A Concise Review of Recent Advancements in Carbon Nanotubes for Aerospace Applications.

Carbon nanotubes (CNTs) have attracted significant attention in the scientific community and in the industrial environment due to their unique structure and remarkable properties, including mechanical strength, thermal stability, electrical conductivity, and chemical inertness. Despite their potential, large-scale applications have been limited by challenges such as high production costs and catalyst contamination. In aerospace applications, CNTs have demonstrated considerable promise either in the form of thin layers or as reinforcements in polymer and metal matrices, where they enhance mechanical, thermal, and electromagnetic performance in lightweight composites.

Baseline characteristics and 2-year functional outcome data of patients undergoing an arthroscopic rotator cuff repair in Switzerland, results of the ARCR_Pred study.

The ARCR_Pred study was initiated to document and predict the safety and effectiveness of arthroscopic rotator cuff repair (ARCR) in a representative Swiss patient cohort. In the present manuscript, we aimed to describe the overall and baseline characteristics of the study, report on functional outcome data and explore case-mix adjustment and differences between public and private hospitals. Between June 2020 and November 2021, primary ARCR patients were prospectively enrolled in a multicenter cohort across 18 Swiss and one German orthopedic center.

Resting-State Cortico-Cerebellar Connectivity Correlates with Post-Stroke Motor Recovery - A Prospective Functional MRI Study.

Cerebellar functional and structural connectivity are likely related to motor function after stroke. Less is known about motor recovery, which is defined as a gain of function between two time points, and about the involvement of the cerebellum. Fifteen patients who were hospitalized between 2018 and 2020 for a first cerebral ischemic event with persistent upper limb deficits were assessed by resting-state functional MRI (rsfMRI) and clinical motor score measurements at 3, 9 and 15 weeks after stroke.

Low-dimensional controllability of brain networks.

Identifying the driver nodes of a network has crucial implications in biological systems from unveiling causal interactions to informing effective intervention strategies. Despite recent advances in network control theory, results remain inaccurate as the number of drivers becomes too small compared to the network size, thus limiting the concrete usability in many real-life applications. To overcome this issue, we introduced a framework that integrates principles from spectral graph theory and output controllability to project the network state into a smaller topological space formed by the Laplacian network structure.