Probabilistic Forecasting and Simulation of Electricity Markets via Online Dictionary Learning

The problem of probabilistic forecasting and online simulation of real-time electricity market with stochastic generation and demand is considered. By exploiting the parametric structure of the direct current optimal power flow, a new technique based on online dictionary learning (ODL) is proposed. The ODL approach incorporates real-time measurements and historical traces to produce forecasts of joint and marginal probability distributions of future locational marginal prices, power flows, and dispatch levels, conditional on the system state at the time of forecasting. Compared with standard Monte Carlo simulation techniques, the ODL approach offers several orders of magnitude improvement in computation time, making it feasible for online forecasting of market operations. Numerical simulations on large and moderate size power systems illustrate its performance and complexity features and its potential as a tool for system operators

Elevation Extraction from Spaceborne SAR Tomography Using Multi-Baseline COSMO-SkyMed SAR Data

SAR tomography (TomoSAR) extends SAR interferometry (InSAR) to image a complex 3D scene with multiple scatterers within the same SAR cell. The phase calibration method and the super-resolution reconstruction method play a crucial role in 3D TomoSAR imaging from multi-baseline SAR stacks, and they both influence the accuracy of the 3D SAR tomographic imaging results. This paper presents a systematic processing method for 3D SAR tomography imaging. Moreover, with the newly released TanDEM-X 12 m DEM, this study proposes a new phase calibration method based on SAR InSAR and DEM error estimation with the super-resolution reconstruction compressive sensing (CS) method for 3D TomoSAR imaging using COSMO-SkyMed Spaceborne SAR data. The test, fieldwork, and results validation were executed at Zipingpu Dam, Dujiangyan, Sichuan, China. After processing, the 1 m resolution TomoSAR elevation extraction results were obtained. Against the terrestrial Lidar ‘truth’ data, the elevation results were shown to have an accuracy of 0.25 ± 1.04 m and a RMSE of 1.07 m in the dam area. The results and their subsequent validation demonstrate that the X band data using the CS method are not suitable for forest structure reconstruction, but are fit for purpose for the elevation extraction of manufactured facilities including buildings in the urban area

Inhibition of SARS Pseudovirus Cell Entry by Lactoferrin Binding to Heparan Sulfate Proteoglycans

It has been reported that lactoferrin (LF) participates in the host immune response against Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) invasion by enhancing NK cell activity and stimulating neutrophil aggregation and adhesion. We further investigated the role of LF in the entry of SARS pseudovirus into HEK293E/ACE2-Myc cells. Our results reveal that LF inhibits SARS pseudovirus infection in a dose-dependent manner. Further analysis suggested that LF was able to block the binding of spike protein to host cells at 4°C, indicating that LF exerted its inhibitory function at the viral attachment stage. However, LF did not disrupt the interaction of spike protein with angiotensin-converting enzyme 2 (ACE2), the functional receptor of SARS-CoV. Previous studies have shown that LF colocalizes with the widely distributed cell-surface heparan sulfate proteoglycans (HSPGs). Our experiments have also confirmed this conclusion. Treatment of the cells with heparinase or exogenous heparin prevented binding of spike protein to host cells and inhibited SARS pseudovirus infection, demonstrating that HSPGs provide the binding sites for SARS-CoV invasion at the early attachment phase. Taken together, our results suggest that, in addition to ACE2, HSPGs are essential cell-surface molecules involved in SARS-CoV cell entry. LF may play a protective role in host defense against SARS-CoV infection through binding to HSPGs and blocking the preliminary interaction between SARS-CoV and host cells. Our findings may provide further understanding of SARS-CoV pathogenesis and aid in treatment of this deadly disease

Inorganic nanozyme with combined self-oxygenation/degradable capabilities for sensitized cancer immunochemotherapy

Recently emerged cancer immunochemotherapy has provided enormous new possibilities to replace traditional chemotherapy in fighting tumor. However, the treatment efficacy is hampered by tumor hypoxia-induced immunosuppression in tumor microenvironment (TME). Herein, we fabricated a self-oxygenation/degradable inorganic nanozyme with a core–shell structure to relieve tumor hypoxia in cancer immunochemotherapy. By integrating the biocompatible CaO2 as the oxygen-storing component, this strategy is more effective than the earlier designed nanocarriers for delivering oxygen or H2O2, and thus provides remarkable oxygenation and long-term capability in relieving hypoxia throughout the tumor tissue. Consequently, in vivo tests validate that the delivery system can successfully relieve hypoxia and reverse the immunosuppressive TME to favor antitumor immune responses, leading to enhanced chemoimmunotherapy with cytotoxic T lymphocyte-associated antigen 4 blockade. Overall, a facile, robust and effective strategy is proposed to improve tumor oxygenation by using self-decomposable and biocompatible inorganic nanozyme reactor, which will not only provide an innovative pathway to relieve intratumoral hypoxia, but also present potential applications in other oxygen-favored cancer therapies or oxygen deficiency-originated diseases

The interface states in gate-all-around transistors (GAAFETs)

The atomic-level structural detail and the quantum effects are becoming crucial to device performance as the emerging advanced transistors, representatively GAAFETs, are scaling down towards sub-3nm nodes. However, a multiscale simulation framework based on atomistic models and ab initio quantum simulation is still absent. Here, we propose such a simulation framework by fulfilling three challenging tasks, i.e., building atomistic all-around interfaces between semiconductor and amorphous gate-oxide, conducting large-scale first-principles calculations on the interface models containing up to 2796 atoms, and finally bridging the state-of-the-art atomic level calculation to commercial TCAD. With this framework, two unnoticed origins of interface states are demonstrated, and their tunability by changing channel size, orientation and geometry is confirmed. The quantitative study of interface states and their effects on device performance explains why the nanosheet channel is preferred in industry. We believe such a bottom-up framework is necessary and promising for the accurate simulation of emerging advanced transistors

Design and analysis of fractional factorial experiments from the viewpoint of computational algebraic statistics

We give an expository review of applications of computational algebraic statistics to design and analysis of fractional factorial experiments based on our recent works. For the purpose of design, the techniques of Gr\"obner bases and indicator functions allow us to treat fractional factorial designs without distinction between regular designs and non-regular designs. For the purpose of analysis of data from fractional factorial designs, the techniques of Markov bases allow us to handle discrete observations. Thus the approach of computational algebraic statistics greatly enlarges the scope of fractional factorial designs.Comment: 16 page

Effects of electron-phonon coupling in the Kondo regime of a two-orbital molecule

We study the interplay between strong electron-electron and electron-phonon interactions within a two-orbital molecule coupled to metallic leads, taking into account Holstein-like coupling of a local phonon mode to the molecular charge as well as phonon-mediated interorbital tunneling. By combining canonical transformations with numerical renormalization-group calculations to address the interactions nonperturbatively and on equal footing, we obtain a comprehensive description of the system's many-body physics in the anti-adiabatic regime where the phonons adjust rapidly to changes in the orbital occupancies, and are thereby able to strongly affect the Kondo physics. The electron-phonon interactions strongly modify the bare orbital energies and the Coulomb repulsion between electrons in the molecule, and tend to inhibit tunneling of electrons between the molecule and the leads. The consequences of these effects are considerably more pronounced when both molecular orbitals lie near the Fermi energy of the leads than when only one orbital is active. In situations where a local moment forms on the molecule, there is a crossover with increasing electron-phonon coupling from a regime of collective Kondo screening of the moment to a limit of local phonon quenching. At low temperatures, this crossover is associated with a rapid increase in the electronic occupancy of the molecule as well as a marked drop in the linear electrical conductance through the single-molecule junction.Comment: 17 pages, 13 figure