Proper Topology Research Articles

DreamUDF: Generating Unsigned Distance Fields from A Single Image

Recent advances in diffusion models and neural implicit surfaces have shown promising progress in generating 3D models. However, existing generative frameworks are limited to closed surfaces, failing to cope with a wide range of commonly seen shapes that have open boundaries. In this work, we present DreamUDF, a novel framework for generating high-quality 3D objects with arbitrary topologies from a single image. To address the challenge of generating proper topology given sparse and ambiguous observations, we propose to incorporate both the data priors from a multi-view diffusion model and the geometry priors brought by an unsigned distance field (UDF) reconstructor. In particular, we leverage a joint framework that consists of 1) a generation module that produces a neural radiance field for photorealistic renderings from arbitrary views; and 2) a reconstruction module that distills the learnable radiance field into surfaces with arbitrary topologies. We further introduce a field coupler that bridges the radiance field and UDF under a novel optimization scheme. This allows the two modules to mutually boost each other during training. Extensive experiments and evaluations demonstrate that DreamUDF achieves high-quality reconstruction and robust 3D generation on both closed and open surfaces with arbitrary topologies, compared to the previous works.

Design Considerations for Power-Efficient Fully Integrated 3:1 Switched Capacitor DC-DC Converter for PV Modules

This article presents a power-efficient DC-DC converter based on a switched-capacitor (SC) cell in power management systems supplied for fully integrated photovoltaic (PV) modules. These modules shall provide high-performance point-of-load voltage regulation. The primary objective of this study is to better utilize capacitance and switches by selecting a proper SC topology in order to improve the power efficiency of SC converters. A general steady-state performance model is investigated to optimize and compare a variety of SC DC-DC topologies. The investigation method relies on a charge-multiplier approach and considers the impact of area constraint on capacitors. To identify the most suitable topology for a given conversion ratio, the performance-limit metrics of SC converters are calculated. The analysis provides framework to determine optimum switch size and switching frequency for a two-phase 3:1 series–parallel converter for a target load current of 10 mA implemented on a 22 nm process technology. The results shows that a minimum of 250 MHz switching frequency is desirable for achieving a target efficiency greater than 85% while maintaining the minimum output voltage of 0.34 V. The analysis results are verified through MATLAB and PSpice-based simulations.

Dispersion curve engineering for automated topology design of a unit cell in spoof surface plasmon polaritons

In this paper, an automatic design method is proposed for unit cell in spoof surface plasmon polaritons (SSPP) with an almost arbitrary dispersion curve. In this method, the pixel configuration is considered for the unit cell and, by using the binary particle swarm optimization method, the proper topology of the unit cell is explored so as to reach the target dispersion curve. Unlike the traditional method of controlling the dispersion curve, which is performed based on changing the geometric parameters of the predetermined unit cell, in this method, there is no need to know the shape of the unit cell, and the dispersion curve of the modes of SSPP unit cell can be controlled independently with more freedom. Two unit cell samples are designed in order to show the efficiency of the procedure. In the first sample, the dispersion curve is designed to have the lowest asymptotic frequency; in the second sample, the dispersion curve of the second mode is controlled independently from the first mode and is changed arbitrarily. SSPP transmission lines which are related to the unit cells of the two samples are designed, and it is demonstrated that measurement and simulation results are greatly in line with each other.

Performance Improvement of Grid-Tied PV System With Boost and Quadratic Boost Converters Using Innovatory Hybridized HPO-PO MPPT

Interconnecting photovoltaics (PV) to the grid reduces energy bills. But, Partial shading condition (PSC) limits the functionality of PV assembly due to mismatch losses, which can be mitigated with proper converter topology, Maximum Power Point Tracking (MPPT) methodology and PV array configuration. In this article, performance enrichment of grid tied 4080 W PV system with Boost Converter and Quadratic Boost Converter (QBC), operated with novel hybrid MPPT has been addressed. Simulated outcomes demonstrate that, both converter-based PV systems with suggested MPPT offers a tracking efficiency of greater than 94% in all analyzed cases and reimburse the investment in 4.709 years. To validate the performance improvement of the suggested system, a prototype of 24 V, 100 W QBC with proposed algorithm is developed using 16-bit dsPIC30F2010 and tested. It yields a maximum efficiency of 97.95%, accomplishing its goal. Further, these experimental results are compared with simulation outcomes for the same input conditions and rating.

Visualizing Orientation and Topology of ER Membrane Proteins In Planta.

The orientation of membrane proteins within the lipid bilayer is key to understanding their molecular function. Similarly, the proper topology of multispanning membrane proteins is crucial for their function. Although bioinformatics tools can predict these parameters assessing the presence of hydrophobic protein domains sufficiently long to span the membrane and other structural features, the predictions from different algorithms are often inconsistent. Therefore, experimental analysis becomes mandatory. Redox-based topology analysis exploits the steep gradient in the glutathione redox potential (EGSH) across the ER membrane of about 80mV to visualize the orientation of ER membrane proteins by fusing the EGSH biosensor roGFP2 to either the N- or the C-termini of the investigated protein sequence. Transient expression of these fusion proteins in tobacco leaves allows direct visualization of orientation and topology of ER membrane proteins in planta. The protocol outlined here is based on either a simple merge of the two excitation channels of roGFP2 or a colocalization analysis of the two channels and thus avoids ratiometric analysis of roGFP2 fluorescence.

The interdisciplinary designing in form, function, and structure coherency

The structural form in the 21st century refers to specific architectural ideas as a strong relationship between ideas, design algorithms, and production processes. Therefore, searching for the relationship between form, function, and structure in the contemporary technological context is essential. The paper analyses the strategies for a holistic understanding of interdisciplinary design through literature review and theoretical case studies on function, shape, and structure. The case study evaluates new possibilities for designers to create objects with a holistic understanding of architectural and structural principles. The key findings show how geometric variables influence the final performance of the shape and the importance of proper topology optimisation at the early stage of the design process. The paper indicates that such an approach enables a better understanding of the structure and leads to designing efficiency.

Meshless Optimization of Triply Periodic Minimal Surface Based Two-Fluid Heat Exchanger

Triply Periodic Minimal Surface (TPMS) is suitable for the heat transfer of fluids, but it is difficult to preserve the integrality of independent fluids channels during optimization. We present an effective meshless optimization framework of Triply Periodic Minimal Surface based two-fluid heat exchangers, which can be represented, analyzed and optimized using function representation. Our method is directly executed on continuous functions instead of time-consuming meshing (tetrahedral/hexahedral), thereby substantially promotes the efficiency and controllability. Specifically, a valid TPMS based two-fluid heat exchanger is first constructed by function expression. The heat exchanger consists of two independent fully-connected spaces, which are used to infill different fluids, respectively. The two spaces are divided by a smooth and continuous separating wall, which can be expressed by functions and inherits several good properties of TPMS, such as large heat exchange surface area, high-order smoothness, independence and full connectivity of each fluid channel, good mechanical properties and controllability. Then, we formulate the optimization model by controlling the thickness and topology of the separating wall directly using the function representation. Also, we adapt an efficient automatic optimization of the modeling problem by maximizing thermal energy exchange under maximum pressure drop constraint. Finally, we obtain an optimized two-fluid heat exchanger with continuous geometry changes and proper topology changes. To our knowledge, this is the first work to provide both design and optimization for the TPMS based two-fluid heat exchangers. Various numerical results demonstrate the effectiveness and efficiency of our method.

Design and Optimization of an Asymmetric Rotor IPM Motor with High Demagnetization Prevention Capability and Robust Torque Performance

In this paper, an asymmetric rotor interior permanent magnet (ARIPM) motor with high demagnetization prevention capability and robust torque performance is proposed. The key contribution of this paper lies in two aspects. On the one hand, a novel asymmetric rotor with a shifted magnet axis is proposed to improve the demagnetization prevention capability and torque density. In order to obtain a proper asymmetric rotor topology of the ARIPM motor, the multi-physical performances, especially the PM demagnetization characteristics of five types of PM arrangements, are analyzed. Furthermore, an asymmetric rotor with V- and VV-type PM arrangement is preliminarily designed, considering the multi-physical performance balance and the potentially high anti-demagnetization ability. On the other hand, it is found that the asymmetric rotor structure can not only improve the nominal value of motor performance but also can enhance the resistance to the influence of manufacturing uncertainties. Therefore, multi-objective optimization of the ARIPM motor with rotor notch design is carried out to obtain an optimal motor structure with both high nominal value and robustness of motor performances. By comparing the simulation results with those of a benchmark motor, the superiority and validity of the proposed ARIPM motor are confirmed. Experimental tests will be carried out in the future to further verify the effectiveness of the proposed motor.

Topological regulation of a transmembrane protein by luminal-to-cytosolic retrotranslocation of glycosylated sequence

Transmembrane proteins must adopt proper topology to perform their functions. We previously demonstrated that ceramide regulates TM4SF20 (transmembrane 4 L6 family 20) by altering the topology of the transmembrane protein, but the underlying mechanism remains obscure. Here we report that TM4SF20 is synthesized in the endoplasmic reticulum (ER) with a cytosolic C terminus and a luminal loop before the last transmembrane helix where N132, N148, and N163 are glycosylated. In the absence of ceramide, the sequence surrounding glycosylated N163 but not N132 is retrotranslocated from lumen to cytosol independent of ER-associated degradation. Accompanying this retrotranslocation, the C terminus of the protein is relocated from cytosol to lumen. Ceramide delays the retrotranslocation process, causing accumulation of the protein that is originally synthesized. Our findings suggest that N-linked glycans, although synthesized in the lumens, may be exposed to cytosol through retrotranslocation, a reaction that may play a crucial role in topological regulation of transmembrane proteins.

A mathematical characterization of anatomically consistent blood capillary networks

Blood microcirculation is the site of control of tissue perfusion, blood-tissue exchange, and tissue blood volume. Despite the many irregularities, almost ubiquitously, one can recognize in microcirculation vessels a hierarchy of arterioles and venules, organized in tree-like structures, and capillary plexi, organized in net-like structures. Whilst for arterioles and venules it may be envisageable to obtain geometries needed for numerical simulations from imaging techniques, the size and numerosity of capillaries makes this task much more cumbersome. For this reason, it is interesting to study approaches to generate in silico-derived artifacts of capillary networks, even in view of machine-learning based approaches which require a large amount of samples for training. Artificial networks must correctly reflect proper metrics and topology, which in turn, will ensure with proper boundary conditions a physiological blood flux in the net and a sufficient nutrient distribution in the surrounding tissues. In this paper, we introduce the sequence of curves whose limit is the space filling Hilbert curve and we discuss its inherent properties and we obtain the backbone of the artificial capillary network from a suitable element of this sequence. The backbone represents a significant synthesis of basic metric features of the network and, in this context, its properties can be studied analytically. In this framework, the Hilbert curve is a malleable entity which allows to shape the backbone according to the physical indicators. In particular, two significant factors are shown to control the network topology and scaling: the iteration step of the Hilbert curve generation and the characteristic length of the REV, respectively. Based on the points we generate for a certain iteration step, we then obtain via spline interpolation a smoothed version of the curve, which fine–tunes the tortuosity. A volumetric construction is obtained building a tubular neighborhood of the backbone, whose metrics can be computed and tuned as well. Numerical simulations of the blood flow in the obtained geometry show the physical fields occurring in the artificial network.

Reduced Multisource Switched-Capacitor Multilevel Inverter Topologies

Multisource switched-capacitor multilevel inverters are proper topologies when multiple dc sources are available as renewable energy sources. However, these multilevel inverters have the main drawbacks of requiring a large number of power semiconductors and capacitors and a low boost factor to achieve a large number of voltage levels, which complicate control, reduce performance, and raise the cost. This article presents two configurations for multisource switched-capacitor multilevel inverters. First, a basic multisource switched-capacitor topology is proposed with a small number of capacitors and semiconductors that produce a zero voltage level and a large number of positive voltage levels. The input dc sources are operated in an asymmetric trinary algorithm, while the capacitors are charged/discharged in a binary algorithm using parallel/series modes (without the need for any circuit balancing). Based on the proposed basic topology, two multilevel inverter topologies are proposed, which create bipolar output voltage levels using two different circuits at the output. The first proposed topology uses a standard H-bridge inverter at the output of the basic topology, while the second topology uses an extra switched-capacitor (self-balancing) circuit. The comparison indicates that both the proposed topologies have advantages over most of the reported multisource switched-capacitor multilevel inverters, such as a small number of capacitors, a small number of power semiconductors, low voltage stress, and high boost factor. Furthermore, the proposed topologies decrease the low cost factor in comparison to other topologies. The capacitors' capacitance, power losses, and voltage ripple losses are all measured and evaluated in detail. Theoretical research is validated with the use of laboratory prototypes to validate the performance of the proposed topologies.

Analog Integrated Circuit Topology Synthesis With Deep Reinforcement Learning

This article presents a novel deep-reinforcement-learning-based method for topology synthesis of analog-integrated circuits, especially operational amplifiers (OpAmps). It behaves like a human designer, who learns from trials, derives design knowledge and experience, and evolves gradually to finally figure out optimal manners to construct proper circuit topologies that meet design specifications. Essential design rules are defined and applied to set up the specialized environment for reinforcement learning in order to reasonably construct circuit topologies with building blocks as the basic components. Our proposed method can not only handle large-size circuit designs but also generate creative circuit topologies. The produced circuit topologies are verified by the simulation-in-loop sizing. In order to improve the evaluation efficiency, hash table and symbolic analysis techniques are utilized to significantly reduce the number of the produced topologies to be sized during the synthesis process. Compared with the state-of-the-art approaches, our proposed method significantly improves the synthesis efficiency by consuming only several hours on average to produce a trustworthy solution. Our experimental results demonstrate its sound efficiency, strong reliability, and wide applicability.

Estimation of the Kinematics and Workspace of a Robot Using Artificial Neural Networks.

At present, in specific and complex industrial operations, robots have to respect certain requirements and criteria as high kinematic or dynamic performance, specific dimensions of the workspace, or limitation of the dimensions of the mobile elements of the robot. In order to respect these criteria, a proper design of the robots has to be achieved, which requires years of practice and a proper knowledge and experience of a human designer. In order to assist the human designer in the process of designing the robots, several methods (including optimization methods) have been developed. The scientific problem addressed in this paper is the development of an artificial intelligence method to estimate the size of the workspace and the kinematics of a robot using a feedforward neural network. The method is applied on a parallel robot composed of a base platform, a mobile platform and six kinematic rotational-universal-spherical open loops. The numerical results show that, with proper training and topology, a feedforward neural network is able to estimate properly values of the volume of the workspace and the values of the generalized coordinates based on the pose of the end effector.

Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization

The transmission of high-speed data over communication channels is the function of digital communication systems. Due to linear and nonlinear distortions, data transmitted through this process is distorted. In a communication system, the channel is the medium through which signals are transmitted. The useful signal received at the receiver becomes corrupted because it is associated with noise, ISI, CCI, etc. The equalizers function at the front end of the receiver to eliminate these factors, and they are designed to make them work efficiently with proper network topology and parameters. In the case of highly dispersive and nonlinear channels, it is well known that neural network-based equalizers are more effective than linear equalizers, which use finite impulse response filters. An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. Here, in this work, to develop the symmetry-based efficient channel equalization in wireless communication, this paper proposes a modified form of bat algorithm trained with ANN for channel equalization. It adopts a population-based and local search algorithm to exploit the advantages of bats’ echolocation. The foremost initiative is to boost the flexibility of both the variants of the proposed algorithm and the utilization of proper weight, topology, and the transfer function of ANN in channel equalization. To evaluate the equalizer’s performance, MSE and BER can be calculated by considering popular nonlinear channels and adding nonlinearities. Experimental and statistical analyses show that, in comparison with the bat as well as variants of the bat and state-of-the-art algorithms, the proposed algorithm substantially outperforms them significantly, based on MSE and BER.

Selective immunocapture reveals neoplastic human mast cells secrete distinct microvesicle- and exosome-like populations of KIT-containing extracellular vesicles.

Activating mutations in the receptor KIT promote the dysregulated proliferation of human mast cells (huMCs). The resulting neoplastic huMCs secrete extracellular vesicles (EVs) that can transfer oncogenic KIT among other cargo into recipient cells. Despite potential contributions to diseases, KIT-containing EVs have not been thoroughly investigated. Here, we isolated and characterized KIT-EV subpopulations released by neoplastic huMCs using an immunocapture approach that selectively isolates EVs containing KIT in its proper topology. Immunocapture of EVs on KIT antibody-coated electron microscopy (EM) affinity grids allowed to assess the morphology and size of KIT-EVs. Immunoblot analysis demonstrated KIT-EVs have a distinct protein profile from KIT-depleted EVs, contain exosome and microvesicle markers, and are separated into these subtypes by ultracentrifugation. Cell treatment with sphingomyelinase inhibitors shifted the protein content among KIT-EV subtypes, suggesting different biogenesis routes. Proteomic analysis revealed huMC KIT-EVs are enriched in proteins involved in signalling, immune responses, and cell migration, suggesting diverse biological functions, and indicated neoplastic huMCs disseminate KIT via shuttling in heterogeneous microvesicle- and exosome-like EVs. Further, selective KIT-immunocapture will enable the enrichment of specific huMC-derived EVs from complex human biosamples and facilitate an understanding of their in vivo functions and potential to serve as biomarkers of specific biological pathologies.

Intermolecular Interactions of Nucleoside Antibiotic Tunicamycin with On-Target MraYCB-TUN and Off-Target DPAGT1-TUN in the Active Sites Delineated by Quantum Mechanics/Molecular Mechanics Calculations.

Tunicamycin (TUN) is a nucleoside antibiotic with a complex structure comprising uracil, tunicamine sugar, N-acetylglucosamine (GlcNAc), and fatty acyl tail moieties. TUN, known as a canonical inhibitor, blocks vital functions of certain transmembrane protein families, for example, the insect enzyme dolichyl phosphate α-N-acetylglucosaminylphosphotransferase (DPAGT1) of Spodoptera frugiperda and the bacterial enzyme phospho-N-acetylmuramoylpentapeptide translocase (MraYCB) of Clostridium bolteae. Accurate description of protein–drug interactions has an immense impact on structure-based drug design, while the main challenge is to create proper topology and parameter entries for TUN in modeling protein–TUN interactions given the structural complexity. Starting from DPAGT1–TUN and MraYCB–TUN crystal structures, we first sketched these structural complexes on the basis of the CHARMM36 force field and optimized each of them using quantum mechanics/molecular mechanics (QM/MM) calculations. By continuing calculations on the active site (QM region) of each optimized structure, we specified the characteristics of intermolecular interactions contributing to the binding of TUN to each active site by quantum theory of atoms in molecules (QTAIM) and natural bond orbital (NBO) analyses at the M06-2X/6-31G** level. The results outlined that TUN insertion into each active site requires multiple weak, moderate, and strong hydrogen bonds accompanying charge–dipole, dipole–dipole, and hydrophobic interactions among different TUN moieties and adjacent residues. The water-mediated interactions also play central roles in situating the uracil and tunicamine moieties of TUN within the DPAGT1 active site as well as in preserving the uracil-binding pocket in the MraYCB active site. The TUN binds more strongly to DPAGT1 than to MraYCB. The information garnered here is valuable particularly for better understanding mode of action at the molecular level, as it is conducive to developing next generations of nucleoside antibiotics.

MAX-Tree: A Novel Topology Formation for Maximal Area Coverage in Wireless Ad-Hoc Networks

For many wireless ad-hoc network (WANET) applications, including wireless sensor, robotic, and flying ad-hoc networks, area coverage is a major challenge. This challenge, which may include the number of required nodes, cumulative energy consumption, or total distance travelled, involves covering the largest possible area with the least cost. Whatever the scenario and cost functions, efficiently deploying the nodes throughout their entire missions is an important factor. For larger networks, this can best be performed using proper topology formations that are essentially designated geometric graph patterns. As a network topology formation and node deployment strategy, this study presents a unique tree-formed geometric graph pattern. With any given number of nodes, it guarantees the maximum possible combined area coverage. Considering its graph theory and Euclidean characteristics, the pattern is then described as both algebraic and algorithmic relations. The formation is remarkably scalable because it may include an unlimited number of nodes while ensuring connectivity in a tree topology. In addition to presenting a breakdown of multiple features and attributes, including symmetry and fractality, we will make a comparative analysis with six known regular lattices and a line formation. Our analyses then show that MAX-Tree covers up to twice as much area compared to all other regular lattices of the same node cardinalities while being more robust and reliable than a line formation. MAX-Tree can be extremely beneficial for drone networks, smart industry and agriculture applications, ocean-bed monitoring systems, and many other WANET scenarios.

Investigation on the flexural properties of sandwich beams with auxetic core

Availing cellular structures as the core of sandwich beams is an innovative approach to improve the efficiency of them. Nonetheless, the flexural characteristics of sandwich beams are affiliated to the core topology. Accordingly, choosing an appropriate core can have a significant efficacy on the performance of sandwich beams. The purpose of the present study is to assess the influence of using auxetic cores in flexural properties of sandwich beams. Specifically, experimental and finite element approaches were implemented to evaluate the flexural behavior, energy absorption and the stiffness of fully integrated 3D printed polymeric sandwich beams, made of square node anti-tetra chiral, arrowhead and re-entrant auxetic cores, compared with the conventional honeycomb core. Fabrication of specimens was performed using the FDM 3D printing method, and three-point bending tests were conducted on the printed specimens. Results indicated that selection of proper core topology has remarkable effect on the flexural properties of sandwich beams, and using auxetic core is potentially an efficient method to enhance mechanical properties of sandwich beams due to high load bearing capacity.

Construction of network topology and geographical vulnerability for telecommunication network

Telecommunications network is vulnerable to large-scale infrastructure failures caused by physical attacks or natural disasters. Academics view this failure as region failure, which is geographically related and highly localized. Several simplified models have been previously proposed, resulting in an inaccurate characterization of network activity. In this paper, we propose a probability model with full consideration of the actual situation, which gives a more realistic picture of network behavior. In particular, the disaster takes the form of a randomly placed disk in a plane. The research aims to find out disaster locations that can cause significant damage to network performance, i.e., vulnerable areas of the network. The topology of vulnerable areas can be redesigned to improve the network’s disaster survivability. Moreover, only a few special cases need to be judged for the sake of achieving the aim despite disasters occur randomly across the plane. Another primary contribution is our attempt to construct a proper network topology by using clusters as units. Finally, numerical experiments conducted on this network topology demonstrate the applicability of the methodology in realistic scenarios. The work in this paper provides guidance for real-world problems and offers a way to figure them.

Comparison and selection strategy of compensating topologies in two coil resonant wireless power transfer system

In this study comparisons of different compensation topologies are investigated for two coil resonant wireless power transfer systems. Compensation circuits are examined individually according to system parameters such as efficiency, equivalent impedance, frequency, load resistance, and phase angle. This paper aims to compares the system variables in order to address the constraints in the system applicability regarding the compensation topology selection in Wireless Power Transfer (WPT) systems. Topology selection schemes related to circuit parameters are given. The main motivation of this study is that it presents a suitable topology selection scheme and flow diagram according to applications with various voltages, currents, power and loads. Simulations performed for four main topologies under various load conditions concludes that choosing the proper compensation topology for appropriate load is essential. Simulation studies are carried out with the Simulink software. The results obtained from here are validated with both Matlab calculation codes and C # calculation codes. The analyses according to the frequency in various load conditions have shown that variation of efficiency depends on the compensation topology of the receiver side. Moreover, in this study, it has been revealed that the topology of the transmitter side only affects the equivalent impedance together with the amount of power drawn from the input hence it has no effect on the efficiency and load characteristics. Consequently in the case of working with low load resistance such as an electric vehicle or mobile phone charging, topologies with series compensation on the receiver side can be preferred. Correlatively, topologies with parallel compensation on the receiver side can be evaluated as suitable for high load resistance, low current, and low power operations such as biomedical appliance charging.