Enhancing the porosity of biphasic calcium phosphate using polyethylene glycol as the porogen for bone regeneration applications.

Biphasic calcium phosphate (BCP) has been used as a material to support bone grafting, repair, recovery, and regeneration over the past decades. However, the inherent weakness of BCP is its low porosity, which limits the infiltration, differentiation, and proliferation of bone cells. To address this issue, porous BCP was synthesized using polyethylene glycol (PEG) 1000 with weight ratio ranging from 20%-60% in BCP as the porogen through the powder-forming method.

Helical-photon-dressed states determining unidirectional π-electron rotations in aromatic ring molecules.

We theoretically demonstrated that helical-photon-dressed states determine the rotational directions of the π-electrons of aromatic ring molecules formed by a circularly polarized or an elliptically polarized laser. This theory was verified using a minimal three-electronic-state model under the frozen nuclei condition. The model consists of the ground state and either a doubly degenerate electronic excited state or two quasi-degenerate excited states.

The natural history of neurolymphomatosis.

Background: Neurolymphomatosis is a lymphoid malignancy of the peripheral nervous system and its natural history is poorly understood.

Methods: We performed PubMed search and extracted clinical data for Kaplan-Meier statistics to determine outcome parameters over time. Kruskal-Wallis test was performed to compare prognostic factors.

Improving the material extrusion processing of thermoplastic olefin/graphene nanoplatelet composites through control of the morphology.

The aim of this research is to develop thermoplastic olefin (TPO) composites containing polypropylene (PP), an elastomeric ethylene-octene copolymer (EOC) and graphene nanoplatelets (GNPs), suitable for material extrusion (MEX). A PP functionalized with amino-pyridine (PP-g-Py) was used as a compatibilizer. The composite blends had droplet-matrix morphology at compositions as high as 40 wt% EOC.

EHNet: Efficient Hybrid Network with Dual Attention for Image Deblurring.

The motion of an object or camera platform makes the acquired image blurred. This degradation is a major reason to obtain a poor-quality image from an imaging sensor. Therefore, developing an efficient deep-learning-based image processing method to remove the blur artifact is desirable.