Topology Construction Research Articles

Efficient Self‐assembly of Isoquinoline‐Based Triply Interlocked Cages

Comprehensive SummaryTriple interlocked systems represent highly intricate topological structures, formed by entwining two mechanically interlocked cages. Achieving controlled and straightforward construction of these aesthetic topologies continues to pose an enduring challenge. Herein, we employ a coordination‐driven self‐assembly strategy, capitalizing on non‐covalent interactions in conjunction with half‐sandwich metal units and meticulously designed isoquinoline‐based ligands, to achieve the effective construction of organometallic interlocked cages 1 and 2. The resulting triple interlocked system's formation and architecture were validated by single‐crystal X‐ray diffraction, electrospray ionization mass spectroscopy, and comprehensive NMR tests. The Independent Gradient Model (IGM) more intuitively demonstrates the multiple stacking interactions within cage compounds, while planarity analysis elucidates the self‐adaptability of the ligands and their tunable conformations.

What ChatGPT Has to Say About Its Topological Structure: The Anyon Hypothesis

Large language models (LLMs) achieve remarkable predictive capabilities but remain opaque in their internal reasoning, creating a pressing need for more interpretable artificial intelligence. Here, we propose bridging this explanatory gap by drawing on concepts from topological quantum computing (TQC), specifically the anyonic frameworks arising from SU(2)k theories. Anyons interpolate between fermions and bosons, offering a mathematical language that may illuminate the latent structure and decision-making processes within LLMs. By examining how these topological constructs relate to token interactions and contextual dependencies in neural architectures, we aim to provide a fresh perspective on how meaning and coherence emerge. After eliciting insights from ChatGPT and exploring low-level cases of SU(2)k models, we argue that the machinery of modular tensor categories and topological phases could inform more transparent, stable, and robust AI systems. This interdisciplinary approach suggests that quantum-theoretic principles may underpin a novel understanding of explainable AI.

Fault-tolerant topology construction and down-link rate maximization in air-ground integrated networks

Due to the advantages in flexible deployment, fast communication recovery and high quality of service (QoS), unmanned aerial vehicles (UAVs) have been widely used in wireless communications and networking. However, existing works have not sufficiently solved the problem of reliable and survivable connectivity of UAV networks. In this paper, we investigate the deployment of multiple UAVs, cooperating with a ground mobile station (GMS), to provide wireless coverage for ground users. Under the constraints of satisfying different QoS of users and the resource limitation of UAVs, our aim is to minimize the number of deployed UAVs and maximize the sum down-link rate of all users. In order to ensure the survivability of the deployed UAV networks, we also constraint that each UAV has at least two disjoint paths to GMS to form a fault-tolerant topology. Unfortunately, the formulate problem is intractable and cannot be solved directly. To solve this problem, we decouple the original problem into two subproblems: (1) minimized fault-tolerant topology construction concerning user demands; (2) maximized down-link rate with access policy optimization. Then, we propose a heuristic link-cost minimization method and a potential-game-based user rate maximization method to solve the two subproblems, respectively. The effectiveness of the solution is validated through simulations. Meanwhile, ours also outperforms some baselines in minimized UAVs, down-link transmission rate as well as running time.

Aperture size control in kirigami metamaterials: Towards enhanced performance and applications

Kirigami metamaterials, inspired by the ancient art of kirigami, have recently emerged as an innovative approach for creating metamaterials with a diverse range of properties. While many studies on 2D kirigami have focused on stretchability and multi-stable properties, the variation in aperture size throughout the unfolding process of kirigami is another significant geometric feature. In this study, two novel kirigami materials are introduced, based on the topological construction of traditional triangular kirigami designs. These novel kirigami materials exhibit a wide range of aperture sizes, offering significant flexibility and tunability in stretch ratio. The diverse range of aperture sizes presents numerous potential applications at both micro and macro scales. Additionally, a hollow technique is proposed for designing kirigami cellular structures, which undergo distinct stages during the compression process characterized by low-reaction response and high-reaction response. This research expands the design possibilities of kirigami metamaterials by enabling precise adjustments in aperture sizes.

EDLIoT: A method for decreasing energy consumption and latency using scheduling algorithm in Internet of Things

Decreasing energy consumption in networks with limited resources, such as the Internet of Things, has always been one of the main challenges in guaranteeing network performance. In this article, cooperative game theory is employed to improve the cooperation patterns of fog computing resources. The EDLIoT method consists of two main steps: “Topology Construction” and “Determining Optimal Fog Computing Resources to Process IoT Object Tasks”. In the first step of the proposed method, the set of reliable communications in the network is identified to establish connections between IoT objects and fog computing resources in the form of a tree structure. Then, in the second step, a model based on cooperative game theory and the cost function is used to determine the optimal computing resources in the fog layer for outsourcing the processing tasks of IoT objects. In EDLIoT, active IoT objects perform computation in the fog layer instead of locally, to conserve energy. This is done so that IoT objects, if possible, discover the most suitable processing resources in the fog based on characteristics such as energy consumption, delay, and processing power of the computing resource. The efficiency of the proposed method has been evaluated in a simulated environment, and the results have been compared with those of previous algorithms. The results demonstrate that using the EDLIoT method, in addition to decreasing energy consumption and delay, more computing tasks can be processed through fog resources, thereby increasing the quality of service for IoT users.

Directed interactive topology optimization design for multi-agent affine formation maneuver control

This paper investigates the directed interactive topology optimization design problem for multi-agent affine formation maneuver control. Firstly, considering the optimization indexes such as information interaction cost and information spreading energy consumption, a directed topology optimization model satisfying affine formation maneuver is established, including two sub-models of topology structure construction and weight allocation. Secondly, aiming at the topological structure construction for affine formation maneuver, a directed k-rooted graph detection method is proposed, which can realize the solution of d +1 -rooted constraint for directed information interaction topology, and then an improved NSGA-II topological structure construction optimization algorithm is designed. Finally, a formation of seven agents in twodimensional space is taken as an example for simulation verification. The results show that the improved topology NSGA -II topology construction optimization The algorithm has better optimization effects, can effectively provide a variety of feasible directed interactive topologies for affine formation maneuver control, and the generated interactive topology can meet the requirements of directed d +1 -rooted graph.

Enhancing Decentralized and Personalized Federated Learning With Topology Construction

Enhancing Decentralized and Personalized Federated Learning With Topology Construction

Hybrid optimization‐based topology construction and DRNN‐based prediction method for data reduction in IoT

SummaryThe Internet of Things (IoT) acts as a prevalent networking setup that plays a vital role in everyday activities due to the increased services provided through uniform data collection. In this research paper, a hybrid optimization approach for the construction of heterogeneous multi‐hop IoT wireless sensor network (WSN) network topology and data aggregation and reduction is performed using a deep learning model. Initially, the IoT network is stimulated and the network topology is constructed using Namib Beetle Spotted Hyena Optimization (NBSHO) by considering different network parameters and encoding solutions. Moreover, the data aggregation and reduction in the IoT network are performed using a Deep Recurrent Neural Network (DRNN)‐based prediction model. In addition, the performance improvement of the designed NBSHO + DRNN approach is validated. Here, the designed NBSHO + DRNN method achieved a packet delivery ratio (PDR) of 0.469, energy of 0.367 J, prediction error of 0.237, and delay of 0.595 s.

Field-Effect Enhancement of Non-Faradaic Processes at Interfaces Governs Electrocatalytic Water Splitting Activity.

Recognizing the essential factor governing interfacial hydrogen/oxygen evolution reactions (HER/OER) is central to electrocatalytic water-splitting. Traditional strategies aiming at enhancing electrocatalytic activities have mainly focused on manipulating active site valencies or coordination environments. Herein, the role of interfacial adsorption is probed and modulated by the topological construct of the electrocatalyst, a frequently underestimated non-Faradaic mechanism in the dynamics of electrocatalysis. The engineered Co0.75Fe0.25P nanorods, anchored with FeOx clusters, manifest a marked amplification of the surface electric field, thus delivering a substantially improved bifunctional electrocatalytic performance. In alkaline water splitting anion exchange membrane (AEM) electrolyzer, the current density of 1.0Acm-2 can be achieved at a cell voltage of only 1.73V for the FeOx@Co0.75Fe0.25P|| FeOx@Co0.75Fe0.25P pairs for 120h of continuous operation at 1.0Acm-2. Detailed investigations of electronic structures, combined with valence state and coordination geometry assessments, reveal that the enhancement of catalytic behavior in FeOx@Co0.75Fe0.25P is chiefly attributed to the strengthened adsorptive interactions prompted by the intensified electric field at the surface. The congruent effects observed in FeOx-cluster-decorated Co0.75Fe0.25P nanosheets underscore the ubiquity of this effect. The results put forth a compelling proposition for leveraging interfacial charge densification via deliberate cluster supplementation.

Research on Parameter Correction of Distribution Network Model Based on CIM Model and Measurement Data

The construction of an energy distribution network can improve the system’s ability to absorb new energy, and its stable and efficient operation has become more and more important. The security and stability analysis of a distribution network needs accurate distribution network model parameters as support. At present, the installation of PMU equipment in China’s distribution network synchronous phase angle measurement unit is limited, which brings challenges to the parameter correction of the distribution network. In this paper, an automatic correction algorithm of distribution network parameters based on the CIM model and measurement data is proposed for the distribution network system without PMU. Firstly, the distribution network topology construction technology based on XML files and key fields of the distribution network is proposed, and the non/small impedance devices (such as switches) are merged and reduced. The breadth-first traversal algorithm is used to verify the connectivity of the constructed topology. Then, based on the topology construction and the least squares method, an iterative parameter correction technique is constructed. Finally, the accuracy and effectiveness of the proposed algorithm are verified in a standard IEEE 33-bus system distribution network and an example of the China Southern Power Grid. The topology connections constructed based on the CIM model have significantly enhanced the efficiency of parameter correction.

Analysis of Stokes singularities using a lateral shear interferometer

Polarization and Poincaré singularities in the optical fields can be studied by analyzing the phase singularities of mathematically constructed Stokes vector fields. The wider applicability of the Stokes construction is found by exploring the generation and detection methods for various types of Stokes singularities and their analysis. Here, we detect and analyze all forms of the Stokes singularities through lateral shear interferometry. Specifically, the projections of a Stokes singularity on three pairs of orthogonal polarization basis states, defined by the eigen polarization states of Pauli’s matrices, are analyzed through unique fork patterns in the shearogram pairs. These interference patterns also provide the topological indices of the singularities. Such a self-referencing interferometric method also helps to remove the degeneracy in the Stokes index and polarization. Through both, simulations and experiments, we have analyzed specific beams represented by higher order Poincaré sphere and hybrid order Poincaré sphere topological constructs.

Design and control studies of six-phase interleaved boost converter for integrated energy efficiency improvement of green ship

The operation of offshore vessels is characterized by stable loads during normal voyages and significant load variations when leaving port or docking. Conventional ships emit large amounts of greenhouse gases during navigation. In the development of the modern shipbuilding industry, how to effectively reduce gas emissions during ship sailing is a challenging task that still remains under-explored. Green ships equipped with new energy power systems have a greater potential for application. They are equipped with fuel cells and lithium batteries as energy sources, and such a hybrid system requires a comprehensive energy management system to achieve the power distribution between the two energy sources. In this paper, a powerful 10kW six-phase interleaved boost converter (IBC) for the hybrid power generation system of ships is designed to manage the output power of the fuel cell. Firstly, the new circuit topology design principle and construction process are introduced. Later, a step-by-step current adjustment controller is designed for the converter to progressively enforce output current and a maximum limitation of the fuel cell. Afterwards, LTspice simulation is performed to verify the ripple suppression effect and stable anti-interference performance. Finally, the designed IBC has been experimentally constructed, including the input/output current and voltage sampling, temperature control and sampling, and other functions, significantly benefiting real-world marine high-power fuel cells. The stability, reasonableness and effectiveness of the designed IBC are further evaluated through the extensive experimental analyses.

A topological construction of families of Galois covers of the line

A topological construction of families of Galois covers of the line

Trisecting a 4-dimensional book into three chapters

We describe an algorithm that takes as input an open book decomposition of a closed oriented 4-manifold and outputs an explicit trisection diagram of that 4-manifold. Moreover, a slight variation of this algorithm also works for open books on manifolds with non-empty boundary and for 3-manifold bundles over S1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$S^1$$\\end{document}. We apply this algorithm to several simple open books, demonstrate that it is compatible with various topological constructions, and argue that it generalizes and unifies several previously known constructions.

Subnetworks in BlockDAG

In this article, we study the horizontal scaling of the Waterfall network or similar blockDAG networks by applying hierarchical and graph-based clustering algorithms to partition them into subnetworks. This results in a reduction of network load and an increase in potential performance parameters of the underlying protocol. We consider methods of topology construction, propose clustering algorithms, and perform a simulation of the partitioning of a network into subnetworks.

Construction of trail networks based on growing self-organizing maps and public GPS data

Manual creation of trail maps for hikers is time-consuming and can be inaccurate. This paper presents a new method to construct trail networks based on a growing self-organizing map (GSOM) using publicly available Global Positioning System (GPS) data. Unlike other network topology construction techniques, this approach is not dependent on sequential GPS traces. Fine-tuning multiple hyperparameters enables to customize this process based on unique features of datasets and networks. The generated maps, which are trained on public GPS data, are compared to a ground truth from Open Street Map (OSM). The performance evaluation is based on the accuracy, completeness, and topological correctness of the trail maps. The proposed approach outperforms, particularly on sparse networks without significant GPS noise.

Topological Group Construction in Proximity and Descriptive Proximity Spaces

Topological Group Construction in Proximity and Descriptive Proximity Spaces

Topological phase transition in compressed van der Waals superlattice heterostructure BiTeCl/HfTe2

Abstract Based on first-principles calculations, we investigate the electronic band structures and topological properties of heterostructure BiTeCl/HfTe2 under c-direction strain. In the primitive structure, this material undergoes a phase transition from an insulator with a narrow indirect gap to a metal by strong spin–orbital coupling. When strain effect is considered, band inversion at time-reversal invariant point Z is responsible for the topological phase transition. These nontrivial topologies are caused by two different types of band crossings. The observable topological surface states in (110) surface also support that this material experiences topological phase transition twice. The layered heterostructure with van der Waals force provides us with a new desirable platform upon which to control topological phase transition and construct topological superconductors.

A Taxonomy and Survey on Grid-Based Routing Protocols Designed for Wireless Sensor Networks

Minimization of energy consumption is the main attention of researchers while developing a routing protocol for wireless sensor networks, as sensor nodes are equipped with limited power supply. Virtual topology is an integral part of routing, and grid-based routing protocols are quite popular due to their simplified and efficient virtual grid topology construction. Although a list of surveys exists that either focus on routing protocols in a broader way or on other virtual topologies, none of these surveys are concerned about grid topology and grid-based routing protocols. Having this motivation in mind and considering the impact of these routing protocols on controlling and managing the energy consumption of wireless sensor networks, this article provides an expansive assessment of grid-based routing protocols based on their methodology. In this survey, the existing grid-based routing protocols are classified into two categories from the perspective of sink mobility: static sink and mobile sink. A phase-wise comprehensive overview of these routing protocols is provided in chronological order, along with their comparative analysis. Furthermore, the characteristics, design issues, and challenges of grid-based routing protocols are also provided.

Right algebras in Sup and the topological representation of semi-unital and semi-integral quantales, revisited

Abstract Let 𝔔 be a reduced left-sided and left-stable quantale without zero divisors. This paper shows how the systematic use of the «quantization» of 2 viewed as a regular and strict right 𝔔-subalgebra of 𝔔 can both strengthen and simplify the rather complicated construction of quantale-enriched topologies given for semi-unital and semi-integral quantales in the original paper [3]. The underlying structure for this new construction is an adjoint situation between the dual category of semi-unital, semi-integral quantales and quantized topological spaces.