Abstract
We are assisting the rise of online coding environments as a strategy to promote youth tech employment. With the growing importance of the technology sector, these type of technical training programs give learners emergent tech skills with a big impact and relevance to the current professional market needs. In this realm, MOOCs (massive open online courses) and online coding bootcamps are two increasingly popular options for learners to improve their code development skills and find work within a relatively short amount of time. Among all the features available on these environments, one stands out, which is the code generation. This chapter aims to detail and compare the most popular solutions for both learning contexts based on several criteria such as impact and maturity, user groups, and tools and features. In the features field, the authors highlight the code generation feature as an efficient way to enhance exercise resolution.

Abstract
Counters are an important abstraction in distributed computing, and play a central role in large scale geo-replicated systems, counting events such as web page impressions or social network likes. Classic distributed counters, strongly consistent via linearisability or sequential consistency, cannot be made both available and partition-tolerant, due to the CAP Theorem, being unsuitable to large scale scenarios. This paper defines Eventually Consistent Distributed Counters (ECDCs) and presents an implementation of the concept, Handoff Counters, that is scalable and works over unreliable networks. By giving up the total operation ordering in classic distributed counters, ECDC implementations can be made AP in the CAP design space, while retaining the essence of counting. Handoff Counters are the first Conflict-free Replicated Data Type (CRDT) based mechanism that overcomes the identity explosion problem in naive CRDTs, such as G-Counters (where state size is linear in the number of independent actors that ever incremented the counter), by managing identities towards avoiding global propagation and garbage collecting temporary entries. The approach used in Handoff Counters is not restricted to counters, being more generally applicable to other data types with associative and commutative operations.

Abstract
Increasing penetration of variable nature wind energy sources (WES) due to environmental issues, impose several technical challenges to power system operation as it is difficult to predict its output power because of wind intermittency. Power generation based on gas turbine with fast starting fitness and high ramping could better deal with inherent uncertainties comparing to other power generation sources. Considering natural gas network constraints impacts flexibility and participation of gas-fueled generation units on reserve and energy markets. Hence, the use of flexible energy storage system can reduce renewable sources alternation and the gas network limitation effects on power system operation cost. This paper proposes a two-stage stochastic network-constrained unit commitment based market clearing model for energy and reserve products in coordinated power and gas networks with the integration of compressed air energy storage (CAES) and WES. A six-bus electric system with a six-node gas system and IEEE reliability test system (RTS) 24-bus electric system with a ten-node gas network are considered to perform numerical tests and demonstrate the performance of the proposed model. The effect of including the constraints of the gas system on the power system operation cost in day-ahead co-optimization of energy and reserve products is evaluated using numerical studies. Also, including CAES reduces the power system operation cost, load shedding and wind spillage. Crown Copyright

Abstract
A reflective fiber optic sensor based on a Fabry-Perot cavity made by splicing two sections of multimode fiber is demonstrated to measure the needle curvature. The sensing structure was incorporated into a medical needle and characterized for curvature and temperature measurements. The maximum sensitivity of -0.152dB/m(-1) was obtained to the curvature measurements, with a resolution of 0.089m(-1). When subjected to temperature, the sensing head presented a low temperature sensitivity, which resulted in a small cross-sensitivity.

Abstract
Safety-critical cooperative vehicle applications such as platooning, require extensive testing, however, the complexity and cost involved in this process, increasingly demands for realistic simulation tools to ease the validation of such technologies, helping to bridge the gap between development and real-word deployment. In this paper we propose a realistic co-simulation framework for cooperative vehicles, that integrates Gazebo, an advanced robotics simulator, with the OMNeT++ network simulator, over the Robot Operating System (ROS) framework, supporting the simulation of advanced cooperative applications such as platooning, in realistic scenarios.

Abstract
Wiki-based crowdsourced repositories have increasingly become an important source of information for users in multiple domains. However, as the amount of wiki-based data increases, so does the information overloading for users. Wikis, and in general crowdsourcing platforms, raise trustability questions since they do not generally store user background data, making the recommendation of pages particularly hard to rely on. In this context, this work explores scalable multi-criteria profiling using side information to model the publishers and pages of wiki-based crowdsourced platforms. Based on streams of publisher-page-review triads, we have modelled publishers and pages in terms of quality and popularity using different criteria and user-page-view events collected via a wiki platform. Our modelling approach classifies statistically, both page-review (quality) and pageview (popularity) events, attributing an appropriate rating. The quality-related information is then merged employing Multiple Linear Regression as well as a weighted average. Based on the quality and popularity, the resulting page profiles are then used to address the problem of recommending the most interesting wiki pages per destination to viewers. This paper also explores the parallelisation of profiling and recommendation algorithms using wiki-based crowdsourced distributed data repositories as data streams via incremental updating. The proposed method has been successfully evaluated using Wikivoyage, a tourism crowdsourced wiki-based repository.