Abstract

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
The present work proposed to study the oxygen uptake slow component (VO2 SC) of breaststroke swimmers at four different intensities of submaximal exercise, via mathematical modeling of a multi-exponential function. The slow component (SC) was also assessed with two different fixed interval methods and the three methods were compared. Twelve male swimmers performed a test comprising four submaximal 300 m bouts at different intensities where all expired gases were collected breath by breath. Multi-exponential modeling showed values above 450 ml.min-1 of the SC in the two last bouts of exercise (those with intensities above the lactate threshold). A significant effect of the method that was used to calculate the VO2 SC was revealed. Higher mean values were observed when using mathematical modeling compared with the fixed interval 3rd min method (F=7.111; p=0.012; eta 2=0.587); furthermore, differences were detected among the two fixed interval methods. No significant relationship was found between the SC determined by any method and the blood lactate measured at each of the four exercise intensities. In addition, no significant association between the SC and peak oxygen uptake was found. It was concluded that in trained breaststroke swimmers, the presence of the VO2 SC may be observed at intensities above that corresponding to the 3.5 mM-1 threshold. Moreover, mathematical modeling of the oxygen uptake on-kinetics tended to show a higher slow component as compared to fixed interval methods.

Abstract
A solution for intuitive robot command and fast robot programming is presented to assemble pins in car doors. Static and dynamic gestures are used to instruct an industrial robot in the execution of the assembly task. An artificial neural network (ANN) was used in the recognition of twelve static gestures and a hidden Markov model (HMM) architecture was used in the recognition of ten dynamic gestures. Results of these two architectures are compared with results displayed by a third architecture based on support vector machine (SVM). Results show recognition rates of 96 % and 94 % for static and dynamic gestures when the ANN and HMM architectures are used, respectively. The SVM architecture presents better results achieving recognition rates of 97 % and 96 % for static and dynamic gestures, respectively.

Abstract
Sensors based on long-period fiber gratings (LPFGs) over coated with metal oxide were fabricated and characterized for refractive index (RI) sensing. Oxidation of Ni, Ti, Al, and Cr was monitored in real time by following the features of the LPFG attenuation band. Themetals were deposited simultaneously on top of Si substrates for further chemical and morphological analysis. Wavelength sensitivities (nm/RIU) of about 10 437 at 1.432, 1150 at 1.400, 20 125 at 1.448, and 875 at 1.420 were achieved for LPFGs coated, with 68 nm of Ni, 60 nm of TiO2, 50 nm of Al2O3, and 62 nm of Cr2O3, respectively. For surrounding RI higher than the cladding RI, the wavelength sensitivities are 1937, 6801, 5762, and 3051 nm/RIU at 1.457 for the Ni, Ti, Al, and Cr oxides, respectively. Working as intensity sensing devices sensitivities up to 167 dB/RIU were measured. Metal oxide coated LPFGs leads to wavelength sensitivity enhancement comparing to bare LPFGs and may be used in systems with RI higher than the fiber cladding, a region where bare LPFGs are insensitive.

Abstract
This study proposes an optimization model to improve the robustness of an existing bus schedule. Robustness represents the ability of schedules to absorb deviations from the timetable and to prevent their propagation through the daily operations. The model developed proposes an optimal assignment of arrival times and distribution of slacks among Time Control Points of a bus line, in order to minimize delays and anticipations from schedule. This required the use of data collected through GPS devices installed in buses, informing the location of buses during their daily operation. The robustness of bus schedules was evaluated through the quantification of delays and anticipations of real observations of bus shifts by comparison with the timetable. The performance measures used to evaluate robustness are the average delay (or anticipation) of buses by comparison with the timetable, and the probability that a passenger that arrives on time according to the timetable will miss the bus or have to wait more than a specified threshold at a Time Control Point. We also compared the improvement of the schedule proposed by the optimization model with the original schedule. The results obtained in a real-world case study, corresponding to a bus line operating in Porto, showed that the model could return an improved schedule for all performance measures considered when compared with the original schedule.