Unsupervised domain adaptation semantic segmentation of high-resolution remote sensing imagery with invariant domain-level prototype memory

Semantic segmentation is a key technique involved in automatic interpretation of high-resolution remote sensing (HRS) imagery and has drawn much attention in the remote sensing community. Deep convolutional neural networks (DCNNs) have been successfully applied to the HRS imagery semantic segmentation task due to their hierarchical representation ability. However, the heavy dependency on a large number of training data with dense annotation and the sensitiveness to the variation of data distribution severely restrict the potential application of DCNNs for the semantic segmentation of HRS imagery. This study proposes a novel unsupervised domain adaptation semantic segmentation network (MemoryAdaptNet) for the semantic segmentation of HRS imagery. MemoryAdaptNet constructs an output space adversarial learning scheme to bridge the domain distribution discrepancy between source domain and target domain and to narrow the influence of domain shift. Specifically, we embed an invariant feature memory module to store invariant domain-level context information because the features obtained from adversarial learning only tend to represent the variant feature of current limited inputs. This module is integrated by a category attention-driven invariant domain-level context aggregation module to current pseudo invariant feature for further augmenting the pixel representations. An entropy-based pseudo label filtering strategy is used to update the memory module with high-confident pseudo invariant feature of current target images. Extensive experiments under three cross-domain tasks indicate that our proposed MemoryAdaptNet is remarkably superior to the state-of-the-art methods.Comment: 17 pages, 12 figures and 8 table

A new method to suppress the MHD instability of cylindrical liquid metal batteries

The magnetohydrodynamics (MHD) instabilities of liquid metal batteries (LMBs) severely limit the wide application and commercialization of LMB. A new technology is proposed, which is called the gridstructure (GS), so as to achieve the suppression effect of the MHD instabilities in LMB. The GS is composed of electrically and magnetically insulated partitions, which fully contact the negative electrode and extended to the positive electrode of the battery. It is found that the GS inserted inside the LMBs can change the distribution of the circumferential induced magnetic field inside the battery, effectively reduce the induced magnetic field and Lorentz force, and thus improve the stability of the LMB

A new method to suppress the MHD instability of cylindrical liquid metal batteries

The magnetohydrodynamics (MHD) instabilities of liquid metal batteries (LMBs) severely limit the wide application and commercialization of LMB. A new technology is proposed, which is called the gridstructure (GS), so as to achieve the suppression effect of the MHD instabilities in LMB. The GS is composed of electrically and magnetically insulated partitions, which fully contact the negative electrode and extended to the positive electrode of the battery. It is found that the GS inserted inside the LMBs can change the distribution of the circumferential induced magnetic field inside the battery, effectively reduce the induced magnetic field and Lorentz force, and thus improve the stability of the LMB

Simulation Study on Methods for Reducing Dynamic Cable Curvature in Floating Wind Power Platforms

As a key component connecting a floating wind turbine with static sea cables, dynamic cables undergo significant tensile and bending loads caused by hydrostatic pressure, self-weight, waves, and ocean currents during service, which can lead to fatigue failure. Thus, dynamic and fatigue analyses are necessary for the design and operation of dynamic cables. In this study, a fatigue analysis of the three-core four-layer armored dynamic cable used in a semisubmersible floating wind turbine was carried out at a water depth of 25 m. The Miner linear cumulative damage method, based on material S-N curves, was used to predict fatigue life. The results indicate that, at 10 times the safety factor, the dynamic cables meet the design requirement of a 30-year service life in the studied marine environment. The maximal curvature of the dynamic cable always appears at the exit of the bend stiffener, even beyond the allowed point. Adding weights to the section where the cable exits the bend stiffener and adjusting the bend stiffener’s hanging angle can both reduce the curvature at the bend stiffener exit. The scheme of adjusting the bend stiffener’s hanging angle is preferred, for it is easier for simultaneous adjusting and inducing much smaller extra stress in the cable. As the hanging angle increases, the curvature at the bend stiffener exit decreases, while the maximal effective tension and maximal von Mises stress gradually increase. For certain operating conditions, especially with higher waves, it is better to adjust the hanging angle to avoid excessive curvature and, meanwhile, ensure the increase in the stress within a reasonable range

Seeing Theory: A Visual Introduction to Probability and Statistics

As mathematics instructors and students know, lucid visualizations are essential to helping learners understand complex mathematical concepts. Seeing Theory is an online, interactive textbook that utilizes colorful, interactive visualizations and animations to explain concepts like compound probability and Bayesian Inference. This resource was envisioned by Daniel Kunin (currently a master's student in mathematics and computer science at Stanford University), who created Seeing Theory along with designer Jingru Guo, software engineer Tyler Dae Devlin, and statistics student Daniel Xiang. Seeing Theory contains six chapters, each of which contains three interactive visualizations. Each visualization contains two panels: a short explanation of each concept appears on the left, while a graph or chart appears on the right. In addition, the left panel often contains an interactive element. For instance, in the basic probability module, users are invited to flip a coin, roll a die, and draw a card. As they do so, the graph on the right reflects the outcome of these actions, revealing the principles of basic probability

Impact of New Energy Vehicle Development on China’s Crude Oil Imports: An Empirical Analysis

Breaking the highly oil-dependent energy use structure in the transportation sector will be crucial for China to reduce its dependence on crude oil imports and ensure its energy security, and the development of new energy vehicles is helping to break this dilemma. A time series analysis summarizes the possible relationships between new energy vehicles and crude oil imports, i.e., new energy vehicles, as alternatives to fuel vehicles, will reduce the demand for oil in the transportation sector, which will in turn reduce crude oil imports, and crude oil prices and crude oil production will inhibit crude oil imports. In this empirical study, monthly data from 2015 to 2021 on crude oil imports, the market share of new energy vehicles, crude oil prices, and crude oil production are selected, time-series multiple regression modelling is adopted, and endogeneity is treated using a generalized method of moments (GMM). The regression results show that crude oil imports decrease by one unit for every 16.32% increase in crude oil prices, indicating that price factor is the most influential factor in China’s crude oil imports, while crude oil imports decrease by one unit for every 133.99% increase in crude oil production, indicating that an increase in crude oil production contributes less to the reduction of crude oil imports. One unit of crude oil imports is added for every 15.53% increase in the share of new energy vehicles, indicating that the effect of new energy vehicles on limiting crude oil imports has not yet emerged. Probably due to the fact that new energy vehicles have not yet had a significant impact on fuel vehicles, oil consumption will continue to increase in the short and medium term, with oil for the petrochemical industry becoming the primary driver of this increase. Finally, policy implications are provided from the perspective of crude oil demand, supply, and China’s oil price mechanism

Engineering a modular double-transmembrane synthetic receptor system for customizing cellular programs

Summary: Implementation of designer receptors in engineered cells confers them to sense a particular physiological or disease state and respond with user-defined programs. To expand the therapeutic application scope of engineered cells, synthetic receptors realized through different strategies are in great demand. Here, we develop a synthetic receptor system that exerts dual control by incorporating two transmembrane helices for the signal chain. Together with a sensor-actuator device with minimal background signals and a positive loop circuit, this receptor system can sensitively respond to extracellular protein signals. We demonstrate that this synthetic receptor system can be readily adapted to respond to various inputs, such as interleukin-1 (IL-1), programmed death ligand 1 (PD-L1), and HER2, and release customized outputs, including fluorescence signals and the therapeutic molecule IL-2. The robust signaling ability and generality of this receptor system promise it to be a useful tool in the field of cell engineering for fundamental research and translational applications

Impact of New Energy Vehicle Development on China’s Crude Oil Imports: An Empirical Analysis

Breaking the highly oil-dependent energy use structure in the transportation sector will be crucial for China to reduce its dependence on crude oil imports and ensure its energy security, and the development of new energy vehicles is helping to break this dilemma. A time series analysis summarizes the possible relationships between new energy vehicles and crude oil imports, i.e., new energy vehicles, as alternatives to fuel vehicles, will reduce the demand for oil in the transportation sector, which will in turn reduce crude oil imports, and crude oil prices and crude oil production will inhibit crude oil imports. In this empirical study, monthly data from 2015 to 2021 on crude oil imports, the market share of new energy vehicles, crude oil prices, and crude oil production are selected, time-series multiple regression modelling is adopted, and endogeneity is treated using a generalized method of moments (GMM). The regression results show that crude oil imports decrease by one unit for every 16.32% increase in crude oil prices, indicating that price factor is the most influential factor in China’s crude oil imports, while crude oil imports decrease by one unit for every 133.99% increase in crude oil production, indicating that an increase in crude oil production contributes less to the reduction of crude oil imports. One unit of crude oil imports is added for every 15.53% increase in the share of new energy vehicles, indicating that the effect of new energy vehicles on limiting crude oil imports has not yet emerged. Probably due to the fact that new energy vehicles have not yet had a significant impact on fuel vehicles, oil consumption will continue to increase in the short and medium term, with oil for the petrochemical industry becoming the primary driver of this increase. Finally, policy implications are provided from the perspective of crude oil demand, supply, and China’s oil price mechanism