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An Overview of Performance Analysis and Optimization in Coexisting Satellites and Future Terrestrial Networks
No full textThe existing radio frequency band is overcrowded and will soon be unable to accommodate the growing demand for greater data rate services. Consequently, considerable efforts are being undertaken to develop adaptable spectrum-sharing techniques and handle the unprecedented data traffic demands. Using satellite services to enhance terrestrial communications is emerging as a cutting-edge solution for future application-aware networks. The coexistence of space and ground communications infrastructures, however, introduces exacerbated levels of wireless interference. Hence, intelligent resource allocation strategies are essential to ensure dependable communication and high-capacity broadband access globally. To this end, this manuscript surveys the advances in optimization and performance analysis methods in coexisting satellites networks and future wireless systems. The paper first presents an overview of the existing papers related to the more general scope of space-air-ground communications. The survey then highlights optimization frameworks for coexisting satellites and sixth-generation communication systems (6G), focusing on maximizing sum rate, maximizing energy efficiency,and minimizing transmit power. Additionally, the survey presents a number of papers dealing with performance analysis, namely outage probability, ergodic capacity, average symbol error rate, and effective capacity. The paper further discusses the critical challenges imposed by such integrated systems, e.g., backhaul-access cross-interference, resource coordination, channel modeling, and algorithmic complexity. Finally, we identify several open research issues, e.g., a cognitive radio approach to the considered network, integrated backhaul-access system, integration with emerging disruptive systems, artificial intelligence, and quantum communication technologies for coexisting satellites and future terrestrial networks
A wheat tandem kinase activates an NLR to trigger immunity
No full textThe role of nucleotide-binding leucine-rich repeat (NLR) receptors in plant immunity is well studied, but the function of a class of tandem kinases (TKs) that confer disease resistance in wheat and barley remains unclear. In this study, we show that the SR62 locus is a digenic module encoding the Sr62TK TK and an NLR (Sr62NLR), and we identify the corresponding AvrSr62 effector. AvrSr62 binds to the N-terminal kinase 1 of Sr62TK, triggering displacement of kinase 2, which activates Sr62NLR. Modeling and mutation analysis indicated that this is mediated by overlapping binding sites (i) on kinase 1 for binding AvrSr62 and kinase 2 and (ii) on kinase 2 for binding kinase 1 and Sr62NLR. Understanding this two-component resistance complex may help engineering and breeding plants for durable resistance
The Nature of Surface Charge Dynamics in Photoactive Materials: Insight from Ultrafast Imaging and Density Functional Theory (DFT) Calculations
No full textThe efficiency and operational stability of photoactive materials are governed by ultrafast charge-carrier dynamics, which unfold on femtosecond to picosecond timescales and are strongly influenced by surfaces and interfaces. Because these regions control charge separation, recombination, and transport, developing methods that combine femtosecond temporal resolution with nanometer spatial sensitivity is essential for uncovering the microscopic processes that dictate device performance.
This thesis investigates surface charge dynamics by combining Four-Dimensional Ultrafast Scanning Electron Microscopy (4D-USEM) with first-principles simulations (DFT). 4D-USEM synchronizes femtosecond laser excitation with pulsed electron probes, producing time-resolved secondary-electron (SE) images that map surface dynamics with femtosecond–nanometer precision. This technique bridges the gap between bulk optical spectroscopy and static electron microscopy, providing a uniquely surface-sensitive window into ultrafast carrier behavior.
Initial experiments on model semiconductor surfaces underscore the decisive role of surface chemistry. Systematic measurements conducted before and after controlled argon sputtering reveal that oxide-terminated surfaces exhibit an increase in work function upon excitation, suppressing SE emission and appearing as dark contrast in time-resolved images. In contrast, oxide-free surfaces display a decrease in work function, enhancing SE emission and producing bright contrast. These complementary behaviors demonstrate that surface composition directly influences ultrafast charge redistribution and transient photovoltage formation, providing compelling evidence that chemical termination governs interfacial dynamics on femtosecond timescales.
The methodology is further applied to halide perovskite single crystals, where crystallographic orientation is shown to critically affect carrier transport. MAPbI₃ with (001) orientation supports higher carrier density and longer diffusion lengths than (110), highlighting orientation and termination control as practical design levers. In mixed-cation systems, FA₀.₆MA₀.₄PbI₃ exhibits longer lifetimes than FA₀.₄MA₀.₆PbI₃. DFT reveals that FA-rich compositions lower the barrier for iodide migration from bulk to surface, enabling vacancy passivation, while simultaneously raising the barrier for ion escape into vacuum, thereby suppressing new vacancy formation. Finally, Cd-doped FAPbI₃ stabilizes the α-phase, reduces trap densities, extends lifetimes, and increases diffusion lengths, establishing doping as a complementary strategy for performance enhancement.
By integrating ultrafast electron microscopy with first-principles theory, this work advances fundamental understanding of light–matter interactions and establishes practical design rules for durable, high-efficiency optoelectronic and energy-conversion devices
Multimodal Safety Evaluation in Generative Agent Social Simulations
No full textCan generative agents be trusted in multimodal environments? Despite advances in large language and vision-language models that enable agents to act autonomously and pursue goals in rich settings, their ability to reason about safety, coherence, and trust across modalities remains limited. We introduce a reproducible simulation framework for evaluating agents along three dimensions: (1) safety improvement over time, including iterative plan revisions in text-visual scenarios; (2) detection of unsafe activities across multiple categories of social situations; and (3) social dynamics, measured as interaction counts and acceptance ratios of social exchanges. Agents are equipped with layered memory, dynamic planning, multimodal perception, and are instrumented with SocialMetrics, a suite of behavioral and structural metrics that quantifies plan revisions, unsafe-to-safe conversions, and information diffusion across networks. Experiments show that while agents can detect direct multimodal contradictions, they often fail to align local revisions with global safety, reaching only a 55 percent success rate in correcting unsafe plans. Across eight simulation runs with three models - Claude, GPT-4o mini, and Qwen-VL - five agents achieved average unsafe-to-safe conversion rates of 75, 55, and 58 percent, respectively. Overall performance ranged from 20 percent in multi-risk scenarios with GPT-4o mini to 98 percent in localized contexts such as fire/heat with Claude. Notably, 45 percent of unsafe actions were accepted when paired with misleading visuals, showing a strong tendency to overtrust images. These findings expose critical limitations in current architectures and provide a reproducible platform for studying multimodal safety, coherence, and social dynamics
On-Surface Reactions of Electronically Active Self-Assembled Monolayers for Electrode Work Function Tuning
No full textSelf-assembled monolayers (SAMs) help improve the performance of organic electronic devices through interface passivation and enhanced carrier transport. Yet, there is limited information regarding the chemical structure of the SAMs upon functionalization and subsequent thermal treatment. Here, we studied the on-surface reaction of carbazole-derived SAMs on model gold electrodes, focusing on the chemical structure changes induced by thermal treatments. Furthermore, we correlate the microscopic changes with their impact on the electrode’s work function. The carbazole-based SAMs first transform into organometallic complexes. At higher annealing temperatures, SAMs convert to oligomeric complexes. The observed chemical reactions significantly reduce the electrode work function and facilitate electron injection in n-type organic thin-film transistors. Our results highlight the on-surface synthesis of electronically active SAMs as an alternative approach for modifying the work function of electrodes for organic electronics.The authors thank T. Stavridis and S. Liu for experimental support. S. Fatayer acknowledges the KAUST Office of Sponsored Research (award no. OSR-CRG2022-5038). For computer time, this research used Shaheen II managed by the Supercomputing Core Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia. Part of this research used the LT-STM/NC-AFM facility of the Center for Functional Nanomaterials (CFN), which is a U.S. Department of Energy Office of Science User Facility, at Brookhaven National Laboratory under Contract No. DE-SC0012704
Efficient Resource Allocation for Semantic Video Surveillance Transmission over LEO Satellites
No full textVideo surveillance in remote areas poses significant challenges due to limited network coverage and the high data requirements of video transmission. In such environments, satellite communication offers a viable solution to provide coverage under limited bandwidth conditions. At the same time, emerging semantic communication technology addresses the issue of data volume by transmitting only the most relevant information. This work proposes a semantic communication framework for video surveillance data transmission in remote areas. The framework transmits compact semantic representations from cameras over LEO satellites using Narrowband communication technology. More importantly, we formulate and solve a resource allocation problem that maximizes semantic information transmission under bandwidth constraints by optimally selecting semantic representations and satellite resource units. Our approach demonstrates the feasibility of semantic video surveillance using limited-bandwidth IoT standards such as LTE eMTC and NB-IoT over LEO satellites
Contrast-Source Inversion with Stochastic Optimization and Plug-And-Play Regularization
No full textA novel contrast-source inversion (CSI) scheme that is accelerated by stochastic optimization and regularized by a plug-and-play neural network denoiser, namely STO-PNPCSI, is proposed to reconstruct the relative permittivity profile of an unknown investigation domain. The idea of stochastic optimization is applied to accelerate the CSI scheme in multitransmitter configuration. At each iteration, instead of updating all the contrast sources corresponding to different transmitters, the proposed method updates only a random one, resulting in much shorter computation time and avoiding local minima and saddle points during the inversion. The noise introduced by stochastic optimization is suppressed by a plug-and-play (PNP) regularization that makes use of a pre-trained neural network, namely Swin-Conv-UNet (SCUNet), as the denoiser. SCUNet integrates residual convolutional blocks and swin transformer blocks within its neural network architecture, offering highly effective image denoising performance. The effectiveness of the proposed STO-PNP-CSI algorithm is validated through a numerical example, where it is compared with other methods. The results show that the proposed method significantly outperforms other methods in computation time and convergenc
Deep-water corals indicate the Red Sea survived the last glacial lowstand.
No full textThe Red Sea, a nascent ocean basin connected to the Indian Ocean via a shallow strait, is assumed to have experienced significant environmental changes during the last glacial period due to a sea-level drop likely exceeding 110 m. This study investigates the hypothesis that hydrodynamic restriction led to severe ecological impacts, including basin-wide extinction due to elevated salinity followed by a short time of oxygen depletion. Uranium-Thorium dating of deep-water corals (DWCs) from 26 northern Red Sea sites reveals coral growth during and after the Last Glacial sea-level lowstand, indicating tolerable seawater chemistry. Additional geochemical data show no significant difference in Red Sea chemistry or temperature between the Latest Pleistocene and Holocene. A meta-analysis of 27 deep-sea cores reveals that while planktonic foraminifera experienced local extinction, other microfossil groups seemingly persisted. These findings suggest that the Red Sea survived the last sea-level lowstand, challenging the paradigm of a complete ecological collapse and providing insights into the resilience of marine ecosystems.We owe a debt of gratitude to our Saudi Arabian partners, NEOM, and to Richard Bush, Deborah Colbourne, Jennifer Munro, and Abdulqader Khamis for their support. We are also indebted to OceanX and the crew of OceanXplorer for their operational and logistical assistance. Special thanks to Andrew Craig, Olaf Dieckoff, Ewan Bason, and Kate von Krusenstiern for data acquisition, sample collection, and support of scientific operations aboard OceanXplorer. We also thank OceanX Media for documenting and communicating this work to the public. Gratitude is extended to Mike Ackerman for assistance with sample preparation. We sincerely thank the three anonymous reviewers for their thoughtful and constructive feedback which improved the clarity and depth of our manuscript. This is Ismar-CNR, Bologna, scientific contribution no. 2095. This study was funded by NEOM Agreement No: SRA-ENV-2023-001/AWD-008854 to the University of Miami
Laser applications to chemical, security, and environmental analysis: introduction to the feature issue
No full textThe 19 th Topical Meeting on Laser Applications to Chemical, Security, and Environmental Analysis (LACSEA) was held in Toulouse, France from 15–19 July 2024, as part of the Optica Optical Sensing Congress, with a return to in-person attendance. The meeting featured 21 sessions covering recent advances in laser and optical spectroscopy, sensor design, and diagnostic application. A total of 125 contributed and invited papers were presented during the meeting, including topics such as photo-acoustic spectroscopy, ultra-fast (fs/ps) laser spectroscopy, frequency comb spectroscopy, infrared imaging, sensor development, remote sensing, environmental monitoring, reacting flow diagnostics, hypersonic flow diagnostics, nuclear diagnostics, and machine learning and computational sensing
Distribution System Reconfiguration to Mitigate Load Altering Attacks via Stackelberg Games
No full textThe widespread integration of IoT-controllable devices (e.g., smart EV charging stations and heat pumps) into modern power systems enhances capabilities but introduces critical cybersecurity risks. Specifically, these devices are susceptible to load-altering attacks (LAAs) that can compromise power system safety. This paper quantifies the impact of LAAs on nodal voltage constraint violations in distribution networks (DNs). We first present closed-form expressions to analytically characterize LAA effects and quantify the minimum number of compromised devices for a successful LAA. Based on these insights, we propose a reactive defense mechanism that mitigates LAAs through DN reconfiguration. To address strategic adversaries, we then formulate defense strategies using a non-cooperative sequential game, which models the knowledgeable and strategic attacker, accounting for the worst-case scenario and enabling the reactive defender to devise an efficient and robust defense. Further, our formulation also accounts for uncertainties in attack localization. A novel Bayesian optimization approach is introduced to compute the Stackelberg equilibrium, significantly reducing computational burden efficiently. The game-theoretic strategy effectively mitigates the attack’s impact while ensuring minimal system reconfiguration.This work has been supported in part by the PhD Cofund WALL-EE project
between the University of Warwick, UK and CY Cergy Paris University,
France and in part by the King Abdullah University of Science and Technology
(KAUST) under Award No. RFS-OFP2023-5505. This work was partially
presented at IEEE PES General Meeting-2024 [1]