esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Ablation Study  
### Impact of Spike Convolutional Attention on Performance  
To assess the contribution of each core component in SpikeCAN, we conducted a series of ablation experiments by systematically removing or modifying individual modules. These experiments were performed on the MFPT dataset using five-fold cross-validation for the 15-class classification task, ensuring statistical robustness across evaluations.  
In our ablation study, we evaluated three modified versions of the original SpikeCAN model. The first variant, referred to as SpikeCAN with one attention module, retains only the first attention module while removing the second, allowing us to examine the marginal benefit of the second attention stage. The second variant, called SpikeCAN without attention modules, completely eliminates both SCA and STA blocks from the architecture. Finally, in the third variant, SpikeCAN without dilation, all dilated convolutions in the MDRF blocks are replaced with standard convolutions to assess the role of dilation in expanding temporal receptive fields.  
The accuracies and F1 Scores for these ablation experiments are provided in Table 5, and the corresponding confusion matrices are shown in Figure 6. The results clearly show that the full SpikeCAN model, with all modules intact, consistently achieves superior performance across all evaluation metrics. Notably, the confusion matrices reveal that the complete model maintains stable accuracy across all classes, including challenging cases such as Class 11 and Class 12. In contrast, the ablated variants exhibit increased misclassification in these classes, highlighting the effectiveness of the removed components.  
Statistical analysis revealed that removing dilation from the SpikeCAN model resulted in a significant decrease in performance, with the accuracy reduced by approximately 2.22% (t = 2.8693, \(p=0.0209\)) and the F1 Score decreased by about 0.0272 (t = 3.3938, \(p=0.0092\)), highlighting the critical role of dilation in feature extraction. When examining the impact of removing attention modules, eliminating one attention module caused a slight performance drop compared to the original model, but this decrease was not statistically significant. However, removing both attention modules led to a marginally significant decrease in accuracy (t-statistic = 2.0669, \(p=0.0719\)) and a statistically significant reduction in F1 Score (t-statistic = 3.3479, \(p=0.0099\)), demonstrating the important contribution of attention mechanisms to the model's performance.  
These findings underscore the importance of both the attention mechanism and the dilated convolutional design in achieving high classification performance. The attention modules help focus on discriminative temporal and channel-wise features, while the use of dilation expands the receptive field without increasing computational cost. Together, they enable SpikeCAN to achieve robust and accurate diagnosis in complex fault scenarios.
## 2 Carbon Nanostructures as Templates for Titania Nanomorphologies
### Nanodiamonds  
Nanodiamonds' high thermal conductivity, hardness and friction-resistance, high surface area, chemical inertness, non-toxicity, tunable structure, and excellent opto-mechanical properties have rendered them attractive building blocks in nanotechnology [183]. Nanodiamonds are typically produced by explosive detonation under oxygen-deficient conditions and consist of nanoparticles as small as 4-5 nm with a large portion of sp\({}^{3}\)-hybridized carbon atoms, in addition to sp\({}^{2}\)-hybridized atoms. A hydrothermal method at 70 \({}^{\circ}\)C was used as an easy and low-cost production method for the nucleation and growth of titania nanoparticles. Despite the limited control over the particle morphology and the presence of agglomerates, the presence of the nanodiamonds allowed for a reduced recombination rate of photogenerated charge carriers, with an improved photodegradation of bisphenol A as a model organic pollutant [102]. Similar protocols produced nanodiamonds-titania composites that were successfully tested for the photodegradation of other pollutants, thus confirming their versatility towards environmental remediation [103, 104]. Further, this kind of nanomaterial has been envisaged as an anodic component for lithium batteries, thanks to the features of nanocarbon, such as its high lithium adsorption capacity, wide surface area, and chemical inertness, as well as is overall high capacitance and the long-term cycle stability of the composites [105].
# An Accurate Direction Finding Scheme Using Virtual Antenna Array via Smartphones
## 6 Conclusions  
In this paper, we propose a novel scheme to estimate the direction of the high frequency acoustic source in indoor environments. By rotating a common smartphone around the user's body for 360\({}^{\circ}\), our system can imitate a VUCA to detect the direction of the user's destination. Compared to other direction finding schemes, our solution does not require any specialized devices or fingerprints. In addition, it is accurate and efficient. In contrast to our previous work of the VULA system, we solve the Blind-zone problem and reduce the impact of elevation angle between the acoustic source and smartphone to increase the accuracy of direction finding. In addition, the nonuniform array problem has been well addressed by using the gyroscope of the smartphone. Eventually, by getting rid of the multipath effect using the MUSIC algorithm, the extensive experiments show that our scheme works well in various indoor environments. In addition, we can optimize the algorithm of the VUCA system in order to obtain faster response speed of our system in the future. In addition, we can try to develop an indoor localization system, which is based on our direction finding technique.  
This paper is supported by National Natural Science Foundation of China under Grant No. 61572453, No. 61202404, No. 61520106007, No. 61170233, No. 61232018, Anhui Provincial Natural Science Foundation, No. 15080855 QF215.  
[PERSON] and [PERSON] conceived and designed the experiments; [PERSON] and [PERSON] performed the experiments; [PERSON] and [PERSON] analyzed the data; [PERSON] wrote the paper.  
The authors declare no conflict of interest.
## 4 Wireless Transmission in WBANs  
Compared with other wireless transmission technology, WBANs which are placed on the human body focus on realizing short-range, low-cost, low-power and low-implementation transmission; the short-range communication channels especially are quite different. Electromagnetic waves among nodes or nodes and smart terminals would pass through the human body or spread along the body's surface. The wireless nodes of WBAN require much lower power consumption than traditional sensor network nodes, generally with less than 1 mW peak power. WBAN communication distance is generally within 2 m, which is shorter than that of a general personal area network. These differences indicate that WBANs need to seek new wireless transmission schemes. Table 7 shows the main specifications for WBAN systems [69].
## Abbreviations  
3 GPP-ITE 3 rd generation partnership project long-term evolution 5G Fifth-generation AIC Active interference cancellation AWGN Additive white Gaussian noise BER Bit error rate BPSK Binary phase-shift keying CEEs Channel estimation errors CP Cyclic prefix CSMA/CA Carrier sense multiple access with collision avoidance DSL Digital subscriber line DM Direct mapping FBMC Filter bank multicarrier GFDM Generalized frequency division multiplexing GS Gold sequence IDFT Inverse discrete Fourier transform IoT Internet of Things LDPC Low-density parity-check M2M Machine-to-machine MIMO Multi-input multi-output MSE Mean square error OFDM Orthogonal frequency-division multiplexing OQAM Offset quadrature amplitude modulation OVSF Orthogonal variable spreading factor PAPR Peak-to-average power ratio PCE Perfect channel estimation QAM Quadrature amplitude modulation \(QPSK\) Quadrature phase-shift keying RB Resource block SNR Signal-to-noise ratios UAC Underwater acoustic communication UFMC universal filtered multi-carrier
## 3 The Framework of CPSS-UPTDN
### The Integration of AI and Big Data in CPSS-UPTDN  
The development of AI and big data has greatly promoted the progress of urban public transportation. Plenty of traffic control strategies and AI algorithms have developed regarding big data and the growing need for real-time traffic information in ITS [25; 26]. CPSS-UPTDN provides a novel approach to merge heterogeneous data and AI models for traffic prediction and resource dispatching.  
The integration of AI and big data is embodied for data preprocessing and artificial environment construction in the platform. For the annotated data such as cellular networks and social media, unsupervised learning (e.g., text feature extraction, clustering) is used to filter out raw data, and implement dimension reduction and extract features. The travel demand under different spatio-temporal granularity can be conducted and summarized. For traffic status estimation, prediction models based on deep learning can be leveraged. For some decision-making problems such as traffic signal and bus dispatching, schemes generated by reinforcement learning can be examined and tested in an artificial environment, which can improve the traffic capacity of the road network and service quality.
# Evaluation of 5G Positioning Based on Uplink SRS and Downlink PRS Under LOS and NLOS Environments
## 2 Methodology
### Time of Arrival Measurement  
The TOA measurements are used to determine the distance between a UE and a gNB by estimating the signal propagation time, as electromagnetic waves propagate at the constant speed of light. TOA is generally determined by generating a replica of the known prior signal and subsequently comparing it with the received signal. This method is applied to a specific segment of the sent signal to achieve precise TOA measurements. The accuracy of TOA measurements is contingent upon the synchronization between the UE and the gNB, as well as the resolution of the correlation function employed to detect  
Figure 7: Resource grid allocation of PRS at comb-6.  
the arrival time of the signal. The distance between the UE and each gNB is calculated by the following equation:  
\[d_{i}=\sqrt{\left(x-x_{i}\right)^{2}+\left(y-y_{i}\right)^{2}},i=1,2,3,\ldots,N \tag{11}\]  
when the gNB \(i\) sends a signal at a time \(T_{i}\) and the UE receives at the time \(t_{i}\) later, then it can be written as  
\[\left(t_{i}-T_{i}\right)=\frac{d_{i}}{c},i=1,2,3,\ldots,N \tag{12}\]  
The TOA measurements, represented as \(r_{  
the receiver. Then, it converts these distances into time measurements by dividing them by the speed of light \(c\).
# A Computational Study on the Aeroacoustics of a Multi-Rotor Unmanned Aerial System
## 3 Results and Discussion
### Local Flow  
#### 3.2.1 Noise Sources  
In order to identify the noise sources, contours, and iso-surfaces of time, the derivative of pressure (\(dp/dt\)) equivalent to the dilatation field is demonstrated in Figures 14 and 15, respectively. The results for CRC-3 are provided at phase angles of \(\gamma=45^{\circ},135^{\circ}\) along with the iso-surface for the isolated propeller at an arbitrary phase angle. The results correspond to the case with \(\theta=0^{\circ}\), \(\text{RPM}=6000\) and \(U_{0}=7\) m/s. The contours show that the noise mainly propagates from the propeller tips through the field, the location of which will be altered as the propellers rotate.  
Figure 13: Acoustic pressure fluctuation and sound pressure level on the fuselage: (**a**) on the nose; (**b**) on the side.  
The iso-surfaces for CRC-3 in Figure 15 at \(\gamma=45^{\circ}\) and \(\gamma=135^{\circ}\) indicate that when the blades are close to each other, the noise is maximum at the proximity location and close to the fuselage, while when the blades are far from each other, the maximum noise occurs close to the wings. Therefore, the manifestation of noise sources for CRC-3 is dependent on phase angle, which explains why there exist more peaks in the spectrum of CRC-3 compared to the isolated propeller in Figure 7. For the isolated propeller, the iso-surface shows blade and tip vortices to be noise sources, and the iso-surface is independent from the phase angle.
# Parametric Investigation of Die-Sinking EDM of Ti6 Al4V Using the Hybrid Taguchi-Rams-RATMI Method
###### Abstract  
Ti6 Al4V is a widely used alloy due to its excellent mechanical qualities and resistance to corrosion, which make it fit for automotive, aerospace, defense, and biomedical sectors. Due to its high strength and limited heat conductivity, it is difficult to machine. Both the workpiece's and the electrode's conductivity are important factors that impact the electro-discharge machining (EDM) process. In this case, the machining efficiency is also influenced by the electrode selection. As a result, choosing the right electrode and machining parameters is essential to improving EDM performance on the Ti6 Al4V alloy. Research on EDM for Ti6 Al4V is limited, with little focus on electrode material selection and shape. The impact of EDM settings on MRR, TWR, and surface roughness is complex, and a comprehensive optimization strategy is needed. Copper electrodes are widely used, but further investigation is needed on EDM's effects on Ti6 Al4V's surface properties and surface integrity. Addressing these research gaps will improve the understanding and application of EDM for Ti6 Al4V, focusing on parameter optimization, surface integrity, and thermal and mechanical effects. By employing copper tools to optimize four crucial EDM process parameters--peak current, duty cycle, discharge current, and pulse-on time--this research aims to increase surface integrity and machining performance. A comprehensive Taguchi experimental design is used to systematically alter the EDM settings. By optimizing parameters using tolerance intervals and response modelling, the recently developed Rams-RATMI approach improves the dependability of the EDM process and increases machining efficiency. With the optimized EDM settings, there were notable gains in depth of cut enhancement, surface roughness minimization, tool wear rate (TWR) reduction, and material removal rate (MRR). The results of the surface integrity examination showed fewer heat-affected zones, fewer microcracks, and a thinner recast layer. Analysis of variance was used to verify the impact and resilience of the optimized parameters. Superior machining performance, higher surface quality, and increased operational dependability were attained with the Ti6 Al4V-optimized EDM process, providing industry practitioners with insightful information and useful recommendations.  
EDM; MRR; Rams; RATMI; surface quality; Taguchi; Ti6 Al4V; tool wear rate
## 2 Materials and Methods
### Statistical Analyses  
Data were evaluated for normality using the Shapiro-Wilk test, normality being accepted at an alpha \(>\) 0.05. Given that data conformed to normality, they are presented as mean \(\pm\) SD unless otherwise stated.  
For the first objective, a two-way repeated measures ANOVA was utilised (factor A: leg (dominant vs. non-dominant); factor B: contraction type (concentric vs. eccentric)) to evaluate differences in normalised peak torques. To meet the second and third objectives, we used a two-way repeated measures ANOVA (factor A: leg (left (non-dominant) vs. right (dominant)); factor B: landing direction (diagonal inside (DI), diagonal outside (DO), lateral inside (LI), lateral outside (LO), or straight jump (SJ)) to evaluate differences in normalised peak landing force and TTS. For instances in which significant within-subject effects were present, post hoc Tukey correction was used to evaluate these differences, coupled with partial eta square (\(\eta^{2}\)p) as a measure of the standardised effect size. Spearman rank correlation was used to evaluate the association between isokinetic knee torques and TTS values, with the correlation coefficient qualitatively interpreted in absolute terms as follows: rs: 1 0.00-0.201 = negligible; 1 0.21-0.401 = weak; 1 0.41-0.601 = moderate; 1 0.61-0.801 = strong; 1 0.81-1.001 = very strong [34].  
To accomplish the fourth objective, we employed the statistical parametric mapping (SPM) equivalent of regression to evaluate the relationship between the continuous 1-D force-time curve from the force plate and the 0-D peak torque values from an isokinetic dynamometer (MATLAB, SPM1d, v. M.0.4.7). The correlation coefficients from the regression analyses were qualitatively interpreted in absolute terms as follows: r: 1 0.00-0.101 = negligible; 1 0.10-0.391 = weak; 1 0.40-0.691 = moderate; 1 0.70-0.891 = strong; 1 0.90-1.001 = very strong [35]. SPM analyses are based on random field theory, which describes the probabilistic behaviour of random curves and accounts for the smoothness of the data, which is used to set a critical threshold (\(\alpha\) = 0.05) [36; 37]. If the SPM curves exceed this critical threshold, the variable of interest (e.g., force-time curve or torque-time curve) is deemed to be significantly different at these specific time nodes.  
All statistical analyses were completed using Jamovi (Version 2.2.5.0, R 4.0) and MATLAB (R2022a, Mathworks(tm), Natick, MA, USA). Statistical significance was accepted when \(p\leq 0.05\).
# Variable Scale Pruning for Transformer Model Compression in End-to-End Speech Recognition
## 4 Adaptive Pruning
### Feedforward Layers' Adaptive Pruning  
The variable scale pruning method we propose focuses on pruning the early feedforward layers to a greater extent compared with the deeper layers. This approach involves utilizing a decreasing pruning rate (see Figure 8). Assuming that the pruning rate of the feedforward layers follows an arithmetic sequence, we define two sequences: \(U\) with parameter \(\alpha\) representing the pruning rate of the encoder layers, and \(V\) with parameter \(\beta\) representing the pruning rate of the decoder layers. When considering two consecutive layers \(n\) and \(n+1\), with \(U_{n}\) denoting the pruning rate of the current layer and \(U_{n+1}\) representing the pruning rate of the next layer, the following relationship holds:  
\[U_{n+1}=U_{n}-\alpha \tag{5}\]  
If \(n\) and \(n+1\) are decoder layers, then:  
\[V_{n+1}=V_{n}-\beta \tag{6}\]  
where \(\alpha\) and \(\beta\) are positive numbers. For the first layers of the encoder and decoder, the initial pruning rates \(U_{0}\) and \(V_{0}\) are set empirically.
## 3 Inverse Kinematics
### Closed-Form Solution for Multiple-GSJ Section  
This section illustrates the process of solving the inverse kinematics problem of the whole manipulator studied in this paper. The inverse kinematics derived in the previous section for a single-GSJ section can be iteratively applied to multiple serial GSJ sections to model an \(n\)-GSJ section manipulator. Given a list of \(\mathbf{a}_{i}^{i-1}\) (\(i=1,\cdots,n\)), the values of \(\beta_{i}\) and \(\gamma_{i}\) can be computed for each GSJ section by applying the single-GSJ inverse kinematics. The list of \(\mathbf{a}_{i}^{i-1}\) (\(i=1,\cdots,n\)) can be determined by providing a list of locations \(\mathbf{p}_{i}\) (\(i=0,\cdots,n-1\)) of GSJs \(i\) (\(i=0,\cdots,n-1\)). This section proposes a distance-based algorithm to determine the list of locations.  
Therefore, the inverse kinematics problem for multiple-GSJ section can be transformed to the determination of the \(x\), \(y\) and \(z\) coordinates \(\mathbf{p}_{i}\) of the GSJs \(i\) (\(i=0,\cdots,n-1\)) and the determination of \(\mathbf{a}_{i}^{i-1}\) based on the above GSJ coordinates. Finally, the solution of the GSJ angles is got by using the inverse kinematics of single-GSJ section. The information flow during the process of solving the inverse kinematics of the whole manipulator is shown in Figure 3.
## 4 Host-Marking Pheromones  
### Chemical Identity, Production and Analytical Approaches to Their Characterisation  
In tephritids, host-marking behaviour was first described in _R. pomonella_[374]. Later, Hafliger speculated that the biological role of this behaviour was to equally distribute the offspring in available host fruits [375]. Following these earlier observations, Prokopy and Cirio were the first that experimentally described in 1972 the HMP deposition in _R. pomonella_[112] and _R. complete_ (Cresson) [135]. Since then, the host marking behaviour has been reported in 25 tephritid species, particularly frugivorous species, belonging to the _Anastrepha_, _Ceratitis_ and _Rhagoletis_ genera [114] (Table 3; Table S3). However, it is not a general feature of the family; it seems to be common in _Rlugoletis_ spp., sporadic in _Anastrepha_ and _Cenatitis_ spp. and rather absent in others (e.g., _Bactrocera_ spp.) [29; 35; 129; 390; 391]. HMPs are low-volatility and highly polar molecules [392]. They are also soluble in water and methanol [30; 393; 394; 382; 395]. HMPs can persist on the surfaces either when they are directly deposited by the fruit flies or as extracts [108]. For instance, the HMP half-life has been estimated to 10.7 days with persisting activity for three weeks in _R. pomonella_[383], 9 days in _R. fustata_[387], 12 days in _R. cerasi_[386], 6 days in _A. suspensa_[376], 6 days in _C. capitata_[111] and 4 days in _R. indifferens_[392]. To the extent of our knowledge, HMPs are produced and stored in the posterior half of the midgut and, thus, the faecal matter contains a huge quantity of these pheromones, suggesting the existence of two main routes for HMP deposition: through ovipositor dragging after egg-lying and through defacacation [395; 396]. In _R. pomonella_, HMP accumulates in the midgut, Malplighian tubules, hindgut and faeces of mature females [395]. HMPs have been isolated from faecal matter extracts using approaches based on liquid chromatography (LC) and MS, in all four species (Table 3), namely HPLC-FAB-MS (Fast Atom Bombardment Mass Spectrometry) for _A. ludens_[382] and _R. cerasi_[30], and LC-quadrupole time-of-flight-mass spectrometry (LC-QTOF-MS) in the case of _Ceratitis_ species [390; 397]. Therefore, all the HMPs that have been chemically identified were isolated from the aqueous or methanol extract of adult female faecal matter. To date, it remains to be determined whether HMPs are produced by specific glands [395]. HMP chemical identity has been so far determined in a few tephriti species (Table 3). The first chemical characterisation of an HMP was achieved in _R. cerasi_. The pheromone was a complex molecule, i.e., N-[15(\(\beta\)-glucopyranosyl)-oxy-8-hydroxypalmitoyl]- taurine, with four stereoisomers [30], showing two chiral centres at the C-8 and C-15 positions. After the synthesis of the four different stereoisomers [398], it has been demonstrated that a racemic mixture of two isomers (8\(R\), 155 and 8\(S\), 15\(R\) isomers) is able to deter oviposition [399].