Abstract
We study a variant of the Probabilistic Travelling Salesman Problem arising when retailers crowdsource last-mile deliveries to their own customers, who can refuse or accept in exchange for a reward. A planner must identify which deliveries to offer, knowing that all deliveries need fulfilment, either via crowdsourcing or using the retailer's own vehicle. We formalise the problem and position it in both the literature about crowdsourcing and among routing problems in which not all customers need a visit. We show that to evaluate the objective function of this stochastic problem for even one solution, one needs to solve an exponential number of Travelling Salesman Problems. To address this complexity, we propose Machine Learning and Monte Carlo simulation methods to approximate the objective function, and both a branch-and-bound algorithm and heuristics to reduce the number of evaluations. We show that these approaches work well on small size instances and derive managerial insights on the economic and environmental benefits of crowdsourcing to customers.

Abstract
Cardiac auscultation is the key exam to screen cardiac diseases both in developed and developing countries. A heart sound auscultation procedure can detect the presence of murmurs and point to a diagnosis, thus it is an important first-line assessment and also cost-effective tool. The design automatic recommendation systems based on heart sound auscultation can play an important role in boosting the accuracy and the pervasiveness of screening tools. One such as step, consists in detecting the fundamental heart sound states, a process known as segmentation. A faulty segmentation or a wrong estimation of the heart rate might result in an incapability of heart sound classifiers to detect abnormal waves, such as murmurs. In the process of understanding the impact of a faulty segmentation, several common heart sound segmentation errors are studied in detail, namely those where the heart rate is badly estimated and those where S1/S2 and Systolic/Diastolic states are swapped in comparison with the ground truth state sequence. From the tested algorithms, support vector machine (SVMs) and random forest (RFs) shown to be more sensitive to a wrong estimation of the heart rate (an expected drop of 6% and 8% on the overall performance, respectively) than to a swap in the state sequence of events (an expected drop of 1.9% and 4.6%, respectively).

Abstract
In this paper we describe the implementation of a secure key distribution system based on an ultra-long fiber laser with a bi-directional erbium doped fiber amplifier. The resilience of the system was tested against passive attacks from an eavesdropper, having been observed a similarity in spectrum for both secure configurations of the system.

Abstract
Orion is a NASA spacecraft being developed for human exploration of the Moon and Mars. Crew Dragon is a commercial spacecraft used to transport astronauts to and from the International Space Station (ISS). Both spacecraft are of similar design and both spacecraft perform a water landing following re-entry. This study evaluated the ability of International Institute of Astronautical Sciences (IIAS) Citizen Astronaut Candidates (CAC) to egress a spacecraft mock-up wearing a commercially available intravehicular activity (IVA) spacesuit manufactured by Final Frontier Design (FFD) (Anderson, 2014; Barker and Bellenkes; 1996; Rubio et al., 2004). This suit is similar to those worn by astronauts traveling to the ISS on board Crew Dragon. Mobility assessment revealed that most participants had sufficient ranges of motion to perform egress tasks successfully. In some instances suited participants were unable to perform selected tasks proficiently, but in these instances this often stemmed from difficulty in achieving a stable upright position in the water. Seat ingress and egress evaluation revealed no significant problems with anthropometric accommodation across participants.

Abstract
HARMONI is the first light visible and near-IR integral field spectrograph for the ELT. It covers a large spectral range from 450nm to 2450nm with resolving powers from 3500 to 18000 and spatial sampling from 60mas to 4mas. It can operate in two Adaptive Optics (AO) modes - SCAO (including a High Contrast capability) and LTAO - or with NOAO. The project is preparing for Final Design Reviews. The SCAO system for HARMONI is based on a pyramid wavefront sensor (PWFS) operating in the visible (700 - 1000 nm). Previous implementations on very large telescopes have demonstrated the challenges associated with optimising PWFS performance on-sky, particularly when operated at visible wavelengths. ELT operation will pose further challenges for AO systems, particularly related to the segmentation of the telescope and the control of badly seen 'etal modes'. In this paper we investigate these challenges in the context of the HARMONI SCAO system. We present the results of end-to-end simulations of our baseline approach, using a coupled control basis to avoid the runaway development of petal modes in the control loop. The impact of key parameters are investigated and methods for optical gain compensation and optimisation of the control basis are presented. We discuss recent updates to the control algorithms and demonstrate the possibility of improving performance using a form of super resolution. Finally, we report on the expected performance across a range of conditions.

Abstract