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It is difficult to build dynamic models for 3D-printed soft actuators because of their material and structural flexibility and the complex intrinsic and extrinsic interactions encountered in human-centric or complex non-structural environments. Soft actuators require the control error during motion to be limited. However, existing control methods with predefined boundary constraints are designed for rigid actuators and are not directly applicable to soft actuators. In this paper, an adaptive neural controller based on a quasi-static model is proposed. The quasi-static model of the soft actuator is used to determine how the viscoelasticity of the flexible material influences the neural network, enabling the neural network to identify a better fit to the dynamic model of the soft actuator. Finally, experimental results verify that the proposed controller constrains the tracking error of the soft actuator to within the predefined boundary.

This study presents a portable device that ensures precise contact force between a subject and a probe to improve the stability and reproducibility of ultrasound (US) acquisition. The mechanical portion of the device includes a servo motor, gears, and a ball screw linear actuator; two photoelectric switches are used to limit the stroke. A combined force and position control system is developed, and a pressure threshold is introduced to reduce the chattering of the system so that it can be applied to US examinations of tissues of different stiffness levels. Force control experiments were conducted on the device, and the results showed that the device can overcome the chattering of a physician's hand and movement caused by a subject's respiration. Additionally, the stability of the US acquisition was substantially improved. Based on clinical trials on humans, this device was observed to improve the consistency of ultrasonic results and the repeatability of images, and it assisted sonographers with maintaining suitable contact force and improving imaging quality. The device can either be handheld by a physician or easily integrated with a manipulator as an autonomous robotic US acquisition device, thereby validating its potential for US applications.

To deal with the problem of energy shortage in wireless sensor networks, wireless power transfer is a promising technology. Using a mobile device (MD) to charge multiple sensor nodes simultaneously is a more efficient way to meet the requirements from a large-scale network. In this article, a periodic multinode charging and data collection scheme based on MD is proposed to maintain a perpetual network operation, in which the network is divided into multiple cells, and the MD periodically traverses each cell to charge and collect data for the sensor nodes with the objective of maximizing the amount of data collected by the unit energy of the MD. To realize a multinode charging, an anchor optimization strategy to optimize the position of anchor point in the cell is proposed. Then, in order to solve the path planning problem of MD, a discrete fireworks algorithm (DFWA) based on population entropy (PE-FWA) is proposed. Compared with MD scheduling algorithm and DFWA, experimental results show that PE-FWA has better performance.

Cortex Mori and Liuwei Dihuang nanoparticle pills nourish Qi and Yin; clear heat; treat diabetes; and promote body fluids, kidney toning, and astringent functions. These are herbal treatments associated with the mechanisms involved in nephrosis, such as the promotion of insulin secretion and enhancement of glucose use in the body via the cooked land, Cornus, or Poria. Ling and yam reduce blood sugar. Alisma orientalis and peony bark inhibit fat accumulation and blood coagulation and also show antithrombotic action. This study investigated the effects of Cortex Mori and Liuwei Dihuang nanoparticle pills on renal interstitial fibrosis and the TGF-β1/Smads signaling in adenineinduced Wistar rats with renal interstitial fibrosis. The expression of TGF-β1and Smad-2/3 protein was detected by immunohistochemistry and western blotting. The expression of TGF-β1 mRNA was detected by semiquantitative RT-PCR. The tested nanoparticle pills significantly reduced the area of renal interstitial fibrosis in treated rats compared with that in control rats (P < 0.05). Furthermore, the pills significantly reduced the expression of TGF-β1 mRNA in renal tissue of treated rats compared with that in the renal of control rats. Thus, Cortex Mori–Liuwei Dihuang nanoparticle pills may affect the mechanism that delays renal interstitial fibrosis via reducing the protein expression of Smad-2/3 and TGF-β1 and inhibiting the TGF-β/Smad singling.

Previous studies of periodic charging planning in Wireless Rechargeable Sensor Networks (WRSNs) assumed that the traveling energy of a mobile Wireless Charging Equipment (WCE) has sufficient energy for charging travel and the energy depletion rate at each sensor is identical. These assumptions, however, are not realistic. In fact, the traveling energy of the WCE is limited by the energy capacity of the WCE and the energy consumptions at different sensor nodes are imbalanced. In this paper, a periodic charging planning for a mobile WCE with limited traveling energy is proposed. With the optimization objective of maximizing the the docking time ratio, this periodic charging planning ensures that the energy of the nodes in the WRSN varies periodically and that nodes perpetually fail to die. To deal with the problem, a Hybrid Particle Swarm Optimization Genetic Algorithm (HPSOGA) is proposed due to the NP-Hard of the problem. Extensive simulations have been conducted, the experimental results indicate that the proposed periodic charging planning can avoid node deaths and keep the energy of sensor nodes varying periodically. Compared with the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), the algorithm HPSOGA outperforms both of these two algorithms empirically.

Wireless energy replenishment using mobile wireless charging equipment (WCE) has been a hot topic recently in areas of wireless rechargeable sensor networks (WRSNs) and mobile computing. Previous studies of multi-node charging planning usually assumed that the WCE was equipped with sufficient energy to accomplish the charging task. However, the energy of the WCE is limited in practice. Therefore, a multi-node charging planning algorithm with energy-limited WCE in WRSNs is proposed in this paper. Moreover, three charging planning models and their corresponding charging planning algorithms are proposed based on the different real conditions of the WCE: sufficient moving energy and limited charging energy, limited moving energy and sufficient charging energy, as well as both limited moving energy and charging energy. Furthermore, a hybrid simulated annealing discrete fireworks algorithm (HSA-DFWA) is proposed due to the NP-Hard complexity of the charging planning problem. The experiments show that compared to DFWA, MM-ANT, E-greedy, and P-greedy algorithms, the HSA-DFWA outperforms these algorithms empirically.

Environmentally friendly ammonia (NH3) decomposition has attracted a lot of interests in recent years to resolve the issue of water eutrophication from a wastewater and achieve a clean H2 storage. Here, we report a novel strategy for solar-driven ammonia decomposition by introducing a highly-activated iron phosphate (FePi) over-layer on the surface of α-Fe2O3 nanorods photoanode (FePi/Fe2O3), and innovatively propose a photoelectrochemical (PEC) ammonia degradation system with enhanced performance. After a facile electrochemical (EC) activation, the FePi over-layer is converted into FeOOH. The EC-activated over-layer provides the efficient active sites for the ammonia adsorption process, which promotes the high catalytic kinetics for ammonia oxidation reaction (AOR). Due to the synergistic effect of the electrocatalytic and the photocatalytic process, the FePi/Fe2O3 exhibits the enhanced PEC AOR performance, which competes with water oxidation reaction (WOR). Comparing to the initial concentration of ammonia, the FePi/Fe2O3 achieves a 54.4% ammonia degradation rate within 3 h at 1.23 V vs. reversible hydrogen electrode (RHE) under 1 sun illumination, which demonstrates the reliable ammonia decomposition performance. This study confirms that it is feasible to achieve PEC ammonia decomposition in an aqueous solution without chloride mediators and provides a promising strategy for the harmless treatment of ammonia wastewater.

In this study, a solution-processable compact vanadium oxide (V2O5) film with a globular nanoparticulate structure is introduced to the hole transport layer (HTL) of polymer bulk-heterojunction based solar cells comprised of PTB7:PC70BM by using a facile metal-organic decomposition method to replace the conventionally utilized poly(3,4-ethylenedioxythiophene): poly(styrenesulfonate) (PEDOT:PSS). For this, a biocompatible structure-determining agent, polyethylene glycol (PEG, Mn 300), is used as an additive in the precursor to form the nanoparticulate compact V2O5 (hereafter referred to as NP-V2O5) film, which possesses an outstandingly smooth surface morphology. The introduction of NP-V2O5 HTL via the solution process with a neutral pH condition successfully improved the stability by preventing the decomposition of indium tin oxide (ITO) glass and the penetration of heavy-metal components and moisture, which are considered as the crucial drawbacks of using PEDOT:PSS. Over 1440 h (60 days) of the stability test, an organic solar cell (OSC) with NP-V2O5 showed a significant durability, maintaining 82% of its initial power conversion efficiency (PCE), whereas an OSC with PEDOT:PSS maintained 51% of its initial PCE. Furthermore, due to the positive effects of the modified surface properties of NP-V2O5, the PCE was slightly enhanced from 7.47% to 7.89% with a significant improvement in the short-circuit current density and fill factor.

In this study, 3D Co3O4/Ni heterostructures were synthesized on the porous Ni substrate by hydrothermal method for electrochemical non-enzymatic glucose detection. Both structure and morphology of fabricated 3D Co3O4/Ni heterostructures were characterized by X-ray diffraction (XRD), Fourier transformed infrared (FTIR) and scanning electron microscopy (SEM) techniques. The results showed that the pure Co3O4 cluster nanofibers with the diameter of ca. 50 nm have grown layer by layer on the 3D Ni substrate. They provided high surface-to-volume ratio resulting in the high specific surface area of 17,886 m2/g. The electrochemical non-enzymatic sensor based on fabricated 3D Co3O4/Ni heterostructures enabled the highest sensitivity of 13,855 μA mM−1 cm−2 towards glucose reported-to-date. This sensor also exhibited fast response time (less than 1 s), detection limit as low as 1 μM (S/N = 3) and excellent selectivity to glucose at the presence of ascorbic acid, uric acid, sodium chloride, dopamine, cysteine and d -fructose.

Please be advised that the name of one of the coauthors in the original article [1] has been incorrectly spelled: ‘Ranish M. Ramachandran’ should be ‘Ranjith K. Ramachandran’.

Wafer-scale, conformal, two-dimensional (2D) TiO2-Ga2O3 n-p heterostructures with a thickness of less than 10 nm were fabricated on the Si/SiO2 substrates by the atomic layer deposition (ALD) technique for the first time with subsequent post-deposition annealing at a temperature of 250 °C. The best deposition parameters were established. The structure and morphology of 2D TiO2-Ga2O3 n-p heterostructures were characterized by the scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), electrochemical impedance spectroscopy (EIS), etc. 2D TiO2-Ga2O3 n-p heterostructures demonstrated efficient photocatalytic activity towards methyl orange (MO) degradation at the UV light (λ = 254 nm) irradiation. The improvement of TiO2-Ga2O3 n-p heterostructure capabilities is due to the development of the defects on Ga2O3-TiO2 interface, which were able to trap electrons faster. Graphical Abstract

To prolong the lifespan of the network, the auxiliary charging equipment is introduced into the traditional Wireless Sensor Networks (WSNs), known as Wireless Rechargeable Sensor Networks (WRSNs). Different from existing researches, in this paper, a periodic charging and data collecting model in WRSNs is proposed to keep the network working perpetually and improve data collection ratio. Meanwhile, the Wireless Charging Vehicle (WCV) has more working patterns, charging, waiting, and collecting data when staying at the sensor nodes. Then, the simultaneous optimization for the traveling path and time sequence is formulated to be a mixed-variable optimization problem. A novel Mixed-Variable Fireworks Optimization Algorithm (MVFOA) is proposed to solve it. A large number of experiments show the feasibility of the MVFOA, and MVFOA is superior to the Greedy Algorithm.

Considering the limited energy of the mobile wireless charging equipment (WCE) in wireless rechargeable sensor networks (WRSNs), strategies for energy replenishment and data collection are proposed. A novel path planning model for the mobile WCE based on multi-objective optimization is constructed to both replenish energy and collect data, as well as to maximize the total energy utility of the mobile WCE and minimize the average delay of data transmission. An algorithm of multi-objective ant colony optimization (ES-MOAC) based on the elitist strategy is proposed to determine the Pareto set, so that the state transition strategy and the pheromone updating strategy improve. How the parameter settings of the ant colony algorithm affect the proposed algorithm is analyzed. The results of 50 groups of numerical simulation experiments show that the average of the Pareto set of the ES-MOAC algorithm is 27.8% higher than that of the NSGA-II algorithm.

Spinel sub-stoichiometric CuxCoyO4 nano-wire framework thin-films were fabricated for the electrochemical glucose biosensors by hydrothermal-annealing process. Developed CuxCoyO4 nano-wire framework thin-films were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Brunauer-Emmet-Teller (BET) and scanning electron microscopy (SEM) techniques. The results confirmed well-established nano-wire sub-stoichiometric CuxCoyO4 framework with high specific surface area and abundant electro-active sites and channels for ions transfer. The average CuxCoyO4 nano-wire was ∼40 nm in diameter and more than 1 μm in length. In electrochemical non-enzymatic biosensor, the CuxCoyO4 electrode has demonstrated superior glucose detection capabilities including high glucose sensitivity of 13291.7 μA mM−1 cm−2, one of the fastest response time (less than 0.5 s), excellent selectivity in serum and detection limit as low as 1.36 μM. More importantly, the outstanding electro-catalytic performance and relatively simple synthesis method makes this spinel CuxCoyO4 nano-wire framework promising for sustainable improvement of electrochemical non-enzymatic glucose sensing.

In this paper, aiming at fully taking advantage of soft manipulators working ability, we propose a parameterized approximating method to characterize their force output in full workspace. We define the Workspace-Load bearing capacity Cloud (WLC) of soft arms and present the method to calculate WLC in the three-dimensional space by linear fitting. At last, finite element analysis is used to validate its effectiveness in characterizing the force output of soft arms in full workspace.

Figure S1. Nitrogen adsorptionâ desorption isotherms of (a) Co3O4, (b) Co3O4/ZnO-5, (c) Co3O4/ZnO-15, (d) Co3O4/ZnO-25, (e) Co3O4/ZnO-35, (f) Co3O4/ZnO-45, and (g) Co3O4/ZnO-55. Figure S2. Irradiation time dependent UV-vis absorbance spectra of MO aqueous solution in the presence ZnO. Figure S3. PL spectra of (a) ZnO, Co3O4, and Co3O4/ZnO heterostructures, and (b) the magnification of the square in (a). Figure S4. FTIR spectra of Co3O4 and Co3O4/ZnO heterostructures after 72Â h degradation of MO. (DOCX 779 kb)

The charging strategy for the mobile charger (MC) has been a hot research topic in wireless rechargeable sensor networks. We focus on the charging path for the MC, since the MC stops at each sensor node until the sensor node is fully charged. Most of the existing reports have designed optimization methods to obtain the charging path, with the target like minimizing the charging cost. However, the autonomous charging path planning for the MC in a changeable network is not taken into consideration. In this paper, Reinforcement Learning (RL) is introduced into the charging path planning for the MC in WRSNs. Considering the influences of the energy variation and the locations of the sensor nodes, a novel Charging Strategy in WRSNs based on RL (CSRL) is proposed so that the autonomy of the MC is improved. Simulation experiments show that CSRL can effectively prolong the lifetime of the network and improve the driving efficiency of the MC.

In this work, p-Co3O4/n-ZnO heterostructures were fabricated on Ni substrate by hydrothermal-decomposition method using cobaltous nitrate hexahydrate (Co(NO3)2·6H2O) and zinc acetate dihydrate (Zn(CH3COO)2·2H2O) as precursors with zinc acetate concentration varying from 5.0 to 55.0 mM. Structure and morphology of the developed samples were characterized by X-ray diffraction (XRD), Raman spectroscopy, and scanning electron microscopy (SEM). Effect of zinc acetate concentration on the photocatalytic activity of p-Co3O4/n-ZnO heterostructures was investigated by degradation of methyl orange (MO) under the UV light irradiation. The fabricated p-Co3O4/n-ZnO heterostructures exhibited higher photocatalytic activity than pure Co3O4 particles. In order to obtain the maximum photocatalytic activity, zinc acetate concentration was optimized. Specifically, at 35 mM of zinc acetate, the p-Co3O4/n-ZnO showed the highest photocatalytic activity with the degradation efficiency of MO reaching 89.38% after 72 h irradiation. The improvement of photocatalytic performance of p-Co3O4/n-ZnO heterostructures is due to the increased concentration of photo-generated holes on Co3O4 surface and the higher surface-to-volume ratio in the hierarchical structure formed by nano-lamellas. Graphical abstract