Geospatial data conflation is the process of combining two datasets to create a better one. It has received increased research attention due to the emergence of new data sources and the need to ...combine information from these sources in spatial analyses. Many conflation methods exist to date, ranging from simple ones based on spatial join, to sophisticated methods based on statistics and optimization models. This paper focuses on the optimization-based conflation approach. It treats feature-matching in conflation as an optimization problem of finding a plan to match features in two datasets that minimizes the total discrepancy. Optimization based conflation methods may overcome some limitations of conventional methods, such as sub-optimality and greediness. However, they have often been deemed impractical in day-to-day analysis because they induce high computational costs (especially in combining large geospatial data).
In this paper, we demonstrate the feasibility of performing optimization-based conflation for large geographic data in Geographic Information Systems. This is accomplished by utilizing efficient network flow-based conflation models and a divide-and-conquer strategy that allows the conflation models to scale to large data. Experiments show that the network-flow based model achieves average recall and precision rates of 97.7% and 90.8%, respectively in small test areas, and outperforms the traditional assignment problem by about 9% each. For larger data, it took the original network-flow model (without divide-and-conquer) nearly two days to conflate the road network in a portion of Los Angeles area near the LAX international airport. By contrast, the same model can be used to conflate the road networks of the entire Los Angeles County, CA in under 3 h with the divide and conquer strategy.
•Utilized optimization models for geospatial conflation, which overcome sub-optimality in conventional methods.•Compared the new network-flow based conflation model with traditional models based on the assignment problem.•Proposed and tested divide-and-conquer strategies for geospatial data conflation.•Discussed and tested the impact of buffering data tiles on divide-and-conquer.•Developed an “equalized” tiling method based on quad-tree, which produces more balanced workload for data tiles.
Geospatial data conflation is aimed at matching counterpart features from two or more data sources in order to combine and better utilize information in the data. Due to the importance of conflation ...in spatial analysis, different approaches to the conflation problem have been proposed ranging from simple buffer-based methods to probability and optimization based models. In this paper, I propose a formal framework for conflation that integrates two powerful tools of geospatial computation: optimization and relational databases. I discuss the connection between the relational database theory and conflation, and demonstrate how the conflation process can be formulated and carried out in standard relational databases. I also propose a set of new optimization models that can be used inside relational databases to solve the conflation problem. The optimization models are based on the minimum cost circulation problem in operations research (also known as the network flow problem), which generalizes existing optimal conflation models that are primarily based on the assignment problem. Using comparable datasets, computational experiments show that the proposed conflation method is effective and outperforms existing optimal conflation models by a large margin. Given its generality, the new method may be applicable to other data types and conflation problems.
Geophysical exploration is developing from qualitative seismic imaging to quantitative imaging, and broadband acoustic impedance is the core. Directly estimating broadband impedance using ...Full-Waveform Inversion is a strong nonlinear problem. It is difficult to obtain a reliable result in practice. We proposed an alternative way: Estimate background velocity, density and broadband reflectivity first, then fuse them to be the broadband impedance by information fusion. This paper studies the method of fusing bandlimited reflectivity and background impedance. Due to the observation with bandlimited seismic wavelet, only bandlimited reflectivity can be obtained even after a lot of processing. The bandlimited reflectivity can lead to oscillation error in impedance. Different from the conventional post-stack impedance inversion, this paper introduces an iterative process without the need of wavelet extraction. Start from the broadband reflectivity that has been subjected to fidelity imaging, least-squares migration and magnitude calibration. In order to reduce the oscillation error, reflectivity is sparsely promoted, such that the reflection coefficients from large to small are gradually fused with background impedance. Reflectivity and impedance are mutually constrained and iteratively updated, and lateral continuity is incorporated. Numerical experiment and three-dimensional field data application demonstrate the effectiveness of the method. Impedance shows higher interpretability than reflectivity.
A deep understanding for collective behavior in an active matter system with complex interactions has far-reaching impact in biology. In the present work, we adopt Langevin dynamics simulations to ...investigate diffusion dynamics and phase separation in an anisotropic active particle system with a tunable biased angle α defined as the deviation between the active force direction and anisotropic orientation. Our results demonstrate that the biased angle can induce super-rotational diffusion dynamics characterized by a power-law relationship between the mean square angle displacement (MSAD) and the time interval Δt in the form of MSAD ∼ Δt
with β > 1 and also result in non-trivial phase separation kinetics. As activity is dominant, nucleation time shows a non-monotonic dependence on the biased angle. Moreover, there arises a distinct transition of phase separation, from spinodal decomposition without apparent nucleation time to binodal decomposition with prominent nucleation delay. A significant inhibition effect occurs at right and obtuse angles, where the remarkable super-rotational diffusion prevents particle aggregation, leading to a slow nucleation process. As active force is competitive to anisotropic interactions, the system is almost homogeneous, while, intriguingly, we observe a re-entrant phase separation as a small acute angle is introduced. The prominent super-rotational diffusion under small angles provides an optimum condition for particle adsorption and cluster growth and, thus, accounts for the re-entrance of phase separation. A consistent scenario for the physical mechanism of our observations is achieved by properly considering the modulation of the biased angle on the interplay between activity and anisotropic interactions.
► The flow behaviors of 7075 aluminum alloy were studied by the processing maps. ► The high-angle boundaries should be avoided. ► The coarse precipitations in grain interior/boundaries should be ...avoided. ► The optimum hot working domain is 623–723K and 0.001–0.05s−1.
The high-temperature flow behavior of 7075 aluminum alloy was studied by hot compressive tests. Based on the experimental data, the efficiencies of power dissipation and instability parameter were evaluated. Processing maps were constructed by superimposing the instability map over the power dissipation map. Microstructural evolution of 7075 aluminum alloy during the hot compression was analyzed to correlate with the processing maps. It can be found that the flow stresses increase with the increase of strain rate or the decrease of deformation temperature. The high-angle boundaries and coarse precipitations distributing in the grain interior/boundaries, which may result in the deep inter-granular corrosion and large areas of denudation layer, should be avoided in the final products. The optimum hot working domain is the temperature range of 623–723K and strain rate range of 0.001–0.05s−1.
Increasing performance demands and shorter use lifetimes of consumer electronics have resulted in the rapid growth of electronic waste. Currently, consumer electronics are typically made with ...nondecomposable, nonbiocompatible, and sometimes even toxic materials, leading to serious ecological challenges worldwide. Here, we report an example of totally disintegrable and biocompatible semiconducting polymers for thin-film transistors. The polymer consists of reversible imine bonds and building blocks that can be easily decomposed under mild acidic conditions. In addition, an ultrathin (800-nm) biodegradable cellulose substrate with high chemical and thermal stability is developed. Coupled with iron electrodes, we have successfully fabricated fully disintegrable and biocompatible polymer transistors. Furthermore, disintegrable and biocompatible pseudo-complementary metal–oxide–semiconductor (CMOS) flexible circuits are demonstrated. These flexible circuits are ultrathin (<1 μm) and ultralightweight (∼2 g/m²) with low operating voltage (4 V), yielding potential applications of these disintegrable semiconducting polymers in low-cost, biocompatible, and ultralightweight transient electronics.
Narrowing the mechanical mismatch between tissue and implantable microelectronics is essential for reducing immune responses and for accommodating body movement. However, the design of implantable ...soft electronics (on the order of 10 kPa in modulus) remains a challenge because of the limited availability of suitable electronic materials. Here, we report electrically conductive hydrogel-based elastic microelectronics with Young's modulus values in the kilopascal range. The system consists of a highly conductive soft hydrogel as a conductor and an elastic fluorinated photoresist as the passivation insulation layer. Owing to the high volumetric capacitance and the passivation layer of the hydrogel, electrode arrays of the thin-film hydrogel 'elastronics', 20 μm in feature size, show a significantly reduced interfacial impedance with tissue, a current-injection density that is ~30 times higher than that of platinum electrodes, and stable electrical performance under strain. We demonstrate the use of the soft elastronic arrays for localized low-voltage electrical stimulation of the sciatic nerve in live mice.
Abstract
Intrinsically and fully stretchable active-matrix-driven displays are an important element to skin electronics that can be applied to many emerging fields, such as wearable electronics, ...consumer electronics and biomedical devices. Here, we show for the first time a fully stretchable active-matrix-driven organic light-emitting electrochemical cell array. Briefly, it is comprised of a stretchable light-emitting electrochemical cell array driven by a solution-processed, vertically integrated stretchable organic thin-film transistor active-matrix, which is enabled by the development of chemically-orthogonal and intrinsically stretchable dielectric materials. Our resulting active-matrix-driven organic light-emitting electrochemical cell array can be readily bent, twisted and stretched without affecting its device performance. When mounted on skin, the array can tolerate to repeated cycles at 30% strain. This work demonstrates the feasibility of skin-applicable displays and lays the foundation for further materials development.
Cholangiocarcinoma, also known as bile duct cancer, is the second most common primary hepatic carcinoma with a median survival of less than 2 years. The molecular mechanisms underlying the ...development of this disease are not clear. To survey activated tyrosine kinases signaling in cholangiocarcinoma, we employed immunoaffinity profiling coupled to mass spectrometry and identified DDR1, EPHA2, EGFR, and ROS tyrosine kinases, along with over 1,000 tyrosine phosphorylation sites from about 750 different proteins in primary cholangiocarcinoma patients. Furthermore, we confirmed the presence of ROS kinase fusions in 8.7% (2 out of 23) of cholangiocarcinoma patients. Expression of the ROS fusions in 3T3 cells confers transforming ability both in vitro and in vivo, and is responsive to its kinase inhibitor. Our data demonstrate that ROS kinase is a promising candidate for a therapeutic target and for a diagnostic molecular marker in cholangiocarcinoma. The identification of ROS tyrosine kinase fusions in cholangiocarcinoma, along with the presence of other ROS kinase fusions in lung cancer and glioblastoma, suggests that a more broadly based screen for activated ROS kinase in cancer is warranted.
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