esa-sceva/satcom-chunk-collection huggingface dataset:
# Compaction of Church Numerals
## 2 Preliminaries
### Lambda Terms  
**Definition 3** (Lambda terms (\(\lambda\)-terms)).: _Let \(x\) be a variable. Then, lambda term (\(\lambda\)-term) \(M\) is defined inductively as follows:_  
\[M::=x\mid\lambda x.M\mid M_{1}\ M_{2}.\]  
We call \(\lambda\)-terms formed \(\lambda x.M\) and \(M_{1}\ M_{2}\)\(\lambda\)_-abstraction_ and _functional application_, respectively. Let \(V_{1}\) and \(V_{2}\) be the sets of the variables occurring in \(M_{1}\) and \(M_{2}\), respectively, then, we identify \(M_{1}\) with \(M_{2}\) if there is an isomorphism from \(V_{1}\) to \(V_{2}\). \(M[x_{1}:=M_{1},x_{2}:=M_{2},\dots]\) denotes the \(\lambda\)-term such that all occurrences of \(x_{1},x_{2},\dots\) in \(M\) are replaced by \(M_{1},M_{2},\dots\), respectively.  
We show in parentheses \"(\" and \")\" the precedence of combining \(\lambda\)-terms. However, for simplicity, we omit these parentheses based on standard omission rules, that is, we consider that functional applications are left-associative and prior to \(\lambda\)-abstractions. For example, we consider \(M_{1}\ M_{2}\ M_{3}\) as \((M_{1}\ M_{2})\ M_{3}\) rather than \(M_{1}\ (M_{2}\ M_{3})\), and consider \(\lambda x.M_{1}M_{2}\) as \(\lambda x.(M_{1}\ M_{2})\) rather than \((\lambda x.M_{1})\ M_{2}\).  
**Definition 4** (\(\beta\)-reduction).: _Let \(x\) be a variable, and \(M_{1}\) and \(M_{2}\) be \(\lambda\)-terms. Then, \(\beta\)-reduction is a relation of \(\lambda\)-terms, denoted by using \(\longrightarrow_{\beta}\), such that \((\lambda x.M_{1})\ M_{2}\longrightarrow_{\beta}M_{1}[x:=M_{2}]\). We write \(\longrightarrow_{\beta}^{*}\) for the reflexive transitive closure of \(\longrightarrow_{\beta}\)._  
For example, \((\lambda x.M_{1}\ x)\ M_{2}\longrightarrow_{\beta}M_{1}\ M_{2}\ M_{2}\) because the right-side of \(\longrightarrow_{\beta}\) is \((M_{1}\ x\ x)[x :=M_{2}]\). Similarly, \((\lambda x.\lambda y.x\ y\ y)\ M_{1}\ M_{2}\longrightarrow_{\beta}^{*}M_{1} \ M_{2}\ M_{2}\) because \((\lambda x.\lambda y.x\ y\ y)\ M_{1}\ M_{2}\longrightarrow_{\beta}(\lambda y.M_{1 }\ y\ y)\ M_{2}\longrightarrow_{\beta}M_{1}\ M_{2}\ M_{2}\).  
We define the sizes of \(\lambda\)-terms as follows. The definition can be found in [1].  
**Definition 5** (Sizes of \(\lambda\)-terms).: _Let \(x\) be a variable and \(M\) be a \(\lambda\)-term. Then, we denote the size of the \(\lambda\)-term by \(\#M\), and inductively define the size of each \(\lambda\)-term as follows:_  
\[\#x=1,\ \ \#(\lambda x.M)=\#M+1,\ \ \#(M_{1}\ M_{2})=\#M_{1}+\#M_{2}+1.\]For \(\lambda\)-terms \(M_{1}\) and \(M_{2}\), we say that \(M_{2}\) is more _compact_ than \(M_{1}\) if \(\#M_{2}<\#M_{1}\). _Compaction_ of a \(\lambda\)-term \(M_{1}\) means to find a \(\lambda\)-term \(M_{2}\) such that \(M_{1}\)\(N\longrightarrow_{\beta}^{*}M^{\prime}\) and \(M_{2}\)\(N\longrightarrow_{\beta}^{*}M^{\prime}\) for every \(N\) with a \(\lambda\)-term \(M^{\prime}\), and \(\#M_{2}<\#M_{1}\).  
In this paper, we assume Word RAM as the computational model. Thus, we ignore the size of names and pointers when we discuss size and space.
# Distributed Joint Source-Channel Coding Using Quasi-Uniform Systematic Polar Codes
###### Abstract  
This paper proposes a distributed joint source-channel coding (DJSCC) scheme using polar-like codes. In the proposed scheme, each distributed source encodes source message with a quasi-uniform systematic polar code (QSPC) or a punctured QSPC, and only transmits parity bits over its independent channel. These systematic codes play the role of both source compression and error protection. For the infinite code-length, we show that the proposed scheme approaches the information-theoretical limit by the technique of joint source-channel polarization with side information. For the finite code-length, the simulation results verify that the proposed scheme outperforms the distributed separate source-channel coding (DSSCC) scheme using polar codes and the DJSCC scheme using classic systematic polar codes.  
correlated sources; noisy independent channels; distributed joint source-channel coding; quasi-uniform systematic polar codes +
Footnote †: journal:  
_Article_  
Distributed Joint Source-Channel Coding Using Quasi-Uniform Systematic Polar Codes
This implementation is meant to reduce the uncertainty in the evaluation of the horizontal wind speeds, especially for situations in which the inclination between the wind direction and the line-of-sight direction of the radial wind speed measurement of one lidar is close to \(90^{\circ}\). The application of MuLiWEA does not require a set of fully synchronised dual-Doppler lidar measurements because it performs grid interpolation. This feature offers the possibility to use measurements from scanning scenarios with low complexity and fast area coverage. We applied MuLiWEA to dual-Doppler lidar measurements simulated in the wake of a wind turbine, considering a series of different scanning scenarios, and compared the reconstructed wind fields to the simulated ones. Additionally, we analysed a test case based on real dual-Doppler lidar measurements offshore.
## 4 Result and Analysis
### SISRE and Orbit-Only SISRE
accuracy is not as obvious as the orbit, the mean RMS and STD of BDS-3 are improved by (71.91%, 65.00%) for SISRE and (90.12%, 88.24%) for orbit-only SISRE compared to BDS-2, respectively. .Due to the inconsistency of the datum of broadcast clock offsets between BDS-2 and BDS-3, BDS-2 and BDS-3 cannot solve SISRE together. The SISRE processing strategies of calculating SISRE of BDS-2 and BDS-3 separately achieve or even exceed the SISRE accuracy corrected by TGD bias [12]. Without additional bias correction, the SISRE processing strategies of calculating SISRE of BDS-2 and BDS-3 separately can more scientifically and accurately reflect the accuracy of the current broadcast ephemeris of BDS-2 and BDS-3. Figure 11: Signal-in-space-range errors of BDS-2 and BDS-3 broadcast ephemeris from DOY 089 to 123, 2020. Figure 12: The orbit-only signal-in-space-range errors of BDS-2 and BDS-3 broadcast ephemeris from DOY 089 to 123, 2020.
# Coverage, Rate, and Last Hop Selection in Multi-Hop Communications in Highway Scenarios
## 4 Numerical Results
### Path Usage  
Having multiple relatively strong propagation paths is a useful property of the vehicular environment. We now proceed to assess the usage of these paths. To this aim, Figure 10 shows the path usage probability as a function of the hop distance for two considered strategies, \"best quality\" and \"MCS = 3\". Here, we see that, for MCS = 3, the LoS path is almost exclusively utilized at all distances. The contribution of the reflected path is insignificant and never reaches even 0.1. In the case of \"best quality\" strategies, shorter links on average are utilized, and they are also dominated by the LoS propagation. Thus, we may conclude that LoS propagation is still the dominant communications way even in vehicular environments.
## 3 Results and Discussion
### PST Removal from Bivalves
#### 3.3.2 Depuration with H-Form and Na+-Form Resins
Therefore, we think that the H-form resin, under the conditions in which it was prepared, may not be the most suitable matrix for in vivo studies involving bivalves. Aiming to overcome the acidification observed previously, the resin was modified by converting the H-form into the corresponding Na\({}^{+}\)-form. First, in a parallel experiment to the one described above, two additional conditions were tested: (4) Na\({}^{+}\)-resin (Control (2) and (5) Na\({}^{+}\)-resin with two mussels (Na\({}^{+}\) + M) (Figure S6). When using the Na\({}^{+}\)-form resin, after introducing the resin to the tank with shellfish the pH remained steady, ranging between 7.83 and 7.98. Moreover, the pH of the container including solely Na\({}^{+}\)-resin ranged from 7.85 to 8.03 (Figure 9), meaning that the Na\({}^{+}\)-form resin did not affect the pH of the saltwater during the in vivo testing. These observations indicate that the sodium form of the resin is less hazardous to shellfish and probably less prone to interact with the ecological environment. Accordingly, we proceeded with the depruation experiments using the Na\({}^{+}\)-form resin. Although we observed a significant difference in the first 24 h (again due to decreasing dcSTX concentration), the acceleration observed in the presence of resin is very small compared to that verified without resin. In fact, after 48 h no significant differences were observed, indicating that, despite cancelling the effect of pH using the Na\({}^{+}\)-form resin, the clearance rate did not seem to improve. As previously explained, the adsorption mechanisms in natural waters are strongly affected by the conditions and  
Figure 9: pH effect upon addition of the different resins, and respective controls. constituents of the medium, which decreases the effectiveness of the method. These factors, allied to the mussels' apparent inability to filter the resin, assume a dominating role that prevails over the cation exchange theory that is successfully applied in the treatment of purest water.
## 4 Multicast Routing Approaches in DTN
### Discussion
All the IoT sensor data in the delay tolerant WSN are gathered and delivered to the cloud for further analysis. [PERSON] et al. [66] proposed an energy efficient packet transmission policy that selects energy efficient wireless networks to reduce energy consumption in the disruption-tolerant IoT network with heterogeneous resources. We believe that energy efficiency algorithms not only enhance multicasting services and delivery success rate but also provide more reliable transmission.
# How Different Fermentation Type Affects Volatile Composition of Plum Jerkums
## 3 Results and Discussion
### Volatile Compounds of Fresh Plum Musts  
Qualitative and quantitative composition of volatiles of plums is very diverse and statistically significantly varies among cultivars. More than 50 volatiles were identified in plum musts of which esters were the dominant group. Among them, ethyl acetate, ethyl butanoate, butyl butanoate, and ethyl decanoate were the most abundant (Table 4). Those esters (except butyl butanoate) were also present in fermented plum musts. Esters contribute to floral and fruity aroma notes in fruit and those esters have sweet, pineapple, banana, and nut-like aroma, respectively [24; 25]. Some of those compounds were characteristic for particular cultivars, e.g., butyl butanoate for Wegierka Zwykla, hexnoate for Wegierka Zwykla and Stanley, ethyl tridecanoate for Wegierka Dabrowicka and Cacanska Lepotica. Due to numerous transformations of volatile compounds during fermentation, we could not assign specific esters to plum jerkums obtained from particular cultivars. However, we observed that samples fermented with _S. cerevisiae_ S1 or _H. warrant_ H2 demonstrated the highest concentration of esters, followed by spontaneous fermentation and musts fermented with Ethanol RED (four times lower concentration, e.g., methyl hexanoate, isoamyl lactate). Differences in the concentration of esters are associated with the fact that esters are produced during fermentation by yeast cells in an enzyme-catalyzed intracellular reaction [26]. Generally, _H. warrant_ is known as a good ester producer and it increases formation of some acetate esters. According to the literature, _H. warrant_ were able to produce ethyl acetate, geranyl acetate, and isoamyl acetate in model solution (GPYM--glucose, peptone, yeast extract, malt extract medium) [27]. Combined cultures of _Hanseniaspora_ spp. and _S. cerevisiae_ increased the formation of esters and improved sensory properties of wines [28]. It is worth mentioning that in the current study, the samples fermented with _S. cerevisiae_ S1 demonstrated the highest concentration of isoamyl lactate. This could be related to the higher concentration of lactic acid in samples fermented with this type of yeast, which probably resulted from spontaneous malolactic fermentation.
# A New Method for Large-Scale Landslide Classification from Satellite Radar
## 4 Discussion
### The Maximum Detectable Landslide Size  
The size of the search window used by RapidSAR for sibling identification is likely to set an upper limit on the maximum size of a landslide that can be detected using the Bx-S method. The method relies on a sibling-based coherence estimate using proportionally fewer landslide pixels in the summation than the boxcar estimation (Equation (1)). We make the assumption that siblings of a given pixel will generally be distributed widely throughout the search window and will not be clustered around it as immediate neighbours. However, for a pixel located at the centre of a landslide that is larger than the RapidSAR window, both of the ensembles of pixels used by the boxcar and sibling-based coherence estimates will lie entirely within the landslide. Both estimates of coherence therefore yield a low value and the difference between them will be small, leading to a false negative. This effect will decrease towards the edges of the landslide.  
The largest landslide included in the [PERSON] et al. [2] inventory is the Langtang Valley landslide (Figure 8), which has an area around 1.7 km\({}^{2}\). Here we used a 41 \(\times\) 41-pixel window, equivalent to an area around 270,000 m\({}^{2}\). In radar coordinates, the Langtang Valley landslide is 221 pixels in length  
Figure 11: Histogram of landslide areas derived from the inventory of [2]. Landslides over 20,000 m\({}^{2}\) in area are omitted for clarity. The sizes of an individual pixel (red) and of the window used in calculation of the boxcar coherence (blue) are marked.  
but has a mean width of just 30 pixels. At its widest point, it is 58 pixels wide. In the centre of the Langtang Valley landslide, we therefore expect to approach the point where both coherence estimates are very low. Therefore, although decreasing the size of the search window decreased computation time, we did not use a smaller 21 \(\times\) 21 window in this study. In future studies, where the maximum landslide size is unknown, it will be necessary to increase the size of the RapidSAR search window in order to ensure that large landslides are not masked.
# Observations on the Computation of Eigenvalue and Eigenvector Jacobians +
## 9 Conclusions  
A new formulation is derived for the complete Jacobians of eigenvalues and eigenvectors with respect to the elements of their parent matrix. The new solution relies on only the eigenvalue and eigenvector being considered and is valid for any unitary complex eigenvalue/eigenvector pair. Furthermore, the parent matrix may contain complex entries and need not be symmetric. As a result, the method presented here is extremely general with applications to finite-element analysis (FEA) solutions to vibration problems, fitting of an ellipse to scattered data points, quaternion-based attitude estimation, and a host of other important scientific and engineering problems.  
The new eigenvalue and eigenvector Jacobians developed in this manuscript are shown to collapse to well-known results if the parent matrix is either (1) real and symmetric or (2) real and diagonal. This new method may also be reinterpreted to gain a deeper understanding of perturbations of the eigenspace.  
Finally, the new eigenvalue and eigenvector Jacobians are validated by comparison with forward finite differencing. The computational performance speed of this new technique was shown to be better by a factor of 10 (or greater for large matrices) when compared with the performance of the technique proposed in [39].  
A.J.L.: Writing--Original Draft Preparation, Writing--Review and Editing, Formal Analysis, Conceptualization, Software, Methodology, Investigation. J.A.C.: Writing--Original Draft Preparation, Writing--Review and Editing, Formal Analysis, Conceptualization, Supervision, Project Administration. S.B.R.: Writing--Original Draft Preparation, Writing--Review and Editing, Formal Analysis, Conceptualization.  
**Funding:** A portion of this work was made possible by NASA under award NNX13 AJ25A.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
Figure 4: A plot of minimum computation time versus matrix size for the method from [39] (original method) and the method proposed in this paper (new method). Note that the method from [39] encounters numerical stability issues around a matrix size of 35 due to Equation (29). This is why there is a cut-off in the data.
# ForecastNet Wind Power Prediction Based on Spatio-Temporal Distribution
## 2 Materials and Methods
### Wind Power Prediction Model
#### 2.2.3 ForecastNet Model
In this paper, the ForecastNet model is used as the basis for wind power spatio-temporal distribution prediction research by using a MLP, CNN, and the dense network based on the attention mechanism in its hidden layer. Each output in the output layer is a prediction result, and a linear output can be used to obtain a deterministic prediction result, or a Gaussian mixture density can be used to establish a probability density output.
## 2 Materials and Methods
### Training Strategy and Transfer Pipeline  
In this study, we designed a comprehensive experimental workflow to validate the effectiveness, efficiency, and generalization ability of the proposed LKF-DCANet. The entire pipeline consists of three main stages: supervised pre-training on a large-scale satellite dataset, knowledge distillation for lightweight optimization, and cross-domain transfer learning on UAV imagery.  
We first trained both the deep network and the lightweight LKF-DCANet on the publicly available GLH-water dataset [44]. The deep network adopts a U-shaped structure with MobileNetV2 as the backbone and integrates an LKF module in the decoder. The lightweight network utilizes a shallower encoder built with CADCN and a decoder that incorporates both the CATM and LKF modules.  
Figure 8: Feature distillation structure between LKF-DCANet and the deep network via multi-level MSE loss.  
To improve the segmentation performance of the lightweight model while maintaining computational efficiency, we adopted a feature-based knowledge distillation strategy. During training, the deep network provided intermediate feature representations, which the lightweight network learned to align at multiple layers via a Mean Squared Error (MSE) loss. This strategy enabled the lightweight model to inherit the discriminative capabilities of the deeper architecture, significantly enhancing segmentation accuracy.  
To assess cross-domain generalization, we transferred the pre-trained lightweight model to a self-constructed UAV dataset collected from the Dongfengqu Irrigation District in Sichuan, China. We fine-tuned the model using only 10% of the labeled images. After adaptation, the model was employed to infer the remaining 90% of the unlabeled data, generating pseudo-labels for evaluation. The complete workflow of pretraining, distillation, fine-tuning, and pseudo-labeling is illustrated in Figure 9.
# Evaluation of Emotional Satisfaction Using Questionnaires in Voice-Based Human-AI Interaction
## 4 Discussion
### Integration of Kansei Engineering Approach and Biosignals  
In this study, evaluation was conducted through a questionnaire using the Kansei engineering approach. The Kansei engineering approach has the advantage of being able to identify various sensibilities and easy classifications. However, since the questionnaire is conducted based on the perceived sensibility that occurs after the interaction, the truth of the user's emotional expression may be distorted. In addition, the evaluation method in the form of a questionnaire has a major disadvantage in that it cannot be evaluated in real time during HAII, which is an obstacle for constructing adaptive interaction in real time. To overcome these disadvantages, efforts should be made to overcome the limitations of the survey method presented in this study. In recent years, many studies using biosignals or facial expressions have been conducted to evaluate emotions. Electroencephalography is used to check real-time emotional changes [38], and it is possible to evaluate integrated emotions using multiple biosignals, such as photoplethysmography or electrocardiograms [39]. However, because most studies do not have a standard for evaluating emotions using biosignals, they display it using pictures or photos that can induce emotions, and infer the emotion based on the changes in biosignals that occur accordingly [40; 41]. It is believed that in the future, it will be extremely important to collect real-time biodata in an interaction situation and analyze the emotional changes in terms of \"pleasurability\" and \"reliability\" using biosignals in this research environment. Therefore, in future research, a framework that integrates biosignals and Kansei engineering data should be created to evaluate the user's emotional satisfaction, and the questionnaire data using the Kansei engineering approach are used as supervised learning labels for biosignal data. It is expected that HAII will be able to evaluate real-time user emotional satisfaction. This can lay an important foundation for evaluating a user's emotional satisfaction during interaction with various intelligent systems, which can ensure user satisfaction when designing intelligent systems.  
\begin{table}
\begin{tabular}{c c} \hline
**Level of Satisfaction** & **Design Parameters** \\ \hline High Satisfaction & 1 Trial, Repeat the question and then answer with a clear reference source \\  & 1 Trial, Repeat the question and then answer \\ \hline Mid-High Satisfaction & 2 Trials, Repeat the question and then answer with a clear reference source \\  & 2 Trials, Repeat the question and then answer \\ \hline Mid-Low Satisfaction & 3 Trials, Repeat the question and then answer with a clear reference source \\  & 3 Trials, Repeat the question and then answer \\ \hline Low Satisfaction & 3 Trials, answer only \\ \hline \end{tabular}
\end{table}
Table 5: Classification of emotional satisfaction of voice-based intelligent systems.
# Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey
## 3 Games Theory for WSNs Security
### Non-Cooperative Games
#### 3.2.3 Stackelberg Game  
The Stackelberg game is used to model two competitive players [21; 47]; one is a game initiator (leader) who chooses an action from a set \(A_{1}\) then the second player traces the leader's action and chooses an action from a set \(A_{2}\). This scenario is widespread in securing different WSNs where the defender acts as a leader and the attacker plays the role of the follower [2; 55; 56; 57].
# A General Euler Angle Error Model of Strapdown Inertial Navigation Systems
## 3 Simulation Experiments  
The Euler angles are used for large-angle attitude movements, which are direct outputs of SINS. Compared with misalignment, the Euler angle error model is more important in some applications. The general Euler angle error model can be classified as the relative Euler angle error model or the convected Euler angle error model. In order to prove the validity of the proposed model, simulation experiments are carried out.  
The simulation experiments are designed in large-angle attitude movements. Firstly, the proposed Euler angle error model can be established according to Equations (41)-(44). Then, the initial attitude, the initial Euler angle errors, and the rotational angular velocity can be set to describe large-angle attitude movements. Finally, the simulation experiments are carried out to verify the accuracy of the proposed model.