A Novel Hybrid Scheme Using Genetic Algorithms and Deep Learning for the Reconstruction of Portuguese Tile Panels

This paper presents a novel scheme, based on a unique combination of genetic algorithms (GAs) and deep learning (DL), for the automatic reconstruction of Portuguese tile panels, a challenging real-world variant of the jigsaw puzzle problem (JPP) with important national heritage implications. Specifically, we introduce an enhanced GA-based puzzle solver, whose integration with a novel DL-based compatibility measure (DLCM) yields state-of-the-art performance, regarding the above application. Current compatibility measures consider typically (the chromatic information of) edge pixels (between adjacent tiles), and help achieve high accuracy for the synthetic JPP variant. However, such measures exhibit rather poor performance when applied to the Portuguese tile panels, which are susceptible to various real-world effects, e.g., monochromatic panels, non-squared tiles, edge degradation, etc. To overcome such difficulties, we have developed a novel DLCM to extract high-level texture/color statistics from the entire tile information. Integrating this measure with our enhanced GA-based puzzle solver, we have demonstrated, for the first time, how to deal most effectively with large-scale real-world problems, such as the Portuguese tile problem. Specifically, we have achieved 82% accuracy for the reconstruction of Portuguese tile panels with unknown piece rotation and puzzle dimension (compared to merely 3.5% average accuracy achieved by the best method known for solving this problem variant). The proposed method outperforms even human experts in several cases, correcting their mistakes in the manual tile assembly

Polymer-stable magnesium nanocomposites prepared by laser ablation for efficient hydrogen storage

Hydrogen is a promising alternative energy carrier that can potentially facilitate the transition from fossil fuels to sources of clean energy because of its prominent advantages such as high energy density (142 MJ per kg), great variety of potential sources (for example water, biomass, organic matter), and low environmental impact (water is the sole combustion product). However, due to its light weight, the efficient storage of hydrogen is still an issue investigated intensely. Various solid media have been considered in that respect among which magnesium hydride stands out as a candidate offering distinct advantages. Recent theoretical work indicates that MgH2 becomes less thermodynamically stable as particle diameter decreases below 2 nm. Our DFT (density functional theory) modeling studies have shown that the smallest enthalpy change, corresponding to 2 unit-cell thickness (1.6 {\AA} Mg/3.0{\AA} MgH2) of the film, is 57.7 kJ/molMg. This enthalpy change is over 10 kJ per molMg smaller than that of the bulk. It is important to note that the range of enthalpy change for systems that are suitable for mobile storage applications is 15 to 24 kJ permolH at 298 K. The important key for the development of air/stable Mg/nanocrystals is the use of PMMA (polymethylmethacrylate) as an encapsulation agent. In our work we use laser ablation, a non-electrochemical method, for producing well dispersed nanoparticles without the presence of any long range aggregation. The observed improved hydrogenation characteristics of the polymer/stable Mg-nanoparticles are associated to the preparation procedure and in any case the polymer laser ablation is a new approach for the production of air/protected and inexpensive Mg/nanoparticles.Comment: Hydrogen Storage, Mg - Nanoparticles, Polymer Matrix Composites, Laser Ablation, to appear in International Journal of Hydrogen Energy, 201

The aquaculture supply chain in the time of covid-19 pandemic: vulnerability, resilience, solutions and priorities at the global scale

The COVID-19 global pandemic has had severe, unpredictable and synchronous impacts on all levels of perishable food supply chains (PFSC), across multiple sectors and spatial scales. Aquaculture plays a vital and rapidly expanding role in food security, in some cases overtaking wild caught fisheries in the production of high-quality animal protein in this PFSC. We performed a rapid global assessment to evaluate the effects of the COVID-19 pandemic and related emerging control measures on the aquaculture supply chain. Socio-economic effects of the pandemic were analysed by surveying the perceptions of stakeholders, who were asked to describe potential supply-side disruption, vulnerabilities and resilience patterns along the production pipeline with four main supply chain components: a) hatchery, b) production/processing, c) distribution/logistics and d) market. We also assessed different farming strategies, comparing land- vs. sea-based systems; extensive vs. intensive methods; and with and without integrated multi-trophic aquaculture, IMTA. In addition to evaluating levels and sources of economic distress, interviewees were asked to identify mitigation solutions adopted at local / internal (i.e., farm-site) scales, and to express their preference on national / external scale mitigation measures among a set of a priori options. Survey responses identified the potential causes of disruption, ripple effects, sources of food insecurity, and socio-economic conflicts. They also pointed to various levels of mitigation strategies. The collated evidence represents a first baseline useful to address future disaster-driven responses, to reinforce the resilience of the sector and to facilitate the design reconstruction plans and mitigation measures, such as financial aid strategies.publishe

The synergistic impacts of anthropogenic stressors and COVID-19 on aquaculture: a current global perspective

The rapid, global spread of COVID-19, and the measures intended to limit or slow its propagation, are having major impacts on diverse sectors of society. Notably, these impacts are occurring in the context of other anthropogenic-driven threats including global climate change. Both anthropogenic stressors and the COVID-19 pandemic represent significant economic challenges to aquaculture systems across the globe, threatening the supply chain of one of the most important sources of animal protein, with potential disproportionate impacts on vulnerable communities. A web survey was conducted in 47 countries in the midst of the COVID-19 pandemic to assess how aquaculture activities have been affected by the pandemic, and to explore how these impacts compare to those from climate change. A positive correlation between the effects of the two categories of drivers was detected, but analysis suggests that the pandemic and the anthropogenic stressors affect different parts of the supply chain. The immediate measurable reported losses varied with aquaculture typology (land vs. marine, and intensive vs. extensive). A comparably lower impact on farmers reporting the use of integrated multitrophic aquaculture (IMTA) methods suggests that IMTA might enhance resilience to multiple stressors by providing different market options under the COVID-19 pandemic. Results emphasize the importance of assessing detrimental effects of COVID-19 under a multiple stressor lens, focusing on areas that have already locally experienced economic loss due to anthropogenic stressors in the last decade. Holistic policies that simultaneously address other ongoing anthropogenic stressors, rather than focusing solely on the acute impacts of COVID-19, are needed to maximize the long-term resilience of the aquaculture sector.publishe

Offshore wind farm layout optimization using particle swarm optimization

This is the author accepted manuscript. The final version is available from Springer via the DOI in this recordThis article explores the application of a wind farm layout optimization framework using a particle swarm optimizer to three benchmark test cases. The developed framework introduces an increased level of detail characterizing the impact that the wind farm layout can have on the levelized cost of energy by modelling the wind farm’s electrical infrastructure, annual energy production, and cost as functions of the wind farm layout. Using this framework, this paper explores the application of a particle swarm optimizer to the wind farm layout optimization problem considering three different levels of wind farm constraint faced by modern wind farm developers. The particle swarm optimizer is found to yield improvements in the layout with respect to the levelized cost of energy for the three benchmark cases when compared to two past studies. This highlights both applicability of the particle swarm optimizer to the problem and the ways in which a wind farm developer could make use of the present framework in the development and design of future wind farms.This work is funded in part by the Energy Technologies Institute (ETI) and RCUK energy program for IDCORE (EP/J500847/1) and supported by EDF Energy R&D UK Centre

Implications of serial measurements of natriuretic peptides in heart failure: insights from BIOSTAT‐CHF

No abstract available

Investigation of ZrFe2-type materials for metal hydride hydrogen compressor systems by substituting Fe with Cr or V

International audienc