Adaptive probabilistic load forecasting for individual buildings

Building-level load forecasting has become essential with the support of fine-grained data collected by widely deployed smart meters. It acts as a basis for arranging distributed energy resources, implementing demand response, etc. Compared to aggregated-level load, the electric load of an individual building is more stochastic and thus spawns many probabilistic forecasting methods. Many of them resort to artificial neural networks (ANN) to build forecasting models. However, a well-designed forecasting model for one building may not be suitable for others, and manually designing and tuning optimal forecasting models for various buildings are tedious and time-consuming. This paper proposes an adaptive probabilistic load forecasting model to automatically generate high-performance NN structures for different buildings and produce quantile forecasts for future loads. Specifically, we cascade the long short term memory (LSTM) layer with the adjusted Differential ArchiTecture Search (DARTS) cell and use the pinball loss function to guide the model during the improved model fitting process. A case study on an open dataset shows that our proposed model has superior performance and adaptivity over the state-of-the-art static neural network model. Besides, the improved fitting process of DARTS is proved to be more time-efficient than the original one

Simulating Heliospheric and Solar Particle Diffusion using the Parker Spiral Geometry

Cosmic Ray transport in curved background magnetic fields is investigated using numerical Monte-Carlo simulation techniques. Special emphasis is laid on the Solar system, where the curvature of the magnetic field can be described in terms of the Parker spiral. Using such geometries, parallel and perpendicular diffusion coefficients have to be re-defined using the arc length of the field lines as the parallel displacement and the distance between field lines as the perpendicular displacement. Furthermore, the turbulent magnetic field is incorporated using a WKB approach for the field strength. Using a test-particle simulation, the diffusion coefficients are then calculated by averaging over a large number of particles starting at the same radial distance from the Sun and over a large number of turbulence realizations, thus enabling one to infer the effects due to the curvature of the magnetic fields and associated drift motions.Comment: accepted for publication at Journal of Geophysical Research - Space Physic

Sharp changes of solar wind ion flux and density within and outside current sheets

Analysis of the Interball-1 spacecraft data (1995-2000) has shown that the solar wind ion flux sometimes increases or decreases abruptly by more than 20% over a time period of several seconds or minutes. Typically, the amplitude of such sharp changes in the solar wind ion flux (SCIFs) is larger than 0.5x10^8 cm^-2 s^-1. These sudden changes of the ion flux were also observed by the Solar Wind Experiment (SWE), on board the WIND spacecraft, as the solar wind density increases and decreases with negligible changes in the solar wind velocity. SCIFs occur irregularly at 1 AU, when plasma flows with specific properties come to the Earth's orbit. SCIFs are usually observed in slow, turbulent solar wind with increased density and interplanetary magnetic field strength. The number of times SCIFs occur during a day is simulated using the solar wind density, magnetic field, and their standard deviations as input parameters for a period of 5 years. A correlation coefficient of ~0.7 is obtained between the modelled and the experimental data. It is found that SCIFs are not associated with coronal mass ejections (CMEs), corotating interaction regions (CIRs), or interplanetary shocks; however, 85% of the sector boundaries are surrounded by SCIFs. The properties of the solar wind plasma for days with 5 or more SCIF observations are the same as those of the solar wind plasma at the sector boundaries. One possible explanation for the occurrence of SCIFs (near sector boundaries) is magnetic reconnection at the heliospheric current sheet or local current sheets. Other probable causes of SCIFs (inside sectors) are turbulent processes in the slow solar wind and at the crossings of flux tubes.Comment: 33 pages, 8 figures, 6 tables, Solar Physics 2011, in pres

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Research on Claw Motion Characteristics and Cavitation Bubbles of Snapping Shrimp

Snapping shrimp produces a high-speed jet through the rapid closure of the snapper claw, which stimulates the formation of cavitation bubbles of various shapes. In order to explore the fast motion characteristics of snapper claw, the formation and change process of cavitation, and the physical principles underlying the biological phenomena, the equivalent model of snapper claw was constructed through CT scanning technology. A high-speed camera was used to capture the claw’s motion characteristics, thereby simulating the production of cavitation bubbles by snapping shrimp. The results show that the rotation speeds of different species of snapping shrimps are different, as well as their motion characteristics. Cavitation is formed by the interaction of the pressure drop caused by the vortex at the nozzle with the inertia of the liquid inside the socket. Under the influence of the jet, the shapes of bubbles change from ring to cone, and eventually collapse into bubble clouds

EEG-Based Emotion Recognition With Emotion Localization via Hierarchical Self-Attention

Emotion recognition based on electroencephalography (EEG) has attracted significant attention due to its wide range of applications, especially in Human-Computer Interaction(HCI). Previous research treats different segments of EEG signals uniformly, ignoring the fact that emotions are unstable and discrete during an extended period. In this paper, we propose a novel two-step spatial-temporal emotion recognition framework. First, considering that the human emotion has not only 'short-term continuity' but also 'long-term similarity', we propose a hierarchical self-attention network to jointly model local and global temporal information, so as to localize most related segments and reduce the influence of noise at the temporal level. Second, in order to extract discriminative features at the spatial level to enhance the emotion recognition performance, we further employ the squeeze-and-excitation module (SE module) along with the channel correlation loss (CC-Loss) to select the most task-related channels. We also define a new task called emotion localization, which aims to localize fragments with stronger emotions. We evaluate the proposed method on the proposed emotion localization task and typical emotion recognition task with three publicly available datasets, i.e., SEED, DEAP, and MAHNOB-HCI. The experimental results demonstrate that the proposed approach outperforms state-of-the-art methods.</p

Bottom-up Approach Design, Band Structure, and Lithium Storage Properties of Atomically Thin γ‑FeOOH Nanosheets

As a novel class of soft matter, two-dimensional (2D) atomic nanosheet-like crystals have attracted much attention for energy storage devices due to the fact that nearly all of the atoms can be exposed to the electrolyte and involved in redox reactions. Herein, atomically thin γ-FeOOH nanosheets with a thickness of ∼1.5 nm are synthesized in a high yield, and the band and electronic structures of the γ-FeOOH nanosheet are revealed using density-functional theory calculations for the first time. The rationally designed γ-FeOOH@rGO composites with a heterostacking structure are used as an anode material for lithium-ion batteries (LIBs). A high reversible capacity over 850 mAh g^–1 after 100 cycles at 200 mA g^–1 is obtained with excellent rate capability. The remarkable performance is attributed to the ultrathin nature of γ-FeOOH nanosheets and 2D heterostacking structure, which provide the minimized Li⁺ diffusion length and buffer zone for volume change. Further investigation on the Li storage electrochemical mechanism of γ-FeOOH@rGO indicates that the charge–discharge processes include both conversion reaction and capacitive behavior. This synergistic effect of conversion reaction and capacitive behavior originating from 2D heterostacking structure casts new light on the development of high-energy anode materials