esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Effect of Other Boundary Conditions on Lateral Migration  
Previous studies have shown that channel lateral migration is also affected by other boundary conditions, such as channel slope, bank soil composition, riparian vegetation, variables of planform geometry, and river training works [29; 31; 35; 45]. Figure 9a shows the relationship between the lateral migration index and channel slope in the Xiaobeiganliu reach during the study period, and the data were relatively scattered. The correlation analysis of two variables was conducted using SPSS, and the result showed that the \(p\)-value equaled 0.523 (\(>\)0.05), which indicated that there was no obvious relationship. Therefore, the channel slope had little effect on the lateral migration in the Xiaobeiganliu reach. [PERSON] et al. [46] argued that the elevation difference between the floodplain and main channel may also influence lateral migration in wandering rivers, but the effect was not very significant. To investigate the effect of the elevation difference between the floodplain and main channel on lateral migration in the Xiaobeiganliu reach, Figure 9b shows the relationship between the lateral migration index and \(\overline{H}\). The correlation analysis of two variables was also conducted using SPSS, and the result showed that the \(p\)-value equaled 0.335 (\(>\)0.05), which implied there was no obvious relationship between the two variables. Therefore, the elevation difference between the floodplain and main channel had little effect on the lateral migration in the Xiaobeiganliu reach.  
Figure 8: Relationship between the lateral migration index and the variation in TG elevation.  
Figure 9: Relationships between the lateral migration index and other boundary conditions of (**a**) channel slope; (**b**) elevation difference between floodplain and main channel.  
Bank soil composition can also influence lateral migration in wandering rivers, and a lower clay content of bank soil usually results in more serious bank erosion [16]. Riparian vegetation can affect bank erosion to some extent, but it has little influence on long-term lateral migration distance [31; 47]. For river training works, levee protection works have little influence on lateral migration because they seldom touch the main channel; however, the flow guide works can reduce the shifting of the thalweg [5; 48]. Therefore, further detailed research on the effect of bank soil composition, riparian vegetation, and river training works must be conducted in the Xiaobeiganiu reach in the future.
## 2 Related Work
### Comparison of Related Work  
The following comparison Table 1 is used to examine the applicability of the related studies discussed earlier in the low-power wireless communication environment of IoT. The comparison is made in the availability aspect and the security aspect.  
The OTP (S/Key) method satisfies the criteria for the encryption key generation communication method and the required computational cost/time for key generation because the dynamic encryption keys used are generated in advance. However, considering the encryption key recovery communication method used in the case of packet loss, it is not appropriate because it requires performing two or more steps of synchronous communication. If a malicious user steals the initial seed value of OTP server, the user can generate all encryption keys; thus, the security is vulnerable to hijacking attacks. Exposure of key generation information can be prevented because only the counter values are sent when generating an encryption key. As long as the seed value is not stolen, the randomness and unpredictability of encryption key are satisfied. Diffie-Hellman method is not appropriate because two or more steps of communication based on the synchronous method are required to generate and recover an encryption key. Because asymmetric key is used, the required computational cost and time for key generation are high compared to those of other related studies. Because the key generation information is exchanged using the discrete logarithm problem, the exposure of key  
Figure 3: History-based encryption key algorithm.  
generation information is prevented. The randomness and unpredictability of encryption key are satisfied on the premise that a safe random number generation algorithm is used. However, if the random number generation algorithm is exposed, the encryption keys can be generated. In the case of block key, the criteria for the encryption key generation communication method and the key generation information exposure prevention are satisfied because the encryption key is generated independently at both ends of communication. However, considering the encryption key recovery communication method, it is not appropriate because two-step communication of synchronous method is required. In the case of hijacking attack, there is no exposure problem of random number generation algorithm and all the history of seed has to be known; thus, the security of block key method is deemed high compared to that of methods of other related studies.
# Space Habitat Data Centers--For Future Computing
## 1 Introduction  
Terrestrial cloud data centres have high powering [1; 2; 3] and cooling (using water) [4; 5] costs. These have prompted the design of solutions [6; 7; 8; 9; 10] that reduce power consumption and water footprint. The water footprint can also be reduced by leveraging free air cooling [11; 12] to a limited extent. The ocean provides free water cooling and can host data centres [13; 14; 15], at the risk of degrading marine biodiversity.  
Siting data centres in space can reduce the water footprint [16; 17; 18; 19]. The approach in references [16; 18] utilises small satellites to realize space-based data centres. Small satellites used as data centres have reduced uptime when faults occur because they are unmanned. It is also challenging to upgrade the computing payload in small satellites being used as data centres. Outer space also hosts satellites and spaceships [20; 19; 21]. Spaceships such as space habitats can support humans (making it easy to address faults) and host a larger computing payload. This paper proposes a manned space habitat data centre (SHDC) for processing space and non-space application data.  
The discussion in this paper addresses the challenge of reducing the water footprint of data centres. The paper proposes that data centres be sited in outer space (Earth's orbit) and make use of asteroid water for cooling to reduce Earth's data centre water footprint. The proposed data centre is located in a space habitat data centre. The use of an SHDC (space-based) also enables low latency computing platform access by satellites with data requiring processing.  
The contributions of the paper are further discussed below:  
The paper proposes manned space habitat data centres (SHDCs) for data processing. In addition, the paper presents the architecture for the design of the proposed SHDC. This is done by describing the aspects related to the access and use of asteroid water for cooling the SHDC. In addition, the paper describes communications between SHDCs, computer-resource-constrained space assets, and the ground segment. The paper also describes SHDC design and computing entities enabling dataprocessing and communications. In addition, the benefits of using the SHDC is formulated and investigated via performance simulation and evaluation.
## 3 Materials and Methods
### Design of TLBO-MHR Technique

Table 4: NODSN analysis of the IMD-EACBR technique compared to other models under various numbers of rounds. Figure 5: NODSN analysis of the IMD-EACBR technique under various numbers of rounds. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Energy Consumption (m)**} \\ \hline
**Density of** & **IMD-** & **EACBR** & **SFO Alg. ** & **GWO Alg. ** & **Genetic Alg. ** & **ALO Alg. ** & **PSO Alg. ** \\ \hline
100 & 0.047 & 0.078 & 0.113 & 0.153 & 0.203 & 0.246 \\
150 & 0.106 & 0.149 & 0.186 & 0.231 & 0.321 & 0.368 \\
200 & 0.125 & 0.193 & 0.262 & 0.323 & 0.415 & 0. Table 6 and Figure 7 illustrate a brief throughput (THPT) examination of the IMD-EACBR approach compared to other approaches. The results indicate that the IMD-EACBR methodology demonstrates supreme THPT under all SNs. For example, with 100 SNs, the IMD-EACBR model achieved a higher THPT of 0.975 Mbps, whereas the SFO, GWO, GA, ALO, and PSO techniques achieved lower THPTs of 0.934 Mbps, 0.891 Mbps, 0.861 Mbps, 0.804 Mbps, and 0.704 Mbps, respectively. Eventually, with 500 SNs, the IMD-EACBR approach reached a superior THPT of 0.902 Mbps, while the SFO, GWO, GA, ALO, and PSO techniques resulted in lower THPTs of 0.819 Mbps, 0.728 Mbps, 0.632 Mbps, 0.565 Mbps, and 0.522 Mbps, respectively. Table 7 and Figure 8 depict a brief packet delivery ratio (PDR) analysis of the IMD-EACBR approach compared to existing algorithms. The results indicate that the IMD-EACBR model achieved the greatest PDR under all SNs. For example, with 100 SNs, the IMD-EACBR model reached a PDR of 98.83%, whereas the SFO, GWO, GA, ALO, and PSO systems obtained lower PDRs of 98.40%, 96.47%, 95.65%, 94.37%, and 93.79%, respectively [20; 23; 24; 25; 26; 27]. Moreover, with 500 SNs, the IMD-EACBR model reached an ultimate PDR of 96.56%, whereas the SFO, GWO, GA, ALO, and PSO methodologies resulted in reduced PDRs of 95.20%, 94.66%, 93.47%, 92.30%, and 91.37%, respectively. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & \multicolumn{6}{c}{**Throughput (Mbps)**} \\ \hline
**Density of** & **IMD-** & \multirow{2}{*}{**SFO Alg.**} & **GWO Alg.** & **Genetic** & \multirow{2}{*}{**ALO Alg.**} & \multirow{2}{*}{**PSO Alg.**} \\
**Sensor Nodes** & & & & & & \\
100 & 0.975 & 0.934 & 0.891 & 0.861 & 0.804 & 0.704 \\
150 & 0.967 & 0.930 & 0.877 & 0.805 & 0.788 & 0.677 \\
200 & 0.958 & 0.916 & 0.855 & 0.781 & 0.762 & 0.658 \\
250 & 0.955 & 0.895 & 0.838 & 0.771 & 0.728 & 0.636 \\
300 & 0.945 & 0.903 & 0.801 & 0.745 & 0.691 & 0.616 \\
350 & 0.945 & 0.878 & 0.776 & 0.707 & 0.656 & 0.573 \\
400 & 0.929 & 0.844 & 0.776 & 0.692 & 0.619 & 0.569 \\
450 & 0.913 & 0.830 & 0.738 & 0.667 & 0.594 & 0.548 \\
500 & 0.902 & 0.819 & 0.728 & 0.632 & 0.565 & 0.522 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Throughput analysis of the IMD-EACBR technique compared to other approaches under different densities of SNs. Figure 6: ECM analysis of the IMD-EACBR technique under various densities of SNs. Figure 8: PDR analysis of the IMD-EACBR technique under different densities of SNs.
###### Abstract  
The intertwurbine transition duct (ITD), located between the high-pressure (HP) and low-pressure (LP) turbines of aeroengines, tends to be designed as an aggressive ITD integrated with wide-chord struts to meet the requirements of civil aeroengines for high bypass ratios and thrust-weight ratios. This paper presents a detailed unsteady numerical investigation of the effects of the HP rotor trailing-edge radius on the unsteady flow characteristics in the integrated aggressive intertwurbine transition duct (AITD), including the transport and dissipation of HP rotor wakes, the control mechanism of HP rotor wakes on flow separation and the influence of wake parameters. A sweeping rod, with a nondimensional diameter ranging from \(d/s=0.056\)-\(0.143\) (based on the pitch (s) of wide-chord struts at the midspan) and a reduced frequency (\(f\)) of \(1.07\), is used to simulate the HP rotor wake to decouple its influence from other secondary flows. Using the k-\(\omega\) SST turbulence model and gamma-theta transition model, a structured grid with 6.3 million nodes can achieve similar global results. The wake in the lower part of the AITD channel dissipates rapidly because of the stretching between its own circumferential motion and the radial upward secondary flow, especially for a small \(d/s\). Only the residual wake in the upper part can reach wide-chord struts in the case with large \(d/s\). A sweeping rod with a large \(d/s\) can reduce the radial pressure gradient in the AITD, inhibit the internal secondary flow to a certain extent, reduce the dissipation rate of the wake, enhance its suppression effect on flow separation on a wide-chord strut, and decrease the flow loss. However, the wake can also enhance the passage vortex due to the increasing circumferential pressure gradient in the wide-chord strut channel, resulting in increasing blade profile loss. In the scope of this study, the aerodynamic gain of the wake is still not enough to compensate for its loss increment (including its own dissipation loss). Therefore, selecting a small trailing-edge radius of the HP rotor is conducive to improving the aerodynamic performance of the integrated AITD.  
interturbine transition duct; sweeping rods; boundary layer transition; unsteady flow +
Footnote †: journal: Applied Sciences
## 3 Maximum Distance between Motes in Experimental Deployments  
For the study of the maximum experimental distance, we use Cypress motes with the Programmable System on Chip (PSoC) Starter Kit [3]. These motes use the ZigBee standard, which is a wireless communications standard designed by the ZigBee Alliance. ZigBee is based on the IEEE 802.15.4 standard and is aimed at applications that require secure communications with low data rate and maximization of battery life, using AA batteries, as shown in Figure 1.  
These motes are used to study the maximum distance as well as analyze the performance of this kind of IEEE 802.15.4 based communications. In particular, measurements are taken in an outdoor real deployment of a WSN to monitor soil moisture and other environmental parameters in a typical area of the interior of the Valencian Community (Spain), in a wood area, following a procedure similar to [57; 58] (Figure 2). Table 1 shows the measurements in different terrains and environments. It must be noticed, as it could be expected, that the communication range is less than 100 m, except when we lift the motes and then we reach 120 m.  
On the basis of the measurements of the maximum distance, a WSN is planned with the aim of monitoring the degree of humidity of the soil in a plot of 20 Ha, as shown in Figure 3, in the vineyards of the Sierra de Negrete (Valencia). The communication between motes within the WSN will be done by multiple hop transmission. But additionally, if a transmission is raised to a BS located 30 km or a LEO satellite as we previously said, we will proceed with the approach of the following section. We must find out the way to get a constructive interference in the direction of the receiver.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Terrain** & **Distance [m]** & **Characteristics of the Terrain** \\ \hline Plain forest & 51 \(\pm\) 5 & Pine forest area with scrubland \\ Plain forest & 80 \(\pm\) 5 & Zone of pine forest with scrubland. BS at 1 m height \\ Irregular forest & 35 \(\pm\) 5 & Pine forest area with slopes \\ Irregular forest & 45 \(\pm\) 5 & Pine forest area with slopes. BS at 1 m height \\ Flat agricultural land & 120 \(\pm\) 10 & Plot of ploughed cereals. BS at 1 m height 1 \\ Flat agricultural land & 70 \(\pm\) 10 & Vineyard plot \\ Farmland & 85 \(\pm\) 10 & Vineyard plot. BS at 1 m height \\ \hline \hline \end{tabular}  
* There is variability associated with unevenness and the degree of humidity of the soil.  
\end{table}
Table 1: Distance measurements using Cypress CY3271 [3] kit.  
Figure 1: Psoc Cypress First Touch Starter Kit [3].  
Figure 2: Measures with CY3271 on a wood area. Deployment of motes to cover an area of 2 Ha in vineyards in the Sierra de Negrete (Valencia): (**a**) Measurements at Vineyards land; (**b**) Screenshot of SIGPAC web tool used to manage plots of fields ([[http://sigpac.mapa.es/](http://sigpac.mapa.es/)]([http://sigpac.mapa.es/](http://sigpac.mapa.es/))).
## 5 Comparative Analysis of Traditional and Modern Methods
### LLM-Based Methods
#### 5.3.3 Fake News Detection Using LLMs and Contextual Analysis  
The ARG method proposed in [75] achieved a 78.6% accuracy in the Chinese dataset Weibo21 and an accuracy of 87.8% in the GossipCop English dataset from FakeNewsNet. When ARG is combined with the LLM judgement predictor, it achieves an accuracy of 77.4% and 88% in the Chinese and English datasets retrospectively. Finally, ARG-D achieves 77.2% and 87% accuracy scores in the Chinese and English datasets, respectively.  
The SheepDog method [76], which extracts content-focused veracity attributions from LLMs, has been tested on the Politifact dataset and achieved an accuracy of 88.44% and on the GossipCop dataset and got an accuracy of 75.77%. On the LUN dataset, the SheepDog method achieved its highest accuracy (93.05%). In all datasets, SheepDog outperformed all other methods that rely on pre-trained models like BERT, RoBERTa, DeBerta, GPT3.5, or InstructGPT.  
The Diverse reaction generation Explainable proxy tasks and LLM-Based expert ensemble method, also known as DELL [77] has been tested on seven datasets related to fake news detection (Pheme and llm-mis), framing detection and propaganda tactic detection. DELL achieved state-of-the-art performance against baselines in all benchmarks. This shows the success of integrating LLMs in multiple stages of news veracity evaluation.
## 4 Iterative Algorithm using Parametric Optimization
\begin{tabular}{l l} \(M\) & Number of primary users (PUs) \\ \(B_{i}\) & Bandwidth of \(i^{\text{th}}\) PU \\ \(N\) & Number of subcarriers of the secondary user's (SU's) transmitter \\ \(\Delta f\) & Bandwidth of a subcarrier \\ \(h_{j}^{ss}\) & Channel fading gain of \(j^{\text{th}}\) subcarrier \\ \(\gamma_{j}^{ss}\) & Channel power gain of \(j^{\text{th}}\) subcarrier \\ \(h_{i}^{sp}\) & Channel fading gain between SU transmitter and \(i^{\text{th}}\) PU \\ \(\gamma_{i}^{sp}\) & Channel power gain between SU transmitter and \(i^{\text{th}}\) PU \\ \(p_{j}\) & Power allocated to \(j^{\text{th}}\) subcarrier \\ \(I_{ji}\) & Interference by \(j^{\text{th}}\) subcarrier to \(i^{\text{th}}\) PU \\ \(I_{i}^{th}\) & Interference threshold \\ \(I_{i}^{P}\) & Interference probability threshold \\ \(C_{j}\) & Capacity/Rate of \(j^{\text{th}}\) subcarrier in bits/sec \\ \(C^{th}\) & Capacity/Rate threshold \\ \(P_{T}\) & Maximum transmitted power over all subcarriers \\ \(J_{ij}\) & Interference by \(i^{\text{th}}\) PU to \(j^{\text{th}}\) subcarrier \\ \(T_{s}\) & OFDM symbol duration \\ \(d_{ji}\) & Spectral distance between \(j^{\text{th}}\) subcarrier and \(i^{\text{th}}\) PU \\ \(f(p)\) & Numerator of fractional program \\ \(g(p)\) & Denominator of fractional program \\ \(y\) & \(=tp\), Charnes-Cooper transformation variable \\ \(t\) & \(=g(p)^{-1}\), Charnes-Cooper transformation variable \\ \(\varepsilon\) & Convergence tolerance parameter in Dinkelbach method \\ \(q\) & Real-valued parameter so that \(F(q)=\max_{p}[f(p)-qg(p)]\) \\ \end{tabular} 

###### Appendix A Derivation of Constraint \(C_{1}\) in Equation (7)

Combining constraint \(C_{1}\) of Equations (3) and (6), we can write,

\[Pr\left(\gamma_{i}^{sp}\leq\Gamma\right)\geq I_{i}^{P},\;\forall i\in\mathcal{M} \tag{1}\]

where \(\Gamma=\frac{I_{i}^{th}}{\sum_{j=1}^{N}p_{j}K_{ji}}\). Since the channel power gain \(\gamma_{i}^{sp}\) is exponentially distributed as given in Equation (4), we can write:

\[\int_{0}^{\Gamma}\frac{1}{\bar{\gamma}_{i}^{sp}}\exp\left(-\frac{\gamma_{i}^ {sp}}{\bar{\gamma}_{i}^{sp}}\right)d\gamma_{i}^{sp}\geq I_{i}^{P},\;\forall i \in\mathcal{M} \tag{2}\]

After integration, we can extract \(\sum_{j=1}^{N}p_{j}K_{ji}\) from Equation (2) as follows:

\[\sum_{j=1}^{N}p_{j}K_{ji}\leq\frac{I_{i}^{th}}{\bar{\gamma}_{i}^{sp}(-\ln(1-I_ {i}^{P}))},\;\forall i\in\mathcal{M} \tag{3}\]

### Proof of Theorem 1

Let us assume that \(\xi_{j}=\frac{\gamma_{j}^{ss}}{\sigma^{2}+\sum_{i=1}^{M}J_{ij}}\) and \(\zeta=\frac{I_{i}^{th}}{\tilde{\gamma}_{i}^{sp}(-\ln(1-I_{i}^{p}))}\).
# Optimization of the Battery Pack Heat Dissipation Structure of a Battery-Type Loader
## 4 Results and Discussion of Single-Factor Analysis
### Analysis of the Effect of Deflector on the Heat Dissipation Characteristics of Battery Packs
Therefore, the width of the deflector was further increased, and the change in the heat dissipation characteristics of the battery pack under the effect of further increases in the width of the deflector was studied. 3.3 Analysis of the Effect of the Deflector Covering Three Rows of Battery Packs on the Heat Dissipation Characteristics of Battery Packs  
Based on the above analysis, the width of the deflector was further increased such that the deflector covered three rows of battery packs, as shown in Figure 18.  
As shown in Figure 18, with the other structural parameters of the battery pack kept unchanged, the deflectors were placed above the 2-3-4, 3-4-5, 4-5-6, and 5-6-7 rows of the battery pack in each layer of the battery pack. Due to the width after this further increase, when the angle \(\alpha\) was \(5^{\circ}\), the deflectors had access to the upper surface of the battery pack, and the angle can be slightly increased due to the lengthening of the deflectors. Thus, this time, the value of the angle was set to 3.5\({}^{\circ}\) or 4\({}^{\circ}\) in the modeling and analysis, and we assessed how the positions of the deflectors of this width and their angles changed the heat dissipation effect of the battery pack. The analysis results are shown in Figure 19.  
Figure 17: Temperature change curves for the battery pack: (**a**) the maximum temperature change curve; (**b**) the average temperature change curve; and (**c**) the temperature difference curve. Figure 18: Schematic diagram of battery pack deflector. Compared with the analysis results in the previous section, it can be seen that with the further increase in the width of the deflector, the maximum temperature of the battery pack only decreased by 0.2 \({}^{\circ}\)C, while the average temperature of the battery pack remained largely unchanged and the temperature difference of the battery pack only decreased by 0.1 \({}^{\circ}\)C. Overall, the heat dissipation effect of the battery pack was only slightly enhanced, which indicates that even if the deflector is further widened, the heat dissipation effect of the battery pack will not be significantly optimized.
## 2 Experimental Setup
### Two-Component Particle Image Velocimetry Measurements  
The time-averaged two-component Particle Image Velocimetry (PIV) measurement was employed to resolve the velocity, vorticity, and turbulence information along the centreline of the articulated lorry model. Details about the setup of the present PIV measurement could be found in [11; 30]. The centreline of the false floor was illuminated by a pair of Neodymium-doped Yttrium Aluminium Garnet (Nd-YAG) Q-switched lasers with maximum pulse energy and frequency of 0.1 J and 0.2 kHz, respectively. The time delay (\(\Delta\)t) between the two laser pulses was \(\Delta\)t = 20 \(\upmu\)s. Olive oil mist with a typical diameter of 1 \(\upmu\)m was used as the seeder. A Phantom (v341, USA) high-speed camera was used for capturing the raw images in the PIV experiments. With the aid of a Cannon 100 mm fixed lens and  
Figure 5: Schematic setup of the wind tunnel tests (adopted and modified from [11]). Note: all units are in mm.  
a viewing area of 478 mm \(\times\) 294 mm was achieved in the PIV measurements. The time-averaged flow field was constructed by averaging 2400 pairs of PIV raw images. Cross-correlation of the captured raw images was conducted by Davis 8.2, supplied by LaVision, Germany, using a two-stage approach. In the first stage, the PIV raw images were divided into a number of 32 \(\times\) 32 pixels interrogation windows, and the window size was refined by half in the second stage. Two and three passes of cross-correlation were conducted in the first and second stages, respectively. The overall uncertainty of the PIV measurements is approximately 4%.