High-dimensional partial differential equations (PDEs) appear in a number of models from the financial industry, such as in derivative pricing models, credit valuation adjustment models, or portfolio optimization models. The PDEs in such applications are high-dimensional as the dimension corresponds to the number of financial assets in a portfolio. Moreover, such PDEs are often fully nonlinear due to the need to incorporate certain nonlinear phenomena in the model such as default risks, transaction costs, volatility uncertainty (Knightian uncertainty), or trading constraints in the model. Such high-dimensional fully nonlinear PDEs are exceedingly difficult to solve as the computational effort for standard approximation methods grows exponentially with the dimension. In this work, we propose a new method for solving high-dimensional fully nonlinear second-order PDEs. Our method can in particular be used to sample from high-dimensional nonlinear expectations. The method is based on (1) a connection between fully nonlinear second-order PDEs and second-order backward stochastic differential equations (2BSDEs), (2) a merged formulation of the PDE and the 2BSDE problem, (3) a temporal forward discretization of the 2BSDE and a spatial approximation via deep neural nets, and (4) a stochastic gradient descent-type optimization procedure. Numerical results obtained using TensorFlow in Python illustrate the efficiency and the accuracy of the method in the cases of a 100-dimensional Black–Scholes–Barenblatt equation, a 100-dimensional Hamilton–Jacobi–Bellman equation, and a nonlinear expectation of a 100-dimensional G-Brownian motion.
A simple solvent ligation effect was successfully used to disrupt the growth of a model compound, Fe[(OH)(O3P(CH2)2CO2H)]?H2O (MIL‐37), into an extended 2D structure by replacing water with dimethylformamide (DMF) as the solvent during the synthesis. Owing to the lack of ?OH group, which provides the corner‐sharing (binding) oxygen atoms for the octahedra, an amorphous and porous structure is formed. When Fe3+ is partially replaced by Ni2+, the amorphous structure remains and the resultant binary metal catalyst displays excellent photocatalytic oxygen evolution activity with almost 100 % yield achieved under visible light irradiation using [Ru(bpy)3]2+ as the photosensitizer. This study opens up new possibilities of using the simple solvent effect to synthesize high surface area metal phosphonates for catalytic and other applications. 相似文献
Peptides have important biological functions. However, their susceptibility to proteolysis limits their applications. We demonstrated here for the first time, that poly(2‐oxazoline) (POX) can work as a functional mimic of peptides. POX‐based glycine pseudopeptides, a host defense peptide mimic, had potent activities against methicillin‐resistant S. aureus, which causes formidable infections. The POX mimic showed potent activity against persisters that are highly resistant to antibiotics. S. aureus did not develop resistance to POX owning to the reactive oxygen species related antimicrobial mechanism. POX‐treated S. aureus is sensitive to common antibiotics, demonstrating no observable antimicrobial pressure or cross‐resistance in using antimicrobial POX. This study highlights POX as a new type of functional mimic of peptides and opens new avenues in designing and exploring peptide mimetics for biological functions and applications. 相似文献
A simple solvent ligation effect was successfully used to disrupt the growth of a model compound, Fe[(OH)(O3P(CH2)2CO2H)]⋅H2O (MIL-37), into an extended 2D structure by replacing water with dimethylformamide (DMF) as the solvent during the synthesis. Owing to the lack of −OH group, which provides the corner-sharing (binding) oxygen atoms for the octahedra, an amorphous and porous structure is formed. When Fe3+ is partially replaced by Ni2+, the amorphous structure remains and the resultant binary metal catalyst displays excellent photocatalytic oxygen evolution activity with almost 100 % yield achieved under visible light irradiation using [Ru(bpy)3]2+ as the photosensitizer. This study opens up new possibilities of using the simple solvent effect to synthesize high surface area metal phosphonates for catalytic and other applications. 相似文献
A novel fluorinated hyperbranched polyimide (HBPI) is synthesized by using a new triamine monomer, 1,3,5‐tris(2‐trifluoromethyl‐4‐aminophenoxy)benzene (TFAPOB) (A3), as a ‘core’ molecule, 4,4‐(hexafluoroisopropylidene)diphthalic anhydride (6FDA) as a B2 monomer, and 3,5‐ditrifuoromethylphenyl as an endcapping reagent. The polymer shows a glass transition temperature of 232 °C and a temperature of 10% weight loss at 535 °C. The HBPI presents a birefringence as low as 0.002 at 650 nm. Near‐IR results indicate that HBPI exhibits desirable properties for low loss optical waveguide applications.
Multicompartmental responsive microstructures with the capability for the pre‐programmed sequential release of multiple target molecules of opposite solubility (hydrophobic and hydrophilic) in a controlled manner have been fabricated. Star block copolymers with dual‐responsive blocks (temperature for poly(N‐isopropylacrylamide) chains and pH for poly(acrylic acid) and poly(2‐vinylpyridine) arms) and unimolecular micellar structures serve as nanocarriers for hydrophobic molecules in the microcapsule shell. The interior of the microcapsule can be loaded with water‐soluble hydrophilic macromolecules. For these dual‐loaded microcapsules, a programmable and sequential release of hydrophobic and hydrophilic molecules from the shell and core, respectively, can be triggered independently by temperature and pH variations. These stimuli affect the hydrophobicity and chain conformation of the star block copolymers to initiate out‐of‐shell release (elevated temperature), or change the overall star conformation and interlayer interactions to trigger increased permeability of the shell and out‐of‐core release (pH). Reversing stimulus order completely alters the release process. 相似文献