IT/IST/IPLeiria Response to the Call for Evidence on JPEG Pleno Point Cloud Coding

This document proposes two scalable point cloud (PC) geometry codecs, submitted to the JPEG Call for Evidence on Point Cloud Coding (PCC).N/

A Study of Generalization and Fitness Landscapes for Neuroevolution

Rodrigues, N. M., Silva, S., & Vanneschi, L. (2020). A Study of Generalization and Fitness Landscapes for Neuroevolution. IEEE Access, 8, 108216-108234. [9113453]. https://doi.org/10.1109/ACCESS.2020.3001505Fitness landscapes are a useful concept for studying the dynamics of meta-heuristics. In the last two decades, they have been successfully used for estimating the optimization capabilities of different flavors of evolutionary algorithms, including genetic algorithms and genetic programming. However, so far they have not been used for studying the performance of machine learning algorithms on unseen data, and they have not been applied to studying neuroevolution landscapes. This paper fills these gaps by applying fitness landscapes to neuroevolution, and using this concept to infer useful information about the learning and generalization ability of the machine learning method. For this task, we use a grammar-based approach to generate convolutional neural networks, and we study the dynamics of three different mutations used to evolve them. To characterize fitness landscapes, we study autocorrelation, entropic measure of ruggedness, and fitness clouds. Also, we propose the use of two additional evaluation measures: density clouds and overfitting measure. The results show that these measures are appropriate for estimating both the learning and the generalization ability of the considered neuroevolution configurations.publishersversionpublishe

A Study of Fitness Landscapes for Neuroevolution

Rodrigues, N. M., Silva, S., & Vanneschi, L. (2020). A Study of Fitness Landscapes for Neuroevolution. In 2020 IEEE Congress on Evolutionary Computation, CEC 2020: Conference Proceedings [9185783] (2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC48606.2020.9185783Fitness landscapes are a useful concept to study the dynamics of meta-heuristics. In the last two decades, they have been applied with success to estimate the optimization power of several types of evolutionary algorithms, including genetic algorithms and genetic programming. However, so far they have never been used to study the performance of machine learning algorithms on unseen data, and they have never been applied to neuroevolution. This paper aims at filling both these gaps, applying for the first time fitness landscapes to neuroevolution and using them to infer useful information about the predictive ability of the method. More specifically, we use a grammar-based approach to generate convolutional neural networks, and we study the dynamics of three different mutations to evolve them. To characterize fitness landscapes, we study autocorrelation and entropic measure of ruggedness. The results show that these measures are appropriate for estimating both the optimization power and the generalization ability of the considered neuroevolution configurations.preprintpublishe

An electronic nose as a non-destructive analytical tool to identify the geographical origin of portuguese olive oils from two adjacent regions

The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils’ geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 < R2 < 0.998 and 0.40 < RMSE < 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES (PIDDAC) to CIMO (UIDB/00690/2020 and UIDP/00690/2020), to CEB (UIDB/04469/2020) and to the Associate Laboratory SusTEC (LA/P/0007/2020). The authors are also grateful to the “Project OLIVECOA—Centenarian olive trees of Côa Valley region: rediscovering the past to valorize the future” (ref. COA/BRB/0035/2019), financed by FCT (Portugal). Nuno Rodrigues thanks the National funding by FCT- Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract.info:eu-repo/semantics/publishedVersio

Lactobacillus crispatus represses vaginolysin expression by BV associated Gardnerella vaginalis and reduces cell cytotoxicity

Using a chemically-defined medium simulating genital tract secretions, we have shown that pre-adhering Lactobacillus crispatus to Hela epithelial cells reduced cytotoxicity caused by Gardnerella vaginalis. This effect was associated to the expression of vaginolysin and was specific to L. crispatus interference, as other vaginal facultative anaerobes had no protective effect.This work was supported by Portuguese National Funds (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). JC, and MER acknowledge the financial support of individual Grants SFRH/BD/93963/2013, and SFRH/BPD/95401/2013 respectively. NC is an Investigador FCT.info:eu-repo/semantics/publishedVersio

An electronic nose as a non-destructive analytical tool to identify the geographical origin of Portuguese olive oils from two adjacent regions

The geographical traceability of extra virgin olive oils (EVOO) is of paramount importance for oil chain actors and consumers. Oils produced in two adjacent Portuguese regions, Côa (36 oils) and Douro (31 oils), were evaluated and fulfilled the European legal thresholds for EVOO categorization. Compared to the Douro region, oils from Côa had higher total phenol contents (505 versus 279 mg GAE/kg) and greater oxidative stabilities (17.5 versus 10.6 h). The majority of Côa oils were fruity-green, bitter, and pungent oils. Conversely, Douro oils exhibited a more intense fruity-ripe and sweet sensation. Accordingly, different volatiles were detected, belonging to eight chemical families, from which aldehydes were the most abundant. Additionally, all oils were evaluated using a lab-made electronic nose, with metal oxide semiconductor sensors. The electrical fingerprints, together with principal component analysis, enabled the unsupervised recognition of the oils’ geographical origin, and their successful supervised linear discrimination (sensitivity of 98.5% and specificity of 98.4%; internal validation). The E-nose also quantified the contents of the two main volatile chemical classes (alcohols and aldehydes) and of the total volatiles content, for the studied olive oils split by geographical origin, using multivariate linear regression models (0.981 ≤ R2 ≤ 0.998 and 0.40 ≤ RMSE ≤ 2.79 mg/kg oil; internal validation). The E-nose-MOS was shown to be a fast, green, non-invasive and cost-effective tool for authenticating the geographical origin of the studied olive oils and to estimate the contents of the most abundant chemical classes of volatiles.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES (PIDDAC) to CIMO (UIDB/00690/2020 and UIDP/00690/2020), to CEB (UIDB/04469/2020) and to the Associate Laboratory SusTEC (LA/P/0007/2020). The authors are also grateful to the “Project OLIVECOA—Centenarian olive trees of Côa Valley region: rediscovering the past to valorize the future” (ref. COA/BRB/0035/2019), financed by FCT (Portugal). Nuno Rodrigues thanks the National funding by FCT- Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract.info:eu-repo/semantics/publishedVersio

A Comparative Study of Automated Deep Learning Segmentation Models for Prostate MRI

Rodrigues, N. M., Silva, S., Vanneschi, L., & Papanikolaou, N. (2023). A Comparative Study of Automated Deep Learning Segmentation Models for Prostate MRI. Cancers, 15(5), 1-21. [1467]. https://doi.org/10.3390/cancers15051467 --- Funding: The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 952159 (ProCAncer-I). This work was partially supported by FCT, Portugal, through funding of the LASIGE Research Unit (UIDB/00408/2020 and UIDP/00408/2020), and under the project UIDB/04152/2020 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS. Nuno Rodrigues was supported by PhD Grant 2021/05322/BD.Prostate cancer is one of the most common forms of cancer globally, affecting roughly one in every eight men according to the American Cancer Society. Although the survival rate for prostate cancer is significantly high given the very high incidence rate, there is an urgent need to improve and develop new clinical aid systems to help detect and treat prostate cancer in a timely manner. In this retrospective study, our contributions are twofold: First, we perform a comparative unified study of different commonly used segmentation models for prostate gland and zone (peripheral and transition) segmentation. Second, we present and evaluate an additional research question regarding the effectiveness of using an object detector as a pre-processing step to aid in the segmentation process. We perform a thorough evaluation of the deep learning models on two public datasets, where one is used for cross-validation and the other as an external test set. Overall, the results reveal that the choice of model is relatively inconsequential, as the majority produce non-significantly different scores, apart from nnU-Net which consistently outperforms others, and that the models trained on data cropped by the object detector often generalize better, despite performing worse during cross-validation.publishersversionpublishe

Olive oil sensory analysis as a tool to preserve and valorize the heritage of centenarian olive trees

In inland areas of Portugal and some regions of the Mediterranean basin, olive production is based on traditional olive groves, with low intensification, local cultivars, aged plants, and centenarian trees. These plants play a key role in the ecosystem, contributing to carbon sequestration and possessing a high genetic diversity, particularly important for selecting cultivars more resistant to climatic changes. Appreciation of the value of this genetic diversity implies genetic, morphological, and physicochemical characterization of centenarian trees, which is expensive and time-consuming. Sensory evaluation is also of utmost importance. Thus, in this study, centenarian olive trees were selected in the Côa Valley region, a UNESCO World Heritage site. The descriptive sensory profile of their extracted olive oils was established and used to cluster the oils, using hierarchical clustering analysis, and consequently the olive trees, into five groups with similar intensities of perceived olfactory–gustatory attributes. Each cluster revealed olive oils with unique sensory patterns, presumably due to similarities of the olive trees, confirming the potential of the proposed screening approach. The identification of sensorially homogeneous oil-tree groups would reduce the number of specimens needed for subsequent morphological, genetic, and chemical characterization, allowing a cost-effective and robust future evaluation procedure.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support from national funds FCT/MCTES to CIMO (UIDB/00690/2020) and SusTEC (LA/P/0007/2020). This work was also supported by the FCT project OLIVECOA-Centenarian olive trees of Coa Valley region: rediscovering the past to valorize the future, ref. COA/BRB/0035/2019. Nuno Rodrigues was funded by FCT-Foundation for Science and Technology, P.I., through the institutional scientific employment program-contract.info:eu-repo/semantics/publishedVersio

Animal model for chronic massive rotator cuff tear: behavioural and histologic analysis

Purpose Massive rotator cuff tears (MRCT) are usually chronic lesions that present associated degenerative changes of the myotendinous unit that have been implicated in limitations for surgical repair. In order to develop effective therapies, it is important to establish animal models that mimic the hallmarks of the injury itself. Therefore, in the present work, we aimed to (1) optimize a rodent animal model of MRCT that closely reproduces the fatty infiltration of the cuff muscles seen in humans and (2) describe the effects of unilateral or bilateral lesion in terms of histology and behaviour. Methods Massive tear was defined as two rotator cuff tendons—supraspinatus and infraspinatus—section. Twenty-one Wistar rats were randomly assigned to four groups: bilateral lesion (five animals), right-sided unilateral lesion (five animals), left-sided unilateral lesion (five animals) and control (six animals). Behaviour was analyzed with open field and staircase test, 16 weeks after lesion. After that, animals were killed, and the supraspinatus and infraspinatus muscles were processed. Results Histologic analysis revealed adipocytes, fatty infiltration and atrophy in the injured side with a greater consistency of these degenerative changes in the bilateral lesion group. Behaviour analysis revealed a significant functional impairment of the fine motor control of the forepaw analyzed in staircase test where the number of eaten pellets was significantly higher in sham animals (sham = 7 ± 5.0; left unilateral = 2.6 ± 3.0; right unilateral = 0 ± 0; and bilateral = 0 ± 0, p left unilateral = 2 ± 2.1 > right unilateral = 0.8 ± 1.3 > bilateral = 0.8 ± 1.1). Conclusions The present study has been able to establish an animal model that disclosed the hallmarks of MRCT. This can now be used as a valuable, cost-effective, pre-clinical instrument to assist in the development of advanced tissue engineered strategies. Moreover, this animal model overcomes some of the limitations of those that have been reported so far and thus represents a more reliable source for the assessment of future therapeutic strategies with potential clinical relevance.Portuguese Foundation for Science and Technology (FCT)Programa Operacional Regional do Norte (ON.2—O Novo Norte), ao abrigo do Quadro de Referência Estratégico Nacional (QREN), através do Fundo Europeu de Desenvolvimento Regional (FEDER