Modelling vessel fleet composition for maintenance operations at offshore wind farms

Chartering a vessel fleet to support maintenance operations at offshore wind farms (OWF's) constitutes one of the major costs of maintaining this type of installations. Literature describes deterministic optimization models based on complete information within scenarios to schedule the maintenance and support decisions on the vessel fleet composition. The operations to be carried out can be classified as preventive and corrective tasks. The first type aims at reducing the likelihood of breakdowns and to prolong the life of turbine components. Corrective tasks are needed to repair breakdowns in turbines when they occur. Our research question is how to generate a vessel fleet composition, where the evaluation is based on scheduling without complete information. Such a model is a bi-level decision problem. On the first (tactical) level, decisions are made on the fleet composition for a certain time horizon. On the second (operational) level, the fleet is used to schedule the operations needed at the OWF, given random events of failures and weather conditions. A scenario based approach allows evaluation by parallel operational scheduling for each scenario..Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish Ministry (TIN2015-66680

Maternidad en parejas constituidas por dos mujeres. Análisis de vivencias desde una perspectiva de género para el Trabajo Social.

La maternidad lésbica ha sido una cuestión silenciada y de la que se cuentan con escasas investigaciones y referentes. Investigar sobre la misma supone analizarla desde una perspectiva interseccional, en la que se tenga en cuenta la multicausalidad de las discriminaciones que sufren estas mujeres. Es por ello por lo que el presente trabajo, une la revisión bibliográfica sobre el tema, junto a experiencias personales de mujeres que han sido madres junto a otra mujer en el seno de una sociedad patriarcal.<br /

Maternidad en parejas constituidas por dos mujeres. Análisis de vivencias desde una perspectiva de género para el Trabajo Social.

La maternidad lésbica ha sido una cuestión silenciada y de la que se cuentan con escasas investigaciones y referentes. Investigar sobre la misma supone analizarla desde una perspectiva interseccional, en la que se tenga en cuenta la multicausalidad de las discriminaciones que sufren estas mujeres. Es por ello por lo que el presente trabajo, une la revisión bibliográfica sobre el tema, junto a experiencias personales de mujeres que han sido madres junto a otra mujer en el seno de una sociedad patriarcal.<br /

Introducing ATR-FTIR Spectroscopy through Analysis of Acetaminophen Drugs: Practical Lessons for Interdisciplinary and Progressive Learning for Undergraduate Students.

Infrared (IR) spectroscopy is a vibrational spectroscopic technique useful in chemical, pharmaceutical, and forensic sciences. It is essential to identify chemicals for reasons spanning from scientific research and academic practices to quality control in companies. However, in some university degrees, graduate students do not get the proficiency to optimize the experimental parameters to obtain the best IR spectra; to correlate the IR spectral bands with the molecular vibrations (chemical elucidation); to have some criteria for any substance identification (especially relevant in quality control to recognize counterfeit); and to apply chemometrics for comparing, visualizing, and classifying the IR spectra. This work presents an experimental laboratory practice for an introductory teaching of the IR instrumental conditions in the identification of substances based on visual spectra comparison and statistical analysis and matching. Then, the selected IR conditions are applied to different commercial drugs, in the solid state or insolution, mostly composed of acetaminophen. Finally, the students apply chemometrics analysis to the IR data. This practice was designed for the training in a chemistry subject for undergraduate students of the chemistry, pharmacy, or forensics degrees, among others related to science, medical, food, or technological sciences.Instituto Universitario de Investigación en Ciencias Policiales (IUICP

An optimized quantum circuit for converting from sign–magnitude to two’s complement

Nowadays, one of the critical issues to implement quantum algorithms is the required number of elementary gates, qubits and delay. Current quantum computers and simulators are mainly prototypes, and there is a lack of computational resources. Therefore, it is necessary to optimize the quantum operations to reduce the necessary number of gates and qubits. This work presents a novel reversible circuit which is able to convert signed binary numbers to two’s complement of N digits in a quantum environment. The depth of the circuit is O(log N). It is based on the fastest out-of-place carry look-ahead addition quantum circuit currently available. This addition circuit has been adapted to make the conversion using the minimum number of gates and qubits, being faster than other adder circuits. A robust metric has been used to measure the quantum cost, delay, ancilla inputs and garbage outputs of the proposed converter. Moreover, it has been compared with others described in the literature

Efficient Reversible Quantum Design of Sign-Magnitude to two's complement converters

Despite the great interest that the scientific community has in quantum computing, the scarcity and high cost of resources prevent to advance in this field. Specifically, qubits are very expensive to build, causing the few available quantum computers are tremendously limited in their number of qubits and delaying their progress. This work presents new reversible circuits that optimize the necessary resources for the conversion of a sign binary number into two's complement of N digits. The benefits of our work are two: on the one hand, the proposed two's complement converters are fault tolerant circuits and also are more efficient in terms of resources (essentially, quantum cost, number of qubits, and T-count) than the described in the literature. On the other hand, valuable information about available converters and, what is more, quantum adders, is summarized in tables for interested researchers. The converters have been measured using robust metrics and have been compared with the state-of-the-art circuits. The code to build them in a real quantum computer is given

Multi-Spectral Imaging for Weed Identification in Herbicides Testing

new methodology to help to improve the efficiency of herbicide assessment is explained. It consists of an automatic tool to quantify the percentage of weeds and plants of interest (sunflowers) that are present in a given area. Images of the crop field taken from Sequoia camera were used. Firstly, the quality of the images of each band is improved. Later, the resulting multispectral images are classified into several classes (soil, sunflower and weed) through a novel algorithm implemented in e-Cognition software. Obtained results of the proposed classifications have been compared with two deep learning-based segmentation methods (U-Net and FPN)

Quantum annealing solution for the unrelated parallel machine scheduling with priorities and delay of task switching on machines

Quantum computing has emerged in recent years as an alternative to classical computing, which could improve the latter in solving some types of problems. One of the quantum programming models, Adiabatic Quantum Computing, has been successfully used to solve problems such as graph partitioning, traffic routing, and task scheduling. In this paper, the focus is on the scheduling of the problem of unrelated parallel machines, where the processing time of tasks on any of the available processing elements is known. Moreover, the proposed model is extended in two relevant aspects for this kind of problem: the existence of some degree of priority of tasks, and the introduction of a delay or penalty every time a processing unit or machine changes the type of task that executes. In all cases, the problem is expressed as Quadratic Unconstrained Binary Optimization, which can be subsequently solved using quantum annealers. The quantum nonlinear programming framework discussed in this work consists of three steps: quadratic approximation of cost function, a binary representation of parameter space, and solving the resulting Quadratic Unconstrained Binary Optimization on the quantum annealer platform D-Wave. One of the novelties in tackling this problem is the compaction of the model bearing in mind the repetitions of each task, to allow solving larger scheduling problems with the quantum resources available in the experimentation platform. An estimation of the number of qubits required in relation to the scheduling parameters is analyzed. The models have been implemented on the D-Wave platform and validated with respect to other traditional methods. Furthermore, the proposed extensions to consider priorities and to switch the delay of tasks have been analyzed using a case study

Finite size effects in active microrheology in colloids

Active microrheology has emerged in recent years as a new technique to probe microscopically the mechanical properties of materials, particularly, viscoelastic ones. In this technique, a colloidal tracer is pulled through the material, and its dynamics is monitored. The interpretation of results usually relies on the Stokes–Einstein approximation, which is valid for a continuous medium in equilibrium. In this work, we have studied with simulations a suspension of quasi-hard colloidal spheres, where a large tracer is pulled by a constant force. The Navier–Stokes equation for a continuous bath predicts important finite size effects, decaying as the inverse box size, which require simulations of different systems to extract the microviscosity of a bulk system. A strategy to optimize the scheduling of the simulation tasks on a multi GPU–CPU cluster based on the adaptation of a genetic algorithm is presented here, and used to study the effect of different conditions on the friction experienced by the tracer (adding the tracer volume to the total system volume, fixing the center of mass of the system, varying the fluid friction coefficient and tracer size). It is observed that the theoretical prediction is not followed, but deviations are observed for large systems in all cases. These are attributed to the finite size of the bath particles, and the intrinsic dynamics of colloidal systems, as shown by the analysis of the velocity profile in the bath

A quantum circuit to generate random numbers within a specific interval

Random numbers are of vital importance in fields such as cyptography and scientific simulations. However, it is well known how difficult it is for classical computers to generate random numbers. This is not the case for quantum computers, which are able to genuinely generate random numbers thanks to the property of superposition and their counter-intuitive concept of measurement. However, despite the simplicity of designing a circuit that generates a random number between 0 and 2^N-1 (being N the number of available qubits), designing a quantum circuit to generate a number within a specific interval is far from trivial. This paper proposes a customizable circuit design to generate random numbers. The circuit is non- hardware dependent, it allows fault-tolerance, and it can be used by current quantum devices. Therefore, it is a valuable tool for all those quantum applications and algorithms that need to work with random numbers. Moreover, a comparator circuit has also been designed as part of this work. This comparator is the best currently available in the literature in terms of qubits, T-count, and T-depth. It is therefore a useful tool for any other circuit or algorithm where this operation is needed