esa-sceva/satcom-chunk-collection huggingface dataset:
# Caching Transient Contents in Vehicular Named Data Networking: A Performance Analysis
## 7 Conclusions  
In this paper we investigated the issues related to the caching of transient contents in V-NDN. We conceived a novel autonomous caching strategy, FDC, in which the caching decision is taken according to the content lifetime. The solution is meant to be as compliant as possible with the legacy NDN caching routines and not to add additional signaling overhead, which could uselessly overwhelm highly dynamic vehicular links. The addition of a single field, i.e., the timestamp, to the NDN Data packet is foreseen to allow nodes infer the actual residual lifetime of contents.  
Simulation results conducted under realistic mobility and data pattern settings confirm the supremacy of the proposal against two representative benchmark solutions in terms of valuable metrics, i.e., content retrieval latency, cache hit ratio, number of hops, and exchanged Data packets.  
FDC can be integrated in traditional caching approaches in order to let them deal with transient content. As future work, we plan to investigate this aspect and to design a more sophisticated caching strategy, e.g., relying on content popularity and topological information of caches, besides content freshness.  
Conceptualization and methodology, M.A., C.C., G.R., G.L. and A.M.; software, M.A.; validation, M.A.; investigation, M.A.; writing-original draft preparation, M.A., C.C. and G.L.; writing-review and editing, M.A., C.C., G.R., A.M. and G.L.; supervision, A.M. and G.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.  
Figure 7: Performance metrics in the highway scenario, when varying the number of consumers (\(\alpha=1.5\)).
## 2 Materials and Methods
### Characterization of MSCs  
MSCs cultured in normal culture conditions (MSCs) and after 24 h starvation and restoration (S-MSCs) were characterized according to the criteria defined by International Society for Cellular Therapy (ISCT) [15], by plastic adhesion, morphology, immunophore-notype, osteogenic and adipogenic differentiation, senescence, and karyotyping. MTT (3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetradizolium bromide) (Sigma-Aldrich, Burlington, MA, USA) assay and immunomodulation assays were also performed in order to evaluate their functionality.
## 3 Results and Discussion
### Spatial Variability of Relative Permeabilities  
Figure 11 shows graphs of the relative phase permeability curves of all sub-volumes from samples A (Figure 13a,b) and B (Figure 13c,d), respectively, before and after rock dissolution. These graphs are provided to analyze the spatial variability of the relative phase permeabilities. As can be seen from Figure 13a, before rock dissolution, sample A can be considered homogeneous in terms of relative phase permeabilities since the relative phase permeability curves of all sub-volumes from this sample are close to each other, and therefore, they can be described by single curves. This is convenient in modeling two-phase fluid flow in larger domains by considering the scaling of the endpoints of the relative phase permeability curves.  
Figure 12: Effect of changes in absolute permeability on the residual (**a**) oil and (**b**) water saturation.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Sub-Volume**} & \multicolumn{2}{c}{**Residual Oil**} & \multicolumn{2}{c}{**Residual Water**} & \multicolumn{2}{c}{**Water Saturation**} \\  & \multicolumn{2}{c}{**Saturation, \%**} & \multicolumn{2}{c}{**Saturation, \%**} & \multicolumn{2}{c}{**Range, \%**} \\ \cline{2-7}  & **Before** & **After** & **Before** & **After** & **Before** & **After** \\ \hline A1 & 44 & 49 & 4 & 3 & 4–58 & 2–76 \\ \hline A2 & 47 & 30 & 4 & 3 & 4–55 & 2–72 \\ \hline A3 & 29 & 22 & 1 & 1 & 1–73 & 1–92 \\ \hline A4 & 30 & 35 & 3 & 3 & 3–77 & 2–70 \\ \hline A5 & 42 & 45 & 3 & 3 & 3–68 & 2–59 \\ \hline B1 & 30 & 24 & 4 & 2 & 3–74 & 2–79 \\ \hline B2 & 41 & 30 & 4 & 2 & 4–68 & 2–75 \\ \hline B3 & 56 & 30 & 5 & 2 & 5–66 & 2–75 \\ \hline B4 & 42 & 27 & 3 & 2 & 3–61 & 1–76 \\ \hline B5 & 48 & 33 & 7 & 3 & 7–55 & 3–67 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Critical points of relative phase permeability curves.  
Rock dissolution affected the sub-volumes of sample A differently, resulting in a redistribution of the relative oil permeability curves in space, and the relative water permeability curves are still close to each other although they have different endpoints (Figure 13b). This indicates an increase in spatial heterogeneity of fluid flow in sample A as a result of rock dissolution.  
In the case of sub-volumes from sample B, there is an opposite trend (see Figure 13c,d). If, before the rock dissolution, the relative permeability curves of sub-volumes exhibited differences, after dissolution, they noticeably converged, indicating a reduction in the spatial heterogeneity of sample B. In addition, the relative oil permeability curves for sub-volumes from sample B became more linear, which could suggest a more uniform displacement of oil by water (see Figure 13d). When comparing Figure 13b with Figure 13d, we can conclude that the relative water permeability slightly changed for sample B, whereas it increased more significantly for sample A, indicating a potential change in wettability from strongly water-wet to less water-wet or even mixed-wet as a result of rock dissolution.
# Enhanced Nondestructive Testing Using Pulsed Eddy Current and Electromagnetic Ultrasonic Techniques
## 1 Introduction
studied the electromagnetic ultrasonic/eddy current composite detection technology for defects in metallic materials. Through the design of composite probes, combined with electromagnetic ultrasonic and eddy current testing methods, it is possible to detect internal and surface defects in metal materials [20]. Therefore, both pulsed eddy current and electromagnetic ultrasonic methods can be used to detect surface and subsurface defects simultaneously. Therefore, this paper presents the design of a combined probe for detecting defects in metal pipelines submerged in seawater, utilizing pulsed eddy current and electromagnetic ultrasonic technologies. A system layer composite method is adopted to obtain independent eddy current signals and electromagnetic ultrasonic signals by applying high-frequency and low-frequency excitation signals, respectively, to the same detector, using an excitation source. By analyzing the two signals, near-surface and deep-layer defect information can be obtained, and the two separate detection methods can complement each other. It is worth noting that the energy conversion efficiency peaks when the excitation frequency aligns with the natural frequency of the EMAT. At this specific frequency, the coil achieves a higher signal-to-noise ratio, thus enhancing detection performance. The choice of excitation frequency should consider the physical properties of the tested object and the operating environment of the EMAT. This study examines the influence of various factors on the energy conversion efficiency of the composite detection probe, aiming to optimize the probe design and determine the most suitable structural design for detecting flaws in ship metals. The experimental results indicate that the probe can comprehensively detect corrosion thinning defects in the target.
## 3 Shake Table Model Tests
### Results and Analysis
#### 3.4.1 Strain Analysis
Figure 7: Peak distribution of (**a**) circumferential and (**b**) longitudinal strain increments along the longitudinal direction of the tunnel under the El-Centro wave. In particular, when subjected to El-Centro wave excitation (refer to Figure 7), the introduction of anti-seismic measures effectively mitigated strain responses. In the absence of these measures, the maximum and minimum circumferential strain values were recorded at 71 \(\upmu\varepsilon\) and \(-\)73 \(\upmu\varepsilon\), respectively. Subsequent to the implementation of interventions such as surrounding rock grouting, seismic joints, and shock absorption layers, reductions in strain levels were evident. Specifically, the maximum circumferential strain decreased to 38 \(\upmu\varepsilon\), 48 \(\upmu\varepsilon\), and 52 \(\upmu\varepsilon\), corresponding to the reduction ratios of \(-\)46.5%, \(-\)32.4%, and \(-\)26.8%, respectively. Similarly, the minimum circumferential strain values decreased to \(-\)33 \(\upmu\varepsilon\), \(-\)38 \(\upmu\varepsilon\), and \(-\)51 \(\upmu\varepsilon\), with reduction ratios of \(-\)54.8%, \(-\)47.9%, and \(-\)30.1%. As for longitudinal strain, the initial maximum value in the absence of measures was recorded at 62 \(\upmu\varepsilon\). Post-grouting, seismic joints installation, and shock absorption layer application, this figure decreased to 34 \(\upmu\varepsilon\), 43 \(\upmu\varepsilon\), and 47 \(\upmu\varepsilon\), respectively. The reduction ratios for longitudinal strain were calculated at \(-\)45%, \(-\)30.64%, and \(-\)24.2%. Under Taft wave excitation, as illustrated in Figure 8, the implementation of surrounding rock grouting, seismic joints, and shock absorption layers effectively reduced strains. The reduction ratios of maximum circumferential strain were \(-\)60.8%, \(-\)38%, and \(-\)38%, respectively, for each measure. Meanwhile, the reduction ratios of minimum circumferential strain were \(-\)33.3%, \(-\)7.8%, and \(-\)13.7%, respectively. In terms of longitudinal strain, the reduction ratios of maximum strain were \(-\)53.6%, \(-\)36.2%, and \(-\)36.2% following the application of the three controls. The reduction ratios of minimum longitudinal strain were \(-\)30.2%, \(-\)22.6%, and \(-\)34%, respectively. Similar trends were observed under artificial wave excitation, as depicted in Figure 9. In this case, the reduction ratios of maximum circumferential strain were \(-\)53.3%, \(-\)34.7%, and \(-\)34.7% with each control. The reduction ratios of minimum circumferential strain were \(-\)51.9%, \(-\)9%, and \(-\)14.8%, respectively. For longitudinal strain, the reduction ratios of maximum strain ranged from \(-\)39% to \(-\)25.4%, while the reduction ratios of minimum strain ranged from \(-\)47% to \(-\)16.3%. Furthermore, the analysis indicated a shift in the locations of peak strain at the fault interface section after the installation of seismic joints and shock absorption layers, demonstrating the effectiveness of these measures against fault zone amplification effects.
# The Potential of Indole Alkaloids in Bone Health and Osteoporosis Management
## 5 Indole Alkaloids
### Vindoline  
The indole alkaloid called vindoline (methyl 3\(\beta\),4\(\beta\)-dihydroxy-16-methoxy-1-methyl-6,7-didehydro-2,8,5\(\alpha\),12\(\beta\),19\(\alpha\)-aspiroespsin-3\(\alpha\)-carboxylate) (**13**) (Figure 5) was isolated from the medicinal plant _Catharanthus roseus_ and has been shown to have anti-tumor, antidiabetic, antioxidant, and anti-inflammatory properties [59; 60]. Vindoline can decrease osteoclast development from bone marrow macrophage (BMM) progenitor cells as well as mature osteocl bone resorption, as [PERSON] et al. [61] were the first to demonstrate.  
Figure 5: Structure of vindoline (**13**).  
Additionally, they have shown that the molecular mechanism of action of vindoline is based on its inhibitory effect against the production of intracellular reactive oxygen species (ROS) and the activation of MAPK, including p38, JNK, and ERK. This effect suppresses the induction of c-Fos and NFATc1, which in turn downregulates the expression of the genes required for the formation of osteoclasts and bone resorption.  
Also, their in vivo investigation on vindoline-treated mice revealed protection against trabecular bone degradation and bone loss brought on by ovariectomies (OVXs). According to their research, vindoline reduced the in vitro bone resorption capacity of mature osteoclasts and the generation of osteoclasts derived from BMM [61]. Vindoline specifically inhibits the activation of all three MAPK signaling pathways as well as the generation of intracellular ROS, which in turn decreases the expression of c-Fos and NFATc1.  
Moreover, they found that the increase in NFATc1 expression was postponed during the differentiation of osteoclasts, which led to the downregulation of several NFAT-responsive genes implicated in the fusion of osteoclasts, such as CTSK, MMP9, and TRAP. The same scientists then looked at the possible advantages of vindoline treatment in OVX mice model-induced bone loss _in vivo_, and they found that vindoline treatment decreased the quantity of TRAP-positive osteoclasts in bone. They demonstrated that vindoline has anti-osteoclastogenic and anti-resorptive qualities that can be used to treat or control osteoporosis and other osteoclast-mediated osteolytic disorders.
# Link Budget Analysis with Laser Energy for Time Transfer Using the Ajisai Satellite
## 2 TLTT Link Budget  
### Link Budget Equation for TLTT  
The radar link equation is used to calculate the mean signal flux at an SLR receiver, which is expressed as the mean number of photoelectrons (\(n_{p}\)) in the SLR system [11].  
\[n_{p}=\left(E_{t}\frac{\lambda}{\hbar c}\right)\eta_{t}\frac{G_{t}}{4\pi R^{2 }}\frac{\sigma}{4\pi R^{2}}A_{r}\eta_{r}\eta_{q}T_{a}^{2}T_{C}^{2},\ \ (1) \tag{1}\]  
where \(\lambda\) is the wavelength of the laser pulse, \(h\) is the Planck's constant, and \(c\) is the speed of light. The link budget equation consists of the system dependent terms and the geometric configuration terms. The system dependent terms include the laser pulse energy \((E_{t})\), the transmit optics efficiency (\(\eta_{t}\)), the transmitter gain (\(G_{t}\)), the receiving area of the telescope (\(A_{r}\)) with receiving optics efficiency (\(\eta_{r}\)), the quantum efficiency of the photon detector (\(\eta_{q}\)), and the cross section of satellite's CCRs (\(\sigma\)). The terms that correspond to the geometric configuration are the free-space loss in the laser travelling path (\(R\)), atmospheric attenuation (\(T_{a}\)), and cirrus cloud effects (\(T_{c}\)).  
The TLTT approach for laser time transfer using the Ajisai satellite has two main differences in calculating the link budget when compared to the general SLR observation. The first is that there are two ground stations for transmitting and receiving the laser signal, respectively, the other is the cross section of Ajisai's reflective mirror used for TLTT application, which is very much smaller than the CCRs on the satellite and is affected by the phase angle of the satellite between the two ground stations. The reflective mirror on Ajisai is a small part of the satellite surface, with a virtual radius of 8.5 m; the average size of the reflective mirrors is 0.04 m\({}^{2}\)[8]. Therefore, we need to take into account these two characteristics in the link budget equation to realize the TLTT technique using the Ajisai satellite.
# VidBlock: A Web3.0-Enabled Decentralized Blockchain Architecture for Live Video Streaming
## 4 Experiment and Evaluation
### Security Analysis
#### 4.3.2 Security Probability Analysis  
The security of VidBlock against 51% attacks is heavily influenced by the network size (\(N\)) and the proportion of malicious nodes (\(P_{m}\)). To evaluate this relationship, a probabilistic model was used to calculate the probability of a successful attack (\(P_{\text{attack}}\)) based on the attacker controlling a majority of the network's nodes (\(k\geq\lceil N/2\rceil\)). The probability is given by the following equation:  
\[P_{\text{attack}}=\sum_{k=\lceil N/2\rceil}^{N}\binom{N}{k}(P_{m})^{k}(1-P_{m} )^{N-k}, \tag{1}\]where  
* \(N\) is the total number of nodes in the network;
* \(k\) is the number of nodes controlled by the attacker (\(k\geq\lceil N/2\rceil\));
* \(P_{m}=\frac{M}{N}\) is the proportion of malicious nodes in the network;
* \(1-P_{m}\) is the proportion of honest nodes in the network.  
Simulation Results  
The results of the simulation, shown in Table 4, highlight the exponential reduction in attack probability as the network size increases. The probability of a successful 51% attack (\(P_{\text{attack}}\)) was evaluated for various network sizes (\(N=50,100,200,300,400,500\)) and attacker power ratios (\(P_{m}=0.1,0.2,0.3,0.4\)).  
Practical Implications for VidBlock  
The results emphasize the critical importance of maintaining a large and decentralized network to mitigate the risk of a 51% attack. By increasing the network size (\(N\)), VidBlock can exponentially reduce the attack probability, even when the attacker controls a significant portion of the network (\(P_{m}\)).  
To further enhance security, strategies such as incentivizing honest participation, promoting decentralization, and implementing robust monitoring systems can be considered. These approaches ensure long-term stability and resilience against both external and internal threats. A detailed discussion of these strategies is provided in Section 5.
# Automatic Modulation Recognition Using Compressive Cyclic Features
## 4 Simulation and Performance Analysis
This results from the larger observation interval (larger symbol number), which is required by the nonuniform sampling. As is well known, a larger observation interval always guarantees a more reliable feature estimation. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Samples** & \multicolumn{2}{c}{**10,240**} & \multicolumn{2}{c}{**15,360**} & \multicolumn{2}{c}{**20,480**} \\ \hline
**Symbols** & 4096 & 640 & 4096 & 960 & 4096 & 1280 \\
0 dB & 39.4\% & 38.4\% & 44.7\% & 40.9\% & 51.8\% & 44.4\% \\
3 dB & 52.8\% & 49.2 \% & 64.6\% & 62.3\% & 77.8\% & 71.3\% \\
6 dB & 68.0\% & 59.6\% & 82.1 \% & 81.7\% & 95.3\% & 90.2\% \\
9 dB & 79.7\% & 78.4\% & 93.4\% & 92.7\% & 98.8\% & 97.2\% \\
12 dB & 84.2\% & 72.1\% & 97.3\% & 94.1\% & 99.6\% & 97.4\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison for \(\Omega_{1}\) between compressive sensing (CS) method and classical method with equivalent number of samples. Figure 4: Performance versus SNR for \(\Omega_{2}\). Figure 3: Performance versus SNR for \(\Omega_{1}\). AMR: automatic modulation recognition.
# POI Recommendation Scheme Based on User Activity Patterns and Category Similarity
## 5 Conclusions  
In this paper, we proposed a POI recommendation scheme in which user activity patterns and the similarity of categories are considered. The proposed scheme was used to organize users based on their activity level and the characteristics of both users and locations. Furthermore, it provided more personalized recommendations by taking into account the category similarity, time, and location data that were collected from users. We evaluated the performance of the proposed scheme and compared it with that of an existing one. The performance evaluation results revealed the proposed scheme's superiority in terms of performance over the existing scheme. Unlike in the existing scheme, user activity patterns and category similarity were considered in the proposed scheme. Therefore, the proposed scheme enhanced the precision of personalized recommendation results by approximately 16%. Expected applications of the proposed scheme include personalized recommendation schemes in which social media data or applications that employ recommendation schemes are utilized.  
In this paper, user patterns based on time periods were utilized. However, the accuracy of the recommendation may be influenced by the manner in which the time period is divided, as the patterns of users are highly diverse. Consequently, we intend to employ sliding windows to analyze time period patterns in future research and explore time periods for utilizing them to provide recommendations. Additionally, we intend to implement the proposed scheme in actual recommendation systems, taking user feedback into account.  
Conceptualization, J.L., S.L., H.L., K.B. and J.Y.; methodology, J.L., S.L., H.L., K.B. and J.Y.; software, S.L.; validation, J.L., S.L., H.L., K.B. and J.Y.; formal analysis, J.L., S.L., H.L., K.B. and J.Y.; data curation, J.L. and S.L.; writing--original draft preparation, J.L. and S.L.; writing--review and editing, J.Y. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT). (No. 2022R1A2B5B02002456/33%, RS-2023-00245650/34%) and Innovative Human Resource Development for Local Intellectualization program through the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (IITP-2024-2020-0-01462, 33%).  
Not applicable.  
The original data presented in the study are openly available in Foursquare Dataset at [[https://sites.google.com/site/yangdingqi/home/foursquare-dataset](https://sites.google.com/site/yangdingqi/home/foursquare-dataset)]([https://sites.google.com/site/yangdingqi/home/foursquare-dataset](https://sites.google.com/site/yangdingqi/home/foursquare-dataset)) (accessed on 19 November 2024).  
The authors declare no conflicts of interest.  
Figure 10: Performance evaluation for low-activity groups.
## 3 Metadata Definition  
In order to formalize the metadata needed to implement the scenario described in Figure 1-3, a simple metadata model was developed (Figure 4). The central concept is that of a _Privacy Profile_, a combination of:  
* _Personal Data_: This is the description of the actual data from public registers
* _Identity_: This is the profile of the user (student, taxpayer, _etc._)
* A _Data Policy_ (explained below in Figure 5), where users define their preferences regarding data sharing and/or data protection; controls are applied so as to respect relevant regulations.  
There are several well-developed and sound approaches to _Personal Data_ and _Identity_ metadata (for example Windows CardSpace [39], OpenID [40] or the open-source Higgins [41]). Furthermore many governments have defined their own practices, such the eCH-0107 [42] standard created by the Swiss eCH standardization body. These various models and standards do not all cover the same ground but  
Figure 4: Privacy profile model.  
Figure 5: Public data access policy model.  
let us take Higgins (Figure 6) in order to exemplify the concept: Personal data (name, address, _etc._) are formalized, as well as relationships with other people (on the basis of FOAF-Friend of a Friend [43]). On top of that an identity layer is added on the basis of a SKOS (Simple Knowledge Organization System [44]) classification and on the SPARQL [45] query language and inference mechanisms (SPIN-SPARQL Inferencing Notation [46]). SPIN is used to attach rules and constraints to the identity and data models (e.g., to check that the data match one's identity in a given context).  
The generic Higgins model is used for _Personal Data_ and _Identity_ metadata, but a specific _Data Policy_ model is needed. There have indeed been efforts to develop privacy policy markup languages (for example P3P-Platform for Privacy Preferences [47]) or access control languages (e.g., XACML-eXtensible Access Control Markup Language [48]). These languages do provide a sound reference to develop a specific set of relevant metadata. They do not however completely suit the requirements of the framework and this is why it needed some adaptations. For the basic description of _Data Policies_ (Figure 5), standards such as Dublin Core are used. A few concepts regarding the life cycle of a document are added: _Creation_, _version_, _validation_, _publication_ and _expiration_. Data are accessible on the basis of given _data access_ policies only between the time when they were officially validated and published until their expiration date, if they are compliant with _data protection_ requirements. Again, SPIN capabilities are used in order to match policies, data and individuals.  
Figure 6: [PERSON] personal data model [49].