Instituto Superior Técnico
Recent publications
We describe Markov interval maps via branching systems and develop the theory of relative branching systems, characterizing when the associated representations of relative graph C*-algebras are faithful. When the Markov interval maps f have escape sets, we use our results to characterize injectivity of the associated relative graph algebra representations, improving on previous work by the first, third, and fourth authors.
In this work we study the global analytic integrability, Louville integrability and Puiseux integrability of the Tolman–Oppenheimer–Volkoff equation.
This paper studies the low cycle fatigue (LCF) behavior of glass fiber-reinforced polymer (GFRP) reinforced concrete (RC) beams by utilizing experimental and analytical investigation. Static and LCF three-point bending tests were carried out on 12 over-reinforced GFRP RC beams and six under-reinforced steel RC beams. The failure modes, fatigue lives, load-deflection, strain, and crack propagation were analyzed. The fatigue life of the steel RC beam with the same maximum stress level was lower than the GFRP RC beam, while the GFRP RC beam illuminated a larger failure mid-span deflection. For GFRP RC beams, the average fatigue lives with the maximum stress levels , , and , were 896, 8491, and 19949, respectively (max 0.85 u S P   0.70 u P 0.65 u P u P =the ultimate static flexural loading capacity). The average fatigue life of the highest stress level () was approximately 22 times the lowest stress level (). Bending shear failure, and 0.85 u P 0.65 u P concrete crush were the dominant fatigue failure mode for GFRP and steel RC beams. The 2 relationship between fatigue stress range and fatigue life was investigated based on fitting and reliability analysis. The stress intensity factor of the type I crack of the GFRP RC beam was deduced theoretically. The fatigue crack clarified a three-stage development trend (crack initiation, stable crack propagation, unstable crack propagation). When the crack continued to expand until it ran through the whole section, the beam was damaged. The fatigue crack propagation was fitted according to the experimental data. The deflection, dynamic stiffness, and damage evolution law of steel and GFRP RC beams were deducted. The fatigue life prediction models based on crack propagation and damage evolution were derived.
Monitoring structural behavior of earth structures during construction and in service is a common practice done for safety reasons, consolidation control and maintenance needs. Several are the techniques available for measuring displacements, water pressures and total stresses, not only in these geotechnical structures but also at their foundations. Materials testing has been used for calibrating models for structural design and behavior prediction, and these models can be validated with instrumentation data as well. Relatively recent investigation on the behavior of these materials considering their degree of saturation focuses on monitoring the evolution of water content or suction as function of soil-atmosphere interaction, necessary to predict cyclic and/or accumulated displacements, and has huge potential to predict the impact of climate changes on the performance of existing geotechnical structures. This new need justifies the investment on developing sensors able to be used for in situ monitoring of water in the soils, such as those presented here. Testing and monitoring becomes even more important nowadays when, for sustainability purposes, traditional construction materials are replaced by other geo-materials with unknown behavior and long-term performance (mainly accumulated displacements). Existing experimental protocols and monitoring equipment are used for such cases, however new techniques must be developed to deal with particular behaviors. Three case studies are presented and discussion is made on monitoring equipment used and how monitored data helped understanding the behaviors observed.KeywordsSuctionClimate changesNon-traditional geo-materialsMonitoringAccumulated displacementsChemical propertiesMineralogy
Medical image analysis models are not guaranteed to generalize beyond the image and task distributions used for training. This transfer-learning problem has been intensively investigated by the field, where several solutions have been proposed, such as pretraining using computer vision datasets, unsupervised pretraining using pseudo-labels produced by clustering techniques, self-supervised pretraining using contrastive learning with data augmentation, or pretraining based on image reconstruction. Despite fairly successful in practice, such transfer-learning approaches cannot offer the theoretical guarantees enabled by meta learning (ML) approaches which explicitly optimize an objective function that can improve the transferability of a learnt model to new image and task distributions. In this chapter, we present and discuss our recently proposed meta learning algorithms that can transfer learned models between different training and testing image and task distributions, where our main contribution lies in the way we design and sample classification and segmentation tasks to train medical image analysis models.
Rigorous and efficient management of the railway infrastructure is crucial to avoid accidents and reduce operation and maintenance costs. This requires in-depth knowledge of the assets, the interaction among them and the effect that each track parameter has on the overall infrastructure performance. In this study, a large set of studies are carried out, on a previously calibrated finite element slab track model, where the relevant track parameters are varied within their usual ranges. The results are then used to train and validate a series of predictive models based on Machine Learning algorithms. This methodology provides greater understanding and enhanced prediction of the behaviour of tracks, which are composed of multiple variables such as the soil/subgrade, supporting layers, sleepers, pads and rails. The study also considers train axle loads and service speeds, which are other key elements that influence the track performance. The results show that the parameters that have greatest influence on the railway infrastructure are the properties of the soil, characteristics of the rail pads and the axle loads. This work can support the implementation of predictive maintenance procedures for railway tracks and the development of innovative technological solutions, providing responses to the industrial needs of reducing costs and contributing to improve the competitiveness of railway transport.
The aggressiveness of melanoma and lack of effective therapies incite the discovery of novel strategies. Recently, a new dual acting hybrid molecule (HM), combining a triazene and a ʟ-tyrosine analogue, was synthesized. HM was designed to specifically be activated by tyrosinase, the enzyme involved in melanin biosynthesis and overexpressed in melanoma. HM displayed remarkable superior antiproliferative activity towards various cancer cell lines compared with temozolomide (TMZ), a triazene drug in clinical use, that acts through DNA alkylation. In B16-F10 cells, HM induced a cell cycle arrest at phase G0/G1 with a 2.8-fold decrease in cell proliferation index. Also, compared to control cells, HM led to a concentration-dependent reduction in tyrosinase activity and increase in caspase 3/7 activity. To maximize the therapeutic performance of HM in vivo, its incorporation in long blood circulating liposomes, containing poly(ethylene glycol) (PEG) at their surface, was performed for passively targeting tumour sites. HM liposomes (LIP HM) exhibited high stability in biological fluids. Preclinical studies demonstrated its safety for systemic administration and in a subcutaneous murine melanoma model, significantly reduced tumour progression. In a metastatic murine melanoma model, a superior antitumour effect was also observed for mice receiving LIP HM, with markedly reduction of lung metastases compared to positive control group (TMZ). Biodistribution studies using ¹¹¹In-labelled LIP HM demonstrated its ability for passively targeting tumour sites, thus correlating with the high therapeutic effect observed in the two experimental murine melanoma models. Overall, our proposed nanotherapeutic strategy was validated as an effective and safe alternative against melanoma.
This paper focuses on the seismic vulnerability assessment of old RC buildings prone to brittle shear effects, i.e., with extremely low transversal reinforcement ratios in columns. Within this context, two limitations are identified: 1) the inadequacy of the available analytical shear models in literature since most of them are based on experimental results performed on specimens with transversal reinforcement ratios higher than those found in old buildings and 2) the lack of simplified numerical modelling approaches to simulate shear failure prior to flexural yielding of the element’s longitudinal reinforcement. To overcome these limitations, a simple modelling approach is proposed, and its impact is evaluated through seismic and loss assessment of a RC structure typical of the Lisbon building stock. For comparison purposes, the building is modelled using two different numerical models: one that only captures the nonlinear flexural behaviour of the structural elements, and another that considers both flexural non-linear behaviour and brittle shear failure through the incorporation of uncoupled shear springs that limit the maximum strength that the RC columns can withstand. The seismic performance evaluation is carried out through nonlinear static and Incremental Dynamic Analysis (IDA). Collapse assessment is evaluated considering two different collapse criteria, namely global failure (GF) based on the identification of flattening of the IDA curves and first component failure (FCF) which is conducted based on post-processing analysis of shear forces and inter-storey drifts. The results show that the proposed modelling approach combined with the GF collapse criterion leads to estimates of expected annual losses (EAL) compatible with those reported in other studies found in the literature. Additionally, it is observed that the adoption of a first component failure criterion based on shear force control conducts to consistent estimates of EAL.
The Standard Penetration Test (SPT) is the most common in-situ tests for soil investigations. On the other hand, the Cone Penetration Test (CPT) is considered one of the best investigation tools. Many CPT-SPT correlation relationships have been proposed worldwide to estimate soil parameter from the other's available data. However, unfortunately, no available SPT-CPT correlations are established for the alluvial soil of Dhaka city. This paper aims at presenting correlations among the SPT-N value, cone tip resistance ( q c ), sleeve friction resistance ( f s ), soil behavior index ( I c ) and mean particle size ( D 50 ) for an alluvial soil deposit of Dhaka city. It is found that for the relationship between equivalent SPT N 60 -value and SPT N 60 -value the coarser soil layers As 1 and As 2 show the coefficient of correlation (R ² ) is 0.7106 and 0.534 respectively, which indicate a reliable relationship. In addition, the correlation between cone tip resistance ( q c ) and SPT N 60 -value shows very strong relationship which is very similar to proposed Meyerhof correlation. Furthermore, the relations between other mentioned parametres also shows a valid correlations similar to other authors.
Organoid cell culture methodologies are enabling the generation of cell models from healthy and diseased tissue. Patient-derived cancer organoids that recapitulate the genetic and histopathological diversity of patient tumours are being systematically generated, providing an opportunity to investigate new cancer biology and therapeutic approaches. The use of organoid cultures for many applications, including genetic and chemical perturbation screens, is limited due to the technical demands and cost associated with their handling and propagation. Here we report and benchmark a suspension culture technique for cancer organoids which allows for the expansion of models to tens of millions of cells with increased efficiency in comparison to standard organoid culturing protocols. Using whole-genome DNA and RNA sequencing analyses, as well as medium-throughput drug sensitivity testing and genome-wide CRISPR-Cas9 screening, we demonstrate that cancer organoids grown as a suspension culture are genetically and phenotypically similar to their counterparts grown in standard conditions. This culture technique simplifies organoid cell culture and extends the range of organoid applications, including for routine use in large-scale perturbation screens.
The Laser Interferometer Space Antenna (LISA) has the potential to reveal wonders about the fundamental theory of nature at play in the extreme gravity regime, where the gravitational interaction is both strong and dynamical. In this white paper, the Fundamental Physics Working Group of the LISA Consortium summarizes the current topics in fundamental physics where LISA observations of gravitational waves can be expected to provide key input. We provide the briefest of reviews to then delineate avenues for future research directions and to discuss connections between this working group, other working groups and the consortium work package teams. These connections must be developed for LISA to live up to its science potential in these areas.
Introduction Worldwide public transport systems are exposed to disruptions caused by malfunctions, accidents, maintenance, reduced fleet, and disasters, compromising mobility. Transport networks’ multimodal planning and management can be explored to increase their robustness against these events. In this context, this research paper proposes and empirically compares methods to assess the robustness of a multimodal transport network, looking at aspects regarding the single-mode and multimodal network topology. Materials and Methods We hypothesize that the appropriate multilayered and traffic sensitive modeling of a multimodal transport network can help characterize robustness and further unravel vulnerabilities related to the integration of different transport modes. Using metric-based targeting, we evaluate how the network decreases performance when simulating failures on stations and pathways using different scenarios. The following six extraction strategies for nodes and edges were used in the simulation: Random removal; Initial Degree removal; Initial Betweenness removal; Recalculate Degree removal; Recalculate Betweenness removal; and Multimodal Hubs removal. Lisbon’s public transport is used as a case study and is modeled as a multiplex network integrating eight different modes of transport. Proposing a novel normalized version of assessing the impact of failures, we were able to compare side by side the robustness of each modality layer, regardless of their size. Lastly, we simulate cascading events such as the breakdown of an entire transportation line. Conclusions Using different ways to induce failures in the network, we observe that to leave all nodes completely disconnected, we would need to remove about half the network nodes, highlighting the robustness of the Lisbon public transport network. Comparing different failure scenarios, methods that rely on recalculating network metrics yield a higher impact on the network robustness assessment. The impact of different events is quantified, showing that failures in stations are generally more dangerous than in pathways and offering views on the consequences of deactivating particular network modules. Overall, the results of this study allow decision-makers to gain further understanding of the topological vulnerabilities of a transportation network.
Several cities around the world rely on urban rail transit systems composed of interconnected lines, serving massive numbers of passengers on a daily basis. Accessing the location of passengers is essential to ensure the efficient and safe operation and planning of these systems. However, passenger route choices between origin and destination pairs are variable, depending on the subjective perception of travel and waiting times, required transfers, convenience factors, and on-site vehicle arrivals. This work proposes a robust methodology to estimate passenger route choices based only on automated fare collection data, i.e. without privacy-invasive sensors and monitoring devices. Unlike previous approaches, our method does not require precise train timetable information or prior route choice models, and is robust to unforeseen operational events like malfunctions and delays. Train arrival times are inferred from passenger volume spikes at the exit gates, and the likelihood of eligible routes per passenger estimated based on the alignment between vehicle location and the passenger timings of entrance and exit. Applying this approach to automated fare collection data in Lisbon, we find that while in most cases passengers preferred the route with the least transfers, there were a significant number of cases where the shorter distance was preferred. Our findings are valuable for decision support among rail operators in various aspects such as passenger traffic bottleneck resolution, train allocation and scheduling, and placement of services.
This paper is focused on the electrical and mechanical performance of aluminum-copper hybrid busbars subjected to corrosion over time. Two different types of hybrid busbars with joints produced by conventional fastening with M8 hexagonal socket head bolt-nut pairs made from medium carbon steel and by a new injection lap riveting process with semi-tubular rivets made from the material of the softer conductor are used and subjected to salt spray and electrochemical tests. Electrical resistance measurements performed on hybrid busbars taken from the corrosion testing cabinet at the end of each exposure period allow concluding that the new injection lap riveted hybrid busbars have a better electrical performance over time due to the elimination of fasteners with a higher electrical resistivity than aluminum and copper and to the elimination of the aluminum-steel and copper-steel galvanic pairs. The capability of the injection lap riveted hybrid busbars to withstand shear forces after corrosion testing also revealed to be adequate and like those of the original (uncorroded) hybrid busbars.
In this paper, we propose a methodology based on machine learning techniques to characterize the flexibility of electricity consumption in the residential sector. The main challenge is that the characterization of flexibility requires to know which and when appliances are being used and how available are users to change its utilization: However, this type of data is not generally available. In this work, we propose a full-stack methodology to solve this problem: we start by processing total electricity consumption data with feature engineering; then we use Non-Intrusive Load Monitoring (NILM) or Interactive Learning (IL) to identify the use of the appliances with higher flexibility (water heating, space heating and clothes drier); then we apply a Random Forest classifier to identify when the flexible appliances are being used; and finally we apply a K-means clustering algorithm to evaluate the flexibility of such appliance. We compare the results using accuracy, recall, and f-score indicators. The results show that the proposed approach can be used to characterize with high accuracy the use of flexible appliances just based on aggregated electricity consumption collected by smart meters with a low sampling rate. Further, we also demonstrate that Interactive Learning is a viable alternative approach to NILM to disaggregate electricity consumption.
This article reports an ultra-low-power (ULP) Bluetooth low-energy (BLE) receiver with an improved spurious-free dynamic range (SFDR). It features two passive-intensive RF techniques: an $N$ -path passive balun-LNA and a pipeline down-mixing baseband (BB)-extraction scheme. They together offer a high- $Q$ bandpass response at RF, and a high passive gain to suppress the noise of the BB hybrid complex filter. Specifically, the balun-LNA is a step-up triple-coil transformer aided by an $N$ -path switched-capacitor (SC) network to perform in-band voltage amplification, high- $Q$ bandpass filtering, $I$ / $Q$ down-mixing, and input-impedance matching. Instead of using active amplifiers as the first-BB gain stage, we passively extract the four-phase ( $I$ / $Q$ and differential) BB signals using a pipeline of passive-SC networks that can stack up the voltage gain. Prototyped in TSMC 28-nm CMOS, the BLE receiver consumes only 266 $\mu$ W, of which 75 $\mu$ W in the BB hybrid filter at 1 V, and 191 $\mu$ W in the LO divider $+$ buffer at 0.6 V. Measured at the maximum RF-to-BB gain of 61 dB, the receiver exhibits a noise figure (NF) of 6.1 dB and an out-of-band (OOB)-IIP $_{3}$ of 22.5 dBm. The corresponding SFDR is 77 dB for a 1-MHz BLE channel and a 10-dB minimum signal-to-noise ratio (SNR $_{\mathrm{min}})$ . The OOB-B $_{{-\text{1\,dB}}}$ is $-$ 3 dBm.
This paper presents an experimental and computational study on the behaviour of pre-tensioned thin solar sails. Firstly, a set of experimental tests of thin rectangular sheets made of Kapton® subjected to uniaxial tension were conducted to characterize the mechanical properties of the membrane. Then, tri-dimensional digital image correlation technique was used to capture the evolution of the wrinkling (shape and amplitude) in pre-tensioned specimens, a phenomenon that often affects the serviceability of solar sails. The influence of membrane thickness and specimen dimensions on the wrinkling behaviour were also studied. Next, nonlinear finite element models were used to simulate the membranes and to study the onset and growth of wrinkles in solar sails. First, by pre-tensioning the membrane with truss cables and using combinations of the eigenmodes extracted from buckling analysis as the membrane initial geometrical imperfections, nonlinear analyses were performed. The computational methodology was verified by comparing the experimental results of membrane specimens with those obtained from finite element analysis. Because the number of truss cables that pre-tension the solar sail plays a key role in their behaviour, two distinct configurations were considered: (i) five points connected sail and (ii) multiple points connected sail. Sensitivity studies were performed, including the influence of (i) membrane size and (ii) pre-tensioning magnitude on the solar sail wrinkling. Larger sails exhibit higher wrinkle dispersion and amplitude. Higher pre-tensioning induces more wrinkles, higher amplitudes and lower wavelengths. The solar sail configuration with multiple connected points connected presents less wrinkles with lower amplitude, and it is preferable to the configuration with five connected points. Finally, it was revealed that the wrinkling maximum amplitude varied approximately in a power law with the pre-tensioning level.
In this paper, we study the structural state and input observability of continuous-time switched linear time-invariant systems and unknown inputs. First, we provide necessary and sufficient conditions for their structural state and input observability that can be efficiently verified in O((m(n+p))2), where n is the number of state variables, p is the number of unknown inputs, and m is the number of modes. Moreover, we address the minimum sensor placement problem for these systems by adopting a feed-forward analysis and by providing an algorithm with a computational complexity of O((m(n+p)+α)2.373), where α is the number of target strongly connected components of the system’s digraph representation. Lastly, we apply our algorithm to a real-world example in power systems to illustrate our results.
Adhesive bonding is increasingly being considered by engineers for load-bearing joints to complement, or supplement, traditional mechanical fasteners for a large variety of structural materials, including fibre-reinforced polymers, timber, and steel. However, practitioners are still largely applying analysis and design methods, including codes and standards, that rely heavily on fudge factors. This is not due to the relative novelty of the joining technique, and the complexity of the associated mechanics. This paper guides the reader through some of the most important aspects of adhesively bonded joints, and the reasons why classical mechanics can only be applied in conjunction with fudge factors. Subsequently, the principles of fracture mechanics (FM) are presented; it is shown that, despite its conceptual strengths, FM is rather difficult to implement, as it introduces mechanical concepts practitioners are not familiar with. Then probabilistic methods (PM) are introduced; it is shown that PM can be considered as an extension of classical mechanics, as they can be easily implemented as a post-processing routine of the latter. Additionally, it is shown that PM, unlike FM, neither require specific test procedures for characterisation, nor complicated numerical analyses. Lastly, the paper offers a step-by-step guide for the implementation of PM for the dimensioning of adhesively bonded joints. The second part of this paper illustrates the latter analysis and design of adhesively bonded joints on a series of examples involving FRP, timber, and steel.
We present here an optimized protocol to obtain primary neuron-enriched cultures from embryonic chicken brains with no need for an animal facility. The protocol details the steps to isolate a neuron-enriched cell fraction from chicken embryos, followed by characterization of the chicken neurons with mass spectrometry proteomics and cell staining. Because of the high homology between chicken and human amyloid precursor protein processing machinery, these chicken neurons can be used as an alternative to rodent models for studying Alzheimer disease.
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Vasco D.B. Bonifácio
  • Department of Bioengineering
Ricardo Santos
  • Microbial Water Laboratory
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Lisbon, Portugal