A unique Valanginian paleoenvironment at an iron ore deposit near Zengővárkony (Mecsek Mts, South Hungary), and a possible genetic model

Abstract The spatially restricted Early Valanginian iron ore (limonite) and manganese deposit at Zengõvárkony (Mecsek Mts, southern Hungary) contains a rich, strongly limonitized, remarkably large-sized (specimens are 30–70% larger than those at their type localities) brachiopod-dominated (mainly Lacunosella and Nucleata) megafauna and a diverse crustacean microfauna, which indicates a shallow, nutrient-rich environment possibly linked to an uplifted block, and/or a hydrothermal vent

Crowdsensing for a sustainable comfort and for energy saving

Energy efficiency in buildings is a key issue in the current energy transition. In order to reduce building energy consumption, users’ behaviour and the perception of indoor environmental comfort must be taken into account; these aspects are inextricably linked to energy demand, consumption and related costs. In this paper, we present the methodological framework, technological solutions and outcomes of the Com- fortSense project. ComfortSense aimed at decoupling energy demand from indoor comfort. We focused on Heating, Ventilating and Air Conditioning (HVAC) systems in buildings, on users’ behaviour and on comfort perception by treating buildings as socio-technical systems. Our approach - which was multi- disciplinary and included the contribution of sociologists, physicists and computer scientists - was based on Internet of Things technologies, on a Living Lab design and testing process and on a Crowdsensing approach. Physical parameters (objective variables), such as temperature, CO 2 concentration and relative humidity, were measured by a Wireless Sensor Network and by wearable devices, while the users’ per- ception of comfort (subjective variables) were recorded as real-time feedback through a Mobile App in three pilot buildings of the University of Turin, engaging about a thousand buildings’ users (professors, researchers, students and employees). Objective and subjective variables were correlated through an ad- hoc Direct Virtual Sensor. Thanks to the Direct Virtual Sensor forecasting we demonstrated that, adopting an adaptive indoor comfort management, users’ comfort can be remarkably improved while reducing the energy consumption of HVAC systems