esa-sceva/satcom-chunk-collection huggingface dataset:
# Dispersion of the Retardation of a Photoelastic Modulator
## 3 Experiment
The ratio of the second and forth harmonic components in the experiment was obtained. As can be seen in Figure 3b,c, the ratio decreases with the increase in the wavelength, and it is directly proportional with the driving voltage at the same light wavelength. Combing Equation (8) and the Bessel function, the ratios shown in Figure 3b,c can be used to calibrate the retardation amplitude \(\delta_{0}\) of the PEM; the calibration results are shown in Figure 4a. The retardation amplitude also decreases with the increase in the wavelength and shows a noticeable dispersion. To eliminate the difference in the \(\delta_{0}\) values due to the wavelength, we also observed the retardance (\(\lambda\cdot\delta_{0}\)), as shown in Figure 4b. Figure 4: _Cont._  
Figure 3: Modulation signals and the ratio of multiple harmonic components. (**a**) Waveform as shown on the oscilloscope at \(\lambda\) = 0.4 \(\upmu\)m; channel \(V\) represents the driving voltage signal, with a peak driving voltage of 164 V (with amplitude of \(V_{0}\) = 82 V), and channel \(I\) is the modulation signal, with a peak value of 13.2 mV; (**b**) ratio of the second and forth harmonic components in the experiment, where the wavelength of the incident light was increased by 10 nm increments for about 4.5 s, from 0.4 \(\upmu\)m to 0.8 \(\upmu\)m; (**c**) mean value of the ratio of the second and forth components varied in the wavelength range of 0.4–0.8 \(\upmu\)m, obtained by the averaging of the ratios shown in (**b**) for every light wavelength. As can be seen in Figure 4b, the PEM retardance also decreases slightly with the increase in the wavelength and shows a dispersion characteristic. According to the theoretical analysis concluded in Equation (5), it is suggested that the retardance dispersion is introduced by the dispersion of the fused silica photoelastic crystal. According to Reference [19], the dispersion of the refractive index of the fused silica can be described by the Sellmeier equation as  
\[{n_{0}}^{2}-1=\frac{0.6961663\lambda^{2}}{\lambda^{2}-\left(0.0684043\right)^{ 2}}+\frac{0.4079426\lambda^{2}}{\lambda^{2}-\left(0.1162414\right)^{2}}+\frac{ 0.8974794\lambda^{2}}{\lambda^{2}-\left(9.896161\right)^{2}};\]  
thus, the dispersion terms in Equation (5) are obtained in the wavelength range of 0.4-0.8 \(\upmu\)m, as shown in Figure 5a. Figure 4: (**a**) Amplitude of the PEM retardation \(\delta_{0}\) and (**b**) PEM retardance. Figure 5: _Cont._  
By using the retardation amplitude \(\delta_{0}\) of the PEM, shown in Figure 4b, and the dispersion term, shown in Figure 5a, the driving term was determined at different driving voltages. As can be seen in Figure 5b, the driving term, as a function of the incident light wavelength, is nearly constant. The mean value and standard deviation of the driving term is also determined and summarized in Table 1.  
The mean value is directly proportional to the driving voltage, and the standard deviation is less than 4.0 \(\times\) 10\({}^{-4}\) mm\(\cdot\)rad. The results shown in Figure 5b and Table 1 indicate that the driving term is non-dispersive.
## 2 Materials and Methods
### MIKE SHE Model Setup
During the temporal discretization, selected time steps are always critical for minimizing the water balance errors [3]. Aquifer BC used in this study are explained in Figure 6; zero flux BC was selected where lateral flows were expected to be minimum based on the GW contours and topographical characteristics, while in case of gradient BC, selected gradient values were estimated based on GW contours. The two-layer UZ method was used to predict the flow through or within the UZ. Soil data and Van Genuchten parameters [52; 53] were obtained from LUNG-MV and were used to develop the detailed soil map. The soil column vertical discretization was kept constant in the entire model with a minimum soil thickness of 0.5 cm at the ground surface to comprehensively quantify the nonlinear evaporation and transpiration to the maximum vertical discretization of 1 m at the model outer depth. The SZ was characterised by \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Component** & \multicolumn{3}{c}{**Numerical Methods**} \\ \hline \(\odot\) & Evapotranspiration (ET) & \(\odot\) & [PERSON] and Jensen method [43] \\  & \(\odot\) & Two-layer water balance method [46] \\ \hline \(\odot\) & Unsaturated zone (UZ) Flow & \(\odot\) & Richards equation \\  & \(\odot\) & Gravity flow \\  & \(\odot\) & Two-layer water balance \\ \hline \(\odot\) & Overland (OL) Flow & \(\odot\) & 2D-finit difference diffusive wave equation \\ \hline \(\odot\) & Channel Flow & \(\bullet\) & No routing \\ \(\bullet\) & Flow Routing & \(\bullet\) & Muskingum method \\  & \(\bullet\) & Muskingum-Cunge method \\ \hline \(\odot\) & Saturated zone (SZ) Flow & \(\odot\) & 3D-Finite difference method \\  & \(\odot\) & Linear reservoir method \\ \hline \hline \end{tabular}
\end{table} 
Table 3: MIKE SHE water modelling components and related numerical solutions [3; 47; 48; 4]. three layers of geology and a three-dimensional Boussinesq equation was used to estimate the SZ flows. The depth of the aquifer was estimated based on geological data obtained from 60 boreholes available in the study area, and these interpolated GW levels were used as SZ initial conditions. Fine tuning of vertical and horizontal hydraulic conductivities of geological layers played a vital part in the successful model calibration.
# Laser Inter-Satellite Link Visibility and Topology Optimization for Mega Constellation
## 2 Background
### Starlink Constellation Configuration Plan  
As of January 2022, SpaceX had launched a total of 35 Starlink satellites employing the Falcon-9 launcher, and with the launch of the latest batch, its total number of satellites has increased to 2042, with three orbital types: non-polar inclined orbit, polar orbit, and sun-synchronous orbit, each with an orbital inclination of 53\({}^{\circ}\), 70\({}^{\circ}\), or 97.5\({}^{\circ}\)[16]. Since 2014, when SpaceX announced the Starlink constellation initiative, the satellite configuration plan has been revised multiple times. In November 2018, SpaceX proposed amending the FCC's license to lower the LEO layer constellation's orbital altitude from 1150 km to 550 km and to operate 1584 satellites at this altitude [17]. In April 2020, SpaceX amended the FCC license once more, increasing the orbital altitude of all satellites in the LEO layer constellation to 540-570 km, as shown in Table 2.  
Figure 1: Satellite LISLs communication system.  
The Starlink constellation of LISLs terminals has been under continuous development and is expected to eventually provide capacities of up to 10 Gb/s. To accomplish SpaceX's goal of establishing an efficient communications network with global coverage in space, inter-satellite links are required to provide transmission capacity measured in gigabits per second capacity, which will eventually expand to terabits per second, which is the development plan of the next-generation satellite network [18].
# Flickering-Free Distance-Independent Modulation Scheme for OCC
## 5 Methodology  
To prove that the proposed modulation works properly for short, medium, and long distance ranges, a two phases procedure was used. During the first stage, a simulation was designed for validating the switching frequencies' selection procedure by using Equations (9) and (13). For this purpose, the modulated signals using the proposed scheme were generated using the switching frequencies obtained by applying Equation (13) for different values of the frequency multiplier \(\alpha\). Then these signals were used as the input of the light emitters and in the reception stage the corresponding PCC values of the acquired consecutive frames were calculated to demonstrate the effectiveness of the calculated frequency multiplier \(\alpha\), the resulting frames from the cameras should have at least \(v=2\) light bands, and each light strip should be greater than five pixels wide. Additionally, for validating the viability of the switching frequencies selection using Equation (9), the obtained PCC for each data symbol must fit within the range defined in Equation (4).  
The second stage was designed for calculating the system's BER, the succeed probability and the transmission failure probability of the system. The experimental implementation of the proposed scheme was done using switching frequencies for three different distance ranges in order to validate the independence of the scheme from the distance. The experimental testing was designed to send data using the whole modulation scheme including the wake-up process. Over all the transmissions, the received data were compared to the sent information to obtain the number of symbols appropriately decoded, and the amount of bits that the system failed to recover. In this way, the BER was calculated along with the probability of transmitting each symbol successfully.
# Point-Graph Neural Network Based Novel Visual Positioning System for Indoor Navigation
## 4 Experimental Results
### VPS Results  
#### 4.2.1 Experimental Setup  
In the case of point cloud data generation, the interior space of the voxel database was captured using four Leica BLK360 imaging laser scanners, which are LiDAR 3D sensors with 3D panoramic features. The point cloud comprises approximately 4.5 million pieces of RGB information with indoor space of length 35 m, height 5 m, and width 25 m. The point cloud of x, y, and z sizes were calculated using the minimum and maximum coordinates of the indoor space point cloud scanned by the LiDAR 3D sensor, and the real values of the calculated x, y, and z sizes converted into integer values increased. Although the minimum size of a voxel that can be set is 0.1 m, the smaller the size, the lower the computing speed. During the evaluation, the voxel size was set to 0.2 m. If the x, y, and z sizes are divided into voxels, the number of voxels along the X, Y, and Z axes can be calculated. The voxels can be addressed through numbering. Figure 8 depicts an interior view of the indoor space, a LiDAR 3D sensor camera, point cloud divided into voxels, and 3D doll-house view of the indoor space.
## 5 Conclusions and Future Work  
This paper addressed the need for standardized accuracy and completeness checks in engineering drawing dimensioning and proposed an intelligent dimensioning method based on Case-Based Reasoning (CBR), KD-Tree, and an improved Iterative Closest Point (ICP) algorithm. Experimental results demonstrated that the proposed MKD-ICP method achieved a dimensioning accuracy of approximately 92%, outperforming traditional machine learning and rule-based methods while maintaining superior computational efficiency. Specifically, CBR effectively extracted key geometric features and matched historical cases to provide reliable initial annotations, while KD-Tree accelerated high-dimensional neigh  
Figure 10: Performance comparison with error bars.  
Figure 9: Comparative error analysis under different conditions.  
bor searches, and the improved ICP ensured precise alignment through joint optimization of distance and normal vector similarity.  
The case study on a refrigerated van model confirmed that the proposed method significantly improved annotation completeness and reduced manual intervention by approximately 40% compared to conventional techniques. These outcomes directly fulfill the research objective of enhancing dimensioning accuracy, standardization, and automation in engineering drawings.  
In future work, we plan to incorporate deep learning and image processing techniques to further enhance feature extraction and annotation efficiency, thereby advancing the intelligence and robustness of automated dimensioning systems.  
Conceptualization, X.F. and Z.B.; methodology, Z.B.; software, Z.B. and B.F.; validation, Z.B., B.F. and Q.L.; formal analysis, Z.B.; investigation, Z.B. and Q.L.; resources, X.F.; data curation, B.F.; writing--original draft preparation, Z.B.; writing--review and editing, X.F.; visualization, B.F.; supervision, X.F.; project administration, X.F.; funding acquisition, X.F. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (Grant No. 52305060), and the Jiangsu Province Education Science \"14 th Five-Year Plan\" Project (Grant No. D/2021/01/102).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to confidentiality restrictions.  
The authors declare no conflict of interest.
# Carbon Nanocomposites in Aerospace Technology: A Way to Protect Low-Orbit Satellites
###### Abstract  
Recent advancements in space technology and reduced launching cost led companies, defence and government organisations to turn their attention to low Earth orbit (LEO) and very low Earth orbit (VLEO) satellites, for they offer significant advantages over other types of spacecraft and present an attractive solution for observation, communication and other tasks. However, keeping satellites in LEO and VLEO presents a unique set of challenges, in addition to those typically associated with exposure to space environment such as damage from space debris, thermal fluctuations, radiation and thermal management in vacuum. The structural and functional elements of LEO and especially VLEO satellites are significantly affected by residual atmosphere and, in particular, atomic oxygen (_AO_). At VLEO, the remaining atmosphere is dense enough to create significant drag and quicky de-orbit satellites; thus, thrusters are needed to keep them on a stable orbit. Atomic oxygen-induced material erosion is another key challenge to overcome during the design phase of LEO and VLEO spacecraft. This review covered the corrosion interactions between the satellites and the low orbit environment, and how it can be minimised through the use of carbon-based nanomaterials and their composites. The review also discussed key mechanisms and challenges underpinning material design and fabrication, and it outlined the current research in this area.  
carbon nanomaterials; LEO satellites; satellite corrosion; spacecraft; space environment; nanotechnology 2023131763390/nano13111763  
1
# The Effect of LEDs on Biomass and Phycobiliproteins Production in Thermotolerant _Oscillatoria_ sp.
## 2 Materials and Methods
### Experimental Design  
Three configurations of LEDs: Cool white (60 LEDs/m, 400-700 nm, 12 V, 8 W/m) (Sinowell, Shanghai, China), Red:Blue (4:1, chips ratio, 60 LEDs/m, Blue: 660 nm, Red 450 nm, 12 V, 8 W/m) (Sinowell, Shanghai, China), and a mixture of the lights mentioned above (white/Red:Blue) were initially evaluated. For each experiment, _Oscillatoria_ sp. was cultured (in triplicate) in 500 mL GL45 flasks (Schott Duran) with 250 mL of BG-11 culture media of working volume. Each flask was enclosed in a box (Figure 1) with 1 m of LEDs strip (2 cm from the surface of the flask).  
Each flask was mixed using filtered air at a flow rate of 0.15 L\({}_{\text{air}}\) min\({}^{-1}\) and a photoperiod of 12:12 h at 100 \(\upmu\)mol m\({}^{-2}\) s\({}^{-1}\) for 15 days. The air was enriched with 1 % (\(v/v\)) CO\({}_{2}\) to accelerate the cyanobacterial growth. Since fluorescent lamps are the most widely available light source for producing algal and cyanobacterial biomass, this lamp was used as a control (Control FL) in all experiments.  
The configuration that maximizes biomass and phycobiliproteins was further analyzed to identify the effect of light intensity (50, 80, 120, 150, and 180 \(\upmu\)mol m\({}^{-2}\) s\({}^{-1}\)) and photoperiod (12:12, 18:6, and 24:0 light:dark). The light intensity was monitored using a PAR (Photosynthetically Active Radiation) sensor (MQ-510, Apogee Instruments, Inc., North Logan, UT, USA).  
The results were analyzed using a one-way ANOVA in GraphPad Prism version 9.3.1. The significant differences obtained in the analysis were represented in each figure.
# Assessment of Fatigue Life and Failure Criteria in Ultrasonic Testing Through Thermal Analyses
## 4 Results
### S-N Curve  
The S-N curve was attained considering tests in RT in order to avoid the temperature effect and its impact on fatigue performance. The results present higher scatter, which is expected for fatigue tests and mainly in VHCF, as illustrated in Figure 12. In fatigue tests, the materials can be affected by several conditions, but in ultrasonic fatigue tests, the influence of internal defects is more pronounced, and this is reflected in the dispersed results. It can be observed that higher stress levels achieve run-out in 10\({}^{9}\) cycles. The \(\sigma_{\rm a}\) equivalent of 40% of \(\sigma_{\rm u}\) reached 2 \(\times\) 10\({}^{9}\) cycles and did not fail. Some stress levels presented fatigue life three orders higher in magnitude.  
Figure 11: Graphical bars for \(R_{\theta}\) with 300–500 ms of pulse–pause.  
Figure 12: S–N curve of DIN 34 CrNiMo6.  
The material constants obtained by the Basquin equation are 816 for A and \(-\)0.0310 for B, and their relation is presented in Equation (1).  
\[N_{f}=816(\sigma_{a})^{-0.0310} \tag{1}\]  
To evaluate the theoretical results, a correlation with predicted life (N\({}_{f\_{\text{rep}}}\)) and experimental life (N\({}_{f\_{\text{exp}}}\)) was applied and presented in Figure 13. Although there is higher scatter, most of the results are reliable (within 1:2 scatter bands) and also conservative.
# Shear Properties of the Interface Between Polyurethane Concrete and Normal Concrete
## 3 Results  
### Failure Modes and Characteristic Values  
Figure 5 illustrates the failure modes at the bond interface of the PUC-NC composite specimens. The failure modes of the composite specimens can be classified into four types: interface failure (Type A), PUC failure (Type B), NC shear failure (Type C), mixed failure (Type D), and partial interface failure with partial failure in the NC (Type A/C). These results align with the interface failure modes observed by [PERSON] et al. (2012) in their study on composite interfaces.  
Figure 4: PUC–NC interface oblique shear test device: (**a**) loading test instrument; (**b**) schematic diagram of specimen model loading.  
Figure 3: Specim preparation process.  
1. Interface Failure (Type A): Shear failure occurs along the interface, with no damage or detachment of the NC. The surfaces of the two materials remain smooth or exhibit minimal bonding with NC (bonding area ratio less than 10%), indicating a low bond strength at the interface, leading to direct splitting of the composite specimen from the interface.
2. PUC Failure (Type B): The cohesive strength of the NC and the bond strength at the interface are higher than the cohesive strength of the PUC. The composite specimen fails on the PUC side.
3. NC Shear Failure (Type C): The NC matrix near the interface experiences shear damage. When failure occurs, a significant amount of NC remains adhered to the PUC surface. The PUC-NC interface remains largely intact, indicating that the cohesive strength of the PUC and the bond strength at the interface are greater than the cohesive strength of the NC, resulting in failure on the concrete side of the specimen.
4. Mixed Failure (Type D): This failure mode suggests that a combination of the PUC's cohesive strength, the concrete's cohesive strength and the adhesion between the PUC and NC contributes to the bond strength at the interface, leading to damage in both the PUC and NC.
5. Partial Interface Failure with Partial NC Failure (Type A/C): This mode involves partial failure of the NC substrate, with shear failure occurring in the transitional zone of the interface and the NC side. A thin layer of NC substrate remains adhered to the surface of the PUC.
# Quality Assurance of Chest X-ray Images with a Combination of Deep Learning Methods
## 2 Materials and Methods
### Dataset for the Orientation Correction  
Throughout the above processing, a total of 20,000 images were prepared for the orientation correction model. To avoid training similar images, all images were selected from the first examination of each patient from Chest-14. The images were divided into 16,000 training images and 4000 test images. The dataset included 1/4 of each of 0\({}^{\circ}\), 90\({}^{\circ}\), 180\({}^{\circ}\), and 270\({}^{\circ}\) rotations. Half of the images were flipped horizontally.
# Reliability Analysis of Response-Controlled Buildings Using Fragility Curves
## 3 Fragility Curve Based on Incremental Dynamic Analysis
### Applying IDA  
IDA was applied to all six models using STERA 3D software [20]. The analysis was performed at each incremental step of ground motion intensity. A total number of 3600 analyses were performed for all six models using 20 GMRs commencing from 0.01 g with an incremental step of 0.05 g and stopping at 1.5 g. IDA graphs were obtained for each model, representing the \(\theta\)max values as a function of increasing intensities of Sa (T\({}_{1}\)). The IDA curves for the TS buildings are shown in Figure 5a-c, while the IDA curves for the CS building (10F_CS_FM) are shown in Figure 5d.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Structural Damage** & **No Damage** & **Minor Damage** & **Significant Damage** & **Severe Damage** & **Collapse** \\ \hline Story drift (\(\theta\)max) & \(\theta\)max \(\leq\) 1/300 & \(1/300<\theta\)max \(\leq\) 1/150 & \(1/150<\theta\)max \(\leq\) 1/100 & \(1/100<\theta\)max \(\leq\) 1/75 & \(\theta\)max\(>\) 1/75 \\ \hline \end{tabular}
\end{table}
Table 6: Structural damage levels based on the story drift ratio.  
Figure 4: GMR acceleration response spectra (5% damping).
# A Systematic Review of Cybersecurity Risks in Higher Education
## 8 Vulnerabilities in HE
### Administrative and Cultural Vulnerabilities in HE
#### 8.1.5 Openness, Attitude and Culture  
Academic freedom, openness, and transparency are strong norms in higher education, but these values might generate conflict when confronted with cybersecurity requirements [7]. One of the challenges addressed by FireEye is attitude and _cultural resistance_ to security measures [5]. FireEye writes that universities might be reluctant to incorporate any changes that may impede research. Security tools, or anything similar, that can limit access to information or communication might be undesirable. It can, therefore, be challenging to implement security controls to protect valuable information. This issue between academia and the security department is named the \"_clash of cultures_\" by [PERSON] and [PERSON] [7], which can lead to the circumvention of security mechanisms caused by low usability and largely blame the HE security departments for not appropriately accommodate the needs of the faculty and students.  
[PERSON] et al. [55] illustrate how the academic openness culture can be exploited through a spear-phishing experiment: The authors targeted the University's security department and exploited the openly available information shared by the University to profile the targets. The small-scale experiment succeeded in tricking all of the targets that were uninformed of the attack vector. NCSC also criticizes information availability as a vulnerability that can be exploited in social engineering [10]. [PERSON] et al. [45] point to cultural issues regarding low tolerance for security requirements and low loyalty to administrative decisions as key contributors to inadequate security at the social level of the University.