esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
Around 3200-3250 cm\({}^{-1}\) as well as 3400-3450 cm\({}^{-1}\) are often located bands assigned to non-structural water vibration [27], although in the range of around 3450 cm\({}^{-1}\) according to [9; 24] where the stretching vibrations of the -OH groups attached to Mg and Al ions are also located. Band ca. 3086-3088 cm\({}^{-1}\) can be attributed to the -OH bond [28]. Bands connected with bending vibrations of water molecules are located around 1639-1647 cm\({}^{-1}\)[10; 29]. While the bands around 1370-1460 cm\({}^{-1}\) can be attributed to stretching vibrations from the carbonate anion [9; 10]. These vibrations are often connected with hydrotalcite. Taking into consideration these bands as well as the results of the thermal analysis, it can be stated that in the studied samples, there is some hydrotalcite-like phase. Comparing the relative intensity of this band in the spectra for each sample, it can be noticed that the higher relative intensity of these bands occurs in the samples with the additives. This suggests that in this samples content of hydrotalcite like phase is higher. Worthy of notice is that some authors [15] connect the band ca. 1380 cm\({}^{-1}\) with deformation vibrations of C-O in adhered tartaric acid to the crystals of the ceramic phases. Figure 5: Comparison of the characteristic XRD peaks for a specified phase: (**a**) Al\({}_{2}\)O\({}_{3}\); (**b**) AlO(OH); (**c**) Mg(OH)\({}_{2}\); and (**d**) Mg\({}_{6}\)Al\({}_{2}\)(OH)\({}_{18}\)-4.5H\({}_{2}\)O. The band at 1072 cm\({}^{-1}\) corresponds to symmetric bending vibrations of the Al-O-H mode in boehmite [28]. Bands ca. 740, 780, 830-860 cm\({}^{-1}\) are attributed to Al-O vibrations mode in boehmite. Vibrations of M-O and M-OH (where M is a metal ion--Al or Mg) in octahedral metal layer are associated with the region around 400-650 cm\({}^{-1}\). Bands ca. 552 cm\({}^{-1}\) are connected with Al-OH and 600-650 cm\({}^{-1}\) with Mg-OH translations mode [9; 10; 28]. The FTIR analysis confirms the results from the thermal analysis and XRD analysis; moreover, it indicates the presence of the hydrotalcite-like phase in the studied samples. The SEM-EDS analysis shows only slight differences between the samples. The microstructure of the samples shown in Figure 7 consists of two kinds of granularly shaped grains. The smaller ones are loosely connected with each other and create a matrix for larger grains. According to the EDS analysis, their chemical composition is varied, and larger aggregates have a higher amount of aluminum with an admixture of magnesium and various levels of oxide. This suggests boehmite or/and aluminum oxide as the main component(s) of these grains. While smaller aggregates have a higher content of magnesium and a high level of oxide, this indicates that magnesium hydroxide and/or double magnesium and aluminum hydroxide hydrate are the main components of these grains. These findings are in agreement with the result of the previous analysis. Figure 6: FTIR spectra of studied samples. Figure 7: SEM images of the studied samples: (**a**) sample 1; (**b**) sample 2; and (**c**) sample 3.
## 5 Experimental Results
### Discussion  
The results obtained from the experimental campaign have confirmed the good performance exhibited by the data dissemination protocol adopted in X-NETAD. In fact, it has been shown that a small number of rounds of requests (at most five) is sufficient to disseminate the whole information archive to all network nodes. This happens also in the case of unfavorable network conditions (as in the case of Scenario 2), where SUs are sparse and distant from the PU (up to three hops away). Remarkably, these results have been obtained limiting the overall number of transmissions in the network.  
The core retransmission mechanism of X-NETAD is the IF broadcast protocol, which is designed to reduce the channel congestion and, thus, scales well with the number of nodes, as shown in [26]. The  
Figure 25: PMF of the archive reception time in Scenario 3.  
Figure 26: CDF of the received _DATA_ messages before a _REQUEST_ in Scenario 3.  
presented results have been obtained in scenarios with a small number of nodes, where the impairments of the wireless channel are the principal cause of the packet losses, while the losses due to channel congestion are negligible. However, we expect that the overall performance of the X-NETAD protocol should scale well with the number of nodes, owing to the equivalent property of the IF protocol.  
Finally, we comment on a comparison between the performance of the X-NETAD protocol with that of other dissemination protocols. Even if we do not have conducted experimental campaigns using alternative protocols, it is possible to get some insights from some of our previous works [27]. In particular, according to the observations in Subsection 3.1, the IF protocol exhibits better performance than the flooding protocol, especially under heavily loaded networks. Unfortunately, as our testbed is composed of a small number of smartphones, we were not able to evaluate scenarios with high spatial densities. Therefore, in our specific experimental scenario, it is reasonable to expect that a flooding-based dissemination strategy will exhibit a performance similar to that of IF.
## 3 An Opportunistic Routing for Data Forwarding Based on Vehicle Mobility Association  
Vehicle communication is useful for supporting numerous vehicular applications that ensure the driver's safety and convenience. It is still a challenge to the VANETs [27]. Because of the rapid change of network topology, the high-speed movement and frequent network disconnection between vehicles have resulted in the invalidation of traditional network routing protocols [28]. An effective algorithm should be proposed to reduce delay and save space utilization in the case of a high data rate.  
If the source vehicle (SV) wishes to send a message to the destination (DV). In the routing algorithm (AODV), the SV sends a packet to the neighbor vehicles and forwards until the packet reaches the DV. The DV implements the reverse path transmission information to the SV. This selection will reduce the data delivery ratio because it only lets the source vehicle send a request to the neighboring vehicles, but does not consider the network structure change of vehicles and the association between vehicles [29]. Therefore, vehicle network structure change and the association between vehicles are important to consider in data delivery path selection.
# Linked Data Triples Enhance Document Relevance Classification
## 4 Energy-Hub
### Topic and Named Entity Analysis  
As articles arrive through the news-feed API, the parsed text from URIs are sent to an Latent Dirichlet Allocation (LDA) topic modeler, and a pre-trained Named Entity Recognition (NER) model is used to identify semantic textual features of each document, as discussed earlier in natural language features section (Section 3). To understand how effectively the natural language features can distinguish between the two document classes, we carried out a statistical analysis on the distributions of LDA topics and NEs in the Energy-Hub dataset.  
The distribution of topics in each class is formed on the basis of the number of documents belonging to a particular topic, i.e., the inverse document frequency of topics. A document \(d\) is assigned to topic \(t_{i}\) if \(t_{i}\) has the largest probability among the topic set \(T=\{t_{1},t_{2},\ldots,t_{n}|n=100\}\) generated by a topic modeler within document \(d\):\[topic_{d}=argmax(i\in\{1\dots 100\}P(t_{i}|d)). \tag{1}\]  
The Named Entity (NE) distribution is formed by counting the number of documents consisting of a particular NE, i.e., the inverse document frequency measure of the NE. The Jensen-Shannon Divergence (JSD), also known as \"Information Radius\", measures the distance between two probability distributions. In Reference [36], authors used JSD to calculate the distance between two corpora by forming probability distributions of vocabularies using term frequencies. Similarly, the same authors used the JSD method over topics and named-entity distributions over the two sets of documents corresponding to the two classes to compute their divergence.  
The JSD measure is calculated using Equation (2) below, where \(P\) and \(Q\) represent the topic (or NE) distribution in the relevant and irrelevant classes, respectively, and \(M=\frac{1}{2}(P+Q)\) and \(D(P||Q)\) is an asymmetric distance measurement based on Kullback-Leibler Divergence.  
\[JSD(P||Q)=\frac{1}{2}D(P||M)+\frac{1}{2}D(Q||M). \tag{2}\]  
The JSD distance between topic distributions in \"relevant\" and \"irrelevant\" classes from the corpus is found to be 0.80, while the JSD distance between the NE distributions is approximately 0.85. These high distance scores provide initial evidence that the natural language features based on topics and NEs can effectively distinguish between the two document classes. Hence, these features are considered as inputs to the neural network classifier which will be described in the Learning Models section below (see Section 5). Triples are also extracted and formed from complete sentences at this time as follows.
## 3 Results and Discussion
### Anti-Interference Studies and Real Samples Analysis  
The selectivity is also a significant analytical factor for sensors, and several common interfering species were chosen to evaluate the selectivity of the flexible Pt/rGOP electrode. Figure 8C represents the typical amperometric responses upon successive addition of 0.1 mmol/L H\({}_{2}\)O\({}_{2}\), 0.2 mmol/L glucose (Glu), 0.2 mmol/L fructose (Fru), 0.2 mmol/L uric acid (UA), 0.2 mmol/L ascorbic acid (AA), 0.2 mmol/L oxalic acid (OA) and 0.2 mmol/L citric acid (CA) into 0.1 mol/L PBS. The result shows that these potential interfering substances do not exhibit obvious amperometric signals and proves the flexible Pt/rGOP electrode has an excellent selectivity to H\({}_{2}\)O\({}_{2}\).  
Figure 8: (**A**) Long-term stability test of the Pt/rGOP. (**B**) Effects of bending times on the current response to 10 \(\upmu\)mol/L of H\({}_{2}\)O\({}_{2}\) of the flexible Pt/rGOP electrode. (**C**) Amperometric responses upon successive addition of 0.1 mmol/L H\({}_{2}\)O\({}_{2}\), 0.2 mmol/L Glu, 0.2 mmol/L Fru, 0.2 mmol/L UA, 0.2 mmol/L AA, 0.2 mmol/L OA, 0.2 mmol/L CA and 0.1 mmol/L H\({}_{2}\)O\({}_{2}\) at \(-\)0.25 V in 10 mL PBS. (**D**) Amperometric curve of successive addition of milk containing H\({}_{2}\)O\({}_{2}\) in 0.1 mol/L PBS.  
Food safety has aroused concern with the improvement of the quality of life. Residual hydrogen peroxide is often found in milk, so the sensor can be used to determine H\({}_{2}\)O\({}_{2}\) in milk. The amperometric curve of successive addition of H\({}_{2}\)O\({}_{2}\) is shown in the Figure 8D. The Pt/rGOP electrode does not exhibit an obvious amperometric response towards pure milk. When the milk contains H\({}_{2}\)O\({}_{2}\), the electrode shows an obvious amperometric response, which is similar in the case of successive addition of H\({}_{2}\)O\({}_{2}\) without milk under the same concentration, as shown in Figure 7C. The result indicates that the Pt/rGOP electrode has excellent practical application.
# Dynamic Rating of Three-Core XLPE Submarine Cables for Offshore Wind Farms
## 3 Results  
This study shows how to construct a thermal ladder network that represents three-core XLPE submarine cables at 36 kV AC and above. By deriving the thermal coefficient contained in the thermal ladder network from the Fourier transfer function, it is possible to describe the temperature behaviour in the centre of the cable by applying a load step to the cables. Using the superposition principle, this study proves the ability to represent a load profile by the sum of each temperature transient.  
The study could be extended to a cable ageing analysis, as the most noticeable wear on cables is due to temperature changes, using an insulation ageing diagnosis of XLPE power cables. These parameters are a significant part of the developed calculations and can potentially be extended to analyse the lifetime of the cables on the basis of an estimated load profile [17].
# Nutrition, Flavor, and Microbial Communities of Two Traditional Bacterial Douchi from Gansu, China
## 3 Results and Analysis
### Correlation Between Major Microorganisms and Flavor Compounds in the Two Types of Douchi  
The intergroup correlation of dominant genera and the relative contents of main flavor compounds were determined for the two types of douchi. The interaction between microorganisms and flavor compounds in Longnan douchi is shown in Figure 3A. There was a significant negative correlation between _Bacillus_ and ethyl hexanoate (\(p<0.05\)), _Pichia_ showed a significant negative correlation with ethyl isobutyrate (\(p<0.05\)), _Candida_ showed a highly significant negative correlation with ethyl butyrate (\(p<0.01\)), and _Rhodosporidium_ was significantly positively correlated with ethyl butyrate (\(p<0.05\)). The interaction between microorganisms and flavor compounds in Qingyang douchi is shown in Figure 3B. _Carnobacterium_ showed a significant positive correlation with 2,4,5-trimethylthiazolo (\(p<0.05\)).  
In Longnan douchi, _Rhodosporidium_ was the main contributor to the production of flavor compounds, whereas _Carnobacterium_ was the main contributor to the flavor in Qingyang douchi. It has been reported that _Rhodosporidium toruloides_ can produce lipids and sugar alcohols commonly used as natural sweeteners from galactose. This may be closely related to the production of sweetness in douchi [37]. _Carnobacterium_ is able to convert glucose into lactic acid, and this group of microorganisms play an important role in the improvement of douchi flavor and nutritional value [38]. In Longnan douchi, _Bacillus_, _Pichia_, and _Candida_ play an inhibitory role in the formation of flavor compounds, which is different from the results of the previous study, in which _Bacillus_, _Pichia_, and _Candida_ were found in 10 commercial douchi to produce enzymes or flavor substances that play an important role in the flavor composition of douchi [19]. This may be due to the different fermentation processes and conditions of different douchi.  
Figure 2: Alpha diversity assessed with [PERSON] index (**A**), Shannon index (**B**), and Simpson index (**C**) of fungal taxon in two types of douchi. Venn plot of fungal ASV number from two types of douchi (**D**). Relative abundance of fungal taxon at phylum (**E**) and genus (**F**) levels in two types of douchi.  
Therefore, the main reason for the great difference in flavor between the two types of douchi was that the microbial communities were different, leading to the formation of the final flavor through the growth and metabolism of microorganisms, which is consistent with the research conclusion of [PERSON] et al. [1].
# High Performance Computing in Satellite SAR Interferometry: A Critical Perspective
## 3 Operational SAR Systems and Applications
### New-Generation and Forthcoming Spaceborne SAR Sensors
RCM will acquire data using a swath width of 20-350 km and a reduced revisit time of 12 days, which is enhanced to 4 days using all the satellites within the constellation. Finally, as part of the Gaofen series of the China High-resolution Earth Observation System (CHEOS), the SAR satellite Gaofen-3 (GF-3) was launched on 10 August 2016. It carries a C-band and multi-polarization high-resolution SAR [113]. It can work in 12 different modes (spotlight, stripmap, and ScanSAR), thus acquiring swaths of 10-650 km with a resolution between 1 and 500 m. China has also planned a series of future SAR missions, including two twin satellites operating at L-band for differential interferometric applications, a dual antenna X-band Interferometric SAR satellite for DEM generation, and a SAR satellite in geosynchronous orbit with 20 m resolution. The main characteristics of the operating and forthcoming SAR sensors are summarized in Table 1.
## 3 Results and Discussion  
### Heavy Metal Concentrations  
All analyzed samples contained high concentrations of Cu, Zn, and Al (Figure 1). The other three metals, Pb, Cd, and Cr, existed in lower concentrations. Cu, Zn, and Al had a similar concentration range (33.1-129, 42.6-149, and 13.5-212 \(\upmu\)g/g-dry weight (dw), respectively). Al had a broader concentration range with the lowest minimum concentration (13.5 \(\upmu\)g/g-dw, AOM) and the highest maximum concentration (212 \(\upmu\)g/g-dw, GAM). Compared with Al, Cu and Zn had a relatively constant concentration range. The level of these three heavy metals was similar to previously reported levels in freshwater trichoptera in Japan [41] and the wharf roach in China [27]. Their average Zn concentration (110 \(\upmu\)g/g-dw) was higher than that of Cu (75.2 \(\upmu\)g/g-dw), and the Zn concentrations were higher than the Cu concentration in all samples except for the SAS sample. Cr had the lowest concentration range (0.02-0.21 \(\upmu\)g/g-dw) among the analyzed metals. The highest Cr concentration was detected in the USU sample (0.21 \(\upmu\)g/g-dw). Pb was detected at a secondary lower level (0.22-1.46 \(\upmu\)g/g-dw), and the HAC sample had the highest concentration (1.46 \(\upmu\)g/g-dw). Cd was present at a higher concentration than Zn and Cr but had a low concentration (0.46-5.60 \(\upmu\)g/g-dw). The NOT samples contained the highest Cd concentration (5.60 \(\upmu\)g/g-dw). These three metals were detected in a relatively wide range; however, their detected levels were lower than those of the other three metals and significant differences in concentrations among the sampling sites were not detected. _Ligia italica_ that was collected in Eastern Sicily, Italy, on September 2001 [26] contained a different pattern of heavy metals with a lower level of Cd (0.22-1.26 ug/g-dw) and a higher level of Pb and Cr (1.74-9.30 and 0.18-1.68 ug/g-dw, respectively), compared with this study. These differences probably reflect pollution differences among the sampling sites. The order of the detected level of the heavy metals was Zn > Al > Cu > Cd > Pb > Cr, and this trend was similar to a previous report that showed Cu > Cd > Pb in _Ligia cirerscens_[27] and a previous report on coastal water and sediment [20,42]. The correlations in the three metal couples (Cu-Zn, Cu-Al, Zn-Al) were not significant ([PERSON]'s rank correlation test, \(p\) = 0.92, 0.45, 0.69, respectively). Additionally, the total concentrations of heavy metals were not distributed widely among the 11 sampling sites (177-377 ug/g-dw). The sum of Cu, Zn, and Al was dominant in six metal total concentrations (Figure 2, 97.2%-99.7%).
# HVdc Circuit Breakers: Prospects and Challenges
## 4 HVdc Circuit Breaker Topologies
### Electro-Mechanical HVdc Breakers
#### 4.1.1 Electro-Mechanical Passive Resonance HVdc Breakers  
The passive DCCB is an obsolete technology that was developed for the LCC-HVDC system [88]. These breakers have a slow response time and are bulky, massive, larger in size, thus interest is dropped to use this breaker for dc grid protection. But these breakers have comparatively low power losses than all other dc breakers. A passive resonance DCCB is shown in Figure 2.  
The nominal current path is shown in Figure 2. Rated current (\(I_{a}\)) flows through this path when the switch (CB) is closed under normal operation. Normally, interrupting circuits are developed with the air blast circuit breaker. Condition of zero-crossings is established with a series resonant circuit connected to an inductor and a capacitor, this forming a commutation path. This condition is necessary for breaker interruption [89]. Energy is absorbed by the surge arrestor during the fault. The current oscillation between the nominal and the commutation path is enabled by the interruption. This interruption works at the natural frequency. When the amplitude of the oscillating current is greater than the input current, zero-crossings occur. At this stage, the switch stops the flow of current in the nominal path [18; 74].  
As a result, the capacitor will be charged by the flow of current (\(I_{o}\)). Consider the capacitor voltage exceeds a dc breaker's voltage capability. Surge arrestor will respond, an ideal zero point will be created on the decrease of current. This will help in the interruption of current. The maximum voltage value is 500 kV for passive electro-mechanical HVdc breakers, being employed for many years. This breaker clears the 5 kA fault current within a fault clearing time of 60-100 ms [90]. However, the development of semiconductor technology has reduced the attraction of electromechanical breakers for short circuit faults in multi-terminal HVdc systems [91].  
The interruption process can be clearly understood by the analysis of the current equation. The differential equation during fault interruption is [89]:  
\[L_{c}\frac{d^{2}is}{d^{2}}+\left(R_{c}+\frac{\partial_{uarc}}{\partial_{is}} \right)\frac{d_{is}}{dt}+\frac{1}{C_{s}}i_{s}=\frac{I_{o}}{C_{c}} \tag{1}\]  
\[i_{s}=I_{o}\,\left(1+e^{\frac{1}{2}\,\left(R_{c}+\frac{\partial_{uarc}}{ \partial_{is}}\right)}.Sin\omega_{c}t\,\right) \tag{2}\]  
Figure 2: Electro–mechanical passive resonance HVdc breakers.  
where \(\omega_{c}=\sqrt{\frac{1}{L_{c}\cdot C_{c}}}\)_and if_\(R_{c}+\frac{\partial_{max}}{d_{is}}<0\); then \"\(i_{s}\)\" is oscillating with growing amplitude. In this scenario, the first zero-crossing of current would be enough for the breaker to interrupt the dc fault.
## 4 Object Recognition
### Robustness to Rotation and Scaling  
Robustness to rotation and scaling is an important property for a shape descriptor. We have tested _RBRC_ for rotation and scale invariance by performing the experiments as specified in the MPEG-7 document ([PERSON] and [PERSON] [22]). Two new additional databases were constructed each containing 420 silhouette images; 70 of them are the reference shapes (one from each class of the original database) and the others are the derived shapes. The derived shapes in the rotation database were obtained by digitally rotating the basic shapes by 9\({}^{\circ}\), 36\({}^{\circ}\), 45\({}^{\circ}\) (composed of 9\({}^{\circ}\) and 36\({}^{\circ}\) rotations), 90\({}^{\circ}\) and 150\({}^{\circ}\). For the scaling database, the derived shapes were obtained by reducing the basic shapes in each dimension by factors 0.3, 0.25, 0.2 and 0.1, and enlarged by a factor of 2. In these experiments, each silhouette is matched against all others and the performance is reported in terms of the top six retrieved images. Since the maximum number of corrected matches for a single query shape is 6, the maximum number of corrected matches is 2520. Table 4 shows the results obtained. Note that achieving scale invariance is more challenging then rotation invariance since some images are severely distorted when scaled by factors of 0.1 and 0.2.  
\begin{table}
\begin{tabular}{l l l l l} \hline \multicolumn{1}{c}{**Method**} & \multicolumn{1}{c}{**Rotation**} & \multicolumn{1}{c}{**Scaling**} & \multicolumn{1}{c}{**Average**} \\ \hline
**Visual Parts** ([PERSON], [PERSON], and [PERSON] [17]) & 100\% & 88.65\% & 94.33\% \\
**CSS** ([PERSON], [PERSON], and [PERSON] [12]) & 99.37\% & 89.76\% & 94.57\% \\
**Wavelets** ([PERSON] and [PERSON] [23]) & 97.46\% & 88.04\% & 92.75\% \\
**Zernike Moments** ([PERSON] and [PERSON] [24]) & 99.60\% & 92.54\% & 96.07\% \\
**Multilayer Eigenvectors** & 100\% & 92.42\% & 96.21\% \\
[[PERSON], [PERSON], and [PERSON] [17], [PERSON] [25]) & 99.52\% & 93.02\% & 96.27\% \\ _RBRC_ & & & & \\ \hline \end{tabular}
\end{table}
Table 4: Results for rotation and scale invariance.  
\begin{table}
\begin{tabular}{c c c c c} \hline \multicolumn{1}{c}{**Train**} & \multicolumn{1}{c}{**1 st half**} & \multicolumn{1}{c}{**1 st half**} & \multicolumn{1}{c}{**2 nd half**} & \multicolumn{1}{c}{**2 nd half**} \\ \hline
**Test** & **1 st half** & **2 nd half** & **1 st half** & **2 nd half** \\ \hline
**Score** & 94.47\% & 94.30\% & 92.06\% & 91.09\% \\ \hline \end{tabular}
\end{table}
Table 3: RBRC retrieval rate when testing on half of the database.