Showing papers by "Polytechnic University of Valencia published in 2019"

SemEval-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in Twitter

Abstract: The paper describes the organization of the SemEval 2019 Task 5 about the detection of hate speech against immigrants and women in Spanish and English messages extracted from Twitter. The task is organized in two related classification subtasks: a main binary subtask for detecting the presence of hate speech, and a finer-grained one devoted to identifying further features in hateful contents such as the aggressive attitude and the target harassed, to distinguish if the incitement is against an individual rather than a group. HatEval has been one of the most popular tasks in SemEval-2019 with a total of 108 submitted runs for Subtask A and 70 runs for Subtask B, from a total of 74 different teams. Data provided for the task are described by showing how they have been collected and annotated. Moreover, the paper provides an analysis and discussion about the participant systems and the results they achieved in both subtasks.

Integrated microwave photonics

Abstract: Recent advances in photonic integration have propelled microwave photonic technologies to new heights. The ability to interface hybrid material platforms to enhance light–matter interactions has led to the development of ultra-small and high-bandwidth electro-optic modulators, low-noise frequency synthesizers and chip signal processors with orders-of-magnitude enhanced spectral resolution. On the other hand, the maturity of high-volume semiconductor processing has finally enabled the complete integration of light sources, modulators and detectors in a single microwave photonic processor chip and has ushered the creation of a complex signal processor with multifunctionality and reconfigurability similar to electronic devices. Here, we review these recent advances and discuss the impact of these new frontiers for short- and long-term applications in communications and information processing. We also take a look at the future perspectives at the intersection of integrated microwave photonics and other fields including quantum and neuromorphic photonics. This Review discusses recent advances of microwave photonic technologies and their applications in communications and information processing, as well as their potential implementations in quantum and neuromorphic photonics.

Mixed-Metal MOFs: Unique Opportunities in Metal–Organic Framework (MOF) Functionality and Design

Abstract: Mixed-metal metal-organic frameworks (MM-MOFs) can be considered to be those MOFs having two different metals anywhere in the structure. Herein we summarize the various strategies for the preparation of MM-MOFs and some of their applications in adsorption, gas separation, and catalysis. It is shown that compared to homometallic MOFs, MM-MOFs bring about the opportunity to take advantage of the complexity and the synergism derived from the presence of different metal ions in the structure of MOFs. This is reflected in a superior performance and even stability of MM-MOFs respect to related single-metal MOFs. Emphasis is made on the use of MM-MOFs as catalysts for tandem reactions.

The tomato pan-genome uncovers new genes and a rare allele regulating fruit flavor.

Abstract: Modern tomatoes have narrow genetic diversity limiting their improvement potential. We present a tomato pan-genome constructed using genome sequences of 725 phylogenetically and geographically representative accessions, revealing 4,873 genes absent from the reference genome. Presence/absence variation analyses reveal substantial gene loss and intense negative selection of genes and promoters during tomato domestication and improvement. Lost or negatively selected genes are enriched for important traits, especially disease resistance. We identify a rare allele in the TomLoxC promoter selected against during domestication. Quantitative trait locus mapping and analysis of transgenic plants reveal a role for TomLoxC in apocarotenoid production, which contributes to desirable tomato flavor. In orange-stage fruit, accessions harboring both the rare and common TomLoxC alleles (heterozygotes) have higher TomLoxC expression than those homozygous for either and are resurgent in modern tomatoes. The tomato pan-genome adds depth and completeness to the reference genome, and is useful for future biological discovery and breeding.

Pepper Rootstock and Scion Physiological Responses Under Drought Stress.

Abstract: In vegetables, tolerance to drought can be improved by grafting commercial varieties onto drought tolerant rootstocks. Grafting has emerged as a tool that copes with drought stress. In previous results, the A25 pepper rootstock accession showed good tolerance to drought in fruit production terms compared with non grafted plants and other rootstocks. The aim of this work was to study if short-term exposure to drought grafted plants using A25 as a rootstock would show tolerance to drought now. To fulfill this objective, some physiological processes involved in roots (rootstock) and leaves (scion) of grafted pepper plants were analyzed. Pepper plants not grafted (A), self-grafted (A/A) and grafted onto a tolerant pepper rootstock A25 (A/A25) were grown under severe water stress induced by PEG addition (-0.55 MPa) or under control conditions for 7 days in hydroponic pure solution. According to our results, water stress severity was alleviated by using the A25 rootstock in grafted plants (A/A25), which indicated that mechanisms stimulated by roots are essential to withstand stress. A/A25 had a bigger root biomass compared with plants A and A/A that resulted in better water absorption, water retention capacity and a sustained CO2 assimilation rate. Consequently, plants A/A25 had a better carbon balance, supported by greater nitrate reductase activity located mainly in leaves. In the non grafted and self-grafted plants, the photosynthesis rate lowered due to stomatal closure, which limited transpiration. Consequently, part of NO3- uptake was reduced in roots. This condition limited water uptake and CO2 fixation in plants A and A/A under drought stress, and accelerated oxidative damage by producing reactive oxygen species (ROS) and H2O2, which were higher highest in their leaves, indicating great sensitivity to drought stress and induced membrane lipid peroxidation. However, drought deleterious effects were slightly marked in plants A than in A/A. To conclude, the A25 rootstock protects the scion against oxidative stress, which is provoked by drought, and shows better C and N balances that enabled the biomass to be maintained under water stress for short-term exposure, with higher yields in the field.

A review of mobile robots: Concepts, methods, theoretical framework, and applications

Abstract: Humanoid robots, unmanned rovers, entertainment pets, drones, and so on are great examples of mobile robots. They can be distinguished from other robots by their ability to move autonomously, with ...

Large Pockels effect in micro- and nanostructured barium titanate integrated on silicon

Abstract: The electro-optical Pockels effect is an essential nonlinear effect used in many applications. The ultrafast modulation of the refractive index is, for example, crucial to optical modulators in photonic circuits. Silicon has emerged as a platform for integrating such compact circuits, but a strong Pockels effect is not available on silicon platforms. Here, we demonstrate a large electro-optical response in silicon photonic devices using barium titanate. We verify the Pockels effect to be the physical origin of the response, with r42 = 923 pm V−1, by confirming key signatures of the Pockels effect in ferroelectrics: the electro-optic response exhibits a crystalline anisotropy, remains strong at high frequencies, and shows hysteresis on changing the electric field. We prove that the Pockels effect remains strong even in nanoscale devices, and show as a practical example data modulation up to 50 Gbit s−1. We foresee that our work will enable novel device concepts with an application area largely extending beyond communication technologies. Electro-optic modulators based on epitaxial barium titanate (BTO) integrated on silicon exhibit speeds up to 50 Gbit s–1 while the Pockels coefficient of the BTO film is found to be approaching the bulk value.

New trends in tailoring active sites in zeolite-based catalysts.

Abstract: This review addresses the recent developments and trends in tailoring the nature and local properties of active sites in zeolite-based catalysts, with a special focus on novel extra-large pore, layered (2D), nanocrystalline, and hierarchical (mesoporous) zeolites with enhanced pore accessibility. In the first part of the review, we discuss the latest achievements in the bottom-up (direct synthesis) and top-down (post-synthesis) approaches for isomorphous substitution in zeolites enabling control over the type (Bronsted, Lewis, or both), amount, strength, and location of acid sites. The benefits in catalysis provided by such zeolites with tuned acidity and improved accessibility are shown for different acid-catalyzed reactions involving bulky molecules, as in the synthesis of fine chemicals and biomass transformations. The incorporation of metal species of different sizes (increasing from single atoms to clusters and to nanoparticles) in zeolites allows expanding the set of reactions catalyzed by these materials. The main preparation strategies for designing metal–zeolite catalysts, especially those offering control over the size of the metal species, and their catalytic behaviour in industrially relevant and emerging sustainable catalytic processes are dealt with in the second part of the review. Particular attention is paid to the stabilization of size-controlled small metal clusters and nanoparticles through their encapsulation in the voids of zeolite frameworks as well as to the dynamic behaviour of the metal species under reactive environments with important implications in catalysis. The need for using advanced operando spectroscopic and imaging tools to unveil the precise nature and functioning of the active sites in working zeolites is emphasized. The information gathered in this review is expected to provide guidance for developing more efficient zeolite-based catalysts for existing and new applications.

Regioselective generation and reactivity control of subnanometric platinum clusters in zeolites for high-temperature catalysis

Abstract: Subnanometric metal species (single atoms and clusters) have been demonstrated to be unique compared with their nanoparticulate counterparts. However, the poor stabilization of subnanometric metal species towards sintering at high temperature (>500 °C) under oxidative or reductive reaction conditions limits their catalytic application. Zeolites can serve as an ideal support to stabilize subnanometric metal catalysts, but it is challenging to localize subnanometric metal species on specific sites and modulate their reactivity. We have achieved a very high preference for localization of highly stable subnanometric Pt and PtSn clusters in the sinusoidal channels of purely siliceous MFI zeolite, as revealed by atomically resolved electron microscopy combining high-angle annular dark-field and integrated differential phase contrast imaging techniques. These catalysts show very high stability, selectivity and activity for the industrially important dehydrogenation of propane to form propylene. This stabilization strategy could be extended to other crystalline porous materials. Subnanometre Pt clusters show high catalytic activity, but can sinter and so reduce reactivity. Here, authors localize Pt clusters in one zeolite channel, preventing sintering and allowing highly stable and selective catalytic propane dehydrogenation.

Solar Energy on Demand: A Review on High Temperature Thermochemical Heat Storage Systems and Materials.

Abstract: Among renewable energies, wind and solar are inherently intermittent and therefore both require efficient energy storage systems to facilitate a round-the-clock electricity production at a global scale. In this context, concentrated solar power (CSP) stands out among other sustainable technologies because it offers the interesting possibility of storing energy collected from the sun as heat by sensible, latent, or thermochemical means. Accordingly, continuous electricity generation in the power block is possible even during off-sun periods, providing CSP plants with a remarkable dispatchability. Sensible heat storage has been already incorporated to commercial CSP plants. However, because of its potentially higher energy storage density, thermochemical heat storage (TCS) systems emerge as an attractive alternative for the design of next-generation power plants, which are expected to operate at higher temperatures. Through these systems, thermal energy is used to drive endothermic chemical reactions, which can subsequently release the stored energy when needed through a reversible exothermic step. This review analyzes the status of this prominent energy storage technology, its major challenges, and future perspectives, covering in detail the numerous strategies proposed for the improvement of materials and thermochemical reactors. Thermodynamic calculations allow selecting high energy density systems, but experimental findings indicate that sufficiently rapid kinetics and long-term stability trough continuous cycles of chemical transformation are also necessary for practical implementation. In addition, selecting easy-to-handle materials with reduced cost and limited toxicity is crucial for large-scale deployment of this technology. In this work, the possible utilization of materials as diverse as metal hydrides, hydroxides, or carbonates for thermochemical storage is discussed. Furthermore, special attention is paid to the development of redox metal oxides, such as Co3O4/CoO, Mn2O3/Mn3O4, and perovskites of different compositions, as an auspicious new class of TCS materials due to the advantage of working with atmospheric air as reactant, avoiding the need of gas storage tanks. Current knowledge about the structural, morphological, and chemical modifications of these solids, either caused during redox transformations or induced wittingly as a way to improve their properties, is revised in detail. In addition, the design of new reactor concepts proposed for the most efficient use of TCS in concentrated solar facilities is also critically considered. Finally, strategies for the harmonic integration of these units in functioning solar power plants as well as the economic aspects are also briefly assessed.

2D Metal–Organic Frameworks as Multifunctional Materials in Heterogeneous Catalysis and Electro/Photocatalysis

Abstract: Metal-organic frameworks (MOFs) are composed of particles with 3D geometry and are currently among the most widely studied heterogeneous catalysts. To further increase their activity, one of the recent trends is to develop related 2D materials with a high aspect ratio derived from a large lateral size and a small thickness. Here, the use of these 2D MOFs as catalysts, electrocatalysts, and photocatalysts is summarized, illustrating the advantages of these 2D materials compared to analogous 3D MOFs. The state of the art is summarized in tables and, when possible, pertinent turnover number (TON) and frequency (TOF) values. This enhanced activity of 2D MOFs derives from the accessibility of the active sites, the presence of a higher density of defects, and exchangeable coordination positions around the MOFs, as well as from their ability to form thin films on electrodes or surfaces. The importance of providing convincing evidence of the stability of 2D MOFs under reaction conditions and general characterization data of the used 2D material after catalysis is highlighted. In the last part, views regarding challenges in the field and new developments that can be expected are presented.

Compositional response of Amazon forests to climate change

Abstract: Most of the planet's diversity is concentrated in the tropics, which includes many regions undergoing rapid climate change. Yet, while climate‐induced biodiversity changes are widely documented elsewhere, few studies have addressed this issue for lowland tropical ecosystems. Here we investigate whether the floristic and functional composition of intact lowland Amazonian forests have been changing by evaluating records from 106 long‐term inventory plots spanning 30 years. We analyse three traits that have been hypothesized to respond to different environmental drivers (increase in moisture stress and atmospheric CO2 concentrations): maximum tree size, biogeographic water‐deficit affiliation and wood density. Tree communities have become increasingly dominated by large‐statured taxa, but to date there has been no detectable change in mean wood density or water deficit affiliation at the community level, despite most forest plots having experienced an intensification of the dry season. However, among newly recruited trees, dry‐affiliated genera have become more abundant, while the mortality of wet‐affiliated genera has increased in those plots where the dry season has intensified most. Thus, a slow shift to a more dry‐affiliated Amazonia is underway, with changes in compositional dynamics (recruits and mortality) consistent with climate‐change drivers, but yet to significantly impact whole‐community composition. The Amazon observational record suggests that the increase in atmospheric CO2 is driving a shift within tree communities to large‐statured species and that climate changes to date will impact forest composition, but long generation times of tropical trees mean that biodiversity change is lagging behind climate change.

Iterated Greedy methods for the distributed permutation flowshop scheduling problem

Abstract: Large manufacturing firms operate more than one production center. As a result, in relation to scheduling problems, which factory manufactures which product is an important consideration. In this paper we study an extension of the well known permutation flowshop scheduling problem in which there is a set of identical factories, each one with a flowshop structure. The objective is to minimize the maximum completion time or makespan among all factories. The resulting problem is known as the distributed permutation flowshop and has attracted considerable interest over the last few years. Contrary to the recent trend in the scheduling literature, where complex nature-inspired or metaphor-based methods are often proposed, we present simple Iterated Greedy algorithms that have performed well in related problems. Improved initialization, construction and destruction procedures, along with a local search with a strong intensification are proposed. The result is a very effective algorithm with little problem-specific knowledge that is shown to provide demonstrably better solutions in a comprehensive and thorough computational and statistical campaign.

Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples

Abstract: OBJECTIVE: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. METHODS: Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). RESULTS: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. CONCLUSIONS: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

Volatile Compounds in Citrus Essential Oils: A Comprehensive Review

Abstract: The essential oil fraction obtained from the rind of Citrus spp. is rich in chemical compounds of interest for the food and perfume industries, and therefore has been extensively studied during the last decades. In this manuscript, we provide a comprehensive review of the volatile composition of this oil fraction and rind extracts for the 10 most studied Citrus species: C. sinensis (sweet orange), C. reticulata (mandarin), C. paradisi (grapefruit), C. grandis (pummelo), C. limon (lemon), C. medica (citron), C. aurantifolia (lime), C. aurantium (bitter orange), C. bergamia (bergamot orange), and C. junos (yuzu). Forty-nine volatile organic compounds have been reported in all 10 species, most of them terpenoid (90%), although about half of the volatile compounds identified in Citrus peel are non-terpenoid. Over 400 volatiles of different chemical nature have been exclusively described in only one of these species and some of them could be useful as species biomarkers. A hierarchical cluster analysis based on volatile composition arranges these Citrus species in three clusters which essentially mirrors those obtained with genetic information. The first cluster is comprised by C. reticulata, C. grandis, C. sinensis, C. paradisi and C. aurantium, and is mainly characterized by the presence of a larger abundance of non-terpenoid ester and aldehyde compounds than in the other species reviewed. The second cluster is comprised by C. junos, C. medica, C. aurantifolia, and C. bergamia, and is characterized by the prevalence of mono- and sesquiterpene hydrocarbons. Finally, C. limon shows a particular volatile profile with some sulfur monoterpenoids and non-terpenoid esters and aldehydes as part of its main differential peculiarities. A systematic description of the rind volatile composition in each of the species is provided together with a general comparison with those in leaves and blossoms. Additionally, the most widely used techniques for the extraction and analysis of volatile Citrus compounds are also described.

Challenges and Opportunities for Bio-oil Refining: A Review

Abstract: Bio-oil derived from fast pyrolysis of lignocellulosic materials is among the most complex and inexpensive raw oils that can be produced today. Although commercial or demonstration scale fast pyrol...

CNNs for automatic glaucoma assessment using fundus images: an extensive validation

Abstract: Most current algorithms for automatic glaucoma assessment using fundus images rely on handcrafted features based on segmentation, which are affected by the performance of the chosen segmentation method and the extracted features. Among other characteristics, convolutional neural networks (CNNs) are known because of their ability to learn highly discriminative features from raw pixel intensities. In this paper, we employed five different ImageNet-trained models (VGG16, VGG19, InceptionV3, ResNet50 and Xception) for automatic glaucoma assessment using fundus images. Results from an extensive validation using cross-validation and cross-testing strategies were compared with previous works in the literature. Using five public databases (1707 images), an average AUC of 0.9605 with a 95% confidence interval of 95.92–97.07%, an average specificity of 0.8580 and an average sensitivity of 0.9346 were obtained after using the Xception architecture, significantly improving the performance of other state-of-the-art works. Moreover, a new clinical database, ACRIMA, has been made publicly available, containing 705 labelled images. It is composed of 396 glaucomatous images and 309 normal images, which means, the largest public database for glaucoma diagnosis. The high specificity and sensitivity obtained from the proposed approach are supported by an extensive validation using not only the cross-validation strategy but also the cross-testing validation on, to the best of the authors’ knowledge, all publicly available glaucoma-labelled databases. These results suggest that using ImageNet-trained models is a robust alternative for automatic glaucoma screening system. All images, CNN weights and software used to fine-tune and test the five CNNs are publicly available, which could be used as a testbed for further comparisons.

Smart destinations and the evolution of ICTs: a new scenario for destination management?

Abstract: The impact of information and communication technologies (ICTs) on tourism and their foreseeable future evolution seem to be shaping a new scenario for destination management. This new context has ...

Toward Commercial Polymer Fiber Bragg Grating Sensors: Review and Applications

Abstract: Interest in polymer optical fiber Bragg gratings (POFBGs) arises from the different material properties and sensing modalities brought by polymers relative to silica. Polymer fibers typically offer twice the sensitivity to temperature of conventional silica fiber and increased sensitivity to strain overall. In addition, polymer fibers have higher elastic limits and as a result a larger range of operation for physical constraints. While some polymers are effectively humidity insensitive, others present inherent humidity sensitivity. Their organic properties also allow a variety of chemical processes to create (bio)chemical sensors, with the consequences of fiber breakage in situ being less hazardous than silica. These attributes have led to the use of POFBGs for applications that remain complex using silica fibers. This review paper covers the progress toward commercialization and the increasing number of specific applications.

Determination of the Evolution of Heterogeneous Single Metal Atoms and Nanoclusters under Reaction Conditions: Which Are the Working Catalytic Sites?

Abstract: Identification of active sites in heterogeneous metal catalysts is critical for understanding the reaction mechanism at the molecular level and for designing more efficient catalysts. Because of their structural flexibility, subnanometric metal catalysts, including single atoms and clusters with a few atoms, can exhibit dynamic structural evolution when interacting with substrate molecules, making it difficult to determine the catalytically active sites. In this work, Pt catalysts containing selected types of Pt entities (from single atoms to clusters and nanoparticles) have been prepared, and their evolution has been followed, while they were reacting in a variety of heterogeneous catalytic reactions, including selective hydrogenation reactions, CO oxidation, dehydrogenation of propane, and photocatalytic H2 evolution reaction. By in situ X-ray absorption spectroscopy, in situ IR spectroscopy, and high-resolution electron microscopy techniques, we will show that some characterization techniques carried out in an inadequate way can introduce confusion on the interpretation of coordination environment of highly dispersed Pt species. Finally, the combination of catalytic reactivity and in situ characterization techniques shows that, depending on the catalyst-reactant interaction and metal-support interaction, singly dispersed metal atoms can rapidly evolve into metal clusters or nanoparticles, being the working active sites for those abovementioned heterogeneous reactions.

Straw mulch as a sustainable solution to decrease runoff and erosion in glyphosate-treated clementine plantations in Eastern Spain. An assessment using rainfall simulation experiments

Abstract: In many Mediterranean areas, citrus orchards exhibit high soil loss rates because of the expansion of drip irrigation that allows cultivation on sloping terrain and the widespread use of glyphosate. To mitigate these non-sustainable soil losses, straw mulch could be applied as an efficient solution but this has been poorly studied. Therefore, the main goal of this paper was to assess the use of straw mulch as a tool to reduce soil losses in clementine plantations, which can be considered representative of a typical Mediterranean citrus orchard. A total of 40 rainfall simulation experiments were carried out on 20 pairs of neighbouring bare and mulched plots. Each experiment involved applying 38.8 mm of rain at a constant rate over 1 h to a circular plot of 0.28 m2 circular plots. The results showed that a cover of 50% of straw (60 g m−2) was able to delay the time to ponding from 32 to 52 s and the time to runoff initiation from 57 to 129 s. Also, the mulching reduced the runoff coefficient from 65.6 to 50.5%. The effect on sediment transport was even more pronounced, as the straw mulch reduced the sediment concentration from 16.7 g l−1 to 3.6 g l−1 and the soil erosion rates from 439 g to 73 g. Our results indicated that mulching can be used as a useful management practice to control soil erosion rates due to the immediate effect on high soil detachment rate and runoff initiation reduction in conventional clementine orchards on sloping land, by slowing down runoff initiation and by reducing runoff generation and, especially, sediment losses. We indirectly concluded that straw mulch is also a sustainable solution in glyphosate-treated citrus plantations.

Mixed proton and electron conducting double perovskite anodes for stable and efficient tubular proton ceramic electrolysers

Abstract: Hydrogen production from water electrolysis is a key enabling energy storage technology for the large-scale deployment of intermittent renewable energy sources. Proton ceramic electrolysers (PCEs) can produce dry pressurized hydrogen directly from steam, avoiding major parts of cost-driving downstream separation and compression. However, the development of PCEs has suffered from limited electrical efficiency due to electronic leakage and poor electrode kinetics. Here, we present the first fully operational BaZrO3-based tubular PCE, with 10 cm2 active area and a hydrogen production rate above 15 Nml min−1. The novel steam anode Ba1−xGd0.8La0.2+xCo2O6−δ exhibits mixed p-type electronic and protonic conduction and low activation energy for water splitting, enabling total polarization resistances below 1 Ω cm2 at 600 °C and Faradaic efficiencies close to 100% at high steam pressures. These tubular PCEs are mechanically robust, tolerate high pressures, allow improved process integration and offer scale-up modularity. Proton ceramic electrolysers can produce hydrogen directly from steam, but their development has suffered from limited electrical efficiency. A fully operational and stable BaZrO3-based tubular electrolyser with high hydrogen production rate is now reported.

Multi-objective optimization for energy-efficient flexible job shop scheduling problem with transportation constraints

Abstract: Manufacturing enterprises nowadays face huge environmental challenges because of energy consumption and associated environmental impacts. One of the effective strategies to reduce energy consumption is by employing intelligent scheduling techniques. Production scheduling can have significant impact on energy saving in manufacturing system from the operation management point of view. Resource flexibility and complex constraints in flexible manufacturing system make production scheduling a complicated nonlinear programming problem. To this end, a multi-objective optimization model with the objective of minimizing energy consumption and makespan is formulated for a flexible job shop scheduling problem with transportation constraints. Then, an enhanced genetic algorithm is developed to solve the problem. Finally, comprehensive experiments are carried out to evaluate the performance of the proposed model and algorithm. The experimental results revealed that the proposed model and algorithm can solve the problem effectively and efficiently. This may provide a basis for the decision makers to consider energy-efficient scheduling in flexible manufacturing system.

A Time-Driven Data Placement Strategy for a Scientific Workflow Combining Edge Computing and Cloud Computing

Abstract: Compared to traditional distributed computing environments such as grids, cloud computing provides a more cost-effective way to deploy scientific workflows. Each task of a scientific workflow requires several large datasets that are located in different datacenters, resulting in serious data transmission delays. Edge computing reduces the data transmission delays and supports the fixed storing manner for scientific workflow private datasets, but there is a bottleneck in its storage capacity. It is a challenge to combine the advantages of both edge computing and cloud computing to rationalize the data placement of scientific workflow, and optimize the data transmission time across different datacenters. In this study, a self-adaptive discrete particle swarm optimization algorithm with genetic algorithm operators (GA-DPSO) was proposed to optimize the data transmission time when placing data for a scientific workflow. This approach considered the characteristics of data placement combining edge computing and cloud computing. In addition, it considered the factors impacting transmission delay, such as the bandwidth between datacenters, the number of edge datacenters, and the storage capacity of edge datacenters. The crossover and mutation operators of the genetic algorithm were adopted to avoid the premature convergence of traditional particle swarm optimization algorithm, which enhanced the diversity of population evolution and effectively reduced the data transmission time. The experimental results show that the data placement strategy based on GA-DPSO can effectively reduce the data transmission time during workflow execution combining edge computing and cloud computing.

A Machine Learning Approach to Zeolite Synthesis Enabled by Automatic Literature Data Extraction.

Abstract: Zeolites are porous, aluminosilicate materials with many industrial and “green” applications. Despite their industrial relevance, many aspects of zeolite synthesis remain poorly understood requiring costly trial and error synthesis. In this paper, we create natural language processing techniques and text markup parsing tools to automatically extract synthesis information and trends from zeolite journal articles. We further engineer a data set of germanium-containing zeolites to test the accuracy of the extracted data and to discover potential opportunities for zeolites containing germanium. We also create a regression model for a zeolite’s framework density from the synthesis conditions. This model has a cross-validated root mean squared error of 0.98 T/1000 A3, and many of the model decision boundaries correspond to known synthesis heuristics in germanium-containing zeolites. We propose that this automatic data extraction can be applied to many different problems in zeolite synthesis and enable novel zeo...

Retinal Image Synthesis and Semi-Supervised Learning for Glaucoma Assessment

Abstract: Recent works show that generative adversarial networks (GANs) can be successfully applied to image synthesis and semi-supervised learning, where, given a small labeled database and a large unlabeled database, the goal is to train a powerful classifier. In this paper, we trained a retinal image synthesizer and a semi-supervised learning method for automatic glaucoma assessment using an adversarial model on a small glaucoma-labeled database and a large unlabeled database. Various studies have shown that glaucoma can be monitored by analyzing the optic disc and its surroundings, and for that reason, the images used in this paper were automatically cropped around the optic disc. The novelty of this paper is to propose a new retinal image synthesizer and a semi-supervised learning method for glaucoma assessment based on the deep convolutional GANs. In addition, and to the best of our knowledge, this system is trained on an unprecedented number of publicly available images (86926 images). This system, hence, is not only able to generate images synthetically but to provide labels automatically. Synthetic images were qualitatively evaluated using t-SNE plots of features associated with the images and their anatomical consistency was estimated by measuring the proportion of pixels corresponding to the anatomical structures around the optic disc. The resulting image synthesizer is able to generate realistic (cropped) retinal images, and subsequently, the glaucoma classifier is able to classify them into glaucomatous and normal with high accuracy (AUC = 0.9017). The obtained retinal image synthesizer and the glaucoma classifier could then be used to generate an unlimited number of cropped retinal images with glaucoma labels.

Cucurbit Genomics Database (CuGenDB): a central portal for comparative and functional genomics of cucurbit crops.

Abstract: The Cucurbitaceae family (cucurbit) includes several economically important crops, such as melon, cucumber, watermelon, pumpkin, squash and gourds. During the past several years, genomic and genetic data have been rapidly accumulated for cucurbits. To store, mine, analyze, integrate and disseminate these large-scale datasets and to provide a central portal for the cucurbit research and breeding community, we have developed the Cucurbit Genomics Database (CuGenDB; http://cucurbitgenomics.org) using the Tripal toolkit. The database currently contains all available genome and expressed sequence tag (EST) sequences, genetic maps, and transcriptome profiles for cucurbit species, as well as sequence annotations, biochemical pathways and comparative genomic analysis results such as synteny blocks and homologous gene pairs between different cucurbit species. A set of analysis and visualization tools and user-friendly query interfaces have been implemented in the database to facilitate the usage of these large-scale data by the community. In particular, two new tools have been developed in the database, a 'SyntenyViewer' to view genome synteny between different cucurbit species and an 'RNA-Seq' module to analyze and visualize gene expression profiles. Both tools have been packed as Tripal extension modules that can be adopted in other genomics databases developed using the Tripal system.

Monitoring strategies for quality control of agricultural products using visible and near-infrared spectroscopy: A review

Abstract: This work was partially funded by INIA and FEDER funds through research project RTA2015-00078-00-00.Victoria Cortes Lopez thanks the Spanish Ministry of Education, Culture and Sports for the FPU grant (FPU13/04202).