Enhancing Predictive Capabilities in Data-Driven Dynamical Modeling with Automatic Differentiation: Koopman and Neural ODE Approaches

Data-driven approximations of the Koopman operator are promising for predicting the time evolution of systems characterized by complex dynamics. Among these methods, the approach known as extended dynamic mode decomposition with dictionary learning (EDMD-DL) has garnered significant attention. Here we present a modification of EDMD-DL that concurrently determines both the dictionary of observables and the corresponding approximation of the Koopman operator. This innovation leverages automatic differentiation to facilitate gradient descent computations through the pseudoinverse. We also address the performance of several alternative methodologies. We assess a 'pure' Koopman approach, which involves the direct time-integration of a linear, high-dimensional system governing the dynamics within the space of observables. Additionally, we explore a modified approach where the system alternates between spaces of states and observables at each time step -- this approach no longer satisfies the linearity of the true Koopman operator representation. For further comparisons, we also apply a state space approach (neural ODEs). We consider systems encompassing two and three-dimensional ordinary differential equation systems featuring steady, oscillatory, and chaotic attractors, as well as partial differential equations exhibiting increasingly complex and intricate behaviors. Our framework significantly outperforms EDMD-DL. Furthermore, the state space approach offers superior performance compared to the 'pure' Koopman approach where the entire time evolution occurs in the space of observables. When the temporal evolution of the Koopman approach alternates between states and observables at each time step, however, its predictions become comparable to those of the state space approach

Las asignaciones económicas del estado a los partidos políticos; su incidencia en los principios democráticos

La composición de la investigación se circunscribe a tres aspectos fundamentales, el primero que recoge bajo un marco teórico referencial, todos los principios, conceptos y normativas que rige en el proceso de elecciones en el país. El segundo de una 1 Diario el Comercio. Portada principal. 12 de Abril de 2000. importancia sustantiva, al realizar un análisis retrospectivo de la situación actual del sistema democrático, considerando para aquello, el desarrollo democrático, la realidad partidista ecuatoriana, evolución presupuestaria de las asignaciones otorgadas a los partidos políticos, la corrupción y descomposición del proceso electoral, dentro del período 1979 –1999. El tercer aspecto, se constituye en el factor fundamental del estudio, pues se realiza el planteamiento de la alternativa de consolidación del sistema democrático del Ecuador, producto de un proceso de investigación que recoge, procesamiento de información existente, verificación directa y apreciaciones de tratadistas políticos que han dado lugar a que bajo una percepción de carácter subjetivo sin orientación política alguna, se establezca recomendaciones que con el carácter de sugerentes se pone a consideración de los organismos que regulan el proceso democrático en el país. Especial énfasis se ha puesto a tres factores que representan de singular importancia para los fines de consolidación democrática, que son: la regulación y control de las fuentes y destinos del financiamiento de campaña, bajo un proceso integral de operación y fortalecimiento; la reinterpretación del debate político y consenso nacional; y la recuperación de la imagen internacional. Tanto las conclusiones como las recomendaciones son efectuadas dentro de una realidad tangible y susceptible de ser aplicados, pero para aquello, demanda de una transformación de la consciencia nacional y política para enfrentar la realidad ecuatoriana y contribuir a la cimentación de un nuevo país. Esta acción imperativa como aspiración de todos los miembros de la sociedad ecuatoriana nos plantea la disyuntiva, o rescatamos la imagen del país y fortalecemos democráticamente la vivencia para las futuras generaciones o nos hundimos en el cieno de la corrupción.I. REGIMEN LEGAL DELSISTEMA DEMOCRATICO EN EL ECUADOR II. DIAGNOSTICO DE LA SITUACION ACTUAL DEL SISTEMA DEMOCRATICO III. ALTERNATIVA DE CONSOLIDACION DEL SISTEMA DEMOCRATICO DEL ECUADOR IV. CONCLUSIONES Y RECOMENDACIONE

Biomass-derived carbon/γ-MnO2 nanorods/S composites prepared by facile procedures with improved performance for Li/S batteries

The promising prospects of the Li/S battery, due to its theoretical energy density of about 2500 Wh kg─1, are severely limited by two main weaknesses: the poor conductivity of S and the solubility of the polysulphides in the electrolyte. A combination of carbon and transition metal oxides is the best option for mitigating both of these shortcomings simultaneously. In this work, we use hydrothermally-tailored γ-MnO2 nanorods combined with an activated biomass-derived carbon, which is an inexpensive material and easy to prepare. This strategy was also followed for a AC/MnO2/S composite, a preparation of which was made by grinding; this is the simplest method for practical applications. More complex procedures for the formation of in situ hydrothermal MnO2 nanorods gave similar results to those obtained from grinding. Compared with the AC/S composite, the presence of MnO2 markedly increased the delivered capacity and improved the cycling stability at both low (0.1 C) and high (1 C) currents. This behaviour results from a combination of two main effects: firstly, the MnO2 nanorods increase the electrical conductivity of the electrode, and secondly, the small particle size of the oxide can enhance the chemisorption properties and facilitate a redox reaction with polysulphides, more efficiently blocking their dissolution in the electrolyte

Importance Sampling for Objetive Funtion Estimations in Neural Detector Traing Driven by Genetic Algorithms

To train Neural Networks (NNs) in a supervised way, estimations of an objective function must be carried out. The value of this function decreases as the training progresses and so, the number of test observations necessary for an accurate estimation has to be increased. Consequently, the training computational cost is unaffordable for very low objective function value estimations, and the use of Importance Sampling (IS) techniques becomes convenient. The study of three different objective functions is considered, which implies the proposal of estimators of the objective function using IS techniques: the Mean-Square error, the Cross Entropy error and the Misclassification error criteria. The values of these functions are estimated by IS techniques, and the results are used to train NNs by the application of Genetic Algorithms. Results for a binary detection in Gaussian noise are provided. These results show the evolution of the parameters during the training and the performances of the proposed detectors in terms of error probability and Receiver Operating Characteristics curves. At the end of the study, the obtained results justify the convenience of using IS in the training

Effective cancer immunotherapy by natural mouse conventional type-1 dendritic cells bearing dead tumor antigen

BACKGROUND: The manipulation of dendritic cells (DCs) for cancer vaccination has not reached its full potential, despite the revolution in cancer immunotherapy. DCs are fundamental for CD8+ T cell activation, which relies on cross-presentation of exogenous antigen on MHC-I and can be fostered by immunogenic cancer cell death. Translational and clinical research has focused on in vitro-generated monocyte-derived DCs, while the vaccination efficacy of natural conventional type 1 DCs (cDC1s), which are associated with improved anti-tumor immunity and specialize on antigen cross-presentation, remains unknown. METHODS: We isolated primary spleen mouse cDC1s and established a protocol for fast ex vivo activation and antigen-loading with lysates of tumor cells that underwent immunogenic cell death by UV irradiation. Natural tumor antigen-loaded cDC1s were transferred and their potential for induction of endogenous CD8+ and CD4+ T cell responses in vivo, cancer prevention and therapy were assessed in three grafted cancer models. Further, we tested the efficacy of natural cDC1 vaccination in combination and comparison with anti-PD-1 treatment in two "wildtype" tumor models not expressing exogenous antigens. RESULTS: Herein, we reveal that primary mouse cDC1s ex vivo loaded with dead tumor cell-derived antigen are activated and induce strong CD8+ T cell responses from the endogenous repertoire upon adoptive transfer in vivo through tumor antigen cross-presentation. Notably, cDC1-based vaccines enhance tumor infiltration by cancer-reactive CD8+ and CD4+ T cells and halt progression of engrafted cancer models, including tumors that are refractory to anti-PD-1 treatment. Moreover, combined tumor antigen-loaded primary cDC1 and anti-PD-1 therapy had strong synergistic effects in a PD-1 checkpoint inhibition susceptible cancer model. CONCLUSIONS: This preclinical proof-of-principle study is first to support the therapeutic efficacy of cancer immunotherapy with syngeneic dead tumor cell antigen-loaded mouse cDC1s, the equivalents of the human dendritic cell subset that correlates with beneficial prognosis of cancer patients. Our data pave the way for translation of cDC1-based cancer treatments into the clinic when isolation of natural human cDC1s becomes feasible.Work in the DS laboratory is funded by the CNIC and grant SAF2016–79040-R from Ministerio de Ciencia, Innovación e Universidades (MCIU), Agencia Estatal de Investigación and Fondo Europeo de Desarrollo Regional (FEDER); B2017/BMD-3733 Immunothercan-CM from Comunidad de Madrid; RD16/0015/0018-REEM from FIS-Instituto de Salud Carlos III, MICINN and FEDER; Acteria Foundation; Constantes y Vitales prize (Atresmedia); La Marató de TV3 Foundation (201723); and the European Research Council (ERC-2016-Consolidator Grant 725091). Work at the IM laboratory is funded by grants from MCIU (SAF2014–52361-R and SAF2017–83267-C2–1-R) and by European Commission VII Framework and Horizon 2020 programs (AICR), Fundación de la Asociación Española Contra el Cáncer (AECC), and Fundación BBVA. SKW is supported by a European Molecular Biology Organization Long-term Fellowship (grant ALTF 438–2016) and a CNIC-International Postdoctoral Program Fellowship (grant 17230–2016). SCK is a recipient of a FPU fellowship (FPU16/03142) from the Spanish Ministry of Education, Culture and Sports. IM and DS labs are funded by the European Commission (635122-PROCROP H2020). The CNIC is supported by the MCIU and the Pro-CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505). AGRADECIENTOS: ProCNIC; Severo Ochoa (SEV-2015-0505)S

Benzo-dipteridine derivatives as organic cathodes for Li- and Na-ion batteries

Organic-based electrodes for Li- and Na-ion batteries present attractive alternatives to commonly applied inorganic counterparts which can often carry with them supply-chain risks, safety concerns with thermal runaway, and adverse environmental impact. The ability to chemically direct the structure of organic electrodes through control over functional groups is of particular importance, as this provides a route to fine-tune electrochemical performance parameters. Here, we report two benzo-dipteridine derivatives, BF-Me2 and BF-H2, as high-capacity electrodes for use in Li- and Na-ion batteries. These moieties permit binding of multiple Li-ions per molecule while simultaneously ensuring low solubility in the supporting electrolyte, often a precluding issue with organic electrodes. Both display excellent electrochemical stability, with discharge capacities of 142 and 182 mAh g–1 after 100 cycles at a C/10 rate and Coulombic efficiencies of 96% and ∼ 100% demonstrated for BF-Me2 and BF-H2, respectively. The application of a Na-ion cell has also been demonstrated, showing discharge capacities of 88.8 and 137 mAh g–1 after 100 cycles at a C/2 rate for BF-Me2 and BF-H2, respectively. This work provides an encouraging precedent for these and related structures to provide versatile, high-energy density, and long cycle-life electrochemical energy storage materials

A systematic review and conceptual framework of key performance indicators for urban public safety smartness for cities in Andalusia, Spain

Background: The smart city approach is one of the most widely implemented urban development frameworks to solve the challenges brought about by urbanization. While the smart city approach has been evaluated across several urban dimensions. However, the extent to which the key performance indicators (KPI) assess security and safety dimensions is unknown. This protocol presents a systematic review of current KPIs to fill this gap. Objectives: This protocol details the work plan for a systematic review of KPI for public safety smartness designed to provide a comprehensive summary and their limitations in the scientific literature. Particularly, the study seeks to critically review the applicability of current public safety KPI to the Andalusian context. Specifically, the systematic review aims to synthesize: (RQ1) What indicators have been designed and used to measure urban public safety smartness; (RQ2) Within which smart city dimensions have the KPI been located; and (RQ3) How are the KPI defined and measured? Design: This systematic review follows the PRISMA statement. Five databases are searched for thematically relevant studies published in English or in Spanish. Studies included peer?reviewed publications, books, book chapters, conference papers, government and company documents, technical reports and doctoral theses. After the initial search, a pilot study was conducted on a sample of the total number of titles identified through the databases searches. After acceptable inter-rater reliability was reached among the three coders, screening of abstracts was carried out by the first author. Next, full-text screening of documents will determine the final sample. Finally, data will be extracted from the final selection of documents.Security and Global Affair

Highly graphitized carbon nanosheets with embedded Ni nanocrystals as anode for Li-ion batteries

A C/Ni composite was prepared via thermal decomposition of a nickel oleate complex at 700 °C, yielding disperse Ni nanocrystals with an average size of 20 nm, encapsulated by carbon nanosheets as deduced from transmission electron microscopy (TEM) images and confirmed from X-ray photoelectron spectroscopy (XPS). Furthermore, the X-ray diffraction pattern revealed a good ordering of the carbon layers, forced by the Ni encapsulation to adopt a bending structure. Considering the close interaction between the graphitized framework and the metallic nanoparticles we have studied the properties of the composite as an anode for Li-ion batteries. Compared with other nanostructured synthetic carbons, this carbon composite has a low voltage hysteresis and a modest irreversible capacity value, properties that play a significant role in its behaviour as electrodes in full cell configuration. At moderate rate values, 0.25 C, the electrode delivers an average capacity value around 723 mAh·g−1 on cycling, among the highest values so far reported for this carbon type. At higher rate values, 1 C, the average capacity values delivered by the cell on cycling decrease, around 205 mAh·g−1, but it maintains good capacity retention, a coulombic efficiency close to 100% after the first cycles and recovery of the capacity values when the rate is restored from 3 to 0.1 C