## 1 Introduction  
The literature reports several examples wherein calculation methodologies for assessing the energy performance of buildings are proposed, and solutions to improve their performance are posited, along with the introduction of advanced technologies and algorithms to reach this goal. Passive Houses, Zero-Energy Buildings (ZEBs), and Positive-Energy Buildings (PEBs) highlight these concepts with the primary objective of reducing energy consumption in the building sector. Additionally, the concept of building efficiency extends beyond energy consumption and includes considerations of embodied impacts and emissions, such as carbon footprint and comprehensive life cycle assessments. The literature also explores operational and life cycle costs (LCCs) and recognizes the significance of various co-benefits that are challenging to quantify, but are nevertheless important, such as well-being, an increased productivity, an enhanced building value, and an improved contextual value. User comfort is a very important topic and requires further insights to better evaluate how people live and experience the built environment. The Special Issue _New Trends in Efficient Buildings_ compiles the research achievements, ideas, and applications of advanced and efficient buildings, covering different technologies and application domains. In [1], the authors used existing standards and the scientific literature on life cycle assessment (LCA) to propose an operational definition for carbon-neutral buildings. Then, they applied this definition to an urban case study, comparing it to a nearly Zero-Energy Building (nZEB) scenario. The objective was to identify the significant practical constraints associated with implementing a methodologically rigorous calculation for carbon neutrality. The case study revealed that achieving carbon-neutral objectives for individual urban buildings is challenging due to the limited availability of spaces that can facilitate onsite carbon-offsetting actions. In [2], the authors investigated the application of Artificial Neural Networks (ANNs) in a heat transfer scenario, involving masonry wall assemblies subjected to elevated temperatures on one side, following the standard fire curve outlined in Eurocode EN1991-1-2. They compared their approach with the previously published methods of ANN development and protocols, assessing the accuracy and reliability of the developed algorithms. The study emphasized the importance of carefully selecting input data density and quality, as well as employing an appropriate algorithm architecture. The possibility of obtaining misleading metric results was acknowledged, and consequent measures to mitigate such risks were suggested. The paper concludes by proposing the further integration of ANNs in heat transfer research and applications. In [3], the authors put forward a management and control system to optimize electrical and energy heating consumption in student dormitories at a university campus. This system uses a Building Management System (BMS) and incorporates a degeneration plant that can be precisely controlled to generate electrical and heating energy based on the specific heating needs during the cold season. As a result, the implementation of this system successfully reduced energy consumption for heating by 13%, and electricity consumption by 32%. In [4], a model is proposed to evaluate the economic benefits generated by energy requalification interventions in relation to the Italian fiscal measure,known as the \"Superbonus\". The model focuses on the convenience for the various stakeholders involved. The analysis specifically considered 110 provincial capitals and their main urban areas, categorized as central, semi-central, and peripheral. For each urban area, the research determined the market value differential between the pre- and post-energy intervention situations. Additionally, by assuming an ordinary profit margin for potential investors, the research estimated the break-even incentive threshold for each urban area.