esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Simulation of Underwater Electric Field Communication
### CSMA/CA Channel Backoff Algorithm Design and Simulation Analysis
#### 4.2.2 Launch Circuit Excitation Signal  
In underwater electric field multi-node communication systems, the most basic elements are baseband signals and carrier signals. This article proposes using a Raspberry Pi to generate baseband signals and carrier signals. Based on the Raspberry Pi 4B development board, which has six UARTs including four new PL011 UARTs compared to Raspberry Pi 0, 1, 2, and 3's dual UARTs. Firstly, due to the default closure of the other four UARTs in the Raspberry Pi system, the command \"sudo nano/boot/config.txt\" is used to configure UART 1 (ttyAMA1), where UART 1 corresponds to GPIO0 and GPIO1 for the read and  
Figure 9: CSMA/CA dynamic backoff process.  
write IO ports, respectively. By loading the Python-specific Serial library and configuring the UART through the serial.Serial() function, parameters such as baud rate, stop bits, and parity bits are set. The data packet is encoded and sent using serial. write(), and UTF-8 encoding and decoding are used in this article. Since the ultimate goal of this system is to achieve an AUV multi-node, the data packet mainly transmits the self-position coordinates. Other information that needs to be included is the frame header, local address, and redundancy code, as shown in Figure 10. The redundancy code is a single character that aims to adjust the PGA gain to an appropriate amplification factor by sending redundant information in advance to avoid signal distortion when the robot's position changes in real-time. The frame header is a fixed character \"99\" used to detect useful information in the data packet.  
For the 2 FSK communication system, the carrier signal is a 14 KHz PWM wave. In Raspberry Pi, pigpio is a library for controlling the General Purpose Input Output (GPIO). The pigpio library is suitable for all versions of Pi. Software-timed PWM is available on all GPIO 0-31, but since the carrier signal in this system reaches up to 14 kHz and software-timed PWM can only achieve a maximum of 1400 Hz, the hardware PWM of Raspberry Pi needed to be used. Raspberry Pi 4B has four output ports, with BCM12 and 18 as one group, and 13 and 19 as the other group. By calling the pi.hardware_PWM() function to configure the PWM frequency and phase, the hardware PWM of Raspberry Pi can be enabled.
## 3 Results
### Experimental Results  
#### 3.2.1 Dimensions of Weld Pools for Different Welding Positions  
By using the high speed imaging system, videos were taken for the weld pools when welding with flat and climbing welding positions. Images from the videos were processed to obtain the features (mainly dimensions in this study) of weld pools, as shown in Figure 10. The main steps of imaging processing include:  
1. Denoise through weighted average of gray levels of adjacent images.
2. Obtain weld pool profiles through image segmentation and derivation.
3. Calculate the lengths and widths of weld pools based the profiles and the calibration results of the high speed camera.  
Figure 10: Processing of images to obtain dimensions of weld pools: (**a**) an image captured; and (**b**) feature extraction of weld pools.  
Figure 9: Velocity fields in the weld pool for climbing welding (unit: m/s): (**a**) whole model; and (**b**) magnified melt pool region.  
Using the aforementioned algorithms, the variations of the lengths and widths of weld pools during climbing welding and flat welding were obtained, as shown in Figure 11. The weld pool lengths for climbing welding (start end of a weld) are about 12.9 mm, which are longer than the flat weld pool (at the finish end of the weld) with lengths varying within a range of 10-11 mm and averaged at 10.7 mm. The widths of the weld pools for climbing and flat welding positions are 10.7 mm and 10.3 mm, respectively.  
Table 5 lists the dimensions of weld pools obtained by CFD predictions and experimental measurements when welding 9.5 mm thick 2219 aluminum alloys with flat and climbing welding positions. Through comparison, it can be found the numerical predictions are in good agreement with the experimental observation, which validate the CFD numerical simulation model used in this paper. The model can take into account the influences of gravity action on the fluid flow of molten metal in weld pools, which enables it to analyze the effects of welding positions on the fluid flow behavior during welding reasonably.
# Simply Applicable Method for Microplastics Determination in Environmental Samples
## 2 Results and Discussion
### Method Applicability in Environmental Samples  
#### 2.2.1 Identification of MPs in the Polymer Blend and Fine Fraction (1 mm-100 \(\upmu\)m)  
With the use of the described identification method and procedure (see Sections 3.2-3.4), we were able to identify individual polymers from the polymer blend of coarse fraction (PET, PS, PVC, PP, and PE). PS, PVC, PP, and PE were identified through analysis after thermal decomposition at 220 \({}^{\circ}\)C for 3 min. PET was identified through analysis after an additional thermal decomposition at 220 \({}^{\circ}\)C for 12 min, 15 min altogether (Figure 6).  
Figure 5: HS-SPME/GC–MS extracted ion chromatogram (XIC, \(m/z\) 85) of PE (5 replicates). Arrow indicates pentadecane(8).  
Figure 6: Total ion chromatograms of polymer blend after thermal decomposition at 220 \({}^{\circ}\)C for 3 min and 15 min with extracted ion chromatograms of PS (3-styrene, 4 and 5-trans (cis)-1.2-diphenylcyclobutane, PVC (6-1-chlorocaten), PP (7-4.6-dimethyl 2-heptanone), PE (8-pentadecane), and PET (1-dimethyl terophthalate)).  
MPs with a size range between 1 mm and 100 um were found to melt faster, therefore thermal decomposition times were adjusted to 1 min for PS, PVC, PP, and PE, and to 3 min for PET. Identification of all MP polymer types was possible with the developed HS-SPME-GC-MS method and XIC comparison with MPs of coarse fraction that were analyzed beforehand (Figure S9). Peak intensities for PS, PE, and PP were in the same range as were particles ranging between 1 and 5 mm, while PVC and PET produced lower intensities of 1-chlorooctane and DMTP, respectively.
## 2 Materials and Methods  
To synthesize crystals and membranes in this work, all chemicals were used without further treatment, including Ludox(r) AS-40 (40 wt%, colloidal silica, Sigma-Aldrich, Steinheim, Germany), tetraethylorthosilicate (TEOS, 98 wt%, Merck, Darmstadt, Germany) and fumed silica (CAB-O-SIL(r) M5, Cabot, Frankfurt am Main, Germany) as sources of Si, aluminum hydroxide (Al(OH)\({}_{3}\), extra pure, ACROS organics, Geel, Belgium), aluminum isopropoxide (IPA, 99 wt%, Sigma-Aldrich, Steinheim, Germany) and sodium aluminate (NaAlO\({}_{2}\), ~45 wt% Na\({}_{2}\)O and ~55 wt% Al\({}_{2}\)O\({}_{3}\), Sigma-Aldrich, Steinheim, Germany) as Al sources, and sodium hydroxide (NaOH, reagent grade \(\geq\) 98%, pellets, anhydrous, Merck, Darmstadt, Germany), as a source of alkali were used. As organic structure directing agent (OSDA), N,N,N-trimethyl-1-adamant ammonium hydroxide (Sachem Inc., TMAdaOH, 25 wt% aqueous in H\({}_{2}\)O, Austin, TX, USA) was used. An ELGA PURELAB Pulse purification system was used to purify deionized water (1 s/cm) for all experiments. Lastly, high-purity gases were used to measure gas permeation--H\({}_{2}\) (99.9995%), He (99.9995%), N\({}_{2}\) (99.9995%), CO\({}_{2}\) (99.998%), CH\({}_{4}\) (99.5%), and SF\({}_{6}\) (99.9%).
# Examining Pipe-Borehole Wall Contact and Pullback Loads for Horizontal Directional Drilling
## 3 Analytical Model for Calculating Pipe Pullback Loads
### Pipeline Pullback Loads
The external load \(P_{k}\) of the calculation unit \(k\) can be estimated by considering an even distribution of \(\Delta P_{k}\) (because \(\Delta P_{k}\) is much smaller than \(P_{k}\), the effect of this estimation on \(\Delta P_{k}\) is considered to be negligible and the shorter the length of the calculation unit, the smaller the error):  
\[P_{k}=wg\cos\theta_{k}+\frac{\Delta P_{k}}{S_{k}}=wg\cos\theta_{k}+\frac{T_{k -1}|\theta_{k}-\theta_{k-1}|}{S_{k}}. \tag{37}\]  
The drilling fluid drag force \(T_{if}\) is calculated using Equation (33), and the friction force between the pipeline and the ground surface of the roller \(T_{ig}\) can be calculated by  
\[T_{ig}=w\mu_{a}S_{0}\cos\theta_{0}, \tag{38}\]  
where \(\mu_{a}\) denotes the coefficient of friction applicable at the surface before the pipe enters the borehole; \(S_{0}\) signifies the length of the pipeline at the ground; and \(\theta_{0}\) represents the angle between the ground and the horizontal. The pipeline's weight \(T_{inv}\) can be expressed as follows:  
\[T_{inv}=\sum_{k=1}^{i}w\sin\theta_{k}S_{k}, \tag{39}\]where \(T_{iw}\) takes a negative value when the angle between the net weight \(w\) and the pullback direction of the calculation unit is less than 90\({}^{\circ}\); otherwise, it takes a positive value. The pullback loads (\(T_{i}\)) for the pipeline to be pulled back to the end of the calculation unit \(i\) can be obtained by summing the friction force between the pipeline and ground or roller \(T_{ig}\), the friction force between the pipeline and borehole wall \(T_{is}\), drilling fluid drag force \(T_{if}\), and pipeline's weight \(T_{in}\):  
\[T_{i}=T_{ig}+T_{if}+T_{is}+T_{iw} \tag{40}\]
## 4 Analysis of the Tunnel Construction Simulation Results
### Vault Settlement and Tunnel Perimeter Convergence
According to Table 3, the settlement of the vault is much larger than the horizontal convergence around the tunnel. The maximum settlement value during the excavation of the CRD method reached 12.2 mm, which appeared at the B1 position of the 60 m surveying point. The maximum settlement value during the excavation of the CD method reached 13.5 mm, which also appeared at the B1 position of the 60 m surveying point. For the full-section method, during the excavation, the maximum settlement value reached 13.7 mm, which also appeared at the 60 m surveying point B1. It can be seen from the vault settlement the CRD method has the smallest maximum settlement value, the full-section method has the largest settlement value, and the settlement value of the CD method is in the middle, which appears at the position of the 60 m surveying point S4. During the excavation of the CD method, the maximum horizontal convergence is 5.46 mm, which also appears at the 60 m surveying point S4. The maximum horizontal convergence during the excavation of the full-section method is 5.62 mm, which also appears at the 60 m surveying point S4. After analyzing the settlement value of each surveying point, it can be concluded the full-section excavation method has the lowest stability of surrounding rock, and the CRD method has the highest surrounding rock stability.
## 2 Case Study
### City of Alqosh  
Alqosh is a small historic Assyrian town, probably older than 2800 years. It is located near the mountain range of Iraqi Kurdistan, approximately 40 km north of Mosul city. Nowadays, it administratively belongs to the Nineveh Province, with Mosul as its capital. From the point of view of security, it is controlled by the Kurdish Peshmerga, which is subordinated to the Duhok Province (Figure 1).  
Figure 1: Map of Iraq with location of the Alqosh city, modified by Google Maps.  
Located at the foot of rugged mountains in the Kurdistan Region, Alqosh has a rich history dating back thousands of years. It is renowned for being one of the oldest continuously inhabited Assyrian towns in the region, with a legacy deeply rooted in its ancient Assyrian heritage [32; 33; 34; 35]. The name of the city appears in the Old Testament, associated with the Prophet [PERSON], who preached in Assyria between 726 and 697 BC and foretold of the fall of the Assyrian Empire. Later, Alqosh became an important city for Judaism and the Church of Eastern Christianity based on the feat of the Assyrian monk [PERSON], who built a monastery in the Alqosh Mountains. This abbey is called the \"Rabban Hormizd Monastery\" and was founded in 640 AD. [36] It was a of residence for many Patriarchs of the Eastern Church. Alqosh is still a residence for Christian Patriarchs and Bishops and it hosts a valuable depository of manuscripts and books in its monasteries [37]. According to this source, Alqosh forced a number of attacks during the centuries [32; 33; 34; 35; 36]. In the period after the world wars, the city experienced difficult times, an important element being a complete exodus of the region's Jewish population after 1947. The most recent threat has been attacks made by the Islamic State. Despite these challenges, the resilient community of Alqosh continues to endure, striving to preserve its cultural identity and historical legacy. A map of the location of Alqosh can be found in Figure 1.
## 2 The Proposed DR Detection System  
DR detection includes extracting useful features from the pre-processed retinal fundus images, which are input into the network, and the classification using these obtained features. ResNet [39], which is a famous deep learning model applied in the residual design to optimize learning, is commonly used as a backbone network in various tasks in computer vision. ResNet-50 was employed as an encoder to learn presentations from the input data in this study. The classifier is actually a MLP with two fully connected layers, and the softmax function is used as an activation function in the final layer. The classifier accepts the flattened input vectors and outputs two values denoting probabilities of RDR or No-RDR for each corresponding input.
# GNSS Code Multipath Mitigation by Cascading Measurement Monitoring Techniques
## 6 Field Data Analysis
### Static Test
#### 6.1.2 Position Results
 } & **East Mean** & **North** & **Height** & **East RMS** & **North** & **Height** \\  & & **(m)** & **Mean (m)** & **Mean (m)** & **(m)** & **RMS (m)** & **RMS (m)** \\ \hline \multirow{4}{*}{ \begin{tabular}{c} GPS L1 \\ C/A \\ \end{tabular}  } & A1 & \(-\)0.95 & 1.49 & 1.76 & 2.56 & 3.81 & 4.95 \\  & A2 & \(-\)0.54 & \(-\)0.03 & 0.92 & 1.81 & 2.27 & 3.98 \\  & A3 & \(-\)0.49 & 1.07 & 2.02 & 1.75 & 2.67 & 4.52 \\  & A4 & \(-\)0.06 & 0.36 & 0.02 & 1.40 & 2.05 & 3.34 \\ \hlineFigure 13: _Cont._
## 3 Results and Discussions
### Comparison with a Flatbed Scanner  
In Figure 6, the red and green color intensities of X-ray irradiated EBT-XD films measured with a conventional flatbed scanner (EPSON GT-X900) are compared to those measured with Nix as to two orientations: 0\({}^{\circ}\) (above) and 90\({}^{\circ}\) (below). The color intensities measured with the flatbed scanner were constantly higher than those with Nix, which implies that the reflection patterns of the LED light used for image scanning were different between the two devices. From these results, the performance of Nix in reading the Gafchromic films was judged to be comparable to that of the conventional flatbed scanner.  
Figure 5: Dose dependence of the color intensities (**left**): red component, (**right**): green component) of EBT-XD irradiated with 160 kV X-rays at up to 40 Gy and measured with Nix at four angles: 0\({}^{\circ}\), 90\({}^{\circ}\), 180\({}^{\circ}\) and 270\({}^{\circ}\).  
Figure 6: Comparison between the dose dependencies of the color intensities (**left**): red component, (**right**): green component) of EBT-XD measured with Nix and those with the flatbed scanner at the angles of 0\({}^{\circ}\) (**above**) and 90\({}^{\circ}\) (**below**).  
It was found that both red and green components obtained with the flatbed scanner tended to saturate at unexpectedly lower dose levels, i.e., around 10 Gy and 15 Gy, respectively. This tendency (saturation at lower dose) observed in the flatbed scanner data can partly be attributed to the selection of the reflection mode, not the transmission mode, as it was reported that the color intensities of the EBT-3 Gafchromic film scanned with a similar-type flatbed scanner (EPSON 10000 XL) in reflection mode had more limited dose range and slightly larger uncertainty than those obtained in transmission mode, while the reflection mode scanning showed higher sensitivity and could lead to more widespread use for the purpose of radiochromic film dosimetry [54]. These findings indicate that the proposed dosimetry method using Nix for reading a radiochromic film (EBT-XD) is promising for on-site dosimetry, i.e., the dosimetry that can be achieved with portable items only. It is expected that this approach would be effectively applied to other radiochromic materials that would be flexibly selected depending on the conditions of real or potential radiation exposures, such as possible dose range, radiation species, mainly affected body parts, etc.
## 4 Experiments
### Parametric Analysis  
1. Sensitivity of \(\Omega\): Communication rate \(\Omega\) is used to control knowledge transfer among different tasks. We examine performance sensitivity with respect to this parameter for IMDE. We set it to 0.2, 0.4, 0.6, 0.8, and 1. Table 2 shows the best achieved fitness values in 20 runs versus \(\Omega\) in IMDE on test suite 1, and the best one is shown in bold. It is clear that IMDE performs well with \(\Omega\) from 0.2 to 1 with a small difference. Nevertheless, the larger \(\Omega\) can encourage more individuals to learn from other tasks, thereby consuming more computing resources. To reduce running time on various problems, we employ a relatively small \(\Omega\) in our algorithms.
2. Sensitivity of \(\gamma\): Randomly chosen ratio \(\gamma\) is another control parameter utilized in IMTO. To discuss performance sensitivity to \(\gamma\) in IMTO, we test its different settings on test suite 1. Table 3 shows the best achieved fitness values in 20 runs versus \(\gamma\) in IMDE on test suite 1, and the best one is shown in bold. IMDE is easily trapped into local optima when only choosing better-performing individuals. However, adding some randomly selected individuals can have better convergence performance. It is clear that IMDE performs best when \(\gamma\) is set to 0.2. We thus set \(\gamma\) to 0.2 in our experiments.
# Laser Vibration Characteristics of Marble Specimens and Failure Criterion
###### Abstract  
Rock failure and instability usually lead to significant engineering disasters. This paper aims to establish an experimental failure criterion to predict rock failure via testing the laser vibration characteristics of marble specimens. Uniaxial compression tests and Brazilian tests were carried out on marble specimens coupled with acoustic emission technology and laser Doppler vibrometry measurement technology. The whole laser vibration waveform of the marble specimen was divided into elastic stage, plastic stage, and failure stage. Although different frequency spectrum characteristics were identified in different waveform phases, a wide frequency spectrum was always present prior to rock failure. Furthermore, the wide frequency band frequency spectra characteristics took place 30.9 s and 21.3 s earlier than the rapid increase of the acoustic emission counts in the uniaxial compression test and Brazilian test, respectively. Taking the wide frequency spectrum as a failure criterion for the failure of loaded marble is quick, convenient, and reasonable. Using laser Doppler vibrometry measurement has the advantages of being remote, non-contacting, and earlier warning. This research can provide a reference for the further study of forecasting rock failure.  
laser vibration characteristics; laser Doppler vibrometry (LDV); uniaxial compression test; Brazilian test; dominant frequency; early warning Article
## 5 Statistical Analysis of Temperature Inversion Layers
This annual wintertime maximum agrees with one of the proposed mechanisms of occurrence of the MILs involving the breaking of gravity waves to sustain the MIL [2]. The lidar and satellite observations reported by [PERSON] and [PERSON] [5] also showed that the frequency of occurrence of MILs follows an annual cycle, with a maximum during the winter months at mid-latitudes and a semi-annual cycle with maxima during the equinoxes at low latitudes. Note that this could also be important earlier in this section, where we compared the distribution of our MIL parameters to those measured by the Gadanki lidar at equatorial latitudes [36]. \begin{table}
\begin{tabular}{p{113.8 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline \multicolumn{1}{c}{**Month**} & \multicolumn{1}{c}{**Season**} & \multicolumn{1}{c}{**Number of MILs**} & \multicolumn{1}{c}{**Number of Lidar Observation**} & \multicolumn{1}{c}{**MIL Detection Ratio (\%)**} & \multicolumn{1}{c}{**Seasonal MIL Detection Ratio (\%)**} \\ \hline December & & 74 & 388 & 19.07 & \\ January & Winter & 122 & 418 & 29.18 & 49.9072 \\ February & & 73 & 390 & 18.71 & \\ \hline March & & 45 & 405 & 11.11 & \\ April & Spring & 14 & 323 & 4.33 & 14.1002 \\ May & & 17 & 272 & 6.25 & \\ \hline June & & 20 & 326 & 6.13 & \\ July & Summer & 32 & 377 & 8.48 & 15.2134 \\ August & & 30 & 345 & 8.69 & \\ \hline September & & 28 & 391 & 7.16 & \\ October & Autumn & 45 & 353 & 12.74 & 20.7792 \\ November & & 39 & 378 & 10.31 & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Distribution of MIL measurements by month, 1978–2019. Figure 5: Observation of MIL’s groups from 1978 to 2019 based on k-mean clustering. There are three main groups. The first group is shown by blue dots, while groups 2 and 3 are shown by orange and yellow, respectively.
## 3 Results and Discussion
### Vertical Distribution of Anthropogenic Radionuclides
Due to the significant number of tests (132 tests, of which 87 were airborne), the largest explosions (at least 10 kilotons yield for fission tests and at least 100 kilotons yield for thermonuclear explosions) were used to calculate the trajectories. A total of 46 nuclear tests were taken into account. The results of the trajectory calculations showed that the air masses following these explosions moved north, west, and east. Western transportation frequently resulted in atmospheric fallout on the continent, such as on the Yamal Peninsula in Russia. Figure 11a-d illustrates air mass trajectories along the primary directions. The nearest trajectory to the research area is associated with the airborne nuclear test at the Sukhoi Nos site on 02.10.1958 with a power of 40 kilotons (Figure 11d). Trajectories are shown at three altitudes--500, 1000 and 1500 m. No additional trajectories were found towards the Kanin Peninsula, encompassing the Nes River basin territory. This suggests that local (tropospheric) fallout is unlikely to be the source of pollution in the Nes River basin. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Radionuclide**} & \multicolumn{6}{c}{**Isotopic Ratio, rel. un.**} \\ \cline{2-6}  & \multicolumn{2}{c}{**Nes River Basin**} & \multicolumn{2}{c}{**Svalbard Island**} & \multirow{2}{*}{**Global Fallout**} \\ \cline{2-6}  & **Average Value** & & & & \\ \hline Sr-90/ & & & & & \\ Cs-137 & 0.501 & 0.2821 & - & - & 0.6 * \\ \hline Pu-238/ & & & & & \\ Pu-239+240 & 0.102 & 0.0524 & 0.034 & 0.0231 & 0.025 ** \\ \hline Pu-239+240/ & & & & & \\ Cs-137 & 0.0323 & 0.0205 & 0.06 & 0.0622 & 0.04 ** \\ \hline Am-241/ & & & & & \\ Pu-239+240 & 0.46 & 0.2697 & 0.46 & 0.4161 & 0.37 ** \\ \hline \hline \end{tabular} Notes: * According to ([PERSON] et al., 2018). ** According to ([PERSON] et al., 2018).  
\end{table} 
Table 1: Results of calculation of isotopic ratios of anthropogenic radionuclides in peat of the Nes River basin. Figure 11: Main trajectories of air masses (HYSPLIT model). (**a**) atmospheric nuclear test at the site Sukhoi Nos, D-2, at an altitude of 1560 m, power—400 kt, 10 August 1962; (**b**) atmospheric thermonuclear test at the site Sukhoi Nos, D-2, at an altitude of 3750 m, power—24,200 kt, 24 December 1962; (**c**) atmospheric thermonuclear test at the site Sukhoi Nos, D-2, height unknown, power—3250 kt, 16 September 1962; (**d**) atmospheric nuclear test at the site Sukhoi Nos, D-2, height unknown, power—40 kt, 2 October 1958 [38].