Learning Predictive Safety Filter via Decomposition of Robust Invariant Set

Ensuring safety of nonlinear systems under model uncertainty and external disturbances is crucial, especially for real-world control tasks. Predictive methods such as robust model predictive control (RMPC) require solving nonconvex optimization problems online, which leads to high computational burden and poor scalability. Reinforcement learning (RL) works well with complex systems, but pays the price of losing rigorous safety guarantee. This paper presents a theoretical framework that bridges the advantages of both RMPC and RL to synthesize safety filters for nonlinear systems with state- and action-dependent uncertainty. We decompose the robust invariant set (RIS) into two parts: a target set that aligns with terminal region design of RMPC, and a reach-avoid set that accounts for the rest of RIS. We propose a policy iteration approach for robust reach-avoid problems and establish its monotone convergence. This method sets the stage for an adversarial actor-critic deep RL algorithm, which simultaneously synthesizes a reach-avoid policy network, a disturbance policy network, and a reach-avoid value network. The learned reach-avoid policy network is utilized to generate nominal trajectories for online verification, which filters potentially unsafe actions that may drive the system into unsafe regions when worst-case disturbances are applied. We formulate a second-order cone programming (SOCP) approach for online verification using system level synthesis, which optimizes for the worst-case reach-avoid value of any possible trajectories. The proposed safety filter requires much lower computational complexity than RMPC and still enjoys persistent robust safety guarantee. The effectiveness of our method is illustrated through a numerical example

Deep Geometrized Cartoon Line Inbetweening

We aim to address a significant but understudied problem in the anime industry, namely the inbetweening of cartoon line drawings. Inbetweening involves generating intermediate frames between two black-and-white line drawings and is a time-consuming and expensive process that can benefit from automation. However, existing frame interpolation methods that rely on matching and warping whole raster images are unsuitable for line inbetweening and often produce blurring artifacts that damage the intricate line structures. To preserve the precision and detail of the line drawings, we propose a new approach, AnimeInbet, which geometrizes raster line drawings into graphs of endpoints and reframes the inbetweening task as a graph fusion problem with vertex repositioning. Our method can effectively capture the sparsity and unique structure of line drawings while preserving the details during inbetweening. This is made possible via our novel modules, i.e., vertex geometric embedding, a vertex correspondence Transformer, an effective mechanism for vertex repositioning and a visibility predictor. To train our method, we introduce MixamoLine240, a new dataset of line drawings with ground truth vectorization and matching labels. Our experiments demonstrate that AnimeInbet synthesizes high-quality, clean, and complete intermediate line drawings, outperforming existing methods quantitatively and qualitatively, especially in cases with large motions. Data and code are available at https://github.com/lisiyao21/AnimeInbet.Comment: ICCV 202

Multi-scale volumetric dynamic optoacoustic and laser ultrasound (OPLUS) imaging enabled by semi-transparent optical guidance

Major biological discoveries have been made by interrogating living organisms with light. However, the limited penetration of unscattered photons within biological tissues severely limits the depth range covered by optical methods. Deep-tissue imaging has been achieved by combining light and ultrasound. Optoacoustic imaging uniquely exploits optical generation of ultrasound to render high-resolution images at depths unattainable with optical microscopy. Recently, laser ultrasound has further been suggested as a means of generating broadband acoustic waves for high-resolution pulse-echo ultrasound imaging. Herein, we propose an approach to simultaneously interrogate biological tissues with light and ultrasound based on layer-by-layer coating of silica optical fibers with a controlled degree of transparency. We exploit the time separation between optoacoustic signals and ultrasound echoes collected with a custom-made spherical array transducer for simultaneous three-dimensional optoacoustic and laser ultrasound (OPLUS) imaging with a single laser pulse. OPLUS is shown to enable large-scale comprehensive anatomical characterization of tissues along with functional multi-spectral imaging of spectrally-distinctive chromophores and assessment of cardiac dynamics at ultrafast rates only limited by the pulse repetition frequency of the laser. The suggested approach provides a flexible and scalable means for developing a new generation of systems synergistically combining the powerful capabilities of optoacoustics and ultrasound imaging in biology and medicine.Comment: 21 pages, 4 figure

Effective Application of Solid Expandable Tubular During the Enhancement of Heavy Oil Recovery in China, Lessons Learned and Experience Shared

As the traditional thermal recovery became less effective in exploring the heavy oil reservoirs, some newly developed techniques such as chemical flooding, SAGD and HDCS are demonstrating their advantage in the recovery process in China. However, the ever increasingly used new techniques often compromised severely the well integrity as the flow of extremely high temperature fluid or gas caused quick damage to casing, leaving the wellbore less reliable. This compromise requires urgently a workover strategy that would maximize the well’s life span and guarantee the effectiveness of new techniques.Solid expandable tubular (SET) was field-proven in casing patching activities, but its application in the heavy oil recovery has not been attempted due to severe temperature challenge. We made innovations on the traditional structure of SET and got valuable results. The tubular after expansion was integrated with the original casing as a whole and the rubber was removed in-between, the wellbore size was maintained utmost and the casing was further strengthened. Meanwhile the expansion cone was put outside the tubular which is a big step forward in SET structure.Indoors experiments demonstrated sound performance of the new structure in the simulative temperature of 350 ℃, the plan for the field application was optimized based on the lessons collected in this experiment. High temperature well applications by SET were carried out in Liaohe oilfield which is famous for its heavy oil resource in China, and the detailed process as well as the outcome were compared and analyzed, finally the conclusions were drawn as a result of the whole study.We expect our work will help expand this enabling technology to better facilitate the enhancement of heavy oil recovery and maintain solid well integrity during the heavy oil production.Key words: Solid expandable tubular; Heavy oil recovery; Chin

Tracking Strain-Specific Morphogenesis and Angiogenesis of Murine Calvaria with Large-Scale Optoacoustic and Ultrasound Microscopy

Skull bone development is a dynamic and well-coordinated process playing a key role in maturation and maintenance of the bone marrow (BM), fracture healing, and progression of diseases such as osteoarthritis or osteoporosis. At present, dynamic transformation of the growing bone (osteogenesis) as well as its vascularization (angiogenesis) remain largely unexplored due to the lack of suitable in vivo imaging techniques capable of noninvasive visualization of the whole developing calvaria at capillary-level resolution. We present a longitudinal study on skull bone development using ultrasound-aided large-scale optoacoustic microscopy (U-LSOM). Skull bone morphogenesis and microvascular growth patterns were monitored in three common mouse strains (C57BL/6J, CD-1, and Athymic Nude-Foxn1nu) at the whole-calvaria scale over a 3-month period. Strain-specific differences in skull development were revealed by quantitative analysis of bone and vessel parameters, indicating the coupling between angiogenesis and osteogenesis during skull bone growth in a minimally invasive and label-free manner. The method further enabled identifying BM-specific sinusoidal vessels, and superficial skull vessels penetrating into BM compartments. Our approach furnishes a new high-throughput longitudinal in vivo imaging platform to study morphological and vascular skull alterations in health and disease, shedding light on the critical links between blood vessel formation, skull growth, and regeneration. © 2022 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR)

Deep learning-aided joint DG-substation siting and sizing in distribution network stochastic expansion planning

The rapid growth of distributed generation (DG) and load has highlighted the necessity of optimizing their ways of integration, as their siting and sizing significantly impact distribution networks. However, little attention has been paid to the siting and sizing of new substations which are to be installed. This paper proposes deep learning-aided joint DG-substation siting and sizing in distribution network stochastic expansion planning. First, as the model depends on an accurate forecast, Long Short-Term Memory (LSTM) deep neural network is used to forecast DG output and load, where electricity growth rate, bidding capacity of the electric expansion, and industrial difference are all considered. Then, a two-stage stochastic mixed integer bilinear programming model was established for joint DG-substation siting and sizing under uncertainties, where multiple objective functions are comprehensively addressed. By using the Fortuny-Amat McCarl Linearization, the resultant bilinear model is equivalently transformed into a mixed integer linear program, which can be efficiently solved. Finally, stochastic power flow calculation in the IEEE 69-node system is conducted to analyze the influence of electric expansion and DG integration on the node voltage and power flow distribution of the power system. The effectiveness of the proposed method is also verified by simulation tests

Spirometra

Sparganosis is a zoonotic disease caused by the spargana of Spirometra, and snake is one of the important intermediate hosts of spargana. In some areas of China, snake is regarded as popular delicious food, and such a food habit potentially increases the prevalence of human sparganosis. To understand the prevalence of Spirometra in snakes in food markets, we conducted a study in two representative cities (Guangzhou and Shenzhen), during January–August 2013. A total of 456 snakes of 13 species were examined and 251 individuals of 10 species were infected by Spirometra, accounting for 55.0% of the total samples. The worm burden per infected snake ranged from 1 to 213, and the prevalence in the 13 species was 0∼96.2%. More than half (58.1%) of the spargana were located in muscular tissue, 25.6% in subcutaneous tissue, and 16.3% in coelomic cavity. The results indicated that Spirometra severely infected snakes in food markets in Guangzhou and Shenzhen, implying that eating snakes has great health risk and improper cooking methods may increase the risk of Spirometra infection in humans in China. Additional steps should be considered by the governments and public health agencies to prevent the risk of snake-associated Spirometra infections in humans

Identification of a HIV Gp41-Specific Human Monoclonal Antibody With Potent Antibody-Dependent Cellular Cytotoxicity

Antibody-Dependent Cellular Cytotoxicity (ADCC) is a major mechanism of protection against viral infections in vivo. Identification of HIV-1-specific monoclonal antibodies (mAbs) with potent ADCC activity may help develop an effective HIV-1 vaccine. In present study, we isolated such human mAb, designated E10, from an HIV-1-infected patient sample by single B cell sorting and single cell PCR. E10 bound to gp140 trimer and linear peptides derived from gp41 membrane proximal external region (MPER). E10 epitope (QEKNEQELLEL) overlapped with mAb 2F5 epitope. However, E10 differentiated from 2F5 in neutralization breadth and potency, as well as ADCC activity. E10 showed low neutralization activity and narrow spectrum of neutralization compared to 2F5, but it mediated higher ADCC activity than 2F5 at low antibody concentration. Fine mapping of E10 epitope may potentiate MPER-based subunit vaccine development