Autonomous Wireless Sensors (AWSs) are at the core of every Wireless Sensor Network (WSN). Current AWS technology allows the development of many IoT-based applications, ranging from military to bioengineering and from industry to education. The energy optimization of AWSs depends mainly on: Structural, functional, and application specifications. The holistic design methodology addresses all the factors mentioned above. In this sense, we propose an original solution based on a novel architecture that duplicates the transceivers and also the power source using a hybrid storage system. By identifying the consumption needs of the transceivers, an appropriate methodology for sizing and controlling the power flow for the power source is proposed. The paper emphasizes the fusion between information, communication, and energy consumption of the AWS in terms of spectrum information through a set of transceiver testing scenarios, identifying the main factors that influence the sensor node design and their inter-dependencies. Optimization of the system considers all these factors obtaining an energy efficient AWS, paving the way towards autonomous sensors by adding an energy harvesting element to them.

In the context of mental wellness support, trust and intimacy between a counselor and a patient are necessary to converge healing processes positively. However, convincing students to trust a virtual human for topics regarding mental wellness is a complex problem that requires understanding students' experiences. Based on research that discusses mental health as a concerning topic regarding Computer Science (CS) students, this paper investigates how undergraduate computing-related students perceive virtual humans' expertise on mental wellness support based on demographic resemblance on spoken accent and gender. Four virtual human counselors were developed to conduct the study, as 58 undergraduate computing-related students from two North American universities were recruited and assessed. Our findings suggest that students were less inclined to interact with a male virtual human than a female one. Also, that spoken accents can impact students' perceptions of expertise under students' multilingualism.