Biosensing technology is leading the next wave of innovation, transforming how we engage with our environment, monitor our health, and connect with each other. Biosensors are analytical devices that combine biological sensing with a physical or chemical detector to identify and measure specific substances. They play a critical role in many aspects of modern science and technology, including medical diagnostics, environmental monitoring, food and agriculture, and biotechnology. From wearable health monitors to implantable devices or environmental biosensors, this technology is redefining what it means for computing to be truly pervasive.

With billions of smartphones in use globally, the daily time spent on these devices contributes significantly to overall electricity consumption. Given this scale, even minor reductions in smartphone power use could result in substantial energy savings. This study explores the impact of Lambda functions on resource consumption in mobile programming. While Lambda functions are known for enhancing code readability and conciseness, their use does not add to the functional capabilities of a programming language. Our research investigates the implications of using Lambda functions in terms of battery utilization, memory usage, and execution time compared to equivalent code structures without Lambda functions. Our findings reveal that Lambda functions impose a considerable resource overhead on mobile devices without offering additional functionalities.

Augmented reality (AR) technology is transforming minimally invasive surgeries by merging physical and virtual spaces to improve intraoperative guidance and training. We present SurgiKLAR, a mixed reality framework for improved surgical training, to clearly (“klar”) visualize segmented anatomies from preoperative scans coregistered with patient-specific models to simulate surgical procedures. The system is adapted for gynecology surgeries, featuring realistic uterine models and instruments for adaptive simulations, personalized guidance, and real-time alerts. Preliminary evaluations with a 3D-printed phantom demonstrated its potential application in preplanning complex scenarios. We conducted a two-phase user study to evaluate the usability of the SurgiKLAR system. Phase I assessed AR adoption challenges, and Phase II validated usability for training. The user feedback highlighted the importance of accurate visualizations and the need for extensive training programs. Future work involves an extension to diverse surgical domains, improved precision, and enhanced safety, thereby highlighting the transformative potential of cross-reality in surgery.