esa-sceva/satcom-chunk-collection huggingface dataset:
# Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems
## 5 Network Architectures and Transmission Technologies
### Wireless Networks
#### 5.2.1 Cellular Networks
Finally, the expected lifetime of a lighting infrastructure is around 15-20 years, which is a very long period in terms of technological evolution. In such a long period, the cellular technology chosen for the smart lighting infrastructure at the time of its deployment might be switched off by network operators to free up frequencies for new technologies. This is what is currently happening with the 3G technology that, although still excellent for many IoT applications, will be dismissed in the next years, 15-20 years after its deployment. It has to be observed, in this regard, that a communication technology is possibly chosen for the smart-lighting service only during its full maturity, which means that its expected residual lifetime might be less than the lighting infrastructure lifespan.
# Research on Microstructure and Mechanical Properties of Laser Welding of BR1500 HS Joints
## 3 Results and Discussion
### Microstructure
#### 3.5.1 Microstructure before Quenching  
Figure 14 illustrates the microstructure of the weld joint before quenching. The macro morphology of the welded joint is shown in Figure 14a. The welded joint consists of the base material (BM), heat-affected zone (HAZ), and fusion zone (FZ). After laser welding, the cooling rate of the FZ is very high and it is instantly solidified from the liquid state. As shown in Figure 14b, the microstructure of the FZ is mainly martensite (M). The HAZ may be classified into an incomplete recrystallization zone (IRZ), coarse grain zone (CGZ), and fine grain zone (FGZ) based on different grain morphologies and the composition of the microstructure. During the welding process, the heating temperature of the metal in the CGZ and FGZ is above \(A_{\text{C3}}\), so that the metal is fully austenitized. Therefore, the microstructure of these two regions is composed of martensite. As shown in Figure 14c, the welding thermal cycle experienced by CGZ causes severe growth of austenite grains, which eventually transformed into coarse M and retained austenite (RA). Compared with the CGZ, the metal in the FGZ is heated to a lower temperature. The residence time at high temperatures is short and the growth of grains is not apparent. Therefore, the M in the FGZ is much finer than that in the CGZ, as shown in Figure 14d. In the IRZ, the peak temperature of this zone is between \(A_{\text{C3}}\) and \(A_{\text{C1}}\), and only part of the pearlite (P) is austenitized and transformed into a small amount of M after rapid cooling. Therefore, as shown in Figure 14e, the microstructure of IRZ consists of ferrite (F) and M. The metal in the BM has not experienced the thermal cycle and almost does not have microstructure transformation. As shown in Figure 14f, the microstructure is still composed of F and P.
## 5 Implementation and Results
### Experimental Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Fruit/Vegetable** & **Accuracy (\%)** & **ER (\%)** & **PPV (\%)** & **TNR (\%)** & **TPR (\%)** & **F1 Score** \\ \hline
1 & Brown onion & 99.47 & 0.53 & 96.00 & 99.71 & 96.00 & 0.960 \\
2 & Carrot & 99.73 & 0.27 & 98.00 & 99.86 & 98.00 & 0.980 \\
3 & Cauliflower & 99.47 & 0.53 & 100.00 & 100.00 & 92.00 & 0.958 \\
4 & Continental cucumber & 99.73 & 0.27 & 100.00 & 100.00 & 96.00 & 0.980 \\
5 & Creme potato & 99.07 & 0.93 & 90.57 & 99.29 & 96.00 & 0.932 \\
6 & Drumhead cabbage & 98.40 & 1.60 & 85.19 & 98.86 & 92.00 & 0.885 \\
7 & Granny Smith apple & 99.47 & 0.53 & 96.00 & 99.71 & 96.00 & 0.960 \\
8 & Iceberg lettuce & 98.53 & 1.47 & 88.24 & 99.14 & 90.00 & 0.891 \\
9 & Lady finger banana & 99.87 & 0.13 & 100.00 & 100.00 & 98.00 & 0.990 \\
10 & Mandarin & 97.73 & 2.27 & 83.67 & 98.86 & 82.00 & 0.828 \\
11 & Navel orange & 97.60 & 2.40 & 80.77 & 98.57 & 84.00 & 0.824 \\
12 & Packham pear & 99.60 & 0.40 & 97.96 & 99.86 & 96.00 & 0.970 \\
13 & Pink lady apple & 99.60 & 0.40 & 100.00 & 100.00 & 94.00 & 0.969 \\
14 & Strawberry & 99.60 & 0.40 & 97.96 & 99.86 & 96.00 & 0.970 \\
15 & Tomato & 99.70 & 0.93 & 90.57 & 99.29 & 96.00 & 0.932 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Classification metric comparison for AdaBoost-optimised CNN based fruit and vegetables classification.
## 2 Materials and Methods
### HS-SPME and GC-MS Analysis for Cyclic Monoterpenes  
After two weeks of light treatment, the second and third leaves (total four leaves) were harvested by cutting the petiole and weighed. The first leaves newly emerged during the 2-week LED treatment, and the size of the leaves was small and immature. To observe the effect of the LED supplements on expanded leaves, we decided to use the second and third leaves for further analyses. The analysis of a volatile compound with the head-space solid phase microextraction (HS-SPME) method was adapted from a previous report [17]. The leaves were then frozen with liquid nitrogen and ground finely with a pre-cooled pestle and mortar. The ground powder was put into 2 mL of 2 M CaCl\({}_{2}\cdot\)H\({}_{2}\)O solution in a head-space 20-mL glass vial (Supelco/Sigma-Aldrich, Tokyo, Japan) to prevent unnecessary enzymatic reactions. The tightly sealed vials were incubated in a hot bath at a temperature of 40 \({}^{\circ}\)C for 5 min. An SPME fiber coated with 60-um-thick PDMS/DVB (polydimethylsiloxane/divinylbenzene, Supelco) was inserted into the head-space through the vial septum, and the volatile released from the warmed solution was absorbed. The fiber was removed from the vial and inserted quickly into the inlet of a gas chromatography-mass spectroscopy (GC-MS) system (GC-17A, Shimadzu, Kyoto, Japan) with a polyethylene glycol column (60 m long, 0.25 mm internal diameter, 0.25 um film thickness; GL Sciences, Tokyo, Japan). The temperature of the inlet was held at 180 \({}^{\circ}\)C with a 9:1 split. Helium was used as the carrier gas at a 2 mL/min flow rate, 245.9 kPa. The starting oven temperature was 100 \({}^{\circ}\)C, followed by an 8 \({}^{\circ}\)C/min ramp until 180 \({}^{\circ}\)C was reached and held for 2 min. The interface to the mass spectrometer was held at 250 \({}^{\circ}\)C. The mass spectrometer was run in the scan mode with electron impact ionization at 1 keV, from \(m/z\) 40 to \(m/z\) 300. Compounds were identified using the National Institute of Standard and Technology Mass Spectral Database (NIST12). The GC-MS analyses of terpen were conducted independently six times in different LED lightning treatments.
## 2 Results
### Transcriptome Results  
#### 2.4.1 Construction and Analysis of the Transcriptome Library  
As obtained via Illumina sequencing (Illumina Novaseq 6000), transcriptome sequencing data are summarized in Table 1. The WT group (CC-125), C18 group and P1 group generated approximately 42.49-51.82 million raw reads. Fastp (version 0.19.7) was used to filter the raw data, obtaining more than 39.19 million clean reads. The scores of Q30 in nine samples' libraries were over 89.27%, indicating that all of the libraries were clean, high-quality reads. The 'Total map' scores were between 82.86% and 95.08%, and the 'Unique map' scores were between 80.43% and 92.72%. The WT group showed an overall stronger alignment than C18 and H1 did.  
There was a good correlation of gene expression (R\({}^{2}\) > 0.968 for the WT, R\({}^{2}\) > 0.891 for C18 and R\({}^{2}\) > 0.82 for P1) among the biological replicates of the three groups, indicating the reliability of the biological replicates (Figure 5a). As obtained via performing PCA (principal component analysis) on the gene expression values (FPKM) of all samples, Figure 5b shows that samples are more dispersed between groups and that samples within groups cluster as closely as possible. As can be seen from the PCA plot, the WT group is more distant from C18 and P1, while C18 was relatively close to P1, indicating that the gene expression levels of these two groups were similar to some extent.
# Image Scanning Microscopy to Investigate Polycomb Protein Colocalization onto Chromatin
## 3 Results and Discussion
### Colocalization by ISM  
Colocalization studies were carried out in PR-ISM and ISM\({}^{++}\) modes targeting single nuclei. Notably, color-merged images already posited the existence of actual colocalization between EZH2 and all its partners (Figure 3).  
This colocalization was quantified by the Pearson coefficient \(R\), which measures the correlation between the intensities of the two fluorescent partners in each pixel as a proxy of their functional association. As complexes are composed by an integer number of associated subunits, we shall refer to \(R\) as a measure of the strength of \"stoichiometric relationship (or correlation)\" between the two partners. Ideally, two partners that engage always in the same complex have a perfect stoichiometric relationship; i.e., their amounts are always found in a fixed ratio and \(R\) = 1. Incomplete engagement in the complex (for instance due to the presence of isoforms) leads to \(R\) < 1.  
\(R\) was calculated by applying the thresholding method of [PERSON] [26], which is known to remove the removes the bias of _visual interpretation_, and it was moderately positive for all protein couples (Figure 4). The statistical significance (\(p\) > 0.05) of these values with respect  
Figure 2: Confocal, PR-ISM, and ISM\({}^{++}\) images of an HCC827 nuclei immunolabeled by RING1b. All images were rescaled to the same digital level interval (0–2000) for better comparison. Scale bar: 10 \(\upmu\)m.  
to the random spatial overlapping of the two signals was assessed by the [PERSON] statistical test on colocalization [18]. Notably, ISM\({}^{++}\) super-resolved images were characterized by slightly lower \(R\) values than PR-ISM. This could be attributed to the colocalization overestimation effect due to the lower resolution of PR-ISM [29]. Alternatively, ISM\({}^{++}\) could underestimate colocalization owing to a working region's size of the protein complexes over chromatin, to which the spacing effect of antibody labels (20-30 nm) must be added, exceeding the resolution of the technique (-100 nm).  
Overall, these data support a model where PRC1 and PRC2 have a moderate stoichiometric relationship at mesoscale, i.e., suggesting that the activity of PRC1 and PRC2 is partially concomitant in space and time. The slightly higher colocalization values found for EZH/RING1b over EZH2/BMI1 (Figure 4) might suggest a stronger stoichiometric correlation (and spatio/temporal overlap) between vPRC1 and PRC2 as compared to cPRC1. Interestingly, a recent elegant study addressing PRC1 dynamics by single-particle tracking has revealed that only a minor (20%) fraction of PRC1 is stably bound to chromatin [30]. This highly dynamic nature of PRC1 could be at the basis of the observed incomplete functional colocalization between PRC1 and PRC2.  
Figure 3: PR-ISM images of HCC827 nuclei immunolabeled by EZH2/RING1b (**upper row**), EZH2/BMI1 (**central row**), and EZH2/H3K27 me3 (**lower row**). For all images, the background was subtracted by a rolling ball algorithm. Scale bar: 10 μm.
# A Survey on Physical Layer Techniques and Challenges in Underwater Communication Systems
## 5 Discussion
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Techniques** & **Mapper** & **Bandwidth** & **Symbol** & **Communication** & **Data Rate** & **Carrier** & **Doppler** \\  & & & **Duration** & **Distance** & & **Frequency** & **Spread** \\ \hline CP-OFDM [2] & PAM & 5 kHz & 0.25 ms & 20 m & - & 12.5 kHz & 0.2 \\ TDS-OFDM [10] & QPSK & 6 kHz & 170.67 ms & 967 m & 11.99 Kbps & 20 kHz & 0.2 \\ UW-OFDM [11] & QPSK & - & 0.25 ms & 150 m & 8 Kbps & 23 kHz & \\ ZP-OFDM [67] & QPSK & 12 kHz & - & - & - & 27 kHz & 0.4 m/s \\ OFDM [69] & BPSK & 10 kHz & - & 500, 1500 m & - & - & 10 Hz \\  & & & 42.67 ms, & 7.0 Kbps, & & & \\ ZP-OFDM [71] & QPSK & 12 kHz & 853.3 ms, & 150, 400 m & 8.6 Kbps, & 27 kHz & 5.86 Hz \\  & & 170.67 ms & & 9.7 Kbps & & & \\ MIMO-OFDM [73] & QPSK, QAM & 12 kHz, & 85.33 ms, & 500, 1500 m & 125.7 Kbps & - & 2 Hz \\  & & 4.88 kHz & 209.71 ms & & 2.86 Kbps, & & \\  & & & & 4.29 Kbps, & & & \\ OFDM [78] & BPSK, QAM, & 3 kHz, 6 kHz, & 209.7152 ms & 500 m & 5.72 Kbps, & & \\  & & & & & 8.59 Kbps & & \\  & & & & & 798.7 bps, & 13, 11 kHz & 9.54, 5.86 Hz \\ OFDM, ZP-OFDM [79] & QAM, QPSK & 9.77, 5 kHz & 170.7 ms & - & 104.4 Kbps & - & 0.1, 1 Hz \\  & & & & & 6.5 Kbps, & & \\  & & & & & 6.2 Kbps, & 13 kHz & 0.54 Hz \\  & & & & & 5.96 Kbps & & \\  & & & & 2.7 Kb/user/s, & & \\  & & & & 5.2 Kb/user/s & & \\  & & & & 5.2 Kb/user/s & & \\  & & & & 5.2 Kb/user/s & & \\  & & & & & 2.7 Kb/user/s & & \\  & & & & 5.2 Kb/user/s & & \\  & & & & & 5.2 Kb/user/s & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\  & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Some notable key contributions of physical layer UWAC technologies.
## 5 Noise-Corrected Clustered-Sparse Channel Estimation
### Data Detection and Noise Measurement
The decisions on the data symbols, \(\mathbf{x}_{\mathbf{d}}^{(m)}\), are obtained by mapping the soft decisions, \(\widehat{\mathbf{x}}_{\mathbf{d}}^{(m)}\), to the closest point on the constellation, meaning that:  
\[\mathbf{x}_{\mathbf{d}}^{(m)}=Quantization\Big{(}\widehat{\mathbf{x}}_{\mathbf{ d}}^{(m)}\Big{)}. \tag{37}\]  
Although the noise distribution is non-uniform, the noise powers of adjacent subcarriers are usually close (especially when the number of subcarriers is large). Then, we divide all subcarriers into non-overlapping \(Q\) groups, so that \(K/Q\) subcarriers can be grouped into the same one.
# Drilling Fluid and Cement Slurry Design for Naturally Fractured Reservoirs
## 5 Lost Circulation While Cementing through Naturally Fractured Reservoirs
### Cement Slurry and Set Cement Properties
#### 5.1.1 Cement Slurry Density
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Category** & **Composition** & **Mechanism of Reaction** \\ \hline \multirow{4}{*}{(Benefit: lower slurry yield)} & Bentonite & Absorption of water \\ \cline{2-3}  & & Sodium silicates & Formation of C-S-H gel and absorption of water \\ \cline{2-3}  & \multirow{2}{*}{Pozzolans (Diatomaceous earth, Fly ash, Fume silica)} & \\ \cline{2-3}  & & Gilsonite & Lower density than cement \\ \cline{2-3}  & & Powdered coal & \\ \cline{2-3}  & & Microspheres & \\ \cline{2-3}  & & Nitrogen & Foamed cement \\ \hline \multirow{4}{*}{**Lost-circulation control agent** (Benefit: prevent loss of slurry to formation)} & Gilsonite & \\ \cline{2-3}  & \multirow{2}{*}{Granular coal} & \multirow{2}{*}{Bridging effect across formation} \\ \cline{2-3}  & & Cellophane flake & \\ \cline{2-3}  & & Nut Shells & \\ \cline{2-3}  & \multirow{2}{*}{Fibrous Additives} & \\ \cline{2-3}  & & Gypsum & \\ \cline{2-3}  & & Soluble sulfate salts & Induce thixotropic behavior of cement slurry \\ \cline{2-3}  & \multirow{2}{*}{Bentonite} & \\ \cline{2-3}  & & Crosslinked cellulosic polymers & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Cement slurry additives—extenders and lost circulation control agent modified to [44]. they can withstand without them crushing because if this pressure is exceeded, it will result in breaking a percentage of the microspheres and a higher slurry density after placement. Ceramic hollow microspheres are added to cement slurries (expressed as By Weight Of Cement (BWOC)) to reduce slurry density to low levels where water in combination with conventional extenders fail to achieve the required properties. A cement slurry prepared using cencospheres is a stable system and the set cement properties show relatively high compressive strength values, low permeability, hence, a high resistance to acid and brine attacks. Unfortunately, high bottom-hole pressure might crush the conventional cencospheres which results in an increase of slurry density in down-hole conditions so the acceptable criteria for this breaking percentage are recommended to have 35% to 45% of the total cencospheres used in the cement slurry [100; 104]. The high-performance hollow glass microspheres provide excellent advantages since they are light weight, they decrease thermal conductivity, increase compressive strength, improve dispersion and liquidity, and they have excellent chemical stability. They can be used as fillers in well cementing to achieve an ultra-light weight slurry with a density as low as 840 kg/m\({}^{3}\)[44]. The minimum achievable density of a cement slurry by common extenders is shown in Table 7.
# Detection of Quasi-Static Trapped Human Being Using Mono-Static UWB Life-Detection Radar
## 3 Experimental Results
### Experimental Results for Scanning Operating Mode
#### 3.2.3 The Ruins Experiment  
In the actual ruin scene shown in Figure 16, detecting the tested human subject buried by real ruins and debris is carried out in the China National Training Base for Urban Search and Rescue. Two Golay-coded radars are placed on the third floor with the interval of 2 m. The tested human subject lies on the first floor while breathing weakly and quasi-periodically. The distances between him and the No. 1 and No. 2 radars are 3.7 and 3.59 m, respectively. There are various bricks, metals and woods in the test environment, especially on the second floor.  
Figure 16: Ruin scene for quasi-static human being detection in scanning operating mode.  
Figure 15: The experiment C result. (**a,b**) The output range-frequency images using the normal FFT-based respiration detection methods using the echoes from a single radar. (**c**) The output two-dimensional (2D) slice (range \(\times\) range) image for the specific respiration frequency. (**d**) The positioning result calculated by the radar system is compared with the actual position of the person.  
For the scanning operating mode, the UWB life-detection radar was placed on two different observation points. The VSF might not be found using the FFT results for the first (Figure 17a) and second (Figure 17b) observation points. However, as the quasi-periodic characteristic, the proposed detection method for scanning operating mode gives the workable result, which makes the subsequent VSF decision easy (Figure 17d). The range locations of D1 = 3.66 m and D2 = 3.60 m corresponding to the first and the second observation points are consistent with the actual situation.
## 2 Methods
### Selection of Evaluation Objects and Data Sources  
Based on the current geographical distribution of CEE countries, 16 countries were selected for evaluation after considering the potential placement of China's outward investment in agriculture in terms of reality, resources and policies. The 2009-2018 basic data are mainly from authoritative data published by the World Bank, the World Economic Forum and International Telecommunication Union. Among them, C1, C2 and C5 are drawn from the World Bank's World Governance Indicators; C6 from the World Bank database; C16 and C17 from the World Bank's Doing Business report; C22 from the International Telecommunication Union's Measuring the Information Society report; and the rest from the World Economic Forum's Global Competitiveness Index indicators.
# On-the-Fly Repairing of Atomicity Violations in ARINC 653 Software
## 4 RAV: Repairing Atomicity Violations  
This section describes the details of repairing AV (RAV; Repairing Atomicity Violation), an on-the-fly repairing tool for atomicity violations in ARINC 653-based airborne software. First, we describe the procedure of the repairing operation of RAV in ARINC 653. Then, we describe the improved version of the AI (anticipate invariant) algorithm, which is called embedded AI (eAI). It is designed to be applicable to embedded systems. Then, we describe how RAV fits into the ARINC 653 health monitor system to repair atomicity violations in ARINC 653 application.
# A Novel UCP Model Based on Artificial Neural Networks and Orthogonal Arrays
## 3 New, Improved UCP--Our Approach  
For the new, improved UCP model, the following architectures and corresponding orthogonal vector plans are used:  
1. UCP and ANN-L16  
The first proposed architecture is denoted as ANN-L16. It consists of six input values, one hidden layer with two nodes, one output, and a total number of fifteen weighting factors (\(W_{i}\), \(i=\overline{1,\,15}\)), whose initial values are from the interval [-1, 1]. The Taguchi Orthogonal Array used in the construction of this proposed architecture contains two levels, L1 and L2 (Figure 1; Table 1) [2,3,30,31].  
UCP and ANN-L36 prim  
The second proposed architecture is denoted as ANN-L36 prim. It consists of four input values, one hidden layer with three nodes, one output, and a total number of sixteen weighting factors (\(W_{i}\), \(i=\overline{1}\), \(\overline{16}\)), whose initial values are from the interval [\(-1\), \(0\), \(1\)]. The Taguchi Orthogonal Array used in the construction of this proposed architecture is combined, where the first eleven parameters and the last sixteenth parameter are with three levels, L1, L2, and L3, while the remaining four parameters are with two levels, L1 and L2 (Figure 2; Table 2) [2,3,30,31].  
The experiment presented in this paper consists of three parts:  
1. Training of two different ANN architectures constructed according to the corresponding Taguchi orthogonal vector plans (ANN-L16 and ANN36 prim);
2. Testing of the ANN that gave the best results (the lowest MMRE value) in the first part of the experiment, for two proposed architectures on the same dataset;
3. Validation of the ANN that gave the best results (the lowest MMRE value) in the first part of the experiment, for each selected architecture, but using different datasets.