Piecewise exact solution of nonlinear momentum conservation equation with unconditional stability for time increment

Exact solution is adopted for computation of the inviscid Burgers equation on finite difference grid. Initial condition and following computed values of the independent variable are assumed to be piecewisely linear between fixed grid points, and local exact solution is used to find the value at the next time step at each grid point. Comparisons of Piecewise Exact Solution Method (PESM), existing upwind scheme, and the analytic solution show that the present method is more accurate than the upwind scheme. The unconditional stability is a strong merit of this method and is shown with a test result

Role of generic scale invariance in a Mott transition from a U(1) spin-liquid insulator to a Landau Fermi-liquid metal

We investigate the role of generic scale invariance in a Mott transition from a U(1) spin-liquid insulator to a Landau Fermi-liquid metal, where there exist massless degrees of freedom in addition to quantum critical fluctuations. Here, the Mott quantum criticality is described by critical charge fluctuations, and additional gapless excitations are U(1) gauge-field fluctuations coupled to a spinon Fermi surface in the spin-liquid state, which turn out to play a central role in the Mott transition. An interesting feature of this problem is that the scaling dimension of effective leading local interactions between critical charge fluctuations differs from that of the coupling constant between U(1) gauge fields and matter-field fluctuations in the presence of a Fermi surface. As a result, there appear dangerously irrelevant operators, which can cause conceptual difficulty in the implementation of renormalization group (RG) transformations. Indeed, we find that the curvature term along the angular direction of the spinon Fermi surface is dangerously irrelevant at this spin-liquid Mott quantum criticality, responsible for divergence of the self-energy correction term in U(1) gauge-field fluctuations. Performing the RG analysis in the one-loop level based on the dimensional regularization method, we reveal that such extremely overdamped dynamics of U(1) gauge-field fluctuations, which originates from the emergent one-dimensional dynamics of spinons, does not cause any renormalization effects to the effective dynamics of both critical charge fluctuations and spinon excitations. However, it turns out that the coupling between U(1) gauge-field fluctuations and both matter-field excitations still persists at this Mott transition, which results in novel mean-field dynamics to explain the nature of the spin-liquid Mott quantum criticality

GraNNDis: Efficient Unified Distributed Training Framework for Deep GNNs on Large Clusters

Graph neural networks (GNNs) are one of the most rapidly growing fields within deep learning. According to the growth in the dataset and the model size used for GNNs, an important problem is that it becomes nearly impossible to keep the whole network on GPU memory. Among numerous attempts, distributed training is one popular approach to address the problem. However, due to the nature of GNNs, existing distributed approaches suffer from poor scalability, mainly due to the slow external server communications. In this paper, we propose GraNNDis, an efficient distributed GNN training framework for training GNNs on large graphs and deep layers. GraNNDis introduces three new techniques. First, shared preloading provides a training structure for a cluster of multi-GPU servers. We suggest server-wise preloading of essential vertex dependencies to reduce the low-bandwidth external server communications. Second, we present expansion-aware sampling. Because shared preloading alone has limitations because of the neighbor explosion, expansion-aware sampling reduces vertex dependencies that span across server boundaries. Third, we propose cooperative batching to create a unified framework for full-graph and minibatch training. It significantly reduces redundant memory usage in mini-batch training. From this, GraNNDis enables a reasonable trade-off between full-graph and mini-batch training through unification especially when the entire graph does not fit into the GPU memory. With experiments conducted on a multi-server/multi-GPU cluster, we show that GraNNDis provides superior speedup over the state-of-the-art distributed GNN training frameworks

An Adaptive Control Technology for Safety of a GTM-like Aircraft

An adaptive control architecture for safe performance of a transport aircraft subject to various adverse conditions is proposed and verified in this report. This architecture combines a nominal controller based on a Linear Quadratic Regulator with integral action, and an adaptive controller that accommodates actuator saturation and bounded disturbances. The effectiveness of the baseline controller and its adaptive augmentation are evaluated using a stand-alone control veri fication methodology. Case studies that pair individual parameter uncertainties with critical flight maneuvers are studied. The resilience of the controllers is determined by evaluating the degradation in closed-loop performance resulting from increasingly larger deviations in the uncertain parameters from their nominal values. Symmetric and asymmetric actuator failures, flight upsets, and center of gravity displacements, are some of the uncertainties considered

Adaptive control design with guaranteed margins for nonlinear plants

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.Includes bibliographical references (p. 139-142).Adaptive control is one of the technologies that improve both performance and safety as controller parameters can be redesigned autonomously in the presence of uncertainties. Considerable research has been accomplished in adaptive control theory for several decades and a solid foundation has been laid out for stability and robustness of adaptive systems. However, a large gap between theory and practice has been an obstacle to transition theoretical results into applications and it still remains. In order to reduce the gap, this thesis presents a unified framework for design and analysis of adaptive control for general nonlinear plants.An augmented adaptive control architecture is proposed where a nominal controller is designed in the inner-loop with an adaptive controller in the outer-loop. The architecture is completed by addressing three separate problems. The first problem is the design of adaptive control in the presence of input constraints. With a rigorous stability analysis, an algorithm is developed to remove the adverse effects of multi-input magnitude saturation. The second problem is the augmentation of adaptive control with a nominal gain-scheduling controller. Though adaptive controllers have been employed with gain-scheduling to various applications, no formal stability analysis has been developed. In the proposed architecture, adaptive control is combined with gain-scheduling in a specific manner while stability is guaranteed. The third problem is the development of analytic stability margins of the closed-loop plant with the proposed adaptive controller. A time-delay margin is derived using standard Lyapunov stability analysis as an analytic stability margin.The overall adaptive control architecture as well as the analytically derived margins are validated by a 6-DoF nonlinear flight dynamics based on the NASA X-15 hypersonic aircraft. Simulation results show that the augmented adaptive control is able to stabilize the plant and tracks desired trajectories with uncertainties in the plant while instability cannot be overcome only with the nominal controller. The time-delay margins are validated based on a generic transport model and they are compared with margins obtained from simulations studies. We utilize numerical methods to find less conservative time-delay margins.by Jinho Jang.Ph.D

Trust and human performance in automated formation flight station-keeping

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2005.Includes bibliographical references (p. 81-84).This thesis primarily describes performance and decision heuristics of human operators intervention with an autonomous formation flight (AFF) system during monitoring of a station-keeping display. Due to mental and physical workloads, automation technologies have been applied to formation flight for precise station-keeping and resultant fuel reduction, shifting control authority from humans to machines. Accordingly, the human is not directly in the control loop, but just supervises whether or not the automation works as intended. One critical problem in AFF supervisory control is that the human pilot needs to intervene with AFF system when the automated systems malfunction or their functions degrade. Thus while monitoring a station-keeping display, operators should minimize incorrect decisions for safety and cost reduction. To examine design issues in such a display, a simulation was constructed that simulated two different control systems as well as the impact of different angles of bank. 20 subjects participated in the monitoring task simulation of the station-keeping display. During the experiments, subjects were asked to intervene with AFF system when the AFF system failed to keep the trailing aircraft in the vortex area. Subjects made the most incorrect decisions when the AFF system was operated with the oscillating controller and high angle of bank.(cont.) Trust of the human in the AFF system was found to be influenced by the damping ratio of the AFF controller. Most significantly, results showed that humans developed biased decision criteria to execute interventions because velocity feedback of the wing tip on this display was not adequately provided.by Jinho Jang.S.M

Single-cell RNA sequencing reveals distinct cellular factors for response to immunotherapy targeting CD73 and PD-1 in colorectal cancer

Background Although cancer immunotherapy is one of the most effective advanced-stage cancer therapies, no clinically approved cancer immunotherapies currently exist for colorectal cancer (CRC). Recently, programmed cell death protein 1 (PD-1) blockade has exhibited clinical benefits according to ongoing clinical trials. However, ongoing clinical trials for cancer immunotherapies are focused on PD-1 signaling inhibitors such as pembrolizumab, nivolumab, and atezolizumab. In this study, we focused on revealing the distinct response mechanism for the potent CD73 ectoenzyme selective inhibitor AB680 as a promising drug candidate that functions by blocking tumorigenic ATP/adenosine signaling in comparison to current therapeutics that block PD-1 to assess the value of this drug as a novel immunotherapy for CRC. Methods To understand the distinct mechanism of AB680 in comparison to that of a neutralizing antibody against murine PD-1 used as a PD-1 blocker, we performed single-cell RNA sequencing of CD45(+) tumor-infiltrating lymphocytes from untreated controls (n=3) and from AB680-treated (n=3) and PD-1-blockade-treated murine CRC in vivo models. We also used flow cytometry, Azoxymethane (AOM)/Dextran Sulfate Sodium (DSS) models, and in vitro functional assays to validate our new findings. Results We initially observed that the expressions of Nt5e (a gene for CD73) and Entpd1 (a gene for CD39) affect T cell receptor (TCR) diversity and transcriptional profiles of T cells, thus suggesting their critical roles in T cell exhaustion within tumor. Importantly, PD-1 blockade significantly increased the TCR diversity of Entpd1-negative T cells and Pdcd1-positive T cells. Additionally, we determined that AB680 improved the anticancer functions of immunosuppressed cells such as Treg and exhausted T cells, while the PD-1 blocker quantitatively reduced Malat1(high) Treg and M2 macrophages. We also verified that PD-1 blockade induced Treg depletion in AOM/DSS CRC in vivo models, and we confirmed that AB680 treatment caused increased activation of CD8(+) T cells using an in vitro T cell assay. Conclusions The intratumoral immunomodulation of CD73 inhibition is distinct from PD-1 inhibition and exhibits potential as a novel anticancer immunotherapy for CRC, possibly through a synergistic effect when combined with PD-1 blocker treatments. This study may contribute to the ongoing development of anticancer immunotherapies targeting refractory CRC