Propagation of Orientation Across Lengthscales in Sheared Self-Assembling Hierarchical Suspensions via Rheo-PLI-SAXS.

Simultaneous rheological, polarized light imaging, and small-angle X-ray scattering experiments (Rheo-PLI-SAXS) are developed, thereby providing unprecedented level of insight into the multiscale orientation of hierarchical systems in simple shear. Notably, it is observed that mesoscale alignment in the flow direction does not develop simultaneously across nano-micro lengthscales in sheared suspensions of rod-like chiral-nematic (meso) phase forming cellulose nanocrystals. Rather, with increasing shear rate, orientation is observed first at mesoscale and then extends to the nanoscale, with influencing factors being the aggregation state of the hierarchy and concentration.

Halbach Array Induced Magnetic Field Alignment in Boron Nitride Nanocomposites.

Thermal conductivity enhancement in polymers is vital for advanced applications. This study introduces a novel method to align hexagonal boron nitride (hBN) nanosheets within polydimethylsiloxane (PDMS) matrices using a Halbach array to create a highly uniform magnetic field. This technique achieves significant improvements in thermal conductivity by effectively aligning hBN nanosheets.

Assessing the Nursing Workload in the Cardiothoracic Intensive Care Unit: Comparative Study.

Aims: This study aimed to assess nursing workload in Cardiac Intensive Care Unit (CICU) after three cardiothoracic surgery procedures during first four postoperative days using Nursing Activities Score (NAS) and Nine Equivalents of Nursing Manpower Use Score (NEMS) systems, to compare their performance for that purpose and to investigate association between nursing workload and type of surgery.

Design: A comparative study.

Methods: The research environment includes CICU of the University Hospital for Cardiovascular Diseases in Serbia.

Transatlantic transferability and replicability of machine-learning algorithms to predict mental health crises.

Transferring and replicating predictive algorithms across healthcare systems constitutes a unique yet crucial challenge that needs to be addressed to enable the widespread adoption of machine learning in healthcare. In this study, we explored the impact of important differences across healthcare systems and the associated Electronic Health Records (EHRs) on machine-learning algorithms to predict mental health crises, up to 28 days in advance. We evaluated both the transferability and replicability of such machine learning models, and for this purpose, we trained six models using features and methods developed on EHR data from the Birmingham and Solihull Mental Health NHS Foundation Trust in the UK.

The Relationship Between Big Five Personality Traits and Sleep Patterns: A Systematic Review.

Sleep, an intrinsic aspect of human life, is experienced by individuals differently which may be influenced by personality traits and characteristics. Exploring how these traits influence behaviors and sleep routines could be used to inform more personalized and effective interventions to promote better sleep. Our objective was to summarize the existing literature on the relationship between personality traits and sleep patterns through a systematic review.