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Over the last few decades, energy efficiency has received increasing attention from the Architecture, Engineering, Construction and Operation (AECO) industry. Digital Twins have the potential to advance the Operation and Maintenance (O&M) phase in different application fields. With the increasing industry interest, there is a need to review the current status of research developments in Digital Twins for building energy efficiency. This paper aims to provide a comprehensive review of the applications of digital twins for building energy efficiency, analyze research trends and identify research gaps and potential future research directions. In this review, Sustainability and Energy and Buildings are among the most frequently cited sources of publications. Literature reviewed was classified into four different topics: topic 1. Optimization design; topic 2. Occupants’ comfort; topic 3. Building operation and maintenance; and topic 4. Energy consumption simulation.

Post-occupancy evaluations are common tools used to periodically assess Indoor Environmental Quality (IEQ) in tertiary buildings. Although the large amount of data collected from surveys contain valuable information, the influence of building characteristics on IEQ considering the different uses of the rooms and different types of occupants is rarely considered in the evaluation. This study presents an analysis of the association between building characteristics and IEQ in different building rooms (classrooms and offices) and different occupants (students and lecturers) using a post occupancy evaluation survey to 1013 occupants in 26 higher educational buildings in Spain under a Mediterranean climate. This research demonstrated that building characteristics influence IEQ perceptions of the different rooms in tertiary education buildings. The possibility of controlling the lighting, shadows or heating, ventilation air or conditioning (HVAC) systems are the most influential factors when analyzing IEQ. The findings of this research are of interest to facility managers aiming at implementing energy efficiency measures based on user-centric satisfaction or developing maintenance plans focused on IEQ enhancement.

Efficient healthcare facility design is crucial for providing high-quality healthcare services. This study introduces an innovative approach that integrates artificial intelligence (AI) algorithms, specifically particle swarm optimization (PSO), with building information modeling (BIM) and digital twin technologies to enhance facility layout optimization. The methodology seamlessly integrates AI-driven layout optimization with the robust visualization, analysis, and real-time capabilities of BIM and digital twins. Through the convergence of AI algorithms, BIM, and digital twins, this framework empowers stakeholders to establish a virtual environment for the streamlined exploration and evaluation of diverse design options, significantly reducing the time and manual effort required for layout design. The PSO algorithm generates optimized 2D layouts, which are seamlessly transformed into 3D BIM models through visual programming in Dynamo. This transition enables stakeholders to visualize, analyze, and monitor designs comprehensively, facilitating well-informed decision-making and collaborative discussions. The study presents a comprehensive methodology that underscores the potential of AI, BIM, and digital twin integration, offering a path toward more efficient and effective facility design.

ICT-based solutions are seen to be almost totally environmentally friendly, but game-based solutions for energy saving have not been explored yet. This paper describes a comprehensive analysis and an in-depth interpretation of the life cycle environmental impact of a game-based solution for domestic energy saving, developed and validated within the EU-funded Horizon 2020 project EnerGAware—Energy Game for Awareness of energy efficiency in social housing communities. Life cycle impacts were calculated with SimaPRO 8.5.2.0 using the ReCiPe 2016 v1.02 midpoint and endpoint methods and information contained within the Ecoinvent v3.4 database. Although the pre-competitive solution, directly arising from the research project, was found to have a relatively high environmental impact, its future exploitation, which mostly relies on existing infrastructure, was found to be highly competitive from an environmental perspective. The game will help reduce the life cycle impact of domestic energy consumption on damage to human health (3.68%), ecosystem quality (3.87%), and resource availability (4.81%). Most of the environmental impact of the market solution was found in the manufacturing phase (77.96–80.12%). Transport (8.86–7.57%), use (3.86–5.82%), and maintenance (7.24–7.54%) phases were found to contribute little to environmental impact. This research provides a useful reference for decision-making as it contributes to the environmental benchmarking of competing energy-saving strategies.

This paper analyzes the impact of an innovative approach based on gamification to promote reduced energy consumption in social housing. The game was developed and validated under the auspices of the EU-funded project EnerGAware-Energy Game for Awareness of energy efficiency in social housing communities in an affordable housing pilot located in Plymouth (United Kingdom). The results showed that the future exploitation of the game holds important energy- and emissions-saving potential. Assuming that the game is distributed freely by European energy providers to their domestic end-users, the game was found to be able to save more than 48.9 secondary terawatt-hours per year (TWhs) and 18.8 million tons of CO2e annually, contributing up to around 8% to the target set for the European buildings sector to keep global warming under 2 °C. The results also showed that the game is highly feasible from the energy point of view, even when we consider the energy consumed upstream, due to its low cumulative energy demand and its potential for household energy reduction. The results of this research provide helpful information for private and public stakeholders, as they contribute to determining the sustainability of promoting energy saving through gaming.

Buildings play a central role in the clean energy transition, which is why it is vital to understand how energy is consumed in this sector. Energy performance certificate databases are considered a key source of information on the characteristics of built building stock. Despite a growing portfolio of studies based on information from such databases, little is known about energy consumption in offices. This paper explores the modelled energy performance of existing offices in Spain, using data from 13,701 energy performance certificates collected by the Catalan Institute of Energy (ICAEN) in 2013–2018. Offices were found to consume between 202.66 and 212.10 kWhp/m2·year and were mostly ranked in classes C and D (~64%). Offices with E, F or G labels represent ~28% of the sample while A and B energy ratings are very scarce (~8%). Key drivers of energy consumption variation were found to be the office type, construction period, climate zone, renewable energy use, energy certification procedure and motivation for obtaining an energy performance certificate. Ownership was not found to affect average calculated energy consumption. The results will help policy makers to plan future energy conservation strategies.

Introduction: Haematopoietic stem cell transplantation (HSCT) recipients and their caregivers may experience psychological distress. This study aimed to evaluate anxiety and depression in patients and caregivers throughout the HSCT process. As a secondary objective, we explored the association between anxiety and depression in patient and caregiver over the same period and compared anxiety and depression according to sociodemographic factors and whether HSCT was homebound or hospitalised.Methodology: Longitudinal descriptive study. Seventy-two HSCT patients and their caregivers were consecutively included at a Spanish hospital between October 2019 and February 2021. The HADS instrument was used to assess anxiety and depression at six time-points, including pre-HSCT, the acute period and one-year follow-up. An adjusted linear mixed model assessed variable changes over time-points and a correlational analysis evaluated the relationship between anxiety and depression. To detect differences between groups over time, a linear mixed model was adjusted.Results: Participants' anxiety levels were high at all time-points and consistently higher among caregivers than patients. Patients and caregivers' depression levels were low pre-HSCT and increased significantly during hospitalisation. Patients' depression decreased during follow-up but remained stable among caregivers. We observed moderate positive correlations between patient and caregiver anxiety or depression at all time-points except pre-HSCT. Caring for other dependents increased depression in patients and being female increased both anxiety and depression in caregivers. Residing in social housing increased patient anxiety and depression and caregiver depression.Conclusions: Diverging trajectories for patient and caregiver anxiety and depression were observed. Caregivers showed higher levels of anxiety than patients throughout the HSCT process and higher levels of depression from 3 months after HSCT. Admission was a critical time that increased depression in both. This study supports the need for new intervention approaches in prevention, early detection and treatment of anxiety and depression in patients receiving HSCT and their caregivers.

Purpose The purpose of this paper is to address the problems of the current facilities maintenance management (FMM) system in finding necessary information, identifying defective facilities and prioritizing maintenance work orders. Design/methodology/approach In this paper, in conjunction with building information modeling, a system is proposed to perform a preliminary inspection of each maintenance request, provide FMM staff with the location of the faulty facility and its associated details and provide recommendations for prioritizing repair work orders. Unity and Revit are used to implement the proposed system and a case study is conducted to demonstrate its effectiveness. Findings An augmented reality (AR)-FMM system was developed using the AR technique in this paper. This system provides the related information even if the FMM receives a problem report without facility information from the occupant and performs a preliminary inspection so that the faulty facility and the route to it are identified. In addition, a work order sequence of pending requests was provided. The visualization of the facility using AR technology has brought great convenience and ease to FMM staff. Originality/value This paper addresses the problems encountered in the current facility maintenance management system concerning AR technology.

Patients with a history of tuberculosis (TB) have a high probability of recurrence because long-term cure is not always maintained in successfully treated patients. The aim of this study was to identify the probability of TB recurrence and its predictive factors in a cohort of socially vulnerable patients who completed treatment in the TB referral center in Catalonia, which acts as the center for patients with social and health problems. This retrospective open cohort study included all patients diagnosed with TB who were admitted and successfully treated in Serveis Clínics between 2000 and 2016 and who remained disease-free for a minimum of 1 year after treatment completion. We calculated the incidence density of TB recurrences per person-years of follow-up. We also estimated the cumulative incidence of TB recurrence at 1, 2, 5, and 10 years of follow-up. Bivariate analysis was conducted using Kaplan-Meier curves. Multivariate analysis was conducted using Cox regression. Hazard ratios (HR) were calculated with their 95% confidence intervals (95%CI). There were 839 patients and 24 recurrences (2.9%), representing 0.49 per 100 person-years. The probability of a recurrence was 0.63% at 1 year of follow-up, 1.35% at 2 years, and 3.69% at 5 years. The multivariate analysis showed that the predictive factors of recurrence were age older than 34 years (aHR = 3.90; CI = 1.06-14.34 at age 35-45 years and aHR = 3.88; CI = 1.02-14.80 at age >45 years) and resistance to at least one anti-TB drug (aHR = 2.91; CI = 1.11-7.65). Attention should be paid to socially vulnerable persons older than 34 years with a previous episode of resistant TB. Surveillance resources should be directed toward adequately treated patients who nevertheless have a high risk of recurrence.

Population ageing, extreme weather, and high energy costs are the current and future global scenarios. The present study analyses the factors affecting the thermal comfort of older adults and evaluates their thermal perceptions and preferences in nursing homes in a Continental Mediterranean climate during winter, through environmental measurements and surveys on site. The sample consists of 1065 occupants. Results of this study revealed that the neutral temperature of older adults in nursing homes in cold winter climates is 24.9°C, 2.3°C higher than what PMV predicts. Results also highlight that older adults feel more comfortable in those spaces with higher CO2 concentrations than recommended by regulation. The analysis of factors affecting thermal comfort revealed that the most relevant factors affecting the thermal comfort of older adults in cold winter climates are (i) the type of room, which indirectly implies the metabolic rate of the occupants, the type of ventilation, and the CO2 level; (ii) the occupancy density; and (iii) the relative humidity of the room. These results will help to develop more accurate thermal comfort and indoor environmental quality regulations for older people that improve their health and quality of life. The modification of temperature setpoints in nursing homes based on the results of this study could influence energy use and should be carefully considered by policy makers and facility managers.