2063 research outputs found
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Screw rotor manufacturing via 5-axis flank CNC machining using conical tools
Get PDFWe propose a new method for 5-axis flank computer numerically controlled (CNC) machining of screw rotors using conical tools. The flanks of screw rotors consist of helical surfaces, which predetermines the motion of the milling tool and reduces the search space for tool positioning to only 4-parametric family, which allows a quick search for good initial positions of a given conical tool. We initialize the search by looking at second order line contact between the tool and the helical flank of the rotor. Several positions of the tool are found, covering major part of the flank of the rotor, followed by global optimization that further reduces the tool-surface error and makes sure that there are no gaps between neighboring sweeps of the tool. We demonstrate our approach on several benchmark screw rotors, showing that our approach meets fine industrial tolerances with only few sweeps of the tool.RYC-2017-2264
Anomalous diffusion originated by two Markovian hopping-trap mechanisms
Get PDFWe show through intensive simulations that the paradigmatic
features of anomalous diffusion are indeed the features of
a (continuous-time) random walk driven by two different Markovian hopping-trap mechanisms.
If and are the probabilities
of occurrence of each Markovian mechanism,
then the anomalousness parameter results to be
.
Ensemble and single-particle observables of this model have been studied
and they match the main characteristics of anomalous diffusion
as they are typically measured in living systems.
In particular, the celebrated transition of the walker's distribution
from exponential to stretched-exponential and finally
to Gaussian distribution is displayed by including also
the Brownian yet non-Gaussian interval.BERC 2018–2021
BERC 2022–2025
MOSAIC project DIT.AD004.14
Modeling the transmission dynamics and vaccination strategies for human papillomavirus infection: An optimal control approach
Get PDFHuman papillomavirus (HPV) vaccines have been introduced in several countries and have shown positive results in reducing HPV infection and related diseases. Nevertheless, immunization programs remain sub-optimal and more effort is needed to design efficient vaccination deployment. We formulate a two-sex deterministic mathematical model that incorporates the most important epidemiological features of HPV infection and associated cancers. To assess the population-level impact of HPV immunization programs, the model incorporates school-based vaccine delivery for juveniles and catch-up vaccination for adults. The dynamics of the model are rigorously analyzed using the next-generation operator, the center manifold theorem, and normal forms theory. We formulate an optimal control problem to determine the best deployment strategy for HPV vaccination for several plausible scenarios. We establish the existence of solutions of the optimal control problem, and use Pontryagin’s Maximum Principle to characterize the necessary conditions for optimal control solutions. The findings suggest that if girls-only programs are complemented with catch-up vaccination for adult females, such program has the potential to achieve HPV-associated cancers eradication even if boys and males do not receive the vaccine. We also find that the optimal vaccine deployment, in terms of minimizing HPV associated diseases and the cost of vaccination, is to allocate as much vaccines as possible at the initial phase of the epidemic and once a high vaccination coverage is reached then gradually decrease vaccination rates
POINT DEFECTS IN 2-D LIQUID CRYSTALS WITH SINGULAR POTENTIAL: PROFILES AND STABILITY
No full textWe study radial symmetric point defects with degree k
2 in 2D disk or R2 in Q-tensor
framework with singular bulk energy, which is defined by Bingham closure. First, we obtain the
existence of solutions for the profiles of radial symmetric point defects with degree k
2 in 2D disk or
R2. Then we prove that the solution is stable for |k| = 1 and unstable for |k| > 1. Some identities
are derived and used throughout the proof of existence and stability/instability
Modeling swelling effects during coffee extraction with smoothed particle hydrodynamics
Get PDFIt is commonly assumed that coffee particles swell during filtration, but it has not been clarified how different degrees of swelling affect the extraction. In this article, we propose a grain swelling model to investigate the influences of swelling on both intra-grain and inter-grain transport. The swelling is modeled through a diffusion process of excess water into the grains. The geometric expansion of the grains is connected to the local concentration of excess water through a specified deformation gradient tensor. Diffusion of soluble compounds inside the grains is coupled with the swelling dynamics through a modified diffusion equation. Inter-grain transport is modeled by solving the Navier-Stokes equation and diffusion equations. This model is solved numerically in the framework of smoothed particle hydrodynamics, and it is used to simulate the extraction of a minimal coffee bed setup and to investigate the effect of a small degree of particle swelling (< 8 % in size) on the extraction kinetics. It is found that under the normal operating parameter regime of espresso filtration, swelling affects the extraction mainly through the change of inter-grain transport. Swelling also alters the diffusion inside the grains, but this process has a secondary effect on the extraction. In general, swelling slightly impedes the extraction rate, but enhances the strength considerably at both fixed brewing time and fixed brewing volume. Our results justify the endeavor in the literatures to clarify the effect of possible swelling on brewing and preparation variables during coffee extraction
Open-Air Microwave Entanglement Distribution for Quantum Teleportation
Get PDFMicrowave technology plays a central role in current wireless communications, including mobile communication and local area networks. The microwave range shows relevant advantages with respect to other frequencies in open-air transmission, such as low absorption losses and low-energy consumption, and in addition, it is the natural working frequency in superconducting quantum technologies. Entanglement distribution between separate parties is at the core of secure quantum communications. Therefore, understanding its limitations in realistic open-air settings, especially in the rather unexplored microwave regime, is crucial for transforming microwave quantum communications into a mainstream technology. Here, we investigate the feasibility of an open-air entanglement distribution scheme with microwave two-mode squeezed states. First, we study the reach of direct entanglement transmission in open air, obtaining a maximum distance of approximately 500 m with parameters feasible for state-of-the-art experiments. Subsequently, we adapt entanglement distillation and entanglement swapping protocols to microwave technology in order to reduce the environment-induced entanglement degradation. The employed entanglement distillation helps to increase quantum correlations in the short-distance low-squeezing regime by up to 46%, and the reach of entanglement increases by 14% with entanglement swapping. Importantly, we compute the fidelity of a continuous-variable quantum teleportation protocol using open-air-distributed entanglement as a resource. Finally, we adapt this machinery to explore the limitations of quantum communication between satellites, where the impact of thermal noise is substantially reduced and diffraction losses are dominant.QUANTEK project from ELKARTEK program (KK-2021/00070)
QMiCS (820505) and OpenSuperQ (820363) of the EU Flagship on Quantum Technologies
EU FET-OPEN projects Quromorphic (828826) and EPIQUS (899368
Hybrid quantum-classical heuristic for the bin packing problem
Get PDFOptimization problems is one of the most challenging applications of quantum computers, as well as one of the most relevants. As a consequence, it has attracted huge efforts to obtain a speedup over classical algorithms using quantum resources. Up to now, many problems of different nature have been addressed through the perspective of this revolutionary computation paradigm, but there are still many open questions. In this work, a hybrid classical-quantum approach is presented for dealing with the one-dimensional Bin Packing Problem (1dBPP). The algorithm comprises two modules, each one designed for being executed in different computational ecosystems. First, a quantum subroutine seeks a set of feasible bin configurations of the problem at hand. Secondly, a classical computation subroutine builds complete solutions to the problem from the subsets given by the quantum subroutine. Being a hybrid solver, we have called our method H-BPP. To test our algorithm, we have built 18 different 1dBPP instances as a benchmarking set, in which we analyse the fitness, the number of solutions and the performance of the QC subroutine. Based on these figures of merit we verify that H-BPP is a valid technique to address the 1dBPP.QUANTEK project (ELKARTEK program from the Basque Government, expedient no. KK-2021/00070)
Spanish Ramón y Cajal Grant RYC-2020-030503- I
QMiCS (820505) and OpenSuperQ (820363) of the EU Flagship on Quantum Technologies
EU FET Open project Quromorphic (828826) and EPIQUS (899368
Estimation of cut-off points under complex-sampling design data
Get PDFIn the context of logistic regression models, a cut-off point is usually selected to dichotomize the estimated predicted probabilities based on the model. The techniques proposed to estimate optimal cut-off points in the literature, are commonly developed to be applied in simple random samples and their applicability to complex sampling designs could be limited. Therefore, in this work we propose a methodology to incorporate sampling weights in the estimation process of the optimal cut-off points, and we evaluate its performance using a real data-based simulation study. The results suggest the convenience of considering sampling weights for estimating optimal cut-off points.IT1294-19
BERC 2018-2021
KK-2020/00049
PIF18/21
Female Models in AI and the Fight Against COVID-19
Get PDFGender imbalance has persisted over time and is well documented in science, technology,
engineering and mathematics (STEM) and singularly in artificial intelligence
(AI). In this article we emphasize the importance of increasing the visibility and
recognition of women researchers to attract and retain women in the AI field. We
review the ratio of women in STEM and AI, its evolution through time, and the differences
among disciplines. Then, we discuss the main sources of this gender
imbalance highlighting the lack of female role models and the problems which may
arise; such as the so called Marie Curie complex, suvivorship bias, and impostor
syndrome. We also emphasize the importance of active participation of women researchers
in conferences, providing statistics corresponding with the leading conferences.
Finally, we give examples of several prestigious female researchers in
the field and we review their research work related to COVID-19 displayed in the
workshop “Artificial Intelligence for the Fight Against COVID-19” (AI4FA COVID-19), which is an example of a more balanced participation between genders.AXA Research Fund through the project “Early Prognosis of COVID-19 Infections via Machine
Learning” under the Exceptional Flash Call “Mitigating risk in the wake of the COVID-19 pandemic”
Basque Government through the project “Mathematical Modeling Applied to Health
Numerical Approaches for Loads and Motions Assessment of Floating WECs Moored by Means of Catenary Mooring Systems
Get PDFTechnologies for harvesting offshore renewable energy based on float- ing platforms, such as offshore wind, wave and tidal energies, are currently being developed with the purpose of achieving a competitive cost of energy. The eco- nomic impact of the mooring system is significant within the total cost of such deployments, and large efforts are being carried out to optimize designs. Analysis of mooring systems at early stages generally require a trade-off between quick analysis methods and accuracy to carry out multi-variate sensitivity analyses. Even though the most accurate approaches are based on the non-linear finite ele- ment method in the time domain, these can result in being very time consuming. The most widely used numerical approaches for mooring line load estimates are introduced and discussed in this paper. It is verified that accurate line tension estimates require lines drag and inertia forces to be accounted for. A mooring and floating structure coupled model based on the lumped mass finite element ap- proach is also discussed, and it is confirmed that the differences found in the coupled numerical model are mainly produced by the uncertainty on hydrody- namic force estimates on the floating structure rather than by the lumped mass method. In order to enable quick line tension estimates, a linearization of the structure and mooring coupled model is discussed. It shows accurate results in operational conditions and enables modal analysis of the coupled system