A Reinvestigation of Crustal Thickness in the Tibetan Plateau Using Absolute Gravity, GPS and GRACE Data

The geodetic evidence of the uplift and crustal thickness of the Tibetan Plateau has been presented for the first time (Sun et al. 2009) using gravity and GPS observations. In this paper, we reinvestigate this tectonic deformation in more detail using GRACE data and taking the GIA effect into account. We first summarize the previous gravity and GPS observations and a local gravity network in the Dali County. The comparison between the surface absolute gravity and space GRACE gravity measurements shows that they are harmonic, agree well. Finally, we assume that the residual gravity change reflects material transport accompanying vertical movements on the crustal bottom; the crustal thickening rate is inferred as 1.9 ¡_ 1.4 cm yr-1. As the crust thickens, the mass of a column of rock beneath the station decreases because mantle is displaced by crust, causing a reduction in gravity

A Learning-based Adaptive Compliance Method for Symmetric Bi-manual Manipulation

Symmetric bi-manual manipulation is essential for various on-orbit operations due to its potent load capacity. As a result, there exists an emerging research interest in the problem of achieving high operation accuracy while enhancing adaptability and compliance. However, previous works relied on an inefficient algorithm framework that separates motion planning from compliant control. Additionally, the compliant controller lacks robustness due to manually adjusted parameters. This paper proposes a novel Learning-based Adaptive Compliance algorithm (LAC) that improves the efficiency and robustness of symmetric bi-manual manipulation. Specifically, first, the algorithm framework combines desired trajectory generation with impedance-parameter adjustment to improve efficiency and robustness. Second, we introduce a centralized Actor-Critic framework with LSTM networks, enhancing the synchronization of bi-manual manipulation. LSTM networks pre-process the force states obtained by the agents, further ameliorating the performance of compliance operations. When evaluated in the dual-arm cooperative handling and peg-in-hole assembly experiments, our method outperforms baseline algorithms in terms of optimality and robustness.Comment: 12 pages, 10 figure

Cleaning effects due to shape oscillation of bubbles over a rigid boundary

Recent experiments have revealed the interesting cleaning effects that take place due to the shape mode oscillation of bubbles over a rigid boundary. While a microbubble was undertaking shape oscillation moving over a bacterial biofilm, it removed the contaminants from the boundary and created a clean path through the biofilm. This demonstrated much higher cleaning efficiency than that associated with the volume oscillation of cavitation bubbles; however, the mechanism is unknown. Here, we study this phenomenon using the boundary integral method with the viscous effects modeled using the viscous potential flow theory and the compressible effects using the weakly compressible theory. The viscous stress at the rigid boundary is approximated using the boundary layer theory. We observed that the natural frequencies of shape mode oscillation decrease significantly due to the presence of the boundary. The shear stress at the boundary due to the shape oscillation of a nearby bubble is at least 20 times higher than that due to volume oscillation with the same energy and is significant only within the area directly beneath the bubble. This is explained by the notably faster decay for higher shape modes of the kinetic energy in the fluid as the distance to the center of the bubble r increases with the induced velocity of mode k decaying at a rate of O(r-(k+ 2)) away from the bubble. These results achieve excellent agreement with the intriguing cleaning effects first observed in the experiment and explain the mechanism behind this new highly efficient method of cleaning

Automatic Recognition and Classification of Future Work Sentences from Academic Articles in a Specific Domain

Future work sentences (FWS) are the particular sentences in academic papers that contain the author's description of their proposed follow-up research direction. This paper presents methods to automatically extract FWS from academic papers and classify them according to the different future directions embodied in the paper's content. FWS recognition methods will enable subsequent researchers to locate future work sentences more accurately and quickly and reduce the time and cost of acquiring the corpus. The current work on automatic identification of future work sentences is relatively small, and the existing research cannot accurately identify FWS from academic papers, and thus cannot conduct data mining on a large scale. Furthermore, there are many aspects to the content of future work, and the subdivision of the content is conducive to the analysis of specific development directions. In this paper, Nature Language Processing (NLP) is used as a case study, and FWS are extracted from academic papers and classified into different types. We manually build an annotated corpus with six different types of FWS. Then, automatic recognition and classification of FWS are implemented using machine learning models, and the performance of these models is compared based on the evaluation metrics. The results show that the Bernoulli Bayesian model has the best performance in the automatic recognition task, with the Macro F1 reaching 90.73%, and the SCIBERT model has the best performance in the automatic classification task, with the weighted average F1 reaching 72.63%. Finally, we extract keywords from FWS and gain a deep understanding of the key content described in FWS, and we also demonstrate that content determination in FWS will be reflected in the subsequent research work by measuring the similarity between future work sentences and the abstracts

Ultrafine-Grained Materials Fabrication with High Pressure Torsion and Simulation of Plastic Deformation Inhomogeneous Characteristics

Utilization of severe plastic deformation (SPD) methods has provided a convenient approach for producing ultrafine-grained (UFG) materials exhibiting outstanding characteristics especially mechanical properties. HPT as one of the SPD methods can lead both to smaller grains and to a higher fraction of high-angle grain boundaries, which is an especially attractive procedure by researchers. In order to understand the nonlinearities relationship between the mechanical properties and the developed strain during plastic deformation, local deformation analysis using the finite element methodwas applied for the HPT process. In this chapter, results are reported of an investigation on the deformed microstructure and mechanical properties of different materials samples during the HPT process using experiments and FEM simulations. Simulation results indicate that the disks show inhomogeneity development and distribution of strain and stress during the plastic deformation. Microstructure and hardness investigation results can give a well support to verify the rules of inhomogenous plastic deformation in the early stage of the HPT disks. Furthermore, the friction and anvil geometry play important roles in the homogeneity of the deformation. After the hollow cone high pressure torsion (HC-HPT), the thermal stability of Zr64.13Cu15.75Ni10.12Al10 BMGs is enhanced, while the elastic modulus of BMG will be decreased

Probiotics and Alcoholic Liver Disease: Treatment and Potential Mechanisms

Despite extensive research, alcohol remains one of the most common causes of liver disease in the United States. Alcoholic liver disease (ALD) encompasses a broad spectrum of disorders, including steatosis, steatohepatitis, and cirrhosis. Although many agents and approaches have been tested in patients with ALD and in animals with experimental ALD in the past, there is still no FDA (Food and Drug Administration) approved therapy for any stage of ALD. With the increasing recognition of the importance of gut microbiota in the onset and development of a variety of diseases, the potential use of probiotics in ALD is receiving increasing investigative and clinical attention. In this review, we summarize recent studies on probiotic intervention in the prevention and treatment of ALD in experimental animal models and patients. Potential mechanisms underlying the probiotic function are also discussed

Groundwater Diffuse Recharge and its Response to Climate Changes in Semi-Arid Northwestern China

Understanding the processes and rates of groundwater recharge in arid and semi-arid areas is crucial for utilizing and managing groundwater resources sustainably. We obtained three chloride profiles of the unsaturated-zone in the desert/loess transition zone of northwestern China and reconstructed the groundwater recharge variations over the last 11, 21, and 37 years, respectively, using the generalized chloride mass balance (GCMB) method. The average recharge rates were 43.7, 43.5, and 45.1 mm yr-1, respectively, which are similar to those evaluated by the chloride mass balance (CMB) or GCMB methods in other semi-arid regions. The results indicate that the annual recharge rates were not in complete linear proportion to the corresponding annual precipitations, although both exhibited descending tendencies on the whole. Comparisons between the daily precipitation aggregate at different intensity and recharge rates reveal that the occurrence of relatively heavy daily precipitation per year may contribute to such nonlinearity between annual precipitation and recharge. The possible influences of vegetation cover alterations following precipitation change cannot be excluded as well. The approximately negative correlation between the average annual recharge and temperature suggests that changes in temperature have had significant influences on recharge