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A multi-perspective interpretative phenomenological analysis of patient and bed partner experiences with CPAP therapy adaptation in obstructive sleep apnoea
Trimethylamine-N-oxide promotes fibrotic activation of quiescent valvular interstitial cells via endoplasmic reticulum stress
Enhancing DAS sensitivity through structural optimization of thin-walled cylinders
A key amino acid site associated with rhodopsin mammal evolution to diurnal vision
Bodily sensations, emotions, and personality traits in the aesthetic experience of everyday photographs
Abstract Aesthetic evaluation is shaped by a complex interplay of bodily sensations, emotions, and personality traits. However, how these factors are correlated with aesthetic evaluation is not yet fully understood, and most prior work has centered on art-appreciation contexts. Here, we focus on everyday photographs to examine these relationships. In this study, 511 participants observed everyday photographs and reported bodily sensations; selected emotion categories from predefined labels; and rated valence, arousal, and aesthetic evaluation. Participants also completed five personality questionnaires assessing sensitivity to beauty, empathy, openness, alexithymia, and interoceptive awareness. The central finding was a robust association between higher aesthetic evaluation and chest-centered bodily sensations. Also, aesthetic evaluation was positively correlated with high-valence emotion categories and with higher levels of empathy and sensitivity to beauty. The contribution of this study lies in its multifaceted investigation of aesthetic experience grounded in everyday photographs. While broadly consistent with hypotheses derived from conventional art appreciation contexts, the results reveal partially distinct patterns of bodily sensations and emotional responses. Extending this line of inquiry to other aesthetic domains, such as music and morality, could help clarify how beauty arises.
High-power laser powder bed fusion of pure copper for simultaneous achievement of high density and electrical conductivity
Representation learning approach for understanding structured documents
Abstract Current document understanding methods struggle with complex layouts and fail to grasp the deep logical connections between elements like text, figures, and tables. To address this, we introduce the Document Relationship Entity Embedding Learner (D-REEL). This is a novel representation learning framework designed to model intricate semantic relationships within documents. D-REEL works by generating extraction candidates for each article. It then learns dense vector representations (embeddings) for these candidates. By comparing these embeddings, the system accurately assesses semantic correlations between document fields. This allows it to effectively determine if articles are related, regardless of their position on the page. This approach uniquely combines spatial information with domain specific schemas. This enables precise extraction and robust correlation scoring, even across diverse and irregular document layouts. To quantify these connections, we also propose the Semantic Structural Congruence (SSC). This new metric uses location agnostic localization to measure relationships effectively. Experiments on public datasets show significant improvements in correlation accuracy and extraction performance. We achieved an average mAP increment of 2-3% and SSC improvement of almost 10% for the PRIMA dataset.
Spatial distributions, driving factors, and future changes of soil organic carbon in China: arid regions vs. humid regions
Fractographic analysis of 3D printed hybrid ceramic single crowns with different aging and post-curing times: an in-vitro study
Abstract Since increasing 3D-printed ceramics are being introduced to restorative dentistry, a critical evaluation of fabrication parameters for optimal clinical performance is necessary. While post-curing treatments have some influence on material properties, their impact on fracture resistance is not clear. This in vitro study aimed to systematically evaluate the effects of different post-curing times (10 vs. 20 min) and thermocycling aging (5,000 vs. 10,000 cycles) on the fracture resistance and failure modes of 3D-printed hybrid ceramic crowns (Saremco CrownTec). CAD software was utilized to create a standardized digital model of a mandibular first premolar crown. Eighty identical samples were produced with a high-precision 3D printer (Asiga Max UV) using Saremco Print Crowntec hybrid ceramic material. Samples were randomly allocated to two major groups according to post-curing time in a UV polymerization unit (10 min vs. 20 min). Each group was then assigned to two subgroups ( n = 20 each) for thermocycling treatment (5,000 or 10,000 cycles between 5 °C and 55 °C). All crowns were adhesively cemented on PEEK dies with standardized preparation geometry. Fracture resistance testing was accomplished with a universal testing machine (Instron 5966) using a 5.6 mm steel ball indenter at 0.5 mm/min crosshead speed. Failure modes were examined using scanning electron microscopy SEM. Statistical analysis was conducted using two-way ANOVA (α = 0.05). The 10-minute post-cure group showed slightly greater mean fracture resistance (506.36 ± 58.44 N) than the 20-minute group (492.50 ± 76.06 N), but the difference was not statistically significant ( p = 0.428). Thermocycling analysis showed that specimens that underwent 5,000 cycles had slightly better fracture resistance (510.00 ± 72.36 N) than those which underwent 10,000 cycles (488.26 ± 62.64 N), but the difference was also not statistically significant ( p = 0.250). The failure patterns were reported and analyzed with SEM, based on extensions of failures on the axial surface. Although long post-curing times and thermocycling aging exhibited tendencies for decreased fracture resistance, the effects were not statistically significant under the parameters tested. Research in the future should examine the influence of various post-curing intensities and extended aging simulations to further support these results.
A neuro-fuzzy multi-topology adaptive routing framework for QoS-aware healthcare IoT communications
FeBTC as peroxidase mimic for colorimetric cholesterol detection
Nonclassical correlations in binary Bose-Einstein condensates: from double-well confinement to twin Schrödinger cat states
Enhancing peak demand forecasting with adaptive FastICA-transformer and entropy-based model customization
Optimised comorbidity indices can reflect patient performance status in register based studies of prostate cancer
Abstract Eastern Cooperative Oncology Group Performance Status (ECOG-PS) is commonly used in cancer trials to select a study population with good performance, but ECOG-PS is rarely available in health-care registers. We assessed if patient age and comorbidity indices can substitute ECOG-PS when selecting men in register-based studies of advanced prostate cancer. ECOG-PS data for 3966 men on androgen deprivation therapy for prostate cancer were retrieved from Prostate Cancer data Base Sweden. Logistic regression models were used to discriminate between ECOG-PS 0–1 versus 2–4 based on age, Charlson comorbidity index (CCI), a novel Multidimensional Diagnosis-based Comorbidity Index (MDCI) based on ICD codes, and a Drug Comorbidity Index (DCI) based on filled prescriptions. The model based on age, MDCI, and DCI provided the best discrimination (AUC = 0.82; 95% CI 0.81–0.84). In a hypothetical cohort of 1000 men where 750 men had ECOG-PS 0–1, 600 men would be included when excluding those with high risk of ECOG-PS 2–4 using this model and 60 of these would have ECOG 2–4 instead of 250 men if all 1000 men had been included. Age and two new comorbidity indices can with reasonable precision substitute ECOG-PS and help identify subsets of study populations likely to have favourable ECOG-PS.
NF-MORL: a neuro-fuzzy multi-objective reinforcement learning framework for task scheduling in fog computing environments
Cyclophilin D suppresses colorectal cancer progression through the activation of an autophagy-mediated apoptotic pathway
A comprehensive approach to enhancing irrigation network management through the water accounting plus framework
Better sleep is associated with higher academic performance from an actigraphy-based analysis of sleep consistency and grades in college students
Abstract Academic performance is influenced by sleep; however, the relationship between academic outcomes and subjective sleep measures remains controversial. This study aimed to evaluate the association between sleep parameters and academic performance using objective actigraphy measurements alongside subjective assessments. University students ( n = 33) enrolled in a sleep psychology course participated in the study and completed all assessments. Participants completed three subjective questionnaires and 14 consecutive days of actigraphy recordings. They were retrospectively divided into high- and low-performing groups based on the median final exam score. Four objective sleep parameters derived from actigraphy were analyzed: sleep efficiency (SE), sleep onset latency (SOL), wake after sleep onset, and total sleep time (TST). Additionally, the mean absolute deviation (MAD) was introduced to assess night-to-night variability in these parameters. Results showed no significant group differences or correlations between subjective sleep measures and academic performance. In contrast, students with higher exam scores exhibited significantly greater SE, shorter SOL, and lower MADs for SE, SOL, and TST. Final exam scores were significantly associated with SE, SOL, and the MADs of SE, SOL, and TST. These associations were especially pronounced on weekdays, where exam scores correlated with SE, SOL, and the MADs of SE and SOL. Our findings highlight the importance of consistent, high-quality sleep during weekdays for academic success. Furthermore, this study contributes novel insights into the predictive value of night-to-night variability (MAD) in sleep parameters for academic performance. Overall, the results underscore the critical role of stable and efficient weekday sleep in supporting positive academic outcomes.