Dense Environments Research Articles

Proposed Explainable Interference Control Technique in 6G Networks Using Large Language Models (LLMs)

After the advent of 5th generation (5G) and 6th generation (6G) cellular networks, the complexity of managing real-time signal interference has increased in dense and dynamic environments. Traditional interference techniques, such as frequency reuse and allocation, while effective, lack robust adaptability and transparency needed to reduce interference in advanced communication networks. This paper introduces a novel approach that fuses large language models (LLMs) and Explainable Artificial Intelligence (XAI) to mitigate interference and enhance interference management in the mathematical foundations of 6G networks. The proposed approach provides accurate interference predictions, which the LLM balances with its complex architecture, necessary to meet the demands of beyond 5G and 6G networks, along with interpretable explanations to ensure transparency in decision-making. The proposed framework has been evaluated across various performance metrics. Interference latency consistently achieves lower rates of 0.95 s, compared to traditional techniques, which average around 1 s. Furthermore, the confidence score of the LLM shows a stable value of 0.87 throughout the system, compared to 0.85 in techniques without LLMs. Overall, the XAI-driven LLM demonstrates the potential of incorporating LLMs and XAI into wireless networks to improve resilience in next-generation networks. This proof of concept introduces a novel framework that offers new dimensions in wireless communication, particularly for interference management, prediction, and mitigation.

A Multi-Active and Multi-Passive Sensor Fusion Algorithm for Multi-Target Tracking in Dense Group Clutter Environments

Multi-target tracking (MTT) of multi-active and multi-passive sensor (MAMPS) systems in dense group clutter environments is facing significant challenges in measurement fusion. Due to the difference in measurement information characteristics in MAMPS fusion, it is difficult to effectively correlate and fuse different types of sensors’ measurements, leading to difficulty in taking full advantage of various types of sensors to improve target tracking accuracy. To this end, we present a novel MAMPS fusion algorithm, which is based on centralized measurement association fusion (MAF) and distributed deep neural network (DNN) track fusion, named the MAMPS-MAF-DNN algorithm. Firstly, to reduce the impact of the dense group clutter, a clutter pre-processing algorithm is elaborated, which combines the advantages of the CFDP (cluster by finding density peaks) and double threshold screening algorithms. Then, for the single-active and multi-passive sensor (SAMPS) system, a centralized MAF algorithm based on angle information is developed, called the SAMPS-MAF algorithm. Finally, the SAMPS-MAF algorithm is extended to the MAMPS system within the DNN framework, and the complete MAMPS-MAF-DNN algorithm is proposed. Experimental results indicate that, compared to the existing MAF and covariance intersection (CI) fusion algorithms, the proposed MAMPS-MAF-DNN algorithm can fully combine the advantages of multi-active and multi-passive sensors, efficiently reduce the computational complexity, and obviously improve the tracking accuracy.

A Study on the Cooling Impact of the River Yamuna and its Surrounding LULC: A Case Study of New Delhi, India

Abstract. The unplanned growth of urban cities has adversely affected the thermal conditions. The Land Use and Land Cover (LULC) present in urban areas significantly impacts the thermal conditions of the surrounding environment. This study investigated the cooling effect of river in dense urban environments. It is conducted on the Yamuna river that flows through New Delhi, the capital city of India. The River Cooling Intensity (RCI) and River Cooling Range (RCR) assessment has been done for the summer season of May 2023 with the help of Landsat 8 images. The RCI ranged from 3.58°C to 1.16°C while the RCR varied from 1320 m to 360 m. It is observed that the river cooling effect is higher in the built-up class while the vegetation class weakens the effect of river cooling intensity and range. Zonal mean temperature varies from 32.02°C to 34.82°C according to the LULC distribution. This study provides valuable insights into the relationship between river cooling and temperature regulation according to the LULC classes. It also establishes the presence of an urban cool island inside the city region due to the river, as the mean temperature of the river surrounding (33.83°C) was lower than that of the city (35.73°C).

Moving Target Detection for Array Antennas in Varying Multipath Environments

Detecting moving targets remains a significant challenge in radar applications, particularly in dense multipath environments where signal complexities present formidable obstacles. However, the application of time reversal (TR) technology offers promising prospects for enhancing target detection capabilities. Utilizing this technology, we propose a detection algorithm tailored specifically for a moving target, designed exclusively for array antennas (AA) operating in dense multipath environments with dynamic channel variations. We establish an AA-TR signal model within this framework and derive the AA-TR likelihood ratio test (AA-TR-LRT) detector. To assess the effectiveness of our proposed approach, we also develop the AA conventional LRT (AA-C-LRT) detector as a comparative benchmark. Comprehensive numerical tests consistently verify the outstanding effectiveness of our detection algorithm, underscoring its precision in detecting moving targets, particularly in highly complex multipath scenarios with varying channels.

QSO MUSEUM

Extended Lyα emission is routinely found around single quasars across cosmic time. However, few studies have investigated how such emission changes in fields with physically associated quasar pairs, which should reside in dense environments and are predicted to be linked through intergalactic filaments. We present VLT/MUSE snapshot observations (45 minutes/source) to unveil extended Lyα emission on scales of the circumgalactic medium (CGM) around the largest sample of physically associated quasar pairs to date, encompassing eight pairs (14 observed quasars) at z ∼ 3 with an i-band magnitude between 18 and 22.75, corresponding to absolute magnitudes Mi(z = 2) between −29.6 and −24.9. The pairs are either at close (∼50–100 kpc, five pairs) or wide (∼450–500 kpc, three pairs) angular separation and have velocity differences of Δv ≤ 2000 km s−1. We detected extended emission around 12 of the 14 targeted quasars and investigated the luminosity, size, kinematics, and morphology of these Lyα nebulae. On average, they span about 90 kpc and are 2.8 × 1043 erg s−1 bright. Irrespective of the quasars’ projected distance, the nebulae often (∼45%) extend toward the other quasar in the pair, leading to asymmetric emission whose flux-weighted centroid is at an offset position from any quasar location. We show that large nebulae are preferentially aligned with the large-scale structure, as traced by the direction between the two quasars, and conclude that the cool gas (104 K) in the CGM traces well the direction of cosmic web filaments. Additionally, the radial profile of the Lyα surface brightness around quasar pairs can be described by a power law with a shallower slope (∼−1.6) with respect to single quasars (∼−2), indicative of increased CGM densities out to large radii and/or an enhanced contribution from the intergalactic medium (IGM) due to the dense environments expected around quasar pairs. The sample presented in this study contains excellent targets for ultra-deep observations to directly study filamentary IGM structures in emission. This work demonstrates that a large snapshot survey of quasar pairs will pave the way to direct statistical study of the IGM.

Evidence of Extreme Ionization Conditions and Low Metallicity in GHZ2/GLASS-Z12 from a Combined Analysis of NIRSpec and MIRI Observations

GHZ2/GLASS-z12, one of the most distant galaxies found in JWST observations, has been recently observed with both the NIRSpec and MIRI spectrographs, establishing a spectroscopic redshift z spec = 12.34 and making it the first system at z > 10 with complete spectroscopic coverage from rest-frame UV to optical wavelengths. This galaxy is identified as a strong C iv λ1549 emitter (EW = 46 Å) with many other detected emission lines, such as N iv] λ1488, He ii λ1640, O iii] λ λ1661,1666, N iii] λ1750, C iii] λ λ1907,1909, [O ii] λ λ3726,3729, [Ne iii] λ3869, [O iii] λ λ4959,5007, and Hα, including a remarkable detection of the O iii Bowen fluorescence line at rest frame λ = 3133 Å. We analyze in this paper the joint NIRSpec + MIRI spectral data set. Combining six optical strong-line diagnostics (namely R2, R3, R23, O32, Ne3O2, and Ne3O2Hd), we find extreme-ionization conditions, with log10 ([O III] λ λ4959,5007/[O II] λ λ3726,3729) = 1.39 ± 0.19 and log10 ([Ne III] λ3869/[O II] λ λ3726,3729) = 0.37 ± 0.18 in stark excess compared to typical values in the interstellar medium (ISM) at lower redshifts. These line properties are compatible either with an active galactic nucleus (AGN) or with a compact, very dense star-forming environment (ΣSFR ≃ 102–103 M ⊙ yr−1 kpc−2 and ΣM* ≃ 104–105 M ⊙ pc−2), with a high ionization parameter (log10(U) =−1.75 ± 0.16), a high ionizing photon production efficiency log(ξion)=25.7−0.1+0.3 , and a low gas-phase metallicity (also confirmed by the direct, T e method) ranging between 4% and 11% Z ⊙, indicating a rapid chemical enrichment of the ISM in the past few megayears. These properties also suggest that a substantial amount of ionizing photons (∼10%) are leaking outside of GHZ2 and starting to reionize the surrounding intergalactic medium, possibly due to strong radiation-driven winds. The general lessons learned from GHZ2 are the following: (i) the UV-to-optical combined nebular indicators are broadly in agreement with UV-only or optical-only indicators; (ii) UV+optical diagnostics fail to discriminate between an AGN and star formation in a low-metallicity, high-density, and extreme-ionization environment; and (iii) comparing the nebular line ratios with local analogs may be approaching its limits at z ≳ 10, as this approach is potentially challenged by the unique conditions of star formation experienced by galaxies at these extreme redshifts.

The Potential for Long-lived Intermediate-mass Black Hole Binaries in the Lowest Density Dwarf Galaxies

Intermediate-mass black hole (IMBH) mergers with masses 104–106 M ⊙ are expected to produce gravitational waves detectable by the Laser Interferometer Space Antenna (LISA) with high signal-to-noise ratios from the present day to cosmic dawn. IMBH mergers are expected to take place within dwarf galaxies; however, the dynamics, timescales, and effect on their hosts are largely unexplored. In a previous study, we examined how IMBHs would pair and merge within nucleated dwarf galaxies. IMBHs in nucleated hosts evolve very efficiently, forming a binary system and coalescing within a few hundred million years. Although the fraction of dwarf galaxies (107 M ⊙ ≤ M ⋆ ≤ 1010 M ⊙) hosting nuclear star clusters is between 60% and 100%, this fraction drops to 20%–70% for lower-mass dwarfs (M ⋆ ≈ 107 M ⊙), with the largest drop in low-density environments. Here, we extend our previous study by performing direct N-body simulations to explore the dynamics and evolution of IMBHs within nonnucleated dwarf galaxies, under the assumption that IMBHs exist within these dwarfs. To our surprise, none of the IMBHs in our simulation suite merge within a Hubble time, despite many attaining high eccentricities e ∼ 0.7–0.95. We conclude that extremely low stellar density environments in the centers of nonnucleated dwarfs do not provide an ample supply of stars to interact with an IMBH binary, resulting in its stalling, in spite of triaxiality and high eccentricity, common means to drive a binary to coalescence. Our findings underline the importance of considering all detailed host properties to predict IMBH merger rates for LISA.

The VANDELS Survey: Star formation and quenching in two over-densities at 3<z<4

Exploring galaxy evolution in dense environments, such as proto-clusters, is pivotal for understanding the mechanisms that drive star formation and the quenching of star formation. This study provides insights into how two over-densities could have impacted the physical properties, such as the star formation rate, stellar mass, morphology, and the evolution of their members, particularly members characterised by a quenching of star formation. We focus on the over-densities identified at $3<z<4$ in the Chandra Deep Field South (CDFS) and in the Ultra Deep Survey (UDS) regions of the VIMOS (VIsible MultiObject Spectrograph) Ultra Deep Survey (VANDELS). Our methodology involves the analysis of the spectral energy distribution of the members of the over-densities and of the galaxies in the field. We relied on Bayesian analysis techniques BEAGLE and BAGPIPES to study the best-fit physical parameters and the rest-frame U-V and V-J colours (UVJ). This approach allowed us to separate quenched and star-forming galaxies based on the UVJ diagram and by estimating their specific star formation rate (sSFR). We used the TNG300 simulation to interpret our results. We find that two out of 13 over-densities host quenched galaxies, with red rest-frame U-V colour and low sSFR. The physical properties of them are consistent with those of massive passive galaxies from the literature. The quenched members are redder, older, more massive, and show a more compact morphology than the other galaxy members. The two over-densities, with the highest-density peaks at $z and $z respectively, have dark matter halo masses consistent with being proto-clusters at $z and they each host an active galactic nucleus (AGN). We found five AGNs in the structure at $z and three AGNs in the one at $z In comparison to quenched galaxies in the field, our massive quenched members show a higher local density environment. By using the IllustrisTNG simulation (TNG300), we find that proto-cluster structures with quenched galaxies at high redshift are likely to evolve into a structure with a higher fraction of passive galaxies by $z = The two over-densities studied here host massive quenched galaxies in their highest-density peaks and AGNs. By following the evolution of the passive galaxies in the simulated proto-clusters at $z = 3$ from the TNG300 simulation, we find that the median of their sSFRs was larger than 10$^ $ yr$^ $ at $z=6$ and the median mass growth rate was 96<!PCT!> from $z=6$ to $z=3$. In 20<!PCT!> of the simulated proto-clusters, the passive galaxy had already accreted 10-20<!PCT!> of the mass at $z=6$, with SFRs $>100$ M$_ odot $ yr$^ $ at $z=8$. The conditions for this favorable mass assembly could be the galaxy interactions and the high gas accretion rate in the dense environment. As a consequence, the quenching of the star formation at $z=3$ could be driven by the black hole mass growth and AGN feedback. This scenario is consistent with the properties of the two quenched galaxies we find in our two over-densities at $z sim3$.

Photometry and kinematics of dwarf galaxies from the Apertif HI survey

Understanding the dwarf galaxy population in low density environments (in the field) is crucial for testing the current Lambda Cold Dark Matter cosmological model. The increase in diversity toward low-mass galaxies is seen as an increase in the scatter of scaling relations, such as the stellar mass--size and the baryonic Tully-Fisher relation (BTFR), and is also demonstrated by recent in-depth studies of an extreme sub-class of dwarf galaxies with low surface brightnesses but large physical sizes called ultra-diffuse galaxies (UDGs). We aim to select dwarf galaxies independent of their stellar content and to make a detailed study of their gas and stellar properties. We selected galaxies from the APERture Tile In Focus (Apertif) survey and applied a constraint on their $i$-band absolute magnitude in order to exclude high-mass systems. The sample consists of 24 galaxies, 22 of which are resolved in by at least three beams, and they span mass ranges of 8.6 $ lesssim 9.7 and a stellar mass range of 8.0 $ lesssim 9.7 (with only three galaxies having log ( msun)>9). We determined the geometrical parameters of the and stellar disks, built kinematic models from the data using and extracted surface brightness profiles in the g-, r- and i- bands from the Pan-STARRS 1 photometric survey. We used these measurements to place our galaxies on the stellar mass--size relation and the BTFR, and we compared them with other samples from the literature. We find that at a fixed stellar mass, our dwarfs have larger optical effective radii than isolated optically selected dwarfs from the literature, and we found misalignments between the optical and morphologies for some of our sample. For most of our galaxies, we used the morphology to determine their kinematics, and we stress that deep optical observations are needed to trace the underlying stellar disks. Standard dwarfs in our sample follow the same BTFR of high-mass galaxies, whereas UDGs are slightly offset toward lower rotational velocities, in qualitative agreement with results from previous studies. Finally, our sample features a fraction (25<!PCT!>) of dwarf galaxies in pairs that is significantly larger with respect to previous estimates based on optical spectroscopic data.

Key Factors in the Design of Urban Underground Metro Lines

Designing sustainable underground metro lines in dense urban environments is a highly challenging task that requires the collaboration of numerous stakeholders and consultants to make crucial decisions influenced by several factors. While it is impossible to address every issue influencing the decision-making process, identifying key factors and their interdependencies is essential for optimal design. This study focuses on six critical aspects of the reference design of metro systems: (1) track alignment, (2) tunneling strategy, (3) station typology, (4) operations and maintenance, (5) procurement strategy, and (6) environmental aspects. Amongst these aspects, we identify track alignment as the primary driving factor that influences the other factors. We analyze the decision between shallow and deep alignments as an engineering choice that necessitates balancing conflicting factors and constraints. Our contribution lies in mapping these factors and their dependencies, thus offering policymakers, project managers, and designers a framework to navigate the design process. Our discussion also provides guidance to public agencies in tendering for design teams more efficiently. Drawing from lessons learned by experienced design managers, this study aims to fill the gap in the literature by offering a generalist perspective on metro design.

Density‐Aware Diffusion Model for Efficient Image Dehazing

AbstractExisting image dehazing methods have made remarkable progress. However, they generally perform poorly on images with dense haze, and often suffer from unsatisfactory results with detail degradation or color distortion. In this paper, we propose a density‐aware diffusion model (DADM) for image dehazing. Guided by the haze density, our DADM can handle images with dense haze and complex environments. Specifically, we introduce a density‐aware dehazing network (DADNet) in the reverse diffusion process, which can help DADM gradually recover a clear haze‐free image from a haze image. To improve the performance of the network, we design a cross‐feature density extraction module (CDEModule) to extract the haze density for the image and a density‐guided feature fusion block (DFFBlock) to learn the effective contextual features. Furthermore, we introduce an indirect sampling strategy in the test sampling process, which not only suppresses the accumulation of errors but also ensures the stability of the results. Extensive experiments on popular benchmarks validate the superior performance of the proposed method. The code is released in https://github.com/benchacha/DADM.

AEFF-SSC: an attention-enhanced feature fusion for 3D semantic scene completion

Abstract Three-dimensional (3D) occupancy perception technology aims to enable autonomous vehicles to observe and understand dense 3D environments. Estimating the complete geometry and semantics of a scene solely from visual images is challenging. However, humans can easily conceive the complete form of objects based on partial key information and their own experience. This ability is crucial for recognizing and interpreting the surrounding environment. To equip 3D occupancy perception systems with a similar capability, a 3D semantic scene completion method called AEFF-SSC is proposed. This method deeply explores boundary and multi-scale information in voxels, aiming to reconstruct 3D geometry more accurately. We have specifically designed an attention-enhanced feature fusion module that effectively fuses image feature information from different scales and focuses on feature boundary information, thereby more efficiently extracting voxel features. Additionally, we introduce a semantic segmentation module driven by a 3D attention-UNet network. This module combines a 3D U-Net network with a 3D attention mechanism. Through feature fusion and feature weighting, it aids in restoring 3D spatial information and significantly improves the accuracy of segmentation results. Experimental verification on the SemanticKITTI dataset demonstrates that AEFF-SSC significantly outperforms other existing methods in terms of both geometry and semantics. Specifically, within a 12.8 m × 12.8 m area ahead, our geometric occupancy accuracy has achieved a significant improvement of 71.58%, and at the same time, the semantic segmentation accuracy has also increased remarkably by 54.20%.

Optimization Methodology of Polar Direct-Drive Illumination for the National Ignition Facility.

Improved laser illumination uniformity drives shocks and implosions to create more extreme high energy density environments. Predominantly, the geometry of experiments that can be performed is dictated by the layout of beams at laser facilities, limiting interfacility and multiscale investigations. This Letter presents the first automated, algorithmic approach for generating illumination configurations for high energy density experiments. The method is demonstrated in comparison to a polar direct-drive solid target experiment at the National Ignition Facility. The new illumination configuration is simulated to create greater than ×3 higher peak pressure and almost ×2 higher density by maintaining better shock uniformity. The optimization process is performed with reduced computational expense and isotropic plasma profiles while accounting for the impact of cross-beam energy transfer.

Joint range and velocity super-resolution estimation with Doppler effects for innovative OFDM-based RFA RadCom system

Conventional radar and communication signals face challenges when integrating for accurate sensing in dense electromagnetic environments, especially in scenarios involving high-velocity targets estimation. To address this issue, we propose the random frequency agile-orthogonal frequency division multiplexing-based radar and communication (RFA-OFDM-based RadCom) signal, a novel framework that combines RFA hopping radar signal and OFDM signal. This framework effectively handles high-velocity Doppler scenarios, enhancing electronic countermeasure capabilities. In high-velocity scenarios, achieving accurate range and velocity estimation is crucial. We introduce a comprehensive received signal model that considers intrapulse and intersubcarrier Doppler effects, often overlooked in traditional high-velocity contexts. The proposed two-phase hierarchical perceptual methodology enables joint super-resolution estimation using the shared signal. We transform the shared signal echo model into a uniform linear array-like model and employ the matrix decomposition algorithm based on bidirectional weighted frequency smoothing (BWFS-MD) for decoherence processing. Subsequently, the estimation of signal parameters via rotational invariance techniques (ESPRIT)-complementary integrated subspace fitting (E-CISF) algorithm accurately estimates joint range and velocity. Meanwhile, the contrastive analysis of the mutual impacts between radar and communication functions is conducted. Theoretical analysis and simulation results robustly validate the superior performance of the proposed BWFS-MD algorithm. Furthermore, considering the precision of joint range-velocity estimation, real-time constraints, and super-resolution capability (which is emphasized), the E-CSIF algorithm demonstrates the best overall performance from a comprehensive perspective.

Precision in situ cryogenic correlative light and electron microscopy of optogenetically positioned organelles.

Unambiguous targeting of cellular structures for in situ cryo-electron microscopy in the heterogeneous, dense and compacted environment of the cytoplasm remains challenging. Here, we have developed a cryogenic correlative light and electron microscopy (cryo-CLEM) workflow that utilizes thin cells grown on a mechanically defined substratum for rapid analysis of organelles and macromolecular complexes by cryo-electron tomography (cryo-ET). We coupled these advancements with optogenetics to redistribute perinuclear-localised organelles to the cell periphery, allowing visualisation of organelles that would otherwise be positioned in cellular regions too thick for cryo-ET. This reliable and robust workflow allows for fast in situ analyses without the requirement for cryo-focused ion beam milling. Using this protocol, cells can be frozen, imaged by cryo-fluorescence microscopy and be ready for batch cryo-ET within a day.

Urban environmental acupuncture as a tool to support nature-based solution implementation: does it deliver what it promises?

Urban environmental acupuncture (UEA) is a novel approach designed to engage with a variety of stakeholders to successfully implement nature-based solutions in dense urban areas. The Interreg Central Europe project SALUTE4CE piloted this concept through small-scale, low-budget interventions in four cities: Chorzow (Poland), Erfurt (Germany), Alessandria (Italy), and Liptovski Mikulas (Slovakia). The pilot projects were designed to be quickly implementable, utilizing abandoned or undesirable sites, with the potential to catalyze both physical and social transformation. Interviews with local actors in these cities after project implementation provided valuable feedback, which was used to develop principles of urban environmental acupuncture. While the limited number of interviews means these findings offer only initial insights, they are largely supported by existing research. Nevertheless, this perspective provides important lessons that can inform future transformation projects and help evaluate the success of the UEA approach. The key contributions of this work are the introduction of urban environmental acupuncture concept, deriving principles of UEA based on feedback from local stakeholders and offering insights in future design and evaluation of similar nature-based solution initiatives in dense urban environments. This perspective helps to establish the potential of UEA as a tool for engaging diverse stakeholders and catalyzing sustainable urban transformation (specifically expansion of nature-based solutions) through low-cost interventions.

Estimating daily road traffic pollution in Hong Kong using CFD modelling: Validation and application

Road traffic is a major source of urban air pollution, exposing residents to harmful levels of pollutants, particularly in densely populated urban centers. In this study, Computational Fluid Dynamics (CFD) modelling is applied to investigate the impact of road traffic emissions on air pollution within a dense urban environment. The model, applied in Mong Kok, Hong Kong, incorporates high-resolution traffic activity, meteorological, and background concentration data. It demonstrates strong agreement with roadside measurements, deviating by 18.8 % for NOx, 15.5 % for CO, and 0.7 % for PM10, with potential underestimation linked to unmodeled NOx-O3 photochemistry during midday hours (12:00–17:00). Results reveal that local road traffic significantly increases background NOx levels (41 % average increase), highlighting the importance of dispersion modelling for accurate pollution assessments. Traffic-induced increases in CO and PM10 background levels are less pronounced. Two applications demonstrate the model's utility. Firstly, analysis of daily pollution distribution reveals that approximately 10 % of the studied area experiences moderate to very high pollution levels during peak hours. Secondly, an investigation into pollution sources within a leisure park identifies heavy-duty and light-duty vehicles as the primary NOx polluters. This modelling approach provides a valuable decision-making tool for policymakers and local authorities. It enables the assessment of urban design changes, strategic placement of sensitive structures, and future traffic fleet composition choices to mitigate pollution exposure. As air quality regulations tighten, this study offers a robust method for guiding impactful mitigation strategies.

Thermally robust hierarchical nanofiber triboelectric yarns for efficient energy harvesting in firefighting E-textiles

Textile-based triboelectric nanogenerators (TENGs) face challenges in achieving high performance and fulfilling functional requirement for special applications. This paper presents the development of a high-performance, thermally robust hierarchical polyimide (PI) nanofiber triboelectric yarns with a charge-trapping interlayer for application in firefighting E-textiles. The hierarchical nanofiber yarns, comprising a stainless-steel core electrode, a PI/MXene interlayer and PI outer tribo-layer, exhibit enhanced triboelectric performance due to the charge-trapping capabilities of MXene, which preventing the recombination of triboelectric and induced charges. When the MXene content in the charge-trapping interlayer reached 1 wt%, the corresponding TENG achieved its optimal output performance, with an output voltage of 153 V and a current of 13.13 μA and a peak power density of 0.84 W/m2 under optimal conditions. It also demonstrates exceptional thermal stability, maintaining stable output at temperatures up to 400 °C. The integration of the TENG into E-textiles enables real-time monitoring of firefighters’ physical activities and location tracking, significantly enhancing their safety and operational efficiency in fire scenarios. Additionally, the TENG powers electroluminescent yarns, improving visibility in dense smoke and dust environments. This research opens new avenues for the application of smart wearable systems in high-temperature environments, providing effective strategies for ensuring the safety of firefighters in fire rescue operations.

Distributed Multi-Vehicle Task Assignment and Motion Planning in Dense Environments

Distributed Multi-Vehicle Task Assignment and Motion Planning in Dense Environments

The Velocity Dispersion Function for Quiescent Galaxies in Massive Clusters from IllustrisTNG

We derive the central stellar velocity dispersion function (VDF) for quiescent galaxies in 280 massive clusters with log(M200/M⊙)>14 in IllustrisTNG300. The VDF is an independent tracer of the dark matter mass distribution of subhalos in galaxy clusters. Based on the IllustrisTNG cluster catalog, we select quiescent member subhalos with a specific star formation rate <2 × 10−11 yr−1 and stellar mass log(M*/M⊙)>9 . We then simulate fiber spectroscopy to measure the stellar velocity dispersion of the simulated galaxies; we compute the line-of-sight velocity dispersions of star particles within a cylindrical volume that penetrates the core of each subhalo. We construct the VDFs for quiescent subhalos within R 200. The simulated cluster VDF exceeds the simulated field VDF for logσ*>2.2 , indicating the preferential formation of large velocity dispersion galaxies in dense environments. The excess is similar in simulations and in the observations. We also compare the simulated VDF for the three most massive clusters with log(M200/M⊙)>15 with the observed VDF for the two most massive clusters in the local Universe, Coma and A2029. Intriguingly, the simulated VDFs are significantly lower for logσ*>2.0 . This discrepancy results from (1) a smaller number of subhalos with log(M*/M⊙)>10 in TNG300 compared to the observed clusters, and (2) a significant offset between the observed and simulated M *–σ * relations. The consistency in the overall shape of the observed and simulated VDFs offers a unique window into galaxy and structure formation in simulations.