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Purpose: Accurate detection and resection of the epileptogenic zone (EZ) in patients with long-term epilepsy-associated tumors (LEATs) are significantly correlated with favorable seizure prognosis. However, the relationship between tumors and the EZ remains unknown. This study aimed to evaluate the spatial relationship between LEATs and the EZ, as well as the electrophysiological features of LEATs. Methods: We retrospectively studied five patients with LEATs who underwent deep electrode implantation and EZ resection in the hospital. The clinical characteristics, surgical outcomes, localizing features and intracranial SEEG results were reviewed. Results: One female and four males (mean age: 25.2 years; median age: 24 years; range: 13–45 years) were included in the study. Five-to-eleven electrodes (mean: 8.4) were implanted per patient. The EZ was located in the tumor and nearby cortex in three cases and in the tumor and distant areas in two cases. Pathological examination revealed ganglioglioma in four cases, two of which were associated with hippocampal sclerosis, and the other case showed a multinodular and vacuolating neuronal tumor with gliosis. All patients were seizure-free for at least 24 months postoperatively. Conclusions: SEEG provides valuable insights into the electrophysiological mechanisms of LEATs. The EZ often contains brain tissue around the tumor. However, only a few cases, particularly those with temporoparietal occipital (TPO) area involvement, a long history of epilepsy and other abnormalities on MRI, such as hippocampal sclerosis and focal cortical dysplasia, may include distant areas. [ABSTRACT FROM AUTHOR]

The reversible intercalation of potassium ion on the graphite anode is one of the shining advantages for potassium ion batteries (PIBs). However, graphite anode suffers from capacity loss and cycling instability due to the increased desolvation energy and the slow transport of ions through the solid electrolyte interface (SEI) during low-temperature operation. In addition, graphite shows instability at high temperature due to the unstable SEI caused by electrolyte decomposition. To address these issues, our rational design is to tune an SEI with fast kinetics and stable property by introducing a weakly solvated electrolyte, 1,2-diethoxyethane, and a fluorinated additive, 1,1,2,2-tetrafluoroethyl-2,2,3,3-tetrafluoropropyl ether. The optimized electrolyte not only reduces the desolvation energy and increases the ion conductivity of the SEI at low temperatures but also forms a uniform SEI at high temperatures, enabling stable cycling over a wide temperature range. Impressively, at −5 °C, the specific capacity of the graphite anode reached 230 mA h g−1 with the capacity retention rate of 85.8% to room temperature. At 45 °C, it obtained a reversible specific capacity of 273 mA h g−1 and stabilized for 200 cycles. In addition, the full cells assembled with 2,3-dimethylene-3,4,9,10-tetracarboxydianhydride (PTCDA) as the cathode and graphite as the anode delivered promising performance at wide temperature. This work provides an advanced insight into wide-temperature graphite-based potassium ion batteries. [ABSTRACT FROM AUTHOR]

The rapid development of vehicle cooperative 3D object-detection technology has significantly improved the perception capabilities of autonomous driving systems. However, ship cooperative perception technology has received limited research attention compared to autonomous driving, primarily due to the lack of appropriate ship cooperative perception datasets. To address this gap, this paper proposes S2S-sim, a novel ship cooperative perception dataset. Ship navigation scenarios were constructed using Unity3D, and accurate ship models were incorporated while simulating sensor parameters of real LiDAR sensors to collect data. The dataset comprises three typical ship navigation scenarios, including ports, islands, and open waters, featuring common ship classes such as container ships, bulk carriers, and cruise ships. It consists of 7000 frames with 96,881 annotated ship bounding boxes. Leveraging this dataset, we assess the performance of mainstream vehicle cooperative perception models when transferred to ship cooperative perception scenes. Furthermore, considering the characteristics of ship navigation data, we propose a regional clustering fusion-based ship cooperative 3D object-detection method. Experimental results demonstrate that our approach achieves state-of-the-art performance in 3D ship object detection, indicating its suitability for ship cooperative perception. [ABSTRACT FROM AUTHOR]