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In this paper good consensus is associated with a high level of group satisfaction and a low level of dissatisfaction. A new method to improve consensus through a reformulation of the original group multi-objective optimization problem is introduced. For each point in the feasible decision set, the level of satisfaction or dissatisfaction from each group member is determined by multi-criteria ordinal classification approaches. Intense satisfaction and dissatisfaction are both modeled. Group satisfaction (respectively, dissatisfaction) is maximized (resp. minimized), finding the best possible consensus solutions in correspondence with a current stage of closeness among group members’ preferences, judgments, beliefs, and conservatism attitudes. Logic models are introduced to evaluate conditions for best consensus. Imperfect information (imprecision, uncertainty, ill-definition, arbitrariness) on the values of objective functions, required and available resources, and decision model parameters is handled by using interval numbers. Two different kinds of multi-criteria decision model are considered: i) an interval outranking approach and ii) an interval weighted-sum value function. The proposal can handle very general cases of group multi-objective optimization problems. The method is illustrated by solving a real size multi-objective project portfolio optimization problem using evolutionary computation tools.

The restrictions related to the COVID-19 pandemic have led to a global hiatus in anthropogenic activities; several scientists have utilized this unique opportunity to assess the human impact on biological systems. In this study, the study describes for a period of five years (2018-2022) how the faunal community have been affected by human disturbances, as well as the effect of the "anthropause" period driven by the COVID-19 lockdown. The results confirmed human disturbances on faunal communities related to coastal urbanization. It was found that the "anthropause" period showed the highest values of abundance and biomass, hence the "COVID-19 lockdown" allowed recovery of faunal communities. The findings highlight the impact of human disturbances and that the community showed resilience. Overall, the authorities must perform restrictive measures aiming to mitigate the impact of anthropogenic activities in the study area including the banning of off-road and recreational vehicles, carrying out efficient cleaning and grooming operations, monitoring the severe harvesting of edible species, as well as penalizing the disposal of anthropogenic waste and sewage discharge from the touristic facilities. Likewise, management actions such as the temporal beach closures and the regular surveillance could be advantageous to provide a more sustainable exploitation of sandy beaches.

Knowledge on the processes controlling the vertical distribution of microplastics (MPs) in estuaries is less. This research was carried out to determine the MP distribution in the surface, middle, and bottom layers of the Udyavara River Estuary in southwest India. The mean (± standard deviation) concentrations were 320.83 (± 98.30), 514.55 (± 352.16), and 755.03 (± 400.96) particles/m

Microplastics (MPs) have become a dominant constituent of several oceanic islands. This study focuses on the occurrence and distribution of MPs present in the beach sediments of Saint Mary's Island (SMI), a geological heritage site located in the south-eastern part of the Arabian Sea. The average (standard deviation) abundance of MPs on this island was 97.18 (80.49) particles/kg. Attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy revealed that MPs are composed of high-density polyethylene (HDPE), low-density polyethylene (LDPE), polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyamide (PA). Scanning Electron Microscopy (SEM) and Energy-Dispersive X-ray Spectroscopy (EDS) highlighted the presence of Cr, As, Pb, and Cd (harmful pollutants) on MP surfaces. The MPs in the SMI are largely contributed by the nearby fishing harbour, touristic beaches and estuaries. The results of this study, act as a starting point for continuous environmental monitoring in this unique region of the world.

Multi-objective Optimization Evolutionary Algorithms (MOEAs) face numerous challenges when they are used to solve Many-objective Optimization Problems (MaOPs). Decomposition-based strategies, such as MOEA/D, divide an MaOP into multiple single-optimization sub-problems, achieving better diversity and a better approximation of the Pareto front, and dealing with some of the challenges of MaOPs. However, these approaches still require one to solve a multi-criteria selection problem that will allow a Decision-Maker (DM) to choose the final solution. Incorporating preferences may provide results that are closer to the region of interest of a DM. Most of the proposals to integrate preferences in decomposition-based MOEAs prefer progressive articulation over the “a priori” incorporation of preferences. Progressive articulation methods can hardly work without comparable and transitive preferences, and they can significantly increase the cognitive effort required of a DM. On the other hand, the “a priori” strategies do not demand transitive judgements from the DM but require a direct parameter elicitation that usually is subject to imprecision. Outranking approaches have properties that allow them to suitably handle non-transitive preferences, veto conditions, and incomparability, which are typical characteristics of many real DMs. This paper explores how to incorporate DM preferences into MOEA/D using the “a priori” incorporation of preferences, based on interval outranking relations, to handle imprecision when preference parameters are elicited. Several experiments make it possible to analyze the proposal's performance on benchmark problems and to compare the results with the classic MOEA/D without preference incorporation and with a recent, state-of-the-art preference-based decomposition algorithm. In many instances, our results are closer to the Region of Interest, particularly when the number of objectives increases.

Visual pollution is the visible deterioration and negative aesthetic quality of the landscape. Erosion, marine wrack, litter, sewage, and beach driving are affecting the coastal scenery and are generating a visual pollution problem on the Rabigh coastal area, Kingdom of Saudi Arabia. This work provides the scenic evaluation of 31 coastal sites using the Coastal Scenery Evaluation System (CSES) to determine the current state of this situation and give management inputs. The CSES assesses values from a checklist of 18 physical and 8 human parameters and allows the calculation of a scenic evaluation index (D Value), which classifies coastal sites into five classes: Class I, usually natural areas of top scenic characteristics, to Class V, poor scenic natural areas with a higher impact of human interventions. Along the study area, three sites (9.7 %) appeared in Class II; five (16.1 %) in Class III; 15 (48.4 %) in Class IV, and eight sites (25.8 %) in Class V. Class I sites were not found in the study area. Assessment presented in this work provides a complete overview of the Rabigh coastal scenery and serves as a baseline for implementing management strategies to cope the visual pollution problem.

Simulated annealing is a metaheuristic that balances exploration and exploitation to solve global optimization problems. However, to deal with multi- and many-objective optimization problems, this balance needs to be improved due to diverse factors such as the number of objectives. To deal with this issue, this work proposes MOSA/D, a hybrid framework for multi-objective simulated annealing based on decomposition and evolutionary perturbation functions. According to the literature, the decomposition strategy allows diversity in a population while evolutionary perturbations add convergence toward the Pareto front; however, a question should be asked: What is the effect of such components when included as part of a multi-objective simulated annealing design? Hence, this work studies the performance of the MOSA/D framework considering in its implementation two widely used perturbation operators: classical genetic operators and differential evolution. The proposed algorithms are MOSA/D-CGO, based on classical genetic operators, and MOSA/D-DE, based on differential evolution operators. The main contribution of this work is the performance analysis of MOSA/D using both perturbation operators and identifying the one most suitable for the framework. The approaches were tested using DTLZ on two and three objectives and CEC2009 benchmarks on two, three, five, and ten objectives; the performance analysis considered diversity and convergence measured through the hypervolume (HV) and inverted generational distance (IGD) indicators. The results pointed out that there is a promising improvement in performance in favor of MOSA/D-DE.

MDM2 amplification represents the leading oncogenic pathway and diagnostic hallmark of liposarcoma, whose assessment is based on Fluorescence In Situ Hybridization (FISH) analysis. Despite its diagnostic relevance, no univocal interpretation criteria regarding FISH assessments of MDM2 amplification have been established so far, leading to several different approaches and potential diagnostic misinterpretations. This study aims to address the most common issues and proposes troubleshooting guidelines for MDM2 amplification assessments by FISH. We retrospectively retrieved 51 liposarcomas, 25 Lipomas, 5 Spindle Cell Lipoma/Pleomorphic Lipomas, and 2 Atypical Spindle Cell Lipomatous Tumors and the corresponding MDM2 FISH analysis. We observed MDM2 amplification in liposarcomas cases only (43 out of 51 cases) and identified three MDM2-amplified patterns (scattered (50% of cases), clustered (14% of cases), and mixed (36% of cases)) and two nonamplified patterns (low number of signals (82% of cases) and polysomic (18% of cases)). Based on these data and published evidence in the literature, we propose a set of criteria to guide MDM2 amplification analysis in liposarcoma. Kindled by the compelling importance of MDM2 assessments to improve diagnostic and therapeutic liposarcoma management, these suggestions could represent the first step to develop a univocal interpretation model and consensus guidelines.

This study describes the contamination, accumulation, and ecological risk assessment of five trace metals (Cd, Pb, Cu, Zn, and Cr) in sediments of an urbanized beach in the central Atlantic coastline of Morocco. The two-year investigation (2018 and 2019) included six sampling sites along a 6 km coastal reach. In both years, none of the studied trace metals exceeded the background or the sediment quality guidelines (SQGs). The eco-toxicological indices revealed low degree of contamination, unpolluted ecosystem, and low ecological risk of metals. However, Cd exceeded the background value and some SQGs following the increase of anthropogenic activities in 2019. Likewise, it indicated unpolluted to moderately polluted sediment as well as moderate ecological risk. Overall, it is highly recommended to mitigate the avoidable anthropogenic activities (marine litter generation, sewage discharge, intense urbanization, and vehicle traffic on the beach) that lead to the elevation of metal pollution in the study area.

Plastic production is an essential part of the world economy that has mushroomed exponentially with c.9.2 billion tonnes estimated to have been made between 1950 and 2017. Now, each year c.8-11 million tonnes of plastic waste escapes into the oceans. Plastic usage is varied but the packaging industry accounts for 47%. Recycling and the circular economy are seen as keys to unlocking the plastic problem, for example, via the Extended Producer Responsibility scheme; a Deposit Return Scheme. The circular economy is a fine idea and has been around a long time, but has it made any real difference? The amount of plastic in circulation keeps getting bigger and bigger. More thought must be given to creating technologies and designs that can deal with waste management, integrate international collaboration and cut waste to a bare minimum at its source point upstream. No single solution exists, but there is a need for a legally binding global governance arrangement that would effectively and measurably limit and control plastic pollution. Many governments are in favour of this.

This paper introduces a strategy to enrich swarm intelligence algorithms with the preferences of the Decision Maker (DM) represented in an ordinal classifier based on interval outranking. Ordinal classification is used to bias the search toward the Region of Interest (RoI), the privileged zone of the Pareto frontier containing the most satisfactory solutions according to the DM’s preferences. We applied this hybridising strategy to two swarm intelligence algorithms, i.e., Multi-objective Grey Wolf Optimisation and Indicator-based Multi-objective Ant Colony Optimisation for continuous domains. The resulting hybrid algorithms were called GWO-InClass and ACO-InClass. To validate our strategy, we conducted experiments on the DTLZ problems, the most widely studied test suit in the framework of multi-objective optimisation. According to the results, our approach is suitable when many objective functions are treated. GWO-InClass and ACO-InClass demonstrated the capacity of reaching the RoI better than the original metaheuristics that approximate the complete Pareto frontier.

In this paper, the portfolio optimization problem is approached. It is a NP-hard problem that consists in periodically creating an instance of the problem, using the time series of the shares value of a stock exchange. The instance is solved to determine the shares set that maximize the return, minimize the risk and minimize the number of selected shares. As far as we know, only three algorithms of the state-of-the-art of the portfolio selection problem with three objectives have been assessed. In this work, we propose a Fuzzy Multi-objective Particle Swarm Optimization (FOMOPSO) that uses an auto-Tuning Fuzzy Controller. To validate our approach, a series of experiments with the realistic instances and the performance of the proposed algorithm were compared with three state-of-the-art evolutionary algorithms using six commonly used metrics. To support the conclusions, two hypothesis tests were applied. The results show that the Fuzzy Rules auto-configuration contributes to that the proposed algorithm performance clearly outperforms three of the algorithms in comparison, for four of the metrics used.

Currently, there are many types of conversational agents whose goal is to emulate human behavior. These agents offer more believable conversations when their responses come from a deliberative process that mimics individuals’ character. Conversational agents are mainly used for response selection linguistics and context situated strategies. These approaches usually build rules to find answers in dialogues; however, this is not the best alternative when the communicative intentions are not literal and context dependent. Deliberative Agents can solve these issues and improve their selection process through the integration of preferences and personality in their cognitive process. Hence, this work investigates how to drive the expression of dialogues of a Conversational Deliberative Agent (CDA) through personality and fuzzy outranking relations; for this, it proposes the characterization of context, and corpus through speech acts theory, and also a selection process based on fuzzy outranking relations to compare corpus phrases and context to choose the best response. The main contributions of this work are (1) the agent architecture that integrates preferences and personality of an individual in the response selection cognitive process; (2) a characterization model of speech acting through criteria based on belief, desires, and intentions to define a more human behavior expression; and (3) the use of fuzzy outranking relations to select phrases from a corpus to match dialogue intentions. An experimental design demonstrated the aptitude of the developed CDA to offer quality responses on a tutor application. Also, the results showed the capacity of speech acts to handle contexts in dialogues.

In decision-making, the multiobjective portfolio selection problem (MPSP) consists of the selection of alternatives based on preferences of a particular decision-maker (DM). In real-world applications, MPSP has several conflicting criteria that DMs must consider to determine an appropriate solution. So far, only fuzzy outranking relations have been used in a relational system of preferences to guide the search process of genetic algorithms (NOSGAII), and ant colony optimization (NOACO) to approximate the region of interest (RoI) of MPSP involving DM’s preferences. The NOSGAII and NOACO strategies are sequential, and they face a real challenge when solving high-dimensional instances which is a decrement in the computational efficiency due to the increment in the number of objectives. The present research proposes to use parallelism to tackle the efficiency situation in metaheuristics. The study first identifies which approach approximates better the RoI, and then, it analyzes the effect of parallelism in the performance. The results showed that NOACO found more best compromises in almost all the instances than NOSGAII. Hence, it can be concluded that NOACO approximates better the RoI. Also, the results showed a better average speedup with coarse-grained parallelism in NOACO than with data-flow parallelism, suggesting the conclusion that ants independently working are faster than ants working collaboratively. Finally, the main contributions are (1) the analysis of the performance of the two approaches for MPSP, (2) the five parallel designs for NOACO, and (3) the parallel NOACO that speedups up to 2× the sequential version when solving MPSP.

Introducción: El incremento de la actividad sísmica como fuente energética asociada a las erupciones volcánicas de lodo en Urabá (Mayo 2017), Cartagena (Junio 2017) y en Canalete, Córdoba (Diciembre 2017), motivó la realización de un estudio geoeléctrico y microsismológico, que busca evaluar la dinámica del volcán El Totumo en límites de los departamentos de Bolívar y Atlántico en la región Caribe de Colombia, por lo tanto el propósito de éste trabajo es presentar los resultados de un estudio Geofísico para determinar anomalías relativas a la dinámica del volcán. Objetivo: Se espera detectar a través de las tomografías los flujos de lodo en ascenso hacia la superficie situación que generaría riesgos para el turismo de la región. Metodología: Para este estudio se aplican dos métodos Geofísicos: Prospección Geoeléctrica y Monitoreo Sísmológico, con el fin de detectar la distribución de los materiales litológicos en profundidad, así como los rasgos estructurales más importantes relacionados con la distribución y ascenso de lodo. Todo lo anterior se logra mediante el análisis de Tomografías que revelan con claridad el peligro generado por los flujos de lodo fino en ascenso y el método SPAC (por sus siglas del Inglés, Spatial Autocorrelation) que permite correlacionar las velocidades de las señales con los estratos sedimentarios, e identificar con claridad la alteración del soporte estructural del volcán El Totumo debido a la presión ejercida por el lodo en ascenso a la superficie. Resultados: Al llevar a cabo el procesamiento de los datos Geofísicos en ambos casos, se observa una distribución litológica normal característica de las resistividades del subsuelo. No obstante, no se observan anomalías o cambios estructurales en las tomografías eléctricas, como tampoco rastros de actividad sísmica o sismológica que hubiesen alterado el perfil de velocidades de ondas de corte. Conclusiones: Por todo lo anterior se puede afirmar que no se presentan anomalías relativas al comportamiento dinámico del volcán en este periodo de tiempo, se sugiere aplicar la misma metodología para estudios futuros del mismo fenómeno no solo al volcán El Totumo sino a cualquier volcán de lodo con el fin de generar alertas tempranas sobre los riesgos que su actividad implica frente a los personas que habitan en sus proximidades. Palabras clave: Salses, Volcán de lodo, Monitoreo sismológico, Diapirismo, Flujo de lodos, Tomografías Eléctricas, Microtremores, Ondas de Corte

Objetivo: previamente se reportó que tumores de seno con proporción receptor de andrógenos/receptor de estrógenos ?2 (AR/ER ?2) se asocian con peores pronósticos. De acuerdo con lo anterior, el objetivo del presente estudio fue evaluar la relación entre la proporción AR/ER y una señal génica de proliferación celular en cáncer de seno (CS; también conocido como cáncer de mama) ER positivo (ER+). Métodos: se obtuvieron 1093 muestras de CS primario con datos de expresión génica de la base de datos pública NCI Genomic Data Commons. Se ejecutaron análisis bioinformáticos para establecer niveles de expresión génica de AR y ER, así como de los marcadores de proliferación AURKb, BUB1B, BUB1, CDK1 y CHEK1. Adicionalmente, se definieron subtipos moleculares de CS utilizando el bioclasificador PAM50. Resultados: 835 casos se reportaron como ER+. Entre estos, 58 tumores (7%) presentaron mayores niveles de expresión de AR respecto a ER (AR/ER ?2). En dichos casos se observaron niveles significativamente más altos de proliferación con respecto a tumores, con proporción AR/ER

Pesticides are a group of environmental pollutants widely used in agriculture to protect crops, and their indiscriminate use has led to a growing public awareness about the health hazards associated with exposure to these substances. In fact, exposure to pesticides has been associated with an increased risk of developing diseases, including cancer. In a study previously published by us, we observed the induction of specific chromosomal alterations and, in general, the deleterious effect of pesticides on the chromosomes of five individuals exposed to pesticides. Considering the importance of our previous findings and their implications in the identification of cytogenetic biomarkers for the monitoring of exposed populations, we decided to conduct a new study with a greater number of individuals exposed to pesticides. Considering the above, the aim of this study was to evaluate the type and frequency of chromosomal alterations, chromosomal variants, the level of chromosomal instability and the clonal heterogeneity in a group of thirty-four farmers occupationally exposed to pesticides in the town of Simijacá, Colombia, and in a control group of thirty-four unexposed individuals, by using Banding Cytogenetics and Molecular Cytogenetics (Fluorescence in situ hybridization). Our results showed that farmers exposed to pesticides had significantly increased frequencies of chromosomal alterations, chromosomal variants, chromosomal instability and clonal heterogeneity when compared with controls. Our results confirm the results previously reported by us, and indicate that occupational exposure to pesticides induces not only chromosomal instability but also clonal heterogeneity in the somatic cells of people exposed to pesticides. This study constitutes, to our knowledge, the first study that reports clonal heterogeneity associated with occupational exposure to pesticides. Chromosomal instability and clonal heterogeneity, in addition to reflecting the instability of the system, could predispose cells to acquire additional instability and, therefore, to an increased risk of developing diseases.

Plastics, "yesterday's hero... today's villain" or "the contemporary symbol of modernity," were invented in the early 20th century by Leo Hendrik Baekeland from macromolecules (resins, elastomers, and artificial fibres) of formaldehyde and phenol. This synthetic organic polymer took hold of daily human life and transformed the modern world with an ever-widening range of applications. Plastics are the third most-widely manufactured material in the world after cement and steel, and they have become widespread in our society with excessive production and consumption to meet demand. Plastics use is so dominant that they are inappropriately considered essential in the world consumers marketplace. Plastics are a clear indicator of the Anthropocene and can be considered the marker of the upper subdivision of this stage: the Plasticene.

Diverse litter studies on Colombia's Central Caribbean Coast have presented the Microplastic issues regarding typology, magnitudes, and distribution. No studies have examined MPs' presence and abundances in relation to sediment grain size and the sediments statistical parameters (mean, median, sorting, skewness, kurtosis). This work attempts to fill this information gap in a study of 15 sampling sites along Colombia's Central Caribbean Coast. Sediment samples were collected and analysed to determine sediment granulometric properties, in association with the presence, magnitudes, shapes, and impact of MPs, and their possible relationships. Within the study area, grain size distribution was similar between surveyed sites, with a dominance of three textural groups: sands, slightly gravelly sands, and slightly gravelly muddy sands. In terms of size-sorting categories, the percentages were moderately well sorted (60 %), moderately sorted (20 %), well sorted (13 %), and very well sorted (7 %). Microplastic abundances (densities) ranged from 160 to 1120 MPs/kg, similar to other global beaches. Microplastic fibers were the dominant typology at 86.8 % of the combined beaches total. Multiple linear regression analysis suggested that approximately 30 % of the MPs' presence could be related to changes in the five sediment statistics used in this work, being the most important statistical parameter sorting with 11 % (r

This study focuses on assessing litter magnitudes along the Torre Guaceto Marine Protected Area (Brindisi, Italy). Collected litter was grouped into twenty different types and classified into four litter typologies according to the Guidance on Monitoring of Marine Litter in European Seas. All data were analyzed using an index-based approach that allowed the classification of a coastal stretch in terms of cleanliness, and presence of plastics as well hazardous items. The average litter abundance in the study area was 0.5 items/m2, being plastics the most common litter item. Hazardous litter items were found along the study area, reaching 21.3% of the total collected items. The application of environmental indices allowed to define the study area with a “moderate cleanliness” and a “moderate” presence of hazardous litter items. Sampled litter typologies and related magnitudes suggest a combination of sources that mainly include direct activities on the nearby coastal zones and river basins (dumping).

Simple Summary Breast cancer (BC) is the second largest cause of death for cancer in women worldwide. Different studies have shown that the androgen receptor (AR), a cytoplasmic ligand-dependent transcription factor, may play a role as a marker of BC biology. We aimed to assess the clinical significance of AR gene expression in BC by meta-analysis of large-scale microarray transcriptomic datasets. Our findings suggest that high mRNA levels of AR have the potential to be a promising non-invasive prognostic biomarker for the identification of the less aggressive BC subtypes. Abstract The androgen receptor (AR) is frequently expressed in breast cancer (BC), but its association with clinical and biological parameters of BC patients remains unclear. Here, we investigated the association of AR gene expression according to intrinsic BC subtypes by meta-analysis of large-scale microarray transcriptomic datasets. Sixty-two datasets including 10315 BC patients were used in the meta-analyses. Interestingly, AR mRNA level is significantly increased in patients categorized with less aggressive intrinsic molecular subtypes including, Luminal A compared to Basal-like (standardized mean difference, SMD: 2.12; 95% confidence interval, CI: 1.88 to 2.35; p < 0.001) or when comparing Luminal B to Basal-like (SMD: 1.53; CI: 1.33 to 1.72; p < 0.001). The same trend was observed when analyses were performed using immunohistochemistry-based surrogate subtypes. Consistently, the AR mRNA expression was higher in patients with low histological grade (p < 0.001). Furthermore, our data revealed higher levels of AR mRNA in BC patients expressing either estrogen or progesterone receptors (p < 0.001). Together, our findings indicate that high mRNA levels of AR are associated with BC subgroups with the less aggressive clinical features.

COVID-19 cases on international cruise ships have attracted extensive attention from the international community as well as the world's tourism and shipping industry. This virus highlighted the plight that must be faced by cruise ships in complicated times and situations such as pandemics. The comparative method is adopted to analyze the management measures taken by the "Diamond Princess", "Costa Serena", "Westerdam" and "Grand Princess" cruises in response to the COVID-19 pandemic and then to summarize the common dilemmas faced by these cruise ships, including defects of their internal environment, unclear health-care obligations during an epidemic, weak collaboration between the parties involved and their limited performance, and widespread infodemic and unfavorable public opinion. Given these dilemmas, measures are suggested to deal with the "cruise dilemma", including establishing and defining isolation standards on boards, enhancing the capacity of international organizations, the international community's joint response to the pandemic, promoting cooperation between countries, building an effective mechanism for the broad participation of the whole society, and standardizing the release of information and reasonably guiding public social opinion.

This work describes the spatiotemporal analysis of microplastics (MPs) pollution in sediments collected on a high urbanized beach located in Taghazout coast, central Atlantic part of Morocco. The study area is mainly composed of moderately well-sorted fine sands with an average density of MPs that ranged between 915 MPs/kg in 2018 and 1448 MPs/kg in 2019. The most polluted sites were in the south part of Taghazout coast, close to facilities of where beachgoers are often found. Microplastic Pollution Index (MPPI), Microplastic Impact Coefficient (CMPI), Agglomerative Hierarchical Clustering (AHC), and Multidimensional Scaling (MDS) revealed spatiotemporal variation of MPs pollution. Thus, the principal component analysis (PCA) showed a low correlation between the sediment characteristics (i.e., grain size, sorting, skewness) and MPs densities. Overall, the outputs of this baseline recommend implementing plastic management strategies to eliminate or at least minimize the collateral effects generated by MPs pollution in sediments of urbanized beaches.

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs, (b) each group member may consider their own set of objective functions and constraints, (c) objective values may be imprecise or uncertain, (d) imperfect information on resources availability and requirements may be handled, (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

Simple Summary Despite increased information showing obesity is an important breast cancer (BC) risk factor, the mechanisms implicated in this association are not well understood. In this review we describe multiple lines of evidence indicating that altered secretion of androgens and adipokines, from dysfunctional adipose tissue, are independently linked with BC development. However, adipokines (adiponectin and leptin) participate in important biological processes in BC cells by modulating signaling pathways similar to those used by the androgen receptor. These similarities suggest that crosstalk between these factors can occur, with a high probability that its interactions may be responsible for modifying the behavior of normal and tumor cells, especially in obesity. The knowledge of how adiponectin and leptin can interact with the androgen receptor signaling may prospectively guide the development of therapeutic approaches aimed at potentiating the inhibitory actions of adiponectin and androgen receptor or interfering with the pro-stimulatory role of leptin in BC. Abstract Obesity is an increasing health challenge and is recognized as a breast cancer risk factor. Although obesity-related breast cancer mechanisms are not fully understood, this association has been linked to impaired hormone secretion by the dysfunctional obese adipose tissue (hyperplasic and hypertrophic adipocytes). Among these hormones, altered production of androgens and adipokines is observed, and both, are independently associated with breast cancer development. In this review, we describe and comment on the relationships reported between these factors and breast cancer, focusing on the biological associations that have helped to unveil the mechanisms by which signaling from androgens and adipokines modifies the behavior of mammary epithelial cells. Furthermore, we discuss the potential crosstalk between the two most abundant adipokines produced by the adipose tissue (adiponectin and leptin) and the androgen receptor, an emerging marker in breast cancer. The identification and understanding of interactions among adipokines and the androgen receptor in cancer cells are necessary to guide the development of new therapeutic approaches in order to prevent and cure obesity and breast cancer.

The decision-making process can be complex and underestimated, where mismanagement could lead to poor results and excessive spending. This situation appears in highly complex multi-criteria problems such as the project portfolio selection (PPS) problem. Therefore, a recommender system becomes crucial to guide the solution search process. To our knowledge, most recommender systems that use argumentation theory are not proposed for multi-criteria optimization problems. Besides, most of the current recommender systems focused on PPS problems do not attempt to justify their recommendations. This work studies the characterization of cognitive tasks involved in the decision-aiding process to propose a framework for the Decision Aid Interactive Recommender System (DAIRS). The proposed system focuses on a user-system interaction that guides the search towards the best solution considering a decision-maker’s preferences. The developed framework uses argumentation theory supported by argumentation schemes, dialogue games, proof standards, and two state transition diagrams (STD) to generate and explain its recommendations to the user. This work presents a prototype of DAIRS to evaluate the user experience on multiple real-life case simulations through a usability measurement. The prototype and both STDs received a satisfying score and mostly overall acceptance by the test users.

The growth of large enterprises in the manufacturing market commonly depends on good New Product Development (NPD) projects; these projects represent a strategy to overcome competitors inside a competitive environment. The management of such projects is usually complex and involves risk due to the changing and conflicting environment. The approaches that tackle the problem lack an explicit consideration of the DM’s attitude facing uncertainty and imprecision related to the risk and particularly in the presence of time-interdependencies. This paper proposes a model of the time-related effects, under imperfect knowledge, and their influence in choosing optimal NPD portfolios. The proposed approach is an interval-based method to solve NPD portfolio optimization problems under different forms of imperfect knowledge. This approach has the advantage of a unified and simple way to model the different sources of imprecision, vagueness, uncertainty, and arbitrariness. The attitude of the DM facing the imperfect knowledge is adjusted by using some meaningful parameters. The research focuses particularly in creating a method useful for risk-averse DMs. The proposal was tested through an experimental design that compared the results achieved by the new method against the expected value in portfolios. The results revealed that high levels of conservatism might prevent wasting resources in failed projects.

Project portfolio selection is addressed here as a multi-objective optimization problem. This work introduces an interval-based method that takes into consideration imperfect knowledge of the contribution of projects to a portfolio, the project requirements, available resources and preference parameters in the model. The multi-objective optimization problem is solved using an evolutionary algorithm that is adapted to handle intervals. To direct the search toward the region of interest of the Pareto frontier, the preferences of the decision maker (DM) are incorporated using an interval-based outranking approach. This allows to address problems with many objective functions; intransitive preferences and incomparability situations can also be handled using this approach. In terms of analyzing robustness, the DM can obtain different solutions according to his/her level of conservatism. The effectiveness of this proposal was tested both on an example from the related literature and another example of a public project portfolio with nine objective functions and large number of applicant projects.