[Modeling and comfort analysis of arrayed air cushion mattress for pressure ulcer prevention and assisted repositioning].

Assisting immobile individuals with regular repositioning to adjust pressure distribution on key prominences such as the back and buttocks is the most effective measure for preventing pressure ulcers. However, compared to active self-repositioning, passive assisted repositioning results in distinct variations in force distribution on different body parts. This incongruity can affect the comfort of repositioning and potentially lead to a risk of secondary injury, for certain trauma or critically ill patients. Therefore, it is of considerable practical importance to study the passive turning comfort and the optimal turning strategy. Initially, in this study, the load-bearing characteristics of various joints during passive repositioning were examined, and a wedge-shaped airbag configuration was proposed. The airbags coupled layout on the mattress was equivalently represented as a spring-damping system, with essential model parameters determined using experimental techniques. Subsequently, different assisted repositioning strategies were devised by adjusting force application positions and sequences. A human-mattress force-coupled simulation model was developed based on rigid human body structure and equivalent flexible springs. This model provided the force distribution across the primary pressure points on the human body. Finally, assisted repositioning experiments were conducted with 15 participants. The passive repositioning effectiveness and pressure redistribution was validated based on the simulation results, experimental data, and questionnaire responses. Furthermore, the mechanical factors influencing comfort during passive assisted repositioning were elucidated, providing a theoretical foundation for subsequent mattress design and optimization of repositioning strategies.

Numerical simulation modeling and kinematic analysis onto double wedge-shaped airbag of nursing appliance.

In previous studies, the numerical modeling and analyzing methods onto industrial or vehicle airbags dynamics were revealed to have high accuracy regarding their actual dynamic properties, but there are scarcely airbag stiffness modeling and comfortableness investigations of nursing cushion or mattress airbags. This study constructs a numerical model illustrating the association between the stiffness property and the internal gas mass of the wedge-shaped airbag of nursing appliance, and then the airbag stiffness variation discipline is described based on various inflation volumes. To start with, based on an averaged pressure prerequisite, a dynamic simulation model of the wedge-shaped airbag is established by the fluid cavity approach. For this modeling, the elastic mechanical behaviors of airbag material are determined according to a material constitutive model built by the quasi-static uniaxial tensile test. Besides, verification experiments clarify that the presented modeling method is accurate for airbag stiffness behavior prediction, and then can be effectively applied into design and optimization phases of wedge-shaped airbags. Ultimately, based on the simulation and experimental results, it is found that the wedge-shaped airbag stiffness exhibits a three stages characteristic evolution with the gas mass increase. Then the mathematical relationship between the airbag stiffness and gas mass is obtained by numerical fitting, which provides a vital basis for structural optimization and differentiated control of nursing equipment airbags.

Numerical simulation-based loaded inflation height modeling of nursing bed airbag.

In previous studies, the numerical simulation models of industrial airbags were verified to have high accuracy regarding their actual dynamics. However, numerical methods were scarcely utilized to simulate and investigate the inflation height behaviors of nursing bed airbag. For this problem, this study constructs a numerical simulation model illustrating the association between the internal pressure and inflating height of nursing bed airbag, under various external loads. Firstly, based on an averaged pressure prerequisite, an airbag dynamic model is established by the control volume approach (the air inside the airbag follows the gas state equation of Poisson's law). Besides, the elastic mechanical behaviors of airbag film material are determined according to a material constitutive model built by the quasi-static uniaxial tensile test. The obtained data are used as the boundary conditions, for the numerical dynamics modeling of the nursing bed airbag. Verification experiments clarify that this numerical modeling is accurate for describing airbag inflation behaviors, and then can be effectively applied to the design and optimization phases of nursing bed airbags. Based on the simulation modeling above, the mathematical equation of controlling airbag inflating height by its internal pressure is obtained. It provides a vital basis for the differentiated and intelligent control of the airbag nursing bed.

Cancer mutational signatures representation by large-scale context embedding.

MOTIVATION: The accumulation of somatic mutations plays critical roles in cancer development and progression. However, the global patterns of somatic mutations, especially non-coding mutations, and their roles in defining molecular subtypes of cancer have not been well characterized due to the computational challenges in analysing the complex mutational patterns. RESULTS: Here, we develop a new algorithm, called MutSpace, to effectively extract patient-specific mutational features using an embedding framework for larger sequence context. Our method is motivated by the observation that the mutation rate at megabase scale and the local mutational patterns jointly contribute to distinguishing cancer subtypes, both of which can be simultaneously captured by MutSpace. Simulation evaluations show that MutSpace can effectively characterize mutational features from known patient subgroups and achieve superior performance compared with previous methods. As a proof-of-principle, we apply MutSpace to 560 breast cancer patient samples and demonstrate that our method achieves high accuracy in subtype identification. In addition, the learned embeddings from MutSpace reflect intrinsic patterns of breast cancer subtypes and other features of genome structure and function. MutSpace is a promising new framework to better understand cancer heterogeneity based on somatic mutations. AVAILABILITY AND IMPLEMENTATION: Source code of MutSpace can be accessed at: https://github.com/ma-compbio/MutSpace. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Carbon nanotube salts. Arylation of single-wall carbon nanotubes.

[reaction: see text] Carbon nanotube salts prepared by treating single-wall carbon nanotubes (SWNTs) with lithium in liquid ammonia react readily with aryl iodides to give SWNTs functionalized by aryl groups.