EFFECTS OF TWO TYPES OF CONTROLLABLE DEFORMATION ON ENERGY EXTRACTION OF A FLEXIBLE HYDROFOIL

Energy extraction capacity of controllably flexible hydrofoil was studied under two identified deformation modes. Deformation modes, flexure parameters (flexure amplitude and flexure coefficient ) and motion parameters (reduced frequency f* and pitching amplitude 0) were investigated to understand the effects of controllably flexible deformation on energy extraction. The results reveal that deformation modes affect the effective angle of attack and vortex structure, which influence hydrodynamic performance. The energy extraction capacity improves from the deformation mode 2 to the rigid hydrofoil and then to the deformation mode 1. Under the deformation mode 1, lift, moment and power coefficients are increased obviously with the increase of , while they increase slightly with . Power coefficients and efficiency are sensitive to , which influences the development of leading-edge vortices. The flexible coefficient affects the wake structure, which has less impact on variation of force coefficient. As the increase in f*, averaged power coefficients firstly increase and then decrease. Further, the optimal f* is subjected to 0. Interestingly, a critical reduced frequency f*s, which is generally increase with increasing 0, was found under three modes. The condition that f* > f*s. is a prerequisite for subsequent adjustments of flexure modes and parameters according to different requirement of power coefficient under different tidal currents. The range of high efficiency () is: deformation mode 1 (36.1% rigid hydrofoils (34.2% deformation mode 2 (26.9%<<30.3%)

Intelligent Technology Analysis in Electronic Engineering Automation Control

The reason why human society will develop more and more civilized and intelligent is because human beings are becoming more and more intelligent and their demand for scientific and technological intelligence is increasing. It is precisely because of human’s continuous pursuit of superior artificial intelligence that the improvement and development of China’s electronic engineering automation system has been promoted. Intelligent technology is also gradually applied to the automation system of electronic engineering, which brings great convenience to electric power engineering. The wide application of intelligent technology in electronic automation system is conducive to the improvement of the control level of electric power system in China and the improvement of people’s living standard. This paper mainly analyzes the intelligent technology in the electronic engineering automation control, and narrates its advantages, characteristics, present situation and application for your reference

Condensation tendency and planar isotropic actin gradient induce radial alignment in confined monolayers

A monolayer of highly motile cells can establish long-range orientational order, which can be explained by hydrodynamic theory of active gels and fluids. However, it is less clear how cell shape changes and rearrangement are governed when the monolayer is in mechanical equilibrium states when cell motility diminishes. In this work, we report that rat embryonic fibroblasts (REF), when confined in circular mesoscale patterns on rigid substrates, can transition from the spindle shapes to more compact morphologies. Cells align radially only at the pattern boundary when they are in the mechanical equilibrium. This radial alignment disappears when cell contractility or cell-cell adhesion is reduced. Unlike monolayers of spindle-like cells such as NIH-3T3 fibroblasts with minimal intercellular interactions or epithelial cells like Madin-Darby canine kidney (MDCK) with strong cortical actin network, confined REF monolayers present an actin gradient with isotropic meshwork, suggesting the existence of a stiffness gradient. In addition, the REF cells tend to condense on soft substrates, a collective cell behavior we refer to as the ‘condensation tendency’. This condensation tendency, together with geometrical confinement, induces tensile prestretch (i.e. an isotropic stretch that causes tissue to contract when released) to the confined monolayer. By developing a Voronoi-cell model, we demonstrate that the combined global tissue prestretch and cell stiffness differential between the inner and boundary cells can sufficiently define the cell radial alignment at the pattern boundary

Biomechanical microenvironment regulates fusogenicity of breast cancer cells

Fusion of cancer cells is thought to contribute to tumor development and drug resistance. The low frequency of cell fusion events and the instability of fused cells have hindered our ability to understand the molecular mechanisms that govern cell fusion. We have demonstrated that several breast cancer cell lines can fuse into multinucleated giant cells in vitro, and the initiation and longevity of fused cells can be regulated solely by biophysical factors. Dynamically tuning the adhesive area of the patterned substrates, reducing cytoskeletal tensions pharmacologically, altering matrix stiffness, and modulating pattern curvature all supported the spontaneous fusion and stability of these multinucleated giant cells. These observations highlight that the biomechanical microenvironment of cancer cells, including the matrix rigidity and interfacial curvature, can directly modulate their fusogenicity, an unexplored mechanism through which biophysical cues regulate tumor progression

Imaging and detecting intercellular tensile forces in spheroids and embryoid bodies using lipid-modified DNA probes

Cells continuously experience and respond to different physical forces that are used to regulate their physiology and functions. Our ability to measure these mechanical cues is essential for understanding the bases of various mechanosensing and mechanotransduction processes. While multiple strategies have been developed to study mechanical forces within two-dimensional (2D) cell culture monolayers, the force measurement at cell-cell junctions in real three-dimensional (3D) cell models is still pretty rare. Considering that in real biological systems, cells are exposed to forces from 3D directions, measuring these molecular forces in their native environment is thus highly critical for the better understanding of different development and disease processes. We have recently developed a type of DNA-based molecular probe for measuring intercellular tensile forces in 2D cell models. Herein, we will report the further development and first-time usage of these molecular tension probes to visualize and detect mechanical forces within 3D spheroids and embryoid bodies (EBs). These probes can spontaneously anchor onto live cell membranes via the attached lipid moieties. By varying the concentrations of these DNA probes and their incubation time, we have first characterized the kinetics and efficiency of probe penetration and loading onto tumor spheroids and stem cell EBs of different sizes. After optimization, we have further imaged and measured E-cadherin-mediated forces in these 3D spheroids and EBs for the first time. Our results indicated that these DNA-based molecular tension probes can be used to study the spatiotemporal distributions of target mechanotransduction processes. These powerful imaging tools may be potentially applied to fill the gap between ongoing research of biomechanics in 2D systems and that in real 3D cell complexes

Two-Step Induction of Trabecular Meshwork Cells from Induced Pluripotent Stem Cells for Glaucoma

Glaucoma is a leading cause of irreversible blindness worldwide. Reducing intraocular pressure is currently the only effective treatment. Elevated intraocular pressure is associated with increased resistance of the outflow pathway, mainly the trabecular meshwork (TM). Despite great progress in the field, the development of novel and effective treatment for glaucoma is still challenging. In this study, we reported that human induced pluripotent stem cells (iPSCs) can be cultured as colonies and monolayer cells expressing OCT4, alkaline phosphatase, SSEA4 and SSEA1. After induction to neural crest cells (NCCs) positive to NGFR and HNK1, the iPSCs can differentiate into TM cells. The induced iPSC-TM cells expressed TM cell marker CHI3L1, were responsive to dexamethasone treatment with increased expression of myocilin, ANGPTL7, and formed CLANs, comparable to primary TM cells. To the best of our knowledge, this is the first study that induces iPSCs to TM cells through a middle neural crest stage, which ensures a stable NCC pool and ensures the high output of the same TM cells. This system can be used to develop personalized treatments using patient-derived iPSCs, explore high throughput screening of new drugs focusing on TM response for controlling intraocular pressure, and investigate stem cell-based therapy for TM regeneration

Channel noise-induced temporal coherence transitions and synchronization transitions in adaptive neuronal networks with time delay

Using spike-timing-dependent plasticity (STDP), we study the effect of channel noise on temporal coherence and synchronization of adaptive scale-free Hodgkin-Huxley neuronal networks with time delay. It is found that the spiking regularity and spatial synchronization of the neurons intermittently increase and decrease as channel noise intensity is varied, exhibiting transitions of temporal coherence and synchronization. Moreover, this phenomenon depends on time delay, STDP, and network average degree. As time delay increases, the phenomenon is weakened, however, there are optimal STDP and network average degree by which the phenomenon becomes strongest. These results show that channel noise can intermittently enhance the temporal coherence and synchronization of the delayed adaptive neuronal networks. These findings provide a new insight into channel noise for the information processing and transmission in neural systems

Mutual and intermittent enhancements of synchronization transitions by autaptic and synaptic delay in scale-free neuron networks

In neural networks, there exist both synaptic delays among different neurons and autaptic self-feedback delays in a neuron itself. In this paper, we study synchronization transitions induced by synaptic and autaptic delays in scale-free neuron networks, mainly exploring how these two time delays affect synchronization transitions induced by each other. It is found that the synchronization transitions induced by synaptic (autaptic) delay are intermittently enhanced when autaptic (synaptic) delay is varied. There are optimal autaptic strength and synaptic coupling strength by which the synchronization transitions induced by autaptic and synaptic delays become strongest. The underlying mechanisms are briefly discussed in terms of the relationships of autaptic delay, synaptic delay, and inter-burst interval. These results show that synaptic and autaptic delays could contribute to each other and enhance synchronization transitions in the neuronal networks. This implies that autaptic and synaptic delays could play a vital role for the information transmission in neural systems

Effect of spike-timing-dependent plasticity on coherence resonance and synchronization transitions by time delay in adaptive neuronal networks

In this paper, we numerically study how time delay induces multiple coherence resonance (MCR) and synchronization transitions (ST) in adaptive Hodgkin-Huxley neuronal networks with spike-timing dependent plasticity (STDP). It is found that MCR induced by time delay STDP can be either enhanced or suppressed as the adjusting rate Ap of STDP changes, and ST by time delay varies with the increase of Ap, and there is optimal Ap by which the ST becomes strongest. It is also found that there are optimal network randomness and network size by which ST by time delay becomes strongest, and when Ap increases, the optimal network randomness and optimal network size increase and related ST is enhanced. These results show that STDP can either enhance or suppress MCR and optimal STDP can enhance ST induced by time delay in the adaptive neuronal networks. These findings provide a new insight into STDP’s role for the information processing and transmission in neural systems