Abstract We present an overview of the Weighing Halos Accurately, Locally, and Efficiently with Supernovae (WHALES) survey, the first to discover and measure Type Ia supernovae (SNe Ia) in and around galaxy superclusters. By building a sample of SNe Ia around these massive environments, we aim to provide new constraints on bulk-flow models while laying the groundwork for improved estimates of supercluster masses. Here, we present data from the first two seasons targeting the Shapley Supercluster (0.02 < z < 0.06), which is responsible for a large but unknown fraction of our Local Group’s motion. Until now, no supernovae (SNe) had been analyzed in the direction of Shapley. Through the WHALES survey, we have identified 12 likely SNe Ia in this region using SkyMapper, including eight with spectroscopic confirmation. We present the first light curves of these SNe and combine our observations with data from the Asteroid Terrestrial-impact Last Alert System. We demonstrate that the low number of discovered SNe Ia per season is consistent with various rate calculations, highlighting the need for future surveys to monitor superclusters over a multiyear time span. Finally, we present simulations of SN Ia observations in the environments of massive galaxy clusters, demonstrating how the inferred peculiar velocities can constrain cluster masses, and highlighting the added complexity within superclusters. We find that a sample of 100 SNe Ia would enable a 25% precision measurement of the total mass of the Shapley Supercluster.

Objective.Clustered pinhole (CP) collimation currently supports sub-millimeter resolution imaging up to ∼1 MeV, enabling SPECT of alpha and beta emitters with gamma emissions, simultaneous multi-isotope PET and PET/SPECT, and positron range-free PET. Nonetheless, increasing sensitivity in the original CP designs by enlarging pinhole diameters is limited, as the resulting pinhole opening cones would overlap.Approach. To address this limitation, the use of Super-Cluster (SC) collimation was evaluated in a simulation study. Two SC designs were assessed: a standard configuration (SC-ST) offering a resolution-sensitivity trade-off similar to CP, and a high-sensitivity variant (SC-HS) with larger pinhole diameters to enhance sensitivity. Their performance was compared to CP collimation for18F at concentrations of 1.0, 0.1, 0.05 MBq ml-1and ⁸⁹Zr at 2.0, 0.2, 0.1 MBq ml-1, evaluating sensitivity, image resolution, recovery coefficients, and uniformity.Main results.CP and SC-ST showed comparable sensitivity and image resolution. Both resolved18F rods of 0.9, 1.4, and 1.8 mm at 1.0, 0.1, and 0.05 MBq ml-1, respectively. For ⁸⁹Zr, rods down to 1.0 mm and 1.6 mm were resolved at 2.0 and 0.2 MBq ml-1, but none at 0.1 MBq ml-1. Compared to CP and SC-ST, SC-HS increased sensitivity threefold for18F and twofold for ⁸⁹Zr. At the highest activity, SC-HS showed slightly reduced resolution for18F (1.0 mm) and similar for ⁸⁹Zr (1.0 mm). However, it clearly outperformed both other collimators at lower activities, resolving18F rods of 1.2 and 1.4 mm at 0.1 and 0.05 MBq ml-1, respectively, and ⁸⁹Zr rods of 1.4 and 1.6 mm at 0.2 and 0.1 MBq ml-1. Additionally, SC-HS showed superior contrast recovery. Image uniformity remained consistent across all collimators, confirming effective angular sampling.Significance.The new SC geometry enables high-sensitivity collimation for high gamma energies, improving image quality at low activities. These results demonstrate SC collimation's strong potential for sensitivity-critical applications.

Current applications in the Internet of Things generally rely on wireless sensor network deployments that measure and control a restricted area. Most of those applications use sensor nodes powered with batteries, so efficient energy management is required to maximize the lifetime of the network. To tackle this issue, clustering becomes a suitable solution to prolong energy sources, being the selection of the cluster heads crucial for its optimal operation. The application of soft computing techniques (e.g. fuzzy logic) to clustering has improved the wireless network performance significantly. Therefore, this approach proposes a centralized, two-tier clustering method in which there are cluster heads and super cluster heads. This hierarchy is defined based on a sustainability filter and a two-stage cascaded fuzzy system. Initially, the sustainability filter removes unsuitable nodes in the process of selecting the cluster heads. The decision is based on the node residual energy, eliminating those with low battery levels. The remainder nodes use a first fuzzy system where some of them are promoted as cluster heads. Then, for each CH, a second stage is run, which takes as input the output of the first fuzzy system and three other variables to allow the selection of super cluster heads. The findings of the simulation of this approach have demonstrated that cascaded fuzzy systems have the capacity to circumvent issues such as rapid depletion of energy at the node in close proximity to the base station. Additionally, the simulation results of the proposed method demonstrated a substantial enhancement in the lifetime across the various scenarios applied. Furthermore, they have been shown to exhibit a substantial degree of adaptability to varying base station locations.

Superclusters of galaxies represent dynamically active environments in which galaxies and their systems form and evolve. We study the substructure, connectivity, and galaxy content of galaxy clusters A1656 and A1367 in the Coma supercluster and of A1185 in the Leo supercluster with the aim of understanding the evolution of clusters from turnaround to virialisation, and the evolution of whole superclusters. We used data from the Sloan Digital Sky Survey DR10 MAIN galaxy sample and from DESI cluster catalogues. The projected phase space diagram and the distribution of mass were used to identify regions of various infall stages (early and late infall, and regions of ongoing infall, i.e. regions of influence), their characteristic radii, embedded mass, and density contrasts in order to study the evolution of clusters with the spherical collapse model. We determined the substructure of clusters using normal mixture modelling and their connectivity by counting filaments in the cluster's regions of influence. We analysed galaxy content in clusters and in their environment and derived scaling relations between cluster masses. All three clusters have a substructure with two to five components and up to six filaments connected to them. The radii of regions of influence are R_ inf ≈ 4 and the density contrast at their borders is Δρ_ inf ≈ 50 - 60. The scaling relations between the masses of clusters have a very small scatter. The galaxy content of the clusters and of their regions of influence vary from cluster to cluster. In high-density regions (superclusters), the percentage of quiescent galaxies is higher than in low-density regions between superclusters, where approximately one-fourth of the galaxies are still quiescent. The collapse of the regions of influence of clusters started at redshifts z ≈ 0.4 - 0.5. Clusters will be virialised approximately in ≈ 3.3 Gyrs. Clusters in superclusters will not merge, and their present-day turnaround regions will be virialised in ≈ 10 Gyrs. The large variety of properties of clusters suggests that they have followed different paths during evolution.

This current study seeks to expand on a sociolinguistic process that is highly understudied, and to which little attention has been paid. Language planning and policy in Nepal between the standard language, Nepali, and other minority languages require significant scholarly attention. To this, I have drawn on abduction theory to elicit information from historical records, current processes implemented to separate the two languages, Nepali as a standard language, and Newari as a binary opposite and minority language, and from agents contributing to these tensions. I have found four clusters of bodies that affect these tensions: the top-down cluster, the bottom-up cluster, the mediating horizontally-placed cluster, and the super top-down and super bottom-up clusters. These bodies together all contribute to the maintenance of the tensions between the standard language, which in the case of Nepal is Nepali, and the minority and subjugated language, which in this study I have selected to be the Newari language.

An unsupervised semantic segmentation network for wood–leaf separation in 3D point clouds

Abstract Eastward‐propagating super cloud clusters (SCCs) are the primary convective features of the Madden‐Julian Oscillation (MJO) envelope and play a crucial role in determining its propagation speed. While the dynamical structures of SCCs resemble those of typical Kelvin waves, their phase speeds are much slower. This study investigates the physical processes underlying the eastward propagation of SCCs using a cloud‐permitting simulation of an MJO event over the tropical Indian Ocean. The results show that the eastward propagation of SCCs is hindered due to intersections with westward‐propagating waves originating from the western edge of the Maritime Continent. During these intersections, new cloud clusters, dominated by shallow convection, are triggered to the east. This shallow convection temporarily stalls the SCC due to positive feedback between shallow convective heating and moisture convergence. As shallow convection transitions to deep convection and new clusters replace the old ones, the system begins to move. Latent heat release causes low surface pressure to build to the east of the new clusters, setting the stage for the next intersection. The timescale of non‐instantaneous convection‐convergence feedback, which quantifies the time lag between moisture convergence and convective heating, governs the stagnation period during cloud cluster replacement and ultimately influences the propagation speed of SCCs.

The richest and largest structures in the cosmic web are galaxy superclusters, their complexes (associations of several almost connected very rich superclusters), and planes. Superclusters represent a special environment where the evolution of galaxies and galaxy groups and clusters differs from the evolution of these systems in a low-density environment. The richest galaxy clusters reside in superclusters. The richest superclusters in the nearby Universe form a quasiregular pattern with the characteristic distance between superclusters 120–140 h−1 Mpc. Moreover, superclusters in the nearby Universe lie in two huge perpendicular planes with the extent of several hundreds of megaparsecs, the Local Supercluster plane and the Dominant supercluster plane. The origin of these patterns in the supercluster distribution is not yet clear, and it is an open question whether the presence of such structures can be explained within the ΛCDM cosmological model. This review presents a brief story of superclusters, their discovery, definitions, main properties, and large-scale distribution.

High-temperature proton exchange membranes (HT-PEMs) are highly desired for fuel cells with high energy density; however, the requirements in balanced anhydrous proton conductivity, mechanical/structural stability, processability and gas-barrier property impose great difficulty for molecular design. Herein, the supramolecular complexation of brush polymers and super acidic metal oxide cluster (H3PW12O40, abbreviation PW12) affords HT-PEMs with comprehensive performance that contributes to the robust performance of high energy density fuel cells. The polymers brush topology enables the decoupling of mechanical properties and proton conduction: the polyethylene glycol (PEG) side chains possess high affinity to PW12 for proton transport while the rigid backbones help maintain structural stability and mechanical strengths up to 250°C. The PW12 clusters can be homogeneously dispersed in PEG with high loadings (≈80wt.%) and it facilitates proton hopping among the crowded PW12 for promising anhydrous proton conduction, e.g., 2 × 10-3 S cm-1 at 200°C. Their dense supramolecular bonds contribute to enhanced mechanical strength, flexibility and gas barrier property with mitigating hydrogen permeation current as 0.73mA cm-2, enabling the feasible processability of PEMs and stable operation of fuel cells. The devices show high power density as 218mW cm-2 at 180°C with long-term stable operation.

Abstract In July 2023, a super cluster of extreme rainfall event attacked North China during the decaying phase of Typhoon Doksuri, which induced a severe flood, causing great damage and people death. Our results show that this event is mainly caused by the cross-time scale interaction between the enhanced anticyclone over the Sea of Japan, the decaying Typhoon Doksuri, and the developing Typhoon Khanun. The anomalous anticyclone exhibits significant 10−30-day and 30–90-day time scales. It interacted with Typhoon Doksuri, providing moisture advection via southeasterly flow. The anticyclone was enhanced by the combination of wave energy dispersed from Typhoons Doksuri and Khanun in the lower troposphere and eastward propagation of Rossby waves in the upper troposphere, which jointly resulted in the local moisture convergence and vertical motion during the flooding. As a result, the 10–30-day and 30–90-day intraseasonal oscillations of the anticyclone play an important role as an initial atmospheric condition. It bridges the East Asian summer monsoon and Typhoons of Doksuri and Khanun, showing an important source of subseasonal predictability of extreme heavy rainfall events in North China.

Context. The properties of magnetic fields in large-scale structure filaments, far beyond galaxy clusters, are still poorly known. Superclusters of galaxies are laboratories for investigating low-density environments, which are not easily identified given the low signals and large scales involved. The observed Faraday rotation measure (RM) of polarised sources along the line of sight of superclusters allows us to constrain the magnetic field properties in these extended environments. Aims. The aim of this work is to constrain the magnetic field intensity in low-density environments within the extent of superclusters of galaxies using the Faraday RM of polarised background sources detected at different frequencies. Methods. We selected three rich and nearby (z < 0.1) superclusters of galaxies for which polarisation observations were available at both 1.4 GHz and 144 MHz: Corona Borealis, Hercules, and Leo. We compiled a catalogue of 4497 polarised background sources that have RM values either from the literature or derived from unpublished observations at 144 MHz. For each supercluster we created a 3D density cube in order to associate a density estimate with each RM measurement. We computed the median absolute deviation (MAD) variance of the RM values grouped in three density bins that correspond to the supercluster outskirts (0.01 < ρ/ρc < 1), filaments (1 < ρ/ρc < 30), and nodes (30 < ρ/ρc < 1000) regimes to investigate how variations in the RM distribution are linked to the mean density crossed by the polarised emission. Results. We find an excess ΔσMAD2RRM = 2.5 ± 0.5 rad2 m−4 between the lowest-density regions (outside supercluster boundaries) and the low-density region inside the supercluster. This excess is attributed to the intervening medium of the filaments in the supercluster. We modelled the variance of the RM distribution as being due to a single-scale, randomly oriented magnetic field distribution and therefore as being dependant upon the magnetic field intensity along the line of sight, the magnetic field reversal scale, and the line-of-sight path length. Our observations do not constrain the latter two parameters, but if we marginalise over their respective prior range, we constrain the magnetic field to B|| = 19+50-8 nG. Conclusions. Our findings are consistent with several other works that studied filaments of the large-scale structure. The results suggest that the purely adiabatic compression of a primordial magnetic field, which would imply observed magnetic fields of the order of B|| ∼ 2 nG, is not the only mechanism playing a role in amplifying the primordial seeds in superclusters of galaxies.

Abstract Statistics that capture the directional dependence of the baryon distribution in the cosmic web enable unique tests of cosmology and astrophysical feedback. We use constrained oriented stacking of thermal Sunyaev–Zel’dovich (tSZ) maps to measure the anisotropic distribution of hot gas 2.5–40 Mpc away from galaxy clusters embedded in massive filaments and superclusters. The cluster selection and orientation (at a scale of ∼15 Mpc) use Dark Energy Survey (DES) Year 3 data, while expanded tSZ maps from the Atacama Cosmology Telescope Data Release 6 enable a ∼3× more significant measurement of the extended gas compared to the technique’s proof-of-concept. Decomposing stacks into cosine multipoles of order m, we detect a dipole (m = 1) and quadrupole (m = 2) at 8σ–10σ, as well as evidence for m = 4 signal at up to 6σ, indicating sensitivity to late-time non-Gaussianity. We compare to Cardinal simulations with spherical gas models pasted onto dark matter halos. The fiducial tSZ data can discriminate between two models that deplete pressure differently in low-mass halos (mimicking astrophysical feedback), preferring higher average pressure in extended structures. However, uncertainty in the amount of cosmic infrared background contamination reduces the constraining power. Additionally, we apply the technique to DES galaxy density and weak lensing to study for the first time their oriented relationships with tSZ. In the tSZ-to-lensing relation, averaged on 7.5 Mpc (transverse) scales, we observe dependence on redshift but not shape or radial distance. Thus, on large scales, the superclustering of gas pressure, galaxies, and total matter is coherent in shape and extent.

The Universal Constants and the Scaling Law provides a transformative framework for understanding the interconnected architecture of reality. By reimagining spacetime as a dynamic scalar field, this work introduces a Unified Scalar Resonance Model (USRM) that bridges quantum mechanics, gravity, and cosmic structure. At its core, the model is governed by three fundamental constants—the Information Coupling Constant (α), the Physical Scaling Constant (β), and the Quantum Coherence Constant (γ) which regulate energy flow, quantum coherence, and resonance dynamics across all physical scales. The USRM addresses critical limitations in modern physics by replacing ad hoc constructs such as dark matter and dark energy with intrinsic scalar field dynamics. It demonstrates how these constants naturally organize matter and energy into stable, quantized structures, from atomic nuclei to galactic superclusters. By leveraging principles of oscillatory coherence, the framework reveals the underlying simplicity and elegance of phenomena previously considered disparate, such as nuclear magic numbers, fractal galactic distributions, and gravitational anomalies. This concise exploration presents the mathematical foundation of the USRM, validates its predictions against empirical observations, and highlights its potential to unify fundamental forces. The results suggest that the scalar field's intrinsic properties not only underpin the observable universe but also offer a coherent pathway for resolving persistent anomalies in physics. By bridging quantum to cosmic scales, this work lays the foundation for a holistic understanding of reality and paves the way for novel theoretical and experimental advancements.

Vehicular ad hoc network (VANET) is an innovative technology that has attracted many researchers and the industrial sector. The increase in vehicle movement and the requirement for effective traffic management systems have resulted in the development of VANETs. The Super Cluster Head based Efficient Traffic Control (SCHETF) model aims to alleviate traffic congestion and decrease energy consumption in VANETs through a novel integration of Cluster Head (CH) election, cluster gateway formation, and effective data transmission. SCHETF utilizes a parameter-driven CH election process that considers factors such as network connectivity, distance, speed, and trust levels. This approach guarantees the most suitable CH selection, reducing energy expenditure while enhancing network efficiency. The model assesses network connectivity through indicators like traffic flow and lane weights, ensuring precise determination of link reliability. Metrics for distance and speed are normalized to evaluate the changing behavior of vehicles, while trust ratings are given based on historical and community information to improve reliability. The creation of cluster gateways reduces unnecessary cluster formations by implementing Cluster Gateway Creation (CGC) at strategic sites, lessening communication load, and boosting cluster stability. Efficient data transmission is accomplished by appointing several Cluster Gateway (CGW) within clusters. A backoff timer mechanism gives priority to the CGW that is farthest from the CH for message forwarding, avoiding unnecessary repetitions and guaranteeing effective message dispatch. The model is smart clustering and gateway strategies lessen signaling load during handovers and enhance resource management in dynamic vehicular settings. The SCHETF model offers a thorough framework for tackling the challenges faced by VANETs, providing scalable and energy-efficient communication options. This improves data distribution, assures dependable connectivity, and plays a crucial role in the progress of intelligent transportation systems. The model has been put into practice through experimentation in Network Simulator 2 (NS2). The parameters considered in this study encompass energy efficiency, throughput, packet delivery ratio, end-to-end delay, packet loss, and routing overhead. To undertake a comparison study, the developed SCHETF findings are compared to older approaches such as Evolutionary Algorithm-based Vehicular Clustering Technique (EAVCT), Region Collaborative Management for Dynamic Clustering (RCMDC), and Novel Hypergraph Clustering Model (NHGCM). The outcomes indicate that the suggested SCHETF strategy outperforms previous methods.

We used the fundamental plane (FP) of early-type galaxies (data from the Sloan Digital Sky Survey) to measure the relative distances and peculiar velocities of 140 groups and clusters of galaxies at low redshifts ( z0.12). We have constructed the Hubble diagram between the distances of galaxy groups/clusters and their radial velocities in the CMB reference frame in the flat ΛCDM model ( Ωm=0.3, H0=70km · s –1 Mpc –1 ). We found that the standard logarithmic scatter of groups and clusters of galaxies on the Hubble diagram (minus peculiar velocities) is ± 0.0173 ( N = 140), which corresponds to the deviation of the Hubble constant 70 ± 2.8 km · s –1 Mpc –1 . For a sample of galaxy systems ( N = 63) with X-ray luminosity in the interval 0.151÷4×1044erg/s we got 70 ± 2.1 km · s –1 Mpc –1 . The standard deviations of peculiar velocities with quadratic allowance for errors are equal to null714 ± 7 km/s and 600 ± 7 km/s, respectively. Five large superclusters of galaxies from the SDSS region show an average peculiar velocity relative to the CMB reference frame +240 ± 250 km/s. We did not detect the outflow of galactic systems from the void (Giant Void, α≈13h, δ≈40°, z≈0.107) formed by groups and clusters of galaxies.

Fire is a dangerous disaster that causes human, ecological, and financial ramifications. Forest fires have increased significantly in recent years due to natural and artificial climatic factors. Therefore, accurate and early prediction of fires is essential. While significant advancements have been made in traditional and Deep Learning (DL) methods for fire detection, challenges remain in accurately pinpointing and recognizing fire regions, especially in diverse and large environments, to prevent damage effectively. To address these challenges, this paper introduces a novel Federated Learning (FL)-based method called Indoor-Outdoor FireNet (IOFireNet) for detecting and localizing fire regions. The proposed method incorporates a Bilateral Filter (BF) to effectively preprocess fire images to reduce noise artifacts and enhance detection clarity. It employs Super Pixel-based Adaptive Clustering (SPAC) to precisely segment fire and non-fire regions. A global IOFireNet model is developed to aggregate parameters from local models, improving detection accuracy across varied environments, while MobileNet is used for efficient data processing, enabling predictions on fire spread, severity, and affected areas to support early warnings. The proposed FL-based IOFireNet attains an accuracy rate of 98.65% for fire detection and 97.14% of mean IoU for segmentation. The proposed SPAC model reaches a mean IoU of 4.06%, which is 2.45% better than the graph cut algorithm and CRF model. The proposed model achieves an accuracy of 0.23%, 4.20%, 3.29%, and 10.02%, better than VGG-19, ResNet-50, Inception, and Dense Net, respectively.

As the key component of various energy storage and conversion devices, proton exchange membranes (PEMs) have been attracting significant interest. However, their further development is limited by the high cost of perfluorosulfonic acid polymers and the poor stability of acid-dopped non-fluorinated polymers. Recently, a new group of PEMs has been developed by hybridizing polyoxometalates (POMs), a group of super acidic sub-nanoscale metal oxide clusters, with polymers. POMs can serve simultaneously as both proton sponges and stabilizing agents, and their complexation with polymers can further improve polymers' mechanical performance and processability. Enormous efforts have been focused on studying supramolecular complexation or covalent grafting of POMs with various polymers to optimize PEMs in terms of cost, mechanical properties and stabilities. This concept summarizes recent advances in this emerging field and outlines the design strategies and application perspectives employed for using POM-polymer hybrid materials as PEMs.

The relationship of the redshift dipole anisotropy in the emission spectra of extragalactic sources and microwave background radiation with gravitational dipoles of large–scale inhomogeneity of the “super cluster of galaxies – super void” type, in which the objects of the pair are located in opposite regions of the celestial sphere, creating an imbalance of gravitational interaction, is analyzed. The union of five gravitational dipoles is considered as a Galactic polar gravitational dipole giant – not only as the cause of the asymmetry of the galactic hemispheres with respect to the dipole anisotropy of the redshift, but also as the cause of the dipole anisotropy of the cosmic microwave background radiation. Based on the results of solving measurement problems related to the identification of the cosmological distance scale based on the redshift in the emission spectra of extragalactic objects, the Local Group considers the anomalous violet shift of 37 galaxies forming alternating concentric circular bands around the North Galactic Pole with 167 other redshifted galaxies. It is hypothesized that the anomalous violet shift may be the result of the action of a gravitational dipole along the line “Local void → Shapley Attractor+ Shapley super cluster + Virgo super cluster” and the gravitational interaction of the most massive galaxies of the Local Group – the Andromeda and Milky Way galaxies.

The WDR11 complex is a receptor for acidic-cluster-containing cargo proteins

Cluster connectivity and super cluster connectivity of half hypercube networks