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This work presents a resilient distributed optimization algorithm based on the event-triggering mechanism for cyber–physical systems (CPSs) to optimize an average of convex cost functions corresponding to multiple agents under adversarial environments. Two attack scenarios, including the f -total (each agent is affected by at most f malicious agents in the whole network) and the f -local (each agent is affected by at most f malicious agents in its in-neighbor set) attacks are considered. Subsequently, the convergence conditions under these two attack scenarios are provided, respectively, both of which guarantee that the state values of benign agents converge to a bounded error range. The optimality conditions are also presented by theoretical analysis, which guarantee that the state values of benign agents converge to a safety interval constructed by local optimal values under certain graph conditions, despite the misbehavior of malicious agents. In addition, four numerical examples are presented to show the effectiveness and superiority of the event-triggering resilient distributed optimization (RDO-E) algorithm. Compared to existing resilient algorithms, the proposed method achieves resilient distributed optimization with higher accuracy and less demanding communication overheads. Finally, by applying the proposed method to the multi-microgrid system, a resilient economic dispatch problem (REDP) is successfully solved, which validates the practical viability of the RDO-E algorithm. • An event-based resilient distributed optimization (RDO-E) algorithm is developed. • The convergence and optimality analysis are conducted under different attack scenarios • The RDO-E algorithm outperforms existing algorithms in accuracy and communication resource saving. • The RDO-E algorithm is applicable to practical muli-microgrid systems. [ABSTRACT FROM AUTHOR]

A nuclear heating system integrated with a heat storage tank (HST-NHS) is a promising technical solution for countries with large-scale heating demand. HST-NHS can greatly curtail carbon dioxide emissions and contribute to sustainable development. Appropriate control strategies are not only crucial to realize the real-time matching between HST-NHS heat supply and heat demand, but also ensure the stable and safe operation of HST-NHS. Until now, control strategies for HST-NHS have received limited attention. A refined dynamic simulation model for HST-NHS is established based on APROS software. The verification of the built model in steady state and transient state is completed. Two basic control strategies for the primary heating network (PHN) of HST-NHS, constant supply water temperature and variable flow rate (CT-VF) and variable supply water temperature and constant flow rate (VT-CF) are presented in detail. Based on various typical working conditions of a central heating region in Liaoyuan City, the control effects of two control strategies are investigated. Additionally, a comprehensive performance comparison between the two strategies is explored. Simulation results indicated that under the two control strategies, the indoor temperature can be effectively controlled at a high comfort level. During the same typical day, the total energy consumption cost under the VT-CF control strategy is 0.5 × 105 yuan lower than that under the CT-VF control strategy. • Dynamic model of nuclear heating system with heat storage is developed. • The verification of the built model in steady and transient state is completed. • Control effects of two basic control strategies during typical days are evaluated. • A performance comparison of two basic control strategies is conducted. [ABSTRACT FROM AUTHOR]

Torreya grandis is a unique tree species in China. Although full use has been made of the timber, the processing and utilization of the bark has not been effective. In order to explore a new way to utilize the bark of Torreya grandis , a powder of T. grandis bark was prepared and analyzed qualitatively and quantitatively. Differential scanning calorimetry (TG) and pyrolysis gas chromatography-mass spectrometry (PY-GC/MS) revealed many bioactive components in the bark of T. grandis, such as acetic acid, 2-methoxy-4-vinyl phenol, D-mannose, and furfural. These substances have potential broad applications in the chemical industry, biomedicine, and food additives. The chemical constituents of the bark of T. grandis suggest a theoretical basis for the future development and utilization of the bark of T. grandis. [ABSTRACT FROM AUTHOR]

Abstract Most current results on coverage control using mobile sensors require that one partitioned cell is associated with precisely one sensor. In this paper, we consider a class of coverage control problems involving higher order Voronoi partitions, motivated by applications where more than one sensor is required to monitor and cover one cell. Such applications are frequent in scenarios requiring the sensors to localize targets. We introduce a framework depending on a coverage performance function incorporating higher order Voronoi cells and then design a gradient-based controller which allows the multi-sensor system to achieve a local equilibrium in a distributed manner. The convergence properties are studied and related to Lloyd algorithm. We study also the extension to coverage of a discrete set of points and its applications to clustering of discrete sets. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the formation scaling control problem for multi-agent systems by utilizing the stress matrix associated with a universally rigid framework. Compared with the existing results on formation scaling control, we consider a more challenging scenario where only one agent has the knowledge of the desired formation size. To cope with this constraint, we first propose a distributed estimator for the remaining agents to estimate the scaling parameter. Then by employing the outputs of the estimator, we design a new class of formation scaling control algorithms for universally rigid frameworks such that the overall formation converges to the prescribed shape with the desired scaling. Numerical simulations are carried out to validate the theoretical results. [ABSTRACT FROM AUTHOR]

Integrating heat storage devices with the pool-type low-temperature heating reactor (PLTHR) can improve the flexibility of PLTHR for load following. A novel low-temperature nuclear heating system (HST-NHS) is proposed, which combines the DHR-400 heating reactor system, a heat storage tank (HST), and a gas boiler (GB) to achieve real-time matching between heating supply and demand. A mixed integer nonlinear programming (MINLP) optimization model with the annual cost (AC) as the optimization objective is established. An operation strategy that considers the device priority is proposed. The capacity and operation of HST-NHS are simultaneously optimized using the CPLEX solver. The optimization results indicate that an HST with a rated capacity of 1324.14 MWh and a GB with a rated capacity of 201.69 MW can provide the operational flexibility needed for the HST-NHS throughout the heating period. When compared with comparison schemes 1 (DHR-400 and HST), 2 (DHR-400 and GB), and 3 (pure gas boiler heating system), HST-NHS achieves significant annual cost savings. Finally, a sensitivity analysis of device price and fuel price is conducted, revealing that the unit price of the DHR-400 heating reactor system and natural gas price are the main factors affecting the AC and dynamic payback period (DPP) of HST-NHS. This work offers theoretical guidance for the subsequent engineering application of the DHR-400 heating reactor system. • A novel nuclear heating system considering heat storage is proposed. • Operation strategy follows device priority is proposed. • The capacity and operation plan are optimized simultaneously by a MINLP model. • The nuclear heating system significantly reduces costs and CO 2 emissions. • Sensitivity analysis of device price and fuel price is carried out. [ABSTRACT FROM AUTHOR]

In this paper we discuss and discover several conservation and associated decay laws in distributed coordination control systems, in particular in formation shape control systems. Specifically, we reveal conservations of linear momentum and angular momentum for gradient-based multi-agent formation systems modelled by single integrators, and show several corresponding conservation/decay laws for double-integrator formation stabilization systems and double-integrator flocking systems, respectively. By exploiting translation and rotation symmetry properties and insights from Noether’s theorem, we further establish a multi-agent version of the relation between symmetry and conservation laws for gradient-based coordination systems derived from general potential functions, from which we generalize the conservation/decay laws to more general networked coordination control systems. The results hold in ambient spaces of any dimensions, and we focus on the 2-D and 3-D cases due to their natural interpretation as positions of agents. [ABSTRACT FROM AUTHOR]

Enthesis is a specialized tissue interface between the tendon and bone. Enthesis structure is very complex because of gradient changes in its composition and structure. There is currently no strategy to create a suitable environment and to regenerate the gradual-changing enthesis because of the modular complexities between two tissue types. Herein, a dual-layer organic/inorganic flexible bipolar fibrous membrane (BFM) was successfully fabricated by electrospinning to generate biomimetic non-mineralized fibrocartilage and mineralized fibrocartilage in tendon-to-bone integration of enthesis. The growth of the in situ apatite nanoparticle layer was induced on the nano hydroxyapatite-poly- l -lactic acid (nHA-PLLA) fibrous layer in simulated body solution, and the poly- l -lactic acid (PLLA) fibrous layer retained its original properties to induce tendon regeneration. The in vivo results showed that BFM significantly increased the area of glycosaminoglycan staining at the tendon–bone interface and improved collagen organization when compared to the simplex fibrous membrane (SFM) of PLLA. Implanting the bipolar membrane also induced bone formation and fibrillogenesis as assessed by micro-CT and histological analysis. Biomechanical testing showed that the BFM group had a greater ultimate load-to-failure and stiffness than the SFM group at 12 weeks after surgery. Therefore, this flexible bipolar nanofibrous membrane improves the healing and regeneration process of the enthesis in rotator cuff repair. Statement of Significance In this study, we generated a biomimetic dual-layer organic/inorganic flexible bipolar fibrous membrane by sequential electrospinning and in situ biomineralization, producing integrated bipolar fibrous membranes of PLLA fibrous membrane as the upper layer and nHA-PLLA fibrous membrane as the lower layer to mimic non-mineralized fibrocartilage and mineralized fibrocartilage in tendon-to-bone integration of enthesis. Flexible bipolar nanofibrous membranes could be easily fabricated with gradient microstructure for enthesis regeneration in rotator cuff tears. [ABSTRACT FROM AUTHOR]

Most rigid formation controllers reported in the literature aim to only stabilize a rigid formation shape, while the formation orientation is not controlled. This paper studies the problem of controlling rigid formations with prescribed orientations in both 2-D and 3-D spaces. The proposed controllers involve the commonly-used gradient descent control for shape stabilization, and an additional term to control the directions of certain relative position vectors associated with certain chosen agents. In this control framework, we show the minimal number of agents which should have knowledge of a global coordinate system (2 agents for a 2-D rigid formation and 3 agents for a 3-D rigid formation), while all other agents do not require any global coordinate knowledge or any coordinate frame alignment to implement the proposed control. The exponential convergence to the desired rigid shape and formation orientation is also proved. [ABSTRACT FROM AUTHOR]

Accurate preoperative path planning plays an essential role in a neurosurgical procedure of deep brain stimulation, leading to a successful procedure with significant surgical outcomes. Conventional preoperative path planning is time-consuming and uncertain, depending highly on the knowledge and experience of the clinician who has to manually plan the electrode-implant path. This work presents a new preoperative path planning strategy for neurostimulation to automatically and accurately find the optimal electrode-implant trajectory. Specifically, a coarse-to-refine neural network model is proposed to accurately segment anatomical brain structures such as the subthalamic nucleus, while the path planning is formulated as an optimization task that minimizes the surgical risk on the implantation trajectory through the segmented brain structures, as well as ensures the puncture path at the safest distance to targets of interest in the brain. We evaluate our method on retrospective neurostimulation data and compare it to the puncture path generated by experienced surgeons, with the experimental results showing that our method provides surgeons with automatic and accurate electrode implant trajectory comparable or even better than manual planning of fellow surgeons. • A coarse-to-refine deep learning segmentation method to extract the target and risk structures in 3D MRI data for the DBS planning. • A safe and optimized puncture trajectory to mimic surgeons for image guided preoperative path planning with 3D MRI data. • Evaluation of automatic puncture trajectory planning on postoperative 3D CT data. [ABSTRACT FROM AUTHOR]

Carbon nanotubes (CNTs) were functionalized with Lanthanum (La) modifier and appropriate acid-treatment methods. CNT-containing film was deposited on silicon substrates via a self-assembly process. The formation and microstructure of La treated CNTs and CNT-containing film were characterized by high-resolution transmission electron microscopy (HRTEM), scanning electron microscopy (SEM), X-ray photoelectron spectrometry (XPS) and water contact angle (WCA). Its tribological properties were evaluated with a UMT-2MT reciprocating friction tester. The results show that CNTs were adsorbed on silicon substrates by means of chemically bonding between La and oxygen-containing functional groups. The friction coefficient of the silicon substrates is reduced from 0.87 to 0.12 after the deposition of CNT-containing film on its surface. CNT-containing film shows excellent antiwear, friction reducing ability and load-carrying capacity due to excellent mechanical and self-lubrication properties of CNTs. [ABSTRACT FROM AUTHOR]