Complex Topology Research Articles

Searching rooms with top-k passenger flows using indoor trajectories

In a wide variety of applications, such as indoor position selection for advertising and setting rents of different shops in a shopping mall, it is better to get the passenger flow of each room. In the indoor space, the positions of users are commonly captured by the indoor positioning system consisting of static positioning devices. And the sequence of all tracking events with the same user ordered by the corresponding time is the indoor trajectory of this user. Thus, in this paper, we define and study two essential queries named Rooms with top-k passenger flows at a Timestamp query (RkT for short) and Rooms with top-k passenger flows within a time Interval query (RkI for short), i.e., how to search rooms with top-k passenger flows at a timestamp and within a time interval in the past using indoor trajectories, respectively. For the indoor positioning system, there are only limited static positioning devices deployed in the indoor space on account of the cost. And the detection ranges of these static positioning devices only cover a small part of the indoor space. When a user is in the undetected state, there is uncertainty in its position combined with the quite complex indoor topology. Such uncertainty brings great challenges to determining the passenger flow in each room. Considering the distribution of static positioning devices, we propose a new method about how to reasonably infer where a user is in the undetected state and the corresponding probability based on its indoor trajectory and the complex indoor topology. In order to quickly retrieve the set of indoor trajectories, we propose a full Binary tree indexing indoor trajectories divided by Time intervals (BiT for short), which is built on the given set of indoor trajectories. Based on the index BiT, we propose PAT Algorithm and PAI Algorithm to efficiently process RkT and RkI queries, respectively. Extensive experiment results demonstrate superior performance of PAT Algorithm and PAI Algorithm.

How Can Anomalous-Diffusion Neural Networks Under Connectomics Generate Optimized Spatiotemporal Dynamics.

Spatiotemporal dynamics in the brain have been recognized as strongly related to the formation of perceived and cognitive diseases, such as delusions and hallucinations in Alzheimer's disease. However, two practical considerations are rarely mentioned in related mechanism research: the connectomics networking and the anomalous diffusion generated by the complex medium between neurons and the complex topology of neural networks, respectively. Furthermore, how to optimize the corresponding dynamics behaviors has excellent implications for treating brain diseases. This article first realizes the networking under connectomics for an anomalous-diffusion single-neuron model and applies a nonlinear state feedback control to generate optimized dynamic behaviors, which provides a paradigm of nonequilibrium self-organization driven by anomalous diffusion. Then, by tracing the root distribution of the characteristic equation, some controlled conditions causing or inhibiting Turing instability and Hopf bifurcation are deduced, and the effects of self-diffusion and cross diffusion on Turing instability range are also revealed. At last, thorough numerical simulations are updated to illustrate the results. It is emphasized that delay, self-diffusion, cross diffusion, and fractional order occupy dominant positions in determining the network's spatiotemporal dynamics, and utilizing the control strategy can efficiently reduce Turing instability and delay Hopf bifurcation.

On the sequential topological complexity of group homomorphisms

We define and develop a homotopy invariant notion for the sequential topological complexity of a map f:X→Y, denoted TCr(f), that interacts with TCr(X) and TCr(Y) in the same way Jamie Scott's topological complexity map TC(f) interacts with TC(X) and TC(Y). Furthermore, we apply TCr(f) to studying group homomorphisms ϕ:Γ→Λ.In addition, we give the characterization of cohomological dimension of group homomorphisms.

Topologically Enhanced Charged Storage in Complex Particles for Redox-Flow Batteries

Self-assembled complex nanoparticles are promising charge carriers for energy storage and conversion systems. High specific capacities have been realized in these materials, which has been attributed to various factors such as their high surface area with complex topology and quantum effects caused by nanoscale dimensions. They have nevertheless found limited use in applications beyond metal-ion batteries. We have investigated the deployment of micron-sized FeSe2 particles with nanostructured spikes as charge carriers in redox flow batteries. These so-called “hedgehog” particles (HPs) were found to be dispersible in aqueous media, and displayed shear-thinning rheology in suspension, which facilitated operation in a flow cell. Suspensions of HPs exhibited redox activity around -0.88 V vs Ag/AgCl at pH 14, leading to a 1.0 V open circuit voltage when deployed as the negolyte with ferro/ferricyanide as the posolyte. High current efficiencies (> 97 %) during cycling, and a volumetric capacity of up to 1.4 mol e/L (~ 36.4 Ah/L) were attained. Mechanisms for capacity fade and potential strategies for its mitigation will be discussed.

Two-phase flow simulation algorithm for numerical estimation of relative phase permeability curves of porous materials

Abstract The paper presents an algorithm for three-dimensional modelling of two-phase flows on the scale of pore size order for numerical evaluation of relative phase permeability curves of porous materials. Such an evaluation is performed based on the results of numerical simulation of primary drainage with subsequent waterflooding. In this case, models of porous materials based on three-dimensional tomographic images of rocks are used. The simulation of the flow considers the Stokes equation and the Cahn–Hilliard equation for modelling phase transfer, which allows us to determine phases using the concentration function. The combination of the phase field method and finite difference method makes it possible to correctly take into account the contact angle and stably calculate surface tension forces in domains with complex topology.

A Systems Biology Analysis of Chronic Lymphocytic Leukemia

Whole-genome sequencing has revealed that TP53, NOTCH1, ATM, SF3B1, BIRC3, ABL, NXF1, BCR, and ZAP70 are often mutated in CLL, but not consistently across all CLL patients. This paper employs a statistical thermodynamics approach in combination with the systems biology of the CLL protein–protein interaction networks to identify the most significant participant proteins in the cancerous transformation. Betti number (a topology of complexity) estimates highlight a protein hierarchy, primarily in the Wnt pathway known for aberrant CLL activation. These individually identified proteins suggest a network-targeted strategy over single-target drug development. The findings advocate for a multi-target inhibition approach, limited to several key proteins to minimize side effects, thereby providing a foundation for designing therapies. This study emphasizes a shift towards a comprehensive, multi-scale analysis to enhance personalized treatment strategies for CLL, which could be experimentally validated using siRNA or small-molecule inhibitors. The result is not just the identification of these proteins but their rank-order, offering a potent signal amplification in the context of the 20,000 proteins produced by the human body, thus providing a strategic basis for therapeutic intervention in CLL, underscoring the necessity for a more holistic, cellular, chromosomal, and genome-wide study to develop tailored treatments for CLL patients.

A hybrid physical and co-simulation modern adaptive power protection testbed for testing the resilience of smart grids under cyber-physical threats

Power protection systems play a critical role in ensuring the safe and reliable operation of modern power grids. With the increasing complexity of grid topologies and the integration of Distributed Energy Resources (DERs), traditional protection schemes face challenges in maintaining effective coordination among relay systems. This paper presents a new adaptive Overcurrent Relay (OCR) protection and investigates the resilience of different traditional and new adaptive OCR protection schemes against various cyber-physical threats in a smart grid environment. Key contributions include the implementation of a novel adaptive protection scheme designed to dynamically adjust OCR settings based on real-time grid conditions, improving flexibility and responsiveness in managing grid variations induced by DER integration and operational changes. The proposed scheme is validated and implemented using the Multifunction Protection Relay SIEMENS 7SJ62, following to the programming standards of IEC 61131–3, ensuring the reliability and practical applicability of the adaptive OCR scheme in real-world scenarios. Additionally, a dedicated testbed is developed to simulate real-time cyber-physical interactions, incorporating hardware components such as the SIEMENS 7SJ62 and OMICRON-256 test device, along with high-performance computers and communication networks to facilitate comprehensive evaluations of adaptive OCR schemes under varying operational conditions. The study also examines the implications of real-time cyber-attacks on power system operations and the effectiveness of adaptive OCR protection schemes, addressing cybersecurity concerns and proposing mitigation strategies to the system resilience.

Below the surface: Unraveling the intricacies of the nonlinear optical properties of aluminum through bound electrons

By uncovering novel aspects of second harmonic generation in aluminum, we show that there are unusual and remarkable consequences of resonant absorption, namely an unexpectedly critical role that bound electrons play for light–matter interactions across the optical spectrum, suggesting that a different basic approach is required to fully explain the physics of surfaces. We tackle an issue that is never under consideration given the generic hostile conditions to the propagation of light under resonant absorption. Unlike most noble metals, aluminum displays Lorentz-like behavior and interband transitions centered near 810 nm, thus splitting the plasmonic range in an atypical manner and setting its linear and nonlinear optical properties apart. Studies of aluminum nanostructures having complex topologies abound, as do reported inconsistencies in the linear spectral response of surface plasmons and harmonic generation. Our experimental observations of second harmonic generation from aluminum nanolayers show that bound electrons are responsible for a unique signature neither predicted nor observed previously: a hole in the second harmonic spectrum. A hydrodynamic-Maxwell theory explains these findings exceptionally well and becomes the basis for renewed studies of surface physics.

Exploring a unique class of flavoenzymes: Identification and biochemical characterization of ribosomal RNA dihydrouridine synthase

Dihydrouridine (D), a prevalent and evolutionarily conserved base in the transcriptome, primarily resides in tRNAs and, to a lesser extent, in mRNAs. Notably, this modification is found at position 2449 in the Escherichia coli 23S rRNA, strategically positioned near the ribosome's peptidyl transferase site. Despite the prior identification, in E. coli genome, of three dihydrouridine synthases (DUS), a set of NADPH and FMN-dependent enzymes known for introducing D in tRNAs and mRNAs, characterization of the enzyme responsible for D2449 deposition has remained elusive. This study introduces a rapid method for detecting D in rRNA, involving reverse transcriptase-blockage at the rhodamine-labeled D2449 site, followed by PCR amplification (RhoRT-PCR). Through analysis of rRNA from diverse E. coli strains, harboring chromosomal or single-gene deletions, we pinpoint the yhiN gene as the ribosomal dihydrouridine synthase, now designated as RdsA. Biochemical characterizations uncovered RdsA as a unique class of flavoenzymes, dependent on FAD and NADH, with a complex structural topology. In vitro assays demonstrated that RdsA dihydrouridylates a short rRNA transcript mimicking the local structure of the peptidyl transferase site. This suggests an early introduction of this modification before ribosome assembly. Phylogenetic studies unveiled the widespread distribution of the yhiN gene in the bacterial kingdom, emphasizing the conservation of rRNA dihydrouridylation. In a broader context, these findings underscore nature's preference for utilizing reduced flavin in the reduction of uridines and their derivatives.

Comparative Study of Multilevel Converters using DQ Current Control

This paper presents a comprehensive comparative analysis of different multilevel converter topologies, including 2-level, Neutral Point-Clamped (NPC), Cascaded H-Bridge (CHB), and T-Type converters using the DQ current control strategy. The study aims to evaluate the performance of these topologies concerning current Total Harmonic Distortion (THD) and ripple in the direct and quadrature components of the current. A mathematical model of the grid is presented to facilitate the simulation study. The DQ current control scheme is implemented to regulate the current in both the direct and quadrature axes. The simulations are conducted under various operating conditions to capture the converters’ performance across different load scenarios and modulation techniques. Results indicate significant variations in the performance metrics among the different converter topologies. The 2-level converter exhibits higher THD and ripple compared to the more complex multilevel topologies.

3D printing of bio-inspired porous polymeric solar steam generators for efficient and sustainable desalination

Freshwater scarcity is a pressing issue worldwide, and solar steam generators (SSGs) have emerged as a promising device for seawater desalination, harnessing renewable solar energy to facilitate sustainable water evaporation. The facile fabrication approach for SSG with complex topologies to achieve high water evaporation efficiency remains a challenge. Herein, a MIL-101 (Fe)-derived C@Fe3O4 ink was employed to multi-jet fusion (MJF) printing of polymeric porous SSGs with specific topologies. The optimized porous structure endows the printed SSGs with capillary force, greatly promoting water transport. The tree-like topology enables high water evaporation rates under various simulated solar radiation conditions. A finite element model was built to fully understand the light-to-thermal energy conversion and water evaporation processes. Moreover, the MJF-printed SSGs exhibit self-cleaning properties and can automatically remove accumulated salt on their surfaces, enabling sustainable desalination. During prolonged testing, the water evaporation rate of the SSGs remained relatively stable and reached as high as 1.55 kg m−2 h−1. Additionally, the desalinated water met the standards for direct drinking water. This study presents a state-of-the-art technology for producing efficient SSGs for desalination and introduces a novel method for MJF printing of functional nanocomposites.

Simulating left atrial arrhythmias with an interactive N-body model

BackgroundHeart disease and strokes are leading global killers. While atrial arrhythmias are not deadly by themselves, they can disrupt blood flow in the heart, causing blood clots. These clots can travel to the brain, causing strokes, or to the coronary arteries, causing heart attacks. Additionally, prolonged periods of elevated heart rates can lead to structural and functional changes in the heart, ultimately leading to heart failure if untreated. The left atrium, with its more complex topology, is the primary site for complex arrhythmias. Much remains unknown about the causes of these arrhythmias, and computer modeling is employed to study them. MethodsWe use N-body modeling techniques and parallel computing to build an interactive model of the left atrium. Through user input, individual muscle attributes can be adjusted, and ectopic events can be placed to induce arrhythmias in the model. Users can test ablation scenarios to determine the most effective way to eliminate these arrhythmias. ResultsWe set up muscle conditions that either spontaneously generate common arrhythmias or, with a properly timed and located ectopic event, induce an arrhythmia. These arrhythmias were successfully eliminated with simulated ablation. ConclusionsWe believe the model could be useful to doctors, researchers, and medical students studying left atrial arrhythmias.

Segmentation and Classification of Medical Images Using Artificial Intelligence: A Review

In the realm of medical imaging, segmenting and classifying medical images is essential for helping medical professionals diagnose and treat a variety of medical disorders. This review discusses artificial intelligence (AI) techniques. AI systems have shown impressive accuracy and efficiency in identifying and quantifying elements in medicalimages, such as MRI, CT, and X-rays, by utilizing deep learning techniques, in particularconvolutional neural network (CNNs). We describe CNN design and training for medical image segmentation and classification, emphasizing the usefulness of CNNs in identifying and defining diseased regions and anatomical features. Even with obstacles like data privacy, requiring sizable annotated datasets, and requiring model interpretability, further research and development in AL-driven medical images analysis has promise for improving clinical decision-making and diagnostic accuracy. Future research in this area should concentrate on improving the generalizability and resilience of AI models by using methods like data augmentation, transfer learning, and the creation of more complex network topologies. Furtheringthe area also requires guaranteeing ethical concerns, enhancing data-sharing mechanisms, and encouraging cooperation between medical practitionersand AI researchers.

Protein complex heterogeneity and topology revealed by electron capture charge reduction and surface induced dissociation.

We illustrate the utility of native mass spectrometry (nMS) combined with a fast, tunable gas-phase charge reduction, electron capture charge reduction (ECCR), for the characterization of protein complex topology and glycoprotein heterogeneity. ECCR efficiently reduces the charge states of tetradecameric GroEL, illustrating Orbitrap m/z measurements to greater than 100,000 m/z. For pentameric C-reactive protein and tetradecameric GroEL, our novel device combining ECCR with surface induced dissociation (SID) reduces the charge states and yields more topologically informative fragmentation. This is the first demonstration that ECCR yields more native-like SID fragmentation. ECCR also significantly improved mass and glycan heterogeneity measurements of heavily glycosylated SARS-CoV-2 spike protein trimer and thyroglobulin dimer. Protein glycosylation is important for structural and functional properties and plays essential roles in many biological processes. The immense heterogeneity in glycosylation sites and glycan structure poses significant analytical challenges that hinder a mechanistic understanding of the biological role of glycosylation. Without ECCR, average mass determination of glycoprotein complexes is available only through charge detection mass spectrometry or mass photometry. With narrow m/z selection windows followed by ECCR, multiple glycoform m/z values are apparent, providing quick global glycoform profiling and providing a future path for glycan localization on individual intact glycoforms.

Retinal waves in adaptive rewiring networks orchestrate convergence and divergence in the visual system.

Spontaneous retinal wave activity shaping the visual system is a complex neurodevelopmental phenomenon. Retinal ganglion cells are the hubs through which activity diverges throughout the visual system. We consider how these divergent hubs emerge, using an adaptively rewiring neural network model. Adaptive rewiring models show in a principled way how brains could achieve their complex topologies. Modular small-world structures with rich-club effects and circuits of convergent-divergent units emerge as networks evolve, driven by their own spontaneous activity. Arbitrary nodes of an initially random model network were designated as retinal ganglion cells. They were intermittently exposed to the retinal waveform, as the network evolved through adaptive rewiring. A significant proportion of these nodes developed into divergent hubs within the characteristic complex network architecture. The proportion depends parametrically on the wave incidence rate. Higher rates increase the likelihood of hub formation, while increasing the potential of ganglion cell death. In addition, direct neighbors of designated ganglion cells differentiate like amacrine cells. The divergence observed in ganglion cells resulted in enhanced convergence downstream, suggesting that retinal waves control the formation of convergence in the lateral geniculate nuclei. We conclude that retinal waves stochastically control the distribution of converging and diverging activity in evolving complex networks.

Relative sectional category revisited

The concept of relative sectional category expands upon classical sectional category theory by incorporating the pullback of a fibration along a map. Our paper aims not only to explore this extension but also to thoroughly investigate its properties. We seek to uncover how the relative sectional category unifies several homotopic numerical invariants found in recent literature. These include the topological complexity of maps according to Murillo–Wu or Scott, relative topological complexity as defined by Farber, and homotopic distance for continuous maps in the sense of Macías-Virgós and Mosquera-Lois, among others.

Reconstruction Of Time-Averaged 3D Pressure Fields In The Wake Of An Ahmed Body With Pressure From PIV

In this contribution, we present and compare time-averaged pressure fields reconstructed from scanned stereoscopic 2D3C-PIV data and volumetric 3D-PTV data (Shake-The-Box) with classic pointwise surface pressure tap measurements. Measurements were conducted in the near-wake region of an one-quarter scaled Ahmed body (Ahmed 1984) with 25° slant angle at height-based Reynolds numbers of Re = 5.06 · 10^4 and 1.13 · 10^5, respectively, i.e. free-stream velocities of 10.5 m/s and 23.5 m/s. The measurements are a continuation of previous measurements (Gericke et al. 2023, Ladwig et al. 2023) with a focus on the more complex flow topology concerning the wake flow structure. Measurements were conducted in a low-speed wind tunnel of Göttinger design with a semi-closed test section at Bochum University of Applied Sciences. The investigated flow field in the near wake region is dominantly characterized by a strongly three-dimensional flow field based on a mutually influenced vortex system in the wake, which challenges the utilized pressure reconstruction algorithm based on the Reynolds-averaged Navier-Stokes equations. The present study addresses challenges in pressure reconstruction due to the presence of highly transient rotational and shearing flow in the context of a practical application. The results show good agreement between reconstructed PIV/PTV-based pressure fields and reference pressure measurements using classic wall pressure measurements. The global characteristics of the pressure distributions are correctly reproduced. The agreement is particularly good in areas of unidirectional flow and local smaller velocity gradients. In shear zones as well as separation and, e.g., recirculation areas, larger deviations are clearly visible, as the velocity gradients present near the surface are not sufficiently captured at all.

Research and Application of a Generalized Power Communication Framework with Joint Security Protection Mechanism

Background: The rapid development of Industry 4.0 has opened up new power systems, which face a more complex network topology and a broader range of security threats. This has led to an urgent demand for a coordinated, lightweight, and secure communication management method. Methods: This paper presents a general power communication framework with a joint security protection mechanism that is suitable for coordinated management and transmission safety. The framework manages the protocol’s thread management of the device by converting it to the framework’s process management. It formulates specifications for protocols and equipment that access the framework to achieve support for multiple protocols and equipment. This reduces the difficulty of system operation and maintenance, as well as system complexity, and improves management efficiency. Additionally, the joint security protective mechanism for plugin authentication and protocol encryption is introduced to enable secure data transmission and guarantee the framework's security management. Finally, two experiments have been conducted to discuss and confirm the effectiveness and safety of the framework. Results: The results of the two experiments and the following analysis show that our framework is superior to the chosen well-known industrial commercial communication platforms, and the time delay cost by our mechanism doesn’t significantly affect the real-time data transmission in the power industry, proving its feasibility in both IoT and power applications. Conclusion: Our framework demonstrates exceptional performance in terms of time lag and packet loss during the experiment, surpassing other IoT communication frameworks. Furthermore, it maintains its high standards even under rigorous security analysis.

Pore-scale investigation of forced imbibition in porous rocks through interface curvature and pore topology analysis

Forced imbibition, the invasion of a wetting fluid into porous rocks, plays an important role in the effective exploitation of hydrocarbon resources and the geological sequestration of carbon dioxide. However, the interface dynamics influenced by complex topology commonly leads to non-wetting fluid trapping. Particularly, the underlying mechanisms under viscously unfavorable conditions remain unclear. This study employs a direct numerical simulation method to simulate forced imbibition through the reconstructed digital rocks of sandstone. The interface dynamics and fluid–fluid interactions are investigated through transient simulations, while the pore topology metrics are introduced to analyze the impact on steady-state residual fluid distribution obtained by a pseudo-transient scheme. The results show that the cooperative pore-filling process promoted by corner flow is dominant at low capillary numbers. This leads to unstable inlet pressure, mass flow, and interface curvature, which correspond to complicated interface dynamics and higher residual fluid saturation. During forced imbibition, the interface curvature gradually increases, with the pore-filling mechanisms involving the cooperation of main terminal meniscus movement and arc menisci filling. Complex topology with small diameter pores may result in the destabilization of interface curvature. The residual fluid saturation is negatively correlated with porosity and pore throat size, and positively correlated with tortuosity and aspect ratio. A large mean coordination number characterizing global connectivity promotes imbibition. However, high connectivity characterized by the standardized Euler number corresponding to small pores is associated with a high probability of non-wetting fluid trapping.

Mission-oriented capability evaluation for combat network based on operation loops

With continuous growth in scale, topology complexity, mission phases, and mission diversity, challenges have been placed for efficient capability evaluation of modern combat systems. Aiming at the problems of insufficient mission consideration and single evaluation dimension in the existing evaluation approaches, this study proposes a mission-oriented capability evaluation method for combat systems based on operation loop. Firstly, a combat network model is given that takes into account the capability properties of combat nodes. Then, based on the transition matrix between combat nodes, an efficient algorithm for operation loop identification is proposed based on the Breadth-First Search. Given the mission-capability satisfaction of nodes, the effectiveness evaluation indexes for operation loops and combat network are proposed, followed by node importance measure. Through a case study of the combat scenario involving space-based support against surface ships under different strategies, the effectiveness of the proposed method is verified. The results indicated that the ROI-priority attack method has a notable impact on reducing the overall efficiency of the network, whereas the O-L betweenness-priority attack is more effective in obstructing the successful execution of enemy attack missions.