Abstract
Male breast cancer (MBC) patients seem to have inferior survival compared to female (FBC) ones, which is not fully explained by usual prognostic factors. Recurrence analysis could show differences in relapse patterns and/or in patients' approaches that justify these outcomes. Retrospective analysis of MBC patients treated in a cancer center between 1990 and 2014, looking for relapse. For each patient, three matched FBC patients were selected by: diagnosis' year, age (within 5 years), stage and tumors' type (only luminal-like were considered). Differences between cohorts were assessed by chi(2) test and hierarchical clustering was performed to define subgroups according to relapse local. Survival curves were calculated by Kaplan-Meier and compared using log-rank test. Statistical significance was defined as p < 0.05. Groups were balanced according to age, histological grade, stage, expression of hormonal receptors and adjuvant treatments. Median time to recurrence was equivalent, p = 0.72, with the majority of patients presented with distant metastases, p = 0.69, with more lung involvement in male, p =0.003. Male patients were more often proposed to symptomatic treatment (21.1% vs. 4.4%, p = 0.02). Overall and from recurrence survivals were poorer for male, median: 5 years [95% confidence interval (CI): 4.1-5.9 years] and 1 year (95% CI: 0-2.1 years) vs. 10 years (95% CI: 7.8-12.2 years) and 2 years (95% CI: 1.6-2.4 years), p < 0.001 and p = 0.004, respectively, and this tendency remained in the five cluster subgroups, that identified five patterns of relapse, p = 0.003. MBC patients had the worst survival, even after controlling important factors, namely the local of relapse. Palliative systemic treatment had favorable impact in prognosis and its frequently avoidance in male could justify the outcomes differences.

Abstract
Photogrowth is a creativity support tool for the creation of nonphoto-realistic renderings of images. The authors discuss its evolution from a generative art application to an interactive evolutionary art tool and finally into a meta-level interactive art system in which users express their artistic intentions through the design of a fitness function. The authors explore the impact of these changes on the sense of authorship, highlighting the range of imagery that can be produced by the system.

Abstract
Purpose: Male Breast Cancer (MBC) remains a poor understood disease. Prognostic factors are not well established and specific prognostic subgroups are warranted. Patients/methods: Retrospectively revision of 111 cases treated in the same Cancer Center. Blinded-central pathological revision with immunohistochemical (IHQ) analysis for estrogen (ER), progesterone (PR) and androgen (AR) receptors, HER2, ki67 and p53 was done. Cox regression model was used for uni/multivariate survival analysis. Two classifications of Female Breast Cancer (FBC) subgroups (based in ER, PR, HER2, 2000 classification, and in ER, PR, HER2, ki67, 2013 classification) were used to achieve their prognostic value in MBC patients. Hierarchical clustering was performed to define subgroups based on the six-IHQ panel. Results: According to FBC classifications, the majority of tumors were luminal: A (89.2%; 60.0%) and B (7.2%; 35.8%). Triple negative phenotype was infrequent (2.7%; 3.2%) and HER2 enriched, non-luminal, was rare (<= 1% in both). In multivariate analysis the poor prognostic factors were: size >2 cm (HR: 1.8; 95% CI: 1.0-3.4years, p = 0.049), absence of ER (HR: 4.9; 95% CI: 1.7-14.3years, p = 0.004) and presence of distant metastasis (HR: 5.3; 95% CI: 2.2-3.1years, p < 0.001). FBC subtypes were independent prognostic factors (p = 0.009, p = 0.046), but when analyzed only luminal groups, prognosis did not differ regardless the classification used (p > 0.20). Clustering defined different subgroups, that have prognostic value in multivariate analysis (p = 0.005), with better survival in ER/PR+, AR-, HER2- and ki67/p53 low group (median: 11.5 years; 95% CI: 6.2-16.8 years) and worst in PR-group (median: 4.5 years; 95% CI: 1.6 -7.8 years). Conclusion: FBC subtypes do not give the same prognostic information in MBC even in luminal groups. Two subgroups with distinct prognosis were identified in a common six-IHQ panel. Future studies must achieve their real prognostic value in these patients.

Abstract
Industrial Internet and Industrial Internet of Things are emerging concepts that concern the use of Internet technologies on industrial environments. The main objective of such architectural visions is allowing a tight and seamless integration between all the functional units and layers that compose industrial processes, from the lowest levels (e.g. field level devices such as sensors and actuators) to the higher layers, including management, logistics and maintenance. This kind of architecture promises, among other advantages, improving efficiency and flexibility, reduce installation and maintenance costs and reduce unplanned downtime. However, industrial processes often encompass functionalities like closed-loop control of physical processes that are highly critical and have strict timeliness requirements. These requirements are not satisfied by normal Ethernet-based systems. Standards such as IEEE AVB and TSN are addressing this problem, enhancing the real-time properties of Ethernet. However, considering the information presently available, such standards still present some limitations and inefficiencies. This paper reports the extension of HaRTES, an Ethernet-based real-time architecture originally developed for use at the lower layers of industrial scenarios, with MAC Bridge standard functionalities, to make it capable of being integrated on Industrial Internet of Things frameworks. The paper also presents preliminary results obtained with a prototype realization of the extended HaRTES switch.

Abstract
Many online communities and services continuously generate data that can be used by recommender systems. When explicit ratings are not available, rating prediction algorithms are not directly applicable. Instead, data consists of positive-only user-item interactions, and the task is therefore not to predict ratings, but rather to predict good items to recommend - item prediction. One particular challenge of positive-only data is how to interpret absent user-item interactions. These can either be seen as negative or as unknown preferences. In this paper, we propose a recency-based scheme to perform negative preference imputation in an incremental matrix factorization algorithm designed for streaming data. Our results show that this approach substantially improves the accuracy of the baseline method, outperforming both classic and state-of-the-art algorithms.

Abstract