Preparation and Properties of Sr3B2O6:Dy3+, Eu3+ White Phosphors Using the High-Temperature Solid-State Method

Journal of Applied Spectroscopy - Sr3B2O6:Dy3+, Eu3+ single-matrix white-light-emitting materials are prepared using the high-temperature solid-state method. The microstructure, emission spectrum,...     

Three-Dimensional Structure of Recombinant Thermophilic Ribokinase from Thermus speсies 2.9 in Complex with Adenosine Diphosphate

Crystallography Reports - The three-dimensional structure of recombinant thermophilic ribokinase from Thermus speсies 2.9 was determined at 2.4 Å resolution using crystals, which were...     

A piecewise conservative method for unconstrained convex optimization

Computational Optimization and Applications - We consider a continuous-time optimization method based on a dynamical system, where a massive particle starting at rest moves in the conservative...     

A Neural Network-Based Policy Iteration Algorithm with Global $$H^2$$ -Superlinear Convergence for Stochastic Games on Domains

In this work, we propose a class of numerical schemes for solving semilinear Hamilton–Jacobi–Bellman–Isaacs (HJBI) boundary value problems which arise naturally from exit time problems of diffusion processes with controlled drift. We exploit policy iteration to reduce the semilinear problem into a sequence of linear Dirichlet problems, which are subsequently approximated by a multilayer feedforward neural network ansatz. We establish that the numerical solutions converge globally in the \(H^2\)-norm and further demonstrate that this convergence is superlinear, by interpreting the algorithm as an inexact Newton iteration for the HJBI equation. Moreover, we construct the optimal feedback controls from the numerical value functions and deduce convergence. The numerical schemes and convergence results are then extended to oblique derivative boundary conditions. Numerical experiments on the stochastic Zermelo navigation problem are presented to illustrate the theoretical results and to demonstrate the effectiveness of the method.

     

Alkaline oxygen evolution: exploring synergy between fcc and hcp cobalt nanoparticles entrapped in N-doped graphene

Herein, we report a Mott-Schottky catalyst by entrapping cobalt nanoparticles inside the N-doped graphene shell (Co@NC). The Co@NC delivered excellent oxygen evolution activity with an overpotential of merely 248 mV at a current density of 10 mA cm^–2 with promising long-term stability. The importance of Co encapsulated in NC has further been demonstrated by synthesizing Co nanoparticles without NC shell. The synergy between the hexagonal close-packed (hcp) and face-centered cubic (fcc) Co plays a major role to improve the OER activity, whereas the NC shell optimizes the electronic structure, improves the electron conductivity, and offers a large number of active sites in Co@NC. The density functional theory calculations have revealed that the hcp Co has a dominant role in the surface reaction of electrocatalytic oxygen evolution, whereas the fcc phase induces the built-in electric field at the interfaces with N-doped graphene to accelerate the H⁺ ion transport.     

Comparative Study of LiInSe2 Single Crystals for Thermal-Neutron Detection

Crystallography Reports - Two LiInSe2 single crystals, grown under different conditions, have been studied. Characteristics of these crystals for neutron detection have been compared using...     

Composition and Antifungal Activity of Lipids from Seeds of Atriplex tatarica

Chemistry of Natural Compounds -     

Restricted testing conditions for the multilinear maximal operator

Restricted testing conditions were considered recently. For the maximal operator, Hytönen, Li and Sawyer [8] first obtained parental testing condition. Later, they [9] showed that it suffices to restrict testing to doubling cubes. Chen and Lacey [3] gave a similar restricted testing condition. In our paper, we discuss a version of the latter in the multilinear setting.

     

Topical application of zein-silk sericin nanoparticles loaded with curcumin for improved therapy of dermatitis

Atopic dermatitis is characterized by leukocyte migration into the skin dermis and typically driven by excessive chemokine production at the site of inflammation. Conventional topical formulations such as gels, creams, and ointments are insufficient for this treatment because of low penetration of drug molecules into the targeted skin tissues. Herein, using a simple, green, sustainable strategy, we have developed novel primary zein nanoparticles embedded in curcumin (Cur) and coated with silk sericin (ZHSCs) for the topical delivery of Cur to penetrate into the dermis and exercise anti-dermatitis effects on the lesion with minimal side-effects. Transdermal delivery experiments and porcine skin fluorescence imaging indicated that ZHSCs facilitate the penetration of Cur across the epidermis layer of skin to reach deep-seated sites. Notably, ZHSCs = 1:0.25 (zein-to-silk sericin mass ratios of 1:0.25) markedly elevated the skin permeability and cumulative turnover of Cur transferred, which were provided a greater than a 3.8-fold increase relative to free Cur. The special nanoparticles of ZHS = 1:0.25 possessed the deepest localization depth and experience a transition of the particle structure and core-shell separation after penetrating into the dermis of skin. In a cell model of dermatitis induced by tumor necrosis factor α/interferon γ co-stimulation, compared with free Cur, Cur-loaded ZHS nanoparticles down-regulated the generation of inflammatory cytokines and chemokines in keratinocytes through suppression of the nuclear translocation of NF-κBp65 and hence exerted an anti-dermatitis effect. This strategy may provide new avenues and direction for the demanding issues of valid topical delivery systems.