Modular Topology Research Articles

Inverse design of 3D reconfigurable curvilinear modular origami structures using geometric and topological reconstructions

The recent development of modular origami structures has ushered in an era for active metamaterials with multiple degrees of freedom (multi-DOF). Notably, no systematic inverse design approach for 3D curvilinear modular origami structures has been reported. Moreover, very few modular origami topologies have been studied to design active metamaterials with multi-DOF. Herein, we develop an inverse design method for constructing 3D reconfigurable architected structures — we synthesize modular origami structures whose unit cells can be volumetrically mapped into a prescribed 3D curvilinear shape followed by volumetric shrinkage to construct modules. After modification of the tubular geometry, we search through all the possible geometric and topological combinations of the modular origami structures to attain the target mobility using a topological reconstruction of modules. Our inverse design using geometric and topological reconstructions can provide an effective solution to construct 3D curvilinear reconfigurable structures with multi-DOF. Our work opens a path toward 3D reconfigurable systems based on volumetric inverse design, such as 3D active metamaterials and 3D morphing devices for automotive, aerospace, and biomedical engineering applications.

Altered development of structural MRI connectome hubs at near-term age in very and moderately preterm infants.

Preterm infants may exhibit altered developmental patterns of the brain structural network by endogenous and exogenous stimuli, which are quantifiable through hub and modular network topologies that develop in the third trimester. Although preterm brain networks can compensate for white matter microstructural abnormalities of core connections, less is known about how the network developmental characteristics of preterm infants differ from those of full-term infants. We identified 13 hubs and 4 modules and revealed subtle differences in edgewise connectivity and local network properties between 134 preterm and 76 full-term infants, identifying specific developmental patterns of the brain structural network in preterm infants. The modules of preterm infants showed an imbalanced composition. The edgewise connectivity in preterm infants showed significantly decreased long- and short-range connections and local network properties in the dorsal superior frontal gyrus. In contrast, the fusiform gyrus and several nonhub regions showed significantly increased wiring of short-range connections and local network properties. Our results suggested that decreased local network in the frontal lobe and excessive development in the occipital lobe may contribute to the understanding of brain developmental deviances in preterm infants.

AC–AC Modular Multilevel Converter—Hexverter

This article proposes the study, control and analysis of the topology of an AC–AC modular multilevel converter, known in the literature as the Hexverter. The Hexverter is capable of converting the energy between two AC systems with a reduced number of elements, if compared with other modular multilevel topologies, which makes this topology attractive in AC–AC applications. However, there are few studies about the Hexverter in the literature, so this work presents its operation principle, conducts modeling, and proposes a control scheme for the converter’s proper operation, validating the operation and control via hardware-in-the-loop emulation.

Performance investigation of modular multilevel inverter topologies for photovoltaic applications with minimal switches

Introduction. In recent years, a growing variety of technical applications have necessitated the employment of more powerful equipment. Power electronics and megawatt power levels are required in far too many medium voltage motor drives and utility applications. It is challenging to incorporate a medium voltage grid with only one power semiconductor that has been extensively modified. As a result, in high power and medium voltage settings, multiple power converter structure has been offered as a solution. A multilevel converter has high power ratings while also allowing for the utilization of renewable energy sources. Renewable energy sources such as photovoltaic, wind, and fuel cells may be readily connected to a multilevel inverter topology for enhanced outcomes. The novelty of the proposed work consists of a novel modular inverter structure for solar applications that uses fewer switches. Purpose. The proposed architecture is to decrease the number of switches and Total Harmonic Distortions. There is no need for passive filters, and the proposed design enhances power quality by creating distortion-free sinusoidal output voltage as the level count grows while also lowering power losses. Methods. The proposed topology is implemented with MATLAB / Simulink, using gating pulses and various pulse width modulation methodologies. Moreover, the proposed model also has been validated and compared to the hardware system. Results. Total harmonic distortion, number of power switches, output voltage and number of DC sources are compared with conventional topologies. Practical value. The proposed topology has been very supportive for implementing photovoltaic based multilevel inverter, which is connected to large demand in grid.

Cascaded Controller for Controlling DC Bus Voltage in Mismatched Input Powers

The lack of uniform production of panels in photovoltaic (PV) systems and snowball effects in fuel cell (FC) systems led us to use a separate dc–dc converter. In addition, in the PV and FC systems, the output voltage is low. Hence, dc–dc boost converters are commonly used in a series connection. Each small unit of a PV or FC operates independently. Therefore, another problem arises in the system that uses the series connection of the converter's output. Owing to the unequal electricity production of the cells, a voltage imbalance occurs at the output terminals. To create voltage balance, a modular structure grounded on a three-level boost converter was investigated. The main objective of this article is to design the control of a modular topology, allowing perfect control of the dc-bus voltage, even with mismatched input powers. The proposed control strategy ensures dynamical properties independent of the operating point, voltage balance, and robust control of the dc output voltage with respect to load perturbations. To ensure the balance of voltages and the control of currents, a sliding mode controller based on indirect synthesis was used. To control the dc–bus voltage, an energy controller is proposed that ensures dynamical performance independent of the operating conditions. The performance in terms of tracking and regulation, as well as its effect on the voltage balance of the output capacitors, was validated through simulations and experimental results. A comparison with a classical proportional integral (PI) approach for controlling the dc-bus voltage was performed.

Compartment niche and bamboo variety influence the diversity, composition, network and potential keystone taxa functions of rhizobacterial communities

Soil bacterial communities play a key role in regulating biogeochemical cycles and plant development. However, variations in soil bacterial communities in rhizosphere soil (RS) and bulk soil (BS) under different varieties of Phyllostachys edulis (bamboo) have not yet been investigated. In this study, we used 16S rRNA gene sequences to investigate the bacterial diversity, composition, network and potential keystone taxa functions in both RS and BS under Phyllostachys edulis and its four variants. We found that RS differed significantly from BS in terms of bacterial community diversity, composition and potential keystone taxa among the bamboo varieties. RS had a lower bacterial richness (931–1325) and Shannon index (4.9–6.3) than BS (1401–1508 and 6.5–6.8, respectively), indicating that the bacterial communities were affected by the compartment niches (i.e. RS vs. BS). The bacterial richness and Shannon index did not differ among bamboo varieties in BS but they decreased in RS following an order of P. edulis f. pachyloen (HB) > P. edulis f. luteosulcata (HC) > P. edulis (M) > P. edulis f. tao kiang (H) > P. edulis f. gracilis (JS). The co-occurrence network analysis revealed that the RS and BS bacteria showed a highly modular topology, and that the complexity of the RS bacterial network was greater (average degrees 11.9) than that of the BS network (6.4). The bacterial communities were predominantly positive, with a number of edges of 98% for RS and 87% for BS, indicating extensive reciprocal symbiosis within the bacterial communities for both RS and BS. The soil bacterial communities under JS and HC were more complex and closely connected than those under the other three varieties (M, H, HB). The co-occurrence network analysis selected 16 potential keystone taxa of soil bacteria, which are mainly involved in the biochemical carbon and nitrogen cycles. These results expand the current understanding of P. edulis soil bacterial communities at the intraspecific level, and they support further functional explorations and experimental validations of the soil bacterial strains in bamboo plants.

A framework for hierarchical compound topologies in species interaction networks

Hierarchical compound topologies of interaction networks that are segmented into internally nested modules have received scant attention, compared to simple nested and modular topologies. This is due to the lack of a theoretical model that encompasses all relevant alternative topologies, and an effective method to differentiate compound from simple topologies. Here we present a framework to address compound topologies in ecological networks. We propose a mechanistic schema of processes that generate modular, nested and compound topologies, based on differences in availability and preferences among species. We show that, in combination, these processes produce a unique signature in the structure of compound topologies. Then, we propose a procedure to identify this signature and hence discriminate among simple and compound topologies. We test the efficiency of this procedure in a set of synthetic matrices and then apply it to an actual plant–herbivore network (Asteraceae and their flowehead feeders in Brazil). In this case, the compound topology is clearly substantiated, demonstrating that these advances are applicable to empirical ecological networks and that compound patterns decidedly belong to the array of topologies to be probed in interaction assemblages at various scales. By including extramodular structures in the analysis of compound topologies, we enhance our understanding of how community‐wide networks are organized and their responses to various drivers.

Hierarchical compound topology uncovers complex structure of species interaction networks.

Nestedness and modularity have been found in many species interaction networks. Despite being conceptually distinct, negatively correlated and having different causes, these patterns often co-occur. A realistic but seldom investigated alternative to these simple topologies is hierarchical compound networks, in which the entire network is modular, and modules are internally nested. In compound networks, nestedness is suppressed by modularity at higher network hierarchical levels, but prevails at lower levels, within modules. The aims of this study are (i) to evaluate the prevalence of simple and hierarchical compound topologies in binary and weighted networks describing different kinds of species interactions and (ii) to probe the relationships between modularity and nestedness at different network hierarchical levels. With a procedure that discriminates between simple and compound structures, we re-analysed the topology of 142 well-studied binary networks including seed dispersal, host-parasite, pollination and plant-herbivore interactions; 68 of these also had quantitative information. Additionally, we tested the relationship between robustness and topology of binary networks and compared the robustness of networks with compound topologies to different sequences of species removals. Compound topologies were detected in 34% of binary and 71% of weighted networks of all interaction kinds. These results establish the hierarchical compound topology as a widespread network architecture, often undetected without quantitative data. Furthermore, they disentangle an apparent paradox: despite conflicting with overall nestedness, modularity usually co-occurs with high values of low-level nestedness. Nestedness progressively decreased, while modularity increased, from seed dispersal to host-parasite, pollination and plant-herbivore networks. There were no consistent differences in the robustness of networks with nested and compound topologies. However, compound topologies were especially vulnerable to removal sequences that accelerate the exclusion of entire modules. Compound topologies improve the depiction of ecological networks and differentiate ecological and evolutionary processes that operate at different hierarchical levels, with the potential to advance our understanding of network dynamics, stability and response to species loss or change. Quantitative data often reveal specialization patterns that are indistinguishable in binary networks, strongly improving the detection of modular and compound topologies.

Spontaneous Activity Predicts Survival of Developing Cortical Neurons.

Spontaneous activity plays a crucial role in brain development by coordinating the integration of immature neurons into emerging cortical networks. High levels and complex patterns of spontaneous activity are generally associated with low rates of apoptosis in the cortex. However, whether spontaneous activity patterns directly encode for survival of individual cortical neurons during development remains an open question. Here, we longitudinally investigated spontaneous activity and apoptosis in developing cortical cultures, combining extracellular electrophysiology with calcium imaging. These experiments demonstrated that the early occurrence of calcium transients was strongly linked to neuronal survival. Silent neurons exhibited a higher probability of cell death, whereas high frequency spiking and burst behavior were almost exclusively detected in surviving neurons. In local neuronal clusters, activity of neighboring neurons exerted a pro-survival effect, whereas on the functional level, networks with a high modular topology were associated with lower cell death rates. Using machine learning algorithms, cell fate of individual neurons was predictable through the integration of spontaneous activity features. Our results indicate that high frequency spiking activity constrains apoptosis in single neurons through sustained calcium rises and thereby consolidates networks in which a high modular topology is reached during early development.

A New Modeling and Control Scheme for Cascaded Split-Source Converter Cells

Cascaded split-source inverter (CSSI) is a new single-stage modular multilevel topology. Each cell of this converter converts dc to ac power in the buck or boost operation mode without any additional power switch. This article develops a design method based on a detailed model for CSSI. This model shows that energy storage elements experience double-fundamental frequency ripples besides high-frequency ones. It accurately calculates voltage gains and capacitor voltage and inductor current ripples. On the other hand, common carrier-based multilevel modulations have been modified in terms of both reference and carrier signals to control the inverter under symmetric and asymmetric conditions. With proposed simple modulations, the cell inductor is charged with the constant duty cycle. Also, the reverse recovery of diodes occurs in the minimum level of input current once per switching cycle and output power is distributed equally between cells. These characteristics reduce power losses, the input inductance of each cell, and the complexity of the system model. By phase-shifted pulsewidth modulation (PWM), the output voltage harmonics of three-cell CSSI are centralized around multiples of the triple switching frequency. In this method, high-frequency ripples on the network impedance are one-third of those in level-shifted PWM. Also, CSSI has been compared with cascaded multilevel inverters with voltage boosting ability and other SSI-based multilevel topologies. Validity of operation principles, mathematical relations, and modulation schemes are verified through simulation and experimental results.

A multiomics and network pharmacological study reveals the neuroprotective efficacy of Fu-Fang-Dan-Zhi tablets against glutamate-induced oxidative cell death

Neuroprotective therapy after ischemic stroke remains a significant need, but current measures are still insufficient. The Fu-Fang-Dan-Zhi tablet (FFDZT) is a proprietary Chinese medicine clinically employed to treat ischemic stroke in the recovery period. This work aims to systematically investigate the neuroprotective mechanism of FFDZT. A systems strategy that integrated metabolomics, transcriptomics, network pharmacology, and in vivo and in vitro experiments was used. First, middle cerebral artery occlusion (MCAO) model rats were treated with FFDZT. FFDZT treatment significantly reduced the infarct volume in the brains of middle cerebral artery occlusion (MCAO) model rats. Then, samples of serum and brain tissue were taken for metabolomics and transcriptomics studies, respectively; gene expression profiles of MCF7 cells treated with FFDZT and its 4 active compounds (senkyunolide I, formononetin, drilodefensin, and tanshinone IIA) were produced for CMAP analysis. Computational analysis of metabolomics and transcriptomics results suggested that FFDZT regulated glutamate and oxidative stress-related metabolites (2-hydroxybutanoic acid and 2-hydroxyglutaric acid), glutamate receptors (NMDAR, KA, and AMPA), glutamate involved pathways (glutamatergic synapse pathway; d-glutamine and d-glutamate metabolism; alanine, aspartate and glutamate metabolism), as well as the reactive oxygen species metabolic process. CMAP analysis indicated that two active ingredients of FFDZT (tanshinone ⅡA and senkyunolide I) could act as glutamate receptor antagonists. Next, putative therapeutic targets of FFDZT's active ingredients identified in the brain were collected from multiple resources and filtered by statistical criteria and tissue expression information. Network pharmacological analysis revealed extensive interactions between FFDZT's putative targets, anti-IS drug targets, and glutamate-related enzymes, while the resulting PPI network exhibited modular topology. The targets in two of the modules were significantly enriched in the glutamatergic synapse pathway. The interactions between FFDZT's ingredients and important targets were verified by molecular docking. Finally, in vitro experiments validated the effects of FFDZT and its ingredients in suppressing glutamate-induced PC12 cell injury and reducing the generation of reactive oxygen species. All of our findings indicated that FFDZT's efficacy for treating ischemic stroke could be due to its neuroprotection against glutamate-induced oxidative cell death.

Application of a modular topology optimization framework to an aerospace bracket design

Abstract In aerospace industry, optimizing designs has become inevitable in terms of weight and performance requirements. Topology optimization is the most suitable optimization type for use in the conceptual design phase. Even though academic topology optimization algorithms have a modular structure (open to development), they are often useable for a regular design domain. Alternatively, commercial topology optimization software products, on the other hand, are very useful in terms of their solution speed, accuracy, and ability to handle complex or irregular design domains. However, the user is restricted with the optimization algorithms available in the software, and these software do not usually have a modular structure. In this study, a modular topology optimization framework that combines useful features of the academic codes (e.g., modularity) and the commercial software tools (e.g., capability of easily handling complex design domains) is developed. The developed framework is tested on two popular academic topology optimization problems, followed by aerospace bracket design problem. It is observed that the proposed framework usually provides lower objective function values and converges to the optimum result in fewer iterations than the Altair Optistruct topology optimization software.

An isolated modular multi‐level AC/AC converter with high‐frequency link and pulse flip circuit for fractional frequency transmission system application

Based on the modular topology and the traditional voltage-sourced converter (VSC) model, this paper presents an isolated modular multi-level AC/AC converter with high-frequency (HF) link and pulse flip circuit for fractional frequency transmission system (FFTS) application. The proposed converter uses the HF transformer to realize electrical isolation, omitting the industrial frequency (IF) transformer with large volume and heavy weight. In the primary side of the HF transformer, the power transmission is realized by the rectifier and the inverter. In the secondary side of the HF transformer, the double H-bridges are used to realize the natural freewheeling of the leakage current, which solves the problem of voltage overshoot. On the basis of carrier phase-shifted pulse width modulation (CPS-PWM), an improved modulation strategy is proposed to realize the HF output voltage of the inverter. It has the advantages of easy expansion, no circulation current, good output voltage quality, low cost and no need of offshore converter station, so it has great potential in the field of offshore wind power grid connection. The working principle, natural freewheeling modes, modulation method and overall system control scheme of the proposed topology are introduced in detail, and the feasibility of the proposed topology is verified by simulation in MATLAB/Simulink environment and test through APPSIM platform.

A digitally controlled adaptive LDO for power management unit in sensor node

Power management unit (PMU) is the core of the sensor node SoC to achieve high performance in wireless body area network (WBAN). This article presents a low power digitally controlled low dropout regulator (LDO) targeted for the power management unit (PMU) in a sensor node. A flash-based approach, substituting the classical error amplifier with an array of dynamic comparators, is employed in order to achieve fast transient response. The proposed LDO minimizes dynamic power consumption by employing clock gating to the comparator array through detecting any abrupt change in load demand with a modular topology. In addition, during the load transient, the proposed LDO effectively detects the voltage droop and generates a set of digital control signals to activate a specific PMOS array for coarse tuning (CT) and fine-tuning (FT). The proposed LDO is capable of handling a load step of 10 μA to 1 mA with a voltage droop of 287 mV. The LDO is implemented with 180 nm CMOS technology node, producing a regulated output voltage of 0.9 V for input voltage ranges from 0.8 V to 1.8 V. The current efficiency at 1 mA load current is 99.4%, with settling time to recover the voltage droop is 80 ns at 50 MHz clock frequency.

Self-organization of in vitro neuronal assemblies drives to complex network topology

Activity-dependent self-organization plays an important role in the formation of specific and stereotyped connectivity patterns in neural circuits. By combining neuronal cultures, and tools with approaches from network neuroscience and information theory, we can study how complex network topology emerges from local neuronal interactions. We constructed effective connectivity networks using a transfer entropy analysis of spike trains recorded from rat embryo dissociated hippocampal neuron cultures between 6 and 35 days in vitro to investigate how the topology evolves during maturation. The methodology for constructing the networks considered the synapse delay and addressed the influence of firing rate and population bursts as well as spurious effects on the inference of connections. We found that the number of links in the networks grew over the course of development, shifting from a segregated to a more integrated architecture. As part of this progression, three significant aspects of complex network topology emerged. In agreement with previous in silico and in vitro studies, a small-world architecture was detected, largely due to strong clustering among neurons. Additionally, the networks developed in a modular topology, with most modules comprising nearby neurons. Finally, highly active neurons acquired topological characteristics that made them important nodes to the network and integrators of modules. These findings leverage new insights into how neuronal effective network topology relates to neuronal assembly self-organization mechanisms.

Brain morphometric similarity and flexibility.

BackgroundThe cerebral cortex is represented through multiple multilayer morphometric similarity networks to study their modular structures. The approach introduces a novel way for studying brain networks' metrics across individuals, and can quantify network properties usually not revealed using conventional network analyses.MethodsA total of 8 combinations or types of morphometric similarity networks were constructed – 4 combinations of the inter-regional cortical features on 2 brain atlases. The networks' modular structures were investigated by identifying those modular interactions that stay consistent across the combinations of inter-regional morphometric features and individuals.ResultsThe results provide evidence of the community structures as the property of (i) cortical lobar divisions, and also as (ii) the product of different combinations of morphometric features used for the construction of the multilayer representations of the cortex. For the first time, this study has mapped out flexible and inflexible morphometric similarity hubs, and evidence has been provided about variations of the modular network topology across the multilayers with age and IQ.ConclusionsThe results contribute to understanding of intra-regional characteristics in cortical interactions, which potentially can be used to map heterogeneous neurodegeneration patterns in diseased brains.

A modified modular multilevel converter topology trigger generator for a pseudospark switch.

A novel trigger generator for operating a pseudospark switch has been developed based on a modified modular multilevel converter topology using insulated gate bipolar transistors. The trigger generator can be operated in either single- or high-repetition rate shot mode. It is characterized by a fast rise time and low temporal jitter between the output trigger pulses of less than 1ns. It produces pulses of 4.5kV and 1 µs duration into a 50 Ω load that can trigger a single pseudospark switch. By minimizing the high-voltage components, faster high-voltage switching takes place and the power density of the unit is increased. Furthermore, the overall volume of the trigger generator is reduced. Using this pseudospark trigger generator, it is possible to trigger single or multiple pseudospark gaps without the requirement to use a pulse shaping circuit.

An Input-Oriented Power Sharing Control Scheme With Fast-Dynamic Response for ISOP DAB DC–DC Converter

With some advantages, such as electric isolation, high efficiency, and fast dynamic response, the input-series output-parallel (ISOP) dual-active-bridge (DAB) dc–dc converter has been regarded as one of the most promising candidates for connecting the medium voltage terminal and the low voltage terminal. For the ISOP DAB dc–dc converter, the existing control strategies are mainly focusing on the equivalent power sharing control, but the fast-dynamic response is not included and the decoupling between the regulation of input voltage and the adjustment of output voltage is not eliminated significantly. In this article, the average model of this ISOP DAB dc–dc converter is presented first, which can be employed to analyze the power distributions of this modular topology clearly. Then, an input-oriented power sharing control scheme with fast-dynamic response is proposed for ensuring both the power sharing ability and the fast-dynamic performance of the ISOP DAB dc–dc converter in this article. Compared with the existing methods, this proposed scheme can also significantly reduce the coupling between the power sharing control and the output voltage regulation. In addition, an inductance-estimating method is proposed for ensuring the power sharing performance of the ISOP DAB dc–dc converter. Finally, the experimental results are provided to verify the effectiveness of the proposed input-oriented power sharing control with fast-dynamic response for the ISOP DAB dc–dc converter system.

Rapid Evaluation Method for Modular Converter Topologies

The success of modular multilevel converters (MMCs) in high-voltage direct current (HVDC) applications has fueled the research on modular converter topologies. New modular converter topologies are often proposed, discussed, and sometimes applied in HVDC, as well as other industrial application such as STATCOMs, DC/DC HVDC, medium-voltage direct current (MVDC), etc. The performance evaluation of new modular converter topologies is a complex and time-consuming process that typically involves dynamic simulations and the design of a control system for the new converter topology. Sadly, many topologies do not progress to the implementation stage. This paper proposes a set of key performance indicators (KPIs) related to the cost and footprint of the converter and a procedure designed to rapidly evaluate these indicators for new converter topologies. The proposed methodology eliminates the need for dynamic simulations and control-system design, and is capable of identifying whether a particular converter is worth considering or not for further studies of a specific application, depending on the operating requirements. Thanks to the method outlined in this work and via the key parameters quantifying the “relevance” of the analyzed converters, promising topologies were easily identified, while the others could be rapidly discarded, resulting in saving valuable time in the study of the solutions that have a real potential. The proposed method is first described from a general point of view and then applied to a case study of the new converter topology—Open-Delta CLSC—and its application in two use cases.

Amyloid-β and tau pathologies relate to distinctive brain dysconnectomics in preclinical autosomal-dominant Alzheimer’s disease

The human brain is composed of functional networks that have a modular topology, where brain regions are organized into communities that form internally dense (segregated) and externally sparse (integrated) subnetworks that underlie higher-order cognitive functioning. It is hypothesized that amyloid-β and tau pathology in preclinical Alzheimer’s disease (AD) spread through functional networks, disrupting neural communication that results in cognitive dysfunction. We used high-resolution (voxel-level) graph-based network analyses to test whether in vivo amyloid-β and tau burden was associated with the segregation and integration of brain functional connections, and episodic memory, in cognitively unimpaired Presenilin-1 E280A carriers who are expected to develop early-onset AD dementia in ∼13 y on average. Compared to noncarriers, mutation carriers exhibited less functional segregation and integration in posterior default-mode network (DMN) regions, particularly the precuneus, and in the retrospenial cortex, which has been shown to link medial temporal regions and cortical regions of the DMN. Mutation carriers also showed greater functional segregation and integration in regions connected to the salience network, including the striatum and thalamus. Greater tau burden was associated with lower segregated and integrated functional connectivity of DMN regions, particularly the precuneus and medial prefrontal cortex. In turn, greater tau pathology was related to higher segregated and integrated functional connectivity in the retrospenial cortex and the anterior cingulate cortex, a hub of the salience network. These findings enlighten our understanding of how AD-related pathology distinctly alters the brain’s functional architecture in the preclinical stage, possibly contributing to pathology propagation and ultimately resulting in dementia.