esa-sceva/satcom-chunk-collection huggingface dataset:
# Joint Optimization of Data Transmission and Energy Harvesting in Relay Satellite Networks
## 6 Simulation Evaluation  
### Simulation Setup  
We build an RSN scenario based on the Satellite Toolkit (STK) which can provide real-world satellite parameters such as orbit inclination and altitude. Then, we evaluate the proposed DTEM algorithm by using the MATLAB simulator. Specifically, the RSN scenario consists of twenty LEO satellites (i.e., user satellites), three GEO satellites, and six GSs. The user satellites are distributed in four orbits with five satellites for each. The orbital altitudes are set to 816 km with an inclination of 86.58\({}^{\circ}\). We assume that one relay satellite is equipped with three antennas, i.e., \(K=3\), and each relay satellite is allocated two ground stations. The network operation period is set to one day which is divided into 1440 time slots, i.e., the slot duration \(\tau\) is 60 s. We obtain the network topology and sunlight time windows of user satellites for all time slots from the Satellite Toolkit (STK). The ISL transmission capacity randomly takes a value between [8; 10] Mbps, and the maximum data acquisition rate is \(\varphi_{\max}=30\) Mbps. The parameters of energy management are set as follows: \(P_{\mu}=10\) W, \(P_{t}=20\) W, \(P_{r}=25\) W, \(\mu=80\%\)[15]. Furthermore, we set the maximum energy harvesting rate as \(\rho_{\max}=50\) W with probability 0.8 or \((1/3)\rho_{\max}\) with probability 0.2 when the RSN expose to the sun. Initially, we set \(\mathcal{D}_{i}(0)=0\) and \(E_{i}(0)=\mathcal{B}\), respectively, where \(\mathcal{B}\) is derived from (26).
## 3 Related Studies and Motivation
### Studies Related to Erasure Coding  
Erasure coding has a significantly increased space efficiency, taking up less disk space than traditional replication-technique-based distributed file systems. However, because various cost problems, such as disk overhead and network bottlenecks, occur in data encoding and decoding, various algorithms and methodologies have been proposed to resolve such issues. A distributed erasure-coding-based file system can divide the data encoding/decoding process into five stages: client overhead, master process, parity calculation, data distribution, and slave process. A cost analysis that occurs when the network bandwidth is sequentially increased to 1 G, 10 G, 40 G, and 100 G suggests that client overhead and data distribution are the costliest [15; 16]. Disk contention availability is applied to efficiently distribute multiple recovery requests using a parallel recovery to reduce client overhead costs, random chunk allocation is used to increase the load balancing efficiency, and asynchronous recovery is utilized to increase the concurrency [17]. To reduce the costs incurred during data distribution, a study has significantly reduced the recovery bandwidth associated with the decoding performance by appropriately adjusting the recovery speed [18]. A study on a top-down data transfer technique also used distributed data calculations for updating the parity nodes [19]. In another previous study, the recovery of failed data was achieved at a small scale throughout the storage node, reducing the recovery time to approximately equal the normal read time for the same amount of data [20]. Other studies [3; 4] also identified and avoided the traffic transmission paths of nodes and associated nodes where bottlenecks occur, thereby reconfiguring the routing paths and eliminating bottlenecks across the entire system to reduce the traffic transmission costs.  
In erasure-coding-related studies, network routing methodologies and algorithms improve the routing paths to the destination nodes where the data and parity blocks are transmitted when decoding the data, reducing the costs of bottlenecks and transmission links. However, because aggregated hardware-based switches are used to reduce the bottlenecks and traffic transmission costs, additional hardware costs are required; in addition, bandwidth is always evaluated at a fixed value and the block transmission rates are inefficient when the bandwidth is suddenly lowered. Therefore, because DQN-EC collects dynamically changing data in a network environment using erasure coding and identifies failed switches, DQN neural network model learning can efficiently yield the optimal routing paths and transfer blocks.
# Influence of Solvent Selection in the Electrospraying Process of Polycaprolactone
## 3 Selection of Solvent Systems Used in PCL Electrospraying
### Solution Properties for Cone-Jet in PCL Electrospraying
#### 3.2.3 Viscosity  
The viscosities of the electrospray solutions influence the formation of a stable Taylor cone, where the direction of the viscoelastic force is opposite to those of gravity and electrostatic attraction ones. On the one hand, the combined viscoelastic force and surface tension are too weak to counteract the gravity and electrostatic attraction ones in a low viscosity medium, leading to a dripping mode rather than a cone-jet one. On the other hand, the use of high viscosity working solutions prevents the  
Figure 4: Prediction of microencapsulation configuration based on spreading coefficients.  
formation of stable Taylor cone. The drying of the polymeric particles with the solvent evaporation during the process occludes the tip of the capillary; and therefore limiting the stability of the Taylor cone [86; 141]. Thus, there is an appropriate range in viscosity of solution for achieving cone-jet mode during the electrospraying process (Table 3). The viscosity ranges from 1.5 to 5500 mPa\(\cdot\)s [62]. An increase of the solution viscosity leads a decrease to the distance from the exit of the nozzle to the apex of the cone. In general, a long distance from the tip of the nozzle to the apex of the cone induces an increase in jetting diameter at the tip of the cone and may lead to dripping mode or spindle mode. An increase in the solution viscosity allows obtaining a cone angle close to the theoretical value of Taylor cone (about \(98.6^{\circ}\)), which reduces the mean diameter of the obtained particles and narrows its size distribution [142]. For a coaxial process, the formation of the Taylor cone is favored, when the viscosity of the outer phase is higher than the inner one. In this case, its formation for the inner phase is driving by the interfacial interactions and related viscosities diffusion.
# A Hybrid Energy Equating Game for Energy Management in the Internet of Underwater Things
## 5 Performance Evaluation
### Routing Overhead  
Figure 10a depicts the comparison of the routing overhead with increasing the number of FNs in the network between the proposed model, ADDP [20], PRADD [21], and DEEP [14]. The overhead of the proposed framework is less than other models because in the proposed scheme, the data forwarding hierarchy remains the same and the burden on CH increases with increasing number of nodes. However, the selected information travels inside the network, which controls the routing overhead and stabilizes the network. ADDP has less overhead as compared to PRADD and DEEP  
Figure 9: The effect of number of field nodes, network size, and data generation interval on the network energy consumption of the proposed model.  
because an ad-hoc on-demand connection is established for forwarding the data. So, more and more nodes are trying to establish the connections with their neighbors, as a result, the overhead increases. While in the case of PRADD and DEEP, as the number of nodes increases the more routing overhead is generated in the network due to connection and disconnection between the FNs and the gateways. From the graph, it is obvious that DEEP suffers more as compared to the opponent's schemes because the optimal and collision-free routes are selected on the cost of routing overhead.  
Figure 10: The comparison of routing overhead with number of field nodes, network size, and data generation interval.  
Figure 10b depicts the comparison of the routing overhead with the network size between the proposed model, ADDP [20], PRADD [21], and DEEP [14]. The overhead of the proposed framework is less than that of the other models because the proposed scheme data forwarding hierarchy is simple, so it is less affected by the increased network size. ADDP has less overhead as compared to PRADD and DEEP because only the data forwarding overhead is increased with increasing the size of the network. While in the case of PRADD and DEEP, as the number of hops increases, the more control overhead is generated, which affects the network efficiency.  
Figure 10c shows the comparison between the data generation interval and the routing overhead of ADDP [20], PRADD [21], and DEEP [14]. The increasing data generation interval does not increase the routing overhead in HEEG as compared to the counterpart schemes, while the ADDP, PRADD, and DEEP lifetime and efficiency are seriously affected with the longer data interval as compared to the HEEG. This is because with the longer data generation interval the gap between data packets becomes longer and the relay nodes start forwarding the data of individual FNs without fusing it as shown in Figure 10c.
## 3 Data and Methods
### Multibeam and Single-Beam Acquisition  
Multibeam echosounder (MBES) data were collected throughout the western inner shelf of Sardinia within the framework of the oceanographic cruise SONOS 07 (Figure 1b), data were collected to define the morphology of the seabed of the MPA \"Penisola del Sinis Isola di Mal di Ventre\" from a depth of about 40 m to a depth of about 10 m. Data were collected in 2007 using the R/V Thetis of the Italian National Research Council (CNR), equipped with a Seabat-Reson 8111 MBES device operating at 100 kHz. Specific indication on the instrument characteristics and processing can be found from [PERSON] et al. [31]. Finally, digital terrain models (DTMs) were produced at a 5 m resolution.  
Single-beam echosounder (SBES) data were collected throughout the western inner shelf of Sardinia within the framework of the project \"Stabilita Litorali Sinis\" in 2005 (Figure 1b), the data were collected to define the morphology of the seabed of the MPA \"Penisola del Sinis Isola di Mal di Ventre\" from a depth of about 15 m to depth of about 1.5 m. Data were collected using a small boat equipped with a Knudsen echosounder (vertical resolution of 10 cm) operating at 200 kHz, coupled with a differential global positioning system (accuracy of 7 cm in both vertical and horizontal positions). During the bathymetric survey, a series of transects, spaced about 50 m, were conducted perpendicular and parallel to the shoreline. A low-resolution DTM (resolution of 20 m) was obtained and used to define the main morphological features of the shallow inner shelf.
## 2 Historical Background
### Face Image Inpainting  
Face image inpainting, also known as face restoration, aims to fill in the missing parts of a face using visually plausible predictions [48]. Face image inpainting is still under-researched and remains a challenging problem. Early inpainting works [49; 50] involved copying suitable pixels or textures into the areas to be restored, relying on existing pixels to reconstruct the missing parts of the image. These methods are mainly suitable for images with only small areas of damage, and their inpainting effect depends on the existing pixel information within the image. Although there have been attempts to use improved diffusion-based inpainting algorithms [51] that do not rely on large datasets and long training times, they have not yet been widely applied and validated. Some methods based on deep learning [14; 15; 52; 53] can directly predict the pixel values of the missing regions, generating high-quality results for the missing areas. Ref. [47] proposed STNet, which effectively restores missing regions by separately reconstructing the structural and textural information of the image and then merging them. It attempted to restore faces in murals with minimal data but failed to successfully reconstruct facial detail features. To further improve the quality of face image inpainting, many methods have adopted techniques that combine GANs with various prior knowledge. This prior knowledge includes facial parsing [54], facial landmark recognition [55], identity information priors [56], and 3D deformable models [57; 58]. However, these methods face robustness issues when dealing with faces that have large pose variations and extensive damage, as they require additional networks to perform auxiliary tasks [59].
## 3 Results and Discussion
### Effect of VPD Regulation on Tomato Crops in Soil
#### 3.1.1 Effect of VPD Regulation on Growth  
Among the results for the experimental treatments T1 and T2 shown in Figure 3, Figure 3 shows the average values of the evolution of the tomato crop height characterized during the vegetative growth phase. The height of the tomato crops increased progressively during the vegetative growth phase in all the experimental treatments evaluated, without finding, in a general way, statistically significant differences between the experimental treatments T1 and T2 throughout the study period. Statistically significant differences were only found between treatments at two moments of the field trial: 23 and 49 days after transplanting the tomato crops.  
Figure 4 shows the average values of the evolution of the number of leaves expanded per plant, characterized during the vegetative growth phase. The number of leaves expanded per plant increased progressively during the vegetative growth phase of the crops. In general, there were no statistically significant differences between the treatments in the number of leaves expanded per plant.  
Figure 4c shows the average values of the evolution of the number of fruit settings per plant during the vegetative growth phase. The fruit setting increased continuously during the study period, without differences between treatments. Statistically significant differences were only found between treatments at one moment of the field trial: 64 days after transplanting the tomato crops, as the standard error bar of 64 days shows.  
Finally, Figure 4d shows the average values of the evolution of the phenological growth stages per plant during the vegetative growth phase for each experimental treatment. The phenological growth increased continuously during the study period. In general, there were no statistically significant differences between the treatments in the phenological growth stages per plant.  
Regarding H1 in this group, except for the phenological growth stages, the treatment results for the growth parameters had a normal distribution, and the \(p\)-values of the \(t\)-tests were greater than 0.05, so H1 for the growth parameters is not true.
# Hollow-Core Optical Fibers for Telecommunications and Data Transmission
## 4 Photonic Bandgap (Photonic Crystal) Fibers
### Fibers with Regular Photonic Structure
Figure 5: Evolution of HC-PBGF to ensure single-mode operation: (**a**) early design without shunts (Blaze Photonics HC-1550-02); (**b**) OFS single-mode fiber with two shunts [20]; (**c**) OFS AccuCore improved single-mode fiber with six shunts [21; 28]. Figure 6: SEM image of NKT Photonics (formerly Blaze Photonics) HC-1550 fiber. Despite overall good control of fiber dimensions during manufacturing, cells in inner layers are noticeably smaller than in outer ones. Image courtesy of NKT Photonics. Problem (a) was solved with the introduction of shunts in the cladding (see Section 4.2), and problem (b) with the spinning of the fiber during drawing [21; 22]. Problems (c) and (d) were eliminated in a new class of HCFs--the anti-resonant fibers (ARFs)--discussed in Section 5. A fragmented transmission spectrum does not affect transmission at one or few wavelengths, including low-capacity DWDM links [22], but spectrally incompatible fibers cannot be spliced into a joint optical path, e.g., during the expansion of an existing network. Large-core HC-PBGF fibers are not suitable for high capacity DWDM networks, where a low loss at least in a full C-band (\(\approx\)1528-1565 nm) is required. To minimize light scattering via surface capillary waves on surfaces around the core, and the resulting component of fiber attenuation (SSL, see Section 6.2) [26], the core diameter of a typical HC-PBGF intended for data transmission is considerably larger than in solid single-mode fibers. For example, the OFS AccuCore fiber [22; 27] has core diameter of 25 um, and an effective cross-section A\({}_{\text{eff}}\) = 200 um\({}^{2}\), while the widely used single-mode fibers conforming to the ITU-T G.652 standard [29], such as the Corning SMF-28e+ [30] and SMF-28 Ultra [31], have an 8.2 um core diameter and A\({}_{\text{eff}}\) = 82 um\({}^{2}\). A large mismatch between the mode field diameters (MFD) of these fibers requires special arrangements during their splicing [27]. Commercial HC-PBGFs are primarily offered as lengths of cable terminated in the factory with pigtails including standard single-mode fibers [28], as described in Section 10.1.
## 4 Conclusions  
The industrial complex chemical accident monitoring system was constructed. It uses an IR-RCD and an LRVS to detect chemical leakages, fires, and smoke in industrial complexes. The facilities comprise a steel tower with monitoring equipment installed at its top (thereby enabling long-range visibility), a steel tower control room that supplies power to the equipment, and a central control room for integrated monitoring and coordination. The industrial complex information includes information about the actual handled chemical substances and monitored sections. The software solutions comprise control software and an AI chemical accident detection model.  
This system combines different technologies and can detect potential chemical accidents (such as chemical leakages and fire outbreaks) occurring in a specific section. As it is a fixed system with equipment mounted on the tower, it can scan the industrial complex 24 h per day, 365 days per year. The main goal of this system is to ensure reliability by cross-checking the detected results for each piece of equipment and verifying data about  
Figure 12: The actual handling information of vinyl chloride (orange dots) in monitoring section G2. (Source: Google earth).  
industrial complexes. Moreover, the accuracy can be improved by continuously updating the information.  
According to the results of a test at the YNIC, the data obtained through the SIGIS-2 were consistent with the chemical substance handling information established in the system. These results confirm that it is possible to monitor an industrial complex from a 70 m high steel tower. However, to secure reliability of the detection results, the information about the chemical substances and handling facilities at the sites must be continuously updated. We plan to investigate different applications of the TORUSS-LR2000 and the AI chemical accident detection model. This system can detect and evaluate chemical leakages and the occurrence of fires or smoke through large-scale scans, and it will be used for the early detection of and effective responses to chemical accidents in industrial complexes.  
Conceptualization, B.C.M. and S.G.L.; methodology, S.G.L.; investigation, S.G.L. and E.H.K.; writing--original draft, S.G.L. and E.H.K.; writing--review and editing, B.C.M.; supervision, B.C.M. All authors have read and agreed to the published version of the manuscript.  
This research was supported by The Graduate School of Chemical Characterization hosted by the Korean Ministry of Environment: 2022030903900.  
Not applicable.  
This research was conducted with the support of the Graduated School of Chemical Characterization hosted by the Korean Ministry of Environment.  
The authors declare no conflict of interest.
# Effect of Rotor-Stator Spacing on Compressor Performance at Variable Operating Conditions
## 2 Geometric Parameters  
The numerical simulations are considered a transonic stage designed for this work, with its meridian view illustrated in Figure 1. The compressor comprises a transonic rotor and a cantilevered stator. The radial clearance of the stator has been optimized to the appropriate size to ensure that only traditional hub leakage flow exists in the region. Meanwhile, no corner separation occurs from choke to stall according to the study by [PERSON] et al. [30]. The entire stage also contains an inlet guide vane (IGV), which is omitted in this study to reduce calculations. The hub and shroud radii are constant from the inlet to the outlet. Furthermore, to weaken the influence of numerical reflection on the transient results, the inlet boundary is two times the rotor chord length upstream of the rotor leading edge (LE), and the outlet boundary is 2.5 times the rotor chord length downstream of the stator trailing edge (TE). The basic geometric parameters are reported in Table 1.  
Figure 2 depicts steady compressor characteristics, with Figure 2a,b presenting the efficiency and total pressure ratio as a function of mass flow. Since the rotor is transonic and the stator has a premature high load at the end wall due to the constant radius flow path, the characteristic line is steep with a low flow margin. The three operating points A, B, and C, whose averaged back pressure is 118 kPa, 123 kPa, and 128 kPa, are considered as the low  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Value** \\ \hline Hub-tip ratio & 0.416 \\ Rotational speed/rpm & 15,000 \\ Rotor aspect ratio & 2.242 \\ Stator aspect ratio & 2.598 \\ Rotor solidity(midspan) & 1.364 \\ Stator solidity(midspan) & 1.177 \\ Rotor blade count & 25 \\ Stator blade count & 25 \\ Rotor tip clearance & 0.18\% span \\ Stator hub clearance & 0.90\% span \\ \hline \hline \end{tabular}
\end{table}
Table 1: Geometric parameters of the research compressor.  
Figure 1: The meridian view of the research compressor.  
load (LL), nominal load (NL), and high load (HL) conditions, respectively. The incidence along all spans at B is about zero, while A and C have negative and positive incidence conditions, respectively. The three points are simulated to explore the unsteady interaction as a typical case.  
This study considers two-axial spacing between the rotor and stator, where the closer is 21.1% of the rotor chord length at the 0.5 span and the farther is 74.8% of the rotor chord length at the 0.5 span. All six cases follow the notation close_A and far_C. The steady performance of all cases is reported in Table 2, highlighting that the mass flow is almost unchanged for the same back pressure. The change in isentropic efficiency does not exceed 0.2 points, and the trend is inconsistent.
# Evaluation of Noise-Reduction Techniques for Gas-Turbine Test Stands: A Preliminary Analysis
## 4 Test-Bench Description
It is considered that in the propagation path of the acoustic wave, in the case of intercalated lamellae, it travels a greater distance \(l_{c}\), which is defined as follows:  
\[l_{c}=n\frac{l_{y}}{\cos(\phi)}\;[\text{m}] \tag{7}\]  
Figure 7: Drawings of the tested configurations: (**a**) Conf. I—single baffled_linear; (**b**) Conf. II—double baffled_linear; (**c**) Conf. III—triple baffled_linear; (**d**) Conf. IV—double baffled_staggered; (**e**) Conf. V—triple baffled_staggered. where \(n\) is the number of baffled levels in staggered topology. [PERSON] proposes the use of silencers with a staggered baffle arrangement, as shown in Figure 9. This design eliminates straight paths for sound waves to travel through the baffles, potentially leading to improved attenuation at higher frequencies. However, [PERSON]'s research [16] is focused on parallel-baffled attenuators, and it did not provide prediction methods for staggered configurations. Consequently, this study proposes an adaptation of [PERSON]'s method specifically targeted to staggered topologies.