esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Test Materials and Test Methods
### Test Scheme  
In the present work, the influence of sand particles (content \(\alpha_{\mathrm{s}}\) and size \(d\)) on the strength and anti-dry-wet cycle characteristics of the cement-solidified soil was studied. According to the research results of [PERSON] et al. (2016) and [PERSON] et al (2016), 15% cement content is both effective and economical for improving the unconfined compression strength (UCS) of soft soil; thus, this cement content was also used in the present work, whereas the water-cement ratio was set at 1:1. In the case of UCS tests, the sand particle content of the CS-SS samples were set at 0%, 2%, 5%, 10%, 15%, and 30%; the sand particle size were set at 0.075\(\sim\)0.25 mm (fine sand), 0.25\(\sim\)0.5 mm (medium sand), and 0.5\(\sim\)1.0 mm (coarse sand). Three parallel samples were prepared for each group of the test. A series of UCS tests were conducted for 135 CS-SS samples in 45 test groups. In the case of the dry-wet cycle tests, the sand particle content of the CS-SS samples was set at 0%, 5%, and 15%; and the sand particle size was set at 0.075\(\sim\)0.25 mm (fine sand), 0.25\(\sim\)0.5 mm (medium sand), and 0.5\(\sim\)1.0 mm (coarse sand), respectively. The CS-SS samples were subjected to two dry-wet cycles N (30 d/cycle) under seawater and freshwater conditions, three parallel samples were prepared for each group of the tests, and a total of 72 groups of the 216 samples were prepared for the dry-wet cycle tests. The specific test scheme is shown in Table 4, and the tests were carried out according to the Specification of the soil test (GB/T50123-2019) ([PERSON] et al., 2018).  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline
**Composition** & **CaO** & **Fe\({}_{2}\)O\({}_{3}\)** & **SiO\({}_{2}\)** & **Al\({}_{2}\)O\({}_{3}\)** & **MgO** & **SO\({}_{3}\)** & **Loss** \\ \hline Content (\%) & 62.36 & 4.27 & 22.65 & 5.74 & 0.85 & 1.08 & 1.03 \\ \hline \end{tabular}
\end{table}
Table 2: Main chemical compositions of cement expressed as relative oxides of the elements by XRF analysis.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Composition** & **NaCl** & **MgCl\({}_{2}\)** & **Na\({}_{2}\)SO\({}_{4}\)** & **CaCl\({}_{2}\)** & **KCI** & **NaHCO\({}_{3}\)** & **KBr** & **H\({}_{3}\)BO\({}_{3}\)** & **SrCl\({}_{2}\)** \\ \hline Dosage (g/L) & 24.53 & 5.20 & 4.09 & 1.16 & 0.695 & 0.201 & 0.10 & 0.027 & 0.025 \\ \hline \end{tabular}
\end{table}
Table 3: Compositions of artificial seawater, expressed as the concentration of salt in the water.
# Consistency Models of NoSQL Databases
## 5 NoSQL Consistency Implementations
### Cassandra
The _Replication Factor_ does not guarantee that the updated value is fully propagated, only that the data will eventually have a given number of copies in the cluster. The _Write Consistency Level_ is responsible for how many copies are made before acknowledging the write operation to the client who had requested it. To analyze how eventual consistency is affected by the write and read consistency configurations offered by Cassandra, UC Berkeley developed a simulator called Probabilistically Bounded Staleness (PBS) [37]. Figures 5-8, show the resulting curves of our simulation using PBS, given the number of available cluster hosts (N), the read quorum (R) and the write quorum (W). They represent the probability of a client request having the latest version of the data over time (ms) for a given N, W and R combination. All the above configurations assume a _Replication Factor_ above 1. If the _Replication Factor_ were 1, there would be a single node storing a given data object, therefore the write operation and read operation would only execute in that single node resulting in strong consistency (as seen in Figure 5) for all configurations in Figures 5-8. Figure 5: Probabilistically Bounded Staleness (PBS) results for (N = 5, R = 1, W = N = 5) and (N = 5, R = N = 5, W = 1).
# Opportunistic Multipath Routing in Long-Hop Wireless Sensor Networks
## 4 Performance Evaluation  
In this section, we describe the simulation results for the REER, RGMR, RRDLA, and the proposed scheme. REER is the most representative multipath routing protocol that constructs two paths and transmits data on the paths. RGMR constructs several paths depending on the required packet delivery ratio. RRDLA selects the best single path based on the learning algorithm.  
In Section 4.1, we analyse a time complexity to confirm that a node has a capability to perform the proposed scheme. In Section 4.2, we describe the simulation environment and evaluation factors. The packet delivery ratio versus the end-to-end distance and link reliability is described in Section 4.3. The energy consumption versus the end-to-end distance and link reliability are explained in Section 4.4. The packet delivery ratio and energy consumption versus the number of source nodes are explained in Section 4.5. Finally, The packet delivery ratio and energy consumption versus the number of nodes are described in Section 4.6.
# Routing Algorithm Based on Trajectory Prediction in Opportunistic Networks
## 4 Performance Evaluation
### Results and Discussion
#### 4.2.3 End-to-End Delay  
This section mainly analyzes the average end-to-end delay performance of four different algorithms. The change law of average end-to-end delay with simulation time length is introduced and the effect of the number of nodes on the average end-to-end delay is studied.  
Figure 6 shows the average end-to-end delay of the RATP algorithm, CHBPR algorithm, GPCR algorithm and Greedy algorithm under different simulation times. It can be seen from the figure that as the simulation time increases, the average end-to-end delay of the four algorithms also increases. This is because, as the simulation time increases, the number of packets in the network increases, and the entire network takes more time to process, resulting in an increase in data transmission delay. In any case, the RATP algorithm average end-to-end delay is significantly slower than the other three algorithms.  
Figure 4: Delivery Ratio vs simulation time.  
Figure 5: Delivery Ratio vs number of nodes.  
Figure 7 shows the average end-to-end delay of the RATP algorithm, CHBPR algorithm, GPCR algorithm and Greedy algorithm under different node numbers. It can be seen from the figure that as the number of nodes increases, the average end-to-end delay of the four algorithms increases first and then decreases. When the number of nodes is small, the selected forwarding node is far away, resulting in an increase in data transmission delay. When the number of nodes reaches a certain level, the number of forwarding nodes in the network increases, the data transmission time is relatively reduced, and the transmission delay is relatively reduced. Compared with the other three algorithms, the RATP algorithm has the lowest average end-to-end delay. This is because the RATP analyzes the distribution of the entire network node and the global information of the network, making the selected routing more connected, the higher the reliability and real-time, the lower the delay.
# An Application of Manifold Learning in Global Shape Descriptors
## 2 Background
### Manifold Learning  
To make the current contribution self-contained, we provide a brief introduction of manifold learning from the data analysis perspective. Dimensionality reduction of high-dimensional data is a critical step in data analysis and processing. Non-linear dimensionality reduction, also known as _manifold learning_, is a problem of finding a low-dimensional representation for high-dimensional data. Several local and global manifold learning methods have been developed including Isomap [38; 39], LLE [40; 41], Laplacian Eigenmap [27], and Diffusion maps [42].  
Consider a set \(x_{1},...,x_{n}\in\mathcal{M}\) of \(n\) points on a manifold embedded in an \(l\)-dimensional space \(\mathbb{R}^{l}\). Manifold learning methods look for a set of corresponding points \(y_{1},...,y_{n}\) in \(\mathbb{R}^{m}(m\ll l)\) as a structural representation, while respecting some local or global information. Each method attempts to minimize a cost function in this mapping.  
Laplacian Eigenmap [43], proposed by [PERSON] and [PERSON] in 2002, is a computationally efficient and mathematically well-studied manifold learning technique. It is based upon graph Laplacian and Laplace-Beltrami operator on the manifold. Accordingly, it is considered as a spectral analysis method. Laplacian Eigenmap deals with sparse, symmetric, and positive semi-definite matrices. It is in close connection to the heat flow [27; 43].  
Briefly speaking, for a given manifold, Laplacian Eigenmap applies the graph Laplacian operator and uses the eigenfunctions of such operator to provide the optimal embedding. Laplacian Eigenmap preserves local information by minimizing the distance between embedded points, which are mapped from adjacent points in the original high-dimensional space [27]. Aside from the locality preserving property, it provides structural equivalence and discrimination by capturing the intrinsic geometric structure of the manifold. The structural equivalence property states that two similar manifolds will have similar representation after projecting into a lower dimension space [44; 45].  
Some other manifold learning methods, e.g., Isomap, LLE, and Diffusion map, are also based on spectral analysis of the high-dimensional manifold. In contrast to these methods that construct the orthogonal basis of their desired low-dimensional space using eigenfunctions of an LB operator, we develop our scale-invariant shape descriptor using the spectrum of the LB operator. Even though our primary focus is on the Laplacian Eigenmap, owing to its unique properties, we believe that other spectral manifold learning methods are also capable of extracting informative and discriminative shape fingerprints.
## 5 System Implementation and Configuration
### Load Profile  
The LTE-macro BS load is critical for designing a reliable and efficient system. Sizing and modelling of the solar power system depend on the load profile. We used 24-hour load values for 365 days for an accurate analysis. The seasonal load profiles for both the DC and AC loads are shown in Figure 10.
# Real-Time Surveillance System for Analyzing Abnormal Behavior of Pedestrians
## 3 Proposed Method
### Intrusion and Loitering Abnormal Behavior Judgment Algorithm  
The intrusion and loitering detection process first checks if an interesting object enters the pre-defined ROI. A pedestrian's action is classified as loitering if one or more people enter a pre-specified ROI for more than 10 seconds. KISA dataset requires 10 s for authentication of loitering, but user can change the time. An action is classified as intrusion if the entire body of one or more people enter a pre-specified ROI. To analyze the abnormal situation for real-time streaming video using a video transmission server, we developed an algorithm that judges the intrusion and loitering situation based on the referenced evaluation criteria only with object tracking information. The coordinate information of the intrusion and roaming area of the image to be determined is obtained from a predefined Extensible Markup Language (XML) file, and the ROI according to the coordinates is set in the input image. Figure 7 shows two ROIs of intrusion and loitering. The green ROI represents the object detection area. This area is predefined, such as intrusion, loitering ROI, and no object is detected outside of this area.  
In this paper, we determine object intrusion in the ROI by detecting its coordinate using deep learning. Since existing intrusion detection methods using a polygonal ROI require a large amount of computation, we proposed a computationally efficient method for intrusion detection in a polygonal ROI using background images. As shown in Figure 8, a background image is generated where the ROI of the coordinates estimated by the OpenCV library is set to 1, and the other regions are set to 0. Since the generated background image has the same image size as the input image, it is possible to determine intrusion and loitering if the coordinate of located object exists. The presence or absence of an object in the ROI is calculated using Formula (5).  
\[\begin{split} Person_{N}(x,y)\times ROI(x,y)=0,\ \ Person_{N}(x,y)\times ROI(x,y)=1\end{split} \tag{5}\]  
In Figure 8a, the pre-specified intrusion region is marked in blue, and Figure 8b shows that the inside of the ROI area has a value of 1, and the outside area of the ROI has a value of 0. In the proposed method, the coordinate information of the tracking object is acquired to determine whether the object is inside or outside the ROI area, and based on this, intrusion and loitering are determined.  
Figure 7: Intrusion and Loitering Region of Interest (ROI): (**a**) Intrusion ROI, (**b**) Loitering ROI.
## 5 Possibilities of Reducing the Acrylamide Content in French Fries and Potato Chips
### Technological Factors
#### 5.2.5 Drying of Potato Chips after Frying  
In the production process of potato chips, there is one more solution to reduce acrylamide content in the ready product. It consists of shortening the frying time of the slices and then drying them to the required humidity. As a result of the drying of potato chips after frying at 185 \({}^{\circ}\)C, the amount of acrylamide in the ready snacks decreased by about 70%, and after treatment at 160 \({}^{\circ}\)C by about 80% [113]. [PERSON] et al. [139] conducteda new study on the possibility of reducing the frying time of potato slices in oil using a conventional fryer and drying the samples to a suitable moisture content using radio-frequency (RF) drying. It was found that in potato chips dried using RF after frying the amount of acrylamide decreased by about 26% in comparison with the control sample (without drying). All the processes used in the production of French fries and potato chips may, to a greater or lesser extent, reduce the amount of acrylamide in potato snacks. However, the fundamental problem with strategies to prevent the formation of AA in ready products lies in the fact that this compound is formed through the same Maillard reactions as the compounds responsible for shaping the pleasant and desirable taste, smell, and color [1; 2; 7; 45] quality features expected by the consumer. Therefore, these actions must be balanced in terms of maintaining the required organoleptic features of potato snacks, with the lowest possible level of acrylamide.  
The harmfulness of this toxic compound for human health and life has been confirmed by many scientific studies and the consumption of potato snacks is constantly increasing. Therefore, it would be extremely important to conduct a campaign aimed at making consumers (especially children and young people) aware of the risks that acrylamide poses to their health.
## 5 Conclusions  
The present study investigated the lung dose and the pulmonary effects in vivo of nebulized surfactant during HFNC. The in vitro study revealed relatively low surfactant lung doses, irrespective of the NC type used (<2% of the nominal dose). No signs of pulmonary efficacy were observed after the nebulization of a 400 mg/kg surfactant dose delivered to surfactant-depleted rabbits with respiratory distress. Conversely, the intratracheal instillation of a clinical dose of surfactant (200 mg/kg) significantly improved arterial oxygenation and lung mechanics. The lack of in vivo effect may be explained by the low surfactant deposition in the animals' lungs, which primarily occurred during nebulization via HFNC due to the impaction of a large fraction of the aerosol in the NCs, and also by the release of a significant amount of the surfactant aerosol dose to the ambient air through the air leak occurring at the HFNC interface. The results of the present study discourage the use of HFNC as a non-invasive respiratory support modality for the delivery of nebulized surfactant under the described configuration  
Conceptualization, I.M., M.L., M.A.T., A.L., F.B. and F.S.; data curation, A.M., M.S., M.N., G.P., A.C. and X.M.; formal analysis, A.M., M.S., M.N. and X.M.; investigation, F.R., A.M., M.S., M.N., G.P., A.C., I.M., M.L., A.L. and F.S.; methodology, F.R., M.S., M.N., G.P., A.C., R.L.D., M.A.T., X.M., A.L. and F.S.; project administration, F.B. and F.S.; resources, R.L.D., M.A.T. and F.S.; software, A.M.; supervision, M.A.T., A.L., F.B. and F.S.; validation, F.R., A.M., M.S., M.N., I.M. and M.L.; visualization, F.R., M.N. and G.P.; writing--original draft, F.R. and X.M.; writing--review and editing, F.R., G.P., A.C., I.M., M.L., R.L.D., M.A.T., X.M., A.L., F.B. and F.S. All authors have read and agreed to the published version of the manuscript.  
This research was supported by Chiesi Farmaceutici S.p.A.  
Not applicable.  
This research was supported by Chiesi Farmaceutici. [PERSON], A.M., M.S., M.N., G.P., A.C., I.M., M.L., F.B. and F.S. are Chiesi Farmaceutici S.p.A. employees. [PERSON], [PERSON] and [PERSON] served as consultants for Chiesi Farmaceutici S.p.A. in this study. R.L.D. has no conflicts of interest to declare that are relevant to the content of this article. The company had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.
# Research on Advancing Radio Wave Source Localization Technology Through UAV Path Optimization
###### Abstract  
With an increasing number of illegal radio stations, connected cars, and IoT devices, high-accuracy radio source localization techniques are in demand. Traditional methods such as GPS positioning and triangulation suffer from accuracy degradation in NLOS (non-line-of-sight) environments due to obstructions. In contrast, the fingerprinting method builds a database of pre-collected radio information and estimates the source location via pattern matching, maintaining relatively high accuracy in NLOS environments. This study aims to improve the accuracy of fingerprinting-based localization by optimizing UAV flight paths. Previous research mainly relied on RSSI-based localization, but we introduce an AOA model considering AOA (angle of arrival) and EOA (elevation of arrival), as well as a HYBRID model that integrates multiple radio features with weighting. Using Wireless Insite, we conducted ray-tracing simulations based on the Institute of Science Tokyo's Ookayama campus and optimized UAV flight paths with PSO (Particle Swarm Optimization). Results show that the HYBRID model achieved the highest accuracy, limiting the maximum error to 20 m. Sequential estimation improved accuracy for high-error sources, particularly when RSSI was used first, followed by AOA or HYBRID. Future work includes estimating unknown frequency sources, refining sequential estimation, and implementing cooperative localization.  
r 2025 19 March 2025 4 May 2025 5 May 2025 16 May 2025 19 March 2025
## 4 Conclusions  
The achieved output pulse duration of 2.1 ps is close to bandwidth limitation in the case of Yb:YAG while a TBWP of 16.3 in the case of Yb:CaF\({}_{2}\) gives room for further pulse compression down to sub-picoseconds. A maximum pulse energy of 40 \(\upmu\)J was obtained. However, nonlinear effects such as self phase modulation (SPM) becomes an issue above 5 \(\upmu\)J. For higher pulse energies either a larger mode-size diameter or a CPA concept has to be chosen. We observed piezoelectric ringing at a repetition rate of 465 kHz of the BBO crystal while a high polarization contrast was achieved outside the resonances. Compared to our previous experiences where BBO crystals could even be damaged/cracked by piezoelectric ringing (at much sharper resonances: \(\approx\)200 Hz) the suppliers achieved good progresses on resonance control and damping. In summary, we demonstrated the to our knowledge highest repetition-rates of regenerative amplification in Ytterbium-doped materials, that is 2 MHz in Yb:YAG and 1 MHz in Yb:CaF\({}_{2}\). At highest repetition rates the duty cycle of the Pockels cell (repetition rate \(\times\) amplification time) approaches 50%. A further scaling of the repetition rate could be performed at a reduced number of round trips, where also multipass amplifiers become attractive.
# Case Study and Risk Assessment of Water Inrush Disaster in Qingdao Metro Line 4
## 3 Analysis on the Causes of the Collapse  
### Factors Leading to the Collapse  
It is obvious from Figure 2 that the topography near the disaster location looks like a \"funnel\", which made groundwater tend to converge at the bottom of the tunnel. The strata at the disaster location, from top to bottom, consists of a 6.4 m plain fill layer, a 0.8 m silt clay, a 7.1 m medium to coarse sand, a 4.9 m silt clay and tuff with different degrees of weathering. The tunnel is located in strongly weathered tuff and moderately weathered tuff. In the collapse zone, the tunnel passes through the bottom of a \"funnel\" with a buried depth of approximately 19.6 m, while the water level relative to the top of the tunnel is 19 m. As the tunnel was excavated, groundwater tended to flow into the tunnel at the bottom of the funnel. The strongly weathered tuff at the tunnel vault is extremely fragmented and fissures were developed. Tensile failure and crack expansion of the rock caused by the blasting vibration provided additional water channels. These factors caused the tunnel vault to bear a large water pressure. In this situation, the thickness of strongly weathered tuff at the tunnel vault in the collapsed area is only 0.7 m. According to the statistics, the  
Figure 6: Evolution process of the disaster.  
Figure 7: Tunnel after cleaning.  
cumulative rainfall in the Shazikou area from 11 May to 27 May was 73 mm, as shown in Figure 8. On 17 May, the rainfall was 56.1 mm. From 26-27 May, the rainfall continued for two days with an amount of 4.8 mm. The continuous rainfall provided ample recharge of groundwater, which worsened the situation. These two main factors are further analyzed in the next section.