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Electronic-structure calculations based on hybrid functionals have emerged as a standard technique used in physics, chemistry, and material science.
Despite this success, hybrid functionals have the drawback of containing undetermined parameters.
To overc ...
In response to the coronavirus disease (COVID-19) pandemic, public health scientists have produced a large and rapidly expanding body of literature that aims to answer critical questions, such as the proportion of the population in a geographic area that h ...
Two low CO2 cement systems are investigated: one made with the use of supplementary cementitious materi-als (SCMs) (metakaolin and limestone) and the other an alternative binder, calcium sulfoaluminate cement (CSA). These two low CO2 cements contain a simi ...
This study demonstrates the efficacy of supplementary cementitious materials (SCMs) to mitigate alkali-silica reaction (ASR) even when used in conjunction with cement of higher alkali contents (up to 1% Na2Oeq). The expansion of concrete prisms was studied ...
The increasing size of Convolutional Neural Networks (CNNs) and the high computational workload required for inference pose major challenges for their deployment on resource-constrained edge devices. In this paper, we address them by proposing a novel In-M ...
Cholera pandemics have been affecting humankind for centuries and are still considered a major public health problem, especially in regions around the world with poor access to clean water and sanitation. Cholera pandemics are caused by a specific lineage ...
The most prevalent materials used in the field of plasmonics are Au and Ag. However, for the past few years, the plasmonic community has also been looking for alternative materials that have lower losses than Au and higher stability than Ag. This thesis is ...
Decentralized training of deep learning models is a key element for enabling data privacy and on-device learning over networks. In realistic learning scenarios, the presence of heterogeneity across different clients' local datasets poses an optimization ch ...
The “Multivariate Ring Learning with Errors” problem was presented as a generalization of Ring Learning with Errors (RLWE), introducing efficiency improvements with respect to the RLWE counterpart thanks to its multivariate structure. Nevertheless, the rec ...
In the transition to a sustainable energy system, energy communities have unique advantages; they require no additional land and allow inhabitants to reduce their energy bills. Nowadays, each shareholder’s profit is calculated based on their share of inves ...
