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Inadequate mechanical compliance of orthopedic implants can result in excessive strain of the bone interface, and ultimately, aseptic loosening. It is hypothesized that a fiber-based biometal with adjustable anisotropic mechanical properties can reduce interface strain, facilitate continuous remodeling, and improve implant survival under complex loads. The biometal is based on strategically layered sintered titanium fibers. Six different topologies are manufactured. Specimens are tested under compression in three orthogonal axes under 3-point bending and torsion until failure. Biocompatibility testing involves murine osteoblasts. Osseointegration is investigated by micro-computed tomography and histomorphometry after implantation in a metaphyseal trepanation model in sheep. The material demonstrates compressive yield strengths of up to 50 MPa and anisotropy correlating closely with fiber layout. Samples with 75% porosity are both stronger and stiffer than those with 85% porosity. The highest bending modulus is found in samples with parallel fiber orientation, while the highest shear modulus is found in cross-ply layouts. Cell metabolism and morphology indicate uncompromised biocompatibility. Implants demonstrate robust circumferential osseointegration in vivo after 8 weeks. The biometal introduced in this study demonstrates anisotropic mechanical properties similar to bone, and excellent osteoconductivity and feasibility as an orthopedic implant material.
The automatic classification of the modulation format of a detected signal is the intermediate step between signal detection and demodulation. If neither the transmitted data nor other signal parameters such as the frequency offset, phase offset and timing information are known, then automatic modulation classification (AMC) is a challenging task in radio monitoring systems. The approach of clustering algorithms is a new trend in AMC for digital modulations. A novel algorithm called `highest constellation pattern matching' is introduced to identify quadrature amplitude modulation and phase shift keying signals. The obtained simulation and measurement results outperform the existing algorithms for AMC based on clustering. Finally, it is shown that the proposed algorithm works in a real monitoring environment.