Local Propagation Research Articles

Local neighbor propagation on graphs for mismatch removal

Recently, despite the promising progress having been achieved, most mismatch removal methods only consider the connection relationships of feature matches in a single neighborhood, and ignore their relationships between different neighborhoods, which will lead to the unavailability of local topological structure for feature matching. In this paper, we propose a novel robust Local Neighbor Propagation on Graphs based mismatch removal (LNPG) method for robust feature matching. LNPG starts from a novel neighborhood graph construction strategy, which leverages both the spatial and the residual information to preserve the local neighborhood structures of potential inliers. Subsequently, LNPG incorporates local neighbor propagation into the graph to enhance connection relationships of the data in different neighborhoods, by using the path-based similarity measurement and the adaptive graph partition. In addition, LNPG includes a novel consistency-filtering-based clustering algorithm, which introduces a reliable neighborhood consistency measure function and an effective cluster merging criterion for robust clustering. Overall, LNPG not only effectively distinguishes inliers from outliers, but also reliably classifies inliers into different transformation models between pairs of images. Extensive experiments on publicly available datasets show the superiority of our LNPG in comparison with other state-of-the-art methods.

Interior Route and Seasonal Dynamics of the Meridional Current in the Eastern Indian Ocean Tropical Gyre

AbstractThe eastern boundary current of the tropical Indian Ocean (IO) connects the equatorial/south tropical IO, contributing to the meridional heat and salinity exchange. As a part of the IO tropical gyre, the meridional current in the eastern IO tropical gyre (East Sumatra Current, ESC) flows southward in the mean state. However, the route of this current varies with months. Drifter trajectories display an exceptional route that turns southeastward before reaching Sumatra in the austral winter and spring, considered the interior ESC. This study uses observations and reanalysis data sets to investigate the seasonal structure and forcing mechanisms behind the interior ESC. The velocity is decomposed into geostrophic and wind‐driven components. The results suggest that the geostrophic component plays a dominant role in the ESC recirculating early from April to June. The southward geostrophic currents are mainly caused by positive zonal temperature gradients, which are induced by both the cold anomaly of the Chagos Dome and the warm water carried by the Indonesian Throughflow, particularly in April and May. Meanwhile, the annual Rossby wave contributes to the temperature anomaly of the Chagos Dome. During the monsoon that prevails after July, the wind‐driven component increases and becomes the primary forcing, accompanying the slowdown of geostrophic velocity. Therefore, the local wind stress, wave propagation, and water mass transport account for the formation of the seasonal interior ESC.

Towards Privacy-Preserving Federated Neuromorphic Learning via Spiking Neuron Models

Federated learning (FL) has been broadly adopted in both academia and industry in recent years. As a bridge to connect the so-called “data islands”, FL has contributed greatly to promoting data utilization. In particular, FL enables disjoint entities to cooperatively train a shared model, while protecting each participant’s data privacy. However, current FL frameworks cannot offer privacy protection and reduce the computation overhead at the same time. Therefore, its implementation in practical scenarios, such as edge computing, is limited. In this paper, we propose a novel FL framework with spiking neuron models and differential privacy, which simultaneously provides theoretically guaranteed privacy protection and achieves low energy consumption. We model the local forward propagation process in a discrete way similar to nerve signal travel in the human brain. Since neurons only fire when the accumulated membrane potential exceeds a threshold, spiking neuron models require significantly lower energy compared to traditional neural networks. In addition, to protect sensitive information in model gradients, we add differently private noise in both the local training phase and server aggregation phase. Empirical evaluation results show that our proposal can effectively reduce the accuracy of membership inference attacks and property inference attacks, while maintaining a relatively low energy cost. blueFor example, the attack accuracy of a membership inference attack drops to 43% in some scenarios. As a result, our proposed FL framework can work well in large-scale cross-device learning scenarios.

Study on Rolling Defects of Al-Mg Alloys with High Mg Content in Normal Rolling and Cross-Rolling Processes.

This study investigated defect formation and strain distribution in high-Mg-content Al-Mg alloys during normal rolling and cross-rolling processes. The finite element analysis (FEA) revealed the presence of wave defects and strain localization-induced zipper cracks in normal cold rolling, which were confirmed by the experimental results. The concentration of shear strain played a significant role in crack formation and propagation. However, the influence of wave defects was minimal in the cross-rolling process, which exhibited a relatively uniform strain distribution. Nonetheless, strain concentration at the edge and center regions led to the formation of zipper cracks and edge cracks, with more pronounced propagation observed in the experiments compared to FEA predictions. Furthermore, texture evolution was found to be a crucial factor affecting crack propagation, particularly with the development of the Goss texture component, which was observed via electron backscattered diffraction analysis at bending points. The Goss texture hindered crack propagation, while the Brass texture allowed cracks to pass through. This phenomenon was consistent with both FEA and experimental observations. To mitigate edge crack formation and propagation, potential strategies involve promoting the formation of the Goss texture at the edge through alloy and process conditions, as well as implementing intermediate annealing to alleviate stress accumulation. These measures can enhance the overall quality and reliability of Al-Mg alloys during cross-rolling processes. In summary, understanding the mechanisms of defect formation and strain distribution in Al-Mg alloys during rolling processes is crucial for optimizing their mechanical properties. The findings of this study provide insights into the challenges associated with wave defects, strain localization, and crack propagation. Future research and optimization efforts should focus on implementing strategies to minimize defects and improve the overall quality of Al-Mg alloys in industrial applications.

Local propagation of visual stimuli in focus of attention

Fast reactions to changes in the surrounding visual environment require efficient attention mechanisms to reallocate computational resources to the most relevant locations in the visual field. In this paper, we present a biologically-plausible computational model of focus of attention that exhibits spatiotemporal locality and that is very well-suited for parallel and distributed implementations. Attention emerges as a wave propagation process originated by visual stimuli corresponding to details and motion information. The resulting field obeys the principle of “inhibition of return” so as not to get stuck in potential holes. The proposed model is obtained as a hyperbolic regularization of the Poisson equation to which it reduces in the limit of high speed of propagation. According to the MultiMatch algorithm for scanpaths comparison, the proposed model achieves very competitive results when considering dynamical input stimuli.

LCPFormer: Towards Effective 3D Point Cloud Analysis via Local Context Propagation in Transformers

Transformer with its underlying attention mechanism and the ability to capture long-range dependencies makes it become a natural choice for unordered point cloud data. However, local regions separated from the general sampling architecture corrupt the structural information of the instances, and the inherent relationships between adjacent local regions lack exploration. In other words, the transformer only focuses on the long-range dependence, while local structural information is still crucial in a transformer-based 3D point cloud model. To enable transformers to incorporate local structural information, we proposed a straightforward solution based on the natural structure of the point clouds to exploit the message passing between neighboring local regions, thus making their representations more comprehensive and discriminative. Concretely, the proposed module, named Local Context Propagation (LCP), is inserted between two transformer layers. It takes advantage of the overlapping points of adjacent local regions (statistically shown to be prevalent) as intermediaries, then re-weighs the features of these shared points from different local regions before passing them to the next layers. Finally, we design a flexible LCPFormer architecture equipped with the LCP module, which is applicable to several different tasks. Experimental results demonstrate that our proposed LCPFormer outperforms various transformer-based methods in benchmarks including 3D shape classification and dense prediction tasks such as 3D object detection and semantic segmentation. Code will be released for reproduction.

Sylvester Equation Induced Collaborative Representation Learning for Recommendation

For an actual recommendation system, it generally involves a variety of heterogeneous interactive relationships, such as the typical user-user (U2U), item-item (I2I), and user-item (U2I) interaction relationships. With the application of graph neural networks (GNNs) in embedding various interactive relations, recommendation technology has made gratifying progress in recent years, which benefits lot from its powerful ability in relation modeling. However, most of the existing GNN-based methods fail to collaboratively explore the above heterogeneous multiple interactive relationships, including the internal correlations among multiple relationships and the intrinsic association behind different relationships. As a consequence, the user's personalized preference for the items to be recommended will not be well captured. In this paper, we propose a <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u> ylvester equation induced <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">C</u> ollaborative <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> epresentation <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</u> earning framework (S-CRL) for recommendation system by utilizing the heterogeneous multiple interactive relationships. In particular, we ingeniously define a novel Sylvester equation to associate tactfully the multiple heterogeneous relations together. From the perspective of rating propagation, such Sylvester equation is shown theoretically to be the optimal solution of a local structure sensitive rating propagation function. Additionally, to seek more expressive embeddings about user and item, a layer-wise attention is introduced to aggregate the multi-hop information from U2U and I2I graphs, respectively, so as to promote the aggregation with the corresponding embeddings from the U2I interaction graph. Extensive experiments on three real-world datasets verify that our model achieves more favorable performance over currently representative methods.

The Influence of Mesoscale Atmospheric Convection on Local Infrasound Propagation

AbstractInfrasound—that is, acoustic waves with frequencies below the threshold of human hearing—has historically been used to detect and locate distant explosive events over global ranges (≥1,000 km). Simulations over these ranges have traditionally relied on large‐scale, synoptic meteorological information. However, infrasound propagation over shorter, local ranges (0–100 km) may be affected by smaller, mesoscale meteorological features. To identify the effects of these mesoscale meteorological features on local infrasound propagation, simulations were conducted using the Weather Research and Forecasting (WRF) meteorological model to approximate the meteorological conditions associated with a series of historical, small‐scale explosive test events that occurred at the Big Black Test Site in Bovina, Mississippi. These meteorological conditions were then incorporated into a full‐wave acoustic model to generate meteorology‐informed predictions of infrasound propagation. A series of WRF simulations was conducted with varying degrees of horizontal resolution—1, 3, and 15 km—to investigate the spatial sensitivity of these infrasound predictions. The results illustrate that convective precipitation events demonstrate potentially observable effects on local infrasound propagation due to strong, heterogeneous gradients in temperature and wind associated with the convective events themselves. Therefore, to accurately predict infrasound propagation on local scales, it may be necessary to use convection‐permitting meteorological models with a horizontal resolution ≤4 km at locations and times that support mesoscale convective activity.

Photonic topological subspace-induced bound states in the continuum.

Bound states in the continuum (BICs) are intriguing localized states that possess eigenvalues embedded within the continuum of extended states. Recently, a combination of topological band theory and BIC physics has given rise to a novel form of topological matter known as topological BICs. In this work, we experimentally demonstrate the photonic topological subspace-induced BICs. By using femtosecond-laser writing, we experimentally establish a photonic nontrivial three-leg ladder lattice, thereby directly observe the localized propagation of two kinds of topological edge states which exist at different boundaries. Interestingly, such edge states appear in the continuum of the bulk modes, and the topological properties are inherited from its independent subspace Hamiltonian which contains a celebrated Su-Schrieffer-Heeger lattice. This work not only presents a novel, to the best of our knowledge, platform for investigating topological physics in optics, but also unveils exciting prospects for future exploration of other remarkable BICs.

Experimental study on local crack propagation of concrete under three-point bending

To investigate the propagation process of local cracks in concrete, three-point bending tests were performed on the beams with a local rectangular pre-crack. Pre-cracks with different sizes were set in the specimens with the widths ranging from 30 mm to 100 mm and the heights ranging from 30 mm to 60 mm. The three-point bending tests were carried out with a controlled displacement rate of 0.024 mm/min. The compressive strength, elastic modulus and tensile strength of the concrete were 40.89 MPa, 32.57 GPa and 3.40 MPa, respectively. By monitoring the initiation and propagation of local cracks on the specimen surfaces, the fracture toughness of the concrete specimen with a local crack was determined and the crack propagation process along the thickness and height directions was investigated. The experimental results indicated that, under three-point bending loading, the local cracks always propagated firstly on the bottom surface of the specimen and formed a through crack in the thickness direction. After that, the crack in the specimen began to propagate in the height direction until full failure. In addition, the initial fracture toughness obtained from the specimens with bottom-through cracks was almost the same as the one from the specimens with local cracks. However, the unstable fracture toughness obtained from the specimens with bottom-through cracks was not consistent with the one from the specimens with local cracks, where the average unstable fracture toughness calculated using the critical crack lengths at different thicknesses was taken as the unstable fracture toughness of the local crack specimens. This indicated that the initial fracture toughness could be considered as a material characteristic, while the unstable fracture toughness was dependent on the crack geometry.

Identifying sources of human interictal discharges with travelling wave and white matter propagation.

Interictal epileptiform discharges have been shown to propagate from focal epileptogenic sources as travelling waves or through more rapid white matter conduction. We hypothesize that both modes of propagation are necessary to explain interictal discharge timing delays. We propose a method that, for the first time, incorporates both propagation modes to identify unique potential sources of interictal activity. We retrospectively analysed 38 focal epilepsy patients who underwent intracranial EEG recordings and diffusion-weighted imaging for epilepsy surgery evaluation. Interictal discharges were detected and localized to the most likely source based on relative delays in time of arrival across electrodes, incorporating travelling waves and white matter propagation. We assessed the influence of white matter propagation on distance of spread, timing and clinical interpretation of interictal activity. To evaluate accuracy, we compared our source localization results to earliest spiking regions to predict seizure outcomes. White matter propagation helps to explain the timing delays observed in interictal discharge sequences, underlying rapid and distant propagation. Sources identified based on differences in time of receipt of interictal discharges are often distinct from the leading electrode location. Receipt of activity propagating rapidly via white matter can occur earlier than more local activity propagating via slower cortical travelling waves. In our cohort, our source localization approach was more accurate in predicting seizure outcomes than the leading electrode location. Inclusion of white matter in addition to travelling wave propagation in our model of discharge spread did not improve overall accuracy but allowed for identification of unique and at times distant potential sources of activity, particularly in patients with persistent postoperative seizures. Since distant white matter propagation can occur more rapidly than local travelling wave propagation, combined modes of propagation within an interictal discharge sequence can decouple the commonly assumed relationship between spike timing and distance from the source. Our findings thus highlight the clinical importance of recognizing the presence of dual modes of propagation during interictal discharges, as this may be a cause of clinical mislocalization.

Implementation of a phase field damage model with a nonlinear evolution equation in an FFT-based solver

This paper focuses on the numerical implementation of phase-field models of fracture using the Fast Fourier Transform (FFT) based numerical method. Recent studies on phase-field models focus on the discussions of the choice of the value of regularization length proposed to smear the discontinuity of the sharp crack. Some studies argue that it should be considered as a material property because it has a significant impact on the mechanical behavior of a material in some phase-field models, for instance, in the model proposed by Miehe. However, our results in this study for heterogeneous materials have shown that the choice of regularization length not only affects the macroscopic mechanical behavior but also the local crack propagation patterns. As a result, it can be challenging to select an appropriate value that produces both accurate macroscopic responses and local crack patterns for certain phase-field models, such as Miehe’s model. Thus, the phase-field model proposed by Wu, which has been proven to reduce the length sensitivity for homogeneous material, has been successfully implemented in an FFT-based solver with the application of Newton–Krylov algorithm.The length sensitivity of Wu’s phase-field model for heterogeneous materials is also investigated in this paper. Our tests show that Wu’s phase-field model has partial length sensitivity for heterogeneous materials. However, the main reason for this sensitivity is that one phase enters the damage zone of other phase, which is different from Miehe’s model. As a result, a set of criteria for accurately choosing the regularization value has been established for Wu’s model in this work. Meanwhile, it has also been found that Wu’s model may be more suitable than Miehe’s model for brittle failure due to the introduction of an elastic stage.

Unidirectional links prefer local firing propagation in the neural network of C. elegans

Understanding the mechanisms of brain functions is currently a hot topic but most studies have been focused on the aspects of synchronization and various partial synchronization. We here study this problem from a new angle of signal propagation, where the local (global) propagation may be related to the status of health (mental disorder). We make a case study on the neural network of C. elegans by presenting a framework where one node is chosen as the source node to generate signals and all the other nodes are chosen as the target nodes. We interestingly find that the existence of the unidirectional links is the key element to generate the local firing propagation and the configuration of the unidirectional links will seriously influence the range of firing propagation. In details, our findings include: (i) The unidirectional links prefer the local firing propagation, while the bidirectional links prefer the global firing propagation. (ii) Multiple source nodes will enhance the firing propagation, where the range of firing propagation for choosing the multiple source nodes from different communities is slightly larger than that from the same community. And (iii) a resonance effect of the range of firing propagation on coupling strength is observed, i.e. there is an optimal coupling strength. Moreover, a brief theoretical analysis is provided to explain these results.

Cascading Failure Propagation and Mitigation Strategies in Power Systems

In this article, we investigate the local and nonlocal failure propagation patterns in power systems and propose effective mitigation strategies. It is widely acknowledged that the sequence of failure events of component overloading is determined by power flow redistribution. To understand the power flow redistribution process, we analyze the prefault power flow condition using network flow theory and by clustering the system into several regions with balanced local power flow. We observe that faults triggering local power imbalance would lead to remote power transfer and faults causing no local power imbalance would lead to local power redistribution. The improved understanding of the failure process permits us to develop effective mitigating strategies consisting of adaptive power balance restoration and selective edge protection for cascading failure propagation. In addition, we propose a set of indexes to measure the local and nonlocal propagation risks of cascading failures. Numerical simulations on the IEEE 118- and 300-bus systems demonstrate that the proposed mitigation strategies can significantly reduce the blackout sizes and are tolerant to incorrect transmission line tripping.

Inhibition of Localized Corrosion Propagation on Carbon Steel: A Potentiostatic Study

The occurrence of localized corrosion in carbon steel pipelines, even when the uniform corrosion rate remains low, is a major concern in the hydrocarbon production and transmission industry. The propagation of these pits, caused by the galvanic coupling between the inhibited surface and the active pit, can lead to serious consequences such as financial loss, environmental damage, production interruption, and even loss of life. To better understand this phenomenon, this work focuses on using the potentiostatic technique to evaluate the tendency of localized corrosion propagation. The experiments were conducted using a primarily imidazolinium-based corrosion inhibitor in produced water conditions (5 wt% NaCl, pH 4.5, CO2-saturated) at 55°C and 80°C. The baseline results were obtained through linear polarization resistance and potentiodynamic polarization tests. The potentiostatic experiments were then conducted to artificially simulate different levels of galvanic coupling that could exist in case of active localized corrosion. The results showed that, at certain anodic potentials, increased inhibitor dosage was necessary to significantly decrease the current. However, at high current levels, further injections were insufficient, indicating that substrate dissolution may affect the adsorption of the inhibitor. This work provides insights into the role of inhibitors and important factors in stopping the propagation of localized corrosion of carbon steel. Further research, such as designing a proper zero-resistance ammeter setup, will be necessary to fully understand this complex phenomenon. The results show that the potentiostatic methodology can be a rapid and easy alternative to obtain electrochemical information and improve understanding of localized corrosion propagation.

Effect of martensite twins on local scale cleavage crack propagation in a medium carbon armor grade steel

This paper proposes the efficacy of martensite nano-twins in a medium carbon armor grade martensitic steel on the cleavage crack resistance at a local scale. Concurrent analyses through electron channeling contrast imaging and electron back scattered diffraction techniques reveal that fine twins of width less than 10 nm are ineffective in deflecting the crack, propagating in the {100} cleavage plane. Coarse twins, on the other hand, resist the crack propagation by deflecting the crack through stepwise crack path propagations, e.g., a combination of matrix-twin {100} cleavage cracking or a combination of matrix {100} and twin-matrix {112} interface cracking. The interfacial cracking along the {112} twin boundaries is attributed to the presence of carbon enriched clusters along the twin boundaries.

HiRN: Hierarchical recurrent neural network for video super-resolution (VSR) using two-stage feature evolution

The aim of video super-resolution (VSR) is generate the high-resolution (HR) frames from their low-resolution (LR) counterparts. As one of the fundamental module of VSR, propagation process provides the path of feature map and specifies how the feature map is leveraged. In the recurrent propagation, the latent features can be propagated and aggregated. Therefore, adopting the recurrent strategy can resolve the limitation of sliding-window-based local propagation. Recently, bi-directional recurrent propagation-based latest methods have achieved powerful performance in VSR. However, existing bi-directional frameworks have structured by combining forward and backward branches. These structures cannot propagate and aggregate previous and future latent features of current branch. In this study, we suggest the hierarchical recurrent neural network (HiRN) based on feature evolution. The proposed HiRN is designed based on the hierarchical recurrent propagation and residual block-based backbone with temporal wavelet attention (TWA) module. The hierarchical recurrent propagation consists of two stages to combine advantages of low frame rate-based forward and backward schemes, and multi-frame rate-based bi-directional access structure. The proposed methods are compared with state-of-the-art (SOTA) methods on the benchmark datasets. Experiments show that the proposed scheme achieves superior performance compared with SOTA methods. In particular, the proposed HiRN achieves better performance than all compared methods in terms of SSIM on Vid4 benchmark. In addition, the proposed HiRN surpasses the existing GBR-WNN by a significant 3.03 dB in PSNR on REDS4 benchmark with fewer parameters.

Indigenous communities’ perceptions reveal threats and management options of wild edible plants in semiarid lands of northwestern Kenya

BackgroundUnderstanding how local communities perceive threats and management options of wild edible plants (WEPs) is essential in developing their conservation strategies and action plans. Due to their multiple use values, including nutrition, medicinal, construction, and cultural as well as biotic and abiotic pressures, WEPs are exposed to overexploitation, especially within arid and semiarid lands, and hence the need to manage and conserve them. We demonstrate how an understanding of indigenous communities’ perceptions could be achieved through an integrated participatory approach involving focus group discussions (FGDs) and field plot surveys.MethodsWe conducted three FGDs between October 2020 and April 2021 within three community units in northwestern Kenya with different socioeconomic and environmental characteristics. We subsequently surveyed 240 field plots of size 1 ha each to assess threats facing WEPs within a 5 km buffer radius in every study community. We compared ranks of threats and management options across community units.ResultsRankings of threats and management options differed across the three study communities. We obtained strong positive linear relationships between field and FGD rankings of threats facing WEPs. Climate change, overstocking, overharvesting, and invasive species were the highest-ranked threats. Mitigation of climate change, local knowledge preservation, selection, propagation, processing, and marketing of WEPs ranked high among possible management options irrespective of the socioeconomic and environmental characteristics of the community unit.ConclusionsOur approach emphasizes the relevance of leveraging indigenous communities’ perceptions and conducting field plot surveys to assess threats and management options for WEPs. Evaluating the effectiveness and cost–benefit implications of implementing the highly ranked management options could help determine potentially suitable habitats of the WEPs for conservation and management purposes, especially for priority WEPs.

In situ synchrotron radiation µCT indentation of cortical bone: Anisotropic crack propagation, local deformation, and fracture

The development of treatment strategies for skeletal diseases relies on the understanding of bone mechanical properties in relation to its structure at different length scales. At the microscale, indention techniques can be used to evaluate the elastic, plastic, and fracture behaviour of bone tissue. Here, we combined in situ high-resolution SRµCT indentation testing and digital volume correlation to elucidate the anisotropic crack propagation, deformation, and fracture of ovine cortical bone under Berkovich and spherical tips. Independently of the indenter type we observed significant dependence of the crack development due to the anisotropy ahead of the tip, with lower strains and smaller crack systems developing in samples indented in the transverse material direction, where the fibrillar bone ultrastructure is largely aligned perpendicular to the indentation direction. Such alignment allows to accommodate the strain energy, inhibiting crack propagation. Higher tensile hoop strains generally correlated with regions that display significant cracking radial to the indenter, indicating a predominant Mode I fracture. This was confirmed by the three-dimensional analysis of crack opening displacements and stress intensity factors along the crack front obtained for the first time from full displacement fields in bone tissue. The X-ray beam significantly influenced the relaxation behaviour independent of the tip. Raman analyses did not show significant changes in specimen composition after irradiation compared to non-irradiated tissue, suggesting an embrittlement process that may be linked to damage of the non-fibrillar organic matrix. This study highlights the importance of three-dimensional investigation of bone deformation and fracture behaviour to explore the mechanisms of bone failure in relation to structural changes due to ageing or disease. Statement of significanceCharacterising the three-dimensional deformation and fracture behaviour of bone remains essential to decipher the interplay between structure, function, and composition with the aim to improve fracture prevention strategies. The experimental methodology presented here, combining high-resolution imaging, indentation testing and digital volume correlation, allows us to quantify the local deformation, crack propagation, and fracture modes of cortical bone tissue. Our results highlight the anisotropic behaviour of osteonal bone and the complex crack propagation patterns and fracture modes initiating by the intricate stress states beneath the indenter tip. This is of wide interest not only for the understanding of bone fracture but also to understand other architectured (bio)structures providing an effective way to quantify their toughening mechanisms in relation to their main mechanical function.

Controllable Local Propagation Environment to Maximize the Multiplexing Capability of Massive MIMO Systems

The capability of controlling and modifying wireless propagation channels is one of the prerogatives of beyond-5G systems. In this paper, we propose the use of a controllable local propagation environment surrounding the terminals, and analyze its positive effect on the multiplexing capability of massive MIMO systems. In particular, we focus on using a few switched passive elements surrounding each terminal. In this way, the modification of the propagation environment is not realized by means of a single structure, as in reconfigurable intelligent surfaces (RIS), but is achieved by the cooperative work of all the terminals. By employing numerical simulations, we show that the proposed system outperforms its non-reconfigurable counterpart in terms of the number of contemporary connected users. Moreover, the optimized system enables a substantial increase in the minimum received power by the terminals, thus guaranteeing superior channel fairness.