PDPP:Projected Diffusion for Procedure Planning in Instructional Videos

In this paper, we study the problem of procedure planning in instructional videos, which aims to make goal-directed plans given the current visual observations in unstructured real-life videos. Previous works cast this problem as a sequence planning problem and leverage either heavy intermediate visual observations or natural language instructions as supervision, resulting in complex learning schemes and expensive annotation costs. In contrast, we treat this problem as a distribution fitting problem. In this sense, we model the whole intermediate action sequence distribution with a diffusion model (PDPP), and thus transform the planning problem to a sampling process from this distribution. In addition, we remove the expensive intermediate supervision, and simply use task labels from instructional videos as supervision instead. Our model is a U-Net based diffusion model, which directly samples action sequences from the learned distribution with the given start and end observations. Furthermore, we apply an efficient projection method to provide accurate conditional guides for our model during the learning and sampling process. Experiments on three datasets with different scales show that our PDPP model can achieve the state-of-the-art performance on multiple metrics, even without the task supervision. Code and trained models are available at https://github.com/MCG-NJU/PDPP.Comment: Accepted as a highlight paper at CVPR 202

Power system disturbance localization using recurrence quantification analysis and minimum-volume-enclosing ellipsoid

A method for determining a location of a disturbance in a power system is provided. The method includes receiving data from a plurality of sensors distributed across the power system; performing a recurrence quantification analysis on the received data to identify a predetermined number of sensors, from the plurality of sensors, that are closest to the disturbance; constructing a plurality of minimum-volume-enclosing ellipsoids based on and enclosing the data received from the identified sensors; extracting one or more parameters from the plurality of minimum-volume-enclosing ellipsoids; inputting the one or more parameters into a multivariate-random-forest regression algorithm to determine the location of the disturbance and a power mismatch corresponding to the disturbance; and presenting, on one or more display units, the determined location of the disturbance and the determined power mismatch

Functional Analysis of MsepOR13 in the Oriental Armyworm Mythimna separata (Walker)

Olfaction in insects has a critical role in recognizing the host, finding food, and choosing mating partners, as well as avoiding predators. Odorant receptors (ORs), which are housed in the dendritic membrane of sensory neurons and extended into the lymph of sensilla on insect antennae, are participating in the detection of volatile compounds in insects. In the present study, we identified an OR gene, named MsepOR13, in the oriental armyworm Mythimna separata (Walker). Quantitative real-time polymerase chain reaction revealed that MsepOR13 was expressed mainly in the antennae of male and female moths. In in vitro heterologous expression experiments, MsepOR13 was widely tuned to 32 of the 67 different compounds tested. Furthermore, MsepOR13 responded to eugenol at a low concentration of 10-9 M, with an EC50 value of 3.91 × 10-6 M. The high sensitivity suggests an important role for the OR13 gene in the moth olfactory system

Adding power of artificial intelligence to situational awareness of large interconnections dominated by inverter‐based resources

Large-scale power systems exhibit more complex dynamics due to the increasing integration of inverter-based resources (IBRs). Therefore, there is an urgent need to enhance the situational awareness capability for better monitoring and control of power grids dominated by IBRs. As a pioneering Wide-Area Measurement System, FNET/GridEye has developed and implemented various advanced applications based on the collected synchrophasor measurements to enhance the situational awareness capability of large-scale power grids. This study provides an overview of the latest progress of FNET/GridEye. The sensors, communication, and data servers are upgraded to handle ultra-high density synchrophasor and point-on-wave data to monitor system dynamics with more details. More importantly, several artificial intelligence (AI)-based advanced applications are introduced, including AI-based inertia estimation, AI-based disturbance size and location estimation, AI-based system stability assessment, and AI-based data authentication

Significance of Thymosin β4 and Implication of PINCH-1-ILK-α-Parvin (PIP) Complex in Human Dilated Cardiomyopathy

Myocardial remodeling is a major contributor in the development of heart failure (HF) after myocardial infarction (MI). Integrin-linked kinase (ILK), LIM-only adaptor PINCH-1, and α-parvin are essential components of focal adhesions (FAs), which are highly expressed in the heart. ILK binds tightly to PINCH-1 and α-parvin, which regulates FA assembly and promotes cell survival via the activation of the kinase Akt. Mice lacking ILK, PINCH or α-parvin have been shown to develop severe defects in the heart, suggesting that these proteins play a critical role in heart function. Utilizing failing human heart tissues (dilated cardiomyopathy, DCM), we found a 2.27-fold (p<0.001) enhanced expression of PINCH, 4 fold for α-parvin, and 10.5 fold (p<0.001) for ILK as compared to non-failing (NF) counterparts. No significant enhancements were found for the PINCH isoform PINCH-2 and parvin isoform β-parvin. Using a co-immunoprecipitation method, we also found that the PINCH-1-ILK-α-parvin (PIP) complex and Akt activation were significantly up-regulated. These observations were further corroborated with the mouse myocardial infarction (MI) and transaortic constriction (TAC) model. Thymosin beta4 (Tβ4), an effective cell penetrating peptide for treating MI, was found to further enhance the level of PIP components and Akt activation, while substantially suppressing NF-κB activation and collagen expression—the hallmarks of cardiac fibrosis. In the presence of an Akt inhibitor, wortmannin, we show that Tβ4 had a decreased effect in protecting the heart from MI. These data suggest that the PIP complex and activation of Akt play critical roles in HF development. Tβ4 treatment likely improves cardiac function by enhancing PIP mediated Akt activation and suppressing NF-κB activation and collagen-mediated fibrosis. These data provide significant insight into the role of the PIP-Akt pathway and its regulation by Tβ4 treatment in post-MI

Non-Volatile Reconfigurable Compact Photonic Logic Gates Based on Phase-Change Materials

Photonic logic gates have important applications in fast data processing and optical communication. This study aims to design a series of ultra-compact non-volatile and reprogrammable photonic logic gates based on the Sb2Se3 phase-change material. A direct binary search algorithm was adopted for the design, and four types of photonic logic gates (OR, NOT, AND, and XOR) are created using silicon-on-insulator technology. The proposed structures had very small sizes of 2.4 μm × 2.4 μm. Three-dimensional finite-difference time-domain simulation results show that, in the C-band near 1550 nm, the OR, NOT, AND, and XOR gates exhibit good logical contrast of 7.64, 6.1, 3.3, and 18.92 dB, respectively. This series of photonic logic gates can be applied in optoelectronic fusion chip solutions and 6G communication systems

Controllable Fabrication of SiC@C-Fe₃O₄ Hybrids and Their Excellent Electromagnetic Absorption Properties

In this work, a batch of novel ternary hybrids (SiC@C-Fe3O4), characterized by SiC nanowires core, carbon shell, and adhered Fe3O4 nanoparticles were controllably synthesized via surface carbonization of SiCnw followed by hydrothermal reaction. Carbon, which was derived from SiC with nanometer thickness, possesses an amorphous structure, while Fe3O4 nanoparticles are in a crystalline state. Simultaneously, the inducement of Fe3O4 nanoparticles can provide significant magnetic loss, which is well-tuned by changing the molar content of iron precursors (FeCl3·6H2O and FeCl2·4H2O). SiC@C-Fe3O4 hybrids show great electromagnetic absorption performance owing to the synergy effect of dielectric and magnetic losses. The minimum refection loss can reach to −63.71 dB at 11.20 GHz with a thickness of 3.10 mm, while the broad effective absorption bandwidth (EAB) can reach to 7.48 GHz in range of 10.52–18.00 GHz with a thickness of 2.63 mm. Moreover, the EAB can also cover the whole X band and Ku band. The outstanding performance of the obtained material implys that it is a promising candidate as an electromagnetic absorber

In situ carbon supplementation in large-scale cultivations of Spirulina platensis in open raceway pond

The objective of this study was to estimate the CO2 absorptivity provided by an in situ carbon supply system using a photosynthetic culture of the cyanobacterium Spirulina platensis in an open raceway pond. The effects of initial total carbon concentrations (ranging from 0 to 0.1 mol/L), suspension depths (ranging from 5 to 20 cm) and pH values (ranging from 8.9 to 11.0) on the CO2 absorptivity were studied. The results indicated that CO2 absorptivity was positively correlated with pH value, negatively correlated with total carbon concentration, and only negligibly affected by the suspension depth. The optimum total carbon concentration range and pH range were 0.03 similar to 0.09 mol/L and 9.7 similar to 10.0, respectively. An average CO2 absorptivity of 86.16% and average CO2 utilization efficiency of 79.18% were achieved using this in situ carbon-supply system in large-scale cultivation of Spirulina platensis, with an initial total carbon concentration of 0.06 mol/L and pH value of 9.8. Our results demonstrated that this system could obtain a favorable CO2 utilization efficiency in outdoor, large-scale cultivation of Spirulina platensis in open raceway ponds