Use of radio base stations to provide ancillary services to the DSO through local flexibility markets

The changes in the energy sector require an appropriate coordination between transmission systems operators (TSOs), distribution systems operators (DSOs) and aggregators. The project SmartNet aims at defining and comparing different TSO-DSO coordination schemes, by implementing dedicated analyses in Italy, Denmark and Spain. This paper describes the pilot project implemented in Spain and presents its main outcomes.The research leading to this article has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 691405

Application of the quantum spin glass theory to image restoration

Quantum fluctuation is introduced into the Markov random fields (MRF's) model for image restoration in the context of Bayesian approach. We investigate the dependence of the quantum fluctuation on the quality of BW image restoration by making use of statistical mechanics. We find that the maximum posterior marginal (MPM) estimate based on the quantum fluctuation gives a fine restoration in comparison with the maximum a posterior (MAP) estimate or the thermal fluctuation based MPM estimate.Comment: 19 pages, 9 figures, 1 table, RevTe

Naive mean field approximation for image restoration

We attempt image restoration in the framework of the Baysian inference. Recently, it has been shown that under a certain criterion the MAP (Maximum A Posterior) estimate, which corresponds to the minimization of energy, can be outperformed by the MPM (Maximizer of the Posterior Marginals) estimate, which is equivalent to a finite-temperature decoding method. Since a lot of computational time is needed for the MPM estimate to calculate the thermal averages, the mean field method, which is a deterministic algorithm, is often utilized to avoid this difficulty. We present a statistical-mechanical analysis of naive mean field approximation in the framework of image restoration. We compare our theoretical results with those of computer simulation, and investigate the potential of naive mean field approximation.Comment: 9 pages, 11 figure

Image restoration using the Q-Ising spin glass

We investigate static and dynamic properties of gray-scale image restoration (GSIR) by making use of the Q-Ising spin glass model, whose ladder symmetry allows to take in account the distance between two spins. We thus give an explicit expression of the Hamming distance between the original and restored images as a function of the hyper-parameters in the mean field limit. Finally, numerical simulations for real-world pictures are carried out to prove the efficiency of our model.Comment: 27pages, 13figures, revte

A Replica Inference Approach to Unsupervised Multi-Scale Image Segmentation

We apply a replica inference based Potts model method to unsupervised image segmentation on multiple scales. This approach was inspired by the statistical mechanics problem of "community detection" and its phase diagram. Specifically, the problem is cast as identifying tightly bound clusters ("communities" or "solutes") against a background or "solvent". Within our multiresolution approach, we compute information theory based correlations among multiple solutions ("replicas") of the same graph over a range of resolutions. Significant multiresolution structures are identified by replica correlations as manifest in information theory overlaps. With the aid of these correlations as well as thermodynamic measures, the phase diagram of the corresponding Potts model is analyzed both at zero and finite temperatures. Optimal parameters corresponding to a sensible unsupervised segmentation correspond to the "easy phase" of the Potts model. Our algorithm is fast and shown to be at least as accurate as the best algorithms to date and to be especially suited to the detection of camouflaged images.Comment: 26 pages, 22 figure

Multi-State Image Restoration by Transmission of Bit-Decomposed Data

We report on the restoration of gray-scale image when it is decomposed into a binary form before transmission. We assume that a gray-scale image expressed by a set of Q-Ising spins is first decomposed into an expression using Ising (binary) spins by means of the threshold division, namely, we produce (Q-1) binary Ising spins from a Q-Ising spin by the function F(\sigma_i - m) = 1 if the input data \sigma_i \in {0,.....,Q-1} is \sigma_i \geq m and 0 otherwise, where m \in {1,....,Q-1} is the threshold value. The effects of noise are different from the case where the raw Q-Ising values are sent. We investigate which is more effective to use the binary data for transmission or to send the raw Q-Ising values. By using the mean-field model, we first analyze the performance of our method quantitatively. Then we obtain the static and dynamical properties of restoration using the bit-decomposed data. In order to investigate what kind of original picture is efficiently restored by our method, the standard image in two dimensions is simulated by the mean-field annealing, and we compare the performance of our method with that using the Q-Ising form. We show that our method is more efficient than the one using the Q-Ising form when the original picture has large parts in which the nearest neighboring pixels take close values.Comment: latex 24 pages using REVTEX, 10 figures, 4 table

Variable order porous media equations: Application on modeling the S&P500 and Bitcoin price return

This article reveals a specific category of solutions for the $1+1$ Variable Order (VO) nonlinear fractional Fokker-Planck equations. These solutions are formulated using VO $q$-Gaussian functions, granting them significant versatility in their application to various real-world systems, such as financial economy areas spanning from conventional stock markets to cryptocurrencies. The VO $q$-Gaussian functions provide a more robust expression for the distribution function of price returns in real-world systems. Additionally, we analyzed the temporal evolution of the anomalous characteristic exponents derived from our study, which are associated with the long-range memory in time series data and autocorrelation patterns.Comment: 15 Pages, 3 Figures. Submitted to Physical Review

Image restoration using the chiral Potts spin-glass

We report on the image reconstruction (IR) problem by making use of the random chiral q-state Potts model, whose Hamiltonian possesses the same gauge invariance as the usual Ising spin glass model. We show that the pixel representation by means of the Potts variables is suitable for the gray-scale level image which can not be represented by the Ising model. We find that the IR quality is highly improved by the presence of a glassy term, besides the usual ferromagnetic term under random external fields, as very recently pointed out by Nishimori and Wong. We give the exact solution of the infinite range model with q=3, the three gray-scale level case. In order to check our analytical result and the efficiency of our model, 2D Monte Carlo simulations have been carried out on real-world pictures with three and eight gray-scale levels.Comment: RevTex 13 pages, 10 figure

Plant defense suppression is mediated by a fungal sirtuin during rice infection by \u3ci\u3eMagnaporthe oryzae\u3c/i\u3e

Crop destruction by the hemibiotrophic rice pathogen Magnaporthe oryzae requires plant defense suppression to facilitate extensive biotrophic growth in host cells before the onset of necrosis. How this is achieved at the genetic level is not well understood. Here, we report that a M. oryzae sirtuin, MoSir2, plays an essential role in rice defense suppression and colonization by controlling superoxide dismutase (SOD) gene expression. Loss of MoSir2 function in Δsir2 strains did not affect appressorial function, but biotrophic growth in rice cells was attenuated. Compared to wild type, Δsir2 strains failed to neutralize plant-derived reactive oxygen species (ROS) and elicited robust defense responses in rice epidermal cells that included elevated pathogenesis-related gene expression and granular depositions. Deletion of a SOD-encoding gene under MoSir2 control generated Δsod1 deletion strains that mimicked Δsir2 for impaired rice defense suppression, confirming SOD activity as a downstream output of MoSir2. In addition, comparative protein acetylation studies and forward genetic analyses identified a JmjC domain-containing protein as a likely target of MoSir2, and a Δsir2 Δjmjc double mutant was restored for MoSOD1 expression and defense suppression in rice epidermal cells. Together, this work reveals MoSir2 and MoJmjC as novel regulators of early rice cell infection

Smallholder Dairy Farmers in the Peruvian Andes Fulfilling the Role of Extension Agents

Dairy farming in the Peruvian Andes is mostly undertaken by smallholder farmers (4-6 cows/family) and of relatively recent development. In fact, over the last 2 decades dairy farming at high altitudes (3,500‒4200 masl) has grown rapidly, replacing the camelids and sheep farming that once predominated. Dairying growth has been catalysed by subsides from state and private organizations. It promotes high input systems based on feedlot technology. Compared to sheep and camelids farming, dairying at the Andes does not have yet an inherent local/indigenous knowledge associated to it. High altitude Andean ecosystems pose many constraints for dairy farming (hypoxia and high UV radiation, high variation between day and night temperatures, short rainy season, and hence shortage of feed and water; and not less importantly, accelerated climate change (CC)). Under these conditions, not only are productivity and profitability low, but there are high negative environmental impacts and poor animal welfare. In Peru, institutionalised research and extension (R&E) services are precarious. Research tackling current issues of high-altitude livestock farming is almost inexistent, whereas extension in support of farmers is dispersed, poorly funded, of short duration (a few months), focused on transfer of technology suitable to intensive farming systems, and has a high turnover of staff. A systems approach to address the complexity of Andean livestock farming development is lacking. The initiatives from the institutions promoting farming are directed to remediate recurrent problems (e.g., cold stress) or prioritise high cost, low impact activities (e.g., genetic improvement). Here, we present the successful experience of the New Zealand Peru Dairy Support Project (NZPDSP) to promote the adoption of improved low input pastoral dairying husbandry principles, where trained smallholder farmers play a key role as agents of change