Experimento de campo sobre la capacidad reproductiva de la almeja invasiva Mya arenaria en el estuario del rio Tajo: coexistencia con la almeja nativa Scrobicularia plana

A three month field experiment with tidal level (upper, middle, lower) and treatment (excavated and not excavated plots) as categorical experimental factors showed that the invasive clam Mya arenaria has reached a more advanced stage in the invasion process in the Tagus estuary. As we observed the smallest recruited juveniles of Mya arenaria (2 mm) throughout the study period, we concluded that the clam is capable of reproducing in the new habitat. Juveniles of both Mya arenaria and the bivalve Scrobicularia plana were found to avoid excavated experimental plots, showing a significantly higher abundance in the control plots. These data, strongly suggest that the recruited bivalves actively avoid unsuitable substrata. Juvenile specimens of Mya arenaria were more abundant in the mid-intertidal zone. However, juvenile specimens of Scrobicularia plana were mainly distributed in the upper intertidal level, which suggests that they have a different settlement behaviour from that observed for the juveniles of the invasive clam. Despite the divergent distribution between the juveniles of the two species in the study site, the possible interaction between these two species is considered and discussed.La almeja invasiva Mya arenaria ha alcanzado un nuevo estadio invasivo en el estuario del Río Tajo, de acuerdo con los resultados de un experimento de campo que transcurrió durante 3 meses y en el que fueron considerados los factores categóricos elevación intermareal (superior, intermedia e inferior) y tratamiento (unidades experimentales excavadas y no excavadas). La presencia continua durante el tiempo de estudio de juveniles del menor tamaño observado (2 mm) nos permitió deducir que la almeja invasiva es capaz de reproducirse en el nuevo hábitat. Individuos juveniles de Mya arenaria y Scrobicularia plana evitaron las unidades experimentales excavadas, siendo más abundantes en las unidades de control. Esta observación sugiere que los juveniles de ambas especies evitan activamente sustratos poco adecuados. Los juveniles de Mya arenaria se distribuyeron principalmente en la zona intermareal media. Sin embargo, los juveniles de Scrobicularia plana se concentraron principalmente en la región intermareal superior, lo que sugiere un comportamiento de fijación distinto al observado en la almeja invasiva. A pesar de la distribución divergente entre los juveniles, la probable interacción entre las dos especies es considerada y discutida

Distribución intermareal de las poblaciones de macroinvertebrados en el estuario del Tajo, Portugal, en relación con factores ambientales

Fourteen intertidal sites from the eastern mid-region of the Tagus estuary were considered in order to study their macrobenthic assemblages in relation to environmental factors. The salinity gradient was displayed in an ordination of the assemblages by non-metric multidimensional scaling (NMDS). However, salinity was not found to be a significant environmental factor to explain the distribution of the assemblages. Conversely, a lateral gradient characterized three clusters of sites identified in relation to their outer, intermediate and inner location also related to organic matter content, oxygen concentration and redox potential values. Although the hydrodynamic factor was not investigated it is thought to be an important environmental factor for characterizing the lateral gradient. As a general trend, there was a transition between the groups of assemblages from the lower estuary towards the inner and upstream locations. The polychaetes Lanice conchilega and Hediste diversicolor and the gastropod Hydrobia ulvae were the characteristic species in the outer, inner and intermediate groups of sites, respectively. It was concluded that the lateral gradient is the main environmental driver that explains the distribution of the intertidal macrobenthic assemblages in the Tagus estuary when the salinity gradient is not find to be a significant environmental factor.Se han estudiado las poblaciones de macroinvertebrados y su distribución en relación a varios factores ambientales en catorce estaciones de muestreo da la zona intermareal situadas en la región central, margen Este, del estuario del Río Tajo. El gradiente salino fue sobrepuesto sobre las poblaciones macrobentónicas tras aplicar un escalado multidimensional no métrico (NMDS). El análisis reveló que la salinidad no es un factor ambiental significativo en la distribución de las poblaciones macrobentónicas de la zona en estudio. En cambio, se identificó un gradiente lateral que caracterizó los grupos de estaciones de muestreo agrupadas según su localización exterior, interior e intermedia, igualmente relacionadas con los factores ambientales contenido de materia orgánica, concentración de oxígeno y potencial redox. Aunque no se ha medido el factor hidrodinámico, éste parece ser importante para la definición del gradiente lateral. De modo general se observó una transición gradual entre los grupos de poblaciones macrobentónicas desde los situados en la parte de mayor influencia marina hacia aquellos que se distribuyeron en zonas más alejadas del mar en sentido lateral o longitudinal. Los poliquetos Lanice conchilega y Hediste diversicolor y el gasterópodo Hydrobia ulvae fueron las especies características de los grupos de estaciones exterior, interior e intermedio respectivamente. Se ha concluido que el gradiente lateral es el principal condicionante ambiental que explica la distribución de las poblaciones de macroinvertebrados intermareales en el estuario del Río Tajo cuando el gradiente salino no es significativamente importante

Two new species and a new distributional record of Alterosa (Trichoptera: Philopotamidae) from southeastern Brazil

The genus Alterosa Blahnik (2005), with 39 extant species, is endemic to Atlantic Forest areas of southern and southeastern Brazil. Herein, we describe and illustrate two new species from Rio de Janeiro state, southeastern Brazil: Alterosa cornuta sp. nov., easily diagnosed by the horn-like intermediate appendages crossing each other, and A. araras sp. nov., recognized mainly by the extremely developed basodorsal protuberance on tergum X and by the rod-like, mesally curved preanal appendages, with at least 2 stout spine-like setae positioned at mid length and with the apex cupped. Additionally, a new distributional record for Espírito Santo state, southeastern Brazil, is provided for Alterosa falcata Blahnik (2005)

Supporting argumentation dialogues in group decision support systems: an approach based on dynamic clustering

Group decision support systems (GDSSs) have been widely studied over the recent decades. The Web-based group decision support systems appeared to support the group decision-making process by creating the conditions for it to be effective, allowing the management and participation in the process to be carried out from any place and at any time. In GDSS, argumentation is ideal, since it makes it easier to use justifications and explanations in interactions between decision-makers so they can sustain their opinions. Aspect-based sentiment analysis (ABSA) intends to classify opinions at the aspect level and identify the elements of an opinion. Intelligent reports for GDSS provide decision makers with accurate information about each decision-making round. Applying ABSA techniques to group decision making context results in the automatic identification of alternatives and criteria, for instance. This automatic identification is essential to reduce the time decision makers take to step themselves up on group decision support systems and to offer them various insights and knowledge on the discussion they are participating in. In this work, we propose and implement a methodology that uses an unsupervised technique and clustering to group arguments on topics around a specific alternative, for example, or a discussion comparing two alternatives. We experimented with several combinations of word embedding, dimensionality reduction techniques, and different clustering algorithms to achieve the best approach. The best method consisted of applying the KMeans++ clustering technique, using SBERT as a word embedder with UMAP dimensionality reduction. These experiments achieved a silhouette score of 0.63 with eight clusters on the baseball dataset, which wielded good cluster results based on their manual review and word clouds. We obtained a silhouette score of 0.59 with 16 clusters on the car brand dataset, which we used as an approach validation dataset. With the results of this work, intelligent reports for GDSS become even more helpful, since they can dynamically organize the conversations taking place by grouping them on the arguments used.This research was funded by National Funds through the Portuguese FCT-Fundacao para a Ciencia e a Tecnologia under the R&D Units Project Scope UIDB/00319/2020, UIDB/00760/2020, UIDP/00760/2020, and by the Luis Conceicao Ph.D. Grant with the reference SFRH/BD/137150/2018

Quality of the information : the application in the winification process in wine production

Knowledge representation techniques as a way to describe the real world, based on mechanical, logical or other means, will be, always, a function of the systems ability to describe the existing world. Knowledge and belief are generally incomplete, contradictory, or error sensitive, being desirable to use formal tools to deal with the problems that arise from the use of incomplete, contradictory, ambiguous, imperfect, or missing information. It is important to evaluate the quality-of-information of the knowledge around the time in order to analyze the best conditions of the universe of the discourse. Based on the vinification process of the wine production this paper analyzes the quality-of-information in the various stages of the process applying Extended Logic Programming as logic mathematical functions

Decision making and quality-of-information

Springer - Series Advances in Intelligent and Soft Computing, vol. 73In Group Decision Making based on argumentation, decisions are made considering the diverse points of view of the different partakers in order to decide which course of action a group should follow. However, knowledge and belief are normally incomplete, contradictory, or error sensitive, being desirable to use formal tools to deal with the problems that arise from the use of uncertain and even not precise information. On the other hand, qualitative models and qualitative reasoning have been around in Artificial Intelligence research for some time, in particular due the growing need to offer support in decision-making processes, a problem that in this work will be addressed in terms of an extension to the logic programming language and based on an evaluation of the Quality-of-Information (QoI) that stems out from those extended logic programs or theories. We present a computational model to address the problem of decision making, in terms of a multitude of scenarios, also defined as logic programs or theories, where the more appropriate ones stand for the higher QoIs values

A framework using open-source software for land use prediction and climate data time series analysis in a protected area of Portugal: Alvão Natural Park

Changes in land use and land cover (LULC) in protected areas can lead to an ecological imbalance in these territories. Temporal monitoring and predictive modeling are valuable tools for making decisions about conserving these areas and planning actions to reduce the pressure caused by activities such as agriculture. This study accordingly developed an LULC analysis framework based on open-source software (QGIS and R language) and predictive methodology using artificial neural networks in the Alvão Natural Park (PNA), a protected area in northern Portugal. The results show that in 2041, Agriculture and Open Space/Non-vegetation classes will evidence the greatest decrease, while Forest and Bushes will have expanded the most. Spatially, the areas to the west and northeast of the protected area will experience the most significant changes. The relationship of land use classes with data from the climate model HadGEM3-GC31-LL (CMIP6) utilizing scenarios RCP 4.5 and 8.5 demonstrates how through the period 2041–2060 there is a tendency for increased precipitation, which when combined with the dynamics of a retraction in classes such as agriculture, favors the advancement of natural classes such as bushes and forest; however, the subsequent climate data period (2061–2080) projects a decrease in precipitation volumes and an increase in the minimum and maximum temperatures, defining a new pattern with an extension of the period of drought and precipitation being concentrated in a short period of the year, which may result in a greater recurrence of extreme events, such as prolonged droughts that result in water shortages and fires.This research was funded by the European Regional Development Fund. Climate Change Resilient Tourism in Protected Areas of Northern Portugal (CLICTOUR-Project NORTE-01-0145-FEDER-000079)

Tropical Semiúmido e Tropical Semiseco: os tipos climáticos do domínio tropical brasileiro

As classificações climáticas são métodos empregados na identificação e caracterização de tipos climáticos, apresentando aplicação em várias áreas que dependem direta ou indiretamente das condições ambientais. O presente trabalho lança uma nova abordagem a respeito do domínio climático tropical, que é subdividido em dois tipos: um semiúmido e outro semiseco. Essa subdivisão é caracterizada pela quantidade de meses secos, que consiste na diferença entre a precipitação pluviométrica e a evapotranpiração potencial (ETP). Dados de temperatura, precipitação e ETP de sete estações meteorológicas do Instituto Nacional de Meteorologia (INMET) serviram como base para a determinação dos tipos climáticos. Essa metodologia, juntamente com o uso de tecnologias atuais e novas fontes de dados históricos, promove um aperfeiçoamento no sistema de classificação climática utilizado no país.

Anomaly Detection on Natural Language Processing to Improve Predictions on Tourist Preferences

This article belongs to the Special Issue Advances in Explainable Artificial Intelligence and Edge Computing Applications[Abstract] Argumentation-based dialogue models have shown to be appropriate for decision contexts in which it is intended to overcome the lack of interaction between decision-makers, either because they are dispersed, they are too many, or they are simply not even known. However, to support decision processes with argumentation-based dialogue models, it is necessary to have knowledge of certain aspects that are specific to each decision-maker, such as preferences, interests, and limitations, among others. Failure to obtain this knowledge could ruin the model’s success. In this work, we sought to facilitate the information acquisition process by studying strategies to automatically predict the tourists’ preferences (ratings) in relation to points of interest based on their reviews. We explored different Machine Learning methods to predict users’ ratings. We used Natural Language Processing strategies to predict whether a review is positive or negative and the rating assigned by users on a scale of 1 to 5. We then applied supervised methods such as Logistic Regression, Random Forest, Decision Trees, K-Nearest Neighbors, and Recurrent Neural Networks to determine whether a tourist likes/dislikes a given point of interest. We also used a distinctive approach in this field through unsupervised techniques for anomaly detection problems. The goal was to improve the supervised model in identifying only those tourists who truly like or dislike a particular point of interest, in which the main objective is not to identify everyone, but fundamentally not to fail those who are identified in those conditions. The experiments carried out showed that the developed models could predict with high accuracy whether a review is positive or negative but have some difficulty in accurately predicting the rating assigned by users. Unsupervised method Local Outlier Factor improved the results, reducing Logistic Regression false positives with an associated cost of increasing false negatives.This work was supported by the GrouPlanner Project under the European Regional Development Fund POCI-01-0145-FEDER-29178 and by National Funds through the FCT—Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UIDB/00319/2020 and UIDP/00760/2020Portugal. Fundação para a Ciência e a Tecnologia; POCI-01-0145-FEDER-29178Portugal. Fundação para a Ciência e a Tecnologia; UIDB/00319/2020Portugal. Fundação para a Ciência e a Tecnologia; UIDP/00760/202