Phase Formation, Thermal Stability and Mechanical Properties of a Cu-Al-Ni-Mn Shape Memory Alloy Prepared by Selective Laser Melting

Selective laser melting (SLM) is an additive manufacturing process used to produce parts with complex geometries layer by layer. This rapid solidification method allows fabricating samples in a non-equilibrium state and with refined microstructure. In this work, this method is used to fabricate 3 mm diameter rods of a Cu-based shape memory alloy. The phase formation, thermal stability and mechanical properties were investigated and correlated. Samples with a relative density higher than 92% and without cracks were obtained. A single monoclinic martensitic phase was formed with average grain size ranging between 28 to 36 μm. The samples exhibit a reverse martensitic transformation temperature around 106 ± 2 °C and a large plasticity in compression (around 15±1%) with a typical “double-yielding” behaviour

Deep Learning Algorithms in Mobile Edge with Real-Time Abnormal Event Detection for 5G-IoT Devices

IoT is becoming increasingly popular due to its quick expansion and variety of applications. In addition, 5G technology helps with communication and network connectivity. This work integrates C-RAN with IoT networks to provide an experimental 5G testbed. In a 5G IoT environment, this experience is utilized to enhance both perpendicular and flat localization (3D localization). DRCaG, an acronym for the proposed model, stands for a deep, complicated network with a gated layer on top. The performance of the proposed model has been demonstrated through extensive simulations in terms of learning reduction, accuracy, and matrix disorientation, with a variable signal-to-noise ratio (SNR) spanning from 20 dB to + 20 dB, which illustrates the superiority of DRCaG compared to others. An online, end-to-end solution based on deep learning techniques is presented in this study for the fast, precise, reliable, and automatic detection of diverse petty crime types. By detecting tiny crimes like hostility, bag snatching, and vandalism, the suggested system may not only identify unusual passenger behavior like vandalism and accidents but also improve passenger security. The solution performs admirably in a variety of use cases and environmental settings

Study on the inflammatory response of PMMA/polystyrene/silica nanocomposite membranes for drug delivery and dental applications.

BackgroundThe application of polymeric materials in medical industry has grown drastically in the last two decades due to their various advantages compared to existing materials. The present research work emphases on the sol-gel technique to formulate the polymethyl methyl acrylate/polystyrene/silica composite membrane.MethodsThe characteristic of the composite was investigated through modern state art of instrumentation.ResultsThe functional groups attached to the polymer was absorbed by FTIR. The FTIR spectrum confirm that the blend was mixed thoroughly and the formation of unite intimately between the polymers. The membranes were observed by SEM for its surface homogeneity which depends upon the composition of the two blending polymers. The captured SEM images showed the formation of microcracks on the surface, which was evidently controlled by varying the constituent polymer ratios. The prepared blend membranes with 2:1 ratio of PMMA/PS/Si displayed higher water uptake compared to other blended membranes. The composite membranes had good hydroxyl apatite growth in SBF solution. Furthermore, the in vitro cytotoxicity studies carried out by MTT method, using RAW macrophage cells showed that all the samples exhibited excellent cell viability.ConclusionThe inflammatory response of composite with equal concentration of PMMA-PS were performed and observed no inflammation in comparison with control and other tested concentrations

Correction: Study on the inflammatory response of PMMA/polystyrene/silica nanocomposite membranes for drug delivery and dental applications.

[This corrects the article DOI: 10.1371/journal.pone.0209948.]