In recent years, panel PET is an interesting field in medical imaging. But the major obstacle of panel PET is the limited view problem. Images reconstructed by traditional algorithms will suffer serious artifacts. Time-of-flight (TOF) information can be incorporated into the image reconstruction to remove the artifacts. However, the best system timing resolution available in current commercial PET scanners is about 500 ps, which is not precise enough to achieve satisfactory images. In this paper, a list mode reconstruction algorithm coupled with non-local means regularizer was formulated to improve the panel PET image quality. It incorporates the anatomical information into the non-local means regularizer and modifies the reconstructed image while it is updating. The results show that our proposed method could remove the distortions effectively without TOF information.
We propose a score-based DAG structure learning method for time-series data that captures linear, nonlinear, lagged and instantaneous relations among variables while ensuring acyclicity throughout the entire graph. The proposed method extends nonparametric NOTEARS, a recent continuous optimization approach for learning nonparametric instantaneous DAGs. The proposed method is faster than constraint-based methods using nonlinear conditional independence tests. We also promote the use of optimization constraints to incorporate prior knowledge into the structure learning process. A broad set of experiments with simulated data demonstrates that the proposed method discovers better DAG structures than several recent comparison methods. We also evaluate the proposed method on complex real-world data acquired from NHL ice hockey games containing a mixture of continuous and discrete variables. The code is available at this https URL.
We consider a stochastic one‐predator‐two‐prey harvesting model with time delays and Lévy jumps in this paper. Using the comparison theorem of stochastic differential equations and asymptotic approaches, sufficient conditions for persistence in mean and extinction of three species are derived. By analyzing the asymptotic invariant distribution, we study the variation of the persistent level of a population. Then we obtain the conditions of global attractivity and stability in distribution. Furthermore, making use of Hessian matrix method and optimal harvesting theory of differential equations, the explicit forms of optimal harvesting effort and maximum expectation of sustainable yield are obtained. Some numerical simulations are given to illustrate the theoretical results.
Uneven local electric fields and limited nucleation sites at the reaction interface can lead to the formation of hazardous lithium (Li) dendrites, posing a significant safety risk and impeding the practical utilization of Li metal anodes (LMAs). Here, we present a method utilizing atomic layer deposition (ALD) to create lithiophilic titanium nitride (TiN) sites on carbon nanotubes (CNTs) surfaces, integrated with nanocellulose to form a lithiophilic interlayer (NFCP@TN). This interlayer, which is highly flexible and electrolyte-wettable, functions as a current collector and host material for LMAs. The uniform deposition of Li is facilitated by the synergistic interplay of the lithiophilic active sites TiN, the conductive CNT network, and excellent electrolyte wettability of nanocellulose. As a result, Li preferentially adsorbs on TiN sheaths with lower diffusion barriers, leading to controlled nucleation sites and dendrite-free Li deposition. Furthermore, the well-designed NFCP@TN interlayer exhibits exceptional electrochemical performance and significantly extended cycle life when paired LMA with high areal capacity NCM811 (5.0 mAh cm−2) electrodes.
With rapid development of renewable energy, especially wind and solar energy, long distance transmission will be the fundamental way for new energy consumption because of the insufficient consumptive ability of local grid. This paper proposed a wind-solar-thermal hybrid system long distance consumption by ultra-high voltage (UHV) transmission lines, which not only make full use of the complementary nature of wind and solar energy in time and region, but also take advantage of good stability of thermal power plant to improve system reliability. A bilevel optimization based on non-cooperative game method was utilized to maximize profit of power plants by changing bidding strategies, where power plants in the transmitting end system are at the upper level and receiving end system are at the lower level. Besides, cost model considering with wheeling cost, carbon emissions cost and government subsidies was presented. Finally, several simulations were implemented and used to verify the feasibility of the non-cooperative game based bilevel optimization method.
