esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Toxicity Reduction in the Water Treated by CWs and FTWs  
The efficacy of the CWs and FTWs for the remediation of phenanthrene-contaminated water was assessed by exposing the seeds of _Tritcium aestivum_ and _Brassica napus_ to the water treated by both wetlands. The germination rate of the seeds was lower when they were allowed to grow in the untreated phenanthrene-contaminated water compared with the germination rate of the seeds that were grown in the water treated by the CWs and FTWs. Hydrocarbon contamination retards the biomass production of plants due to its toxicity [2,23]. A poor seed germination rate of various other crops grown with untreated water has also been reported [47]. The highest germination rate was found in the seeds that were exposed to the water treated by the bacterial-augmented CWs (Figure 9). The maximum germination of the seeds in the presence of the water treated by the bacterial-augmented CWs and FTWs might be due to the mineralization of the phenanthrene by the augmented bacteria.  
FTWs and CWs are the most cost-effective techniques compared with conventional methods. Wetlands imitate natural habitats and have a green partner and biodegraders for the remediation of contaminated water [48]. They do not use any chemicals or have a high-cost infrastructure for the construction, unlike other conventional treatments.  
Figure 8: _Phragmites australis_ growth comparison in CWs and FTWs: **(A)**_P. australis_ growth in CWs; **(B)**_P. australis_ growth in FTWs; **(C)**_P. australis_ root growth in CWs; **(D)**_P. australis_ root growth in FTWs.  
Figure 9: _Cont._
# Scaled Experiment of the Detonation Control System for the High-Speed Penetration on Concrete
## 2 Characteristics Analysis of the High-Speed Deep Penetration  
The target to be hit by the kinetic energy penetrator is usually deep underground. After the meter-level penetration depth, the working time of the detonation control system can reach millisecond level. The high-speed deep penetration test can be used to examine whether the detonation control system can withstand such a complex working environment. The impact velocity of the projectile is more than 800 m/s, and the target material is generally concrete with a thickness unit of meter, which is much greater than the projectile length.  
The sensor in the detonation control system collects the deceleration data of the whole process. The deceleration trend of the high-speed deep penetration can be like the curve in Figure 1. As can be seen from Figure 1, the peak collected by the sensor reaches 16,598 g. Before about 5.6 ms, the working environment of the components installed into the projectile is extremely harsh, so the initial stage of deep penetration needs to be mainly considered in the scaled experiment. Compared with the data in the initial stage, the deceleration decreases rapidly after about 5.6 ms, and the deceleration can be considered that it basically falls back to 0 and fluctuates around 0.  
The high-speed deep penetration is a hot and difficult point in the field of penetration. When the launching platform provides the projectile with high speed (more than 800 m/s), and the concrete target is usually several meters thick, the deceleration data of the detonation control system during the high-speed deep penetration has three main characteristics.  
1. The deceleration peak is very high, which can reach \(10^{4}\) orders of magnitude;
2. The time history of deceleration is very long, and the significantly large oscillation time is usually at the millisecond level;
3. The attenuation of deceleration signal is obvious in the middle and rear section of the curve, and the deceleration can decay to \(10^{2}\) orders of magnitude.  
Next, this paper will propose the scaled experiment method for the deceleration of the detonation control system during the high-speed deep penetration to simulate the complex working environment experienced by the detonation control system.
# A Multipath Data-Scheduling Strategy Based on Path Correlation for Information-Centric Networking
## 4 Multipath Data Scheduling  
In Section 3, we introduced a prototype system for multipath transmission in ICN, but we did not involve issues such as path correlation analysis and data scheduling. In this section, we focus on how to reduce the correlation of sub-paths and how to distribute data to each sub-path to enhance transmission efficiency and robustness. First, we propose a relay path selection algorithm based on path correlation to minimize the impact of overlapping links. Secondly, we comprehensively calculate the path state value by combining RTT and packet loss rate, and then propose a data-scheduling algorithm based on path state value.
## 3 Methodology
### Monte-Carlo Mooring Area Detection Model  
There are four main elements in solving the mooring area detection:  
1. Establish a mooring area detection model. By establishing the plane rectangular coordinate system of the anchorage area, two-dimensional coordinates are set for ships or objects in the anchorage that hinder the anchoring operation. Then, the Euclidean metric method is adopted to construct the anchoring area detection model of the anchoring ship, so as to select the anchor position that meets the safety distance between two anchoring ships, as in Equation (12). \[\left\{\begin{array}{l}d_{n}=\sqrt{\left(x_{a}-x_{n}\right)^{2}+\left(y_{a }-y_{n}\right)^{2}}\\ Min(d_{n})\geq D_{S}\end{array}\right.\] (12) where, \((x_{n},y_{n})\) is the position of the existing ship or other objects in the plane rectangular coordinate system of the anchorage area. \((x_{a},y_{a})\) is the anchor position, which satisfies the safety distance of anchoring ships.
2. The random function of the Monte-Carlo method is taken to generate random two-dimensional coordinates \((x_{1},y_{1}),(x_{2},y_{2})\ldots(x_{n},y_{n})\) in varying amounts within the anchorage, so as to simulate the ship position of the existing anchoring ship, namely, to simulate the interference term of the target anchoring ship during the detection of the anchorage area. The distance of these coordinates meets the safety distance \(D_{S}\) requirements for anchoring ships. Then, with the conversion model of the anchor position, the above ship positions are converted into the anchor position \(\left(x_{1}^{\prime},y_{1}^{\prime}\right)\), \(\left(x_{2}^{\prime},y_{2}^{\prime}\right)\ldots\left(x_{n}^{\prime},y_{n}^{ \prime}\right)\) of the existing anchoring ship.
3. The random function of the Monte-Carlo method is taken to generate random two-dimensional coordinates \(\left(x_{1}^{\prime\prime},y_{1}^{\prime\prime}\right)\), \(\left(x_{2}^{\prime\prime},y_{2}^{\prime\prime}\right)\ldots\left(x_{n}^{ \prime\prime},y_{n}^{\prime\prime}\right)\) in varying numbers within the anchorage, so as to simulate the two-dimensional coordinates of the ship positions of the target ship.
4. Based on Equation (12), the two-dimensional coordinates of the anchor positions of the target ships are calculated that meet the requirements of \(D_{S}\).
## 5 WST Applications
### Climate Monitoring  
The automation of the monitoring process can be used in diverse types of climates and conditions. [PERSON] and [PERSON] monitored agroclimate in the Amazon, analyzing WSN short range transmission. They found that more distant nodes suffered a performance loss, while nodes closer to the sink maintained their throughput levels. Another example of climate supervision is flood prediction by means of wireless sensors, which can detect rainfall, water level and weather conditions. The sensors supply information to a centralized database system [64]. [PERSON] and [PERSON] extended the implementation to a regional and on-farm sensor networks at 900 MHz that provide remote, real-time monitoring and control of farming operations in two agricultural applications, a weather monitoring network and an on-farm frost monitoring network [65].  
[PERSON] and [PERSON] presented a moisture distribution map obtained through the integration of WSN with GIS (Geographic Information Systems). The wireless nodes with moisture sensors were located at predetermined locations; geographic coordinates of these points were obtained with GPS and then, all the information was evaluated using GIS [66].  
[PERSON] _et al_. developed a wireless data transmission system, using wireless ZigBee motes, developed to remotely monitor sediment runoff at a low-water crossing in real time. The gateway transmitted the sensor signals to an Internet server using the GPRS [18].  
[PERSON] and [PERSON] developed a lab prototype for wireless measurement of soil temperature. The system was based in a commercial 13.56 MHz RFID tag. Measurements showed a high correlation (greater than 99%) with those obtained using a thermocouple [67].
# Characteristics of Photon Beam and Preservation of Coherence in Fourth-Generation Light Sources
## 2 Worldwide 4 GSRs  
The MAX-IV 3-GeV electron storage ring was the first new generation light source that used an MBA lattice [11] to reduce emittance, and hence increase brightness and transverse coherence. Brilliance and coherent fraction are the major performance parameters for 4 GSR. Brilliance is defined as the ratio of the photon spectral flux to the phase space volume formed by convolution of the electron and photon beam:  
\[\text{Brilliance}=\frac{flux}{4\pi^{2}\Sigma_{x}\Sigma_{x^{\prime}}\Sigma_{y} \Sigma_{y^{\prime}}} \tag{3}\]  
where the convoluted size is  
\[\Sigma_{x}=\sqrt{\sigma_{x,\rho}^{2}+\sigma_{ph}^{2}}\, \tag{4}\]  
and the divergence is  
\[\Sigma_{x^{\prime}}=\sqrt{\sigma_{x^{\prime},\rho}^{2}+{\sigma^{\prime}}^{2}_{ ph}} \tag{5}\]  
where \(\sigma_{x,\rho}\) is electron-beam size, \(\sigma_{ph}\) is photon-beam size from a single electron, \(\sigma_{x^{\prime},\rho}\) is electron-beam divergence, and \(\sigma_{ph}^{\prime}\) is photon-beam divergence from a single electron. The coherent fraction is represented as the ratio of the photon wavelength to the volume, which is a convolution of the electron and the photon beam in phase space:  
\[F=\frac{\lambda^{2}/\left(4\pi\right)^{2}}{\Sigma_{x}\Sigma_{x^{\prime}}\Sigma_{y }\Sigma_{y^{\prime}}} \tag{6}\]  
where \(\lambda\) is the photon wavelength.  
Therefore, the brilliance and coherent fraction are maximized by decreasing the electron-beam emittances until the diffraction limit is reached. Typically, an electron emittance of ~10 pm can reach the diffraction limit at ~1 A (12.4 keV).  
Emittance distributions of various storage rings including 4 GSRs, tend to decrease as ring circumference increases (Figure 2). The distribution of 3 GSR natural emittances indicates that they decrease in inverse proportion to the cube of circumference. By implementing the MBA lattice concept and compact technology, the Korean 4 GSR (red asterisk) obtains 100 times the emittance reduction (or even more) of 3 GSRs. When an on-axis injection scheme, reverse bends and cutting-edge technology are taken into consideration, emittance is reduced by another 3-4 times. Ultra-low emittance rings such as HEPS (<60 pm), Korea-4 GSR (58 pm), APS-U (42 pm) and PETRA IV (20 pm) provide high brightness and coherence up to high photon energies.  
4 GSR projects worldwide (Table 1) choose energies ranging from 2 to 6 GeV. All have emittances <300 pm; the lowest is 20 pm, which is obtained by PETRA IV, as a consequence of its huge (2300 m) circumference. The recent trend of 4 GSR design is to consider reverse bends. However, not all machines realize beta function optimization for phase-space matching between electron and photon beams. To facilitate beam injection, several machines have a large horizontal beta function at the injection point.  
Figure 2: Emittance according to the circumference of 3 GSRs and 4 GSRs. Vertical axis: natural emittance normalized by the square of energy. Facilities indicated in blue are 4 GSRs that use the multi-bend lattice concept.
# Adaptive Threshold-Aided K-Best Sphere Decoding for Large MIMO Systems
## 4 Simulation Results
This is because, in the high-SNR region, \(\rho\) in (8) is large, and the ratio of the second path metric to the first tends to be small, which results in a small number of retained nodes at each layer in the proposed AKSD scheme. Figure 1: The BER performance comparison of KSD algorithms for a \(48\times 48\) MIMO system with 16-QAM. Figure 4 illustrates the comparison of the average number of visited nodes for a MIMO system with \(N_{r}=64,N_{t}=64\), and 16-QAM. Similar to Figure 3, it is seen that the proposed AKSD scheme provides significant complexity reduction compared to the other existing schemes that provide comparable performances, i.e., the conventional KSD and IKSD. The complexity reduction ratio of the AKSD at SNR \(=\) 20 dB with respect to the conventional KSD with \(K=1024\) is approximately 71%. Furthermore, at SNR \(=\) 20 dB, the AKSD scheme achieves approximately 30% and 41% complexity reduction compared to the adaptive threshold-based IKSD and fixed threshold-based IKSD with \(K=400\), respectively. Figure 3: The complexity comparison of KSD algorithms for a 48 \(\times\) 48 MIMO system with 16-QAM. Figure 2: The BER performance comparison of KSD algorithms for a 64 \(\times\) 64 MIMO system with 16-QAM.
## 3 Results and Discussion  
The proposed algorithm selector and the scheduling algorithms were programmed in Python version 3.9 and run on an 11 th generation Intel(r) Core i7-1165G7 @ 2.80 GHz processor with 16.0 GB of RAM. The time limits of the solvers were set to 30 s and 300 s to ensure realistic calculation times and to also test the effects of extending the time limit.  
The experiments were conducted on all presented instances, and the solvers successfully solved the instances.  
In order to ensure the correctness of the algorithms, the results were compared to the results of [65] for the FJSSP benchmark instances and the JSSP with the benchmark instance collection [66]. The comparison showed similar results, which ensured the overall correctness of the algorithms. Furthermore, for some instances, CP Optimizer or the OR-Tools solver found better values for the makespan. This illustrated the development of solvers over the years and their improvements in solving larger instances faster.
# Real-Time 3D Reconstruction Pipeline for Room-Scale, Immersive, Medical Teleconsultation
## 6 Evaluation
### Comparison with Existing Offline Methods  
We compare our implementation with a limited selection of existing, publicly available implementations for mesh reconstruction. As a primary, direct triangulation method of the input point cloud, we compare it with ball pivoting [71], which is implemented in Open3D [67] using ball radii of 1, 2, 3, 4, and 8 cm (Figure 15a). The more optimized greedy projection triangulation [69], which is part of the PCL point cloud processing library [72], greedily connects all points in the projected 2D neighborhood using the point's normals (Figure 15b). For this method, we used a neighborhood radius of 5 cm, a maximum surface angle of 45\({}^{\circ}\), a minimum triangle angle of 10\({}^{\circ}\), and a maximum triangle angle of 120\({}^{\circ}\) to find as many connections as possible. For an implicit surface reconstruction method, we compare it with smooth signed distance surface reconstruction (SSD) [12] using the implementation of [PERSON] [73] with an octree depth of 10 and _SurfaceTrimmer_ for level 8 or higher to remove all surfaces without many underlying samples. All methods use the unsimplified, voxelized point cloud generated using the first frame of our recording and the _unsimplified-low-detail_ preset as their input. Other implicit surface reconstruction techniques, such as variants of Poisson reconstruction [32; 33; 49], are visually very similar to SSD in our particular dataset.  
Figure 15: Comparison with Existing Approaches. (**a**) Ball-pivoting algorithm [71] with 177,825 triangles, (**b**) greedy projection triangulation of [PERSON] et al. [69] with 187,028 triangles in total, (**c**) trimmed SSD reconstruction [12] with 398,736 triangles in total, and (**d**) our approach with multiple LODs with 49,340 triangles in total.  
Our method generates fewer holes than the other general purpose direct meshing techniques (Figures 14b and 15a) but cannot fill arbitrarily large gaps like implicit surface reconstruction (Figure 15c), which also inadvertently fills gaps, such as between the legs of the person in the background. Since our method also uses the voxelized samples directly, the resulting surfaces are not as smooth as the reconstruction with SSD since noisy points are still connected if they are in the immediate neighborhood. Therefore, our mesh extraction method heavily relies on correct, trustworthy samples from voxelization. Due to the simplification of flat surfaces, our method generates significantly fewer triangles.
# An Energy Efficient Routing Approach for Cloud-Assisted Green Industrial IoT Networks
## 4 Preliminaries
### RPL Routing Specification  
RPL is a distance vector routing protocol that makes use of IPv6 based addressing technique and operates on top of the IEEE 802.15.4 and supports various types of link-layer technologies such as ZigBee and Bluetooth. It is capable of constructing a robust tree-like topology that connects hundreds of resource-constrained devices in the network, typically known as a directed acyclic graph (DAG).  
Figure 1: Superframe structure of IEEE 802.15.4.  
Each node in a graph connects in a way where there exist no cycles. The DAG is destined to one or more root and generally known as destination oriented DAG (DODAG). The DODAG root constructs and maintain the network through different control messages. For this, RPL specifies three main Internet control message protocol version 6 (ICMPv6) messages and exchange the network-related information. These messages are DODAG information object (DIO), DODAG information solicitation (DIS), and designation advertisement object (DAO). The DODAG root node initiates the topology formation process by broadcasting the network information through the DIO message. Once the DIO message is received by the neighboring nodes, they decide whether to join the network or not, based on the OF and policy. Afterward, the node adds the address of the DIO sender in its candidate parent table and calculates the rank, abstract distance between a node and the root node, based on the defined metric and OF, which must monotonically increase towards the leaf node. Each node selects the preferred parent (next hop towards the DODAG root) from the candidate parent set that has the best rank. In this way, the upward path from leaf nodes to the root node can be established. In RPL scope, it is not mandatory that OF should use a particular routing metric, consequently, the OF can be defined according to the application requirements. Technically, we can use OF for two purposes, the rank calculation and optimum path selection based on routing metrics and constraints. As described in [16], different node and link metrics can be used during topology construction and route selection. Therefore, it is possible to use multiple routing metrics to fulfill the application goal, which is one of the objectives of this paper.
## 2 State of the Art
### Real Measurements--Related Works  
Whereas simulations and adjustment of values can be conducted easily on a computer by defining input values, real measurements represent the whole set of permanently varying input factors. Such changes are caused by irregular events both on the power grid and the effects caused outside network itself. This behavior is strongly influenced by stochastic processes of different types. Real measurements in the majority of cases reflect a more accurate performance of the whole system, often while conclusively revealing its limitations.  
Authors in [59] describe the results of real measurements of pilot BPL technology deployed in India (Topology for Site-2 scenario). Authors offer very few results, especially the influence of repeaters used in the project are discussed in a limited range. The main focus is on throughput analysis with regard to day time and utilization of power grid network and its events.  
Authors in [60] focus mainly on PLC communication with a maximum distance of 200 m, including 21 nodes field tested in Germany. The topic of usage repeater is discussed with regard to the quality of communication channels, round-trip time and throughput. The exact influence of one or more repeaters is not fully recognized. Network topology changes dynamically throughout time and number of repeaters, then it may vary. Even though this article is based on measurements with devices working in a narrow band of PLC, the principles applied to the communication mechanism remain the same.  
Project MoMa, which is described in article [61], plans deployment of 10,000 repeaters and 550 headends which should cover up to 120,000 households in Germany. A repeater's typical latency per hop is recognized as 15-20 ms. This paper is mostly focused on promotion of the whole project, and results are not included nor discussed. This paper summarizes benefits of massive BPL technology deployment and emphasizes its importance in the Smart Grid concept.  
A study on the influence of repeaters on overall performance (throughput and latency) of the network is described in research [62]. In most of the scenarios, only direct connections by copper wire were used. A scenario containing a real BPL network is missing, and there are no details on its parameters; hence, the results lack validity. The authors suggest results for different network topologies (linear, star, etc.). Nevertheless, this article shares some main ideas, which are going to be further developed.  
Based on the literature review covered in this section, we found that there are no pertinent articles presenting differences between common methods of powerline communication simulations and real results of devices deployed on power lines under the load. With our experiences, with performance evaluation of networks based on PLC and mutual cooperation with electric utilities in the Czech Republic [63; 64; 22; 65; 66; 67], we mainly focus on correlating simulations and real measurements with consequent outcomes. Our goal is to enhance knowledge in terms of determining the necessity of repeater usage in PLC network design.