Clustering Techniques Performance for the Coordination of Adaptive Overcurrent Protections

Inclusion of distributed generation and topological changes in a network originate several operating scenarios. For this reason, techniques that adjust the configuration of overcurrent relays have been developed in order to provide protection coordination strategies capable of operating in different schemes. However, the adjustments allowed by these devices are limited. Thus, scenario grouping techniques are proposed to reduce the number of required configurations. This paper aims to evaluate the performance of different grouping techniques with input parameters for coordination strategies of electrical overcurrent protections, where it is required to associate the different modes of operation of a distribution network. For the clustering process, unsupervised learning techniques such as K-means, K-medoids and Agglomerative Hierarchical Clustering were employed. Additionally, for the input characteristics, fault currents, nominal currents and other parameters obtained from the electrical system were taken into account. From the results obtained when evaluating different combinations of techniques and inputs, it is important to mention that the characteristics that describe the different modes of operation necessary for the grouping are decisive for the coordination strategies of electrical protections and that it is not possible to establish a significant difference between the clustering techniques evaluated. Lastly, the combination that presents the best performance was K-means: Manhattan and maximum short-circuit phase currents per relay with a sum of operation time of 428.72s and zero restriction violation. © 2022 IEEE

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as active distribution network (ADN) and microgrid (MG) play an important role in power system operation. The design and implementation of appropriate protection systems for MG and ADN must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small graphic processing unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE 13-node test feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications. © 2013 State Grid Electric Power Research Institute

La Cultura General Integral en el logro y preservación de los intereses y objetivos nacionales

This work exposes the comprehensive general culture of our young students as a priority task of teachers, as this is a fundamental strategic objective in the development of the Cuban Revolution and its defense, since it guarantees the training of the we consider valuing the importance of Comprehensive General Culture for the achievement and preservation of national objectives and interests.El presente trabajo expone la cultura general integral de nuestros jóvenes estudiantes como tarea prioritaria de los docentes, por ser esta un objetivo estratégico fundamental en el desarrollo de la Revolución Cubana y su defensa, ya que esta garantiza la formación del hombre nuevo, consideramos Valorar la importancia de la Cultura General Integral para el logro y la preservación de los objetivos e intereses Nacionales

Are black holes a serious threat to scalar field dark matter models?

Classical scalar fields have been proposed as possible candidates for the dark matter component of the universe. Given the fact that super-massive black holes seem to exist at the center of most galaxies, in order to be a viable candidate for the dark matter halo a scalar field configuration should be stable in the presence of a central black hole, or at least be able to survive for cosmological time-scales. In the present work we consider a scalar field as a test field on a Schwarzschild background, and study under which conditions one can obtain long-lived configurations. We present a detailed study of the Klein-Gordon equation in the Schwarzschild spacetime, both from an analytical and numerical point of view, and show that indeed there exist quasi-stationary solutions that can remain surrounding a black hole for large time-scales.Comment: 34 pages, 13 figure

Upgrade of a climate service tailored to water reservoirs management

We present the upgrade of a web tool designed to help in the decision making process for water reservoirs management in Spain. The tool, called S-ClimWaRe (Seasonal Climate predictions in support of Water Reservoirs management), covers the extended winter season (from November to March), when the North Atlantic Oscillation (NAO) pattern strongly influences the hydrological interannual variability in South-Western Europe. This climate service is fully user driven, and aims at meeting their requirements incorporating recent scientific progress.The research leading to these results has received funding from the MEDSCOPE project co-funded by the European Commission as part of ERA4CS, an ERA-NET initiated by JPI Climate, grant agreement 690462

A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression among University Students:A Secondary Analysis of a Randomized Clinical Trial

Importance: Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT. Objective: To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors. Design, Setting, and Participants: This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022. Interventions: Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435). Main Outcomes and Measures: Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline. Results: The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P =.003) or treatment as usual (40.0% [2.7%]; P =.001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P =.007; self-guided i-CBT: 25.4% [8.8%]; P =.004; treatment as usual: 31.0% [9.4%]; P =.001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P =.14; treatment as usual: 53.0% [6.0%]; P =.25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P =.001; treatment as usual: 41.8% [3.2%]; P &lt;.001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P =.07). Conclusions and Relevance: Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings. Trial Registration: ClinicalTrials.gov Identifier: NCT04780542.</p

Oligonucleotide array-CGH identifies genomic subgroups and prognostic markers for tumor stage mycosis fungoides

Mycosis fungoide (MF) patients who develop tumors or extracutaneous involvement usually have a poor prognosis with no curative therapy available so far. In the present European Organization for Research and Treatment of Cancer (EORTC) multicenter study, the genomic profile of 41 skin biopsies from tumor stage MF (MFt) was analyzed using a high-resolution oligo-array comparative genomic hybridization platform. Seventy-six percent of cases showed genomic aberrations. The most common imbalances were gains of 7q33.3q35 followed by 17q21.1, 8q24.21, 9q34qter, and 10p14 and losses of 9p21.3 followed by 9q31.2, 17p13.1, 13q14.11, 6q21.3, 10p11.22, 16q23.2, and 16q24.3. Three specific chromosomal regions, 9p21.3, 8q24.21, and 10q26qter, were defined as prognostic markers showing a significant correlation with overall survival (OS) (P=0.042, 0.017, and 0.022, respectively). Moreover, we have established two MFt genomic subgroups distinguishing a stable group (0-5 DNA aberrations) and an unstable group (>5 DNA aberrations), showing that the genomic unstable group had a shorter OS (P=0.05). We therefore conclude that specific chromosomal abnormalities, such as gains of 8q24.21 (MYC) and losses of 9p21.3 (CDKN2A, CDKN2B, and MTAP) and 10q26qter (MGMT and EBF3) may have an important role in prognosis. In addition, we describe the MFt genomic instability profile, which, to our knowledge, has not been reported earlier

Dualising the baryonic branch: Dynamic SU(2) and confining backgrounds in IIA

In this paper we construct and examine new supersymmetric solutions of massive IIA supergravity that are obtained using non-Abelian T-duality applied to the Baryonic Branch of the Klebanov-Strassler background. The geometries display SU(2) structure which we show flows from static in the UV to dynamical in the IR. Confinement and symmetry breaking are given a geometrical interpretation by this change of structure. Various field theory observables are studied, suggesting possible ways to break conformality and flow in N=1 TN and related field theories

Mesons from (non) Abelian T-dual backgrounds

In this work we study mesonic excitations in a Quantum Field Theory dual to the non Abelian T-dual of $AdS_5\times S^5$, using a D6 brane probe on the Sfetsos-Thompson background. Before and after the duality, we observe interesting differences between the spectra and interpret them. The spectrum of masses and the interactions among mesonic excitations teach valuable lessons about the character of non-Abelian T-duality and its implications for Holography. The case of Abelian T-duality is also studied.Comment: 26 pages plus many long appendice

Holographic flows in non-Abelian T-dual geometries

We use non-Abelian T-duality to construct new N=1 solutions of type IIA supergravity (and their M-theory lifts) that interpolate between AdS_5 geometries. We initiate a study of the holographic interpretation of these backgrounds as RG flows between conformal fixed points. Along the way we give an elegant formulation of non-Abelian T-duality when acting on a wide class of backgrounds, including those corresponding to such flows, in terms of their SU(2) structure