Abstract
This paper presents a stochastic planning algorithm to plan an operation of a multi-microgrid (MMG) in an electricity market considering the integration of stochastic renewable energy resources (RERs). The proposed planning algorithm investigates the optimal operation of resources (i.e., wind turbine (WT), fuel cell (FC), Electrolyzer, photovoltaic (PV) panel, and microturbine (MT)) and energy storage (ES). Various uncertainties (e.g., the power production of WT, the power production of PV, the departure time of electric vehicle (EV), the arrival time of EV, and the traveled distance of EV) are initially forecasted according to the observed data. The prediction error is estimated by fitting the forecasted data and observed data using a Copula method. A Cournot equilibrium and game theory (GT) are applied to model the real-time electricity market and its interactions with the MMG. The proposed algorithm is examined in a sample MMG to determine the operation of uncertain resources and ES. The obtained results are compared with a baseline and the other conventional optimization methods to verify the effectiveness of the proposed algorithm. The obtained results authenticate the importance of modeling the interaction between the MMG and electricity market, especially under the high integration of uncertain RERs, resulting in above 8% cost reduction in the MMG.

Abstract
We present a model for measuring the impact of offloading soft real-time jobs over multi-tier cloud infrastructures. The jobs originate in mobile devices and offloading strategies may choose to execute them locally, in neighbouring devices, in cloudlets or in infrastructure cloud servers. Within this specification, we put forward several such offloading strategies characterised by their differential use of the cloud tiers with the goal of optimizing execution time and/or energy consumption. We implement an instance of the model using Jay, a software framework for adaptive computation offloading in hybrid edge clouds. The framework is modular and allows the model and the offloading strategies to be seamlessly implemented while providing the tools to make informed runtime offloading decisions based on system feedback, namely through a built-in system profiler that gathers runtime information such as workload, energy consumption and available bandwidth for every participating device or server. The results show that offloading strategies sensitive to runtime conditions can effectively and dynamically adjust their offloading decisions to produce significant gains in terms of their target optimization functions, namely, execution time, energy consumption and fulfilment of job deadlines.

Abstract
Reference evapotranspiration (ETo) estimations may be used to improve the efficiency of irrigated agriculture. However, its computation can be complex and could require numerous weather data that are not always available for many locations. Different methods are available to estimate ETo when limited data are available, and the assessment of the most accurate one can be difficult and time consuming. There are some standalone softwares available for computing ETo but none of them allow for the comparison of different methods for the same or different datasets simultaneously. This paper aims to present an application for estimating ETo using several methods that require different levels of data availability, namely FAO-56 Penman-Monteith (PM), the Original and the three modified Hargreaves-Samani (HS and MHS1, MHS2 and MHS3), Trajkovic (TR) and the single temperature procedure (MaxTET). Also, it facilitates the comparison of the accuracy estimation of two selected methods. From an example case, for where the application was used to compute ETo for three different locations, results show that the application can easily and successfully estimate ETo using the proposed methods, allowing for statistical comparison of those estimations. HS proves to be the most accurate method for the studied locations; however, the accuracy of all methods tends to be lower for costal locations than for more continental sites. With this application, users can select the best ETo estimation methods for a specific location and use it for irrigation purposes.

Abstract
Network slicing emerged in 5G networks as a key component to enable the use of multiple services with different performance requirements on top of a shared physical network infrastructure. A major challenge lies on ensuring wireless coverage and enough communications resources to meet the target Quality of Service (QoS) levels demanded by these services, including throughput and delay guarantees. The challenge is exacerbated in temporary events, such as disaster management scenarios and outdoor festivities, where the existing wireless infrastructures may collapse, fail to provide sufficient wireless coverage, or lack the required communications resources. Flying networks, composed of Unmanned Aerial Vehicles (UAVs), emerged as a solution to provide on-demand wireless coverage and communications resources anywhere, anytime. However, existing solutions mostly rely on best-effort networks. The main contribution of this paper is SLICER, an algorithm enabling the placement and allocation of communications resources in slicing-aware flying networks. The evaluation carried out by means of ns-3 simulations shows SLICER can meet the targeted QoS levels, while using the minimum amount of communications resources.

Abstract
The potential of evanescent Mach-Zehnder interferometers, embedded in Eagle2000 substrates, as refractive index sensors was assessed. For that, femtosecond laser direct writing and wet etching were used to fabricate and expose the sensing arm at the surface of the glass substrate, while keeping the reference arm buried. From the analysis of the structures' spectral response, we found that the wavelength shift of the different order peaks increased greatly for refractive indices nearing that of the glass, indicating a greater overlap between the guided mode's evanescent field and the external medium. Therefore, a maximum sensitivity of 10271 nm/RIU was obtained at a refractive index of 1.491. The sensitivity in the refractive index range of water-based solutions was, on the other hand, limited to 446 +/- 39 nm/RIU. Due to the geometry of the device, applications with films deposited at the surface of the substrate and PDMS based microfluidic channels can be explored.

Abstract
A detailed study of turn around point (TAP) long period fiber gratings (LPFGs) with coupling to the asymmetric cladding modes of a standard single-mode fiber (SMF-28e), fabricated by femtosecond (fs) laser direct writing was realized. The entire fabrication process, including the coating with different titanium dioxide (TiO2) film thicknesses of LPFGs and the corrections needed to achieve coated devices operating precisely in the TAP condition with coupling to the asymmetric cladding modes, was addressed. The significant fabrication details are also given, such as inscription periods, shape and localization of the refractive index modifications across the core. The fabrication process described allows the optimization of the LPFGs sensitivity in regards to the surrounding refractive index (SRI). Optimization of the writing parameters to obtain gratings working at the TAP for two different media surrounding the fiber (water and air) was achieved. It was demonstrated that for a grating period of 191.8 mu m, the LP1,12 mode exhibits a TAP at 1442.7 nm in air, and for a period of 192.5 mu m, the same mode exhibits a TAP at 1448.6 nm in water. The LPFGs operating at the TAP in air and water were coated with 10, 20, and 30 nm thin TiO2 film thicknesses and the spectral behavior characterized. The wavelength sensitivity to the surrounding refractive index (SRI) was assessed in the range between 1.3700 to 1.4120, and a maximum sensitivity of similar to 8051.4 nm/RIU was measured for the 192.5 mu m LPFG coated with a 30 nm thick TiO2 film.