City 5.0

Citizens’ access to goods and services in the private sector is restricted, in some cases by affordability, in other by limited availability in some areas or at some times. Public services are subject to similar restrictions. Digital technologies can help in overcoming these restrictions and by doing so shift goods and services from the private sector into the public domain. For instance, a free public live screening of an opera performance that is usually restricted to a limited number of wealthy citizens is a new form of public services that is delivered in a new way. This article explains the notion of City 5.0, a symbolic metaphor for a liveable city in which the potential of digital technologies is used to eliminate citizens’ restrictions in consuming public goods and services

Coalition Formation Algorithm of Prosumers in a Smart Grid Environment

In a smart grid environment, we study coalition formation of prosumers that aim at entering the energy market. It is paramount for the grid operation that the energy producers are able to sustain the grid demand in terms of stability and minimum production requirement. We design an algorithm that seeks to form coalitions that will meet both of these requirements: a minimum energy level for the coalitions and a steady production level which leads to finding uncorrelated sources of energy to form a coalition. We propose an algorithm that uses graph tools such as correlation graphs or clique percolation to form coalitions that meet such complex constraints. We validate the algorithm against a random procedure and show that, it not only performs better in term of social welfare for the power grid, but also that it is more robust against unforeseen production variations due to changing weather conditions for instance.Comment: 6 pages, 4 figures, 1 table. submited to ICC 201

A cluster partitioning method: determination of density matrices of solids and comparison with X-ray experiments

In this paper we show that 1-electron properties such as Compton profiles and structure factors of crystals can be asymptotically retrieved through cluster-based calculations, followed by an appropriate partition of the 1-electron reduced density matrix (1RDM). This approach, conceptually simple, is checked with respects to both position and momentum spaces simultaneously for insulators and a covalent crystal. Restricting the calculations to small clusters further enables a fair description of local correlation effects in ionic compounds, which improves both Compton profiles and structure factors vs. their experimentally determined counterparts.Comment: 19 pages, 9 figures, 3 tables. Currently submitted to PR

mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R

Spatial and spatiotemporal machine-learning models require a suitable framework for their model assessment, model selection, and hyperparameter tuning, in order to avoid error estimation bias and over-fitting. This contribution reviews the state-of-the-art in spatial and spatiotemporal cross-validation, and introduces the {R} package {mlr3spatiotempcv} as an extension package of the machine-learning framework {mlr3}. Currently various {R} packages implementing different spatiotemporal partitioning strategies exist: {blockCV}, {CAST}, {skmeans} and {sperrorest}. The goal of {mlr3spatiotempcv} is to gather the available spatiotemporal resampling methods in {R} and make them available to users through a simple and common interface. This is made possible by integrating the package directly into the {mlr3} machine-learning framework, which already has support for generic non-spatiotemporal resampling methods such as random partitioning. One advantage is the use of a consistent nomenclature in an overarching machine-learning toolkit instead of a varying package-specific syntax, making it easier for users to choose from a variety of spatiotemporal resampling methods. This package avoids giving recommendations which method to use in practice as this decision depends on the predictive task at hand, the autocorrelation within the data, and the spatial structure of the sampling design or geographic objects being studied.Comment: 35 pages, 15 Figures, 1 Tabl

Metformin-mediated increase in DICER1 regulates microRNA expression and cellular senescence

Metformin, an oral hypoglycemic agent, has been used for decades to treat type 2 diabetes mellitus. Recent studies indicate that mice treated with metformin live longer and have fewer manifestations of age-related chronic disease. However, the molecular mechanisms underlying this phenotype are unknown. Here, we show that metformin treatment increases the levels of the microRNA-processing protein DICER1 in mice and in humans with diabetes mellitus. Our results indicate that metformin upregulates DICER1 through a post-transcriptional mechanism involving the RNA-binding protein AUF1. Treatment with metformin altered the subcellular localization of AUF1, disrupting its interaction with DICER1 mRNA and rendering DICER1 mRNA stable, allowing DICER1 to accumulate. Consistent with the role of DICER1 in the biogenesis of microRNAs, we found differential patterns of microRNA expression in mice treated with metformin or caloric restriction, two proven life-extending interventions. Interestingly, several microRNAs previously associated with senescence and aging, including miR-20a, miR-34a, miR-130a, miR-106b, miR-125, and let-7c, were found elevated. In agreement with these findings, treatment with metformin decreased cellular senescence in several senescence models in a DICER1- dependent manner. Metformin lowered p16 and p21 protein levels and the abundance of inflammatory cytokines and oncogenes that are hallmarks of the senescence-associated secretory phenotype (SASP). These data lead us to hypothesize that changes in DICER1 levels may be important for organismal aging and to propose that interventions that upregulate DICER1 expression (e.g., metformin) may offer new pharmacotherapeutic approaches for age-related disease