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Fabrication of flame-retardant and water-resistant nanopapers through electrostatic complexation of phosphorylated cellulose nanofibers and chitin nanocrystals
No full textAbstract
Biogenic, sustainable two-dimensional architectures, such as films and nanopapers, have garnered considerable interest because of their low carbon footprint, biodegradability, advanced optical/mechanical characteristics, and diverse potential applications. Here, bio-based nanopapers with tailored characteristics were engineered by the electrostatic complexation of oppositely charged colloidal phosphorylated cellulose nanofibers (P-CNFs) and deacetylated chitin nanocrystals (ChNCs). The electrostatic interaction between anionic P-CNFs and cationic ChNCs enhanced the stretchability and water stability of the nanopapers. Correspondingly, they exhibited a wet tensile strength of 17.7 MPa after 24 h of water immersion. Furthermore, the nanopapers exhibited good thermal stability and excellent self-extinguishing behavior, triggered by both phosphorous and nitrogen. These features make the nanopapers sustainable and promising structures for application in advanced fields, such as optoelectronics.Abstract
Biogenic, sustainable two-dimensional architectures, such as films and nanopapers, have garnered considerable interest because of their low carbon footprint, biodegradability, advanced optical/mechanical characteristics, and diverse potential applications. Here, bio-based nanopapers with tailored characteristics were engineered by the electrostatic complexation of oppositely charged colloidal phosphorylated cellulose nanofibers (P-CNFs) and deacetylated chitin nanocrystals (ChNCs). The electrostatic interaction between anionic P-CNFs and cationic ChNCs enhanced the stretchability and water stability of the nanopapers. Correspondingly, they exhibited a wet tensile strength of 17.7 MPa after 24 h of water immersion. Furthermore, the nanopapers exhibited good thermal stability and excellent self-extinguishing behavior, triggered by both phosphorous and nitrogen. These features make the nanopapers sustainable and promising structures for application in advanced fields, such as optoelectronics
Productivity prediction of a spherical distiller using a machine learning model and triangulation topology aggregation optimizer
No full textAbstract
Solar stills offer a sustainable and environmentally friendly solution to water scarcity in remote areas, but their limited productivity hinders their wider adoption. This study proposes innovative modifications to the spherical solar distiller to address this challenge. We introduce a rotating spherical ball within the distiller and investigate its impact on productivity at various speeds (0–2 rpm) with and without a wick. Additionally, we explore the effectiveness of preheating feed water to different temperatures (45–70 °C) and its interaction with the rotating ball mechanism. Moreover, six machine learning models were employed to predict the water productivity of the distillers under different working conditions. The employed models were standalone long short-term memory (LSTM), LSTM optimized by reptile search algorithm, LSTM optimized by grey wolf optimizer, LSTM optimized by dwarf mongoose optimization algorithm, LSTM optimized by manta ray foraging optimizer, LSTM optimized by triangulation topology aggregation optimizer. The results showcased that with an optimal rotation speed of 0.5 rpm and 1 rpm for configurations with and without wick, respectively, we achieved productivity increases of 62 % and 55 %. Notably, preheating feed water to 65 °C further boosted the new distiller performance, surpassing the conventional solar still by 91 %, achieving an impressive output of 6000–6200 mL/m2.day compared to 3000–3250 mL/m2.day for the conventional distiller. Moreover, the thermal efficiency of the new distiller configuration reached 62 %, almost doubling that of the conventional distiller (32 %). Moreover, the triangulation topology aggregation optimizer outperformed other models in predicting water productivity with a high R2 range of 0.953–0.999.Abstract
Solar stills offer a sustainable and environmentally friendly solution to water scarcity in remote areas, but their limited productivity hinders their wider adoption. This study proposes innovative modifications to the spherical solar distiller to address this challenge. We introduce a rotating spherical ball within the distiller and investigate its impact on productivity at various speeds (0–2 rpm) with and without a wick. Additionally, we explore the effectiveness of preheating feed water to different temperatures (45–70 °C) and its interaction with the rotating ball mechanism. Moreover, six machine learning models were employed to predict the water productivity of the distillers under different working conditions. The employed models were standalone long short-term memory (LSTM), LSTM optimized by reptile search algorithm, LSTM optimized by grey wolf optimizer, LSTM optimized by dwarf mongoose optimization algorithm, LSTM optimized by manta ray foraging optimizer, LSTM optimized by triangulation topology aggregation optimizer. The results showcased that with an optimal rotation speed of 0.5 rpm and 1 rpm for configurations with and without wick, respectively, we achieved productivity increases of 62 % and 55 %. Notably, preheating feed water to 65 °C further boosted the new distiller performance, surpassing the conventional solar still by 91 %, achieving an impressive output of 6000–6200 mL/m2.day compared to 3000–3250 mL/m2.day for the conventional distiller. Moreover, the thermal efficiency of the new distiller configuration reached 62 %, almost doubling that of the conventional distiller (32 %). Moreover, the triangulation topology aggregation optimizer outperformed other models in predicting water productivity with a high R2 range of 0.953–0.999
Siirteen merkitys autologisissa kantasolusiirroissa
No full textVerestä kerätyn autologisen kantasolusiirteen tärkeimpänä ominaisuutena on pidetty CD34-positiivisten (CD34+) solujen määrää, joka vaikuttaa veriarvojen korjaantumiseen intensiivihoidon jälkeen. Osassa tutkimuksista siirteen suurempi CD34+-solujen määrä on korreloinut myös paremman ennusteen kanssa. Siirteessä on paljon enemmän muita kuin CD34+-ssoluja, kuten erilaisia lymfosyyttejä, antigeenejä esitteleviä soluja ja luonnollisia tappajasoluja. Näiden solujen suurempi määrä siirteessä näyttää liittyvän sekä varhaisempaan immunologiseen toipumiseen että parempaan pitkäaikaisennusteeseen. Suurempi lymfosyyttimäärä potilaalle palautettavassa siirteessä saattaisi parantaa kantasolusiirtohoidon pitkäaikaistuloksia. Lisää tutkimuksia kantasolujen mobilisaatiosta ja siirteen keruusta tarvitaan erityisesti myeloomapotilaiden osalta, sillä siirteen lymfaattisten solujen määrän merkityksestä heille on vähemmän tietoa kuin merkityksestä lymfoomapotilaille.Verestä kerätyn autologisen kantasolusiirteen tärkeimpänä ominaisuutena on pidetty CD34-positiivisten (CD34+) solujen määrää, joka vaikuttaa veriarvojen korjaantumiseen intensiivihoidon jälkeen. Osassa tutkimuksista siirteen suurempi CD34+-solujen määrä on korreloinut myös paremman ennusteen kanssa. Siirteessä on paljon enemmän muita kuin CD34+-ssoluja, kuten erilaisia lymfosyyttejä, antigeenejä esitteleviä soluja ja luonnollisia tappajasoluja. Näiden solujen suurempi määrä siirteessä näyttää liittyvän sekä varhaisempaan immunologiseen toipumiseen että parempaan pitkäaikaisennusteeseen. Suurempi lymfosyyttimäärä potilaalle palautettavassa siirteessä saattaisi parantaa kantasolusiirtohoidon pitkäaikaistuloksia. Lisää tutkimuksia kantasolujen mobilisaatiosta ja siirteen keruusta tarvitaan erityisesti myeloomapotilaiden osalta, sillä siirteen lymfaattisten solujen määrän merkityksestä heille on vähemmän tietoa kuin merkityksestä lymfoomapotilaille
Knowledge Workers Mental Workload Classification Using Voting Ensemble Learning Framework
No full textAbstract
In recent years, the mental workload of knowledge workers has received heightened attention, driven by its significant influence on productivity and its critical implications for overall well-being and mental health. Knowledge workers often face high mental demands, particularly in planning and coordination tasks, leading to stress and reduced efficiency. While several machine learning (ML) models have been employed to predict mental workload, their accuracy has remained below optimal. This study introduces an ensemble classification model that combines K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF) through a voting ensemble algorithm to classify the mental workload of knowledge workers. Utilizing the SWELL-KW dataset, including physiological and subjective data, the proposed model achieved a 97% accuracy rate, outperforming individual ML models. These findings indicate that the ensemble model offers a promising approach to enhancing the prediction of mental workload, providing companies with a powerful tool to address mental health challenges in the workplace better.Abstract
In recent years, the mental workload of knowledge workers has received heightened attention, driven by its significant influence on productivity and its critical implications for overall well-being and mental health. Knowledge workers often face high mental demands, particularly in planning and coordination tasks, leading to stress and reduced efficiency. While several machine learning (ML) models have been employed to predict mental workload, their accuracy has remained below optimal. This study introduces an ensemble classification model that combines K-Nearest Neighbors (KNN), Support Vector Machine (SVM), and Random Forest (RF) through a voting ensemble algorithm to classify the mental workload of knowledge workers. Utilizing the SWELL-KW dataset, including physiological and subjective data, the proposed model achieved a 97% accuracy rate, outperforming individual ML models. These findings indicate that the ensemble model offers a promising approach to enhancing the prediction of mental workload, providing companies with a powerful tool to address mental health challenges in the workplace better
Comparing Traditional Book Wisdom with Large Language Model’s Guidance on Time and Stress Management
No full textAbstract
The high prevalence of deteriorating mental health among university students, driven by stress, is a pressing concern. One significant stressor is poor time management, which directly affects students’ academic success and overall well-being. Despite providing counseling services and time management resources, the scale of the problem is causing academic institutions to fall short of meeting the demand. To alleviate this situation, this study seeks to evaluate the role of scalable systems like Large Language Model (LLM) based chatbots. The focus of the study is to compare how users perceive stress and time management advice generated by a LLM versus that extracted from a book authored by an expert. The study utilized GPT-4, a leading LLM, whose advice was evaluated by seventy participants. These participants perceived GPT-4’s advice as more practical and better explained compared to the book’s recommendations. For practicality, GPT-4’s advice scored better with 73% rating it as practical or highly practical versus only 68% giving that rating for the book’s advice (t = 2.87, p < 0.01). Similarly, for the well-explained variable, 88% of LLM’s guidance were rated as clear or very clear, exceeding the book’s 79% (t = 4.437, p < 0.01). This study highlights AI’s ability in giving effective advice that can be extended to a full coaching engagement. Such capabilities would not only augment human coaching but also address scalability challenge and expand accessibility.Abstract
The high prevalence of deteriorating mental health among university students, driven by stress, is a pressing concern. One significant stressor is poor time management, which directly affects students’ academic success and overall well-being. Despite providing counseling services and time management resources, the scale of the problem is causing academic institutions to fall short of meeting the demand. To alleviate this situation, this study seeks to evaluate the role of scalable systems like Large Language Model (LLM) based chatbots. The focus of the study is to compare how users perceive stress and time management advice generated by a LLM versus that extracted from a book authored by an expert. The study utilized GPT-4, a leading LLM, whose advice was evaluated by seventy participants. These participants perceived GPT-4’s advice as more practical and better explained compared to the book’s recommendations. For practicality, GPT-4’s advice scored better with 73% rating it as practical or highly practical versus only 68% giving that rating for the book’s advice (t = 2.87, p < 0.01). Similarly, for the well-explained variable, 88% of LLM’s guidance were rated as clear or very clear, exceeding the book’s 79% (t = 4.437, p < 0.01). This study highlights AI’s ability in giving effective advice that can be extended to a full coaching engagement. Such capabilities would not only augment human coaching but also address scalability challenge and expand accessibility
Exploring the Core of Emotional Intelligence in Healthcare Leadership: A Concept Analysis
No full textAbstract
Aim:
To define and clarify the concept of emotional intelligence in healthcare leadership.
Design:
Walker and Avant's concept analysis model.
Methods:
The study was conducted using Walker and Avant's concept analysis model. In the search of the relevant literature, the Joanna Briggs Institute's methodology and search protocol for scoping reviews were applied. Searches were conducted in May 2023 with no time or geographical limits on Scopus, CINAHL, ProQuest, the Web of Science, Medic and Mednar and 42 studies were included. The data were analysed using narrative synthesis by categorising results using the steps of concept analysis.
Results:
Concept analysis identified defining attributes of emotional intelligence in healthcare leadership, including leadership qualities, management competencies, and sets of leadership styles which were related to supportive and transformational leadership behaviour. The antecedents were socio-demographic factors, well-being, and workplace resources. Finally, employee-, manager-, organisation- and patient-related consequences were identified, such as the well-being of both employees and managers, organisational performance and patient care quality.
Conclusions:
Emotional intelligence in healthcare leadership contributes to better performing organisations, as emotionally capable leaders can inspire and empower their employees. Holistic management of organisational duties and people-oriented leadership is a crucial resource in healthcare organisations. Well-being and workplace resources can be vitally important for leaders to manifest emotional intelligence in their work.
Implications for Practice and Research:
Emotional intelligence can contribute to efficient leadership behaviour and have positive outcomes at the employee, manager, organisation and patient levels. Therefore, emotional intelligence should be addressed in leadership education, training programmes and recruitment procedures. Finally, policymakers should be encouraged to acknowledge the role of sufficient resources in health care to ensure effective leadership.
Impact:
Emotional intelligence is a widely studied concept in the healthcare field. However, thorough conceptualisation regarding emotional intelligence in healthcare leadership has been lacking. Conceptualising this phenomenon was therefore outlined, providing a deeper understanding of the concept. The findings can be utilised in healthcare leadership development and research.
Reporting Method:
N/A.
Patient or Public Contribution
No patient or public contribution.Abstract
Aim:
To define and clarify the concept of emotional intelligence in healthcare leadership.
Design:
Walker and Avant's concept analysis model.
Methods:
The study was conducted using Walker and Avant's concept analysis model. In the search of the relevant literature, the Joanna Briggs Institute's methodology and search protocol for scoping reviews were applied. Searches were conducted in May 2023 with no time or geographical limits on Scopus, CINAHL, ProQuest, the Web of Science, Medic and Mednar and 42 studies were included. The data were analysed using narrative synthesis by categorising results using the steps of concept analysis.
Results:
Concept analysis identified defining attributes of emotional intelligence in healthcare leadership, including leadership qualities, management competencies, and sets of leadership styles which were related to supportive and transformational leadership behaviour. The antecedents were socio-demographic factors, well-being, and workplace resources. Finally, employee-, manager-, organisation- and patient-related consequences were identified, such as the well-being of both employees and managers, organisational performance and patient care quality.
Conclusions:
Emotional intelligence in healthcare leadership contributes to better performing organisations, as emotionally capable leaders can inspire and empower their employees. Holistic management of organisational duties and people-oriented leadership is a crucial resource in healthcare organisations. Well-being and workplace resources can be vitally important for leaders to manifest emotional intelligence in their work.
Implications for Practice and Research:
Emotional intelligence can contribute to efficient leadership behaviour and have positive outcomes at the employee, manager, organisation and patient levels. Therefore, emotional intelligence should be addressed in leadership education, training programmes and recruitment procedures. Finally, policymakers should be encouraged to acknowledge the role of sufficient resources in health care to ensure effective leadership.
Impact:
Emotional intelligence is a widely studied concept in the healthcare field. However, thorough conceptualisation regarding emotional intelligence in healthcare leadership has been lacking. Conceptualising this phenomenon was therefore outlined, providing a deeper understanding of the concept. The findings can be utilised in healthcare leadership development and research.
Reporting Method:
N/A.
Patient or Public Contribution
No patient or public contribution
Ecological uniqueness of fish assemblages and species contributions to beta diversity are affected by river-lake disconnection
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Ecological uniqueness is an important aspect intrinsically associated with beta diversity, highlighting the relative contributions of sites (LCBD) and species (SCBD) to overall compositional variation, and has important theoretical implications and practical applications in biodiversity conservation. However, it is still unclear how human disturbances affect the ecological uniqueness of lake fish assemblages, especially at intermediate and large spatial scales. Here, we explored how river–lake disconnection affected LCBD and SCBD of fish assemblages in 51 lakes (i.e., 13 lakes connected to the mainstem river, CLs; and 38 river-disconnected lakes, DLs) scattered across the floodplains of the Yangtze River, China. We compared the relationship of LCBD with species richness, as well as of LCBD with functional alpha diversity, contrasting the CLs and DLs, and examined how environmental factors and spatial variables account for variation in LCBD. We also examined the relationships between species occupancy, functional traits and SCBD. We found that an opposite patterns between LCBD and alpha diversity (here, based on species richness, the number of rare species, and a set of functional diversity indices) in CLs and DLs. More specifically, in CLs, sites with high ecological uniqueness generally supported high alpha diversity. Conversely, in DLs, sites with high ecological uniqueness generally supported low alpha diversity. Furthermore, LCBD was explained both by environmental and spatial factors, with connectivity being the most important spatial factor. SCBD showed a hump-shaped relationship with species occupancy and was poorly explained by functional traits, although these relationships were likely influenced by the proportion of rare species. From an applied perspective, our findings suggest to (i) incorporate LCBD and alpha diversity into modern-day frameworks aimed at identifying sites of high conservation priority, and (ii) consider both SCBD values and species rarity for targeting individual species of conservation interest.Abstract
Ecological uniqueness is an important aspect intrinsically associated with beta diversity, highlighting the relative contributions of sites (LCBD) and species (SCBD) to overall compositional variation, and has important theoretical implications and practical applications in biodiversity conservation. However, it is still unclear how human disturbances affect the ecological uniqueness of lake fish assemblages, especially at intermediate and large spatial scales. Here, we explored how river–lake disconnection affected LCBD and SCBD of fish assemblages in 51 lakes (i.e., 13 lakes connected to the mainstem river, CLs; and 38 river-disconnected lakes, DLs) scattered across the floodplains of the Yangtze River, China. We compared the relationship of LCBD with species richness, as well as of LCBD with functional alpha diversity, contrasting the CLs and DLs, and examined how environmental factors and spatial variables account for variation in LCBD. We also examined the relationships between species occupancy, functional traits and SCBD. We found that an opposite patterns between LCBD and alpha diversity (here, based on species richness, the number of rare species, and a set of functional diversity indices) in CLs and DLs. More specifically, in CLs, sites with high ecological uniqueness generally supported high alpha diversity. Conversely, in DLs, sites with high ecological uniqueness generally supported low alpha diversity. Furthermore, LCBD was explained both by environmental and spatial factors, with connectivity being the most important spatial factor. SCBD showed a hump-shaped relationship with species occupancy and was poorly explained by functional traits, although these relationships were likely influenced by the proportion of rare species. From an applied perspective, our findings suggest to (i) incorporate LCBD and alpha diversity into modern-day frameworks aimed at identifying sites of high conservation priority, and (ii) consider both SCBD values and species rarity for targeting individual species of conservation interest
Furfural-Based Vinyl Ester Resins: Syntheses, Properties and Comparison to Bisphenol A-Glycidyl Methacrylate-Based Vinyl Ester Resin
No full textAbstract
The environmental impact of using fossil-based resources in polymer production has raised serious concerns in recent decades. As a response, the development of renewable alternatives has garnered significant interest. In this study, we report the syntheses of two renewable sulfur-bridged dimethacrylates via three-step routes starting from commercial 5-bromofurfural. The dialdehyde and aldehyde intermediates were obtained using sodium sulfide and 2-mercaptoethanol, respectively, followed by reduction to diols and subsequent methacrylation using methacrylic anhydride (MAA). The properties of the resulting biobased dimethacrylates were compared to those of a commercially available petroleum-based vinyl ester resin and its neat monomer, bisphenol A-glycidyl methacrylate (BisGMA). The difuran-based monomer was a waxy solid at room temperature but exhibited low viscosity in its liquid state at elevated temperature, while the unsymmetrical monomer, containing a single furan ring, showed low viscosity already at room temperature – highlighting their favorable processing characteristics. Upon curing, both bioresins formed highly cross-linked networks with outstanding glass transition temperatures (183 and 162 °C), while thermal decomposition took place at 251 and 285 °C. Tensile strengths were approximately 46 and 16 MPa. Furthermore, both materials demonstrated chemical and water resistance comparable to that of their fossil-based counterpart. The results support the potential of these dimethacrylates as renewable alternatives to widely utilized fossil-based vinyl ester resins in various applications.Abstract
The environmental impact of using fossil-based resources in polymer production has raised serious concerns in recent decades. As a response, the development of renewable alternatives has garnered significant interest. In this study, we report the syntheses of two renewable sulfur-bridged dimethacrylates via three-step routes starting from commercial 5-bromofurfural. The dialdehyde and aldehyde intermediates were obtained using sodium sulfide and 2-mercaptoethanol, respectively, followed by reduction to diols and subsequent methacrylation using methacrylic anhydride (MAA). The properties of the resulting biobased dimethacrylates were compared to those of a commercially available petroleum-based vinyl ester resin and its neat monomer, bisphenol A-glycidyl methacrylate (BisGMA). The difuran-based monomer was a waxy solid at room temperature but exhibited low viscosity in its liquid state at elevated temperature, while the unsymmetrical monomer, containing a single furan ring, showed low viscosity already at room temperature – highlighting their favorable processing characteristics. Upon curing, both bioresins formed highly cross-linked networks with outstanding glass transition temperatures (183 and 162 °C), while thermal decomposition took place at 251 and 285 °C. Tensile strengths were approximately 46 and 16 MPa. Furthermore, both materials demonstrated chemical and water resistance comparable to that of their fossil-based counterpart. The results support the potential of these dimethacrylates as renewable alternatives to widely utilized fossil-based vinyl ester resins in various applications
Unveiling the Potential Photothermal Activity of Vanadium Carbide for Driving Chemical Reactions
No full textAbstract
Photothermally activated chemical reactions play a pivotal role in a wide range of applications, highlighting the need for efficient photothermal agents. The photothermal effect, which utilizes dominant nonradiative deexcitation mechanisms, has been extensively demonstrated in nanoscale systems, including plasmonic metals, inorganic semiconductors, organic materials, and polymers. However, the development of these photothermal materials often requires intricate fabrication and separation techniques, presenting significant challenges for practical implementation. Here we demonstrate that commercially available bulk vanadium monocarbide (VC) powder exhibits excellent light-to-heat conversion efficiency (∼70%), combined with remarkable chemical, thermal, and optical stability (against intense laser irradiation). These unique attributes of VC were harnessed to drive industrially relevant photothermally activated chemical reactions, specifically in the polymerization of acrylic monomers and the Diels–Alder (DA) reaction between anthracene and N-phenyl maleimide. Comprehensive analysis through FTIR and 1H NMR studies confirms the successful formation of products in both the reactions. Importantly, the photothermal reactions exhibit significantly reduced reaction times compared to the conventional thermal protocols. Furthermore, the recoverability of VC powder after the completion of the reactions enhances environmental sustainability. This study contributes valuable insights into the utilization of commercially available bulk VC powder as an off-the-shelf, cost-effective, efficient and sustainable photothermal agent for various chemical transformations.Abstract
Photothermally activated chemical reactions play a pivotal role in a wide range of applications, highlighting the need for efficient photothermal agents. The photothermal effect, which utilizes dominant nonradiative deexcitation mechanisms, has been extensively demonstrated in nanoscale systems, including plasmonic metals, inorganic semiconductors, organic materials, and polymers. However, the development of these photothermal materials often requires intricate fabrication and separation techniques, presenting significant challenges for practical implementation. Here we demonstrate that commercially available bulk vanadium monocarbide (VC) powder exhibits excellent light-to-heat conversion efficiency (∼70%), combined with remarkable chemical, thermal, and optical stability (against intense laser irradiation). These unique attributes of VC were harnessed to drive industrially relevant photothermally activated chemical reactions, specifically in the polymerization of acrylic monomers and the Diels–Alder (DA) reaction between anthracene and N-phenyl maleimide. Comprehensive analysis through FTIR and 1H NMR studies confirms the successful formation of products in both the reactions. Importantly, the photothermal reactions exhibit significantly reduced reaction times compared to the conventional thermal protocols. Furthermore, the recoverability of VC powder after the completion of the reactions enhances environmental sustainability. This study contributes valuable insights into the utilization of commercially available bulk VC powder as an off-the-shelf, cost-effective, efficient and sustainable photothermal agent for various chemical transformations
Material Memories of Lost Karelia: Affective Reminders of Ancestral Villages in the Finnish Second World War Evacuee Families’ Homes
No full textAbstract
In the end of the Second World War, Finland had to resettle about 430 000 people, 11 percent of the country's population, displaced from the areas annexed by the Soviet Union in 1944. Nearly 410 000 evacuees originated from the province of Vyborg in Karelia, southeast Finland (present-day Russia). Many of them had been living for centuries in the small family-based communities far in the countryside, for example, our Seitsonen family in our ancestral Seitsola village since the mid16th century. After the evacuation and relocation these former tight-knit agricultural communities were broken, and the villagers became scattered. Despite this dispersion, many Karelian families have maintained a strong connection to their roots and former homelands. This takes place for instance through the activities of municipal and parish associations. However, there are also more personal and home-based ways of remembering. These are manifested, for instance, through the small mementoes, photographs, books, documents, and maps related to the past life in Karelia. These are typically found on display in the first- and second-generation evacuees' homes, typically not in the living room but in more private quarters. This Chapter offers a personal, autoethnographic review of my extended family’s ways of recalling our former village through the small affective objects. These act as agents of memory that materialize and carry on the transgenerational memories and nostalgia for the lost homes for the third and fourth evacuee generations.Abstract
In the end of the Second World War, Finland had to resettle about 430 000 people, 11 percent of the country's population, displaced from the areas annexed by the Soviet Union in 1944. Nearly 410 000 evacuees originated from the province of Vyborg in Karelia, southeast Finland (present-day Russia). Many of them had been living for centuries in the small family-based communities far in the countryside, for example, our Seitsonen family in our ancestral Seitsola village since the mid16th century. After the evacuation and relocation these former tight-knit agricultural communities were broken, and the villagers became scattered. Despite this dispersion, many Karelian families have maintained a strong connection to their roots and former homelands. This takes place for instance through the activities of municipal and parish associations. However, there are also more personal and home-based ways of remembering. These are manifested, for instance, through the small mementoes, photographs, books, documents, and maps related to the past life in Karelia. These are typically found on display in the first- and second-generation evacuees' homes, typically not in the living room but in more private quarters. This Chapter offers a personal, autoethnographic review of my extended family’s ways of recalling our former village through the small affective objects. These act as agents of memory that materialize and carry on the transgenerational memories and nostalgia for the lost homes for the third and fourth evacuee generations