esa-sceva/satcom-chunk-collection huggingface dataset:
# Diversity of Collagen Proteins and Their Biomedical Applications in Drug Delivery
## 2 Diversity of Collagens
### Prokaryotic Collagen  
The earliest report on bacterial collagen was that a collagen-like domain containing several units of (Gly-Xaa-Pro)\({}_{6}\) was identified in the amino acid sequence of pullulanase from _Klebsiella pneumoniae_[4]. At the turn of the twenty-first century, the first true prokaryotic collagens, forming the triple helices, were discovered in the Gram-positive bacteria _Streptococcus pyogenes_ and named Streptococcus collagen-like protein 1 and 2 (Scl1 and Scl2 or SclA and SclB) [5,6] (Figure 1). Since then, different non-animal CLPs have been found in bacteria, such as Mcl1 protein from _M. anisopliae_[7], Bcl proteins from _B. anthracis_[8], Pc1 from _S. pneumoniae_[9], Lc1 from _L. pneumoniae_[10], Buc1 from _Burkholderia_ spp. [11], and CLPs from _Bacillus amyloidosisateaciens_[12]. In addition, there are some pieces of evidence suggesting that virophases have collagen-modifying enzymes and CLPs. For example, the genes coding glycosyltransferase were discovered in the _Paramecium bursaria_ chlorella virus and the genome sequences of viruses such as lymphocystis disease virus, shrimp white spot syndrome virus, the Saimiriine herpesvirus 2, and bacteriophage T4 (Figure 1) suggested that these viruses possess their own CLPs [13, 14, 15, 16]. The discovery of prokaryotic collagen has become a growing field with intense studies. As for the origins of collagen-like sequences in prokaryotes, a possible hypothesis is that the convergent evolution led to the rise in collagen-like repeats by spontaneous mutations, transposition of repeat sequences, and motif organization [17]. In addition, the genetic transfer facilitated by viruses or bacteriophages may be the cause of the diffusion of collagenous sequences between bacteria [18].  
To comprehend the genetic distribution of bacteria CLPs, the [PERSON] group gathered 60,789 CLP sequences to analyze their distribution and characteristics. The results indicated that the vast majority of CLPs, approximately 98.9%, were classified into four phyla: Firmicutes (68.1%), Proteobacteria (22.2%), Actinobacteria (5.3%), and Bacteroides (3.2%). The number of GXY repeats, which is a typical characteristic of CLPs, was significantly different among the four main bacterial phyla. The most GXY repeats were present in CLPs from _Bacillus subtilis_, reaching 1034 [19].  
Three characteristic domains are present in the prokaryotic CLPs, just like in eukaryotic proteins. For example, the Scl proteins have an N-terminal variable domain, a typical triple helix Gly-X-Y repeat domain, and a C-terminal non-collogenous domain required for cell-wall anchoring. The N-terminal variable domain differs among the CLPs (Figure 2). Additionally, the number of Gly-X-Y repeats varies [19; 20; 21]. In the G-X-Y repeats, prokaryotic collagen has a Y residue that is predominantly threonine, while eukaryotic collagen has a Y residue that is either proline or hydroxyproline. Hydroxylation of proline to hydroxyproline and glycosylation and cleavage of collagen are absent in most prokaryotic organisms [22].
## 5 Modeling of Existing Processes and Situations. Results and Discussion
### Simulation of Changes in Air Buoyancy Coefficient C
#### 5.1.2 Air Density Variability with Temperature, Pressure, and Humidity  
Air density due to temperature, pressure, and relative humidity can vary within the following limits: 0.88 kg/m\({}^{3}\) at 35 \({}^{\circ}\)C, pressure 80 kPa, relative air humidity from 100% to 1.50 kg/m\({}^{3}\); at \(-30\ ^{\circ}\)C, pressure 105 kPa at any relative humidity. The simulation incorporates a range of air densities from 0.8 to 1.6 kg/m\({}^{3}\) to capture these potential variations.
# Research on the Impact Force of Rockfall Impacting Sand Cushions with Different Shapes
## 4 Numerical Model and Discussion
### Discussion  
In this section, the application scope of the correction formula is expanded by numerical simulation of the large-scale rockfall impact process. However, the formula proposed in this paper also has certain limitations. First of all, this paper only considers the frontal collision between the rockfall and the cushion, that is, assuming the rockfall is free-falling, without considering the horizontal component of the impact force. The behaviour pattern of rockfall is various [32], and the oblique collision behaviour between rockfall and shed tunnel cushion occurs occasionally [33]. Secondly, this paper only assumes that the shed tunnel cushion is a single sand cushion. Many studies have shown that when using some lightweight and high strength cushioning materials instead of sand, the cushioning efficiency of the composite cushion is better. Finally, the correction formula in this paper is obtained by fitting the test results. Although it can well reflect the actual situation, it is still necessary to obtain a more objective impact force algorithm through theoretical derivation.  
In addition, this paper focuses on the impact of different shapes of rockfall on shed tunnel cushions. However, in the design of the shed tunnel structure, the penetration depth of the cushion and the diffusion mechanism of impact force in cushion soil is also very important. Therefore, the influence of rockfall shape on penetration depth and diffusion mechanism is also worth exploring. The penetration depth of the cushion cannot be accurately measured due to various reasons, but this problem can be avoided in numerical simulation. Taking the results of numerical simulation when the falling height is 0.9 m as an example, this paper briefly expounds on the influence of falling stone shape on penetration depth and diffusion mechanism.
## 3 Stray Current Corrosion Morphology, Measurement Method, and Influencing Factors  
### Corrosion Morphology of DC Stray Current  
DC stray current is more harmful to the corrosion strength of metals than AC stray current. When there is no stray current influencing metal gas pipes, there is only natural corrosion, most of which is galvanic cell type. Additionally, the corrosion current is only a few tens of milliamps, and the driving potential difference is only a few hundred millivolts; however, the principal of stray current interference with corrosion is the electrolytic cell. That means potential can reach several volts and the current can be as high as 100 amperes; thus, the harm of stray current corrosion is far greater than that of natural corrosion.  
The appearance of corrosion caused by DC interference is a continuous bubble-shaped round pit, which is caused by an electrolytic corrosion process caused by a large instantaneous direct current. In addition, the corrosion is mostly pitting, the wound surface is generally smooth, and the edge is neat. Its product is mainly carbon black fine powder.
## 2 Theoretical Background and Previous Studies
### Analysis on the Status of VDI Utilization in Other Industries
\begin{table}
\begin{tabular}{c c} \hline
**Company** & **Characteristic** \\ \hline
1. CUK Hospital & Building cloud computing environment \\  & Comfortable Care spaces \\ \hline
2. SNUH (Seoul National University Hospital) & Minimized power consumption \\  & Use of health information systems \\ \hline
3. GangNam Severance Hospital & Real-time health information delivery \\  & Improvement of desktop resource data reliability \\ \hline
4. Kundred Healthcare & Saved money by using thin PCs \\  & Managed virtual desktop system, 4000+ virtual machines \\ \hline
5. Bell & PC included built-in disaster recovery solution \\  & Saved time and on operating hardware \\ \hline
6. IRMC & Saved time on additional new PCs \\  & Data breach prevention \\ \hline
7. Samsung Advanced Institute of Technology & Available in mobile environment \\  & Faster speeds (mobile environment) \\ \hline
8. Hyundai Heavy Industries & Comfortable office space \\  & High level of security \\ \hline
9. LG consulting NS & Integrated service storage supply \\  & Provided environment through appropriate resource management \\ \hline
10. SKT & Comfortable space with thin PCs in work environment \\  & Increased speed \\ \hline
11. KWCWS (Korea Workers’ Compensation \& Welfare Service) & Protected against cyber terrorism and prevented information leakage \\  & Providing smart work \\ \hline
12. Court of Korea & Provided the same work environment in every location \\  & Improved working environment (reduction in dust, heat, and noise generation) \\ \hline
13. Woong-Jin & Enhanced corporate image (eco-friendliness company) \\  & Changed old PC to VDI \\ \hline
14. Allianz & System improvement by maintenance management \\  & Mobile environment \\ \hline
15. MPC Marketing Technology & Network environments for outsourcing services \\  & Smart classroom provision through VDI \\ \hline
16. University of Incheon & Fan noise and heat from PC, complicated PC accessories \\ \hline
17. National Health Insurance Service & Green IT-based environment implementation \\  & 83\% cost savings with zero client installations \\ \hline
18. Korea Institute Curriculum and Evaluation & Reduced operating cost according to test environment \\  & Reflecting the VDI environment \\ \hline
19. Korean Intellectual Property Office & Patent Information Security \\  & Stabilized the examiner PC \\ \hline
20. Multifunctional Administrative City Construction Agency & Sharing data between teachers and students \\  & Effective use on any device \\ \hline \end{tabular}
\end{table} 
Table 1: Applications of VDI server. Accordingly, introducing an optimized VDI system to the construction sector could relieve the financial burden incurred by setting up the computing server environment requisite for the BIM design platform system, as well as the cost of system maintenance and repair. In addition, it means that efficiency can be improved by creating a mobile environment for design work that can be divided between the construction site and office, while maintaining the security of important data.
# High Reliability Evaluation and Lifetime Prediction of 50 GHz Athermal AWG Module
## 5 Lifetime Estimation
### Accelerated Life Test Results  
Table 6 shows the failures that occurred under the temperature conditions during the accelerated life test for 4000 h. The samples consisted of 28 96-channel (50 GHz-spacing) athermal AWGs (Gaussian type 21, Flat type 7). Four failures occurred only in the Gaussian type. After the accelerated life test, the insertion loss for each channel of each representative sample was measured, as shown in Figure 13. After the high-temperature acceleration test, the average insertion loss was \(-4.35\) dB at 71 \({}^{\circ}\)C, \(-4.89\) dB at 83 \({}^{\circ}\)C, and \(-4.68\) dB at 95 \({}^{\circ}\)C, and the higher the temperature, the greater the loss tends to be.  
Although the high-temperature accelerated life test lasted for 4000 h, it satisfied the Telcordia-GR-1209 standards and showed reliability in wavelength.  
The accelerated tests on the athermal AWG module under high-temperature stress followed a lognormal distribution. The activation energy calculated by ALTA S/W was 0.482 eV, and the predicted mean life under 40 \({}^{\circ}\)C operating conditions was up to 3.22 \(\times\) 10\({}^{5}\) (about 36.7 years), which guarantees the 10-year service life required for optical communication components. Although an accelerated life test of 4000 h was performed at high temperature, the wavelength showed reliability.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Temperature**\({}^{\circ}\)C & \(n\) & **Fail** & **Fail Time** \\ \hline
71 & 16 & 2 & 3000 h, 3500 h \\
83 & 8 & 1 & 1250 h \\
95 & 4 & 1 & 750 h \\ \hline \hline \end{tabular}
\end{table}
Table 6: Results after the accelerated life test.  
Figure 12: Life vs. stress.
# Antibacterial Bio-Based Polymers for Cranio-Maxillofacial Regeneration Applications
## 3 Scaffolds and Implanting Medical Devices for Soft and Hard Maxilofacial Tissues
### Other Approaches  
Flavonoids are phenolic compounds which have been studied because of their antioxidant, anti-inflammatory, and antimicrobial capacities. They are present in fruit and vegetables mostly as glycosides, but they can also appear in a free form as sulfates, esters, dimers or polymers. Indeed, some studies have reported antibacterial effects of different flavonoids such as quercetin, galangin, chrysin and taxifolin against diverse bacteria like _S. aureus_, considering its use for periodontal applications [102; 103; 104].  
In this regard, [PERSON] et al. studied the effect of different flavonoids on human gingival fibroblasts showing that quercetin had the most promising biological effects due to its non-toxicity; its capacity of increasing collagen III\(\alpha\)1 and decorin levels while decreasing the expression of profibrotic markers during wound healing and also its capacity for decreasing the bacterial growth rate [103]. For these reasons, it is expected that quercetin might contribute to protect and recover the integrity of gingival tissue after injuries. In another study, quercetin was found to increase mineralization, alkaline phosphatase activity and osteoblastic differentiation of human mesenchymal stem cells. These findings suggest that quercetin might be a novel bioactive molecule with potential therapeutic effects for soft and hard tissue regeneration processes and could be used in its polymeric form for periodontal applications [103; 104].  
In another approach, [PERSON] et al. reported the use of a polymerizable eugenol derivative to provide hydroxyapatite, ZnO\({}_{2}\)-containing, Bis-GMA/TEGDMA (2,2-bis [4-(2-hydroxy-3-methacryloyloxypropyl)-phenyl] propane/tri-ethyleneglycol dimethacrylate) resin-based formulations with antibacterial properties. They found that the anchoring of the eugenyl-derivative onto the surfaces of the material exhibited an effective bacteriostatic activity against _E. faecalis_, _S. mutans_ and _Propionibacterium acnes_ (Figure 5) [105; 106].
# Leveraging Internet News-Based Data for Rockfall Hazard Susceptibility Assessment on Highways
## 2 Materials and Methods
### Rockfall Data Collection
The primary objective of this study is to predict the occurrence of rockfalls along highways, with the model's target outcome being binary--either the occurrence or non-occurrence of a rockfall. To build a robust predictive model, we used the 182 known rockfall locations (positive samples), and supplemented them with 182 randomly generated non-rockfall locations (negative samples) along the highways, as shown in Figure 1.  
Given that different types of highways have varying design requirements and service levels--such as minimum lane widths, turning radius, pavement thickness, signage, lighting, and bridge design--the selection of negative samples needed to reflect the characteristics of the positive samples across different highway types. To achieve this, we maintained the same proportion of negative samples as positive samples within each type of highway. This was performed by generating a 20-m buffer around the roads and employing stratified random sampling within each highway category. Specifically, 126 negative samples were created along Provincial Highways, 19 along City and County Highways, and 37 along District and Rural Highways, resulting in a total of 364 data points for analysis. \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Highway Type** & **Num.** & **Total Length** & **Num. of** & **Rockfall** & **\% Rockfall** & **Rockfall/km** \\ \hline National Expressway & 10 & 1061.8 & 0 & 0 & 0.0\% & 0.0000 \\ Provincial Highway & 97 & 5323.2 & 126 & 24 & 24.7\% & 0.0237 \\ City/County Highway & 158 & 3684.1 & 19 & 13 & 8.2\% & 0.0052 \\ District/Rural Highway & 2250 & 11362.7 & 37 & 16 & 0.7\% & 0.0033 \\ Exclusive Highway & 35 & 407.8 & 0 & 0 & 0.0\% & 0.0000 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Summary of rockfall incidents on different types of highways in Taiwan.
# Interplay Between Wear and Thermal Expansion in 6082 Aluminum: A Simulation and Experimental Study
## 3 Results and Discussion
### Wear Scar Profile  
Figure 10 compares the wear scar profiles under different operating parameters in both simulations and experiments. Under a 5 N load, 300 RPM, and 1 min duration, the experimental wear scar profile aligns closely with the simulation results that include thermal effects. Under a 10 N load, the wear center shifts slightly, revealing two wear scar valleys. Under a 15 N load, these two wear scar valleys become more pronounced. Compared to the simulation without thermal effects, which shows wear only at the nominal contact center, the simulation with thermal effects better matches the experimental wear scar profile, showing two wear valleys. However, some overall differences remain between the experimental and thermal simulation wear scar profiles. This deviation may result from unaccounted randomness in the wear process or slight environmental temperature differences between the experimental and simulation conditions.  
Figure 10: Comparison of the wear scar profiles between the experiments and simulations for (**a**) 5 N, 300 RPM, and 1 min, (**b**) 10 N, 300 RPM, and 2 min, and (**c**) 10 N, 300 RPM, and 2 min. (**d**) The maximum wear depth difference between the experiments and simulations with and without thermal effects.  
Figure 9: Comparison of contact pressure distribution along the radial direction for (**a**) 15 N and 300 RPM without the thermal effect, and (**b**) 15 N and 300 RPM with the thermal effect (the results are taken from the FEM simulation).  
Overall, when load and speed are sufficient to activate thermal expansion, the simulations with thermal effects provide better predictions of the wear scar profiles. However, they still tend to overestimate wear scar width compared to the experimental results.
# Towards Accurate Children's Arabic Handwriting Recognition via Deep Learning
## 3 Material and Methods
### Proposed Deep Learning Models
#### 3.2.1 Convolutional Neural Network Model
**Fully Connected Layer:** There can be any number of fully connected layers after the convolutional and pooling layers. Each neuron in a fully connected layer is connected to every other neuron in the layers around it. These layers are used to generate predictions and provide the final nonlinear feature combinations of the network. Therefore, in our case, the output of the previous convolutional layers was flattened to create a single long feature vector. Figure 2 shows the last three steps of the learning process, including the fully concatenated layers FC1 and FC2, which provided 512 and 1,024-dimensional feature vectors, respectively. In addition, FC3 was the output layer, and it provided 29 classes using the Softmax activation function, see Equation (3), where \(N\) was the number of output classes. \[Softmax(x_{i})=\frac{e^{x_{i}}}{\sum_{k=1}^{N}e^{x_{k}}} \tag{3}\]  
**Optimization:** We employed Adam, a computationally efficient optimization solver for neural network algorithms, as an optimizer [25]. Furthermore, we used the categorical cross-entropy loss function for this model to estimate the loss (error) and make comparisons and measurements of the distance between the prediction and the correct results; this was used for multiclass classification.
## 4 Practical Experiments
### Boverbream
#### 4.2.2 Evaluation  
We also used _demcoreg_ to assess the accuracy of the PlanetScope DEM by comparing it with a reference DEM in stable terrain (see Figure 15). For this purpose, we utilized a LiDAR DEM _nsajonal detaljert haydemodell 2020_ provided by the Norwegian authorities, acquired at the beginning of August 2020 using airborne laser scanning. This DEM has a GSD of 2 m and a vertical accuracy of 0.12 m [42]. Although coverage of the southern Smerstabb Massif is limited, the available data are sufficient to evaluate the accuracy of the PlanetScope DEM around the Boverbren area.  
The observed errors range from \(\pm\)40 m, with an NMAD of 6.47 m and a StdDev of 14.24 m. Pronounced negative deviations were noted inside the southern Smerstabb Massif, likely due to shadowed areas over steep terrain. Planetscope images, captured in the local morning, often expose strong cast shadows at such locations, as shown in Figure 15. The orthophoto mosaic reveals darkened, steep areas, both of which pose challenges for surface reconstruction due to ambiguities in image matching or steep intersection angles during triangulation.  
Figure 15: Results of the DEM calculation for the Boverbren glacier in 2021. **Top left**: orthophoto mosaic from PSS images. **Top right**: computed PlanetScope DEM with hillshading and the outline of the glaciers in south Smerstabb Massif. **Bottom left**: DoD calculation in the anticipated stable areas comparing the PlanetScope DEM with the LiDAR reference DEM. **Bottom right**: histogram of the DoD calculation, including metrics such as mean, median, and StdDev. Additionally, the NMAD was computed for the outlined area, resulting in 6.47 m.  
However, it is conceivable that these offsets are also attributable to actual terrain changes as the reference dataset and PlanetScope DEM were acquired with a one-year delay. To clearly disentangle these effects, comparisons with reference data collected concurrently would be necessary.  
A statistical evaluation of the DoD for the western area outside the Smerstabb Massif, near the terminus of the Boverbren glacier (highlighted with stronger contour in Figure 15), reveals minor deviations, with mean differences of several decimeters (\(-0.80\) m) and median differences of a few centimeters (0.04 m) compared to the reference LiDAR DEM. The area features mostly flat terrain with moderately steep sections, while the far western region shows steeper slopes and again larger deviations in the DoD.  
The analysis highlights significant errors in steep shadowed areas, likely due to challenges in surface reconstruction, while flatter regions show only minor deviations. However, the potential influence of actual terrain changes remains given the one-year temporal gap between datasets, emphasizing the importance of concurrent validation data for clearer interpretation.