esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Related Work
### Evaluation of SQL Equivalence  
Although evaluating the equivalence of two queries plays a crucial role in advancing Text-to-SQL models, few works have addressed this challenge. [PERSON] et al. (2020) introduced Cosette, an automatic SQL solver that compiles queries over relational tables and checks their semantic equivalence, producing counterexamples when not equivalent; however, it supports limited SQL operations. [PERSON] et al. (2020) presented EQUITAS, an automated verification tool that transforms SQL queries into first-order logic to verify equivalence, although its source code is not publicly available. [PERSON] et al. (2020) proposed test-suite execution matching to measure semantic accuracy, which generates a small suite of slightly altered databases to help reduce the false positive rate of EXE. However, this approach is not scalable and suffers from the long execution times of some queries, especially when dealing with larger databases. More recently, [PERSON] et al. (2020) introduced soft and partial execution accuracy, which aimed to reduce error from ambiguous questions by allowing multiple answers to be correct. However, in doing this, it relaxes the definition of semantic equivalence, allowing for more false positives. [PERSON] et al. (2020) evaluated SQL queries using the editing difference between their abstract syntax trees (TSED), which faces challenges, as two queries can vary in structure but still be equivalent. [PERSON] et al. (2020) proposed FuncEvalGMN, which compares queries by transforming them into relational operator trees and using a graph matching network to assess functional equivalence by comparing their embeddings. However, it relies on an embedding similarity threshold for accurate results, which can struggle with subtle semantic differences and threshold tuning.  
Therefore, the most accessible and widely used automatic evaluation approaches for Text-to-SQL remain EXE and ESM (2019). Their combined evaluation script provides options to disable value and distinct checks, which were employed due to prior model limitations. However, despite the proficiency of LLM-based models in handling these aspects, the results in the literature for Spider are still reported with both value and distinct checking disabled, obscuring the true performance of LLM-based models in real-world applications. BIRD uses EXE as its primary metric, but evaluates the query output without regard to duplicate rows or ordering. Since this can lead to even more false positives, we focus primarily on the original \(\mathsf{EXE}\) metric, which has more strict output matching.
## 1 Introduction
After that, the functional correlations that existed between the PPVs and the maximum tensile stresses were determined based on the maximum tensile stress criteria. Through the utilization of relationship models, the PPV threshold of every sensitive location was determined. Many criteria exist for the analysis and prediction of tunnel damage using numerical analysis, including deflection or the deflection-span ratio by [PERSON] et al. [17], crack grades by [PERSON] et al. [18], moment-force interaction diagram by [PERSON] et al. [19], charge weight versus standoff distance diagram by [PERSON] et al. [20], and peak particle velocity (PPV) by [PERSON] and [PERSON]; [PERSON] et al. ; [PERSON] et al. ; and [PERSON] et al. [15; 21; 22; 23]. Although extensive research has been conducted to investigate the behavior of underground tunnels and their response to blast-induced vibrations, previous research has primarily focused on predicting tunnel damage based on the PPV threshold and maximum tensile strength criteria. However, in addition to the PPV, the dynamic response and damage of underground tunnels depend on the blast wave's frequency content. It is important to mention that even if the PPV falls within the acceptable limit, there may still be significant damage to nearby tunnels. This is because the damage criteria based on PPV do not take into account the impact of blast-induced stress wave frequency on the dynamic response of nearby tunnels [4]. This study has developed a three-dimensional numerical model to examine the dynamic response and damage assessment of an underground reinforced concrete tunnel subjected to blast loads of varying frequencies.
# Spinel Magnetic Iron Oxide Nanoparticles: Properties, Synthesis and Washing Methods
## 1 Introduction  
Nanomaterials and particularly nanoparticles NPs have experienced growing interest over the last three decades owing to the development of new synthesis methods and the adaptation of analysis tools with spatial resolutions below the micrometer.  
The decrease at the nanoscale intrinsically leads to the increase in the surface to volume ratio which then calls the behavior of the external atoms and the surface effects. The dimensional characteristic associated with the surface chemical state and the composition of nanoparticles leads to magnetic, optical, catalytic, and biological properties different from those of bulk materials, thus opening the way to many potential applications.  
Among the different types of nanoparticles developed in recent years (metals, metal oxides, silica, polymers, etc.), significant scientific interest has developed around superparamagnetic iron oxide nanoparticles with a spinel structure. Indeed, the magnetic properties of these nanoparticles make them prime candidates for many applications [1], including biomedical ones such as contrast agent for magnetic resonance imaging or hyperthermia and treatment of cancers [1, 2]. In this domain, for example, generally below a size of about 20 nm, these superparamagnetic nanoparticles will only be magnetized under the effect of an external magnetic field. Moreover, the absence of attractive magnetic forces between the NPs will promote their stability in suspension by limiting their tendency to agglomeration and aggregation. However, surface functionalization of iron oxide nanoparticles may be necessary to improve the dispersion and stability of suspended nanoparticles.  
In this review, the crystal structures and magnetic properties of spinel-structured iron oxide nanoparticles will be presented. Then, the main methods of synthesis and washing of these nanoparticles will be discussed. Finally, the stabilization of iron oxide nanoparticles in solution will be discussed considering the experience of our team in the synthesis of iron oxide nanoparticles.
## 3 Results
### Biomarker Concentrations and Correlation Analysis
Biomarker concentrations of all investigated parameters correlated with CRP and serum creatinine (CRP: sST2: rs = 0.438, \(p<0.0001\), suPAR: rs = 0.461, \(p<0.0001\), GDF-15: rs = 0.443, \(p<0.0001\), H-FABP: rs = 0.256, \(p<0.0001\); creatinine: sST2: rs = 0.336, \(p<0.0001\), suPAR: rs = 0.395, \(p<0.0001\), GDF-15: rs = 0.378, \(p<0.0001\), H-FABP: rs = 0.308, \(p<0.0001\)), whereas only GDF-15 correlated with age (rs = 0.194, \(p=0.001\)) (see Table 3). Figure 1: Biomarker concentrations in the three investigated disease entities vs. controls. * indicates a \(p\) of \(<\)0.05, ** a \(p\) of \(<\)0.01 and *** a \(p\) of \(<\)0.001, rs = not significant. \begin{table}
\begin{tabular}{l c c c c c c c} \hline  & **Total Cohort** & **Heart Failure** & **STEMM** & **Seguis** & **Control** & \(p\)**-Value** \\ \hline s**ST2 (pg/ml; median (IQR))** & 860.75 (5033.5-1714.0) & 8818.3 (5683.1-11217.4) & 13,2120.9 (8469.9-23,113.5) & 38,701.9 (21,8345.5-53,509.3) & 5209.9 (4242.9-4650.2) & -0.0001 \\ \hline s**VAR (pg/ml; median (IQR))** & 3459.6 (2394.4-5303.7) & 3596.6 (2454.3-4897.3) & 3461.2 (2282.2-5091.0) & 8053.4 (6297.6-12,597.0) & 2513.0 (1975.2-2054.6) & -0.0001 \\ \hline CDP-13 (pg/ml; median (IQR)) & 711.2 (4892.1-1495.5) & 667.8 (420.5-1002.4) & 8413.6 (644.1-1264.7) & 3455.9 (2545.4-4976.6) & 531.9 (978.7-206.2) & -0.0001 \\ \hline H-FARP (ng/ml; median (IQR)) & 2.25 (0.00-6.84) & 1.90 (0.99-3.26) & 6.44 (2.69-13.99) & 15.28 (4.40-01.13) & 0.00 (0.00-0.00) & -0.0001 \\ \hline \end{tabular}
\end{table} 
Table 2: Biomarker concentrations of the total cohort, divided by disease entity. Abbreviations: IQR = interquartile range. \begin{table}
\begin{tabular}{l l c c c c c c} \hline  & **Age (Years)** & **BMI (kg/m\({}^{3}\))** & **EF** & **CFP (mg/L)** & **Creatinine (sum/L)** & **Urea (mm/L)** \\ \hline s**ST2 (pg/ml)** & **rs** & 0.038 & \(-\)0.019 & \(-\)0.306 & 0.438 & 0.336 & 0.329 \\  & **p-value** & 0.525 & 0.748 & \(<\)0.001 & \(<\)0.001 & \(<\)0.0001 & \(<\)0.0001 \\  & **rs** & 0.104 & \(-\)0.090 & \(-
# Performance Analysis of a 3D Wireless Massively Parallel Computer
## 1 Introduction
### Packet-Switching
#### 1.2.1 Store-and-Forward  
Store-and-forward algorithms are based on the idea of relaying a message only after receiving all of it in an intermediate node. Such algorithms are easy to implement but on the negative side, the intermediate nodes leave the output channel unused until the whole package is received, which loses considerable time. In this method, the overall multi-hop transfer time relates to the number of hops, which in turn is relevant to the software and hardware latencies. This is a significant issue in direct networks.
## 3 Results
### Electrical Characterization
In order to statistically characterize the electrical performance of fabricated devices on PET and ultra-thin Parylene C films, basic electrical parameters were extrapolated by transfer characteristic curves; average and 1-\(\sigma\) confidence band values for these parameters are reported in Table 1. Devices fabricated on both PET and Parylene C substrates are in enhancement mode, with a negative threshold voltage in the range of 0 V (\(-0.1\)\(\pm\) 0.16 V on PET, 0 \(\pm\) 0.1 V on Parylene C). On PET, an average charge carrier mobility of 0.25 cm\({}^{2}\)V\({}^{-1}\)s\({}^{-1}\) was obtained, which is a remarkable value for a non-purified TIPS pentacene solution deposited by inkjet printing. The subthreshold slope is about 130 mVdec\({}^{-1}\), a significant value for low-voltage OFETs, demonstrating one more time that the insulator/semiconductor interface is almost ideal. Indeed, this parameter is related to the maximum surface trap concentration by the well-known relationship [39]  
\[N_{SS}^{max}\ =\ \frac{C_{INS}}{q}\bigg{[}\frac{SS\log_{10}e}{k_{B}T/q}\bigg{]} \tag{1}\]  
where \(C_{INS}\) is the capacitance per area unit of the insulator, \(q\) the elementary charge, \(SS\) the subthreshold slope, and T the absolute temperature. Using this equation, a maximum surface trap states concentration of \(1.3\times 10^{11}\) cm\({}^{-2}\) eV\({}^{-1}\) can be obtained, which is comparable to or lower than the ones for low-voltage structures with a much higher gate capacitance. As previously discussed, a slight reduction in charge carrier mobility was observed on ultra-thin substrates (\(0.13\pm 0.04\) cm\({}^{2}\) V\({}^{-1}\) s\({}^{-1}\)); at the same time, a slight increase in subthreshold slope (i.e., an increase of \(N_{SS}\)\({}^{max}\)) was recorded, as a further demonstration of a sensible worsening of the insulator/semiconductor interface. It is worth noting that these values  
Figure 2: Typical output (**a**) and transfer characteristic curves (**b**) of OFETs fabricated over 175 \(\upmu\)m-thick PET substrates; typical output (**c**) and transfer characteristic curves (**d**) of OFETs fabricated over 700 nm-thick Parylene C substrates. remain valuable for a low-voltage, all-organic device. For both structures, the average leakage current is in the range of 100 pA.
# Post-Quantum Digital Signature: Verkle-Based HORST
## 6 Merkle Signature Scheme (MSS)
By employing a more adaptable tree structure and lowering the overhead associated with state management, XMSS increases efficiency and scalability. It presents cutting-edge methods to maximize key generation and signing, such as WOTS+ and L-trees. For instance, the Merkle tree effectively authenticates the compressed hash value created by compressing huge one-time signature (OTS) public keys using L-trees. This makes XMSS more feasible for real-world applications by lowering the computational and storage overhead. As part of its post-quantum cryptography portfolio, NIST has also standardized XMSS. SPHINCS+ is a stateless version of MSS that is more useful for real-world applications as it does not need to track the utilized OTS keys. It achieves statelessness while preserving security by utilizing a hyper-tree topology and a few-times signature (FTS) mechanism. SPHINCS+ is regarded as one of the best candidates for post-quantum safe digital signatures and is also a member of the NIST Post-Quantum Cryptography Standardization Project. In the post-quantum age, developments in MSS have enhanced the security of digital signatures, making them appropriate for use in secure communication protocols, blockchain technology, and digital certificates. Because Verkle trees are more efficient at creating and verifying proofs than regular Merkle trees, they are being employed in blockchain systems more and more. These trees are a major advance over Merkle trees in contemporary, high-performance systems because they allow for smaller proof sizes and lower computational overhead, which increases scalability and supports lightweight clients.
# DNS over HTTPS Tunneling Detection System Based on Selected Features via Ant Colony Optimization
###### Abstract  
DNS over HTTPS (DoH) is an advanced version of the traditional DNS protocol that prevents eavesdropping and man-in-the-middle attacks by encrypting queries and responses. However, it introduces new challenges such as encrypted traffic communication, masking malicious activity, tunneling attacks, and complicating intrusion detection system (IDS) packet inspection. In contrast, unencrypted packets in the traditional Non-DoH version remain vulnerable to eavesdropping, privacy breaches, and spoofing. To address these challenges, an optimized dual-path feature selection approach is designed to select the most efficient packet features for binary class (DoH-Normal, DoH-Malicious) and multiclass (Non-DoH, DoH-Normal, DoH-Malicious) classification. Ant Colony Optimization (ACO) is integrated with machine learning algorithms such as XGBoost, K-Nearest Neighbors (KNN), Random Forest (RF), and Convolutional Neural Networks (CNNs) using CIRA-CIC-DoHBrw-2020 as the benchmark dataset. Experimental results show that the proposed model selects the most effective features for both scenarios, achieving the highest detection and outperforming previous studies in IDS. The highest accuracy obtained for binary and multiclass classifications was 0.9999 and 0.9955, respectively. The optimized feature set contributed significantly to reducing computational costs and processing time across all utilized classifiers. The results provide a robust, fast, and accurate solution to challenges associated with encrypted DNS packets.  
Keywords: intrusion detection system; DNS over HTTPS; ant colony optimization; feature selection; dimensionality reduction; machine learning +
Footnote †: journal:  
_Article_
# Enhanced Gain Difference Power Allocation for NOMA-Based Visible Light Communications
## 1 Introduction
In [22], the nonlinear marine predator algorithm was applied to solve the fair power allocation problem, optimizing the sum rate efficiently and allowing for quick convergence. By utilizing the derived lower bound of the achievable rate and semidefinite relaxation technology, optimal power allocation schemes for static and mobile users were derived in [24]. However, the negative impact of residual user interference on system performance during SIC implementation has not been fully considered in the above literature. In [25], adjustable superposition coding and SIC decoding schemes were proposed to alleviate the influence of error propagation by adjusting the relative bit rate of each user. A convolutional neural network-based demodulator for NOMA-VLC was presented in [26], aiming to achieve joint signal compensation and recovery. The experimental results demonstrated that this receiver exhibited improved robustness against linear and non-linear distortions compared to receivers using SIC and joint detection. A modified SIC decoder was proposed to improve the symbol error rate performance of the three-user uplink/downlink NOMA by assuming channel gains, and the joint influence of the SNR and channel gains on the symbol error rate was also analyzed in [27]. Based on the above analysis, we can see that most existing works have focused primarily on designing signal detection algorithms at the receiver to improve error performance. However, the residual interference is not well mitigated, which may lead to significant performance degradation in the achievable data rate and BER performance. In this paper, a new multi-user power allocation scheme named enhanced gain difference power allocation (EGDPA) is proposed to mitigate the adverse effect of residual interference and then improve the achievable data rate and detection performance. The allocation factors are determined by considering users' channel gains and utilizing the residual allocation principle, which focuses on the remaining power available after allocating to the previous user rather than the initially assigned power. Moreover, the corresponding achievable data rate, energy efficiency, and error probability are analyzed to characterize the impact of power allocation factors on NOMA design. Simulation results show that the proposed scheme can provide a satisfactory sum rate, energy efficiency, and error performance compared with the OMA scheme or traditional NOMA power allocation strategies, which validates the effectiveness of the proposed scheme. The rest of this paper is organized as follows. In Section 2, the system model for MIMO-NOMA-VLC is presented. In Section 3, the EGDPA scheme is proposed. The system sum achievable data rate, energy efficiency, and error probability are also evaluated in Section 3. Simulation results are included in Section 4, followed by conclusions summarized in Section 5.
# Full-Duplex MAC Protocol for CSMA/CA-Based Single-Hop Wireless Networks
## 3 Proposed FD MAC Protocol
### Modeling and Analyzing the Performance of the Proposed Protocol
The probability (denoted by \(P_{col(FD)}\)) is as follows:  
\[P_{col(FD)}=1-P_{idle}-P_{ggl}-P_{dbl}. \tag{22}\]  
Given that the collisions only waste the transmission time of a frame's header, the channel access time occupied by this case (denoted by \(T_{col(FD)}\)) is as follows:  
\[T_{col(FD)}=\text{DIFS}+T_{Hdr}. \tag{23}\]Furthermore, the average length of the time interval can be obtained as follows:  
\[T_{ave}\ =\ P_{iitle}\sigma+P_{col(FD)}T_{col(FD)}+P_{sgl}T_{sgl}+P_{bi}T_{bi}+P_{ non-bi}T_{non-bi}. \tag{24}\]  
Moreover, the total number of the transmitted bits in a time interval can be obtained as follows:  
\[L_{tol}\ =\ 2\times\Big{(}P_{sgl}+P_{dbi}\Big{)}\Big{(}L_{Hdr}+L_{Psi}\Big{)}. \tag{25}\]  
Note that the length of the whole frame is considered in the solution of \(L_{tol}\). The subsequent numerical simulations for \(Th_{HD(Basic)}\) and \(Th_{HD(RTS)}\) are also based on this criterion. Finally, the system normalized throughput can be obtained as follows:  
\[Th_{FD}\ =\ \frac{L_{tol}}{T_{ave}}. \tag{26}\]  
Note that we focused on the system throughput that could be achieved under the saturated flow. This performance metric can be directly converted to the transmission delay.
## 5 Results  
### Theoretical Evaluation of Proposed Lattices  
The SIMP method predicts an optimal material distribution within a given design space. The other structure characteristics such as anisotropy are not easily integrated into general Topological Optimization algorithms. Respectively, the avoidance of fatigue or buckling effects in microstructures produced with Topology Optimization cannot be guaranteed. Therefore, the homogenization of the topology optimized structures is an appropriated step. An exception is auxetic microstructures, where Topology Optimization is used to design compliant microstructures so that the desired flexibility leads macroscopically to auxetic behavior [36].  
A key parameter to understand lattice behavior is the relative density (\(\overline{\rho}\)). As relative density is defined as the density ratio of the lattice material to the solid material (\(\overline{\rho}=\rho^{*}\) /\(\rho_{s}\)), if a lattice has high porosity, then the value of the relative density is low; otherwise, a high value of that indicates a low porosity [32]. The relative density increases for the higher volume fraction. In Figure 12, the relative density of the proposed lattices against the volume fraction is presented. The homogenized domain of structure #2 showed similar trends as structure #1; however, the slope is lower. The lower the slope is, the larger the amount of material that can be added for a given relative density (Figure 8). In Figure 13, Maximum Young's modulus for different relative density values is presented. Structure #2 seems to have better performance in comparison to structure #1 with the use of a lower amount of material.  
In the current study, a general homogenization method is utilized to evaluate and characterize the results of the above proposed structures. Specifically, the anisotropy of the proposed structures through the measure of the maximum Young's modulus (E\({}_{\text{max}}\)) and local minimum Young's modulus (E\({}_{\text{min}}\)) is checked (Figure 13). According to Tancogne Dejean, a measure of the anisotropy of the lattice structure is derived from E\({}_{\text{max}}\)/E\({}_{\text{min}}\)[37].
# Explainability and Interpretability in Concept and Data Drift: A Systematic Literature Review
## 6 Taxonomy
### Prototype/Medoid and Exemplar Tracking
#### 6.9.3 Multidimensional Class Evaluation  
As visible from Table 26, this class predominantly addresses gradual and incremental concept drift, with a single occurrence of recurrent drift. This selection highlights the suitability of exemplar-based methods in detecting and visually explaining gradual transitions through explicit shifts or replacements of representative cases. The application contexts identified span financial analysis, image classification, IoT, network traffic, and healthcare, underscoring the versatility of prototype-based techniques across structured and visual data domains. Financial and IoT contexts particularly illustrate how exemplar tracking facilitates clear and concrete interpretability when domains exhibit incremental or subtle changes. In terms of scope, explanations provided are consistently global, indicating that these approaches inherently offer overarching insights through exemplar changes rather than fine-grained instance-level interpretability. This global perspective naturally emerges from visually comparing exemplars as they evolve or shift over time. The intended audience includes both end-users and data scientists, with a slight preference for data scientists. The direct visual representation of drift through exemplar comparisons also makes these methods accessible to domain experts, simplifying communication of shifts. Explicit interpretability-related metrics appear minimally, with only Intersection over Union (IoU) mentioned. This limited quantification suggests that interpretability arises mainly through visual inspection and direct exemplar comparison rather than standardized metrics. Regarding the learning mode, the presence of hybrid, offline, and online approaches highlights the adaptability of exemplar methods across various operational and analytical scenarios, accommodating both real-time monitoring and retrospective analysis.