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Contexts, affective and physical states and their variations during physical activity in older adults : an intensive longitudinal study with sensor-triggered event-based ecological momentary assessments
No full textBackgroundTo design effective tailored interventions to promote physical activity (PA) among older adults, insights are needed into the contexts in which older adults engage in PA and their affective and physical experiences. Sensor-triggered event-based ecological momentary assessment (EMA) is an innovative method for capturing real-life contexts, as well as affective and physical states, during or immediately after specific events, such as PA. This study aimed to (1) describe the physical and social contexts, and the affective and physical states during PA among older adults, (2) evaluate how these constructs fluctuate during PA episodes, and (3) describe affective states during PA according to the context.MethodsAn intensive longitudinal sensor-triggered event-based EMA study was conducted with 92 Belgian older adults (65 + years). During seven days, participants were monitored using a Fitbit, which triggered a smartphone-based questionnaire on the event-based EMA platform 'HealthReact' after a five-minute walk. Participants reported on contexts and affective (positive/negative valence) and physical states (pain and fatigue) during the PA event. Descriptive statistics and generalized mixed models were used for data analysis.ResultsOlder adults predominantly engaged in daily physical activities, such as walking for transport, leisure walking, and gardening, rather than structured exercise. They consistently reported high positive affect, low negative affect, and minimal physical complaints during PA. Furthermore, older adults mainly engage in physical activities alone, particularly in outdoor settings. Variations in contexts, affect, and fatigue were mostly driven by within-subject differences. The model showed significant differences across times of day, with negative affect being highest in the evening and fatigue lowest in the morning. Additionally, the physical and social context influenced negative affect (but not positive affect), with outdoor activities performed alone and indoor activities performed with others being associated with lower negative affect.ConclusionsWhile these findings could enhance the effectiveness of tailored PA interventions, it remains unclear whether the observed affective and physical states are causes or effects of PA, and whether the contexts in which the activities were performed align with older adults' preferences. Further research is needed to explore these relationships and to better understand older adults' preferred PA contexts.BackgroundTo design effective tailored interventions to promote physical activity (PA) among older adults, insights are needed into the contexts in which older adults engage in PA and their affective and physical experiences. Sensor-triggered event-based ecological momentary assessment (EMA) is an innovative method for capturing real-life contexts, as well as affective and physical states, during or immediately after specific events, such as PA. This study aimed to (1) describe the physical and social contexts, and the affective and physical states during PA among older adults, (2) evaluate how these constructs fluctuate during PA episodes, and (3) describe affective states during PA according to the context.MethodsAn intensive longitudinal sensor-triggered event-based EMA study was conducted with 92 Belgian older adults (65 + years). During seven days, participants were monitored using a Fitbit, which triggered a smartphone-based questionnaire on the event-based EMA platform 'HealthReact' after a five-minute walk. Participants reported on contexts and affective (positive/negative valence) and physical states (pain and fatigue) during the PA event. Descriptive statistics and generalized mixed models were used for data analysis.ResultsOlder adults predominantly engaged in daily physical activities, such as walking for transport, leisure walking, and gardening, rather than structured exercise. They consistently reported high positive affect, low negative affect, and minimal physical complaints during PA. Furthermore, older adults mainly engage in physical activities alone, particularly in outdoor settings. Variations in contexts, affect, and fatigue were mostly driven by within-subject differences. The model showed significant differences across times of day, with negative affect being highest in the evening and fatigue lowest in the morning. Additionally, the physical and social context influenced negative affect (but not positive affect), with outdoor activities performed alone and indoor activities performed with others being associated with lower negative affect.ConclusionsWhile these findings could enhance the effectiveness of tailored PA interventions, it remains unclear whether the observed affective and physical states are causes or effects of PA, and whether the contexts in which the activities were performed align with older adults' preferences. Further research is needed to explore these relationships and to better understand older adults' preferred PA contexts.A
The attitude of nursing staff towards oral healthcare for care‐dependent older adults (ANOCO) questionnaire : development and validation
No full textAimsThis study aims to report on the development and validation of the Attitude of Nursing staff towards Oral healthcare for Care-dependent Older adults (ANOCO) questionnaire.MethodsThe development of the ANOCO questionnaire was performed in three stages between 2008 and 2019. In a first stage, domains related to oral healthcare attitudes were identified. Next, relevant statements per domain were formulated by a Delphi panel in two rounds, resulting in a questionnaire with 32 statements. In a final phase, this questionnaire was subjected to psychometric analysis, including an evaluation of the construct validity, an internal consistency analysis (Cronbachs alpha) and a principal component analysis.ResultsThe questionnaire could significantly distinguish between known groups (dentists, nurses' aides, nursing students and nurses). Regarding internal consistency, Cronbach's alpha was 0.863 in the first sample (n = 361) and 0.843 in the second sample (n = 1051). Based on principal component analysis, 22 statements were retained. Four components with an eigenvalue of more than 1 explained 45% of the total variance.ConclusionThe ANOCO-22 questionnaire consists of 22 statements and is a valid tool to assess the changes or differences in the attitude of nursing staff towards oral healthcare for care-dependent older adults.AimsThis study aims to report on the development and validation of the Attitude of Nursing staff towards Oral healthcare for Care-dependent Older adults (ANOCO) questionnaire.MethodsThe development of the ANOCO questionnaire was performed in three stages between 2008 and 2019. In a first stage, domains related to oral healthcare attitudes were identified. Next, relevant statements per domain were formulated by a Delphi panel in two rounds, resulting in a questionnaire with 32 statements. In a final phase, this questionnaire was subjected to psychometric analysis, including an evaluation of the construct validity, an internal consistency analysis (Cronbachs alpha) and a principal component analysis.ResultsThe questionnaire could significantly distinguish between known groups (dentists, nurses' aides, nursing students and nurses). Regarding internal consistency, Cronbach's alpha was 0.863 in the first sample (n = 361) and 0.843 in the second sample (n = 1051). Based on principal component analysis, 22 statements were retained. Four components with an eigenvalue of more than 1 explained 45% of the total variance.ConclusionThe ANOCO-22 questionnaire consists of 22 statements and is a valid tool to assess the changes or differences in the attitude of nursing staff towards oral healthcare for care-dependent older adults.A
Realizing the full potential of digital innovation : exploring maturity levels for integrating interorganizational value chains
No full textMaturity models, with their defined levels, help organizations recognize the need for change and implement measures to integrate digital Industry 4.0 (I4.0) innovations, thereby enhancing their value chains’ performance. However, fully realizing the potential of I4.0 necessitates effective interorganizational collaboration, an area in which empirical research remains limited. In this study, we expand on existing research on business-process maturity models by investigating their application in an interorganizational context. Through an examination of 21 existing models and a survey of 188 manufacturing firms, we identified four distinct maturity levels for digital interorganizational value chain capabilities. Statistical analysis has validated these levels, consistent with our initial pilot study’s results. These results contribute to the development of a comprehensive interorganizational maturity model, offering valuable insights for scholars and practitioners to realize the full potential of digital I4.0 innovations. This approach necessitates robust collaboration among interorganizational entities to attain the best value chain performance.Maturity models, with their defined levels, help organizations recognize the need for change and implement measures to integrate digital Industry 4.0 (I4.0) innovations, thereby enhancing their value chains’ performance. However, fully realizing the potential of I4.0 necessitates effective interorganizational collaboration, an area in which empirical research remains limited. In this study, we expand on existing research on business-process maturity models by investigating their application in an interorganizational context. Through an examination of 21 existing models and a survey of 188 manufacturing firms, we identified four distinct maturity levels for digital interorganizational value chain capabilities. Statistical analysis has validated these levels, consistent with our initial pilot study’s results. These results contribute to the development of a comprehensive interorganizational maturity model, offering valuable insights for scholars and practitioners to realize the full potential of digital I4.0 innovations. This approach necessitates robust collaboration among interorganizational entities to attain the best value chain performance.C
Stoichiometry of carbon, nitrogen, and phosphorus in soil : impacts of soil development and land use across the catchment scale
No full textUnderstanding the evolution and regulation of soil nutrients stoichiometry at different stages of geological development provides critical insights for optimizing fertilization strategies and the sustainable use of land resources. In this study, 1029 soil samples derived from alluvium in the downstream region of the Yangtze River were analyzed, encompassing woodland, dryland and paddy-dryland rotation (paddies). Using the chemical index of alteration (CIA), a relative age sequence of soil development was established, facilitating an investigation into the evolution of soil C:N:P stoichiometry across various stages of parent material development, as well as the factors influencing these changes. As soil matures, organic carbon (OC) and total nitrogen (TN) contents in the surface layer (A horizon) significantly increased by 41.3% and 29.3%, respectively, whereas the content in the deep layer decreased by 51.4% and 9.41%, respectively. Additionally, total phosphorus (TP) content exhibited a marked decline over time in both the A horizon and deep layer. While the C:N ratio of the A horizon and deep layer showed only minor fluctuations, the C:P and N:P ratios in the A horizon significantly increased. Notably, phosphorus limitation, commonly observed in highly developed soils, is absent in this region. At comparable stages of soil development, woodlands and paddies exhibited higher reserves of soil OC and TN compared to adjacent drylands, but they had relatively lower contents of soil TP. These findings suggest that in the downstream region of the Yangtze River, more mature soils exhibited a more balanced ratio of various nutrients. This equilibrium arose from the gradual accumulation of initially deficient OC and TN, alongside a moderate decline in the initially abundant TP. However, for effective soil management, fertilization strategies should account for the contrasting nutrient limitations-namely, OC and TN deficiencies in dryland soils and TP deficiency in paddies.Understanding the evolution and regulation of soil nutrients stoichiometry at different stages of geological development provides critical insights for optimizing fertilization strategies and the sustainable use of land resources. In this study, 1029 soil samples derived from alluvium in the downstream region of the Yangtze River were analyzed, encompassing woodland, dryland and paddy-dryland rotation (paddies). Using the chemical index of alteration (CIA), a relative age sequence of soil development was established, facilitating an investigation into the evolution of soil C:N:P stoichiometry across various stages of parent material development, as well as the factors influencing these changes. As soil matures, organic carbon (OC) and total nitrogen (TN) contents in the surface layer (A horizon) significantly increased by 41.3% and 29.3%, respectively, whereas the content in the deep layer decreased by 51.4% and 9.41%, respectively. Additionally, total phosphorus (TP) content exhibited a marked decline over time in both the A horizon and deep layer. While the C:N ratio of the A horizon and deep layer showed only minor fluctuations, the C:P and N:P ratios in the A horizon significantly increased. Notably, phosphorus limitation, commonly observed in highly developed soils, is absent in this region. At comparable stages of soil development, woodlands and paddies exhibited higher reserves of soil OC and TN compared to adjacent drylands, but they had relatively lower contents of soil TP. These findings suggest that in the downstream region of the Yangtze River, more mature soils exhibited a more balanced ratio of various nutrients. This equilibrium arose from the gradual accumulation of initially deficient OC and TN, alongside a moderate decline in the initially abundant TP. However, for effective soil management, fertilization strategies should account for the contrasting nutrient limitations-namely, OC and TN deficiencies in dryland soils and TP deficiency in paddies.A
Reduced RG-II pectin dimerization disrupts differential growth by attenuating hormonal regulation
No full textDefects in cell wall integrity (CWI) profoundly affect plant growth, although, underlying mechanisms are not well understood. We show that in Arabidopsis mur1 mutant, CWI defects from compromising dimerization of RG-II pectin, a key component of cell wall, attenuate the expression of auxin response factors ARF7-ARF19. As a result, polar auxin transport components are misexpressed, disrupting auxin response asymmetry, leading to defective apical hook development. Accordingly, mur1 hook defects are suppressed by enhancing ARF7 expression. In addition, expression of brassinosteroid biosynthesis genes is down-regulated in mur1 mutant, and supplementing brassinosteroid or enhancing brassinosteroid signaling suppresses mur1 hook defects. Intriguingly, brassinosteroid enhances RG-II dimerization, showing hormonal feedback to the cell wall. Our results thus reveal a previously unrecognized link between cell wall defects from reduced RG-II dimerization and growth regulation mediated via modulation of auxin-brassinosteroid pathways in early seedling development.Defects in cell wall integrity (CWI) profoundly affect plant growth, although, underlying mechanisms are not well understood. We show that in Arabidopsis mur1 mutant, CWI defects from compromising dimerization of RG-II pectin, a key component of cell wall, attenuate the expression of auxin response factors ARF7-ARF19. As a result, polar auxin transport components are misexpressed, disrupting auxin response asymmetry, leading to defective apical hook development. Accordingly, mur1 hook defects are suppressed by enhancing ARF7 expression. In addition, expression of brassinosteroid biosynthesis genes is down-regulated in mur1 mutant, and supplementing brassinosteroid or enhancing brassinosteroid signaling suppresses mur1 hook defects. Intriguingly, brassinosteroid enhances RG-II dimerization, showing hormonal feedback to the cell wall. Our results thus reveal a previously unrecognized link between cell wall defects from reduced RG-II dimerization and growth regulation mediated via modulation of auxin-brassinosteroid pathways in early seedling development.A
3D-FLOR: An innovative framework for tuning lattice structures via rheological optimization
No full textWhile Extrusion-Based Additive Manufacturing (EB-AM) is highly versatile and supports a wide range of materials today, optimizing the rheological parameters during printing remains a challenge. This study introduces the 3D-FLOR framework (3D Flexible Lattice Optimization via Rheology), a new approach that connects rheological properties with mechanical performance to optimize lattice structures for specific uses. Using thermoplastic polyurethane (TPU) as a material case, this framework employs the Doehlert Design and Response Surface Methodology (RSM) to systematically optimize printing speeds and temperatures, reducing reliance on trial-and-error methods. It demonstrates an application with a morphing wing optimized for better compression and flexural performance. This framework serves as a general protocol to enhance mechanical behaviour in EB-AM by integrating rheology and manufacturing processes. It minimizes inefficient experimentation and can be easily extended to other printable materials.While Extrusion-Based Additive Manufacturing (EB-AM) is highly versatile and supports a wide range of materials today, optimizing the rheological parameters during printing remains a challenge. This study introduces the 3D-FLOR framework (3D Flexible Lattice Optimization via Rheology), a new approach that connects rheological properties with mechanical performance to optimize lattice structures for specific uses. Using thermoplastic polyurethane (TPU) as a material case, this framework employs the Doehlert Design and Response Surface Methodology (RSM) to systematically optimize printing speeds and temperatures, reducing reliance on trial-and-error methods. It demonstrates an application with a morphing wing optimized for better compression and flexural performance. This framework serves as a general protocol to enhance mechanical behaviour in EB-AM by integrating rheology and manufacturing processes. It minimizes inefficient experimentation and can be easily extended to other printable materials.
Shock stability of a combined method of advection upstream splitting and time-accurate momentum interpolation
No full textA combined finite volume method of advection upstream splitting (AUSM) and time-accurate momentum interpolation (TAMI), which we developed earlier for flows with very low Mach number, especially for simulation of acoustic wave propagation, is extended by shock-stability terms. The combined method, which we call AUSM-TAMI, is suitable for flows with very low Mach number, thanks to the transporting velocity in the convection part of the flow equations, derived from time-accurate momentum interpolation. The shock-stability terms are velocity difference terms that are added to the pressure force components, made similar to the shock-stability terms of a modern AUSM-method. We show with three test cases, with very different character, two unsteady flows and a steady flow, that the combined method, extended with the shock-stability terms, produces solutions without shock-induced oscillations in flows with high Mach number and strong shock waves.A combined finite volume method of advection upstream splitting (AUSM) and time-accurate momentum interpolation (TAMI), which we developed earlier for flows with very low Mach number, especially for simulation of acoustic wave propagation, is extended by shock-stability terms. The combined method, which we call AUSM-TAMI, is suitable for flows with very low Mach number, thanks to the transporting velocity in the convection part of the flow equations, derived from time-accurate momentum interpolation. The shock-stability terms are velocity difference terms that are added to the pressure force components, made similar to the shock-stability terms of a modern AUSM-method. We show with three test cases, with very different character, two unsteady flows and a steady flow, that the combined method, extended with the shock-stability terms, produces solutions without shock-induced oscillations in flows with high Mach number and strong shock waves.A
Biased heritage : how datasets shape models in facial expression recognition
No full textIn recent years, the rapid development of artificial intelligence (AI)systems has raised concerns about our ability to ensure their fairness, thatis, how to avoid discrimination based on protected characteristics such asgender, race, or age. While algorithmic fairness is well-studied in simplebinary classification tasks on tabular data, its application to complex,real-world scenarios-such as Facial Expression Recognition (FER)-remainsunderexplored. FER presents unique challenges: it is inherently multiclass, andbiases emerge across intersecting demographic variables, each potentiallycomprising multiple protected groups. We present a comprehensive framework toanalyze bias propagation from datasets to trained models in image-based FERsystems, while introducing new bias metrics specifically designed formulticlass problems with multiple demographic groups. Our methodology studiesbias propagation by (1) inducing controlled biases in FER datasets, (2)training models on these biased datasets, and (3) analyzing the correlationbetween dataset bias metrics and model fairness notions. Our findings revealthat stereotypical biases propagate more strongly to model predictions thanrepresentational biases, suggesting that preventing emotion-specificdemographic patterns should be prioritized over general demographic balance inFER datasets. Additionally, we observe that biased datasets lead to reducedmodel accuracy, challenging the assumed fairness-accuracy trade-off.In recent years, the rapid development of artificial intelligence (AI)systems has raised concerns about our ability to ensure their fairness, thatis, how to avoid discrimination based on protected characteristics such asgender, race, or age. While algorithmic fairness is well-studied in simplebinary classification tasks on tabular data, its application to complex,real-world scenarios-such as Facial Expression Recognition (FER)-remainsunderexplored. FER presents unique challenges: it is inherently multiclass, andbiases emerge across intersecting demographic variables, each potentiallycomprising multiple protected groups. We present a comprehensive framework toanalyze bias propagation from datasets to trained models in image-based FERsystems, while introducing new bias metrics specifically designed formulticlass problems with multiple demographic groups. Our methodology studiesbias propagation by (1) inducing controlled biases in FER datasets, (2)training models on these biased datasets, and (3) analyzing the correlationbetween dataset bias metrics and model fairness notions. Our findings revealthat stereotypical biases propagate more strongly to model predictions thanrepresentational biases, suggesting that preventing emotion-specificdemographic patterns should be prioritized over general demographic balance inFER datasets. Additionally, we observe that biased datasets lead to reducedmodel accuracy, challenging the assumed fairness-accuracy trade-off.