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Triply Periodic Minimal Surfaces (TPMS), such as Gyroid, are widely accepted for bone tissue engineering due to their interconnected porous structures with tunable properties that enable high surface area to volume ratios, energy absorption, and relative strength. Among these topologies, the Fischer-Koch-S (FKS) has also been suggested for compact bone scaffolds, but few studies have investigated these structures beyond computer simulations. FKS scaffolds have been fabricated in metal and polymer, but to date none have been fabricated in a ceramic used in bone tissue engineering (BTE) scaffolds. This study is the first to fabricate ceramic FKS scaffolds and compare them with the more common Gyroid topology. Results showed that FKS scaffolds were 32% stronger, absorbed 49% more energy, and had only 11% lower permeability than Gyroid scaffolds when manufactured at high porosity (70%). Both FKS and Gyroid scaffolds displayed strength and permeability in the low range of trabecular long bones with high reliability (Weibull failure probability) in the normal direction. Fracture modes were further investigated to explicate the quasi-brittle failure exhibited by both scaffold topologies, exploring stress-strain relationships along with scanning electron microscopy for failure analysis. Considering the physical aspects of successful bone tissue engineering scaffolds, FKS scaffolds appear to be more promising for further study as bone regeneration scaffolds than Gyroid due to their higher compressive strength and reliability, at only a small penalty to permeability. In the context of BTE, FKS scaffolds may be better suited than Gyroids to applications where denser bone and strength is prioritized over permeability, as suggested by earlier simulation studies.

Automated remote sensing has revolutionized the fields of wildlife ecology and environmental science. Yet, a cost-effective and flexible approach for large scale monitoring has not been fully developed, resulting in a limited collection of high-resolution data. Here, we describe BioSense, a low-cost and fully programmable automated sensing platform for applications in bioacoustics and environmental studies. Our design offers customization and flexibility to address a broad array of research goals and field conditions. Each BioSense is programmed through an integrated Raspberry Pi computer board and designed to collect and analyze avian vocalizations while simultaneously collecting temperature, humidity, and soil moisture data. We illustrate the different steps involved in manufacturing this sensor including hardware and software design and present the results of our laboratory and field testing in southwestern United States.