A neural network approach in the sensorial comfort of wool light fabrics by subjective and objective evaluation

The textile and clothing industry, aware of the marketing evolution cannot neglect the requests of comfort, which have been increasing and are actual exigency for clothing goods consumers. There is an urgent need to evaluate and quantify the comfort properties of textile in general. The present work aims to make a study of the different types of lightweight wool fabrics, based on the objective evaluation of thermo and sensorial comfort, according to real preferences, to develop a simple sensorial comfort “predictable model”. The approach presented uses a self-organizing map (SOM), this type of neural network perform classification in a non-supervised fashion performing vector quantization and therefore placing similar vectors close together in the two dimensional output space. The unsupervised process leads to the self organization of modelling with no previous knowledge of what is being modelled and therefore it does not model a predetermined environment. Taking the above into account objective properties (physical and mechanical measured parameters) were selected and used to train the neural network to recognize subjective evaluations of sensorial comfort. The methodology applied in this work to develop the model is divided in two parts. In the first part, it was carried out the subjective evaluation of the materials, using a psychophysical methodology that enables the quantification of descriptive aspects of hand sensation (subjective evaluation by a panel of experts). One the other part, studies were conducted on fabric objective measurements: structural, thermal, physical and mechanical properties (KES-FB system). The results of the two parts were correlated by neural network techniques, in order to quantify the comfort, contributing for the definition of comfort sensorial standards for lightweight wool fabrics.Fundação para a Ciência e a Tecnologia (FCT

Temporal patterns in acoustic presence and foraging activity of oceanic dolphins at seamounts in the Azores

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cascao, I., Lammers, M. O., Prieto, R., Santos, R. S., & Silva, M. A. Temporal patterns in acoustic presence and foraging activity of oceanic dolphins at seamounts in the Azores. Scientific Reports, 10(1), (2020): 3610, doi:10.1038/s41598-020-60441-4.Several seamounts have been identified as hotspots of marine life in the Azores, acting as feeding stations for top predators, including cetaceans. Passive acoustic monitoring is an efficient tool to study temporal variations in the occurrence and behaviour of vocalizing cetacean species. We deployed bottom-moored Ecological Acoustic Recorders (EARs) to investigate the temporal patterns in acoustic presence and foraging activity of oceanic dolphins at two seamounts (Condor and Gigante) in the Azores. Data were collected in March–May 2008 and April 2010–February 2011. Dolphins were present year round and nearly every day at both seamounts. Foraging signals (buzzes and bray calls) were recorded in >87% of the days dolphin were present. There was a strong diel pattern in dolphin acoustic occurrence and behaviour, with higher detections of foraging and echolocation vocalizations during the night and of social signals during daylight hours. Acoustic data demonstrate that small dolphins consistently use Condor and Gigante seamounts to forage at night. These results suggest that these seamounts likely are important feeding areas for dolphins. This study contributes to a better understanding of the feeding ecology of oceanic dolphins and provides new insights into the role of seamount habitats for top predators.This research was supported by the Fundação para a Ciência e a Tecnologia (FCT), Azores 2020 Operational Programme and the Fundo Regional da Ciência e Tecnologia (FRCT), through research projects TRACE (PTDC/MAR/74071/2006), MAPCET (M2.1.2/F/012/2011), FCT-Exploratory (IF/00943/2013/CP1199/CT0001), WATCH IT (Acores-01-0145-FEDER-000057) and MISTIC SEAS II (GA11.0661/2017/750679/SUB/ENV.C2), co-funded by FEDER, COMPETE, QREN, POPH, European Social Fund (ESF), the Portuguese Ministry for Science and Education, and EU-DG/ENV. The Azores 2020 Operational Programme is funded by the community structural funds ERDF and ESF. Funds were also provided by FCT to MARE, through the strategic project UID/MAR/04292/2013. MAS was supported through a FCT Investigator contract funded by POPH, QREN, ESF and the Portuguese Ministry for Science and Education (IF/00943/2013). IC was supported by a FCT doctoral grant (SFRH/BD/41192/2007) and RP by a FCT postdoctoral grant (SFRH/BPD/108007/2015). We thank the field and crew teams for assisting with the many deployments and recoveries of the EARs. Special thanks to Norberto Serpa for helping with mooring design, Ken Sexton and Michael Richlen for their roles in manufacturing the EARs, Sergio Gomes for building the battery packs, and Lisa Munger for adapting Triton for EAR data analysis

Linear and nonlinear models for the analysis of the relationship between stock market prices and macroeconomic and financial factors

The main objective of this paper is to assess how mutual information as a measure of global dependence between stock markets and macroeconomic factors can overcome some of the weaknesses of the traditional linear approaches commonly used in this context. One of the advantages of mutual information is that it does not require any prior assumption regarding the specification of a theoretical probability distribution or the specification of the dependence model. This study focuses on the Portuguese stock market where we evaluate the relevance of the macroeconomic and financial variables as determinants of the stock prices behaviour.nonlinear dependence, stock market, financial and macroeconomic factors

Characterization of wine fermentations using fiber optic LWUV-Vis-SWNIR spectroscopy

Spectroscopy is widely used in biological sciences, being applied to liquids, pastes, powders, films, fibers, gases and surfaces. It makes possible to characterize proteins, peptides, lipids, membranes and carbohydrates in pharmaceuticals, foods, plants or animal tissues. It can also provide detailed information about the structure and mechanism of action of molecules. In this work we explore the use of fiber optics UV-VISSWNIR spectroscopy to characterize grape must fermentations of 114 different Saccharomyces cerevisiae strains. Results show that fiber optics UVVIS- SWNIR spectroscopy is a robust technique for characterize different wine fermentations, being able to characterize and differentiate the fermentation of different strains of S. cerevisiae based on their origins, by each spectroscopic fingerprint

Habitat preferences of baleen whales in a mid-latitude habitat

© The Author(s), 2016. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 141 (2017): 155-167, doi:10.1016/j.dsr2.2016.07.015.Understanding the dynamics of baleen whale distribution is essential to predict how environmental changes can affect their ecology and, in turn, ecosystem functioning. Recent work showed that mid-latitude habitats along migratory routes may play an important role on the feeding ecology of baleen whales. This study aimed to investigate the function of a mid-latitude habitat for blue (Balaenoptera musculus), fin (B. physalus) and sei (B. borealis) whales occurring in sympatry during spring and summer months and to what extent their environmental niches overlap. We addressed those questions by developing environmental niche models (ENM) for each species and then making pairwise comparisons of niche overlap and relative habitat patch importance among the three species. ENMs were created using sightings from the Azorean Fisheries Observer Program from May to November, between 2004 and 2009, and a set of 18 predictor environmental variables. We then assessed monthly (April-July) overlap among ENMs using a modified Hellinger’s distance metric (I). Results show that the habitat niches of blue and fin whales are strongly influenced by primary productivity and sea surface temperature and are highly dynamic both spatially and temporally due to the oceanography of the region. Niche overlap analyses show that blue and fin whale environmental niches are similar and that the suitable habitats for the two species have high degree of spatial coincidence. These results in combination suggest that this habitat may function as a mid-latitude feeding ground to both species while conditions are adequate. The sei whale model, on the other hand, did not include variables considered to be proxies for prey distribution and little environmental niche overlap was found between this species and the other two. We argue that these results suggest that the region holds little importance as a foraging habitat for the sei whale.This work was supported by FEDER funds, through the Competitiveness Factors Operational Programme - COMPETE, by national funds, through FCT - Foundation for Science and Technology, under project TRACE (PTDC/ MAR/74071/2006), and by regional funds, through DRCT/SRCTE, under project MAPCET (M2.1.2/ F/012/2011). We acknowledge funds provided by FCT to MARE, through the strategic project UID/MAR/04292/2013. RP was supported by an FCT postdoctoral grant (SFRH_BPD_108007_2015); MT’s fellowship was supported by the FCT Exploratory project (IF/00943/2013); MAS has an FCT Investigador contract (IF/00943/2013).2018-08-0

Environmental drivers of large-scale movements of baleen whales in the mid-North Atlantic Ocean

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Perez-Jorge, S., Tobena, M., Prieto, R., Vandeperre, F., Calmettes, B., Lehodey, P., & Silva, M. A. Environmental drivers of large-scale movements of baleen whales in the mid-North Atlantic Ocean. Diversity and Distributions, 00, (2020): 1-16, doi:10.1111/ddi.13038.Aim Understanding the environmental drivers of movement and habitat use of highly migratory marine species is crucial to implement appropriate management and conservation measures. However, this requires quantitative information on their spatial and temporal presence, which is limited in the high seas. Here, we aimed to gain insights of the essential habitats of three baleen whale species around the mid‐North Atlantic (NA) region, linking their large‐scale movements with information on oceanographic and biological processes. Location Mid‐NA Ocean. Methods We present the first study combining data from 31 satellite tracks of baleen whales (15, 10 and 6 from fin, blue and sei whales, respectively) from March to July (2008–2016) with data on remotely sensed oceanography and mid‐ and lower trophic level biomass derived from the spatial ecosystem and population dynamics model (SEAPODYM). A Bayesian switching state‐space model was applied to obtain regular tracks and correct for location errors, and pseudo‐absences were created through simulated positions using a correlated random walk model. Based on the tracks and pseudo‐absences, we applied generalized additive mixed models (GAMMs) to determine the probability of occurrence and predict monthly distributions. Results This study provides the most detailed research on the spatio‐temporal distribution of baleen whales in the mid‐NA, showing how dynamic biophysical processes determine their habitat preference. Movement patterns were mainly influenced by the interaction of temperature and the lower trophic level biomass; however, this relationship differed substantially among species. Best‐fit models suggest that movements of whales migrating towards more productive areas in northern latitudes were constrained by depth and eddy kinetic energy. Main conclusions These novel insights highlight the importance of integrating telemetry data with spatially explicit prey models to understand which factors shape the movement patterns of highly migratory species across large geographical scales. In addition, our outcomes could contribute to inform management of anthropogenic threats to baleen whales in sparsely surveyed region.We are very grateful to Cláudia Oliveira, Irma Cascão, Maria João Cruz, Miriam Romagosa and many volunteers, skilled skippers, crew and spotters that participated in the tagging fieldwork. This work was supported by Fundação para a Ciência e Tecnologia (FCT), Azores 2020 Operational Programme and Fundo Regional da Ciência e Tecnologia (FRCT) through research projects FCT‐Exploratory project (IF/00943/2013/CP1199/CT0001), TRACE (PTDC/MAR/74071/2006) and MAPCET (M2.1.2/F/012/2011) co‐funded by FEDER, COMPETE, QREN, POPH, ESF, ERDF, Portuguese Ministry for Science and Education, and Proconvergencia Açores/EU Program. We also acknowledge funds provided by FCT to MARE, through the strategic project UID/MAR/04292/2013. SPJ was supported by a postdoctoral grant (REF.GREENUP/001‐2016), MT by a DRCT doctoral grant (M3.1.a/F/028/2015), MAS by an FCT‐Investigator contract (IF/00943/2013), FV by an FCT Investigator contract (CEECIND/03469/2017) and RP by an FCT postdoctoral grant (SFRH/BPD/108007/2015). LMTL modelling work has been supported by the CMEMS Service Evolution GREENUP project, funded by Mercator Ocean. We are grateful to Elliott Hazen for offering guidance and advice, and to two anonymous referees whose comments greatly improved this work

Can Credit Rating Agencies Affect Election Outcomes?

We show that credit rating agencies can have a significant effect on election outcomes. We identify these effects by exploiting exogenous variation in municipal bond ratings due to Moody’s recalibration of its scale in 2010. We find that incumbent politicians in upgraded municipalities experience an increase in their likelihood of reelection and their vote shares. These rating upgrades improve voters’ opinions about the incumbent and produce positive wealth effects through voters’ holdings of local municipal bonds. In addition, rating upgrades cause an expansion of local governments’ debt capacity that allows the incumbent to increase spending and improve local economic conditions

A data-driven approach for the definition of metropolitan regions

The objective of this paper is to present a data-driven approach for the definition of metropolitan regions. The proposed approach, which constitutes an option to avoid the endless confrontations that may be derived from the essentially subjective political criteria, explores two branches of Spatial Analyses: Spatial Statistics and Spatial Modeling. Spatial Statistics tools are used to identify the characteristics of local association and combined with Cellular Automata techniques in order to build prediction models. The analyses conducted with Exploratory Spatial Data Analyses (ESDA) tools and census data give a clear indication of clusters of zones with similar characteristics, which can be seen as uniform regions. Spatial dynamic models can then be used to foresee the global behavior of regions in terms of growth, although based on local (and historical) relationships among zones. The proposed approach is tested in a case study carried out in Portugal, where this is a timely issue

A spatial analysis approach for the definition of metropolitan regions : the case of Portugal

The objective of this paper is to present a combined, two-step spatial analysis approach for the definition of metropolitan regions. The proposed approach, which constitutes an option to avoid the endless confrontations that may be derived from the essentially subjective political criteria, explores two branches of spatial analysis: spatial statistics and spatial modelling. Spatial statistics tools are used to identify the characteristics of local association and are combined with a neural network in order to build prediction models. The analyses conducted with exploratory spatial data analysis tools and census data give a clear indication of clusters of zones with similar characteristics, which can be seen as uniform regions. Spatial models can then be used to foresee the global behaviour of regions in terms of growth, albeit the basis of local (and historical) relationships among zones. The proposed approach is tested in a case study carried out in Portugal, where this is a timely issue

On the use of hedonic regression models to measure the effect of energy efficiency on residential property transaction prices : evidence for Portugal and selected data issues

Using a unique dataset containing information of around 256 thousand residential property sales, this paper discloses a clear sales premium for most energy efficient dwellings, which is more pronounced for apartments (13%) than for houses (5 to 6%). Cross-country comparisons support the finding that energy efficiency price premiums are higher in the Portuguese residential market than in central and northern European markets. Results emphasize the relevance of data issues in hedonic regression models. They illustrate how the use of appraisal prices, explanatory variables with measurement errors, and the omission of variables associated with the quality of the properties, may seriously bias energy efficiency partial effect estimates. These findings provide valuable information not only to policy-makers, but also to researchers interested in this area.info:eu-repo/semantics/publishedVersio