esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Method and Materials
### Filter Sample Analysis  
Collected PM filter samples were analyzed for nitrogen and carbon among the low-volatile water-soluble organic components in PM from noyaki. The details of the analytical procedure were described elsewhere [30]. Briefly, filter samples were submerged in 15 mL Milli-Q water (Milli-Q Integral 3, Merck KGaA, Darmstadt, Germany) and then sonicated for 15 min. The water-soluble component was transferred to a 100 mL evaporation flask (COSMOS VID). The sonication procedure was repeated twice with an additional 10 mL of Milli-Q water. All extracts were combined in the evaporating flask. The volume was reduced to approximately 0.2 mL, then transferred to a conically shaped microbial (GL Science, Osaka, Japan). Further volume reduction to 0.2 mL was completely by gently blowing the extract in the vial (GL Sciences) with pure nitrogen gas. A certain volume of each concentrated extract was then pipetted into a tin cup (Ludi Swiss AG, Flawil, Switzerland), together with a drop of 0.1 M hydrochloric acid solution, then the sample solution was dried under a gentle stream of pure nitrogen to produce residual low-volatile water soluble nitrogen (LV-WSN) and organic carbon (LV-WSOC). This extract was subjected to quantitative and isotope analyses.  
Quantities of nitrogen and carbon in LV-WSN and LV-WSOC and \(\delta^{13}\)C of LV-WSOC were analyzed by an elemental analyzer (EA; Flush EA 1112, Thermo Fisher Scientific GmbH) coupled with an isotope ratio mass spectrometer (IRMS; Delta Plus, Thermo Fisher Scientific GmbH). The stable carbon isotope ratio in delta expression for \(\delta^{13}\)C is defined as follows:  
\[\delta^{13}\text{C (\%_{\text{e}})}=\left[\frac{\left(\frac{{}^{13}\text{C}}{ \text{C}}\right)_{\text{sample}}}{\left(\frac{{}^{13}\text{C}}{\text{C}} \right)_{\text{VPDB}}}-1\right]\times 1000 \tag{2}\]  
where the bracketed isotope ratios with subscripts \"sample\" and \"VPDB\" indicate the stable carbon isotope ratios for the sample and the reference Vienna Pee Dee Belemnite, respectively. The minimum quantities for stable nitrogen and carbon isotope analysis were 50 \(\mu\)gN and 20 \(\mu\)gC, respectively. For radiocarbon (\({}^{14}\)C) analysis, LV-WSOC extracts sampled on the same day were combined to have sufficient carbon. The LV-WSOC samples were converted to graphite, and the ratio of \({}^{14}\)C to \({}^{12}\)C was analyzed using an acceleration mass spectrometer (AMS; Pelletron 1.5 SDH-1, National Electrostatic Corp., Middleton, WI, USA). The overall minimum carbon quantity required for \({}^{14}\)C analysis was 300 \(\mu\)gC. Here, the \({}^{14}\)C ratio (\({}^{14}\)C/\({}^{12}\)C) of the samples was relative to that of SRM 4990c (NIST, Gaithersburg, MD, USA) and was reported in percent modern carbon (pMC) with and without \(\delta^{13}\)C corrections.  
Naturally dried plant samples were cut into small pieces, vacuum dried, and ground to powder using a multi-bead shocker ([PERSON], Osaka, Japan). Then 0.1-0.2 mg of the powder was put into a tin cup (Ludy Swiss AG) and analyzed by EA-IRMS for \(\delta^{13}\)C.
# Research Progress in the Flight Characteristics of Flyers Driven by Different Technologies
## 3 Research Progress in Flyer Velocity
### Two-Dimensional (2D) VISAR
#### 3.1.10 Electric Probe Method  
As shown in Figure 19, the front end face of the flyer successively connects two probes with a spacing, which causes the discharge circuit to generate the signal output. The flyer speed can be obtained by interpreting the time interval between the two signals on the timing instrument.  
The electric probe device is simple and convenient for on-site installation. However, it is still difficult to complete high-precision measurements for special-shaped flyers and non-metallic flyers. The contact measurement also affects the effective impact area of small-diameter flyers. In addition, when the environment medium is hydrogen, the hydrogen escaping to the front end of the flyer makes it easy to ionize the residual air at the tip of the charged probe, causing the probe to conduct ahead of time.  
[PERSON] et al. used multi-channel VISAR and electric probes to monitor the free-surface velocity history of a metal flyer driven by detonation in order to verify experimental results and analyze test system parameters affecting measurement precision [55].  
The aforementioned velocity measurement technologies are compared in Table 2.  
Figure 19: Schematic diagram of electric probe method.  
Most of the current flyer velocity measurement technologies are discussed, and each of them has clear advantages and disadvantages. In practical applications, researchers in a certain field are usually restricted by some measurement methods, which may be due to low measurement requirements, limited funding, or information asymmetry. This paper may lay the foundation for breaking the information asymmetry.  
The development of the flyer velocity investigation technology mainly depends on measurement requirements. Some research, such as detonation reaction zone structure measurement, requires high spatial and temporal resolution; however, other research focuses on low cost and simple operation. In the future, a technical library of surveying velocity may be established and improved with the emerging measurement needs in fundamental research and application fields.
## 4 Discussion
### Improvement of Measuring Techniques for the Past 10 Years
With the development of the computer-aided design and computer-aided manufacturing (CAD-CAM) industry, the laser scanning technique has become popular as it is simple and easy to use. In line with this development, various types of scanners were introduced, and there are many studies that tested the accuracy and validity of the scanners. Some studies [32; 33; 39; 40; 45] have proven that this measuring technique is valid and reliable in determining the residual limb volume. The handheld scanners such as TT Design, Omega Scanner, BioSculptor Biosconsanner, Radin4D Scanner, Artec Eva scanner, VIUscan marker-assisted laser scanner, GoSCAN 3D structured white scanner, and Sense 3D markerless laser scanner that were used in the studies have shown small mean percentage errors (less than 2%) [45]. This laser scanning technique was also compared with other measuring techniques such as the water displacement, anthropometric measurement, and optical scanning techniques [32; 33], and these studies discovered that the laser scanning technique had the lowest repeatability coefficient [32], which indicates that this technique has the best reliability. The laser scanning technique is also user-friendly as it does not involve any contact with the residual limb while the scanning process is conducted. Also, it takes less time to scan the limb (60-240 s) [39], and the scanning method is easy to learn (based on Post-Study System Usability Questionnaire) [40]. Comparing these with the years before 10 years ago, fewer studies focused on this technique. During that time, there was no usage of a handheld scanner in the research, and the residual limb measuring apparatus was complicated and not portable [30; 43; 44]. The measuring device may have caused difficulty to the subjects as they had to sit or stand on the measuring device, and the measurement results may have been affected by subject movement as well as the post-doffing effect, which would give a wrong interpretation of the measured volume as the subjects needed some time to stand or sit on the measuring device. Even though these techniques (during that time) applied quite a large and unportable measuring apparatus, studies still showed that this technique (CAPOD System) had lower random and systematic errors compared to the optical scanning technique (ShapeMaker) [30]. Thus, the findings prove that the laser scanning technique was reliable to use and gave good results. Other techniques seem to be less popular for the past 10 years' publications, with only one article published for water displacement, anthropometric measurement, and optical scanning, while no publication was found for other techniques (contact probes, SXCT, MRI, and ultrasound). Some factors that may contribute to these unpopular techniques include less sensitivity of the devices used in the techniques, less accurate results due to the post-doffing effect, difficult positions of the subjects, techniques that involve contact with the residual limb until they cause distortion to the residual limb, cost, and complicated setups.
## 2 Research Background
### Mining Area Overview  
The main coal area of the 5 th coal seam is zone F, which includes the backfill working face under consideration in this study. At a ground elevation of +17 m and an underground elevation ranging from \(-\)582 to \(-\)709 m, the working face is characterized by an average coal seam thickness of 2.5 m and an inclination angle of 13\({}^{\circ}\). It extends over an inclination length of 65 m and an impressive strike length of 652 m. The backfill work face adopts an inclined filling mining face using the upward-mining method. The mining requirements of the backfill working face are to protect the buildings and railway tracks on the surface of the mine. Figure 1 depicts the location and layout of the backfill working face beneath Tangshan City. An overview of the layout parameters of the backfill working face is presented in Table 1.  
\begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Conditions** \\ \hline Production time & November 2017–December 2018 \\ Coal seam condition & Under wellbore and surface structures \\ Ground elevation & +17 m \\ Depth & \(-\)582 to \(-\)709 m \\ Inclination angle & 13\({}^{\circ}\), inclined upward mining \\ Coal seam height & 2.0–2.5 m \\ Coal seam structure and stability & Simple and complex \\ Backfilling system & Full mining and full backfilling \\ Face length & 65 m \\ Strike length & 652 m \\ Coal production/ton & 178,524 \\ Gangue filling/ton & 231,416 \\ Filling ratio & 1:1.30 \\ Control effect of stop pressure and surface subsidence & Higher \\ Mine pressure control requirements & Compacting rate \textgreater{} 80\% \\ Mining and backfilling step/day & 5 m \\ Backfilling efficiency ton/hour & 64.35 \\ \hline \end{tabular}
\end{table}
Table 1: Overview of the backfill working face’s layout parameters.
## 2 Measurements
### Instruments  
The instrumentation employed for measurement is illustrated in Figure 2, comprising a JM3873 wireless data acquisition system (Figure 2a) and 941B accelerometers (Figure 2b).  
Prior to conducting field measurements, all wireless units were time synchronized through a laptop connected to a wireless gateway placed side-by-side. Subsequently, the wireless units were left operational to ensure synchronization among them and securely mounted at their respective measurement locations. The potential concerns regarding interference and blockage issues were mitigated during the measurement process by avoiding the transmission of internally sampled/stored time signals. Subsequently, upon completion of the measurements, the time-synchronized data were retrieved from each wireless unit.  
The wireless units were configured with a sampling frequency of 512 Hz, enabling spectral analysis up to the Nyquist frequency of 256 Hz. It should be noted that the dominant frequency range of train-induced floor vibration in this study was found to be below 80 Hz. More details about the measuring instruments and signal processing can be found in the reference [7].  
Figure 1: View of the measurement area. (**a**) Over-track building; (**b**) setup in the building; (**c**) train operation area; (**d**) setup in the track area.  
Figure 2: Instruments of measurement. (**a**) JM3873 system; (**b**) 941B accelerometer.
# FrameAugment: A Simple Data Augmentation Method for Encoder-Decoder Speech Recognition
## 4 Results
### Augmentation Range  
Since the proposed method changes the speed of some sections of an utterance, we used the degree of augmentation according to the range of the augmentation section. We experimented with changing the maximum number of frames to find the parameter showing the optimal performance. In addition, experiments were conducted when the proposed augmentation method was repeatedly applied while the sections did not overlap. If the augmentation range \(n\) was longer than the length of the utterance, the entire utterance was augmented. Table 1 shows the experimental results for the WSJ database.  
When the maximum augmentation range \(N\) is 500 frames, it shows the highest performance on average in the validation data. Repetition of the augmentation method did not significantly affect the recognition performance. Figure 6 is the graphical plot corresponding to Table 1.  
The average frame length of the WSJ database is about 900 frames. Performance was best at 500 frames; thus, the performance was best when it was about 60% of the utterance length on average. Table 2 shows the experimental results for the LibriSpeech database.  
Figure 5: Method of calculating replacement frames. The red cross indicates replacement frame values and the black bullet indicates original frame values when \(s=\frac{6}{10}\), respectively.  
The average frame length of the LibriSpeech database is about 1500 frames. Performance was best at 1200 frame; thus, the performance was best when it was about 80% of the utterance length on average.  
\begin{table}
\begin{tabular}{c c c c} \hline \(N\) & **Number of Repetitions** & **Dev93** & **Eval92** \\ \hline
0 & 0 & 7.88 & 5.02 \\
100 & 1 & 7.81 & 4.78 \\
100 & 2 & 7.35 & 4.86 \\
200 & 1 & 7.27 & 4.45 \\
200 & 2 & 7.51 & 4.91 \\
300 & 1 & 7.66 & 5.07 \\
300 & 2 & 7.27 & 4.43 \\
400 & 1 & 7.55 & 4.27 \\
400 & 2 & 7.20 & 5.05 \\
500 & 1 & 7.03 & 4.75 \\
500 & 2 & 6.97 & 5.00 \\
600 & 1 & 7.25 & 4.73 \\
600 & 2 & 7.31 & 5.12 \\
700 & 1 & 7.49 & 4.50 \\
700 & 2 & 7.26 & 4.92 \\ \hline \end{tabular}
\end{table}
Table 1: WER (%) results of WSJ database according to the maximum augmentation range \(N\) when \(s\sim\text{Uniform}[0.9,1.1]\).  
\begin{table}
\begin{tabular}{c c c} \hline \(N\) & **Dev-Clean** & **Test-Clean** \\ \hline
0 & 6.62 & 7.33 \\
200 & 6.71 & 7.44 \\
400 & 6.74 & 7.37 \\
600 & 6.28 & 7.01 \\
800 & 6.46 & 7.12 \\
1000 & 6.31 & 6.95 \\
1200 & 6.26 & 6.96 \\
1400 & 6.61 & 7.16 \\ \hline \end{tabular}
\end{table}
Table 2: WER (%) results of LibriSpeech database according to the maximum augmentation range \(N\) when \(s\sim\text{Uniform}[0.9,1.1]\).  
Figure 6: WER results of WSJ database according to augmented frame range. The horizontal axis denotes the maximum augmentation range and the vertical axis denotes WER.  
Through the results of the LibriSpeech and the WSJ database, the recognition result did not change according to the absolute number of frames, but according to the ratio of the augmentation section in the utterance.
## 3 Challenges for Routing Protocols in FANETs
### Low Latency and Enhanced QoS  
Due to the high speeds at which information must be transferred, search and rescue operations, surveillance, and disaster monitoring have a low-latency requirement. As a result, selecting the best routing protocol for minimizing latency and enhancing QoS in UAV networks is critical. As discussed in [PERSON] et al. [80], route discovery and route maintenance must minimize latency. Priority schemes are a technique that can be utilized in UAV networks to control and minimize delay [81]. Distributed priority-based routing protocols can also be used to regulate the quality of service (QoS) for different types of messages [82; 83]. Controlling packet collisions and traffic congestion effectively is also an important consideration for reducing latency in the network, such as FANETs.
Remote Sens._**2015**, \(7\), 8705-8727; doi:10.3390/rs70708705  
_remote sensing_  
**ISSN 2072-4292**  
www.mdpi.com/journal/remotesensing  
Detecting Change Dates from Dense Satellite Time Series Using a Sub-Annual Change Detection Algorithm  
**[PERSON] and [PERSON] ***  
Department of Geography, The Ohio State University, 1036 Derby Hall, 154 North Oval Mall,  
Columbus, OH 43210, USA; E-Mail: [EMAIL_ADDRESS]  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS];  
Tel.: +1-614-247-2775; Fax: +1-614-292-6213.  
Academic Editors: [PERSON] and [PERSON]  
_Received: 20 April 2015 / Accepted: 2 July 2015 / Published: 9 July 2015_  
**Abstract: Multi-temporal satellite images are available at very high revisit frequency, allowing the characterization of land-cover transitions and trajectories in greater detail. However, most change detection methods aim to capture a snapshot of land cover, for instance on an annual scale, which do not describe changes that occurred between the annual time points. In this study, we present a sub-annual change detection (SCD) approach to detect change dates from dense satellite time series. SCD estimates change dates by analyzing differences between two consecutive annual segments in two steps. To validate the proposed method, SCD was applied to real and simulated time series of MODIS 16-day NDVI from 2000 to 2012 for MODIS tile h11v05 and a sub-area in southeast Ohio, USA. The results show that SCD can successfully detect from dense time series the dates of changes representing land-cover transitions among various vegetated land covers. In addition, SCD can achieve comparable accuracy on the date of abrupt land-cover changes for the real time series tested in the study area when compared with the trend and seasonal changes identified by a Breaks for Additive Seasonal and Trend (BFAST) method. Future effort will be given to apply the proposed approach to various remotely sensed time series for other areas with extreme climates.**  
**Keywords: change detection; land cover; sub-annual; time series; NDVI; MODIS**
## 3 Results and Discussion
### Consumer Evaluation  
The average consumer ratings of the bread from the individual parameters were similar in each sample and were not statistically significantly different from each other (Table 5). The control and enriched bread received similar overall ratings and were of good quality, according to consumers. The control bread received an overall score of 3.96, the bread in which 10% of the water was replaced with prepared _Calendula officinalis_ water extract received 4.02, and in the case of 15% replacement of water with extract 3.94. The results show that the addition of _Calendula officinalis_ water extract used in the experiment had no significant effect on the organoleptic properties of the bread.  
The attractiveness of bread consists of many different characteristics, but the first to attract the consumer's attention is external appearance and colour. Edible flowers or extracts from them can be an interesting alternative to artificial colours used in food technology [54]. The obtained _Calendula officinalis_ extract was brown, but the amount of additive used was low enough that it did not significantly change the colour of the finished product. The addition of plant extracts rich in phenolic compounds, which aim to increase the antioxidant capacity of wheat bread, can also affect certain rheological properties of the dough, such as gumminess, strength, elasticity, adhesiveness, and chewiness, among others [1]. As a result, the sensory properties of the final product are also modified, which is not always acceptable to consumers. For example, in a study by [PERSON] et al. [51], according  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Evaluation Parameters** & **Control** & **N10** & **N15** \\ \hline \multirow{3}{*}{Crust} & \multirow{3}{*}{\
\begin{tabular}{l} Appearance and connection \\ with the crumb \\ \end{tabular} } & 4.14 \(\pm\) 0.64  & 4.10 \(\pm\) 0.72  & 4.00 \(\pm\) 0.76  \\ \cline{2-4}  & \multirow{3}{*}{
\begin{tabular}{l} Appearance and connection \\ with the crumb \\ \end{tabular} } & 4.10 \(\pm\) 0.62  & 4.09 \(\pm\) 0.70  & 4.00 \(\pm\) 0.89  \\ \cline{2-4}  & Color & 4.10 \(\pm\) 0.77  & 4.07 \(\pm\) 0.88  & 3.86 \(\pm\) 0.95  \\ \cline{2-4}  & Thickness & 4.14 \(\pm\) 0.74  & 3.93 \(\pm\) 0.88  & 4.14 \(\pm\) 0.79  \\ \hline \multirow{3}{*}{Crumb} & Appearance & 4.07 \(\pm\) 0.70  & 4.00 \(\pm\) 0.80  & 4.17 \(\pm\) 0.80  \\ \cline{2-4}  & Color & 3.93 \(\pm\) 0.80  & 4.14 \(\pm\) 0.83  & 4.14 \(\pm\) 0.95  \\ \cline{2-4}  & Porosity & 3.97 \(\pm\) 0.73  & 3.83 \(\pm\) 1.04  & 4.14 \(\pm\) 0.83  \\ \cline{2-4}  & Elasticity & 3.83 \(\pm\) 0.85 [FOOTNOto consumers, bread enriched with onion extract had a less acceptable smell and taste than the control bread. In the development of functional foods, a key role is played by finding ingredients that allow specific beneficial effects to be achieved without modifying the sensory properties of the enriched product. Therefore, the results obtained in the present study are significant and encourage further research into using _Calendula officinalis_ water extract for bread fortification.
# Road Crack Detection by Combining Dynamic Snake Convolution and Attention Mechanism
###### Abstract  
As one of the early manifestations of road pavement structure degradation, road cracks will accelerate the deterioration of the road if not detected and repaired in time. Aiming at the problems of low recall and incomplete crack detection in current road detection, based on the U-Net network, this paper proposed an Attention-Dynamic Snake Convolution U-Net (ADSC-U-Net) network. Firstly, the dynamic snake-shaped convolution was added to the normal downsampling process to make the network adaptively focus on the slender and curved local features, which can solve the problem of low accuracy of small crack detection. Secondly, the attention mechanism was used to pay better attention to the significant features of positive samples under the condition of a large proportion gap between positive and negative samples, which solved the problem of the poor crack integrity detection effect. Finally, the dataset was expanded by random vertical and horizontal flip operations, which solved the problem of network training overfitting caused by the small-scale datasets. The experimental results showed that, when the input image had a resolution of 480 \(\times\) 320, evaluation indices \(P\), \(R\), and \(F1\) of ADSC-U-Net on the self-built dataset were 74.44%, 68.77%, and 69.42%, respectively. Compared to SegNet, DeepLab, and DeepCrack, the \(P\) was improved by 1.90%, 2.49%, and 11.64%, respectively; the \(R\) was improved by 8.01%, 4.70%, and 59.58%, respectively; and the comprehensive evaluation index \(F1\) was improved by 5.73%, 4.02%, and 55.87%, respectively, which proves the effectiveness of the proposed method.  
crack detection; dynamic snake convolution; attention mechanism; CBAM; U-Net network; semantic segmentation +
Footnote †: journal: Applied sciences