versio Cañellas, M. L., Nguyen, L., Mukherjee, A., Casado, C. Á., Wu, X., Susarla, P., Sharifipour, S., Jayagopi, D. B., & López, M. B. (2024). Omusense-23: A multimodal dataset for contactless breathing pattern recognition and biometric analysis. arXiv. https://doi.org/10.48550/ARXIV.2407.06137 https://doi.org/10.48550/ARXIV.2407.06137 Lage Cañellas, M., Álvarez Casado, C., Nguyen, L., & Bordallo López, M. (2025). A self-supervised multimodal framework for 1D physiological data fusion in remote health monitoring. Information Fusion, 124, 103397. https://doi.org/10.1016/j.inffus.2025.103397 https://doi.org/10.1016/j.inffus.2025.103397 Rinnakkaistallennettu versio Cañellas, M. L., Casado, C. Á., Malin, M., Prencipe, N., Sharifipour, S., & López, M. B. (2025). Fusion of handcrafted and deep-learned cardiorespiratory features for breathing pattern classification. 2025 33rd European Signal Processing Conference (EUSIPCO), 1627–1631. https://doi.org/10.23919/EUSIPCO63237.2025.11226671 https://doi.org/10.23919/EUSIPCO63237.2025.11226671 Academic dissertation to be presented with the assent of the Doctoral Programme Committee of Information Technology and Electrical Engineering of the University of Oulu for public defence in the Oulun Puhelin auditorium (L5), Linnanmaa, on 6 February 2026, at 12 noonAbstract
The increasing demand for continuous health monitoring, particularly in home environments, is driven by the demographic shift toward aging populations and the growing prevalence of individuals living alone. Traditional monitoring systems, often reliant on wearable devices or user-initiated actions, are limited by compliance, comfort, and accessibility. Unobtrusive technologies offer a solution by enabling remote sensing of physiological signals without requiring active user participation, providing continuous and passive monitoring while preserving comfort and autonomy.
This dissertation investigates unobtrusive physiological sensing for reliable human monitoring, focusing on multiple non-contact technologies, including RGB-D cameras, thermal imaging, and millimeter-wave radar. It proposes novel methods for fusing multimodal data to improve accuracy and robustness. To support this research, a multimodal dataset, OMuSense-23, was established, capturing respiratory and cardiac activities across different poses. This dataset serves both as a benchmark and as a foundation to evaluate challenges such as synchronization complexity, scalability, and ecological validity.
Findings demonstrate that combining multiple sensing modalities enhances monitoring performance, while they introduce challenges in data alignment, processing, and generalization to real-world conditions. The dissertation provides insights into designing and leveraging multimodal sensing frameworks, highlighting strategies for integrating handcrafted and learned features, self-supervised representation learning, and robust fusion techniques. This work contributes to scalable, interpretable, and reliable systems for unobtrusive physiological monitoring in home and assistive living environments.Tiivistelmä
Kasvava tarve jatkuvalle terveydentilan seurannalle erityisesti kotiympäristöissä johtuu väestön ikääntymisestä sekä yksin asumisen yleistymisestä. Perinteiset seurantajärjestelmät, jotka usein perustuvat joko puettaviin laitteisiin tai käyttäjän tekemiin toimenpiteisiin, ovat rajoittuneita muun muassa vaatimustenmukaisuuden, mukavuuden ja saatavuuden näkökulmista. Huomaamattomat teknologiat tarjoavat ratkaisun mahdollistamalla fysiologisten signaalien etähavainnoinnin ilman käyttäjän aktiivista osallistumista ja tarjoavat näin jatkuvaa ja passiivista seurantaa säilyttäen samalla mukavuuden ja autonomian.
Tämä väitöskirja tutkii huomaamatonta fysiologista havainnointia osana ihmisten luotettavaa seurantaa keskittyen useisiin kosketuksettoman havainnoinnin teknologioihin, kuten RGB-D-kameroihin, lämpökamerakuvantamiseen ja millimetriaaltotutkaan. Tässä väitöskirjassa esitetään uusia menetelmiä multimodaalisen datan yhdistämiseen tarkkuuden ja luotettavuuden parantamiseksi. Tutkimusta varten on koottu multimodaalinen OMuSense-23-aineisto, joka sisältää hengitys- ja sydäntoiminnan mittauksia kehon eri asennoissa. Tämä aineisto toimii sekä vertailukohtana että perustana haasteiden, esimerkiksi synkronoinnin monimutkaisuuden, skaalautuvuuden ja ekologisen validiteetin, arvioinnille.
Tulokset osoittavat, että useiden havainnointi-tekniikoiden yhdistäminen parantaa seurantatarkkuutta, mutta tuo mukanaan haasteita liittyen datan kohdistukseen, prosessointiin ja yleistettävyyteen todellisissa olosuhteissa. Väitöskirja tarjoaa näkemyksiä multimodaalisten havainnointi-järjestelmien suunnitteluun ja hyödyntämiseen korostaen strategioita, jotka liittyvät käsin tehtyjen ja opittujen ominaisuuksien integroimiseen, itseohjautuvaan oppimiseen sekä kestäviin fuusiotekniikoihin. Tämä väitöskirja edistää skaalautuvien, tulkittavien ja luotettavien järjestelmien kehittämistä kodeissa ja avustetun asumisen ympäristöissä tehtävään huomaamattomaan seurantaan
Integration of electrolysers into Net Zero Energy Ecosystems
No full textDue to the gradual removing of fossil fuels from energy systems, new technologies are being developed for ensuring sustainable future. Net Zero Energy Ecosystem (NZEE) concept, being developed by Sumitomo SHI FW Energia Oy, aims to achieve zero or even negative net amount of carbon emissions in integrated energy systems. Hydrogen is also in focus of interest in the industry due to its ability to carry and store renewable energy and as a valuable feedstock for numerous chemical processes. Utilizing water electrolysis to produce hydrogen it is possible to achieve carbon emission free hydrogen production if combined with renewable energy source.
The focus of this thesis is on the integration of three most advanced electrolyser types into net zero energy ecosystem. Alkaline, proton exchange membrane and solid oxide electrolysers are considered in this study. The goal of the thesis is to determine key performance indices and evaluate the roles of the three main electrolysers in the NZEE. Models, built in Aspen Plus software, were utilised in the assessment. To simulate the dynamic behaviour of the core of the balance of plant (BoP) of the selected electrolyser, a thermodynamic state-space model is built in MATLAB. The topic of interest for the thermodynamic model is the solid oxide electrolyser.
The results obtained from the models showed that the solid oxide electrolyser was the preferrable technology for the integrating electrolysers into net zero energy ecosystem in the selected configuration. Modelling of the thermodynamic behaviour of the BoP was successful,and the model provided stable transient responses due to modification on the boundary conditions
Construction perspectives in the design of nature-based stormwater structures
No full textTämän diplomityön tavoitteena oli selvittää hulevesi- ja työmaavesienhallintarakenteiden toteutuksen (suunnittelusta kunnossapitoon) haasteita ja käytänteitä sekä sitä, kuinka toteutusprosessia voitaisiin kehittää jatkossa, jotta toteutetut luontopohjaiset rakenteet olisivat entistä toimivampia. Työn aineisto muodostui kirjallisuudesta sekä toteutuneesta kyselystä ja työpajasta. Menetelmien avulla saatiin kerättyä Oulussa toimivilta rakennuttajilta, suunnitteluttajilta ja urakoitsijoilta näkemyksiä nykyisistä ongelmakohdista ja keskeisistä kehittämistarpeista sekä niiden ratkaisuehdotuksista.
Tulokset osoittavat, että koko toteutusprosessissa on kehitettävää ja yhtenäistettävää. Työssä tunnistettiin, että rakentamisjärjestykseen tulisi ottaa enemmän kantaa suunnitelmissa ja pyrkiä rakentamaan rakenteet mahdollisimman valmiiksi rakentamisen alkuvaiheessa. Myös toteutusta palveleva informaatio tulisi huomioida jo suunnittelussa paremmin sekä yhteistyötä kehittää. Lisäksi työmaavesienhallinnansuunnitteluun, rakenteiden työmaa-aikaiseen huoltoon sekä tiedonhallintaan tulee kiinnittää huomiota enemmän ja laatia toimivia menetelmiä näiden vaiheiden kehittämiseen.
Prosessin kehittämiseksi, työssä tärkeimpinä suosituksina esitetään rakentamisjärjestyksen paremmuusjärjestyksen käyttöä, kaaviokuvan sisällyttämistä, tarkastuslistan hyödyntämistä, osaamisen laajentamista, kunnossapitokorttien laatimista ja tiedonhallintaprosessin kehittämistä. Varsinkin alkuvaiheessa suosituksien käyttöönotto voi kasvattaa kustannuksia, joten mahdollisissa pilottikohteissa olisi hyödyllistä selvittää suositusten konkreettiset vaikutukset suhteessa niiden aiheuttamiin kustannuksiin.The aim of this Diploma thesis was to investigate the challenges, practices and how the implementation process (from design to maintenance) of stormwater and construction site water management structures could be improved in the future to make the implemented nature-based structures more effective. The material for the work consisted of literature as well as completed survey and workshop. Through these methods, insights were gathered from developers, designers, and contractors operating in Oulu about current problem areas, key development needs, and their proposed solutions.
The results indicate that the entire implementation process needs development and standardization. The study identified that more attention should be paid to the order of construction in the plans and the structures should be built as completely as possible in the early stages of construction. Additionally, information that serves the implementation should be better considered in the planning stage and cooperation should be improved. More focus is also needed on the planning of construction site water management, maintenance of structures during the construction period, and information management, and effective methods should be devised to improve these phases.
For process improvement, the main recommendations presented in the work include the use of priority order for construction, the inclusion of schematic diagram, the utilization of a checklist, the creation of maintenance cards, and the development of the information management process. Especially in the initial phase, the adoption of recommendation may increase the costs, so it would be useful to investigate the concrete impacts of the recommendations in relation to the cost they incur in potential pilot projects
The effect of air pollution and household environmental indicators on anemia status among under-five children in low-middle income countries: exploring potential machine learning applications on demographic and health surveys
No full textAbstract
Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in which the prevalence of anemia is persistently high. This study aimed to assess the effects of air pollution and household environmental indicators on anemia among children aged 6–59 months using machine learning algorithms. The Demographic and Health Survey (DHS) datasets from 45 LMICs were linked with the satellite-derived estimates of annual average particulate matter (PM2.5) and nitrogen dioxide (NO2) based on children’s area of residence. The modified Poisson regression model was used to assess the association between exposure to air pollutants, household environmental indicators, and anemia status of children. Machine learning algorithms (MLA) such as logistic regression, Ridge, Lasso, elastic net, Artificial Neural Network, Naïve Bayes, Boosting, and Random Forest were used for predicting the anemia status. We randomly split the dataset into two (train/test), and the model performance was evaluated using sensitivity, specificity and the area under the receiver operating characteristic curve (AU-ROC). The study included 177,251 under-five children, of which 99,290 (56%) were anemic and varied across countries ranging from 16% (Armenia) to 81% (Mali). A child who lived in areas with a PM2.5 concentration above the WHO recommended guidelines has a 26% higher risk of being anemic (aPR = 1.26; 95% CI 1.22–1.30) and a child from households having clean fuel for cooking, improved water, and improved sanitation have 24%, 3%, and 13% lower risk of being anemic. The random forest MLA achieved the best classification accuracy of 68%, specificity of 54%, sensitivity of 79% and AUC of 74%. The MLA is more effective than traditional analytical approaches in predicting anemia status. The RF revealed that the age of the child, wet day of the environment, the location of the child, and PM2.5 are the most important features to predict the anemia status of a child.Abstract
Exposure to air pollution has been associated with anemia in children, but little effort has been made in low- and middle-income countries (LMICs) in which the prevalence of anemia is persistently high. This study aimed to assess the effects of air pollution and household environmental indicators on anemia among children aged 6–59 months using machine learning algorithms. The Demographic and Health Survey (DHS) datasets from 45 LMICs were linked with the satellite-derived estimates of annual average particulate matter (PM2.5) and nitrogen dioxide (NO2) based on children’s area of residence. The modified Poisson regression model was used to assess the association between exposure to air pollutants, household environmental indicators, and anemia status of children. Machine learning algorithms (MLA) such as logistic regression, Ridge, Lasso, elastic net, Artificial Neural Network, Naïve Bayes, Boosting, and Random Forest were used for predicting the anemia status. We randomly split the dataset into two (train/test), and the model performance was evaluated using sensitivity, specificity and the area under the receiver operating characteristic curve (AU-ROC). The study included 177,251 under-five children, of which 99,290 (56%) were anemic and varied across countries ranging from 16% (Armenia) to 81% (Mali). A child who lived in areas with a PM2.5 concentration above the WHO recommended guidelines has a 26% higher risk of being anemic (aPR = 1.26; 95% CI 1.22–1.30) and a child from households having clean fuel for cooking, improved water, and improved sanitation have 24%, 3%, and 13% lower risk of being anemic. The random forest MLA achieved the best classification accuracy of 68%, specificity of 54%, sensitivity of 79% and AUC of 74%. The MLA is more effective than traditional analytical approaches in predicting anemia status. The RF revealed that the age of the child, wet day of the environment, the location of the child, and PM2.5 are the most important features to predict the anemia status of a child
Innovative mix design of lightweight porcelainised matrix for building comfort: pore - network and microstructures
No full textAbstract
Controlling pore structure gives ceramic products particular beneficial features such as low thermal conductivity, high chemical and mechanical resistance, or weight reduction. In this study, a novel class of ceramic material was produced with raw mixtures prepared with varying proportions of powdered limestone (1 to 5 wt.%) as a modifier and pore-forming agent on pegmatite and syenite-nepheline-based formulations. The ceramics were characterised using a variety of procedures and analytical techniques after being sintered at 1125 to 1225 °C under a fast-sintering rate of 25 °C/min. The results revealed that, using fast and controlled sintering, the proper addition of limestone into the pegmatite and nepheline syenite-based matrix allowed for the development of controlled porosity (formation of macro and meso‑pores), resulting in a reduced material density (1.9 – 2.1 g/cm3). Moreover, despite their good mechanical properties (flexural strength of 54 – 72 MPa and compressive strength of 70 – 150 MPa), the synthesised ceramics exhibited thermal conductivity performance ranging between 0.4562 and 0.5539 Wm-1K-1. Based on the obtained functional properties, the produced high-strength porous ceramics could act as a potential candidate for thermal building materials applications.Abstract
Controlling pore structure gives ceramic products particular beneficial features such as low thermal conductivity, high chemical and mechanical resistance, or weight reduction. In this study, a novel class of ceramic material was produced with raw mixtures prepared with varying proportions of powdered limestone (1 to 5 wt.%) as a modifier and pore-forming agent on pegmatite and syenite-nepheline-based formulations. The ceramics were characterised using a variety of procedures and analytical techniques after being sintered at 1125 to 1225 °C under a fast-sintering rate of 25 °C/min. The results revealed that, using fast and controlled sintering, the proper addition of limestone into the pegmatite and nepheline syenite-based matrix allowed for the development of controlled porosity (formation of macro and meso‑pores), resulting in a reduced material density (1.9 – 2.1 g/cm3). Moreover, despite their good mechanical properties (flexural strength of 54 – 72 MPa and compressive strength of 70 – 150 MPa), the synthesised ceramics exhibited thermal conductivity performance ranging between 0.4562 and 0.5539 Wm-1K-1. Based on the obtained functional properties, the produced high-strength porous ceramics could act as a potential candidate for thermal building materials applications
Portable and label-free optical detection of sweat glucose using functionalized plasmonic nanopillar array
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Continuous glucose monitoring (CGM) is vital for diabetes care, but current invasive electrochemical sensors of blood glucose often cause potential infection and skin irritation. Non-invasive sensors in sweat glucose are promising alternatives but limited by low sensitivity and poor compatibility with complex sweat environments, because the sweat glucose has concentrations of 20 – 600 μmol/L and are 100-fold more dilute than the blood glucose. Here, we report a portable optical sensing system that integrates an optical watch prototype with functionalized plasmonic silver-coated silicon nanopillars substrate for non-invasive and label-free glucose detection in sweat. The nanopillar sensor with wide-range plasmonic hot spots is functionalized with 4-mercaptophenylboronic acid for selective glucose capture and optical signal transduction through both Raman scattering and plasmonic detection. The optical watch system has a compact LED illumination at 623–660 nm and wireless transmission of data to a smartphone application. Significantly, the whole system demonstrated excellent sensitivity down to 22 μmol/L and high selectivity in detecting glucose in artificial sweat, which were validated by human sweat samples to confirm its applicability in real-life scenarios. Our study offers a promising portable and non-invasive alternative to traditional CGM and highlights the potential of integrating nanophotonic sensors with wearable platforms for continuous health monitoring and personalized medicine.Abstract
Continuous glucose monitoring (CGM) is vital for diabetes care, but current invasive electrochemical sensors of blood glucose often cause potential infection and skin irritation. Non-invasive sensors in sweat glucose are promising alternatives but limited by low sensitivity and poor compatibility with complex sweat environments, because the sweat glucose has concentrations of 20 – 600 μmol/L and are 100-fold more dilute than the blood glucose. Here, we report a portable optical sensing system that integrates an optical watch prototype with functionalized plasmonic silver-coated silicon nanopillars substrate for non-invasive and label-free glucose detection in sweat. The nanopillar sensor with wide-range plasmonic hot spots is functionalized with 4-mercaptophenylboronic acid for selective glucose capture and optical signal transduction through both Raman scattering and plasmonic detection. The optical watch system has a compact LED illumination at 623–660 nm and wireless transmission of data to a smartphone application. Significantly, the whole system demonstrated excellent sensitivity down to 22 μmol/L and high selectivity in detecting glucose in artificial sweat, which were validated by human sweat samples to confirm its applicability in real-life scenarios. Our study offers a promising portable and non-invasive alternative to traditional CGM and highlights the potential of integrating nanophotonic sensors with wearable platforms for continuous health monitoring and personalized medicine
The effect of scrap originating trace elements on the properties of low alloyed steels
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The present intention to reach fossil-free steel manufacturing will inevitably result in an increase in the use of steel scrap as a raw material for steel production. Consequently, the amounts of elements, seen as impurities, will increase in steels. This has already been seen in electric arc furnace (EAF) processed steels, where the Cu and Sn levels have doubled in some cases after 1980’s. This may cause problems, as it is well-known, that some impurity elements have harmful effects on the properties of steel. This has been widely studied in low-alloy steels containing chromium and molybdenum which are widely used in components for the petroleum and electrical power generation applications. However, limited number of studies have been performed on formable steel grades, and the published reports/articles have mostly concentrated on the effects of P and B. Thus, there is still a need to understand the roles of other impurity elements. In the present study, a formable C-Mn steels containing additions (either individually or in combination) of Cu and Sn is investigated. The samples were cold rolled and annealed following typical time-temperature profiles of modern continuous annealing lines. Mechanical and forming properties (incl. bending and cupping tests) are determined as well as elemental profile analysis is conducted. The results identify that minor additions of impurity elements, in this case Cu and Sn, does not affect the mechanical and forming properties of low alloyed formable steel grades considerably.Abstract
The present intention to reach fossil-free steel manufacturing will inevitably result in an increase in the use of steel scrap as a raw material for steel production. Consequently, the amounts of elements, seen as impurities, will increase in steels. This has already been seen in electric arc furnace (EAF) processed steels, where the Cu and Sn levels have doubled in some cases after 1980’s. This may cause problems, as it is well-known, that some impurity elements have harmful effects on the properties of steel. This has been widely studied in low-alloy steels containing chromium and molybdenum which are widely used in components for the petroleum and electrical power generation applications. However, limited number of studies have been performed on formable steel grades, and the published reports/articles have mostly concentrated on the effects of P and B. Thus, there is still a need to understand the roles of other impurity elements. In the present study, a formable C-Mn steels containing additions (either individually or in combination) of Cu and Sn is investigated. The samples were cold rolled and annealed following typical time-temperature profiles of modern continuous annealing lines. Mechanical and forming properties (incl. bending and cupping tests) are determined as well as elemental profile analysis is conducted. The results identify that minor additions of impurity elements, in this case Cu and Sn, does not affect the mechanical and forming properties of low alloyed formable steel grades considerably
Do I have to wear mud pants? Mud pants as material agent in Finnish preschool
No full textAbstract
Mud pants have protected Finnish preschool children from dirt and water for many years. However, children do not like to wear them and educators in preschools feel that mud pants cause hard work. This contradiction made us wonder with mud pants. Drawing on relational–material approaches, we understand mud pants as material agent and ask the following question: How mud pants act as material agent in everyday relations in preschool? Our wondering showed that mud pants act as material agent since they create different actions within non-human and human relations. Children in their mud pants strengthen the discourse of happy, clean and healthy outdoor child. However, mud pants limit children’s bodies and cause discomfort, making it hard for them to perform happy childhoods. We argue that it is necessary to think with mud pants and other material agents in preschool to make the material discourses more visible.Abstract
Mud pants have protected Finnish preschool children from dirt and water for many years. However, children do not like to wear them and educators in preschools feel that mud pants cause hard work. This contradiction made us wonder with mud pants. Drawing on relational–material approaches, we understand mud pants as material agent and ask the following question: How mud pants act as material agent in everyday relations in preschool? Our wondering showed that mud pants act as material agent since they create different actions within non-human and human relations. Children in their mud pants strengthen the discourse of happy, clean and healthy outdoor child. However, mud pants limit children’s bodies and cause discomfort, making it hard for them to perform happy childhoods. We argue that it is necessary to think with mud pants and other material agents in preschool to make the material discourses more visible