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Performance Analysis of Infrastructure Sharing Techniques in Cellular Networks: A Percolation Theory Approach

IEEE Transactions on Vehicular Technology 2025年

作者： Lin, Hao Kishk, Mustafa A. Alouini, Mohamed-Slim King Abdullah University of Science and Technology (KAUST) Electrical and Computer Engineering Program Computer Electrical and Mathematical Sciences and Engineering Division (CEMSE) Thuwal 23955-6900 Saudi Arabia Maynooth University Department of Electronic Engineering Maynooth W23 F2H6 Ireland King Abdullah University of Science and Technology (KAUST) CEMSE Division Thuwal 23955-6900 Saudi Arabia

In the context of 5G, infrastructure sharing has been identified as a potential solution to reduce the investment costs of cellular networks. In particular, it can help low-income regions build 5G networks more affordably and further bridge the digital divide. There are two main kinds of infrastructure sharing: passive sharing (i.e., site sharing) and active sharing (i.e., access sharing), which require mobile network operators (MNOs) to share their non-electronic elements or electronic elements, respectively. Because co-construction and sharing can achieve broader coverage with lower investment, through percolation theory, we investigate how different sharing strategies can deliver large-scale continuous services. First, we examine the percolation characteristics in signal-to-interference-plus-noise ratio (SINR) coverage graphs and the necessary conditions for percolation. Second, we propose an ‘average coverage radius’ to approximate the SINR graph with a low base station (BS) density based on the Gilbert disk model. Finally, we estimate the critical conditions of BS densities of MNOs for different sharing strategies and compare the percolation probabilities under different infrastructure sharing strategies. © 1967-2012 IEEE.

关键词： Gilbert disk model graph theory Infrastructure sharing percolation theory stochastic geometry

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AVTENet: A Human-Cognition-Inspired Audio-Visual Transformer-Based Ensemble Network for Video Deepfake Detection

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IEEE Transactions on Cognitive and Developmental Systems 2025年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min Taiwan International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei11529 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu30013 Taiwan National Chengchi University Department of Computer Science Taipei11605 Taiwan National Tsing Hua University Department of Electrical Engineering Institute of Communications Engineering Hsinchu300044 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei11529 Taiwan

The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous studies on detecting artificial intelligence-generated fake videos only utilize visual modality or audio modality. While some methods exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multimodal datasets of deepfake videos involving acoustic and visual manipulations, and are mostly based on convolutional neural networks with low detection accuracy. Considering that human cognition instinctively integrates multisensory information including audio and visual cues to perceive and interpret content and the success of transformer in various fields, this study introduces the audio-visual transformer-based ensemble network (AVTENet). This innovative framework tackles the complexities of deepfake technology by integrating both acoustic and visual manipulations to enhance the accuracy of video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multimodal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that the proposed model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. We also compare AVTENet against humans in detecting video forgery. The results show that AVTENet significantly outperforms humans. © 2016 IEEE.

关键词： audio-visual AVTENet Deepfake detection

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Visual Control and Mapping for UAV-Based Platform Inspection

Visual Control and Mapping for UAV-Based Platform Inspection

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Leonardo A. Fagundes Carlos M. Soria Raquel F. Vassallo Alexandre S. Brandão Department of Electrical Engineering Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil Facultad de Ingeniería Instituto de Automática Universidad Nacional de San Juan Argentine Department of Electric Engineering Federal University of Espirito Santo Vitória ES Brazil

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety of landing platforms are required. In this context, this paper presents a servo-visual controller that uses pattern detection and color segmentation techniques to identify take-off/landing platforms and estimate their current orientation. The proposed system was subjected to experimental validation with four platforms positioned in different orientations, heights, and positions, demonstrating its versatility in various conditions. Our study addresses the Flying Robots Trial League challenge, which emulates mapping and inspection tasks in offshore platforms.

关键词： Visualization Offshore installations Navigation Color Inspection Autonomous aerial vehicles Aircraft Drones Aerospace control

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MV-CLAM: Multi-View Molecular Interpretation with Cross-Modal Projection via Language Model

arXiv

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arXiv 2025年

作者： Ha, Sumin Kim, Jun Hyeong Piao, Yinhua Kim, Sun Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of Bio-MAX/N-Bio Seoul National University Korea Republic of Department of Computer Science and Engineering Seoul National University Korea Republic of Interdisciplinary Program in Bioinformatics Seoul National University Korea Republic of AIGENDRUG Co. Ltd. Korea Republic of

Human expertise in chemistry and biomedicine relies on contextual molecular understanding, a capability that large language models (LLMs) can extend through fine-grained alignment between molecular structures and text. Recent multimodal learning advances focus on cross-modal alignment, but existing molecule-text models ignore complementary information in different molecular views and rely on single-view representations, limiting molecular understanding. Moreover, naïve multi-view alignment strategies face two challenges: (1) separate aligned spaces with inconsistent mappings between molecule and text embeddings, and that (2) existing loss objectives fail to preserve complementary information for fine-grained alignment. This can limit the LLM’s ability to fully understand the molecular properties. To address these issues, we propose MV-CLAM, a novel framework that aligns multi-view molecular representations into a unified textual space using a multi-query transformer (MQ-Former). Our approach ensures cross-view consistency while a token-level contrastive loss preserves diverse molecular features across textual queries. MV-CLAM enhances molecular reasoning, improving retrieval and captioning accuracy. The source code of MV-CLAM is available in https://***/sumin124/***. © 2025, CC BY-NC-SA.

关键词： Molecular docking

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Microbial Communities in Coastal Salt Marshes Along the Southeast Coast of China and their Effects on Carbon Storage

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Current Analytical Chemistry 2025年

作者： Lv, Chunguang Li, Yan Zhang, Huining Wang, Chenyi Ren, Min Zhang, Chiqian Zhejiang Wanli University College of Biological & Environmental Sciences 315000 China NingboTech University School of Civil Engineering 315000 China Marine Environmental Monitoring Centre of Ningbo 315100 China Civil Engineering Program College of Engineering & Computer Science Arkansas State University 72467 AR United States

Background: Wetlands are vital carbon sinks, with coastal salt marshes being particularly effective in carbon sequestration. Understanding how different vegetation types influence soil carbon storage and microbial composition can enhance our knowledge of these ecosystems’ roles in global carbon cycling. Methods: This study investigates soil physicochemical properties, soil carbon storage, and microbial community composition and diversity at three depths (10, 30, and 60 cm) in five salt marsh plots from five coastal salt marshes: Bare flat (a non-vegetated marsh) and plots dominated by Imperata cylindrica, Solidago canadensis, Suaeda spp., and Phragmites australis. Carbon storage was evaluated by measuring soil organic carbon (SOC) content. At the same time, high-throughput sequencing was employed to analyze microbial communities, aiming to elucidate their relationships with soil carbon storage and wetland vegetation. Results: The average SOC contents in the five plots were in the order of S. canadensis (13.33 g·kg^–1) > Bare flat (11.45 g·kg^–1) > Suaeda spp. (8.10 g·kg^–1) > I. cylindrica (6.15 g·kg^–1) > P. australis (5.80 g·kg^–1). S. canadensis and Bare flat marshes had the highest carbon content, which is mainly attributed to the presence of the most abundant carbon-fixation microbes, Fulvivirgaceae (family) and Acidobacteria RB41 (genus), in the soil of these two plots. Both organic and dissolved organic carbon contents at 10 cm were higher than those at the other two depths for all five marshes. Conclusion: The Bare flat exhibited strong carbon sequestration capability, second only to the invasive S. canadensis plot among the five plots surveyed. It also showed the highest microbial abundance and the greatest number of carbon-sequestration-related functional genes. The S. canadensis plot exhibited the lowest microbial community diversity and abundance despite having the highest carbon storage capacity. As an i

关键词： carbon content carbon fixation carbon storage Coastal salt marsh invasive vegetation microbial community

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Mixotrophic Chlorella pyrenoidosa biofilm with enhanced biomass production, microalgal activity, and nutrient removal from nutrient-rich wastewater

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Journal of Environmental sciences (China) 2025年 157卷 366-377页

作者： Wu, Xiongwei Jin, Cong Zhang, Chiqian Li, Ping Huang, Jim Junhui Wu, Jing Wu, Jinhua Hu, Zhiqiang School of Environment and Energy South China University of Technology Guangzhou510006 China Zhongshan Institute of Modern Industrial Technology of South China University of Technology Zhongshan528400 China Civil Engineering Program College of Engineering & Computer Science Arkansas State University JonesboroAR72467 United States Environmental Research Institute National University of Singapore Singapore117411 Singapore Department of Civil and Environmental Engineering University of Missouri-Columbia 65211 United States

Microalgae possess significant advantages in nitrogen and phosphorus removal from nutrient-rich wastewater that are highly efficient and independent of the C/N ratio. However, challenges such as low biomass productivity, high variability in nutrient removal under different trophic types, and difficulty in harvesting biomass limits the large-scale application of microalgae wastewater treatment. This study attempted to employ mixotrophic microalgae biofilm to address these issues. The biomass production, microalgal activity, and nutrient removal of Chlorella pyrenoidosa biofilms with different trophic types were compared for nutrient-rich wastewater treatment. The results showed that the biomass productivity of the mixotrophic microalgal biofilm (0.215 g/(L·d)) was 2.3, 8.6, and 6.0 times higher than that of photoautotrophic microalgal biofilm, heterotrophic microalgal biofilm, and photoautotrophic suspended microalga, respectively. Additionally, the dehydrogenase activity (DHA), indicating microalgal activity, of the mixotrophic biofilm was 2.3 and 16.5 times higher than that of photoautotrophic and heterotrophic biofilms, respectively. Meanwhile, the mixotrophic biofilm removed 96.0 % of NH4+-N and 99.2 % of PO43–-P, more efficient than that with other types of biofilms and suspended microalgae. In an open-ended air-lift photobioreactor, the mixotrophic microalgal biofilm produced biomass at 0.12 g/(L·d) and removed 90.0 % of NH4+-N and 97.6 % of PO43–-P. This study suggests that the mixotrophic microalgal biofilm shows promise in treating nutrient-rich wastewater and producing microalgal biomass for value-added products. © 2024

关键词： Microalgae

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Unavoidable multilevel biaxial symmetry breaking in chiral hybrid liquid crystals

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Physical Review E 2025年第4期111卷 045410-045410页

作者： Jin-Sheng Wu Marina Torres Lázaro Souvik Ghosh Haridas Mundoor Henricus H. Wensink Ivan I. Smalyukh Department of Physics and Chemical Physics Program University of Colorado Boulder Colorado 80309 USA Laboratoire de Physique des Solides–UMR 8502 Université Paris-Saclay and CNRS 91405 Orsay France International Institute for Sustainability with Knotted Chiral Meta Matter Hiroshima University Higashihiroshima Japan Department of Electrical Computer and Energy Engineering Materials Science and Engineering Program and Soft Materials Research Center University of Colorado Boulder Colorado 80309 USA Renewable and Sustainable Energy Institute National Renewable Energy Laboratory and University of Colorado Boulder Colorado 80309 USA

Chiral nematic or cholesteric liquid crystals (LCs) are fluid mesophases with long-ranged orientational order featuring a quasilayered periodicity imparted by a helical director configuration but lacking long-range positional order. Doping molecular cholesteric LCs with strongly anisotropic uniaxial colloidal particles adds another level of complexity because of the interplay between weak surface-anchoring boundary conditions and bulk-based elastic distortions near the particle-LC interface. Using cylindrical colloidal disks and rods with different geometric shapes and surface conditions, we demonstrate that these colloidal inclusions generically exhibit biaxial orientational probability distributions which may impart anomalously strong local biaxiality onto the hybrid cholesteric LC structure. Unlike nonchiral hybrid molecular-colloidal LCs, where biaxial order emerges only at critical colloid volume fractions exceeding some uniaxial-biaxial transition value, the orientational probability of the colloidal inclusions immersed in chiral nematic hosts is unambiguously biaxial even at infinite dilution. We demonstrate that the colloids induce local biaxial perturbations within the molecular orientational order of the LC host medium which strongly enhances the weak but native biaxial order of chiral nematic LC induced by the chiral symmetry breaking of the director field. With the help of analytical modeling and computer simulations based on the Landau–de Gennes free energy of the host LC around the colloids, we rationalize the observed multilevel biaxial order and conclude that it is not only unavoidable but also strongly enhanced compared to both achiral hybrid LCs and purely molecular cholesteric LCs.

关键词： Cholesteric liquid crystals

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Effects of Superabsorbent Polymers on Autogenous Shrinkage and Microstructure in Metakaolin-Based Cementitious Materials

SSRN

引用

SSRN 2025年

作者： Palma e Silva, Arthur Aviz Capuzzo, Valdirene Maria Silva da Silva, Eugência Fonseca Agostinho, Lívia Borba Pereira, André Maués Brabo University of Brasília Postgraduate Program in Structures and Civil Construction DF BrasíliaCEP: 70910-900 Brazil Federal Fluminense University Department of Computer Science RJ Rio de JaneiroCEP: 22290-240 Brazil Federal University Uberlândia Postgraduate Program in Civil Engineering Minas Gerais UberlandiaCEP: 38408-100 Brazil

The use of superabsorbent polymers (SAPs) in combination with supplementary cementitious materials like metakaolin presents an opportunity to enhance concrete performance while addressing environmental concerns in construction, lowering CO2 emissions by clincker substitution. This study investigates the behavior of high-strength microconcrete incorporating SAPs and metakaolin, evaluating their feasibility and sustainability for construction applications. Three microconcrete and paste mixes were analyzed: a reference mix and two mixes containing 0.15% and 0.30% SAP by cement mass. All mixes included a 10% metakaolin substitution by cement mass and maintained the same water/cement ratio, without additional curing water for SAPs. Fresh-state tests assessed consistency and specific mass, while hardened-state tests measured elastic modulus. Autogenous shrinkage was evaluated through linear volumetric variation using dial gauges. Microstructural analysis of the pastes and microconcretes involved thermogravimetry, isothermal conduction calorimetry, and X-ray microtomography. The results highlight the beneficial effects of SAPs with metakaolin, including enhanced hardened state properties and refined pore structure, achieved despite the absence of extra curing water. SAPs contributed to increased pozzolanic activity in metakaolin, likely due to delayed water release from SAP desorption. Furthermore, SAPs effectively mitigated autogenous shrinkage, making their application in concrete mixes promising. These findings emphasize the dual benefit of improving concrete performance and advancing environmental sustainability, showcasing the potential of SAPs and metakaolin in producing high-performance, eco-friendly concrete solutions for the construction industry. © 2025, The Authors. All rights reserved.

关键词： Hardening

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A Multi-Step Multivariate Fuzzy-based Time Series Forecasting on Internet of Things Data

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IEEE Internet of Things Journal 2025年

作者： Bitencourt, Hugo Vinicius Lucas, Patri-Cia de Oliveira Orang, Omid Silva, Petronio C. L. Guimaraes, Frederico Gadelha Universidade Federal de Minas Gerais -UFMG Graduate Program in Electrical Engineering MG Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais IFNMG MG Salinas Brazil Universidade Federal de Minas Gerais -UFMG Computer Science MG Belo Horizonte31270-901 Brazil Federal Institute of Northern Minas Gerais IFNMG MG Januaria Brazil Universidade Federal de Minas Gerais -UFMG Department of Computer Science MG Belo Horizonte Brazil

Multi-step ahead time series forecasting is essential in Internet of Things (IoT) applications in smart cities and smart homes to make accurate future predictions and precise decision-making. Thus, this study introduces a novel multiple-input single-output (MISO) forecasting method called Multi-Step Embedding-based Fuzzy Time Series (MS-EFTS), designed to predict high-dimensional non-stationary time series data. As a first-order approach, it employs a direct strategy that integrates an embedding transformation with a weighted multivariate FTS (WMVFTS) model. This combination allows for effective predictions over long-term horizons within low-dimensional, learned continuous representations. The effectiveness of the proposed MS-EFTS is assessed using three high-dimensional IoT time series in this investigation. The obtained results showcase the superior performance of the proposed method compared to some deep learning forecasting methods, including LSTM, BiLSTM, TCN, and CNN-LSTM, in terms of accuracy, parsimony, and efficiency. © 2014 IEEE.

关键词： Smart homes

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Local and global sensitivity analyses on the overflow probability of Abadia de Goiás radioactive near surface repository

引用

Nuclear engineering and Design 2025年 439卷

作者： Teixeira, D.G. Frutuoso e Melo, P.F. Alvim, L.G.M. Alvim, A.C.M. Alves, A.S.M. Graduate Program of Nuclear Engineering COPPE Federal University of Rio de Janeiro RJ Rio de Janeiro Brazil Department of Computer Science Multidisciplinary Institute Federal Rural University of Rio de Janeiro UFRRJ RJ Nova Iguaçu Brazil Eletronuclear S. A. RJ Rio de Janeiro Brazil

This work presents a sensitivity analysis of the overflow probability of the near- surface radioactive repository built after the Abadia de Goiás accident, where radioactive 137Cs was released. The purpose of the analysis is to help the repository owner and the regulatory body make decisions on design parameters that affect the overflow probability. The following parameters have been considered: degradation function of the repository ceiling, internal porosity of the repository, internal area of the repository base, repository base and wall thicknesses, repository height, height of the liquid column inside the repository, average rainfall rate, evapotranspiration rate, surface runoff and hydraulic conductivity of the repository concrete. The choice for the range of each parameter is discussed. An investigation of the role of the mentioned parameters is detailed based on results obtained in a previous paper, and the dependencies among the rate parameters on the average rainfall rate is emphasized and modeled. To give a deeper perspective, local and global sensitivity analyses have been performed. In the case of global analysis, two approaches have been followed: in the first, the concept of Normalized Mutual Information and the other one leverages Shapley values derived from Light Gradient Boosting Machine and Shapley values have been used for investigating non-linearities. For some parameters the lowest values are to be considered, e.g., the repository base thickness and the average rainfall rate, while for others the highest value is desirable, like the evapotranspiration rate and the surface runoff in order to obtain lower overflow probabilities. These results should be looked with care because nonlinearities have been identified by the Shapley value analysis. Overall, the degradation function and the evapotranspiration rate emerge as the most influential parameters. The legacy of this work lies in the robust methodological framework it provides, paving the way fo

关键词： Nuclear reactor accidents

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