Search Results (649)

LEGO^® Serious Play^® (LSP) was used to understand the ideals of connectivity and inclusivity among students, adult learners, and workers in a higher education community. While connectivity in nature’s ecosystem has been well studied, it is important to explore this form of connectivity among humans. The objectives of this study were to determine and analyze the main barriers and enablers of connectivity and inclusivity in higher education teaching, learning, and operations, and to propose key action plans. By using LSP in our study, we explored a kinesthetic approach where participants from diverse age groups (20–56 years) and professional/academic levels built models and shared their stories with others. An evaluation of the workshop was obtained using questionnaires (open-ended and scale-based surveys). All the participants found the LSP useful for the overall experience, indicating a strong overall support for its use. In total, 75% of the participants found it valuable and 50% of the participants found the process “difficult”, particularly in group communication and model representation, which require further refinement. Participants’ responses showed that both affective and cognitive elements were active during the workshop, suggesting that this method encourages all voices to be heard. In addition, the methodology for problem-solving and entertainment is a promising pedagogical and andragogical tool for teaching in higher education and in non-academic settings. Full article

During the Modern Age, Seville was known as the Port of the Indies due to its key role in transatlantic trade, although the actual port was located in Triana, a riverside quarter outside the city walls along the Guadalquivir River. This area was essential for maritime and commercial activities, shaping Seville’s economic and social development. This study analyses Triana’s urban layout, social composition, and architecture in the 16th century using historical sources and graphic representations. The quarter combined defensive structures, religious buildings, and residential complexes, reflecting both its strategic importance and distinct identity. Its streets and architecture supported defense, commerce, and daily life, while its diverse community (including sailors, merchants, craftsmen, and dockworkers) was central to its mercantile and manufacturing activity. Architecturally, Triana featured traditional dwellings, corrales de vecinos, mesones, and posadas, that facilitated trade and travel. Examining these elements reveals Triana’s adaptability to economic and social conditions, highlighting its resilience, diverse population, and rich architectural heritage within Seville’s historical context and Atlantic trade. Full article

Bovine viral diarrhea virus (BVDV) is a globally prevalent pathogen causing severe detriment to the cattle industry. Vertical infection occurring before the development of the fetal adaptive immune response, before 125 days of gestation, results in an immunotolerant, persistently infected (PI) calf. It was hypothesized that epigenetic alterations observed in the splenic tissue of PI fetuses at gestational day 245 would persist into the postnatal period. White blood cell DNA from five PI and five control heifers at 4 months of age was subjected to reduced representation bisulfite sequencing and interpreted within the context of complete blood count and flow cytometry data herein. Analysis revealed 8367 differentially methylated sites contained within genes associated with the immune and cardiac system, as well as hematopoiesis. Differences observed in the complete blood counts of PI heifers include increased monocytes, microcytic anemia, and elevated platelets with decreased mean platelet volume. Flow cytometry revealed increased classical monocytes, B cells, and CD4⁺/CD8B⁺ and CD25⁺/CD127⁻ T cells, as well as decreased γδ⁺, CD4⁺, and CD4⁻/CD8B⁻ T cells. Investigation of the PI methylome provides a new perspective on the mechanisms of pathologies and provides potential biomarkers for the rapid identification of PI cattle. Full article

The effect of thermo-oxidative aging on the hyperelastic behavior of ethylene propylene diene monomer (EPDM) rubber was investigated by a combined experimental and theoretical modeling approach. Firstly, the uniaxial tensile test of aged and unaged EPDM rubber was carried out. The test results show that the unaged EPDM rubber had the nonlinear large deformation characteristic of a “S” shape. The stiffness of the EPDM rubber was found to increase with the aging time and aging temperature. Then, in order to quantitatively characterize the hyperelastic behavior of unaged EPDM rubber, the fitting performances of the Mooney–Rivlin, Arruda–Boyce, and Ogden models were compared based on a uniaxial tensile stress–strain curve. The results show that the Ogden model provided a more accurate representation of the hyperelastic behavior of unaged EPDM rubber. Subsequently, the Dakin dynamic equation was adopted to associate the parameters of the Ogden model with the aging time, and the Arrhenius relationship was utilized to introduce the aging temperature into the rate term of the Dakin dynamic equation, thereby establishing an improved Ogden constitutive model. This improved model expanded the Ogden model’s ability to explain aging time and aging temperature. Finally, the improved model prediction results and the test results were compared, and they indicate that the proposed improved Ogden constitutive model can accurately describe the hyperelastic behavior of aged and unaged EPDM rubber. Full article

Background: Medulloblastoma is the most common malignant brain tumor in children, classified into four primary molecular subgroups: WNT, SHH, Group 3, and Group 4, each exhibiting significant molecular heterogeneity and varied survival outcomes. Accurate classification of these subgroups is crucial for optimizing treatments and improving patient outcomes. DNA methylation profiling is a promising approach for subgroup classification; however, its application is still evolving, with ongoing efforts to improve accessibility and develop more accurate classification methods. Objectives: This study aims to develop a supervised machine learning-based framework using Illumina 450K methylation data to classify medulloblastoma into seven molecular subgroups: WNT, SHH-Infant, SHH-Child, Group3-LowRisk, Group3-HighRisk, Group4-LowRisk, and Group4-HighRisk, incorporating age and risk factors for enhanced subgroup differentiation. Methods: The proposed model leverages six metagenes, capturing the underlying patterns of the top 10,000 probes with the highest variances from Illumina 450K data, thus enhancing methylation data representation while reducing computational demands. Results: Among the models evaluated, the SVM achieved the highest performance, with a mean balanced accuracy 98% and a macro-averaged AUC of 0.99 in an independent validation. This suggests that the model effectively captures the relevant methylation patterns for medulloblastoma subgroup classification. Conclusions: The developed SVM-based model provides a robust framework for accurate classification of medulloblastoma subgroups using DNA methylation data. Integrating this model into clinical decision making could enhance subgroup-directed therapies and improve patient outcomes. Full article

This study investigates the effects of aging trees on wood properties, which are caused by climate change, the withdrawal of coniferous species from Central Europe, and the increased crown sweep in old beech stands. The research was carried out in old tree stands with a high proportion of Scots pine (Pinus sylvestris L.) and beech (Fagus sylvatica L.) species. The collected material was from five tree pine stands aged between 151 and 182 and three beech stands between the ages of 165 and 184. The samples were subjected to an analysis of wood properties such as density and modulus of elasticity. The results and findings of this study indicate that the Scots pine currently reaches the optimal wood tissue quality at around 80 years of age, which is approximately 20 years earlier than the species’ anticipated cutting age. However, the beech, which reaches maturity at about 120–140 years, reaches the maximal quality of wood tissue already at the age of 80–90 years. Above the age of 110, the quality of beech wood (density and modulus of elasticity) decreases. Moreover, it is necessary to emphasize that the radial trend of wood density does not coincide with the trend of the modulus of elasticity. Additionally, it is found that wood density is not a perfect representation of its mechanical qualities; it can, however, be regarded as a measure of the technical quality of wood tissue. The results indicate that the pine and the beech that grow on the European Plain mature faster and reach technical quality earlier than just a couple of decades before. Full article

In Italy, the current demographic transition makes it a strategic goal to realign the distribution of health services based on the population aged over 65. The traditional challenge of achieving a fine-grained assessment of health resource statistics and evaluating the fairness of health services across regions is a concern in current research on the fairness of health services. In this study, the authors propose a methodological approach to foster a novel analysis of fairness in the allocation of primary health care services in Italy with a specific focus on the population aged 65 or over, which facilitates the processing of extensive administrative and demographic data to ensure a clear and precise visualization for informed decision making. The proposed methodology integrates convolution matrices weighted by aged population density within a fine-grained geographic grid representation. This approach is combined with an image convolution technique for filtering, enabling an effective estimation of health resource impact and a clear visualization of their spatial distribution across geographical areas. The integration of several data sources to evaluate the equity in accessibility distribution through the Gini index is also exploited to quantify the disparity between healthcare service provision and the aged population at the regional district level. Our findings showed a substantial unfairness in service distribution, with a concentration of healthcare effect in prominent regions such as Campania, Lazio, and Lombardia, indicating that healthcare accessibility is predominantly disproportionate in Italy, particularly for the population aged over 65. Full article

Maternal nutrition’s impact on liver transcriptome in beef cattle offspring is still underexplored. We investigated the long-term effects of maternal nutrition strategies on the liver transcriptome of pre-slaughter Nelore bulls. Pregnant cows were divided into three groups, each receiving different nutritional regimens: NP (control, only mineral supplementation), PP (late gestation protein–energy supplementation), and FP (protein–energy supplementation throughout pregnancy). Liver samples were collected from male offspring aged 22.5 ± 1 months and analyzed using RNA-Seq (n = 5 per treatment). Principal component analysis (PCA) and differential gene expression analysis were carried out in an R statistical environment. Genes were considered significant when FDR < 0.05. The over-representation analysis (ORA) was performed using the clusterProfiler package from R. Metabolic pathways were considered significant when the Q-value < 0.1. The PCA showed overlapping clusters among the groups. We identified 16 differentially expressed genes (DEGs) associated with PP × NP contrast, four with FP × NP, and two with FP × PP. The ORA revealed two significant pathways (thiamine and butanoate metabolism). The identified genes and pathways were associated with vitamins, energy, oxidative metabolism, and immune function. This study emphasizes the more significant long-term effects of the PP treatment on the offspring’s liver transcriptome compared to the FP treatment. Full article

The phenomenological universalities (PU) approach is employed to derive the Richards growth function in the unknown hyperbolic representation. The formula derived can be applied in theoretical modeling of sigmoid and involuted growth of biological systems. In the model proposed, the exponent in the Richards function has the following clear biological meaning: it describes the number of cells doubling, leading to an increase in a biomass of the system from $m_0$ (birth or hatching mass) to the limiting value $m_{\infty }$ (mass at maturity). The generalized form of the universal growth function is derived. It can be employed in fitting the weight–age data for a variety of biological systems, including copepods, tumors, fish, birds, mammals and dinosaurs. Both the PU methodology and the Richards model can be effectively applied in the theoretical modeling of infectious disease outbreaks. To substantiate this assertion, the simplest PU-SIR (Susceptible–Infective–Removed) epidemiological model is considered. In this approach, it is assumed that the number of births is approximately equal to the number of deaths, while the impact of recovered (quarantined) individuals on the dynamics of the infection is negligible. Full article

Improving public awareness of palliative care is crucial for improving access to, and uptake of, palliative care, which has demonstrated benefits for patients and health systems. However, there is a lack of engaging, accessible educational palliative care resources designed for public audiences. As part of a larger quality improvement initiative to strengthen awareness of palliative care, we developed “Understanding Palliative Care”—an innovative, online educational module incorporating best practices for defining and promoting palliative care to a public audience. An expert working group with representation from nursing, medicine, social work, instructional design, and care navigation advised on the development of the module. Incorporating the perspectives of Albertans with lived palliative care experience was deemed essential by the working group. We identified three Albertans (one patient and two family caregivers) of diverse ages and cultural backgrounds who had personally benefitted from palliative care and consented to record virtual interviews. We incorporated multiple interview segments into the module that highlight the physical, emotional, social, and spiritual support provided by palliative care. Finally, a panel of thirteen public volunteers provided feedback on the content, design, and navigation of the draft module. The Understanding Palliative Care module fills an important gap in Alberta, providing a free, online, evidence-based, and engaging educational tool to improve public awareness and understanding of palliative care. Full article

Sub-symbolic Machine Learning (ML) techniques, and specifically Neural Network-based ones, recently took over the research landscape, thanks to their efficiency and impressive effectiveness. On the other hand, the recent debate on ethics and AI and the first regulations on AI are progressively calling for anthropocentricity, which in turn requires explicit, human-understandable, and explainable approaches and representations that allow humans to be active parts in the loop. In these cases, logic-based approaches are more suitable. The Inductive Logic Programming (ILP) branch of research in ML provides an anwer to this need and a uniform and unifying framework for three relevant industrial and research concerns: management of databases, implementation of software systems, and modeling of human-like reasoning strategies. A particular ILP framework based on the Object Identity (OI) assumption was proposed in the 1990s, for which desirable theoretical and pratical properties were demonstrated and working tools and systems that successfully approached real-world and classical problems in AI were developed. In an age when mainstream research and media seem to reduce AI and ML to just deep learning, this paper celebrates the 30th anniversary of OI by providing for the first time a comprehensive overview of the framework to be used as a reference for researchers still interested in investigating the ILP approach to ML. Full article

Medication adherence is a crucial factor for managing chronic conditions, especially in aging adults. Previous studies have identified predictors of medication adherence. However, current methods fail to capture the time-varying nature of how risk factors can influence adherence behavior. This objective of this study was to implement multitrajectory group-based models to compare a time-varying to a time-fixed approach to identifying non-adherence risk factors. The study population comprised 11,068 Medicare beneficiaries aged 65 and older taking select medications for hypertension, high blood cholesterol, and oral diabetes medications, between 2008 and 2016. Time-fixed predictors (e.g., sex, education) were examined using generalized multinomial logistic regression, while time-varying predictors were explored through multitrajectory group-based modeling. Several predisposing, enabling, and need characteristics were identified as risk factors for following at least one non-adherence trajectory. Time-varying predictors displayed an alternative representation of those risk factors, especially depression symptoms. This study highlights the dynamic nature of medication adherence predictors and the utility of multitrajectory modeling. Findings suggest that targeted interventions can be developed by addressing the key time-varying factors affecting adherence. Full article

This study investigates the relative age effect (RAE) in Spanish orienteering, comparing birth distributions between the general population and federated athletes, as well as across different age groups. A cross-sectional and retrospective observational analysis was conducted on data from 34,718 athletes federated (female: n = 12,338; male: n = 22,380) with the Spanish Orienteering Federation (FEDO) between 2005 and 2023. Birth distributions by quartiles and semesters were compared with birth data from the Spanish National Institute of Statistics. Chi-square tests, Z-tests for proportions, and odds ratio (OR) analysis were used to assess differences and the magnitude of the RAE. A significant RAE was found in the total population of federated athletes and the youth and male elite subgroups, with an over-representation of athletes born in the first semester of the year. The effect was small in magnitude but persistent in youth categories and intensified in the male elite category. In contrast, no significant RAE was observed in the female elite category. The RAE exists in Spanish orienteering, although its magnitude is smaller compared to other sports. The persistence of the RAE in the male elite category suggests that advantages accumulated in formative stages influence access to higher levels. Strategies to mitigate the impact of the RAE in talent identification and development are recommended. Full article

Episodic memory training plays a crucial role in cognitive enhancement, particularly in addressing age-related memory decline and cognitive disorders. Accurately assessing the effectiveness of such training requires reliable methods to capture changes in memory function. Electroencephalography (EEG) offers an objective way of evaluating neural activity before and after training. However, EEG classification in episodic memory assessment remains challenging due to the variability in brain responses, individual differences, and the complex temporal–spatial dynamics of neural signals. Traditional EEG classification methods, such as Support Vector Machines (SVMs) and Convolutional Neural Networks (CNNs), face limitations when applied to episodic memory training assessment, struggling to extract meaningful features and handle the inherent uncertainty in EEG signals. To address these issues, this paper introduces DU-former, which improves feature extraction and enhances the model’s robustness against noise. Specifically, data uncertainty (DU) explicitly handles data uncertainty by modeling input features as Gaussian distributions within the reparameterization module. One branch predicts the mean through convolution and normalization, while the other estimates the variance via average pooling and normalization. These values are then used for Gaussian reparameterization, enabling the model to learn more robust feature representations. This approach allows the model to remain stable when dealing with complex or noisy data. To validate the method, an episodic memory training experiment was designed with 17 participants who underwent 28 days of training. Behavioral data showed a significant reduction in task completion time. Object recognition accuracy also improved, as indicated by the higher proportion of correctly identified target items in the episodic memory testing game. Furthermore, EEG data collected before and after the training were used to evaluate the DU-former’s performance, demonstrating significant improvements in classification accuracy. This paper contributes by introducing uncertainty learning and proposing a more efficient and robust method for EEG signal classification, demonstrating superior performance in episodic memory assessment. Full article

Background/Objectives: Dual tasks are increasingly being employed in research on concussion, since they provide a somewhat more realistic representation of the demands athletes face on the field. While single cognitive and motor tasks have revealed persisting autonomic alterations in concussed athletes, the unique autonomic response required by a dual task remains unexplored in this population. The purpose of this study was to evaluate autonomic responses in asymptomatic athletes with a history of concussion (m = 5.46 months ± 2.00) following a complex dual task. Methods: Heart rate variability (HRV), a biomarker of autonomic regulation, was measured in 34 athletes (16 concussed, 18 controls) aged 17 to 24. HRV data were collected using the Polar H10 chest belt. Five-minute segments were extracted under four conditions: rest, following a cognitive task (switch task), after a dual task combining both motor and cognitive components, and after the same dual task preceded by 20 min of aerobic exercise. A series of 4 × 2 mixed-design ANOVAs were conducted to assess the differences between the conditions and groups. Results: The results indicated a significant increase in a global marker of HRV (i.e., the standard deviation of normal-to-normal intervals (SDNN)) following the switch task compared to rest (p = 0.014) only in concussed participants. These results suggest that the switch task may stimulate frontal regions and promote a parasympathetic response, as reflected by the rise in HRV. Notably, the effect of the switch task disappeared when combined with the motor component of the dual task, whether it was preceded by aerobic exercise or not. Conclusions: The dual task results indicate potential competing mechanisms between the motor and cognitive components of the task, which future studies using similar protocols should consider. Meanwhile, the switch task appears sufficiently demanding to reveal autonomic alterations, which, when measured through HRV, may constitute a relevant clinical tool for assessing athletes’ readiness to return to sport and academic study. Full article