Mechanical Performance of Eco-Friendly Sandwich Wall with Rice Husk Recycled Concrete

In the construction industry, an approach to alleviate the environmental problem is to apply ecological composite materials to the construction field. In this paper, the authors added the recycled aggregate and the rice husks to the concrete and measured the strengths of rich husk recycled concrete (RHRC) with different factors as well as determined the constitutive model. Subsequently, the flexural experiment of RHRC sandwich wall was carried out and analyzed in detail, which proved that it could bear the wind loads in normal use condition by the calculation of the experimental data. Then, the compressive experiment and analyses were conducted similarly. Moreover, the finite element method was applied to study the influence of tie bars on the flexural bearing capacity and to deduce the simplified calculation method of vertical bearing capacity of RHRC walls

Stability of nonlinear neutral delay differential equations with variable delays

We present new criteria for asymptotic stability of two classes of nonlinear neutral delay differential equations. By using two auxiliary functions on a contraction condition, we extend the results in [12]. Also we give two examples that illustrate our results

Stability results for nonlinear functional differential equations using fixed point methods

We present new conditions for stability of the zero solution for three distinct classes of scalar nonlinear delay differential equations. Our approach is based on fixed point methods and has the advantage that our conditions neither require boundedness of delays nor fixed sign conditions on the coefficient functions. Our work extends and improves a number of recent stability results for nonlinear functional differential equations in a unified framework. A number of examples are given to illustrate our main results

Stability results for nonlinear functional differential equations using fixed point methods

We present new conditions for stability of the zero solution for three distinct classes of scalar nonlinear delay differential equations. Our approach is based on fixed point methods and has the advantage that our conditions neither require boundedness of delays nor fixed sign conditions on the coefficient functions. Our work extends and improves a number of recent stability results for nonlinear functional differential equations in a unified framework. A number of examples are given to illustrate our main results

Stability of nonlinear neutral delay differential equations with variable delays

We present new criteria for asymptotic stability of two classes of nonlinear neutral delay differential equations. By using two auxiliary functions on a contraction condition, we extend the results in [12]. Also we give two examples that illustrate our results

Stability results for stochastic delayed recurrent neural networks with discrete and distributed delays

We present new conditions for asymptotic stability and exponential stability of a class of stochastic recurrent neural networks with discrete and distributed time varying delays. Our approach is based on the method using fixed point theory, which do not resort to any Liapunov function or Liapunov functional. Our results neither require the boundedness, monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. In particular, a class of neural networks without stochastic perturbations is also considered. Examples are given to illustrate our main results

Stability results for stochastic delayed recurrent neural networks with discrete and distributed delays

We present new conditions for asymptotic stability and exponential stability of a class of stochastic recurrent neural networks with discrete and distributed time varying delays. Our approach is based on the method using fixed point theory, which do not resort to any Liapunov function or Liapunov functional. Our results neither require the boundedness, monotonicity and differentiability of the activation functions nor differentiability of the time varying delays. In particular, a class of neural networks without stochastic perturbations is also considered. Examples are given to illustrate our main results

Recent Advances of NIR-II Emissive Semiconducting Polymer Dots for In Vivo Tumor Fluorescence Imaging and Theranostics

Accurate diagnosis and treatment of tumors, one of the top global health problems, has always been the research focus of scientists and doctors. Near-infrared (NIR) emissive semiconducting polymers dots (Pdots) have demonstrated bright prospects in field of in vivo tumor fluorescence imaging owing to some of their intrinsic advantages, including good water-dispersibility, facile surface-functionalization, easily tunable optical properties, and good biocompatibility. During recent years, much effort has been devoted to developing Pdots with emission bands located in the second near-infrared (NIR-II, 1000–1700 nm) region, which hold great advantages of higher spatial resolution, better signal-to-background ratios (SBR), and deeper tissue penetration for solid-tumor imaging in comparison with the visible region (400–680 nm) and the first near-infrared (NIR-I, 680–900 nm) window, by virtue of the reduced tissue autofluorescence, minimal photon scattering, and low photon absorption. In this review, we mainly summarize the latest advances of NIR-II emissive semiconducting Pdots for in vivo tumor fluorescence imaging, including molecular engineering to improve the fluorescence quantum yields and surface functionalization to elevate the tumor-targeting capability. We also present several NIR-II theranostic Pdots used for integrated tumor fluorescence diagnosis and photothermal/photodynamic therapy. Finally, we give our perspectives on future developments in this field