Macromolecular structural dynamics visualized by pulsed dose control in 4D electron microscopy

Macromolecular conformation dynamics, which span a wide range of time scales, are fundamental to the understanding of properties and functions of their structures. Here, we report direct imaging of structural dynamics of helical macromolecules over the time scales of conformational dynamics (ns to subsecond) by means of four-dimensional (4D) electron microscopy in the single-pulse and stroboscopic modes. With temporally controlled electron dosage, both diffraction and real-space images are obtained without irreversible radiation damage. In this way, the order-disorder transition is revealed for the organic chain polymer. Through a series of equilibrium-temperature and temperature-jump dependencies, it is shown that the metastable structures and entropy of conformations can be mapped in the nonequilibrium region of a “funnel-like” free-energy landscape. The T-jump is introduced through a substrate (a “hot plate” type arrangement) because only the substrate is made to absorb the pulsed energy. These results illustrate the promise of ultrafast 4D imaging for other applications in the study of polymer physics as well as in the visualization of biological phenomena

Magnetization plateau in a two-dimensional multiple-spin exchange model

We study a multiple-spin exchange model on a triangular lattice, which is a possible model for low-density solid 3He films. Due to strong competitions between ferromagnetic three-spin exchange and antiferromagnetic four-spin one, the ground states are highly degenerate in the classical limit. At least 2^{L/2}-fold degeneracy exists on the L*L triangular lattice except for the SO(3) symmetry. In the magnetization process, we found a plateau at m/m_{sat}=1/2, in which the ground state is "uuud state" (a collinear state with four sublattices). The 1/2-plateau appears due to the strong four-spin exchange interaction. This plateau survives against both quantum and thermal fluctuations. Under a magnetic field which realizes the "uuud" ordered state, a phase transition occurs at a finite temperature. We predict that low-density solid 3He thin films may show the 1/2-plateau in the magnetization process. Experimental observation of the plateau will verify strength of the four-spin exchange. It is also discussed that this magnetization plateau can be understood as an insulating-conducting transition in a particle picture.Comment: 10 pages, RevTeX, 12 figures, added a reference and corrected typos, to be published in Phys.Rev.B (01 APR 99

Predicting Thermoelectric Power Plants Diesel/Heavy Fuel Oil Engine Fuel Consumption Using Univariate Forecasting and XGBoost Machine Learning Models

Monitoring and controlling thermoelectric power plants (TPPs) operational parameters have become essential to ensure system reliability, especially in emergencies. Due to system complexity, operating parameters control is often performed based on technical know-how and simplified analytical models that can result in limited observations. An alternative to this task is using time series forecasting methods that seek to generalize system characteristics based on past information. However, the analysis of these techniques on large diesel/HFO engines used in Brazilian power plants under the dispatch regime has not yet been well-explored. Therefore, given the complex characteristics of engine fuel consumption during power generation, this work aimed to investigate patterns generalization abilities when linear and nonlinear univariate forecasting models are used on a representative database related to an engine-driven generator used in a TPP located in Pernambuco, Brazil. Fuel consumption predictions based on artificial neural networks were directly compared to XGBoost regressor adaptation to perform this task as an alternative with lower computational cost. AR and ARIMA linear models were applied as a benchmark, and the PSO optimizer was used as an alternative during model adjustment. In summary, it was possible to observe that AR and ARIMA-PSO had similar performances in operations and lower error distributions during full-load power output with normal error frequency distribution of −0.03 ± 3.55 and 0.03 ± 3.78 kg/h, respectively. Despite their similarities, ARIMA-PSO achieved better adherence in capturing load adjustment periods. On the other hand, the nonlinear approaches NAR and XGBoost showed significantly better performance, achieving mean absolute error reductions of 42.37% and 30.30%, respectively, when compared with the best linear model. XGBoost modeling was 8.7 times computationally faster than NAR during training. The nonlinear models were better at capturing disturbances related to fuel consumption ramp, shut-down, and sudden fluctuations steps, despite being inferior in forecasting at full-load, especially XGBoost due to its high sensitivity with slight fuel consumption variations

Forecasting Particulate Matter Concentrations: Use of Unorganized Machines

Air pollution is an environmental issue studied worldwide, as it has serious impacts on human health. Therefore, forecasting its concentration is of great importance. Then, this study presents an analysis comprising the appliance of Unorganized Machines – Extreme Learning Machines (ELM) and Echo State Networks (ESN) aiming to predict particulate matter with aerodynamic diameter less than 2.5 m (PM2.5) and less than 10 m (PM10). The databases were from Kallio and Vallilla stations in Helsinki, Finland. The computational results showed that the ELM presented best results to PM2.5, while the ESN achieved the best performance to PM10

Possible chiral phase transition in two-dimensional solid 3^3He

We study a spin system with two- and four-spin exchange interactions on the triangular lattice, which is a possible model for the nuclear magnetism of solid $^3$He layers. It is found that a novel spin structure with scalar chiral order appears if the four-spin interaction is dominant. Ground-state properties are studied using the spin-wave approximation. A phase transition concerning the scalar chirality occurs at a finite temperature, even though the dimensionality of the system is two and the interaction has isotropic spin symmetry. Critical properties of this transition are studied with Monte Carlo simulations in the classical limit.Comment: 4 pages, Revtex, 4 figures, to appear in Phys.Rev.Let

Balanço hidrológico da microbacia do córrego lageado, Município de Uberaba-MG, para o ano de 2012.

O manejo integrado em microbacia hidrográfica implementa uma nova maneira de se planejar e usar os recursos naturais, indo de encontro ao desenvolvimento sustentável. A compreensão do balanço hídrico, mesmo que de forma simplificada, é importante para o entendimento dos processos de degradação e conservação dos recursos naturais relacionados ao uso do solo e da água. Dentro deste contexto, o presente estudo teve por objetivo fazer o balanço hídrico da microbacia do córrego Lageado, situada no município de Uberaba, MG, para o ano de 2012. A escolha desta microbacia para este trabalho baseou-se na sua importância como terceiro maior manancial pertencente à APA (Área de Proteção Ambiental) do rio Uberaba e por estar parcialmente dentro do perímetro urbano. Nas últimas décadas, esta microbacia hidrográfica passou por intensas transformações relacionadas ao uso e à ocupação do solo

High-resolution abundance analysis of red giants in the metal-poor bulge globular cluster HP~1

The globular cluster HP~1 is projected at only 3.33 degrees from the Galactic center. Together with its distance, this makes it one of the most central globular clusters in the Milky Way. It has a blue horizontal branch (BHB) and a metallicity of [Fe/H]~-1.0. This means that it probably is one of the oldest objects in the Galaxy. Abundance ratios can reveal the nucleosynthesis pattern of the first stars as well as the early chemical enrichment and early formation of stellar populations. High-resolution spectra obtained for six stars were analyzed to derive the abundances of the light elements C, N, O, Na, and Al, the alpha-elements Mg, Si, Ca, and Ti, and the heavy elements Sr, Y , Zr, Ba, La, and Eu.} High-resolution spectra of six red giants that are confirmed members of the bulge globular cluster HP~1 were obtained with the 8m VLT UT2-Kueyen telescope with the UVES spectrograph in FLAMES-UVES configuration. The spectroscopic parameter derivation was based on the excitation and ionization equilibrium of FeI and FeII. We confirm a mean metallicity of [Fe/H] = -1.06~0.10, by adding the two stars that were previously analyzed in HP~1. The alpha-elements O and Mg are enhanced by about +0.3<[O,Mg/Fe]<+0.5 dex, Si is moderately enhanced with +0.15<[Si/Fe]<+0.35dex, while Ca and Ti show lower values of -0.04<[Ca,Ti/Fe]<+0.28dex. The r-element Eu is also enhanced with [Eu/Fe]~+0.4, which together with O and Mg is indicative of early enrichment by type II supernovae. Na and Al are low, but it is unclear if Na-O are anticorrelated. The heavy elements are moderately enhanced, with -0.20<[La/Fe]<+0.43dex and 0.0<[Ba/Fe]<+0.75~dex, which is compatible with r-process formation. The spread in Y, Zr, Ba, and La abundances, on the other hand, appears to be compatible with the spinstar scenario or other additional mechanisms such as the weak r-process.Comment: 15 pages, 8 figures In press in Astronomy & Astrophysics (2016

Spin-Wave Theory of the Multiple-Spin Exchange Model on a Triangular Lattice in a Magnetic Field : 3-Sublattice Structures

We study the spin wave in the S=1/2 multiple-spin exchange model on a triangular lattice in a magnetic field within the linear spin-wave theory. We take only two-, three- and four-spin exchange interactions into account and restrict ourselves to the region where a coplanar three-sublattice state is the mean-field ground state. We found that the Y-shape ground state survives quantum fluctuations and the phase transition to a phase with a 6-sublattice structure occurs with softening of the spin wave. We estimated the quantum corrections to the ground state sublattice magnetizations due to zero-point spin-wave fluctuations.Comment: 8 pages, 20 figure

Forecasting Electricity Demand by Neural Networks and Definition of Inputs by Multi-Criteria Analysis

The planning of efficient policies based on forecasting electricity demand is essential to guarantee the continuity of energy supply for consumers. Some techniques for forecasting electricity demand have used specific procedures to define input variables, which can be particular to each case study. However, the definition of independent and casual variables is still an issue to be explored. There is a lack of models that could help the selection of independent variables, based on correlate criteria and level of importance integrated with artificial networks, which could directly impact the forecasting quality. This work presents a model that integrates a multi-criteria approach which provides the selection of relevant independent variables and artificial neural networks to forecast the electricity demand in countries. It provides to consider the particularities of each application. To demonstrate the applicability of the model a time series of electricity consumption from a southern region of Brazil was used. The dependent inputs used by the neural networks were selected using a traditional method called Wrapper. As a result of this application, with the multi-criteria ELECTRE I method was possible to recognize temperature and average evaporation as explanatory variables. When the variables selected by the multi-criteria approach were included in the predictive models, were observed more consistent results together with artificial neural networks, better than the traditional linear models. The Radial Basis Function Networks and Extreme Learning Machines stood out as potential techniques to be used integrated with a multi-criteria method to better perform the forecasting

Thermofield Dynamics for Twisted Poincare-Invariant Field Theories: Wick Theorem and S-matrix

Poincare invariant quantum field theories can be formulated on non-commutative planes if the statistics of fields is twisted. This is equivalent to state that the coproduct on the Poincare group is suitably twisted. In the present work we present a twisted Poincare invariant quantum field theory at finite temperature. For that we use the formalism of Thermofield Dynamics (TFD). This TFD formalism is extend to incorporate interacting fields. This is a non trivial step, since the separation in positive and negative frequency terms is no longer valid in TFD. In particular, we prove the validity of Wick's theorem for twisted scalar quantum field at finite temperature.Comment: v1: 25 pages, no figure v2: references added; typos corrected; typo in title correcte