Hydroxyapatite cages with aligned pores for bone grafting – Seeding of human osteoblast-like cells in vitro and their response in dynamic culture mode

Hydroxyapatite (HA) is a highly regarded synthetic bone graft material. Porous HA ceramics blocks are used to substitute harvested natural bone grafts. Being similar to bone mineral, HA material integrates with the host bone through surface osteointegration and slowly resorb along with the natural bone remodeling process. The blocks in use currently have random and tortuous pore structures. The present work explores the usefulness of cage-like HA ceramic design with end-to-end open pores, with the help of in vitro cell culture methods. Such a structure, on implantation, will take up the blood factors and cells and host the bone remodeling process inside the bulk of the cage, leading to early healing. In the study, HA samples with aligned through-pores were prepared and explored in vitro, with a focus on how the pores host the cells inside and to what level the cells maintain their activity. Human osteoblast-like cells (HOS) were used, at different seeding and culturing approaches. Cell seeding was done through (i) conventional large volume cell suspension, (ii) a confined mini chamber with a limited volume of cell suspension, and (iii) placing a concentrated drop of cell suspension directly on top of the scaffold. The third approach gave the best cell adhesion and proliferation, and hence used for further explorations. A dynamic culture system was designed in-house by bifurcating the cell culture wells using vertical inserts, holding the samples horizontally with their ends open to both sides, and making the media flow across using a rocker platform. The HOS cell adhesion, viability and proliferation were tested in the HA cages, in static and dynamic culture conditions, with conventional porous ceramics as the control. The cell infiltration was deeper and the cell viability over a period of 7 days was significantly higher in dynamic culture conditions in the test samples.     

Biologically Inspired Design of Context-Aware Smart Products

The rapid development of information and communication technologies (ICTs) and cyber–physical systems (CPSs) has paved the way for the increasing popularity of smart products. Context-awareness is an important facet of product smartness. Unlike artifacts, various bio-systems are naturally characterized by their extraordinary context-awareness. Biologically inspired design (BID) is one of the most commonly employed design strategies. However, few studies have examined the BID of context-aware smart products to date. This paper presents a structured design framework to support the BID of context-aware smart products. The meaning of context-awareness is defined from the perspective of product design. The framework is developed based on the theoretical foundations of the situated function–behavior–structure ontology. A structured design process is prescribed to leverage various biological inspirations in order to support different conceptual design activities, such as problem formulation, structure reformulation, behavior reformulation, and function reformulation. Some existing design methods and emerging design tools are incorporated into the framework. A case study is presented to showcase how this framework can be followed to redesign a robot vacuum cleaner and make it more context-aware.     

Torsional statics of two-dimensionally functionally graded microtubes

A size-dependent governing equation is derived to investigate the torsional static behaviors of two-dimensionally functionally graded microtubes based on the modified couple stress theory. The shear modulus is assumed to vary along the tube’s length direction according to an exponential distribute function, and varies along the tube’s radius direction according to a power-law function. A generalized differential quadrature method is developed to determine the rotational angle and shear stresses. Some illustrative examples are given to investigate the effects of applied torques, the length scale parameter and various material compositions on the torsional angle and shear stresses.     

Synthesis of Benzophenones and in vitro Evaluation of Their Anticancer Potential in Breast and Prostate Cancer Cells

Breast and prostate cancers are frequently treated with chemotherapy. Several novel chemicals are being reported for this purpose, particularly synthetic and natural benzophenones. This work reports the synthesis of substituted 2-hydroxybenzophenones through 1,4-conjugate addition/intramolecular cycloaddition/dehydration of nitromethane on key intermediate chromones. Structures were extensively studied by means of 2D NMR spectroscopy and single-crystal XRD. Their cytotoxicity was evaluated in vitro in two breast cancer cell lines (MDA-MB-231 and T47-D) and one prostate cancer cell line (PC3). The most potent compound exhibited good cytotoxic effects against the three cancer cell lines (IC₅₀ values ranging from 12.09 to 26.49 μm ) and induced cell-cycle retardation only on prostate cancer cells, which suggested that it might exert cell-type-specific effects.     

When Does Communication Learning Need Hierarchical Multi-Agent Deep Reinforcement Learning

Abstract

Multi-agent systems need to communicate to coordinate a shared task. We show that a recurrent neural network (RNN) can learn a communication protocol for coordination, even if the actions to coordinate are performed steps after the communication phase. We show that a separation of tasks with different temporal scale is necessary for successful learning. We contribute a hierarchical deep reinforcement learning model for multi-agent systems that separates the communication and coordination task from the action picking through a hierarchical policy. We further on show, that a separation of concerns in communication is beneficial but not necessary. As a testbed, we propose the Dungeon Lever Game and we extend the Differentiable Inter-Agent Learning (DIAL) framework. We present and compare results from different model variations on the Dungeon Lever Game.     

On one boundary problem for nonlinear stationary controlled system

The object of study is nonlinear stationary controlled system of ordinary differential equations with constant disturbance in the right part. The problem of constructing the synthesising control function providing the transfer of this system from the initial state to the origin is considered. The sufficiently simple for numerical implementation algorithm of solution of the above-mentioned problem is obtained. It is shown that for local null controllability of the considered system, it is sufficient that the conditions of the Kalman's type were satisfied. In addition, the estimates restricting the choice of initial conditions and external disturbances under which the transfer is guaranteed are obtained. The main idea of the method of construction of the desired control function consists in reducing the original problem to stabilisation of a special kind linear non-stationary system and solving the Cauchy problem for an auxiliary system of ordinary differential equations closed by stabilising control. The simplicity of the realisation of this algorithm is determined by the construction of the auxiliary system and its stabilisation that could be obtained by analytical methods. The effectiveness of the method is illustrated by solving the problem of crane control and its numerical simulation.     

An energy-saving nonlinear position control strategy for electro-hydraulic servo systems

The electro-hydraulic servo system (EHSS) demonstrates numerous advantages in size and performance compared to other actuation methods. Oftentimes, its utilization in industrial and machinery settings is limited by its inferior efficiency. In this paper, a nonlinear backstepping control algorithm with an energy-saving approach is proposed for position control in the EHSS. To achieve improved efficiency, two control valves including a proportional directional valve (PDV) and a proportional relief valve (PRV) are used to achieve the control objectives. To design the control algorithm, the state space model equations of the system are transformed to their normal form and the control law through the PDV is designed using a backstepping approach for position tracking. Then, another nonlinear set of laws is derived to achieve energy-saving through the PRV input. This control design method, based on the normal form representation, imposes internal dynamics on the closed-loop system. The stability of the internal dynamics is analyzed in special cases of operation. Experimental results verify that both tracking and energy-saving objectives are satisfied for the closed-loop system.     

A web-based software tool for participatory optimization of conservation practices in watersheds

WRESTORE (Watershed Restoration Using Spatio-Temporal Optimization of Resources) is a web-based, participatory planning tool that can be used to engage with watershed stakeholder communities, and involve them in using science-based, human-guided, interactive simulation–optimization methods for designing potential conservation practices on their landscape. The underlying optimization algorithms, process simulation models, and interfaces allow users to not only spatially optimize the locations and types of new conservation practices based on quantifiable goals estimated by the dynamic simulation models, but also to include their personal subjective and/or unquantifiable criteria in the location and design of these practices. In this paper, we describe the software, interfaces, and architecture of WRESTORE, provide scenarios for implementing the WRESTORE tool in a watershed community's planning process, and discuss considerations for future developments.     

Design of disturbance observer based on adaptive-neural control for large-scale time-delay systems in the presence of actuator fault and unknown dead zone

This article presents an adaptive neural compensation scheme for a class of large-scale time delay nonlinear systems in the presence of unknown dead zone, external disturbances, and actuator faults. In this article, the quadratic Lyapunov–Krasovskii functionals are introduced to tackle the system delays. The unknown functions of the system are estimated by using radial basis function neural networks. Furthermore, a disturbance observer is developed to approximate the external disturbances. The proposed adaptive neural compensation control method is constructed by utilizing a backstepping technique. The boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis and the tracking errors are proved to converge to a small neighborhood of the origin. Simulation results are provided to illustrate the effectiveness of the proposed control approach.     

Delay compensated control of the Stefan problem and robustness to delay mismatch

This paper presents a control design for the one‐phase Stefan problem under actuator delay via a backstepping method. The Stefan problem represents a liquid‐solid phase change phenomenon which describes the time evolution of a material's temperature profile and the interface position. The actuator delay is modeled by a first‐order hyperbolic partial differential equation (PDE), resulting in a cascaded transport‐diffusion PDE system defined on a time‐varying spatial domain described by an ordinary differential equation (ODE). Two nonlinear backstepping transformations are utilized for the control design. The setpoint restriction is given to guarantee a physical constraint on the proposed controller for the melting process. This constraint ensures the exponential convergence of the moving interface to a setpoint and the exponential stability of the temperature equilibrium profile and the delayed controller in the norm. Furthermore, robustness analysis with respect to the delay mismatch between the plant and the controller is studied, which provides analogous results to the exact compensation by restricting the control gain.