Universitat Politècnica de Catalunya

The microelectromechanical systems (MEMS) technology has been successful in yielding high-performance sensors for the measurement of pressure, vibration, inclination, and position. It is making progressive inroads in the gas sensing field for healthcare monitoring systems. This technology yields miniaturized sensors with reduced power consumption, faster response times, and lower unit costs in high volumes. This paper presents a brief introduction to exhaled breath acetone sensors based on MEMS and a study of a low-current front-end circuit for healthcare systems implementation for the detection of acetone vapor. The proposed capacitive sensor includes a high-sensitivity current-to-voltage converter, also known as a transimpedance circuit (TIA) is suggested. The advantage of t-network topology is that high gain and high sensitivity (1 V/1 nA) can be obtained by using kilo-range resistors, which are appropriate for on-chip circuitry. The obtained results offer a non-invasive alternative way the diagnosis of diabetic patients through exhaled breath analysis.

According to various international standards, many high-voltage devices must withstand short-circuit tests. Due to the enormous power and current requirements, they have to be tested in very specialized and expensive power laboratories, which are scarce and not affordable for the vast majority of electrical product manufacturers. It is proposed to break the time limit of about one second imposed by the standards by using a lower current to heat for a longer time, requiring more affordable equipment and thus reducing the cost for testing. This work analyzes the limits of the adiabatic assumption in short-circuit tests in order to quantify how the duration of these tests can be extended to reduce the power required and the current applied, while obtaining almost the same results, i.e., the same temperature at the end of the heating phase of the tests. For this purpose, bare cylindrical conductors are analyzed and the temperature dependence of the properties of the conductor material is considered. Experimental and simulation results presented in this paper suggest that by applying this approach, short-circuit tests intended for product design, verification and quality control can be performed in much less demanding and affordable laboratory facilities.

The presence of unbalanced loads in power systems creates voltage imbalances that perturb the operation of sensitive equipment like induction motors, power electronics converters, and adjustable speed drives. To address this issue, this paper presents a novel control scheme to perform remote negative-sequence voltage fair compensation at any node of a grid-forming inverter-based islanded AC microgrid. The fair compensation reduces the voltage imbalance of the remote node by adjusting the negative-sequence output voltage of the inverters according to a predefined objective. For example, the goal could be to equalize the inverters' negative-sequence output voltage. Alternatively, the aim could be to reduce this voltage at some inverters to perturb less the local loads at the expense of increasing it in other inverters. Therefore, the proposed controller achieves two control objectives: negative-sequence voltage reduction at a remote node and fair compensation through the inverters running this service. The controller also features inherent plug-and-play and parallel operation. Unlike state-of-the-art controllers on negative-sequence voltage compensation, the control scheme operation is accomplished by only broadcasting the remote node voltage measurement, thus significantly reducing the communication control data. The paper presents the large-signal control design and stability analysis, and the performance in a laboratory microgrid with selected experimental results.

The emergence of large language models (LLMs), such as ChatGPT, has garnered significant attention, particularly in academic and scientific circles. Researchers, scientists, and instructors hold varying perspectives on the advantages and disadvantages of using ChatGPT for research and teaching purposes. This commentary offers a brief explanation of the fundamental principles behind ChatGPT and how it can be applied in the fields of hydrology and other Earth sciences. The article examines the primary applications of this open artificial intelligence tool within these fields, specifically its ability to assist with writing and coding tasks, and highlights both the advantages and concerns associated with using such a model. Moreover, the study brings up some other limitations of the model, and the dangers of potential miss‐uses. Finally, we suggest that the academic community adapts its regulations and policies to harness the potential benefits of LLMs while mitigating its pitfalls. ChatGPT will be used by many scientists going forward for creating content and driving scientific progress. Drawing from our own experiences and the conclusions of this study, we suggest that the Hydrology and other Earth Science communities establish a structure for utilizing LLMs and presents clear regulations for their implementation. We also outline some specific steps on how to accomplish this structure. This article is protected by copyright. All rights reserved.

Historic buildings are the bearers of human civilization. Kunming, a famous historical and cultural city in China, has numerous historical and cultural heritages and a diverse and prosperous historical and cultural background. This study takes the renovation project of the historic district of Wenming Street in Kunming as the research object and proposes a holistic, multi-dimensional, and multi-factor planning and renovation method that should focus on the district in the conservation and renovation of historic buildings through the hierarchical analysis method. Through expert scoring and weighting analysis, questionnaires, and index scores, it is found that there is a lack of "spirit of place" and insufficient expression of non-material elements in the renovation of the historic district. This study aims to realize the integration of the historic environment with the needs of modern life using a monistic logic and to provide theoretical reference and practical guidance for the conservation, renovation, and sustainable development of historic buildings and the historic environment.

The exposure to smoking related products has been evaluated through urine illness risk marker determination through the analysis of urine samples of smokers and vapers. Biomarkers and their metabolites such as N -acetyl- S -(2-cyanoethyl)-L-cysteine (CEMA), N -acetyl- S -(3,4-dihydroxybutyl)-L-cysteine (DHBMA), N -acetyl- S -[1-(hydroxymethyl)-2-propen-1-yl)-L-cysteine (MHBMA), N -acetyl- S -(3-hydroxypropyl)-L-cysteine (3HPMA), 2 R - N -acetyl- S -(4-hydroxybutan-2-yl)-L-cysteine (HMPMA), and N -acetyl- S -(3-carboxy-2-propyl)-L-cysteine (CMEMA) together with nicotine and cotinine were identified and quantified by LC-HRMS and LC-MS/MS, and data found normalized to the creatinine level. One hundred two urine samples were collected from smokers, non-smokers, and vapers, spanning an age range from 16 to 79 years. Results obtained showed that CEMA was only detected in urine samples from smokers and MHBMA was in the same order of magnitude in all the urine samples analyzed. HMPMA was found in the urine of vapers at the same order of concentration as in non-smokers. 3HPMA in vapers was lower than in the urine of smokers, presenting an intermediate situation between smokers and non-smokers. On the other hand, DHBMA in vapers can reach similar values to those found for smokers, while CMEMA shows concentrations in the urine of vapers higher than in the case of non-smokers and traditional smokers, requiring new research to link this metabolite to the use of electronic cigarettes and possible alternative metabolomic routes. In general, this study seems to verify that traditional smoking practice constitutes a major source of carcinogenic chemicals compared with substitutive practices, although those practices are not free of potential harm. Graphical abstract

Molecular solar thermal (MOST) energy storage systems are getting increased attention related to renewable energy storage applications. Particularly, 2,3‐difunctionalized norbornadiene‐quadricyclane (NBD‐QC) switches bearing a nitrile (CN) group as one of the two substituents are investigated as promising MOST candidates thanks to their high energy storage densities and their red‐shifted absorbance. Moreover, such NBD systems can be prepared in large quantities (a requirement for MOST‐device applications) in flow through Diels‐Alder reaction between cyclopentadiene and appropriately functionalized propynenitriles. However, these acetylene precursors are traditionally prepared in batch from their corresponding acetophenones using reactive chemicals potentially leading to health and physical hazards, especially when working on a several‐grams scale. Here, we develop a multistep flow‐chemistry route to enhance the production of these crucial precursors. Furthermore, we assess the atom economy (AE) and the E‐factor showing improved green metrics compared to classical batch methods. Our results pave the way for a complete flow synthesis of NBDs with a positive impact on green chemistry aspects.

The implementation of Structural Health Monitoring (SHM) offers the prospect for sustainable and safe service‐life extension of existing bridges, a large portion of which is approaching the end of their nominal life. Many SHM frameworks for civil infrastructure address timely damage detection and identification. However, the scarcity of case studies on real damaged bridges hinders the generalized application of SHM in practice. In this contribution, monitoring data from a four‐day campaign on the Ponte‐Moesa bridge, a three‐span concrete box‐girder bridge, is presented as a benchmark for data‐driven damage diagnosis schemes. The monitoring data, covering accelerations from ambient and forced vibrations, contains the reference state after concluding the service life along with several gradually increasing damage states, including drilling holes and cutting reinforcement rebars and prestressed cables. The potential of damage‐sensitive features to identify damage is presented and the uncertainties, resulting from the environmental and operational conditions and sensor malfunctioning, pertaining to robust damage detection are discussed. Drawing from real bridge monitoring data, a range of prospects and open challenges of vibration‐based SHM for bridges are reviewed.

As cells migrate and experience forces from their surroundings, they constantly undergo mechanical deformations which reshape their plasma membrane (PM). To maintain homeostasis, cells need to detect and restore such changes, not only in terms of overall PM area and tension as previously described, but also in terms of local, nano-scale topography. Here we describe a novel phenomenon, by which cells sense and restore mechanically induced PM nano-scale deformations. We show that cell stretch and subsequent compression reshape the PM in a way that generates local membrane evaginations in the 100 nm scale. These evaginations are recognized by I-BAR proteins, which triggers a burst of actin polymerization mediated by Rac1 and Arp2/3. The actin polymerization burst subsequently re-flattens the evagination, completing the mechanochemical feedback loop. Our results demonstrate a new mechanosensing mechanism for PM shape homeostasis, with potential applicability in different physiological scenarios.

In the H2020 European project ASHVIN “Assistants for Healthy, Safe, and Productive Virtual Construction Design, Operation & Maintenance using a Digital Twin”, a set of Key Performance Indicators (KPIs) and Performance Indicators (PIs) to plan and control productive, resource efficient, and safe maintenance are being developed for transport infrastructure. This paper is presenting PIs and KPIs for the assessment and monitoring of the following aspects: Productivity, Resource Efficiency, Cost, Health & Safety during the operational life cycle stage, which is mainly focusing on the inspection and maintenance planning. Quantifiable and measurable PIs and KPIs are proposed and applied on two demonstration projects, highway bridge in Spain and airport runway in Croatia, as part of transportation infrastructure. Proposed PIs and KPIs are integrated into digital twins of the analyzed assets and into decision making tools for risk based maintenance planning. This paper presents the overview of the proposed digital PIs and KPIs applied on two demonstration projects and the integration into decision support tools for efficient and sustainable maintenance planning.

Shoreline position is a key parameter of a beach state, often used as a descriptor of the response of the system to changes in external forcing, such as sea‐level rise. Changes in shoreline position are the result of coupled hydrodynamic and morphodynamic processes happening in the nearshore and acting at different temporal scales. Due to this complexity, methodologies aimed at reproducing shoreline evolution at decadal time scale require many simplifications. Simpler methods usually consider an equilibrium beach profile whose shape depends only on beach morphology, and whose location varies depending on incoming forcing. Here, we derive a general equation for shoreline evolution using equilibrium beach profiles. We particularize it based on several common assumptions, and evaluate changes on shoreline position caused by sea‐level rise, combined with simultaneous wave and high‐frequency sea‐level forcing. We compare our model against other analytical equilibrium beach profile‐based models and with a dynamic model explicitly computing sediment transport. Results indicate that: (i) it is necessary to consider the area of the emerged beach subject to marine forcing rather than focusing only on the submerged part, (ii) the rates of shoreline recession may change for narrow beaches, defined as those for which marine forcings act onto all of their aerial surface, and (iii) Bruun’s Rule can describe beach shoreline evolution, but the uncertainty in selecting the landward boundary of the active profile entails a huge uncertainty in the magnitude of shoreline evolution. This problematic uncertainty can be drastically reduced if instantaneous forcing conditions are used instead of the arbitrary emerged/submerged active profile boundaries typically defined by only one statistic parameter of extreme conditions.

Spiking Neural Networks (SNNs) offer bioinspired computation based on local adaptation and plasticity as well as close biological compatibility. In this work, after reviewing the Hardware Emulator of Evolving Neural Systems (HEENS) architecture and its Computer-Aided Engineering (CAE) design flow, a spiking implementation of an adaptive physical sensor input scheme based on time-rate Band-Pass Filter (BPF) is proposed for real-time execution of large dynamic range sensory edge processing nodes. Simulation and experimental results of the SNN operating in real-time with an adaptive-range accelerometer input example are shown. This work opens the path to compute with SNNs multiple physical sensor information for perception applications.

In the geological disposal of high-level radioactive waste in argillaceous rocks, studying the barrier integrity after gas transport and the pathway closure thanks to self-sealing capacity is a crucial aspect for the safety assessment. This paper presents experimental research in Boom Clay (a potential host rock in Belgium) to evaluate the effectiveness of self-sealing and possible fissure reactivation during a second gas invasion event. Initial water permeability under oedometer conditions was first measured on samples at two bedding orientations, being higher the sample with bedding planes parallel to flow, highlighting marked anisotropy. Then, gas injection tests at a constant volume rate were performed. Results indicated that Boom Clay underwent expansion and degradation during gas injection due to the development of fissures that were quantified using microstructural techniques. The computed effective gas permeability was not significantly dependent on bedding orientation and was slightly larger than the initial intrinsic water permeability. The re-saturation of the samples led to a recovery of the initial water permeability for both orientations, replicating the original anisotropy. The microstructural analyses confirmed the gas pathways’ closure, indicating good self-sealing and the regaining of the hydraulic barrier function. However, a small volume of large unconnected pores was detected on undrained unloading before the microstructural study. An additional gas injection after the self-sealing resulted in a higher effective gas permeability and a larger increase in pore volume, suggesting the reopening of fissures generated during the first injection. Finally, the experimental data were compiled within a multi-scale phenomenological model to relate the microstructural information to macroscopic flow transport properties capturing the intrinsic permeability increase on gas invasion and its recovery during self-sealing.

The aim of this research is to analyze the influence of park design and location on their cooling effect during summer daytime in Barcelona. Spatial analytical methods, utilizing the land surface temperature data from the Landsat 8 satellite, were employed to assess the intensity and spatial extent of the Park Cool Island (PCI) in 86 parks over four consecutive years. The study investigated the influence of factors such as the proportion of green land cover, park shape, and surrounding characteristics on these PCI indicators using bivariate correlation and multiple linear regression analysis. Results revealed that 84 parks exhibited a positive cooling effect on their urban surroundings during the studied years, whereas the remaining parks showed no PCI. The statistical analysis indicated that these results are associated with the microclimatic uncertainty caused by the diverse relationships between the proportion of natural vegetated or pervious surfaces and the built spaces within the parks, proposed by the administration aiming to accommodate civic, cultural, and recreational usage. In conclusion, we discuss the parameters for modeling the interaction between park design and their urban surroundings in the context of climatic considerations. This information is crucial for leveraging urban parks as spaces that can mitigate the urban heat island effect while preserving their social value as community public spaces.