An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

Control of self-assembly in micro- and nano-scale systems

Control of self-assembling systems at the micro- and nano-scale provides new opportunities for the engineering of novel materials in a bottom-up fashion. These systems have several challenges associated with control including high-dimensional and stochastic nonlinear dynamics, limited sensors for real-time measurements, limited actuation for control, and kinetic trapping of the system in undesirable configurations. Three main strategies for addressing these challenges are described, which include particle design (active self-assembly), open-loop control, and closed-loop (feedback) control. The strategies are illustrated using a variety of examples such as the design of patchy and Janus particles, the toggling of magnetic fields to induce the crystallization of paramagnetic colloids, and high-throughput crystallization of organic compounds in nanoliter droplets. An outlook of the future research directions and the necessary technological advancements for control of micro- and nano-scale self-assembly is provided.     

Stimuli-Responsive Nanocomposite Hydrogels for Biomedical Applications

The complex tissue-specific physiology that is orchestrated from the nano- to the macroscale, in conjugation with the dynamic biophysical/biochemical stimuli underlying biological processes, has inspired the design of sophisticated hydrogels and nanoparticle systems exhibiting stimuli-responsive features. Recently, hydrogels and nanoparticles have been combined in advanced nanocomposite hybrid platforms expanding their range of biomedical applications. The ease and flexibility of attaining modular nanocomposite hydrogel constructs by selecting different classes of nanomaterials/hydrogels, or tuning nanoparticle-hydrogel physicochemical interactions widely expands the range of attainable properties to levels beyond those of traditional platforms. This review showcases the intrinsic ability of hybrid constructs to react to external or internal/physiological stimuli in the scope of developing sophisticated and intelligent systems with application-oriented features. Moreover, nanoparticle-hydrogel platforms are overviewed in the context of encoding stimuli-responsive cascades that recapitulate signaling interplays present in native biosystems. Collectively, recent breakthroughs in the design of stimuli-responsive nanocomposite hydrogels improve their potential for operating as advanced systems in different biomedical applications that benefit from tailored single or multi-responsiveness.     

关于信息化测绘时代工程测量发展的思考

如今我国信息化技术全面发展，尤其对于工程测量工作领域来讲，不管是在工程建设和管理方面都产生不小的支撑引导效用。由此，笔者具体结合如今工程建设信息化测绘核心任何以及设备布置细节，进行结构整体安全管理周期和周边地理空间信息技术发展能效整理解析，试图将工程测量最新发展机遇和技术挑战问题处理完全。希望能够借此为日后一定时期范围内相关工程测量规划主体提供合理指导性建议内容，最终为我国各类工程事业可持续发展前景绽放奠定深刻适应基础。     

Mining fleet management systems: a review of models and algorithms

The objective of this paper is to review and document the mine fleet management systems’ models and algorithms. The purpose is to understand the algorithms behind the fleet management systems and the proposed academic solutions in this area to identify any gaps in the current literature and to open up opportunities to establish research questions that need to be addressed in an integrated simulation and optimisation operational planning research framework. In this paper, we review industrial fleet management systems and the main academic algorithms behind such systems. The fleet management systems are divided into three subsequently related problems to review: shortest path, production optimisation and real-time dispatching. Finally, the limitations of current algorithms for fleet management systems are documented in terms of mining practice feasibility and optimality of the solution on large-scale problems. The results of this literature review enable us to evaluate the logical links between major components of an integrated simulation and optimisation operational planning framework with current theory of fleet management systems.     

Intersecting Xenobiology and Neometabolism To Bring Novel Chemistries to Life

The diversity of life relies on a handful of chemical elements (carbon, oxygen, hydrogen, nitrogen, sulfur and phosphorus) as part of essential building blocks; some other atoms are needed to a lesser extent, but most of the remaining elements are excluded from biology. This circumstance limits the scope of biochemical reactions in extant metabolism – yet it offers a phenomenal playground for synthetic biology. Xenobiology aims to bring novel bricks to life that could be exploited for (xeno)metabolite synthesis. In particular, the assembly of novel pathways engineered to handle nonbiological elements (neometabolism) will broaden chemical space beyond the reach of natural evolution. In this review, xeno-elements that could be blended into nature's biosynthetic portfolio are discussed together with their physicochemical properties and tools and strategies to incorporate them into biochemistry. We argue that current bioproduction methods can be revolutionized by bridging xenobiology and neometabolism for the synthesis of new-to-nature molecules, such as organohalides.     

Computational Analysis of the Solid-State and Solvation Properties of Carbamazepine in Relation to its Polymorphism

The solvent-dependent polymorphism of the active pharmaceutical ingredient (API) carbamazepine is interpreted from calculations of the solid-state and API-solvent intermolecular interactions. These simulations suggested that apolar solute-solute interactions could be disrupted by apolar solvents. In contrast, the polar solute-solute interactions were found to be easily disrupted by polar and protic solvents. This is consistent with experimental observations that the crystallization of the metastable form II is more dominant in apolar solvents. The Mercury program remains the gold standard in terms of usability; however, further expansion into more complex simulation techniques could make this package of even greater use in pharmaceutical manufacturing workflows.     

Calcium phosphates grown on bacterial cellulose template

Bacterial cellulose membranes were employed as templates for calcium phosphates deposition by successive immersion in solutions of Ca(NO₃)₂·4H₂O and (NH₄)₂HPO₄, under ultrasonication. During the wet chemical reaction, mineral phases were loaded on bacterial cellulose fibrils, leading to precursor hybrid composites. These were subjected to a lyophilisation procedure in order to preserve the 3D porous aspect and afterwards to a thermal treatment with the aim of removing the polymeric phase and generating well crystallized structures. Different types of morphologies were achieved by varying the heating rate, as well as the calcination temperature and period. The as-prepared samples and the final ones were investigated from compositional and structural point of view through X-ray diffraction and Fourier-transform infrared spectroscopy and morphologically concerning by scanning electron microscopy. The magnetic properties were also evaluated in order to demonstrate the suitability of the obtained materials for the development of magnetic scaffolds dedicated to hard tissue applications.     

An iterative method for suboptimal control of linear time-delayed systems

This article presents a new approach for solving the Optimal Control Problem (OCP) of linear time-delay systems with a quadratic cost functional. The proposed method can also be used for designing optimal control time-delay systems with disturbance. In this study, the Variational Iteration Method (VIM) is employed to convert the original Time-Delay Optimal Control Problem (TDOCP) into a sequence of nonhomogeneous linear two-point boundary value problems (TPBVPs). The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term which is the limit of an adjoint vector sequence. The feedback term is determined by solving Riccati matrix differential equation. By using the finite-step iteration of a nonlinear compensation sequence, we can obtain a suboptimal control law. Finally, Illustrative examples are included to demonstrate the validity and applicability of the technique.     

Cloud based cyber-physical systems: Network evaluation study

In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers’ locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency. The most significant impact lies in the data center distance and the speed of the communication channel. Moreover, the communication protocol also has impact on the latency. The feasibility of controlling each level of RAMI 4.0 through cloud services was investigated. Experimental results showed that control is possible in many solutions, but these solutions mostly cannot depend just on cloud services. The intelligence on the edge of the network will play a significant role. The main contribution is a thorough evaluation of different cloud providers, locations, and communication protocols to provide recommendations sufficient for different levels of the RAMI 4.0 architecture.