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Communication, Navigation, and Surveillance (CNS) is the backbone of the Air Traffic Management (ATM) and Unmanned Aircraft System (UAS) Traffic Management (UTM) systems, ensuring safe and efficient operations of modern and future aviation. Traditionally, the CNS is considered three independent systems: communications, navigation, and surveillance. The current CNS system is fragmented, with limited integration across its three domains. Integrated CNS (ICNS) is a contemporary concept implying that those systems are provisioned through the same technology stack. ICNS is envisioned to improve service quality, spectrum efficiency, communication capacity, navigation predictability, and surveillance capabilities. The 5G technology stack offers higher throughput, lower latency, and massive connectivity compared to many existing communication technologies. This paper presents our 5G ICNS vision and network architecture and discusses how 5G technology can support integrated CNS services using terrestrial and non-terrestrial networks. We also discuss key 5G radio access technologies for delivering integrated CNS services at low altitudes for Innovative Air Mobility (IAM) and Advanced Air Mobility (AAM) operations. Finally, we present relevant challenges and potential research directions for further studies., Comment: This work has been accepted in IEEE 25th Integrated Communications, Navigation and Surveillance Conference, April 8-10, 2025, Brussels, Belgium. Copyright has been transferred to IEEE

Tree balance plays an important role in various research areas in phylogenetics and computer science. Typically, it is measured with the help of a balance index or imbalance index. There are more than 25 such indices available, recently surveyed in a book by Fischer et al. They are used to rank rooted binary trees on a scale from the most balanced to the stringiest. We show that a wide range of subtree-sized based measures satisfying concavity and monotonicity conditions are minimized by the complete or greedy-from-the-bottom (GFB) tree and maximized by the caterpillar tree, yielding an infinitely large family of distinct new imbalance indices. Answering an open question from the literature, we show that one such established measure, the $\widehat{s}$-shape statistic, has the GFB tree as its unique minimizer. We also provide an alternative characterization of GFB trees, showing that they are equivalent to complete trees, which arise in different contexts. We give asymptotic bounds on the expected $\widehat{s}$-shape statistic under the uniform and Yule-Harding distributions of trees, and answer questions for the related $Q$-shape statistic as well.

Large numbers of unstable periodic orbits (UPOs) have been found recently in doubly periodic, two-dimensional Kolmogorov flow at moderate Reynolds numbers $Re \in \{40, 100\}$ using gradient based-optimisation. While these solutions lead to robust statistical reconstructions at the $Re$-values where they were obtained, it is unclear how their dynamical importance evolves as $Re$ is increased. We investigate this by performing arclength continuation of these UPOs to beyond $Re \approx 1000$, and examine how the contribution of each UPO to the reconstruction of statistics evolves with $Re$. Statistical reconstruction away from the $Re$-value where the states were converged is relatively robust for the mean and root-mean-squared velocities, but challenging for complete PDFs, as a large number of solutions rapidly leave the attractor. The UPOs can be grouped into three classes based on whether the limiting dissipation rate is above, beneath or within the range of values typical for the turbulent flow, and we introduce a labelling procedure for identifying dominant vortical interactions in the turbulent UPOs by searching for point vortex periodic orbits that reproduce the dynamics of large scale coherent vortices. Convergence of the point vortex UPOs is achieved via gradient-based optimisation of a scalar loss function which both (1) matches the dynamics of the point vortices to the turbulent vortex cores at $Re=100$ and (2) insist that the point vortex evolution is itself time-periodic. The point vortex UPOs identify a wide range of simpler dynamical processes in the turbulent collection, including slowly-propagating crystals, tripolar structures and bound states. These features persist in the high-dissipation class of UPOs as $Re$ increases, while the role of the forcing diminishes, suggesting a connection to solutions of the Euler equation as $Re \to \infty$.

We present measurements of large-scale cosmic microwave background (CMB) E-mode polarization from the Cosmology Large Angular Scale Surveyor (CLASS) 90 GHz data. Using 115 det-yr of observations collected through 2024 with a variable-delay polarization modulator, we achieved a polarization sensitivity of $78\,\mathrm{\mu K\,arcmin}$, comparable to Planck at similar frequencies (100 and 143 GHz). The analysis demonstrates effective mitigation of systematic errors and addresses challenges to large-angular-scale power recovery posed by time-domain filtering in maximum-likelihood map-making. A novel implementation of the pixel-space transfer matrix is introduced, which enables efficient filtering simulations and bias correction in the power spectrum using the quadratic cross-spectrum estimator. Overall, we achieved an unbiased time-domain filtering correction to recover the largest angular scale polarization, with the only power deficit, arising from map-making non-linearity, being characterized as less than $3\%$. Through cross-correlation with Planck, we detected the cosmic reionization at $99.4\%$ significance and measured the reionization optical depth $\tau=0.053^{+0.018}_{-0.019}$, marking the first ground-based attempt at such a measurement. At intermediate angular scales ($\ell>30$), our results, both independently and in cross-correlation with Planck, remain fully consistent with Planck's measurements., Comment: 24 pages, 19 figures, 3 tables; submitted to ApJ

Unlike biomarkers in biofluids, airborne biomarkers are dilute and difficult to trace. Detecting diverse airborne biomarkers with sufficient sensitivity typically relies on bulky and expensive equipment like mass spectrometers that remain inaccessible to the general population. Here, we introduce Airborne Biomarker Localization Engine (ABLE), a simple, affordable, and portable platform that can detect both volatile, non-volatile, molecular, and particulate biomarkers in about 15 minutes. ABLE significantly improves gas detection limits by converting dilute gases into droplets by water condensation, producing concentrated aqueous samples that are easy to be tested. Fundamental studies of multiphase condensation revealed unexpected stability in condensate-trapped biomarkers, making ABLE a reliable, accessible, and high-performance system for open-air-based biosensing applications such as non-contact infant healthcare, pathogen detection in public space, and food safety., Comment: 17 pages, 5 figures. An additional 67-page supplementary materials document containing a detailed description of methods, 15 additional discussions, 30 figures, and 3 tables, will be made available after the manuscript is published after peer-review process

The compact directed acyclic word graph (CDAWG) is the minimal compact automaton that recognizes all the suffixes of a string. Classically the CDAWG has been implemented as an index of the string it recognizes, requiring $o(n)$ space for a copy of the string $T$ being indexed, where $n=|T|$. In this work, we propose using the CDAWG as an index for grammar-compressed strings. While this enables all analyses supported by the CDAWG on any grammar-compressed string, in this work we specifically consider pattern matching. Using the CDAWG index, pattern matching can be performed on any grammar-compressed string in $\mathcal{O}(\text{ra}(m)+\text{occ})$ time while requiring only $\mathcal{O}(\text{er}(T))$ additional space, where $m$ is the length of the pattern, $\text{ra}(m)$ is the grammar random access time, $\text{occ}$ is the number of occurrences of the pattern in $T$, and $\text{er}(T)$ is the number of right-extensions of the maximal repeats in $T$. Our experiments show that even when using a na\"ive random access algorithm, the CDAWG index achieves state of the art run-time performance for pattern matching on grammar-compressed strings. Additionally, we find that all of the grammars computed for our experiments are smaller than the number of right-extensions in the string they produce and, thus, their CDAWGs are within the best known $\mathcal{O}(\text{er}(T))$ space asymptotic bound.

Grammar-based compression is a widely-accepted model of string compression that allows for efficient and direct manipulations on the compressed data. Most, if not all, such manipulations rely on the primitive \emph{random access} queries, a task of quickly returning the character at a specified position of the original uncompressed string without explicit decompression. While there are advanced data structures for random access to grammar-compressed strings that guarantee theoretical query time and space bounds, little has been done for the \emph{practical} perspective of this important problem. In this paper, we revisit a well-known folklore random access algorithm for grammars in the Chomsky normal form, modify it to work directly on general grammars, and show that this modified version is fast and memory efficient in practice.

Purpose: To develop a 3D distortion-free reduced-FOV diffusion-prepared GRE sequence and demonstrate its in-vivo application for diffusion imaging of the spinal cord in healthy volunteers. Methods: A 3D multi-shot reduced-FOV diffusion-prepared GRE (RFOV-DP-GRE) acquisition is achieved using a slice-selective tip-down pulse in the phase encoding direction in the diffusion preparation, combined with magnitude stabilisers. The efficacy of the developed reduced FOV approach and accuracy of ADC estimates were evaluated in a phantom. In addition, 5 healthy volunteers were enrolled and scanned at 3T using the proposed sequence and a standard spin echo diffusion-weighted single-shot EPI sequence (DW-SS-EPI) for spinal cord imaging. Image quality, perceived SNR and image distortion were assessed by two expert readers and quantitative measurements of apparent SNR were performed. Results: The phantom scan demonstrates the efficacy of the proposed reduced FOV approach. Consistent ADC estimates were measured with RFOV-DP-GRE when compared with DW-SS-EPI. In-vivo, RFOV-DP-GRE demonstrated improved image quality and reduced perceived distortion, while maintaining perceived SNR compared to DW-SS-EPI. Conclusion: 3D Distortion-free diffusion-prepared imaging can be achieved using the proposed sequence, Comment: 16 pages, 4 figures, submitted to Magnetic Resonance in Medicine

The Carbon monOxide Mapping Array Project (COMAP) Pathfinder survey continues to demonstrate the feasibility of line-intensity mapping using high-redshift carbon monoxide (CO) line emission traced at cosmological scales. The latest COMAP Pathfinder power spectrum analysis is based on observations through the end of Season 2, covering the first three years of Pathfinder operations. We use our latest constraints on the CO(1-0) line-intensity power spectrum at $z\sim3$ to update corresponding constraints on the cosmological clustering of CO line emission and thus the cosmic molecular gas content at a key epoch of galaxy assembly. We first mirror the COMAP Early Science interpretation, considering how Season 2 results translate to limits on the shot noise power of CO fluctuations and the bias of CO emission as a tracer of the underlying dark matter distribution. The COMAP Season 2 results place the most stringent limits on the CO tracer bias to date, at $\langle{Tb}\rangle<4.8$ $\mu$K. These limits narrow the model space significantly compared to previous CO line-intensity mapping results while maintaining consistency with small-volume interferometric surveys of resolved line candidates. The results also express a weak preference for CO emission models used to guide fiducial forecasts from COMAP Early Science, including our data-driven priors. We also consider directly constraining a model of the halo-CO connection, and show qualitative hints of capturing the total contribution of faint CO emitters through the improved sensitivity of COMAP data. With continued observations and matching improvements in analysis, the COMAP Pathfinder remains on track for a detection of cosmological clustering of CO emission., Comment: 9 pages + bibliography and appendices (13 pages total); 9 figures, 1 table; v2 reflects minor changes made for version submitted to A&A, with no changes to top-line results

We present updated constraints on the cosmological 3D power spectrum of carbon monoxide CO(1-0) emission in the redshift range $2.4$-$3.4$. The constraints are derived from the two first seasons of Carbon monOxide Mapping Array Project (COMAP) Pathfinder line-intensity mapping observations aiming to trace star-formation during the Epoch of Galaxy Assembly. These results improve on the previous Early Science (ES) results through both increased data volume and improved data processing methodology. On the methodological side, we now perform cross-correlations between groups of detectors (''feed-groups''), as opposed to cross-correlations between single feeds, and this new feed-group pseudo power spectrum (FGPXS) is constructed to be more robust against systematic effects. In terms of data volume, the effective mapping speed is significantly increased due to an improved observational strategy as well as better data selection methodology. The updated spherically- and field-averaged FGPXS, $\tilde{C}(k)$, is consistent with zero, at a probability-to-exceed of around $34\,\%$, with an excess of $2.7\,\sigma$ in the most sensitive bin. Our power spectrum estimate is about an order of magnitude more sensitive in our six deepest bins across ${0.09\,\mathrm{Mpc}^{-1} < k < 0.73\,\mathrm{Mpc}^{-1}}$, as compared to the feed-feed pseudo power spectrum (FPXS) of COMAP ES. Each of these bins individually constrains the CO power spectrum to ${kP_\mathrm{CO}(k)< 2400-4900\,\mathrm{\mu K^2 Mpc^{2}}}$ at $95\,\%$ confidence. To monitor potential contamination from residual systematic effects, we analyze a set of 312 difference-map null tests and find that these are consistent with the instrumental noise prediction. In sum, these results provide the strongest direct constraints on the cosmological 3D CO(1-0) power spectrum published to date., Comment: 19 pages, 10 figures, v3 reflects changes made for version accepted and published by Astronomy and Astrophysics, no change to final results

The CO Mapping Array Project (COMAP) Pathfinder is performing line intensity mapping of CO emission to trace the distribution of unresolved galaxies at redshift $z \sim 3$. We present an improved version of the COMAP data processing pipeline and apply this to the first two seasons of observations. This analysis improves on the COMAP Early Science (ES) results in several key aspects. On the observational side, all second season scans were made in constant-elevation mode, after noting that the previous Lissajous scans were associated with increased systematic errors; those scans accounted for 50% of the total Season 1 data volume. Secondly, all new observations were restricted to an elevation range of 35-65 degrees, to minimize sidelobe ground pickup. On the data processing side, more effective data cleaning in both the time- and map-domain has allowed us to eliminate all data-driven power spectrum-based cuts. This increases the overall data retention and reduces the risk of signal subtraction bias. On the other hand, due to the increased sensitivity, two new pointing-correlated systematic errors have emerged, and we introduce a new map-domain PCA filter to suppress these. Subtracting only 5 out of 256 PCA modes, we find that the standard deviation of the cleaned maps decreases by 67% on large angular scales, and after applying this filter, the maps appear consistent with instrumental noise. Combining all these improvements, we find that each hour of raw Season 2 observations yields on average 3.2 times more cleaned data compared to ES analysis. Combining this with the increase in raw observational hours, the effective amount of data available for high-level analysis is a factor of 8 higher than in ES. The resulting maps have reached an uncertainty of $25$-$50\,\mu K$ per voxel, providing by far the strongest constraints on cosmological CO line emission published to date., Comment: 22 pages, 22 figures, 2 tables, v3 reflects changes made for version accepted and published by Astronomy and Astrophysics, no change to final results

Anomalous Microwave Emission (AME) is a major component of Galactic emission in the frequency band 10 to 60 GHz and is commonly modelled as rapidly rotating spinning dust grains. The photodissociation region (PDR) at the boundary of the $\lambda$-Orionis Hii region has been identified by several recent analyses as one of the brightest spinning dust emitting sources in the sky. We investigate the Barnard 30 dark cloud, a dark cloud embedded within the $\lambda$-Orionis PDR. We use total-power observations of Barnard 30 from the CO Mapping Array Project (COMAP) pathfinder instrument at 26 to 34GHz with a resolution of 4.5 arcminutes alongside existing data from Planck, WISE, IRAS, ACT, and the 1.447GHz GALFACTS survey. We use aperture photometry and template fitting to measure the spectral energy distribution of Barnard 30. We find that the spinning dust is the dominant emission component in the 26 to 34GHz range at the $7 \sigma$ level ($S_{30GHz} = 2.85\pm0.43$Jy). We find no evidence that polycyclic aromatic hydrocarbons are the preferred carrier for the spinning dust emission, suggesting that the spinning dust carriers are due to a mixed population of very small grains. Finally, we find evidence for variations in spinning dust emissivity and peak frequency within Barnard 30, and that these variations are possibly driven by changes in dust grain population and the total radiation field. Confirming the origin of the variations in the spinning dust spectrum will require both future COMAP observations at 15GHz combined with spectroscopic mid-infrared data of Barnard 30., Comment: 21 pages, 13 figures. Submitted to MNRAS

We describe standard forms for elements of the higher-dimensional Thompson groups $nV$ arising from gridding subdivision processes. These processes lead to standard normal form descriptions for elements in these groups, and sizes of these standard forms estimate the word length with respect to finite generating sets. These gridded forms lead to standard algebraic descriptions as well, with respect to the both infinite and finite generating sets for these groups., Comment: 18 pages, 6 figures