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Predictors of post‐exercise affect : a self‐determination theory approach considering physical, social, and psychological factors
No full textBackground: Studies have shown increases in affect after acute exercise. However, the specific aspects of an exercise experience that predict or contribute to post-exercise affect remain relatively unknown. This study aimed to determine which physical (i.e., duration and intensity), contextual (i.e., social context and time of day), and psychological factors (i.e., motivation and need satisfaction) predicted post-exercise affect.Methods: In 2021, 296 gym users self-reported affect before and immediately after exercising at a gym facility. Participants also reported situational motivation towards exercise, need satisfaction (i.e., autonomy, competence, and relatedness), who they exercised with (social interaction), and the duration and perceived intensity of their exercise session. We first conducted a paired samples t-test to identify whether affect significantly increased from before to after exercise, and then a hierarchical regression model to determine which factors predicted post-exercise affect.Results: Affect significantly increased from before to after exercise (t[291] = 8.116, p < .001). Autonomous motivation (β = .23, p = <.001), autonomy satisfaction (β = .15, p = <.05), and relatedness satisfaction (β = .19, p = <.01) significantly predicted post-exercise affect, whereas duration, perceived intensity, social interaction, and time of day did not.Conclusions: People should be encouraged to engage in activities that satisfy their need for autonomy and relatedness during leisure-time (i.e., not during the workday). SO WHAT?: This approach to physical activity promotion may lead to better affective outcomes and increased adherence compared to focusing on how long, how intense, or with whom people exercise.Background: Studies have shown increases in affect after acute exercise. However, the specific aspects of an exercise experience that predict or contribute to post-exercise affect remain relatively unknown. This study aimed to determine which physical (i.e., duration and intensity), contextual (i.e., social context and time of day), and psychological factors (i.e., motivation and need satisfaction) predicted post-exercise affect.Methods: In 2021, 296 gym users self-reported affect before and immediately after exercising at a gym facility. Participants also reported situational motivation towards exercise, need satisfaction (i.e., autonomy, competence, and relatedness), who they exercised with (social interaction), and the duration and perceived intensity of their exercise session. We first conducted a paired samples t-test to identify whether affect significantly increased from before to after exercise, and then a hierarchical regression model to determine which factors predicted post-exercise affect.Results: Affect significantly increased from before to after exercise (t[291] = 8.116, p < .001). Autonomous motivation (β = .23, p = <.001), autonomy satisfaction (β = .15, p = <.05), and relatedness satisfaction (β = .19, p = <.01) significantly predicted post-exercise affect, whereas duration, perceived intensity, social interaction, and time of day did not.Conclusions: People should be encouraged to engage in activities that satisfy their need for autonomy and relatedness during leisure-time (i.e., not during the workday). SO WHAT?: This approach to physical activity promotion may lead to better affective outcomes and increased adherence compared to focusing on how long, how intense, or with whom people exercise.A
Patient safety in general practice during COVID-19 : a descriptive analysis in 38 countries (PRICOV-19)
No full textBackground: This article aims to examine patient safety in general practice during COVID-19. Methods: In total, 5489 GP practices from 37 European countries and Israel filled in the online self-reported PRICOV-19 survey between November 2020 and December 2021. The outcome measures include 30 patient safety indicators on structure, process, and outcome. Results: The data showed that structural problems often impeded patient safety during COVID-19, as 58.6% of practices (3209/5479) reported limitations related to their building or infrastructure. Nevertheless, GP practices rapidly changed their processes, including the appointment systems. Implementation proved challenging as, although 76.1% of practices (3751/4932) developed a protocol to answer calls from potential COVID patients, only 34.4% (1252/3643) always used it. The proportion of practices reported having sufficient protected time in general practitioners’ schedules to review guidelines remained consistent when comparing the pre-COVID (34.2%,1647/4813) with the COVID period (33.2%,1600/4813). Overall, 42.8% of practices (1966/4590) always informed home care services when patients were diagnosed with COVID-19, while this decreased to 30.1% for other major infectious diseases (1341/4458). Most practices reported at least one incident of delayed care in patients with an urgent condition, most often because the patient did not come to the practice sooner (60.4%, 2561/4237). Moreover, 31.1% of practices (1349/4199) always organized a team discussion when incidents happened. Overall, large variations were found across countries and patient safety indicators. Conclusions: The results demonstrated that European GP practices adopted numerous measures to deliver safe care during COVID-19. However, multilayered interventions are needed to improve infection control and GP practice accessibility in future pandemics.Background: This article aims to examine patient safety in general practice during COVID-19. Methods: In total, 5489 GP practices from 37 European countries and Israel filled in the online self-reported PRICOV-19 survey between November 2020 and December 2021. The outcome measures include 30 patient safety indicators on structure, process, and outcome. Results: The data showed that structural problems often impeded patient safety during COVID-19, as 58.6% of practices (3209/5479) reported limitations related to their building or infrastructure. Nevertheless, GP practices rapidly changed their processes, including the appointment systems. Implementation proved challenging as, although 76.1% of practices (3751/4932) developed a protocol to answer calls from potential COVID patients, only 34.4% (1252/3643) always used it. The proportion of practices reported having sufficient protected time in general practitioners’ schedules to review guidelines remained consistent when comparing the pre-COVID (34.2%,1647/4813) with the COVID period (33.2%,1600/4813). Overall, 42.8% of practices (1966/4590) always informed home care services when patients were diagnosed with COVID-19, while this decreased to 30.1% for other major infectious diseases (1341/4458). Most practices reported at least one incident of delayed care in patients with an urgent condition, most often because the patient did not come to the practice sooner (60.4%, 2561/4237). Moreover, 31.1% of practices (1349/4199) always organized a team discussion when incidents happened. Overall, large variations were found across countries and patient safety indicators. Conclusions: The results demonstrated that European GP practices adopted numerous measures to deliver safe care during COVID-19. However, multilayered interventions are needed to improve infection control and GP practice accessibility in future pandemics.A
Evaluation of genetic diversity of Ethiopian mango genotypes and comparison with a worldwide germplasm collection
No full textMango is a fruit crop holding significant economic importance in east Africa. However, the genetic diversity of Ethiopian mango remains so far unexplored. Therefore, we carried out the genetic characterization of Ethiopian populations and germplasm resources using eight SSR markers. A total of 162 domestic mango accessions were compared with the available information on the genetic profile of 73 international reference cultivars maintained in the European mango reference collection. We detected 69 alleles and found a high level of heterozygosity (0.68) among Ethiopian mango populations. As expected, there was broader genetic variability in the international reference germplasm (i.e., higher expected heterozygosity, allelic richness and number of private alleles). The study revealed frequent cases of mismatches among the commercially distributed varieties in Ethiopia and their synonymous cultivars in the international reference germplasm. The UPGMA dendrogram and model based structure analysis showed the relationship of locally grown mango trees with commercially available cultivars in Ethiopia. The clustering and differentiation estimates indicate a consistent relationship among accessions, aligning with their geographical distribution. Structure analysis identified three subgroups within the entire dataset of genotypes and highlighted the distinctness of the domestic gene pool in comparison to the accessions in the international collection. Furthermore, our analysis identified unique cultivars within the reference germplasm that exhibited close genetic proximity to the domestic samples, thereby providing evidence of their significant role in diversifying Ethiopian mango populations. These findings contribute to the effective management and utilization of mango germplasm in Ethiopia and will enhance current breeding efforts in the country.Mango is a fruit crop holding significant economic importance in east Africa. However, the genetic diversity of Ethiopian mango remains so far unexplored. Therefore, we carried out the genetic characterization of Ethiopian populations and germplasm resources using eight SSR markers. A total of 162 domestic mango accessions were compared with the available information on the genetic profile of 73 international reference cultivars maintained in the European mango reference collection. We detected 69 alleles and found a high level of heterozygosity (0.68) among Ethiopian mango populations. As expected, there was broader genetic variability in the international reference germplasm (i.e., higher expected heterozygosity, allelic richness and number of private alleles). The study revealed frequent cases of mismatches among the commercially distributed varieties in Ethiopia and their synonymous cultivars in the international reference germplasm. The UPGMA dendrogram and model based structure analysis showed the relationship of locally grown mango trees with commercially available cultivars in Ethiopia. The clustering and differentiation estimates indicate a consistent relationship among accessions, aligning with their geographical distribution. Structure analysis identified three subgroups within the entire dataset of genotypes and highlighted the distinctness of the domestic gene pool in comparison to the accessions in the international collection. Furthermore, our analysis identified unique cultivars within the reference germplasm that exhibited close genetic proximity to the domestic samples, thereby providing evidence of their significant role in diversifying Ethiopian mango populations. These findings contribute to the effective management and utilization of mango germplasm in Ethiopia and will enhance current breeding efforts in the country.A
From visualization to machine learning : advancing time series analytics on wearable sensor data
No full textDoor de opmars van draagbare sensoren zoals smartwatches, worden er nieuwe mogelijkheden geopend voor langdurige en niet-invasieve monitoring van gedrag en gezondheid in het dagelijks leven. Deze toestellen genereren enorme hoeveelheden tijdreeksdata — vaak complex, ruisvol en onvolledig — wat grote uitdagingen met zich meebrengt op vlak van verwerking, interpretatie en betrouwbaarheid.Dit doctoraatsonderzoek bevindt zich op het snijvlak van datavisualisatie, machine learning en medische monitoring, met een specifieke focus op de analyse van wearables. Het werk introduceert schaalbare open-source visualisatietools, onderzoekt de rol van klassieke machine-learning technieken voor activiteitsherkenning, en ontwikkelt methodes om datakwaliteit te evalueren in alledaagse monitoring omgevingen. Zo wordt onder meer een nieuwe aggregatieheuristiek voorgesteld om visualisaties performanter te maken, en toont een case-study bij patiënten met primaire hoofdpijn aan hoe visualisatie gerichte analyses met beperkte data hoeveelheden kunnen leiden tot relevante inzichten.Dit onderzoek illustreert hoe een combinatie van visualisatie, klassieke algoritmes en kritische datakwaliteitscontrole kan leiden tot robuuste en interpreteerbare resultaten. In een wereld waar data steeds sneller groeit, blijft dergelijke zorgvuldige en schaalbare aanpakken essentieel om technologische beloftes te vertalen naar maatschappelijke impact.Public defense: 2025-06-26Door de opmars van draagbare sensoren zoals smartwatches, worden er nieuwe mogelijkheden geopend voor langdurige en niet-invasieve monitoring van gedrag en gezondheid in het dagelijks leven. Deze toestellen genereren enorme hoeveelheden tijdreeksdata — vaak complex, ruisvol en onvolledig — wat grote uitdagingen met zich meebrengt op vlak van verwerking, interpretatie en betrouwbaarheid.Dit doctoraatsonderzoek bevindt zich op het snijvlak van datavisualisatie, machine learning en medische monitoring, met een specifieke focus op de analyse van wearables. Het werk introduceert schaalbare open-source visualisatietools, onderzoekt de rol van klassieke machine-learning technieken voor activiteitsherkenning, en ontwikkelt methodes om datakwaliteit te evalueren in alledaagse monitoring omgevingen. Zo wordt onder meer een nieuwe aggregatieheuristiek voorgesteld om visualisaties performanter te maken, en toont een case-study bij patiënten met primaire hoofdpijn aan hoe visualisatie gerichte analyses met beperkte data hoeveelheden kunnen leiden tot relevante inzichten.Dit onderzoek illustreert hoe een combinatie van visualisatie, klassieke algoritmes en kritische datakwaliteitscontrole kan leiden tot robuuste en interpreteerbare resultaten. In een wereld waar data steeds sneller groeit, blijft dergelijke zorgvuldige en schaalbare aanpakken essentieel om technologische beloftes te vertalen naar maatschappelijke impact.D
Dynamic multi-behaviour, orientation-invariant re-identification of Holstein-Friesian cattle
No full textTo perform reliable animal re-identification, most available algorithms require standardised animal poses. However, this lack of versatility prevents widespread application of these algorithms in behavioural research and commercial environments. To circumvent this, we incorporated information about the orientation and behaviour of the animals in an embedding-based algorithm to re-identify Holstein-Friesian cattle. After all, the orientation and behaviour of an animal determine which body parts of an animal are visible from the camera's perspective. We evaluated our approach using a dataset with more than 11,000 instance segments of Holstein-Friesian cattle, but our methodology is readily generalisable to different animal species. Our results show that incorporation of informative metadata parameters in the re-identification procedure increases the rank-1 re-identification accuracy from 0.822 to 0.894, corresponding to a 40% reduction in the number of incorrectly identified animals.To perform reliable animal re-identification, most available algorithms require standardised animal poses. However, this lack of versatility prevents widespread application of these algorithms in behavioural research and commercial environments. To circumvent this, we incorporated information about the orientation and behaviour of the animals in an embedding-based algorithm to re-identify Holstein-Friesian cattle. After all, the orientation and behaviour of an animal determine which body parts of an animal are visible from the camera's perspective. We evaluated our approach using a dataset with more than 11,000 instance segments of Holstein-Friesian cattle, but our methodology is readily generalisable to different animal species. Our results show that incorporation of informative metadata parameters in the re-identification procedure increases the rank-1 re-identification accuracy from 0.822 to 0.894, corresponding to a 40% reduction in the number of incorrectly identified animals.A
Fostering the implementation of liquid biopsy in clinical practice : meeting report 2024 of the European Liquid Biopsy Society (ELBS)
No full text
Design and validation of a low-cost triaxial 5G RF-EMF exposure sensor
No full textA low-cost monitoring network, to measure radio frequency (RF) electromagnetic field (EMF) exposure induced by 5G, is required for risk communication and to support research into long-term health and ecological effects related to 5G technologies. A low-cost triaxial fifth generation (5G) RF-EMF exposure sensor was designed, calibrated, and validated in the field, using a commercial network. The sensor uses a triaxial antenna-based measurement design and is able to measure the exposure induced by 5G communication in the n78 (3300-3800 MHz) and the n77 (3300-4200 MHz) frequency band up to 3900 MHz. The sensitivity of the simultaneous analog-to-digital converter (ADC)-based triaxial sensor is 0.06 V/m, while having a combined uncertainty u(c) of 3.12 dB. The sensor was tested indoor and in two outdoor environments (private and commercial 5G networks). The maximum measured electric-field level induced by 5G (n77 band) was 0.89 V/m [500 m from a commercial base station (BS)] and 2.87 V/m (60 m from a private BS), which are 1.5% and 4.8% of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines, respectively. A second measurement campaign was used to compare the values of the electric field captured by the novel triaxial 5G sensor and commercial measurement equipment (SRM-3006). The average values of the electric field registered by the triaxial 5G sensor differ on average 2.8 dB from the values of the SRM-3006, which is within the measurement uncertainty of the SRM-3006.A low-cost monitoring network, to measure radio frequency (RF) electromagnetic field (EMF) exposure induced by 5G, is required for risk communication and to support research into long-term health and ecological effects related to 5G technologies. A low-cost triaxial fifth generation (5G) RF-EMF exposure sensor was designed, calibrated, and validated in the field, using a commercial network. The sensor uses a triaxial antenna-based measurement design and is able to measure the exposure induced by 5G communication in the n78 (3300-3800 MHz) and the n77 (3300-4200 MHz) frequency band up to 3900 MHz. The sensitivity of the simultaneous analog-to-digital converter (ADC)-based triaxial sensor is 0.06 V/m, while having a combined uncertainty u(c) of 3.12 dB. The sensor was tested indoor and in two outdoor environments (private and commercial 5G networks). The maximum measured electric-field level induced by 5G (n77 band) was 0.89 V/m [500 m from a commercial base station (BS)] and 2.87 V/m (60 m from a private BS), which are 1.5% and 4.8% of the International Commission on Non-Ionizing Radiation Protection (ICNIRP) guidelines, respectively. A second measurement campaign was used to compare the values of the electric field captured by the novel triaxial 5G sensor and commercial measurement equipment (SRM-3006). The average values of the electric field registered by the triaxial 5G sensor differ on average 2.8 dB from the values of the SRM-3006, which is within the measurement uncertainty of the SRM-3006.A
