Abstract
The Gemini Infra-Red Multi-Object Spectrograph (GIRMOS) is a four-arm, Multi-Object Adaptive Optics (MOAO) IFU spectrograph being built for Gemini (commissioning in 2024). GIRMOS is being planned to interface with the new Gemini-North Adaptive Optics (GNAO) system, and is base lined with a requirement of 50% EE within a 0.100 spaxel at H-band. We present a design and forecast the error budget and performance of GIRMOS-MOAO working behind GNAO. The MOAO system will patrol the 20 field of regard of GNAO, utilizing closed loop GLAO or MCAO for lower order correction. GIRMOS MOAA will perform tomographic reconstruction of the turbulence using the GNAO WFS, and utilize order 16x16 actuator DMs operating in open loop to perform an additional correction from the Pseudo Open Loop (POL) slopes, achieving close to diffraction limited performance from the combined GNAO+MOAO correction. This high performance AO spectrograph will have the broadest impact in the study of the formation and evolution of galaxies, but will also have broad reach in fields such as star and planet formation within our Milky Way and supermassive black holes in nearby galaxies.

Abstract
The beginning of the 21st century brought a new Industrial Revolution - the 4th Industrial Revolution which assumes that each physical object is equipped with an integrated technology that allows its connection with other objects. Therefore, Cyber-Physical Systems (CPSs) are becoming essential elements to be implemented in the companies' workspace in order to improve their production efficiency and flexibility by bringing digitalisation to the production processes. The implementation of these CPSs creates several changes for companies' operations that are expected to have a deep impact in human workers. A lack of studies on the social impact of the use of CPSs has been identified and, through a comprehensive literature review, this work aims at contributing for this discussion by defining a questionnaire about the topic. In the future, this questionnaire is intended to be sent to companies to collect data from their C-level managers about the use of CPSs applied to manufacturing.

Abstract
It is expected that demand response might provide soon ancillary services to the power system. This could be done, for example, by managing the use of Electric Vehicles (EV) batteries, or the production of flexible energy commodities such as hydrogen (H-2), that can be used for fuel cell vehicles (H2EV) or in industrial processes. This paper analyses the impact of a transition to H2EV as an alternative to EV for passengers' cars on a Spanish-like power sector. A simple H-2 demand estimation is developed and provided to CEVESA, an operation and expansion model for the Iberian Power System Electricity Market (MIBEL). For this study, CEVESA was extended to include the investments and operation decisions of H-2 production. Simulations were performed to determine the optimal evolution of the H-2 production capacity and of the electricity generation mix, considering scenarios with different shares of EV and H2EV. The impact of H2EV vs EV mobility is assessed based on the recent Spanish National Plan for Energy and Climate (NECP) as the base case scenario. Results show that, even if H2EV mobility alternative is still more costly than EV, H-2 production could provide a significant flexibility to the system that should also be appraised. Indeed, H2EV mobility could become a feasible and complementary alternative to decarbonize mobility by powering H-2 production with the renewable generation surplus. This, together with the on-going learning process of this technology that will decrease its production costs and increase its efficiency in the coming years, could boost, even more, the development of the H-2 economy.

Abstract
Energy and social welfare management of smart buildings have been influenced by cooling systems. Although the combination of cooling systems in the smart grid has stimulated serious discussions over the last decade, its execution and control with more penetration of renewable energy have not been directly tackled. Hence, the present paper is designed to explore the suitability of implementing a novel controller for a cooling system in smart grid settings and high shares of renewable energies. The controller operates from a local control entity by responding to a set of inside nominated points and outside signals, such as access to renewable energy sources and customer welfare. Not only it reduces the purchasing power from the distribution grid with the help of optimization processes, but also minimizes the overall cost and size of the microgrid. Managing the cooling system simultaneously increases the reliability of the microgrid. As a result, the smart cooling system and renewable energy operate in unity, thus providing separate and mutual benefits for the whole system. The results presented in this study support that the proposed cooling system controller is capable of planning a microgrid system.

Abstract
Can we design efficient algorithms for finding fast algorithms? This question is captured by various circuit minimization problems, and algorithms for the corresponding tasks have significant practical applications. Following the work of Cook and Levin in the early 1970s, a central question is whether minimizing the circuit size of an explicitly given function is NP-complete. While this is known to hold in restricted models such as DNFs, making progress with respect to more expressive classes of circuits has been elusive. In this work, we establish the first NP-hardness result for circuit minimization of total functions in the setting of general (unrestricted) Boolean circuits. More precisely, we show that computing the minimum circuit size of a given multi-output Boolean function f: {0, 1}n ? {0, 1}m is NP-hard under many-one polynomial-time randomized reductions. Our argument builds on a simpler NP-hardness proof for the circuit minimization problem for (single-output) Boolean functions under an extended set of generators. Complementing these results, we investigate the computational hardness of minimizing communication. We establish that several variants of this problem are NP-hard under deterministic reductions. In particular, unless P = NP, no polynomial-time computable function can approximate the deterministic two-party communication complexity of a partial Boolean function up to a polynomial. This has consequences for the class of structural results that one might hope to show about the communication complexity of partial functions. © Rahul Ilango, Bruno Loff, and Igor C. Oliveira; licensed under Creative Commons License CC-BY 35th Computational Complexity Conference (CCC 2020).

Abstract