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Path Loss (PL) is vital to evaluate the performance of Unmanned Aerial Vehicles (UAVs) as Aerial Base Stations (ABSs), particularly in urban environments with complex propagation due to various obstacles. Accurately modeling PL requires a generalized Probability of Line-of-Sight (PLoS) that can consider multiple obstructions. While the existing PLoS models mostly assume a simplified Manhattan grid with uniform building sizes and spacing, they overlook the real-world variability in building dimensions. Furthermore, such models do not consider other obstacles, such as trees and streetlights, which may also impact the performance, especially in millimeter-wave (mmWave) bands. This paper introduces a Manhattan Random Simulator (MRS) to estimate PLoS for UAV-based communications in urban areas by incorporating irregular building shapes, non-uniform spacing, and additional random obstacles to create a more realistic environment. Lastly, we present the PL differences with and without obstacles for standard urban environments and derive the empirical PL for these environments., Comment: 9th European Conference on Antennas and Propagation (EuCAP)

Accurate Probability of Line-of-Sight (PLoS) modeling is important in evaluating the performance of Unmanned Aerial Vehicle (UAV)-based communication systems in urban environments, where real-time communication and low latency are often major requirements. Existing PLoS models often rely on simplified Manhattan grid layouts using International Telecommunication Union (ITU)-defined built-up parameters, which may not reflect the randomness of real cities. Therefore, this paper introduces the Urban LoS Simulator (ULS) to model PLoS for three random city layouts with varying building sizes and shapes constructed using ITU built-up parameters. Based on the ULS simulated data, we obtained the empirical PLoS for four standard urban environments across three different city layouts. Finally, we analyze how well Manhattan grid-based models replicate PLoS results from random and real-world layouts, providing insights into their applicability for time-critical communication systems in urban IoT networks., Comment: 2025 IEEE Wireless Communications and Networking Conference (WCNC): 2025 IEEE Wireless Communications and Networking Conference (WCNC) Workshops - WCNC 2025 WS03: The 3rd International Workshop on the Internet of Time-Critical Things (IoTime 2025)

Co-crystallization is an accessible way to control physicochemical characteristics of organic crystals, which finds many biomedical applications. In this work, we present Generative Method for Co-crystal Design (GEMCODE), a novel pipeline for automated co-crystal screening based on the hybridization of deep generative models and evolutionary optimization for broader exploration of the target chemical space. GEMCODE enables fast de novo co-crystal design with target tabletability profiles, which is crucial for the development of pharmaceuticals. With a series of experimental studies highlighting validation and discovery cases, we show that GEMCODE is effective even under realistic computational constraints. Furthermore, we explore the potential of language models in generating co-crystals. Finally, we present numerous previously unknown co-crystals predicted by GEMCODE and discuss its potential in accelerating drug development., Comment: Accepted at 38th Conference on Neural Information Processing Systems (NeurIPS)

Quantum computers must achieve large-scale, fault-tolerant operation to deliver on their promise of transformational processing power [1-4]. This will require thousands or millions of high-fidelity quantum gates and similar numbers of qubits [5]. Demonstrations using neutral-atom qubits trapped and manipulated by lasers have shown that this modality can provide high two-qubit gate (CZ) fidelities and scalable operation [6-13]. However, the gates in these demonstrations are driven by lasers that do not resolve individual qubits, with universal computation enabled by physical mid-circuit shuttling of the qubits. This relatively slow operation may greatly extend runtimes for useful, large-scale computation. Here we demonstrate a universal neutral-atom quantum computer with gate rates limited by optical switching times, rather than shuttling, by individually addressing tightly focused laser beams at an array of single atoms. We achieve CZ fidelity of 99.35(4)% and local single-qubit RZ gate fidelity of 99.902(8)%. Moreover, we demonstrate non-destructive readout of alkali-atom qubits with 0.9(3)% loss, which boosts operational speed. This technique also enables us to measure a state-of-the-art CZ fidelity of 99.73(3)% when excluding atom-loss events, which may be mitigated through erasure conversion. Our results represent a critical step towards large-scale, fault-tolerant neutral-atom quantum computers that can execute computations on practical timescales.

In an era where digital connectivity is increasingly foundational to daily life, the security of Wi-Fi Access Points (APs) is a critical concern. This paper addresses the vulnerabilities inherent in Wi-Fi APs, with a particular focus on those using proprietary file systems like MiniFS found in TP-Link's AC1900 WiFi router. Through reverse engineering, we unravel the structure and operation of MiniFS, marking a significant advancement in our understanding of this previously opaque file system. Our investigation reveals not only the architecture of MiniFS but also identifies several private keys and underscores a concerning lack of cryptographic protection. These findings point to broader security vulnerabilities, emphasizing the risks of security-by-obscurity practices in an interconnected environment. Our contributions are twofold: firstly, based, on the file system structure, we develop a methodology for the extraction and analysis of MiniFS, facilitating the identification and mitigation of potential vulnerabilities. Secondly, our work lays the groundwork for further research into WiFi APs' security, particularly those running on similar proprietary systems. By highlighting the critical need for transparency and community engagement in firmware analysis, this study contributes to the development of more secure network devices, thus enhancing the overall security posture of digital infrastructures., Comment: The 19th International Conference on Availability, Reliability and Security (ARES 2024), July 30-August 2, 2024, Vienna, Austria

Recent successes in virtual screening have been made possible by large models and extensive chemical libraries. However, combining these elements is challenging: the larger the model, the more expensive it is to run, making ultra-large libraries unfeasible. To address this, we developed a target-agnostic, efficacy-based molecule search model, which allows us to find structurally dissimilar molecules with similar biological activities. We used the best practices to design fast retrieval system, based on processor-optimized SIMD instructions, enabling us to screen the ultra-large 40B Enamine REAL library with 100\% recall rate. We extensively benchmarked our model and several state-of-the-art models for both speed performance and retrieval quality of novel molecules.

High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html

Creation of nanomaterials with specific morphology remains a complex experimental process, even though there is a growing demand for these materials in various industry sectors. This study explores the potential of AI to predict the morphology of nanoparticles within the data availability constraints. For that, we first generated a new multi-modal dataset that is double the size of analogous studies. Then, we systematically evaluated performance of classical machine learning and large language models in prediction of nanomaterial shapes and sizes. Finally, we prototyped a text-to-image system, discussed the obtained empirical results, as well as the limitations and promises of existing approaches.

To keep supporting 6G requirements, the radio access infrastructure will increasingly densify. Cell-free (CF) networks offer extreme flexibility by coherently serving users with multiple Access points (APs). This paradigm requires precise and stable phase synchronization. In this article, we adapt the standardized 5G NR setup (subcarrier spacing, OFDM symbol duration and allocation) to investigate the effect of Phase Noise (PN) on the simulated performance of scalable CF networks. In contrast to the prior literature relying on the simplified model of a free-running oscillator with the Wiener process, we deploy a realistic hardware-inspired phase noise model reproducing the Local Oscillator (LO) phase drift. Our results demonstrate that even affordable LOs offer sufficient stability to ensure negligible loss of uplink Spectral Efficiency (SE) on the time scale of the standardized 5G Transmission Time Interval of 1 ms. This study substantiates the feasibility of CF networks based on 5G standards.

The study of volatiles and the search for water are the primary objectives of the Luna-27 mission, which is planned to land on the south pole of the Moon in 2028. Here we present the tunable Diode Laser Spectrometer (DLS-L) that will be onboard the lander. The DLS-L will perform isotopic analysis of volatiles that are pyrolytically evolved from regolith. This article dives into the design of the spectrometer and the characterisation of isotopic signature retrieval. We look forward to expanding our knowledge of Lunar geochemistry by measuring D/H, 18O/17O/16O, 13C/12C ratios in situ, which could be the one-of-a-kind direct study of the lunar soil isotopy without sample contamination.

Unmanned aerial vehicles (UAVs) have gained popularity in the communications research community because of their versatility in placement and potential to extend the functions of communication networks. However, there remains still a gap in existing works regarding detailed and measurement-verified air-to-ground (A2G) Massive Multi-Input Multi-Output (MaMIMO) channel characteristics which play an important role in realistic deployment. In this paper, we first design a UAV MaMIMO communication platform for channel acquisition. We then use the testbed to measure uplink Channel State Information (CSI) between a rotary-wing drone and a 64-element MaMIMO base station (BS). For characterization, we focus on multidimensional channel stationarity which is a fundamental metric in communication systems. Afterward, we present measurement results and analyze the channel statistics based on power delay profiles (PDPs) considering space, time, and frequency domains. We propose the stationary angle (SA) as a supplementary metric of stationary distance (SD) in the time domain. We analyze the coherence bandwidth and RMS delay spread for frequency stationarity. Finally, spatial correlations between elements are analyzed to indicate the spatial stationarity of the array. The space-time-frequency channel stationary characterization will benefit the physical layer design of MaMIMO-UAV communications., Comment: 10 pages, 12 figures

Nanofluids have the potential to enhance oil recovery through the structural disjoining pressure, a pressure developed when nanoparticles concentrate at the three-phase contact line. A model microfluidic porous network is used to measure the percentage of oil displaced from this channel as the volume fraction of a Triton X-100 micelle nanofluid is varied from 0 - 30%. The percentage of oil displaced varies nearly linearly with micellar nanoparticle volume fraction starting with 39% using deionized water and 89% using a volume fraction of 30%. While the trend is clear, significant variability between experiments was observed for a fixed nanofluid volume fraction. This indicates that surface energy heterogeneity is important for the nanofluid oil displacement performance.

In this paper, we investigate the integration of drone identification data (Remote ID) with collision avoidance mechanisms to improve the safety and efficiency of multi-drone operations. We introduce an improved Near Mid-Air Collision (NMAC) definition, termed as UAV NMAC (uNMAC), which accounts for uncertainties in the drone's location due to self-localization errors and possible displacements between two location reports. Our proposed uNMAC-based Reciprocal Velocity Obstacle (RVO) model integrates Remote ID messages with RVO to enable enhanced collision-free navigation. We propose modifications to the Remote ID format to include data on localization accuracy and drone airframe size, facilitating more efficient collision avoidance decisions. Through extensive simulations, we demonstrate that our approach halves mission execution times compared to a conservative standard Remote ID-based RVO. Importantly, it ensures collision-free operations even under localization uncertainties. By integrating the improved Remote ID messages and uNMAC-based RVO, we offer a solution to significantly increase airspace capacity while adhering to strict safety standards. Our study emphasizes the potential to augment the safety and efficiency of future drone operations, thereby benefiting industries reliant on drone technologies., Comment: 10 pages, 8 figures, 2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC)

We study intermittent coherent structures in solar wind magnetic turbulence from MHD to kinetic plasma scales using Parker Solar Probe data during its first perihelion (at 0.17 au), when the satellite was in the Alfv\'enic slow wind of 340 km/s. The coherent structures are energetic events localized in time and covering wide range of scales. We detect them using Morlet wavelets. For the first time, we apply a multi-scale analyses in physical space to study these structures. At MHD scales within the inertial range, times scales $\tau \in (1, 10^{2} )$ s, we find (i) current sheets including switchback boundaries and (ii) Alfv\'en vortices. Within these events, there are embedded structures at smaller scales: typically Alfv\'en vortices at ion scales, $\tau \in (0.08, 1)$ s, and a compressible vortices at sub-ion scales, $\tau \in (8,80)$ ms. The number of coherent structures grows toward smaller scales: we observe about $\sim 200$ events during 5 h time interval at MHD scales, $\sim 10^{3}$ events ai ion scales and $\sim 10^{4}$ events at sub-ion scales. In general, there are multiple structures of ion and sub-ion scales embedded within one MHD structure. There are also examples of ion and sub-ion scales structures outside of MHD structures. To quantify the relative importance of different type of structures, we do a statistical comparison of the observed structures with the expectations of models of the current sheets and vortices. This comparison is based on amplitude anisotropy of magnetic fluctuations within the structures. The results show the dominance of Alfv\'en vortices at all scales in contrast to the widespread view of dominance of current sheets. This means that Alfv\'en vortices are important building blocs of solar wind turbulence., Comment: Revised version of the article, accepted for publication in Astrophysical Journal, 30 pages, 15 figures

This paper presents a quasi-deterministic ray tracing (QD-RT) method for analyzing the propagation of electromagnetic waves in street canyons. The method uses a statistical bistatic distribution to model the Radar Cross Section (RCS) of various irregular objects such as cars and pedestrians, instead of relying on exact values as in a deterministic propagation model. The performance of the QD-RT method is evaluated by comparing its generated path loss distributions to those of the deterministic ray tracing (D-RT) model using the Two-sample Cramer-von Mises test. The results indicate that the QD-RT method generates the same path loss distributions as the D-RT model while offering lower complexity. This study suggests that the QD-RT method has the potential to be used for analyzing complicated scenarios such as street canyon scenarios in mmWave wireless communication systems.