Vortex-line liquid phases: Longitudinal superconductivity in the lattice London model

We study the vortex-line lattice and liquid phases of a clean type-II superconductor by means of Monte Carlo simulations of the lattice London model. Motivated by a recent controversy regarding the presence, within this model, of a vortex-liquid regime with longitudinal superconducting coherence over long length scales, we directly compare two different ways to calculate the longitudinal coherence. For an isotropic superconductor, we interpret our results in terms of a temperature regime within the liquid phase in which longitudinal superconducting coherence extends over length scales larger than the system thickness studied. We note that this regime disappears in the moderately anisotropic case due to a proliferation, close to the flux-line lattice melting temperature, of vortex loops between the layers.Comment: 8 pages, Revtex, with eps figures. To appear in Phys. Rev.

Uncertainty-aware Multi-modal Learning via Cross-modal Random Network Prediction

Multi-modal learning focuses on training models by equally combining multiple input data modalities during the prediction process. However, this equal combination can be detrimental to the prediction accuracy because different modalities are usually accompanied by varying levels of uncertainty. Using such uncertainty to combine modalities has been studied by a couple of approaches, but with limited success because these approaches are either designed to deal with specific classification or segmentation problems and cannot be easily translated into other tasks, or suffer from numerical instabilities. In this paper, we propose a new Uncertainty-aware Multi-modal Learner that estimates uncertainty by measuring feature density via Cross-modal Random Network Prediction (CRNP). CRNP is designed to require little adaptation to translate between different prediction tasks, while having a stable training process. From a technical point of view, CRNP is the first approach to explore random network prediction to estimate uncertainty and to combine multi-modal data. Experiments on two 3D multi-modal medical image segmentation tasks and three 2D multi-modal computer vision classification tasks show the effectiveness, adaptability and robustness of CRNP. Also, we provide an extensive discussion on different fusion functions and visualization to validate the proposed model

Additive manufacturing assisted investment casting: a low-cost method to fabricate periodic metallic cellular lattices

Metallic cellular solids are a class of materials known for their high specific mechanical properties, being desirable in applications where a combination of high strength or stiffness and low density are important. These lightweight materials are often stochastic and manufactured by foaming or casting. If regular (periodic) lattice structures are desired, they may be manufactured by metallic additive manufacturing techniques. However, these have characteristic issues, such as un-melted powders, porosity and heterogeneous microstructures. This study reports a novel low-cost route for producing regular lattice structures by an additive manufacturing assisted investment casting technique. Fused filament fabrication is used to produce the lattice structure pattern which is infiltrated with plaster. The pattern is then burnt off and the aluminum is cast in vacuum. In this way we can manufacture non-stochastic metallic lattices having fine struts/ribs (0.6mm cross-section using a 0.4mm nozzle) and relative densities down to 0.036. X-ray micro computed tomography (μCT) showed that as-cast A356 Aluminium alloy frameworks have high dimensional tolerances and fine detail control. Frameworks based on units of six connected struts ranging from intruding (auxetic) to protruding (hexagonal) strut angles are studied. Vertical struts are finer than expected, reducing their moment of area which could impact their compressive strength. This new, low cost, route for producing high precision metallic cellular lattices offers an attractive alternative to other additive manufacturing techniques (e.g. selective laser and electron beam melting).European Research Council through the ERC grant CORREL-CT, number 695638 to enable VHC to visit the Henry Royce Institute to undertake the X-ray CT studies. This work was supported by the Henry Royce Institute for Advanced Materials, funded through EPSRC grants EP/R00661X/1, EP/S019367/1, EP/P025021/1 and EP/P025498/1. Also, this work was supported by Portuguese FCT, under the reference project UIDB/04436/2020. project iRAIL Innovation in Railway Systems and Technologies Doctoral Programme funds and by national funds through FCT - Portuguese Foundation for Science and Technology and was developed on the aim of the Doctoral grant PD/ BD/114096/2015

Including cognitive aspects in multiple criteria decision analysis

"First Online: 21 December 2016"Many Multiple Criteria Decision Analysis (MCDA) methods have been proposed over the last decades. Some of the most known methods share some similarities in the way they are used and configured. However, we live in a time of change and nowadays the decision-making process (especially when done in group) is even more demanding and dynamic. In this work, we propose a Multiple Criteria Decision Analysis method that includes cognitive aspects (Cognitive Analytic Process). By taking advantage of aspects such as expertise level, credibility and behaviour style of the decision-makers, we propose a method that relates these aspects with problem configurations (alternatives and criteria preferences) done by each decision-maker. In this work, we evaluated the Cognitive Analytic Process (CAP) in terms of configuration costs and the capability to enhance the quality of the decision. We have used the satisfaction level as a metric to compare our method with other known MCDA methods in literature (Utility function, AHP and TOPSIS). Our method proved to be capable to achieve higher satisfaction levels compared to other MCDA methods, especially when the decision suggested by CAP is different from the one proposed by those methods.This work was supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersio

A web analytics approach to map the influence and reach of CCAFS

This evaluation sought to understand CCAFS’ influence in motivating actors to tackle climate change. In CCAFS’ theory of change, a cross-cutting aim is to work with strategic partners to “foster policy and institutional change” that will enable large-scale CSA adoption. A conceptual framework was developed, and an innovative approach based on the Digital Methods epistemology was employed to explore the dynamics of knowledge dissemination and changes in attitude towards CSA among stakeholders at various levels. It considered online networks and narratives as evidence of “offline” program influence. Results show that CCAFS has inspired positive change in government policy; built a global community for climate adaption; and sparked public interest in “Climate Smart Agriculture”

Through the lens of inequality: What can we learn from CGIAR as a case study of research on the climate security nexus?

Grasping the indirect and non-linear linkages between climate and conflict merits uncovering how inequalities entrenched in existing social structures may inform and mediate this intricate relationship. Despite growing understanding around the need to focus on the entire climate security inequality nexus, existing literature has so far been tipping towards either unpacking inequality and conflict or inequality and climate linkages. Furthermore, research for development work is yet to unpack in detail context-specific nuances of this complex nexus. Building on this understanding, this working paper aims to study how research for development work has engaged with the climate security inequality nexus. Using CGIAR’s work on land, water, and food systems as case study, the paper conducts a knowledge mapping exercise to highlight gaps and scope for guiding future research

Monte Carlo calculation of the linear resistance of a three dimensional lattice Superconductor model in the London limit

We have studied the linear resistance of a three dimensional lattice Superconductor model in the London limit London lattice model by Monte Carlo simulation of the vortex loop dynamics. We find excellent finite size scaling at the phase transition. We determine the dynamical exponent $z = 1.51$ for the isotropic London lattice model.Comment: 4 pages, RevTeX with 3 postscript figures include

CCAFS’ influence and reach in promoting CSA

Since its inception, CCAFS has engaged with hundreds of partner institutions, from research centers to government bodies, in order to foster policy and institutional change that enable large-scale Climate Smart Agriculture (CSA) adoption. This Info Note summarizes the findings from two studies that aimed to assess the program’s influence on various dimensions. 1. CCAFS has shifted the debate on climate adaptation among strategic partners, with the program’s ideas having reached nearly 60 million people. 2. The program has also inspired positive change in government policy, with nearly 100 policy wins in just the two years up to 2019. 3. It has built a global community for climate adaption and is a key player within a network of more than 60 thousand entities. 4. CCAFS has sparked public interest in CSA, with Google searches for “Climate Smart Agriculture” consistently increasing every month since the program was inaugurated in 2011. 5. The reach of CCAFS science is growing exponentially, with content from CCAFS projects disseminated across 35 thousand URLs from 10 thousand unique domains from more than 150 countries. 6. CCAFS research in partnership with governments in many countries has contributed to increases in public investment in CSA reaching several billions of dollars. Strategies for accelerating private sector financing are now being pursued that are mobilizing new corporate and impact investor spending in climate adaptation actions and innovative CSA-related blended financing (joint government and private sector) approaches towards more sustainable food systems

Vortex Line Fluctuations in Model High Temperature Superconductors

We carry out Monte Carlo simulations of the uniformly frustrated 3d XY model as a model for vortex line fluctuations in a high Tc superconductor. A density of vortex lines of f=1/25 is considered. We find two sharp phase transitions. The low T phase is an ordered vortex line lattice. The high T normal phase is a vortex line liquid with much entangling, cutting, and loop excitations. An intermediate phase is found which is characterized as a vortex line liquid of disentangled lines. In this phase, the system displays superconducting properties in the direction parallel to the magnetic field, but normal behavior in planes perpendicular to the magnetic field.Comment: 38 pages, LaTeX 15 figures (upon request to [email protected]

Direct Measurement of Nuclear Dependence of Charged Current Quasielastic-like Neutrino Interactions using MINERvA

Charged-current $\nu_{\mu}$ interactions on carbon, iron, and lead with a final state hadronic system of one or more protons with zero mesons are used to investigate the influence of the nuclear environment on quasielastic-like interactions. The transfered four-momentum squared to the target nucleus, $Q^2$, is reconstructed based on the kinematics of the leading proton, and differential cross sections versus $Q^2$ and the cross-section ratios of iron, lead and carbon to scintillator are measured for the first time in a single experiment. The measurements show a dependence on atomic number. While the quasielastic-like scattering on carbon is compatible with predictions, the trends exhibited by scattering on iron and lead favor a prediction with intranuclear rescattering of hadrons accounted for by a conventional particle cascade treatment. These measurements help discriminate between different models of both initial state nucleons and final state interactions used in the neutrino oscillation experiments