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In the field of urban building energy models (UBEM), the significant mismatch between simulation results and energy metered data is one of the most important barriers when using them as a planning tool. Their implementation requires a great amount of detailed building-related data, which is not always available. These data could be collected or measured for a small group of existing buildings, however such detailed data collection effort becomes impractical for large urban areas. Therefore, UBEM require certain simplifications and assumptions which can distance the input data from reality, leading to a performance gap. In this sense, knowing the influence of all the input parameters on UBEM simulation results would allow to focus the data collection efforts on the inputs with the greatest sensitivity. In this context, the aim of this research is to quantify the influence of the window-to-wall ratio (WWR) input parameter in an UBEM implemented on the residential building stock in Escaldes-Engordany (Andorra). After gathering the WWR data from a significant sample of the building stock, heating simulations of the entire building stock were carried out using the extreme WWR values, minimum and maximum, in order to analyse the variation of the results. The results obtained show an average difference of 12% between the two heating consumption simulation results. Furthermore, it can also be seen that the differences are more significant for the single-family building typology, as well as for more recently constructed buildings., Peer Reviewed, Postprint (author's final draft)

(English) The building sector has nowadays become a key point for policies and strategies to reduce energy and greenhouse gas emissions. The significant and unprecedented urban expansion that occurred in recent years and that is still ongoing today, combined with the high energy consumption that characterises the construction sector and the longevity of buildings built before the appearance of energy regulations, are some of the reasons that have put the building sector in the spotlight in order to achieve the ambitious goal of carbon neutrality by 2050. To significantly reduce energy consumption and emissions, in both existing and new buildings, and thus achieve climate goals, municipalities need a better understanding not only of the current energy performance of buildings, but also the future impact that could have energy retrofit programs and changes in the energy supply infrastructure. In this sense, bottom-up urban building energy models, known as UBEM, are considered as one of the most promising tools in the field of urban simulation, as they are able to incorporate different data sets related to the building stock as well as the external factors affecting it. Unfortunately, the discrepancies between UBEM results and real energy consumption data are an obstacle to their widespread use in political decision-making. Reducing these discrepancies is one of the main challenges in this area of research. While most of the research carried out for this purpose points to the calibration of UBEM as the solution to this discrepancy, few studies address the issue of the building stock fragmentation, necessary to implement energy models at the urban scale. With the aim of reducing the mismatches between the UBEM and buildings’ metered energy consumption, the backbone of this thesis consists in the definition of a new methodology for building stocks fragmentation in order to obtain representative archetypes of the heterogeneity and energy diversity of the buildings using d, (Català) El sector de l’edificació s’ha convertit a hores d’ara en un punt clau per a les polítiques i estratègies de reducció d’energia i emissions de gasos d’efecte hivernacle. L’important expansió urbana sense precedents soferta durant els darrers anys encara persistent a dia d’avui, així com l’elevat consum energètic del sector de l’edificació i la longevitat dels edificis construïts abans de l’aparició dels reglaments energètics són algunes de les raons que han posat al sector de l’edificació en el punt de mira per atènyer l’ambiciós objectiu de neutralitat carboni per l’any 2050. Per reduir notablement el consum d’energia i les emissions, tant en edificis existents com de nova construcció, i assolir així els objectius climàtics, les ciutats necessiten d’una millor comprensió, no només del comportament energètic actual dels edificis sinó també de quins efectes futurs podrien tenir els programes integrals de reconversió energètica i els canvis en la infraestructura de subministrament d’energia. En aquest sentit, els models energètics d’edificis a escala urbana de tipus bottom-up, coneguts com a UBEM, estan considerats com una de les eines més prometedores en l’àmbit de la simulació urbana capaç d’incorporar diferents conjunts de dades sobre el parc edificat així com els factors externs que l’afecten. Malauradament, els desajustos entre els resultats d’aquests i les dades reals de consum energètic representen una barrera per a la seva utilització generalitzada en la presa de decisions polítiques. La reducció d’aquests desajustos és un dels principals reptes d’aquest camp d’estudi. Mentre la majoria de recerca realitzada amb aquest propòsit assenyala al calibratge dels UBEM com la solució a aquest desajust, pocs estudis aborden la qüestió de la fragmentació del parc edificat necessària per poder implementar models energètics a escala urbana. Amb l’objectiu de reduir els desajustos entre els UBEM i la realitat energètica del parc edificat, l’eix central d’aquesta t, Postprint (published version)

Purpose: This study explores the differences between digital immigrants (DIs) and digital natives (DNs) in the continuance of routine and innovative information system use. Design/methodology/approach: A quantitative survey was conducted with two different samples comprising 100 DIs and 152 DNs in mandatory information system use contexts. Data were analyzed with structural equation modeling to examine the hypothesized relationships in the research model. Findings: Results revealed differences among digital nativity groups. The effect of confirmation of expectations about system use on satisfaction is stronger for DNs whereas the effect on task–technology fit (TTF) is similar in both digital groups. Interestingly, significant differences between digital nativity groups occur in routine use. For DIs, TTF and habit are significant while for DNs, satisfaction significantly affects routine use. The results show no difference between digital native groups regarding innovative use. Originality/value: This study extends the concept of digital nativity to routine and innovative system use, contributing to an enhanced understanding about the differences in information systems continuance (ISC) based on digital nativity. It also provides a fine-grained discussion of how to classify digital nativity and its impact in working contexts and extends the IS continuance model by considering two types of IS usage.

© 2021, The Author(s). Target delivery of large foreign materials to cells requires transient permeabilization of the cell membrane without toxicity. Giant unilamellar vesicles (GUVs) mimic the phospholipid bilayer of the cell membrane and are also useful drug delivery vehicles. Controlled increase of the permeability of GUVs is a delicate balance between sufficient perturbation for the delivery of the GUV contents and damage to the vesicles. Here we show that photoacoustic waves can promote the release of FITC-dextran or GFP from GUVs without damage. Real-time interferometric imaging offers the first movies of photoacoustic wave propagation and interaction with GUVs. The photoacoustic waves are seen as mostly compressive half-cycle pulses with peak pressures of ~ 1 MPa and spatial extent FWHM ~ 36 µm. At a repetition rate of 10 Hz, they enable the release of 25% of the FITC-dextran content of GUVs in 15 min. Such photoacoustic waves may enable non-invasive targeted release of GUVs and cell transfection over large volumes of tissues in just a few minutes.

Building archetypes development has been the focus of numerous research works over the past decades and are considered one of the biggest challenges, as well as one of the main sources of inaccuracies in Urban Buildings Energy Models (UBEM). The development of machine learning and data mining techniques, such as clustering, as well as the access to building data at disaggregated scales, has opened new horizons in this field. With the aim to reduce additional simulation errors derived from the fragmentation process of the archetype approach in UBEMs, this paper presents an alternative hybrid approach to identify representative building archetypes combining the classic deterministic and a data-driven clustering approach using building data at both building and cadastral unit scales. The methodology was tested in the Escaldes-Engordany building stock, a city of the Principality of Andorra, and the resulting archetypes have been compared with the archetypes obtained by the application of both approaches applied separately. A total of 71 archetypes were identified in the Escaldes-Engordany building stock. The results show that both approaches complement each other and allow to overcome the identified barriers when applied separately. In addition, the results also reveal that there is an important heterogeneity of certain building aspects not only between buildings, but also within buildings, which cannot be detected if the fragmentation is still carried out at the building scale., Peer Reviewed, Objectius de Desenvolupament Sostenible::11 - Ciutats i Comunitats Sostenibles, Objectius de Desenvolupament Sostenible::7 - Energia Assequible i No Contaminant, Postprint (author's final draft)