We present NeuroSim, the prototype of a training simulator for open surgical interventions on the human brain. The simulator is based on virtual reality and uses real-time simulation algorithms to interact with models generated from MRT- or CT-datasets. NeuroSim provides a native interface by using a real surgical microscope and original instruments tracked by a combination of inertial measurement units and optical tracking. Conclusively an immersive environment is generated. In a first step the navigation in an open surgery setup as well as the hand-eye coordination through a microscope can be trained. Due to its modular design further training modules and extensions can be integrated. NeuroSim has been developed in cooperation with the neurosurgical clinic of the University of Heidelberg and the VRmagic GmbH in Mannheim.
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J Robot Surg
January 2025
Department of Thoracic Surgery, West China Hospital, Sichuan University, No. 37, Guoxue Lane, Wuhou District, Chengdu, 610041, Sichuan Province, China.
Sci Rep
January 2025
Key Laboratory of Gas and Fire Control for Mines, Ministry of Education, Xuzhou, 221116, China.
Confined space fires could easily cause serious casualties and property damage, and foam is an effective means of preventing confined space fires. The existing foam generator does not have both momentum and foam expansion rate (FER) and is poorly suited to confined spaces. In order to develop a foam generator suitable for confined space fire protection, an in-depth analysis of the physical foaming characteristics of self-suction foam is required, and the structure of the foam generator is optimized accordingly.
View Article and Find Full Text PDFThe increasing availability of coarse-scale climate simulations and the need for ready-to-use high-resolution variables drive the climate community to the challenge of reducing computational resources and time for downscaling purposes. To this end, statistical downscaling is gaining interest as a potential strategy for integrating high-resolution climate information obtained through dynamical downscaling over limited years, providing a clear understanding of the gains and losses in combining dynamical and statistical downscaling. In this regard, several questions can be raised: (i) what is the performance of statistical downscaling, assuming dynamical downscaling as a reference over a shared time window; (ii) how much the performance of statistical downscaling is affected by changes in the number of years available for training; (iii) how does the climate normal considered for the training affect the predictions.
View Article and Find Full Text PDFSci Rep
January 2025
Water Conservancy Project & Civil Engineering College, Tibet Agriculture & Animal Husbandry University, Linzhi, 860000, China.
The paper addresses the economic operation optimization problem of photovoltaic charging-swapping-storage integrated stations (PCSSIS) in high-penetration distribution networks. It proposes a dual-layer optimization scheduling model for PCSSIS clusters and distribution network systems. Firstly, a master-slave game model is constructed.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Chemistry, Theoretical Chemistry Institute, University of Wisconsin-Madison, Madison, WI, 53706, USA.
Identifying transitional states is crucial for understanding protein conformational changes that underlie numerous biological processes. Markov state models (MSMs), built from Molecular Dynamics (MD) simulations, capture these dynamics through transitions among metastable conformational states, and have demonstrated success in studying protein conformational changes. However, MSMs face challenges in identifying transition states, as they partition MD conformations into discrete metastable states (or free energy minima), lacking description of transition states located at the free energy barriers.
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