Abstract
In this paper, deep convolutional neural networks are used to segment heart sounds into their main components. The proposed method is based on the adoption of a novel deep convolutional neural network architecture, which is inspired by similar approaches used for image segmentation. A further post-processing step is applied to the output of the proposed neural network, which induces the output state sequence to be consistent with the natural sequence of states within a heart sound signal (S1, systole, S2, diastole). The proposed approach is tested on heart sound signals longer than 5 seconds from the publicly available PhysioNet dataset, and it is shown to outperform current state-of-the-art segmentation methods by achieving an average sensitivity of 93.4% and an average positive predictive value of 94.5% in detecting S1 and S2 sounds.

Abstract
Regular monitoring is essential to understand coastal morphodynamics and anthropic as well as natural impacts, at different temporal and spatial scales. A stereoscopic video-based terrestrial mobile mapping system, three airborne digital photography systems (mounted on a small manned airplane, a fixed-wing UAV and a multi-rotor UAV, respectively) and airborne LiDAR were compared in terms of: system features, such as range, autonomy, acquisition and operating costs; information supplied, its type and precision; and constraints to system applicability in coastal topographic surveys. Systems differed in resolution, efficiency, and applicability. The terrestrial and UAV-based systems provided the most accurate 3D data, being particularly suited for small-scale, high-resolution surveys. UAVs were easy to deploy, but limited by weather condition, particularly wind speed. Observations from a plane were most efficient and suited for larger areas. Airborne systems had the advantage of being less (UAV) to non-invasive (plane) and thus suitable for the monitoring of sensitive areas (e.g. dunes) and/or areas with difficult access. Systems should be chosen according to the specific survey aims, spatial scale, and local conditions, taking into account their applicability and cost-benefit ratios. They may complement each other to provide a comprehensive picture of coastal morphology and dynamics at different scales.

Abstract

Abstract
We explore the application of phase diversity to calibrate the non common path aberrations (NCPA) in the Gemini Planet Imager (GPI). This is first investigated in simulation in order to characterize the ideal technique parameters with simulated GPI calibration source data. The best working simulation parameters are derived and we establish the algorithm's capability to recover an injected astigmatism. Furthermore, the real data appear to exhibit signs of de-centering between the in and out of focus images that are required by phase diversity; this effect can arise when the diverse images are acquired in closed loop and are close to the non-linear regime of the wavefront sensor. We show in simulation that this effect can inhibit our algorithm, which does not take into account the impact of de-centering between images. To mitigate this effect, we validate the technique of using a single diverse image with our algorithm; this is first demonstrated in simulation and then applied to the real GPI data. Following this approach, we find that we can successfully recover a known astigmatism injection using the real GPI data and subsequently apply an NCPA correction to GPI (in the format of offset reference slopes) to improve the relative Strehl ratio by 5%; we note this NCPA correction application is rudimentary and a more thorough application will be investigated in the near future. Finally, the estimated NCPA in the form of astigmatism and coma agree well with the magnitude of the same modes reported by Poyneer et al. 2016.

Abstract
This paper presents a new concept for an approach to deal with measurements contaminated with gross errors, prior to power system state estimation. Instead of a simple filtering operation, the new procedure develops a screen-and-repair process, going through the phases of detection, identification and correction of multiple gross errors. The method is based on the definition of the coverage of the measurement set by a tiling scheme of 3-overlapping autoencoders, trained with denoising techniques and correntropy, that produce an ensemble-like set of three proposals for each measurement. These proposals are then subject to a process of fusion to produce a vector of proposed/corrected measurements, and two fusion methods are compared, with advantage to the Parzen Windows method. The original measurement vector can then be recognized as clean or diagnosed with possible gross errors, together with corrections that remove these errors. The repaired vectors can then serve as input to classical state estimation procedures, as only a small noise remains. A test case illustrates the effectiveness of the technique, which could deal with four simultaneous gross errors and achieve a result close to full recognition and correction of the errors.

Abstract
This is a case study on leadership, a topic which has been much debated in the literature, as solutions for many diverse situations are still lacking and seem to escape us. The case describes how an entrepreneurial wood veneer factory operates, in the USA, with images included of a number of operations. The manager-owner took us on a guided tour from raw material (logs) to finished product (veneer wood). Waste is minimized at the factory in a very stream-lined operation which has a minimal amount of managers in place. Each worker is responsible for his or her job, done to perfection, as one task rolls on to the next, without stopping. The attitude of the innovative servant-type leadership in place is that "win-win" situations are better for all, and there is enough profit to go around. Servant-leadership-type leaders exist to serve employees and exercise minimal management control. At this firm there are no self-serving managers. Rather, mature and great working relationships are developed. Being greedy would mean that unions would have to be brought in. At this firm that was not necessary, by request of the employees themselves. Hispanic workers are very good and are cherished at this firm, in the heart of the USA. As leadership is dependent on culture, the discussion also includes references to cultural aspects relevant to management. The story is thus of a positive firm with positive leadership and subordinates. We conclude that employees who have emigrated from poorer countries in search of a better lifestyle may indeed make excellent workers, despite what some political leaders have announced in the media. We have found evidence that Spanish-speaking individuals do not only work well under autocratic leadership, as portrayed by the literature. Our study is thus revealing of a new cultural-type involving workers working outside their home countries. Under different leaders, in different countries and environments, certain workers are prepared to go the "extra mile" and behave in a completely different way as to what is expected from them in their home countries. This is surprising and may have important implications for multinational firms worldwide.