We introduce the SceneDiffuser, a conditional generative model for 3D scene understanding. SceneDiffuser provides a unified model for solving scene-conditioned generation, optimization, and planning. In contrast to prior work, SceneDiffuser is intrinsically scene-aware, physics-based, and goal-oriented. With an iterative sampling strategy, SceneDiffuser jointly formulates the scene-aware generation, physics-based optimization, and goal-oriented planning via a diffusion-based denoising process in a fully differentiable fashion. Such a design alleviates the discrepancies among different modules and the posterior collapse of previous scene-conditioned generative models. We evaluate the SceneDiffuser on various 3D scene understanding tasks, including human pose and motion generation, dexterous grasp generation, path planning for 3D navigation, and motion planning for robot arms. The results show significant improvements compared with previous models, demonstrating the tremendous potential of the SceneDiffuser for the broad community of 3D scene understanding.
There are many dynamic disturbances during the continuous annealing production line (CAPL) in iron and steel enterprise. Traditional robust operation optimization considers only the maximum disturbance range in previous production and overrides the dynamic changes of these disturbances, which often results in high production cost and low product quality. Therefore, this paper proposes a novel multiobjective dynamic robust optimization (MODRO) modeling method by further taking into account the dynamic changes of these disturbances and adopting a time series prediction model based on a least square support vector regression (LSSVR) to predict the range of disturbances in next time slot. The main feature of the model is that the robustness can be dynamically adjusted according to the disturbance range predicted by the LSSVR. To solve this model, an improved NSGA-II algorithm is developed based on a new crowding metric. Numerical results based on actual production process data illustrate that the proposed MODRO modeling method is obviously superior to traditional static robust operation optimization, and that it can significantly improve the strip quality and the capacity utilization of the CAPL, and reduce the total energy consumption.
In order to study the leakage of buried natural gas pipeline caused serious environmental pollution and human casualties, the acoustic propagation characteristics of buried natural gas pipeline leakage monitored by distributed optical fiber were studied. At present, the research on the leakage of buried pipeline mainly focuses on the propagation of sound waves along the pipe wall, while the study on the propagation of sound waves in the soil is still lacking. The acoustic attenuation of acoustic wave propagation in soil by the size of leakage hole and leakage pressure is studied, and the evolution process of acoustic wave in soil is revealed. The conclusion is that the acoustic source of buried natural gas pipeline leakage belongs to broadband noise, and the acoustic energy of leakage is prominent in the low frequency band of 15kHz. The lower frequency, the higher sound pressure level. The oscillation of the sound pressure level attenuates with the increase of frequency. Fiber optic monitoring of buried natural gas pipeline leakage early warning provides theoretical support for the conclusion. The sound pressure level in low frequency band is of great significance for buried pipeline leakage monitoring.
ABSTRACT Two new alkaloids, named migenomycin I ( 1 ) and II ( 2 ), along with nine known compounds ( 3–11 ), were isolated from the fungus Rhizopus oryzae from Atractylodes macrocephala Koidz. The structures of compounds 1 and 2 were determined by spectroscopic methods (MS, NMR, and CD). All compounds were isolated from Rhizopus oryzae for the first time. In addition, the antitumor activities of compounds 1 and 2 and the hypoglycemic activities of most compounds were evaluated.
Current computer vision models, unlike the human visual system, cannot yet achieve general-purpose visual understanding. Existing efforts to create a general vision model are limited in the scope of assessed tasks and offer no overarching framework to perform them holistically. We present a new comprehensive benchmark, General-purpose Visual Understanding Evaluation (G-VUE), covering the full spectrum of visual cognitive abilities with four functional domains $\unicode{x2014}$ Perceive, Ground, Reason, and Act. The four domains are embodied in 11 carefully curated tasks, from 3D reconstruction to visual reasoning and manipulation. Along with the benchmark, we provide a general encoder-decoder framework to allow for the evaluation of arbitrary visual representation on all 11 tasks. We evaluate various pre-trained visual representations with our framework and observe that (1) Transformer-based visual backbone generally outperforms CNN-based backbone on G-VUE, (2) visual representations from vision-language pre-training are superior to those with vision-only pre-training across visual tasks. With G-VUE, we provide a holistic evaluation standard to motivate research toward building general-purpose visual systems via obtaining more general-purpose visual representations.
In this paper, we consider the diffuse type of indoor wireless optical communication (WOC) system. To find the channel characteristics of indoor wireless infrared communication system, we investigate the simulation process to get the impulse response of diffuse type and analyze the scenario of the indoor structure which we have built. The simulation results of the impulse response include power ratio and time delay due to bounce times. We get and discuss the receiving power distribution according to six configurations which have different transmitter and receiver positions and reflection coefficients of the indoor structure assumed. The results of this paper are useful to design the indoor wireless optical communication systems.
The mechanical properties of Al-Zn-Mg-Cu alloys prepared by direct solidification are often compromised due to severe intergranular segregation. Even with adjustments in homogenization and aging treatments, satisfactory mechanical properties remain elusive. Inducing solute atom supersaturation during non-equilibrium solidification by increasing the cooling rate is a promising strategy to fabricate high-strength aluminum alloys. In this study, we synthesized a novel Al-4.5Zn-2.5Mg-1.5Cu-0.6Zr alloy, controlling nominal cooling rates of 0.1°C/s, 3°C/s, 19°C/s, and 180°C/s during the melt solidification process. The alloy's microstructure and composition were characterized. Results revealed that the cooling rate significantly influenced the alloy's solidification microstructure. As the cooling rate increased, the volume fraction of intergranular segregation phases decreased markedly, accompanied by a reduction in the size of these phases. There was also a noticeable shift in the types of intergranular segregation phases, transitioning from a mixture of T-Mg(Al, Zn, Cu)2 phase, η-MgZn2 phase, Al2CuMg phase and θ-Al2Cu to predominantly MgZn2 and Al2Cu phases. Furthermore, the large, brittle Al7Cu2Fe phase formed at low cooling rates was suppressed as the cooling rate increased, replaced by metastable Al6(Fe,Mn). Subsequent heat treatment resulted in the formation of small Al13(Fe,Mn)4 phases, significantly mitigating the grain boundary weakening caused by Al7Cu2Fe. With increasing cooling rate, although grain size remained relatively constant, the quantity and proportion of low-angle and subgrain boundaries increased substantially. During aging, abundant Al2Cu precipitates formed on subgrain boundaries, while discontinuous distributions of MgZn2 occurred on low-angle boundaries, and a mixed precipitation of MgZn2 and Al2Cu appeared on high-angle grain boundaries. Additionally, D023-Al3Zr, which coarsened along grain boundaries at low cooling rates, was significantly inhibited. As the cooling rate increased, the size and morphology of precipitates within the grains underwent noticeable changes. Plate-like and short rod-like coarse MgZn2 phases were suppressed, giving way to finer granular MgZn2. The size of L12-Al3Zr precipitates also decreased significantly, with uneven distribution observed along the core and edge of dendrites. Further increases in cooling rate exacerbated this effect before inhibition occurred, resulting in the abundant distribution of fine spherical L12-Al3Zr precipitates mixed with MgZn2 phases and Al2Cu phase within the alloy. The combined effects of higher cooling rate-induced dislocation strengthening, low-angle grain boundary strengthening, reduced precipitate size, and increased volume fraction culminated in exceptional mechanical properties for the sample aged after cooling at a rate of 180°C/s, with ultimate tensile strength, yield strength, and elongation values reaching 549 MPa, 482 MPa, and 12.3%, respectively.
Gastric cancer (GC) is a worldwide public health concern. We aimed to investigate the association between preoperative prognostic scoring system based on the combination of age, American Society of Anesthesiologists physical status (ASA-PS), and prognostic nutritional index (PNI) and long-term survival outcomes in patients with (GC). Data from 513 patients were analyzed using Cox proportional hazards regression models to evaluate the association between this prognostic score system and risks of all-cause mortality. This simple prognostic score system (0–3 points) was an independent predictor of long-term survival outcomes in patients with GC after radical gastrectomy based on multivariate analyses. Prognostic 1-point score, 2-point score, and 3-point score significantly increased 50% (95% CI, 14%–98%; P = 0.004), 75% (95% CI, 22%–151%; P = 0.003), and 116% (95% CI, 26%–271%; P = 0.005) hazards of 5-year all-cause mortality, respectively, compared to prognostic 0-point score. Five-year overall survival rates were significantly decreased as prognostic scores increased, (0 point, 57.3%; 1-point, 41.3%; 2-ponint, 36.6%; 3-point, 25.9%; P < 0.01; area under the curve [AUC] = 0.62). A prognostic scoring method based on combination of age, ASA-PS, and PNI may serve as an independent risk stratification metric for long-term survival in patients with GC.
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