In this paper we discuss thermostatting using stochastic methods for molecular simulations where constraints are present. For so-called impulsive thermostats, like the Andersen thermostat, the equilibrium temperature will differ significantly from the imposed temperature when a limited number of particles are picked and constraints are applied. We analyze this problem and give two rigorous solutions for it. A correct general treatment of impulsive stochastic thermostatting, including pairwise dissipative particle dynamics and stochastic forcing in the presence of constraints, is given and it is shown that the constrained canonical distribution is sampled rigorously. We discuss implementation issues such as second order Trotter expansions. The method is shown to rigorously maintain the correct temperature for the case of extended simple point charge (SPC/E) water simulations.
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http://dx.doi.org/10.1021/ct500380x | DOI Listing |
Sensors (Basel)
December 2024
Department of Mobile Systems Engineering, Dankook University, Yongin 16890, Republic of Korea.
As proximity-aware services among devices such as sensors, IoT devices, and user equipment are expected to facilitate a wide range of new applications in the beyond 5G and 6G era, managing heterogeneous environments with diverse node capabilities becomes essential. This paper analytically models and characterizes the performance of heterogeneous random access-based wireless mutual broadcast (RA-WMB) with distinct transmit (Tx) power levels, leveraging a marked Poisson point process to account for nodes' various Tx power. In particular, this study enables the performance of RA-WMB with heterogeneous Tx power to be represented in terms of the performance of RA-WMB with a common Tx power by deriving an equivalent Tx power based on the probability distribution of heterogeneous Tx power and the path loss exponent.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Computer Science and Engineering, Northeastern University, Shenyang 110000, China.
Natural disasters cause significant losses. Unmanned aerial vehicles (UAVs) are valuable in rescue missions but need to offload tasks to edge servers due to their limited computing power and battery life. This study proposes a task offloading decision algorithm called the multi-agent deep deterministic policy gradient with cooperation and experience replay (CER-MADDPG), which is based on multi-agent reinforcement learning for UAV computation offloading.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Mechanical Engineering Department, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel.
Several stochastic H∞ filters for estimating the attitude of a rigid body from line-of-sight measurements and rate gyro readings are developed. The measurements are corrupted by white noise with unknown variances. Our approach consists of estimating the quaternion while attenuating the transmission gain from the unknown variances and initial errors to the current estimation error.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Mathematics and Statistics, Guangdong University of Technology, Guangzhou 510006, China.
This paper proposes the fixed-time prescribed performance optimal consensus control method for stochastic nonlinear multi-agent systems with sensor faults. The consensus error converges to the prescribed performance bounds in fixed-time by an improved performance function and coordinate transformation. Due to the unknown faults in sensors, the system states cannot be gained correctly; therefore, an adaptive compensation strategy is constructed based on the approximation capabilities of neural networks to solve the negative impact of sensor failures.
View Article and Find Full Text PDFMicroorganisms
December 2024
Key Laboratory of Integrated Rice-Fish Farming Ecology, Ministry of Agriculture and Rural Affairs, Freshwater Fisheries Research Center, Chinese Academy of Fishery Sciences, Wuxi 214081, China.
In aquatic benthic environments, benthic organisms have been found to regulate important biogeochemical characteristics and perform key ecosystem functions. To further explore the ecological impact of the snail 's, presence on the benthic environment, we employed high-throughput sequencing technology to investigate its effects on the bacterial, fungal, and protist communities in sediment and their intrinsic interactions. Our findings revealed that 's presence significantly enhanced the diversity and evenness of the fungal community while simultaneously decreasing the diversity and richness of the protist community, and it also altered the composition and relative abundance of the dominant phyla across the bacterial, fungal, and protist communities.
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