Universal Charge-Radius Relation for Subatomic and Astrophysical Compact Objects

Electron-positron pair creation in supercritical electric fields limits the net charge of any static, spherical object, such as superheavy nuclei, strangelets, and Q-balls, or compact stars like neutron stars, quark stars, and black holes. For radii between $4\times10^2$ fm and $10^4$ fm the upper bound on the net charge is given by the universal relation $Z=0.71R_{fm}$, and for larger radii (measured in fm or km) $Z = 7 \times 10^{-5} R_{fm}^2 = 7 \times 10^{31} R_{km}^2$. For objects with nuclear density the relation corresponds to $Z \approx 0.7 A^{1/3}$ ($10^{8} < A < 10^{12}$) and $Z \approx 7\times10^{-5} A^{2/3}$ ($A > 10^{12}$), where $A$ is the baryon number. For some systems this universal upper bound improves existing charge limits in the literature

A novel bidding method for combined heat and power units in district heating systems

We propose a bidding method for the participation of combined heat and power (CHP) units in the day-ahead electricity market. More specifically, we consider a district heating system where heat can be produced by CHP units or heat-only units, e.g., gas or wood chip boilers. We use a mixed-integer linear program to determine the optimal operation of the portfolio of production units and storages on a daily basis. Based on the optimal production of subsets of units, we can derive the bidding prices and amounts of electricity offered by the CHP units for the day-ahead market. The novelty about our approach is that the prices are derived by iteratively replacing the production of heat-only units through CHP production. This results in an algorithm with a robust bidding strategy that does not increase the system costs even if the bids are not won. We analyze our method on a small realistic test case to illustrate our method and compare it with other bidding strategies from literature, which consider CHP units individually. The analysis shows that considering a portfolio of units in a district heating system and determining bids based on replacement of heat production of other units leads to better results

Operational planning and bidding for district heating systems with uncertain renewable energy production

In countries with an extended use of district heating (DH), the integrated operation of DH and power systems can increase the flexibility of the power system achieving a higher integration of renewable energy sources (RES). DH operators can not only provide flexibility to the power system by acting on the electricity market, but also profit from the situation to lower the overall system cost. However, the operational planning and bidding includes several uncertain components at the time of planning: electricity prices as well as heat and power production from RES. In this publication, we propose a planning method that supports DH operators by scheduling the production and creating bids for the day-ahead and balancing electricity markets. The method is based on stochastic programming and extends bidding strategies for virtual power plants to the DH application. The uncertain factors are considered explicitly through scenario generation. We apply our solution approach to a real case study in Denmark and perform an extensive analysis of the production and trading behaviour of the DH system. The analysis provides insights on how DH system can provide regulating power as well as the impact of uncertainties and renewable sources on the planning. Furthermore, the case study shows the benefit in terms of cost reductions from considering a portfolio of units and both markets to adapt to RES production and market states

High-order harmonic generation from polyatomic molecules including nuclear motion and a nuclear modes analysis

We present a generic approach for treating the effect of nuclear motion in the high-order harmonic generation from polyatomic molecules. Our procedure relies on a separation of nuclear and electron dynamics where we account for the electronic part using the Lewenstein model and nuclear motion enters as a nuclear correlation function. We express the nuclear correlation function in terms of Franck-Condon factors which allows us to decompose nuclear motion into modes and identify the modes that are dominant in the high-order harmonic generation process. We show results for the isotopes CH$_4$ and CD$_4$ and thereby provide direct theoretical support for a recent experiment [Baker {\it et al.}, Science {\bf 312}, 424 (2006)] that uses high-order harmonic generation to probe the ultra-fast structural nuclear rearrangement of ionized methane.Comment: 6 pages, 6 figure

Nonparametric Modeling of Dynamic Functional Connectivity in fMRI Data

Dynamic functional connectivity (FC) has in recent years become a topic of interest in the neuroimaging community. Several models and methods exist for both functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), and the results point towards the conclusion that FC exhibits dynamic changes. The existing approaches modeling dynamic connectivity have primarily been based on time-windowing the data and k-means clustering. We propose a non-parametric generative model for dynamic FC in fMRI that does not rely on specifying window lengths and number of dynamic states. Rooted in Bayesian statistical modeling we use the predictive likelihood to investigate if the model can discriminate between a motor task and rest both within and across subjects. We further investigate what drives dynamic states using the model on the entire data collated across subjects and task/rest. We find that the number of states extracted are driven by subject variability and preprocessing differences while the individual states are almost purely defined by either task or rest. This questions how we in general interpret dynamic FC and points to the need for more research on what drives dynamic FC.Comment: 8 pages, 1 figure. Presented at the Machine Learning and Interpretation in Neuroimaging Workshop (MLINI-2015), 2015 (arXiv:1605.04435