Sallingwhitfield4418

Polymers are widely used in many applications in the field of biomedical engineering. Among eclectic selections of polymers, those with low melting temperature (Tm less then 200 °C), such as poly(methyl methacrylate), poly(lactic-co-glycolic acid), or polyethylene, are often used in bone, dental, maxillofacial, and corneal tissue engineering as substrates or scaffolds. These polymers, however, are bioinert, have a lack of reactive surface functional groups, and have poor wettability, affecting their ability to promote cellular functions and biointegration with the surrounding tissue. Improving the biointegration can be achieved by depositing hydroxyapatite (HAp) on the polymeric substrates. Conventional thermal spray and vapor phase coating, including the Food and Drug Administration (FDA)-approved plasma spray technique, is not suitable for application on the low Tm polymers due to the high processing temperature, reaching more than 1000 °C. Two non-thermal HAp coating approaches have been described in the literature, namely, the biomimetic deposition and direct nanoparticle immobilization techniques. In the current review, we elaborate on the unique features of each technique, followed by discussing the advantages and disadvantages of each technique to help readers decide on which method is more suitable for their intended applications. Finally, the future perspectives of the non-thermal HAp coating are given in the conclusion.We prepared poly(ethylaniline)-coated graphene oxide nanoflakes and then treated them with different concentrations of hydrazine solution to form dielectric composite nanoflakes having different reduction degrees of reduced graphene oxide core and insulating polyethylaniline shell (PEANI/rGO). The morphology of PEANI/rGO was observed by scanning electron microscopy, while the chemical structure was confirmed by Fourier transform infrared spectroscopy and X-ray photoelectron spectrometer. The influence of reduction degrees on the conductivity, dielectric polarization and electrorheological effect of PEANI/rGO in suspensions was investigated by dielectric spectroscopy and rheological test under electric fields. It shows that the PEANI/rGO has two interfacial polarization processes respectively due to rGO core and PEANI shell. As the number of hydrazine increases, the conductivity and polarization rate of rGO core increase. Protokylol cell line As a result, the difference between the polarization rate of rGO core and that of the PEANI shell gradually becomes large. This increased difference does not significantly decrease the yield stress but causes the flow instability of PEANI/GO suspensions under the simultaneous action of electric and shear fields.Melanoma remains the most lethal form of skin cancer and most challenging to treat despite advances in the oncology field. Our work describes the utilization of nanotechnology to target melanoma locally in an attempt to provide an advanced and efficient quality of therapy. Amino-functionalized mesoporous silica nanoparticles (MSN-NH2) were developed in situ through the utilization of anionic surfactant and different volumes of 3-aminopropyltriethoxysilane (APTES) as a co-structure directing agent (CSDA). Prepared particles were characterized for their morphology, particles size, 5-flurouracol (5-FU) and dexamethasone (DEX) loading capacity and release, skin penetration, and cytotoxicity in vitro in HT-144 melanoma cells. Results of transmission electron microscopy (TEM) and nitrogen adsorption-desorption isotherm showed that using different volumes of APTES during the functionalization process had an impact on the internal and external morphology of the particles, as well as particle size. However, changing tEX induced 5-FU resistance in melanoma cells.K9 optical glass has superb material properties used for various industrial applications. However, the high hardness and low fracture toughness greatly fluctuate the cutting force generated during the grinding process, which are the main factors affecting machining accuracy and surface integrity. With a view to further understand the grinding mechanism of K9 glass and improve the machining quality, a new arithmetical force model and parameter optimization for grinding the K9 glass are introduced in this study. Originally, the grinding force components and the grinding path were analyzed according to the critical depth of plowing, rubbing, and brittle tear. Thereafter, the arithmetical model of grinding force was established based on the geometrical model of a single abrasive grain, taking into account the random distribution of grinding grains, and this fact was considered when establishing the number of active grains participating in cutting Nd-Tot. It should be noted that the tool diameter changed with machining, therefore this change was taking into account when building the arithmetical force model during processing as well as the variable value of the maximum chip thickness amax accordingly. Besides, the force analysis recommends how to control the processing parameters to achieve high surface and subsurface quality. Finally, the force model was evaluated by comparing theoretical results with experimental ones. The experimental values of surface grinding forces are in good conformity with the predicted results with changes in the grinding parameters, which proves that the mathematical model is reliable.For underwater acoustic covert communications, biomimetic covert communications have been developed using dolphin whistles. The conventional biomimetic covert communication methods transmit slightly different signal patterns from real dolphin whistles, which results in a low degree of mimic (DoM). In this paper, we propose a novel biomimetic communication method that preserves the large DoM with a low bit error rate (BER). For the transmission, the proposed method utilizes the various contours of real dolphin whistles with the link information among consecutive whistles, and the proposed receiver uses machine learning based whistle detectors with the aid of the link information. Computer simulations and practical ocean experiments were executed to demonstrate the better BER performance of the proposed method. Ocean experiments demonstrate that the BER of the proposed method was 0.002, while the BER of the conventional Deep Neural Network (DNN) based detector showed 0.36.