esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 ORITE Project Field Experiment  
ORITE (Ohio Research Institute for Transportation and the Environment) and ODOT (Ohio Department of Transportation) conducted a comprehensive soil experimentation program to identify the behavior of PVC and HDPE pipes buried under high fills [63]. Under the scope of the testing program, pipes used a negative projection installation in narrow and shallow trenches dug in native soil. As a backfill material, sand and crushed stone (Cr. S.) materials were used at 86, 90, and 96% relative compaction levels. Following the backfill, the embankment fill was constructed at two heights (6.1 and 12.2 m) using native soil. The pipe installation plan and directions for the cross-sections are shown in Figure 2. Test pipe installation conditions are summarized in Table 1[63]. Compaction was not used on the mid 1/3 section of the bedding layer to maintain thermoplastic pipe seating in the bedding layer. In addition, bedding material was prepared at different thicknesses. Letters A, B, C, D, E, and F, listed under the pipe type section in Table 1, indicate the pipe wall profile. [PERSON] et al. [63] provided more details about pipe wall profiles. In this project, native soil was used as embankment fill material. The liquid limit of the soil was 27.2%, and the plastic limit was 16.5%. The Unified Soil Classification System (USC) classifies this as low-plasticity clay (CL). After embankment construction, consolidated-undrained (CU) triaxial compression tests were conducted on soil samples taken, and shear strength parameters (c and \(\varphi\)) were determined for sand and crushed stone used as backfill material. In addition, sieve analysis, compaction, one-dimensional compression, and consolidated-drained (CD) triaxial compression tests were conducted [65]. The field study data and evaluations based on this study were published in many periodicals [63; 66; 67; 68; 69; 70; 71; 72; 73; 74]. More information on the work performed in the field test can be obtained from these articles.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Pipe No** & **Pipe Material** & **Pipe Diameter (mm)** & **Wall Type (1)** & **Ring Stiffness (2)** & **Backfill** & **H** & **Bedding Thickness (\%)** & **Thickness (mm)** \\ \hline
2 & PVC & 762 & A & 45.15 & Cr. S. & 96 & 12.2 & 150 \\ \hline
4 & PVC & 762 & B & 97.45 & Sand & 86 & 6.1 & 150 \\ \hline
5 & PVC & 762 & B & 97.45 & Cr. S. & 96 & 12.2 & 150 \\ \hline
8 & HDPE & 762 & C & 73.31 & Sand & 96 & 12.2 & 150 \\ \hline
14 & HDPE & 1067 & E & 61.69 & Sand & 96 & 12.2 & 80–230 \\ \hline
17 & HDPE & 1524 & F & 34.42 & Cr. S. & 96 & 12.2 & 80–230 \\ \hline \end{tabular} \({}^{(1)}\)[63] for details. \({}^{(2)}\) Initial values. Cr. S.—Crushed Stone. RC—Relative compaction.  
\end{table}
Table 1: Field test pipe properties and installation conditions.
# Disentangling Long Trajectory Contributions in Two-Colour High Harmonic Generation
## 3 CTMC Method
The red dotted curve is a long trajectory, which was ionised right when the electric field (blue dashed) reaches its maximum value, corresponding to the shortest possible exit radius (grey dot-dashed line) in the simulation. Compare also the sketch in Figure 1 for short and long trajectories within the SFA and three-step-model. The green dotted curve represents a short trajectory that was launched just shortly before the electric field changes sign. The comparatively small field strength this late in the quarter cycle results in a larger exit radius. Evidently, the short trajectory must first be accelerated towards the ion in order to reach a smaller recombination distance condition. Figure 4: The plot compares two example trajectories from the CTMC calculations. Red dots: ionised immediately at the peak of the field, resulting in a long trajectory. Green dots: short trajectory ionised later in the quarter-cycle. The grey dot-dashed curve represents the shortest exit radius. If this radius is chosen as recombination condition \(R\), then short trajectories travel a relatively large distance from their initially larger exit radius towards the ion nucleus until they cross this radius, while being accelerated by the laser field (blue dashed) that has already turned around. Long trajectories, however, can be decelerated by the field during their approach to the ion. Figure 3: Kinetic energy of single classical trajectory calculations with Coulomb. (**A**) recorded at the exit radius for each trajectory; (**B**) recorded at a radius of 3 au from the parent ion. A fixed radius yields spurious energy for trajectories which are ionised late in the cycle, and low harmonics in the spectrum can not be recovered. Dark blue stars (light blue circles) represent short (long) trajectories, respectively. Red dots show the experimental data from [PERSON] et al. black the values from quantum stationary phase calculation [PERSON] et al. (2018) and grey the three-step-model [PERSON] et al. (2018). Values for the last three provided from [PERSON] et al. (2018). The values extracted from the Classical Trajectory Monte Carlo (CTMC) simulation in (**A**) reproduce the three-step-model so closely that the grey line is barely visible. The CTMC is of course based on this analytical model, except that it takes the Coulomb potential into account.
# Metabolic Reaction Network-Based Model Predictive Control of Bioprocesses
## 2 Methods  
### Metabolic Reaction Network-Based Modeling  
For a full overview of metabolic reaction network theory, the reader is referred to [1]. Here, only the final dynamic metabolic flux analysis model structure, which is used for the simulation and control parts of this work, is given [15]:  
\[\frac{d\mathbf{c_{ext}}(t)}{dt} =\mathbf{S}_{\text{ext}}\cdot\mathbf{K}\cdot\mathbf{u}(t)\cdot c_ {\text{bio}}(t) \tag{1}\] \[\frac{dc_{\text{bio}}(t)}{dt} =\mathbf{s}_{\text{bio}}^{\top}\cdot\mathbf{K}\cdot\mathbf{u}(t) \cdot c_{\text{bio}}(t) \tag{2}\]  
with \(\mathbf{c_{ext}}\) being the (\(m_{\text{ext}}\times 1\)) vector of concentrations of extracellular metabolites (mol/L), \(c_{\text{bio}}\) the scalar biomass concentration (gDW/L), \(\mathbf{S_{\text{ext}}}\) the \(m_{\text{ext}}\) rows of the stoichiometric matrix which correspond to the extracellular metabolites, and \(\mathbf{s}_{\text{bio}}^{T}\) the row of the stoichiometric matrix which corresponds to the biomass pseudo-metabolite. It is assumed that the production of biomass can be described by a pseudo-reaction/metabolic flux (a so-called biomass flux) as illustrated in [15]. This biomass concentration is used in Equations (1) and (2) to match dimensions of the RHS and the LHS as the (free) fluxes are expressed per gDW biomass and the metabolite concentrations are expressed in mol/L. \(\mathbf{u}\) is the (\(d\times 1\)) vector of free fluxes (mol/gDW/h), and \(\mathbf{K}\) is a suitable basis for the intracellular part of the stoichiometric matrix \(\mathbf{S_{\text{int}}}\). As the fluxes are parameterized as a function of the basis and the free fluxes \(\mathbf{v}=\mathbf{K}\ast\mathbf{u}\), the choice of the basis is an important one as this determines the definition of the free fluxes and the complexity of the flux profiles and the number of parameters to be estimated. The authors of [15] demonstrated that three options exist to select a basis: (i) a fixed rational basis, (ii) a fixed orthonormal basis, or (iii) an optimal orthonormal basis. In this case, a fixed rational basis based on fluxes 1, 4, and 5 has been chosen. This matrix is of dimension (\(n\times d\)), where \(n\) is the total number of fluxes in the network. The number of free fluxes \(d\) is equal to \(n-rank(\mathbf{S_{\text{int}}})\). This formulation stems from the pseudo steady state that is assumed at the intracellular level, with respect to the extracellular dynamics.  
This model is only fully defined when all free fluxes are expressed as a function of the concentrations and possibly environmental conditions like temperature and pH:  
\[\mathbf{u}(t)=\mathbf{f}(\mathbf{c_{ext}},T,pH,\ldots,\Phi) \tag{3}\]  
with \(\Phi\) being the parameter vector specific to the model structure which is used. As the fluxes are defined as specific fluxes, i.e., on a per-biomass basis, they do not depend on the biomass concentration anymore. Furthermore, in this contribution, only the dependence on the extracellular metabolite concentrations is considered.
# Fragility Assessment of Traffic Embarkments Exposed to Earthquake-Induced Liquefaction
## 2 Methodology for the Derivation of Fragility Curves
### Definition of Damage States, EDP and IM  
During dynamic excitation, additional stresses occur in the soil structure and embankments, leading to additional deformations. Even greater displacements are expected when the foundation ground is susceptible to liquefaction. Regarding various failure mechanisms of embankments (slope instability, crest settlements, lateral spreading, piping, etc.), different EDPs and their threshold values can be used in the analyses.  
Apart from the characteristics of the seismic load, other factors can have a great impact on the extent of any deformations, including the height and shape of an embankment [23]. Moreover, [PERSON] et al. [24] identified other parameters that control the seismic behavior of liquefiable soils, such as thickness of the liquefiable layer, stress history, depth of the sand layer and other site conditions, along with soil characteristics.  
In this study, the permanent vertical displacement at embankment crest was used as the EDP in the derivation of the fragility curves. Threshold values for three damage states (ds1--minor, ds2--moderate and ds3--extensive) of the selected EDP were taken from the literature [14], and are equal to 0.05 m, 0.15 m and 0.40 m for road embankments and 0.03 m, 0.08 m and 0.20 m for railway embankments, respectively. In terms of serviceability, the damage state ds1 corresponds to open road/railway with speed reduction, while ds2 and ds3 to partially closed or fully closed traffic line during repair works. According to [PERSON] and [PERSON] [14], the used limit values were obtained on the basis of expert opinion and were corroborated by the experiment driving test, in which the influence of road embankment settling in relation to driving speed was studied [25]. Additional damage state parameters with threshold values can be found in the literature (e.g., [12; 13; 18]).  
PGA at bedrock was selected as the IMs for the derivation of the fragility curves in this research. This selection was based on the wide usage of PGA in practice, and its numerous correlations with other engineering parameters.  
Figure 1: Example of the results of a seismic response assessment, with identification of the number of cases exceeding a selected damage state (**a**), and the corresponding fitted fragility curve (**b**).
## 3 Blockchain-Enhanced Security and Operational Efficiency in VANETs
### System Operational Behavior
Query and Verification: Upon receipt of an event observation report from a vehicular node, the RSU engages in rigorous data queries and verification protocols. 2. Reputation Value Recalculation: Once the trust scores are received from the cooperative vehicular nodes, the RSU consults the historical reputation and social trust of the target vehicle stored in the reputation blockchain. The new comprehensive reputation score is then calculated through weighted integration.
# Wet Snow Flashover Characteristics of 500-kV AC Insulator Strings with Different Arrangements
## 4 Conclusions  
Based on the tests carried out in this paper, the following conclusions can be drawn:  
1. Installing anti-icing sheds is an effective method to improve the flashover performance of insulators used in cold regions.
2. Increasing the connection angle can reduce the severity of snow bridging, and therefore increase the flashover performance of insulators with common sheds as the connection angle is increased. However, it was found that for insulators with anti-icing sheds and connection angle higher than 60\({}^{\circ}\), with a small angle between the insulator string and the conductor, the air gap between the icicle and the conductor can breakdown readily if long icicles are accreted on the big shed. According to the test results, when it comes to the electrical performance, the recommended connection angles for \(\Lambda\)-string arrangements with common sheds and with anti-icing sheds are 90\({}^{\circ}\) and 60\({}^{\circ}\), respectively.
3. Increasing the distance between two insulators can improve the flashover voltage performance. When the distance between the two insulators is too close, the flashover voltage will be reduced due to the floating arcs bridging two parallel insulators. For an II-string arrangement, when the distance was increased from 450 mm to 650 mm, the flashover voltages were increased 3.2% and 7.1% for common shed and anti-icing shed insulators. The recommended distance between the two high-voltage terminals is at least 600 mm for the strings with common sheds and at least 650 mm for the strings with anti-icing sheds.
4. When the connection angle is 60\({}^{\circ}\), which is widely adopted in transmission lines, the flashover performance of common insulators under \(\Lambda\)-string and V-string arrangements are almost same for the same snowing conditions. However, due to the presence of long icicles, the flashover voltage of anti-icing insulators under a V-string arrangement is higher than that of a \(\Lambda\)-string arrangement.  
Conceptualization, Z.J.; investigation, J.X., L.L., Q.W. and S.L.; data curation, H.W.; writing--original draft preparation, J.X. and F.Y.; writing--review and editing, F.Y. and M.F.; project administration, Z.J.  
The project was supported by the National Natural Science Foundation of China (51777107) and the Guangzhou Industry-university-research Collaborative Innovation Alliance Special Project (201604046014).  
The authors would like to thank the technicians from China Electric Power Research Institute for their invaluable help in carrying out the experiments.  
The authors declare no conflict of interest.
###### Abstract  
The in situ spraying method is widely used because of its advantages as a trenchless pipeline repair technology, including a fast construction speed and close bonding between the repair lining layer and the reinforced concrete pipe. However, current research on high-performance spray repair materials, the bearing capacity of pipelines before and after repair, and the failure modes between the two interfaces after repair is insufficient. Through laboratory tests designed with multiple sets of control tests, this paper outlines the bearing capacity of reinforced concrete pipelines with corrosion thinning defects repaired with ultra-high-performance concrete. The variation law of the residual bearing capacity of reinforced concrete pipes and the influence of different corrosion degrees, repair thicknesses, and interface forms on the bearing capacity of reinforced concrete pipes were studied following UHP-ECC for pipe repair. The results showed that the bearing capacity of the structure decreased with an increase in the corrosion thickness of the pipeline. After repair with ultra-high-performance concrete, the bearing capacity of corroded pipelines greatly improved. When the corrosion and repair thicknesses were the same, the bearing capacity of the repaired pipeline with different interface forms was very different. After the interface was implanted with nails, spray repair was carried out and the bearing capacity of the pipeline improved the most, followed by the naturally bonded interface. When plastic film was pasted on the repair interface, the bearing capacity of the pipeline improved the least.  
in situ spray construction method; ultra-high-performance concrete (UHP-ECC); reinforced concrete pipe; bearing capacity
## 5 Conclusions  
By combining the VMS data with the fishing logs from three sample vessels during the TACs project for _A. chinensis_ in the Yellow Sea, a high-accuracy artificial neural network for identifying the position states of the vessels fishing shrimp was trained, verified, and obtained. Then, the fishing activities of all vessels, such as net positions, azimuths, and fishing efforts, were characterized. This study is the first application of BeiDou VMS data and artificial neural networks to manage TACs projects. This objectively reflects the distribution characteristics of species resources based on the distribution of fishing intensity. With the advent of the big data era, machine learning, as a science of artificial intelligence, should closely follow the massive and diversified characteristics of big data and mine valuable information from the data to provide a basis for fishery management. Taking this study as a case, the combination of big data mining and machine learning can be used as an effective method to control elements in international TACs projects and to track the spatiotemporal distribution of marine species in the future.  
Conceptualization, Methodology, Formal analysis, Writing--original draft preparation, G.L.; Writing--review & editing, G.L., Y.X., X.Z. and D.S.; Investigation, Data curation, G.L., D.S., Z.K., D.L., F.Y. and X.W. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Fisheries Ecology and Resources Monitoring Project of Agricultural Ecological Protection and Resource Utilization in Jiangsu Province (2021-SJ-110-02) and the Comprehensive Agricultural Law Enforcement Special Project of Agricultural Public Service in Jiangsu Province (2020-SJ-018).  
Not applicable.  
Data Availability Statement: Data are not publicly available; however, the data may be made available on request from the corresponding author.  
We would like to express our respect to all the reviewers and editors for their valuable comments, which have substantially improved the manuscript. We are also grateful to the captains and crews from the fishing vessels for their assistance.  
The authors declare no conflict of interest.
# Incoherent Digital Holography: A Review
## 4 Special Topics and Applications  
### Fluorescence Holography  
Fluorescence imaging is an essential tool in biological inspection. Because fluorescence holography can provide the 3D distribution of a fluorescent object, it is one of the most important applications of incoherent DH. Fluorescence holography was first demonstrated using OSH by [PERSON] et al. in 1997 [22], and in 2006, [PERSON] and [PERSON] demonstrated an OSH-based fluorescence holographic system with transverse resolution of about 1 \(\upmu\)m [26]. Furthermore, the use of OSH to 3D locate fluorescent inhomogeneities in turbid media has been demonstrated [69]. The first FINCH-based fluorescence holography was proposed by [PERSON] and [PERSON] in 2007 [34]. In 2008, [PERSON] and [PERSON] demonstrated a FINCH-based fluorescence holographic microscope for 1 \(\upmu\)m particles [35]. After that, [PERSON], [PERSON], and [PERSON] performed 3D mapping of multiple objects with 500 nm diameters simultaneously by using fluorescence holography [42; 70]. In recent years, multicolor fluorescence 3D imaging of a biological specimens with a 100 nm resolution has been reported using FINCH with birefringent lenses [38].  
Essentially, the setups of FINCH and OSH can be easily modified to perform fluorescence holography by using an excitation light source and an emission filter, as shown in Figure 5. A self-interference fringe of fluorescence is recorded in FINCH, and thus all properties of FINCH-based fluorescence holography are the same as those in conventional FINCH. Figure 6 shows examples of experimental results with fluorescence digital holographic microscopy. Fluorescent nanoparticles with 500 nm diameters have been randomly distributed and set as incoherent objects in 3D space. Phase-shifted holograms have been recorded, and the intensity and phase distributions on the image sensor plane have been obtained successfully. By calculating diffraction integrals, reconstructed images focused on arbitrary depths have been obtained. Figure 6d shows an image reconstructed at a specified depth as an example. After that, the 3D mapping of nanoparticles, as shown in Figure 6e, had been conducted with a sequence of the reconstructed images and digital signal processing, such as a space-division matching method [70].  
In OSH, a TDFZP of excitation light is generated to scan the fluorescent object. The emittance of the fluorescence is proportional to the irradiance of the excitation scanning light. In addition, the response time of the fluorescence is typically in the order of nanoseconds. Hence the excited fluorescence also oscillates at the modulation frequency, that is, the heterodyne frequency \(\Omega\), which is typically between kilohertz and hundreds of megahertz. Finally, the modulated fluorescence is sensed by a detector and demodulated, as in regular OSH. Because fluorescence is very weak, a photomultiplier tube (PMT) or an avalanche photodiode (APD) is usually used as the detector.  
Figure 5: Setups of fluorescence holography: (**a**) Fresnel incoherent correlation holography (FINCH), and (**b**) optical scanning holography (OSH).
# The Model of the Virtual Air Carrier as a Concept for the
## 4 Results
### Passenger Segment  
To correctly determine the business model setting of a virtual airline, it is necessary to take into account the behavior of the consumer--the passenger [42]. Establishing partnerships with airlines (virtual codeshare) plays a role in targeting a specific segment of customers. In the case of cooperation with low-cost or charter airlines, it is mostly aimed at leisure travelers. In the case that the virtual carrier establishes cooperation with traditional airlines, it focuses more on leisure and business travelers. Therefore, it is very difficult to say who is the primary customer of such a virtual airline, which is the most important question when starting one. According to study from 2020, it is important to cover a wide range of passengers and satisfy the demand for the services required by them [35]. In 2014, at the initiative of the Ministry of Transport, Construction and Regional Development of the Slovak Republic, a survey of air passenger transport at Bratislava, Kosice and Poprad airports was prepared. The survey was conducted through questionnaires and focused on the behavior of passengers using the largest Slovak airports. Travelers for work were represented in this survey by almost 40%, which indicates a relatively high rate of labor migration [43]. In practice, the proposed virtual carrier could impress at destinations, typical for this segment, with a specified service package containing a ticket, one checked baggage (alternatively of a higher permitted weight) and standard cabin baggage. The price for a comprehensive transport service should be competitive compared to the total price for a ticket and additional services with low-cost carriers. The segment of business travelers is fundamentally different from leisure travelers. Its price elasticity is significantly lower and the demand for flight frequencies is higher. Statistically, the biggest potential for a virtual carrier in Slovakia is represented by the tourism segment [44]. In this case, it is possible to attract travelers to holiday destinations, when flights are more or less seasonal, and demand is relatively high. A worse situation can occur in the winter months, in this case the offer of destinations should mainly include destinations where people go skiing, for example.  
In general, the potential of the virtual carrier is very strong, because it develops activities in the field of cooperation with other air carriers and thus can have a wide range of destinations. Based on well-agreed conditions in the contract with partners, it can also provide passengers with connecting flights. This segment is characterized by diverse price elasticity. Flight frequencies should offer sufficient time variations so that passengers can choose an individual period of stay, without having to adapt significantly. The optimal number of flights to the destination should be 2-3 flights per week.