Switchable opening and closing of a liquid marble via ultrasonic levitation

Liquid marbles have promising applications in the field of microreactors, where the opening and closing of their surfaces plays a central role. We have levitated liquid water marbles using an acoustic levitator and, thereby, achieved the manipulation of the particle shell in a controlled manner. Upon increasing the sound intensity, the stable levitated liquid marble changes from a quasi-sphere to a flattened ellipsoid. Interestingly, a cavity on the particle shell can be produced on the polar areas, which can be completely healed when decreasing the sound intensity, allowing it to serve as a microreactor. The integral of the acoustic radiation pressure on the part of the particle surface protruding into air is responsible for particle migration from the center of the liquid marble to the edge. Our results demonstrate that the opening and closing of the liquid marble particle shell can be conveniently achieved via acoustic levitation, opening up a new possibility to manipulate liquid marbles coated with non-ferromagnetic particles

Model-based Offline Policy Optimization with Adversarial Network

Model-based offline reinforcement learning (RL), which builds a supervised transition model with logging dataset to avoid costly interactions with the online environment, has been a promising approach for offline policy optimization. As the discrepancy between the logging data and online environment may result in a distributional shift problem, many prior works have studied how to build robust transition models conservatively and estimate the model uncertainty accurately. However, the over-conservatism can limit the exploration of the agent, and the uncertainty estimates may be unreliable. In this work, we propose a novel Model-based Offline policy optimization framework with Adversarial Network (MOAN). The key idea is to use adversarial learning to build a transition model with better generalization, where an adversary is introduced to distinguish between in-distribution and out-of-distribution samples. Moreover, the adversary can naturally provide a quantification of the model's uncertainty with theoretical guarantees. Extensive experiments showed that our approach outperforms existing state-of-the-art baselines on widely studied offline RL benchmarks. It can also generate diverse in-distribution samples, and quantify the uncertainty more accurately.Comment: Accepted by 26th European Conference on Artificial Intelligence ECAI 202

Preparation and In Vitro/In Vivo Evaluation of Vinpocetine Elementary Osmotic Pump System

Preparation and in vitro and in vivo evaluation of vinpocetine (VIN) elementary osmotic pump (EOP) formulations were investigated. A method for the preparation of VIN elementary osmotic pump tablet was obtained by adding organic acid additives to increase VIN solubility. VIN was used as the active pharmaceutical ingredient, lactose and mannitol as osmotic agent. Citric acid was used as increasing API solubility and without resulting in the API degradation. It is found that the VIN release rate was increasing with the citric acid amount at a constant range. Cellulose acetate 398-3 was employed as semipermeable membrane containing polyethylene glycol 6000 and diethyl-o-phthalate as pore-forming agent and plasticizer for controlling membrane permeability. In addition, a clear difference between the pharmacokinetic patterns of VIN immediate release and VIN elementary osmotic pump formulations was revealed. The area under the plasma concentration-time curve after oral administration of elementary osmotic pump formulations was equivalent to VIN immediate release formulation. Furthermore, significant differences found for mean residence time, elimination half-life, and elimination rate constant values corroborated prolonged release of VIN from elementary osmotic pump formulations. These results suggest that the VIN osmotic pump controlled release tablets have marked controlled release characters and the VIN osmotic pump controlled release tablets and the normal tablets were bioequivalent

Divergent Changes in Plant Community Composition under 3-Decade Grazing Exclusion in Continental Steppe

An understanding of the factors controlling plant community composition will allow improved prediction of the responses of plant communities to natural and anthropogenic environmental change. Using monitoring data from 1980 to 2009, we quantified the changes in community composition in Leymus chinensis and Stipa grandis dominated grasslands in Inner Mongolia under long-term grazing-exclusion and free-grazing conditions, respectively. We demonstrated that the practice of long-term grazing exclusion has significant effects on the heterogeneity, the dominant species, and the community composition in the two grasslands. The community composition of L. chinensis and S. grandis grasslands exhibited directional changes with time under long-term grazing exclusion. Under free grazing, the L. chinensis community changed directionally with time, but the pattern of change was stochastic in the S. grandis community. We attributed the divergent responses to long-term grazing exclusion in the S. grandis and L. chinensis grasslands to litter accumulation and changes in the microenvironment after grazing exclusion, which collectively altered the growth and regeneration of the dominant species. The changes in the grazed grasslands were primarily determined by the selective feeding of sheep during long-term heavy grazing. Overall, the responses of the community composition of the Inner Mongolian grasslands to long-term grazing exclusion and heavy grazing were divergent, and depended primarily on the grassland type. Our findings provide new insights into the role of grazing in the maintenance of community structure and function and therefore have important implications for grassland management

Multi-Agent Game Abstraction via Graph Attention Neural Network

In large-scale multi-agent systems, the large number of agents and complex game relationship cause great difficulty for policy learning. Therefore, simplifying the learning process is an important research issue. In many multi-agent systems, the interactions between agents often happen locally, which means that agents neither need to coordinate with all other agents nor need to coordinate with others all the time. Traditional methods attempt to use pre-defined rules to capture the interaction relationship between agents. However, the methods cannot be directly used in a large-scale environment due to the difficulty of transforming the complex interactions between agents into rules. In this paper, we model the relationship between agents by a complete graph and propose a novel game abstraction mechanism based on two-stage attention network (G2ANet), which can indicate whether there is an interaction between two agents and the importance of the interaction. We integrate this detection mechanism into graph neural network-based multi-agent reinforcement learning for conducting game abstraction and propose two novel learning algorithms GA-Comm and GA-AC. We conduct experiments in Traffic Junction and Predator-Prey. The results indicate that the proposed methods can simplify the learning process and meanwhile get better asymptotic performance compared with state-of-the-art algorithms.Comment: Accepted by AAAI202

Weak ferromagnetism and spin glass state with nano-sized nickel carbide

Ni3C nanoparticles of about 40 nm have been studied experimentally to exhibit weak ferromagnetic (FM), spin-glass (SG) and paramagnetic (PM) properties. The freezing temperature of the SG phase at zero applied field is determined as, TF0 ~ 11.0 K. At T > TF0, a very weak ferromagnetism has been observed over a PM background. The Curie temperature, TC, is shown to exceed 300 K and the ferromagnetism at 300 K is determined as about 0.02 emu/g (~6.7*10^{-4}mu_B per Ni3C formula unit) by subtracting the background paramagnetism. An anomalous dip appears in the temperature dependent coercivity, HC(T), near the freezing temperature, TF0. It reflects a distortedly reduced coercivity in the M(H) hysteresis loop measured at T = TF0 with the applied sweeping field around H = 0. This is attributable to the exchange coupling effect between the SG and the weak FM phases. The possible origin of the magnetic moments that account for the observed FM, SG and PM properties is discussed.Comment: 25 pages, 8 figures, 1 table, J Appl Phys In pres