esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
Moreover, these particular sites are important study-cases because satellite ground stations of NASA and ESA are located there (Fucino, Madrid, White Sands), or because long-term radio propagation experiments were performed at the sites (Fucino, Gera Lario, Madrid, Spino d'Adda), or just because there are large cities in these areas (Prague, Norman, Tampa, Vancouver). Following our previous studies of the GeoSurf links [22], we simulate \(A(t)\) at 80 GHz (mm-wave), circular polarization, which is the new frontier of satellite frequencies. After this introduction, in Section 2, we summarize the theory of the method mentioned above; in Section 3, we calculate the link efficiency-and related parameters-in the zenith paths at the sites indicated in Table 1; in Section 4, we extend the theory by considering extra fixed power margins; in Section 5, we summarize and discuss the main findings and discuss potential directions for future work. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Site** & **Latitude N (\({}^{\circ}\))** & **Longitude E (\({}^{\circ}\))** & **Altitude \(H_{S}\) (m)** & **Rain Rate Observation Time (Years)** \\ \hline Spino d’Adda (Italy) & 45.4 & 9.5 & 84 & 8 \\ \hline Gera Lario (Italy) & 46.2 & 9.4 & 210 & 5 \\ \hline Fucino (Italy) & 42.0 & 13.6 & 680 & 5 \\ \hline Madrid (Spain) & 40.4 & 356.3 & 630 & 8 \\ \hline Prague (Czech Republic) & 50.0 & 14.5 & 250 & 5 \\ \hline Tampa (Florida) & 28.1 & 277.6 & 50 & 4 \\ \hline Norman (Oklahoma) & 35.2 & 262.6 & 420 & 4 \\ \hline White Sands (New Mexico) & 32.5 & 253.4 & 1463 & 5 \\ \hline Vancouver (Canada) & 49.2 & 236.8 & 80 & 3 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Geographical coordinates, altitude (km), number of years of continuous rain—rate time series measurements at the indicated sites.
# Next-Generation Gravity Missions: Sino-European Numerical Simulation Comparison Exercise
## 1 Introduction
On US side, the United States National Academies of Sciences, Engineering, and Medicine published the decadal strategy for Earth observation from space [13], where mass change was identified as one of the top five designated observables to be implemented by future US Earth observation missions, in order to ensure continuity and enable long-term mass budget analyses of the Earth system. A NGGM concept was also proposed in China, and the key technologies have been developed to meet the requirements of NGGM [14; 15; 16]. The objectives of Chinese NGGM are not only to perform global gravity measurements, but also to verify the maturity of key technologies required for space-based gravitational-wave detection [17] to a certain level of precision. The scientific objectives and the system requirements of Chinese NGGM are under investigation in these years. This mission is expected to be approved soon, and is planned to launch in the middle 2020s. The existence of this study roots back to a Round Table China-Europe meeting on Satellite Gravity Exploration, which took place in September 2013 in Beijing. There it was agreed to evaluate options for further joint activities on NGGMs, especially science studies on numerical mission simulations. This was eventually realized in the frame of the European Space Agency's \"Additional Constellation and Scientific Analysis Studies of the Next Generation Gravity Mission (ADDCON)\" study. ESA's ADDCON study team and a Chinese study team joined forces in an initiative to perform numerical studies on NGGMs based on double-pair and multi-pair constellations of GRACE/GRACE-FO-type satellites. A main prerequisite for the performance assessment and interpretation of joint numerical simulations is to ensure comparability of the results of the contributing groups. Therefore, it was decided early in the project to jointly set up common test scenarios and corresponding data sets, which shall be processed by all contributing processing centers. This paper reports on results of this inter-comparison exercise. The contributing processing centers are Technical University of Munich (TUM), Institute of Geodesy and Geophysics, Chinese Academy of Sciences (IGG-CAS), Tongji University (Tongji), Wuhan University (WHU), and Huazhong University of Science and Technology (HUST). The paper is structured as follows. Chapter 2 describes the basic idea of a numerical closed-loop NGGM simulation, and describes the main input data, which have been jointly used by all groups. Chapter 3 provides an overview of different methods applied by the study teams. Chapter 4 reports the numerical simulation results, their comparison, assessment, and inter-comparison. The final Chapter 5 contains main conclusions as well as an outlook to future work.
## 4 Semantic Interoperability Provision in Heterogeneous Healthcare Service Environments
### Semantic Interoperability in Healthcare Data Models
#### 4.2.1 Development of Ontology Models for Semantic Alignments  
To mitigate semantic heterogeneity so that cross-domain healthcare applications could be developed, semantic alignment and annotation based on the standard vocabularies are highly required. We developed three ontology models of affective human health conditions and realized their annotations, where standard National Cancer Institute (NCI) Thesaurus [43] and Systematized Nomenclature of Medicine (SNOMED) terminologies [44] have been followed (as shown in Figure 5). The developed ontology models and their alignment with the base ontology have been further discussed in Section 5.1.  
Moreover, the semantic base ontology consists of the generic concepts to support the interoperability for healthcare applications (as shown in Figure 6). It includes the base object entity, which represents Real-World Objects (RWOs). The RWO has the operation mode as it may represent any sensor or actuator; however, if the RWO represents any other information, this mode will be set to none. A Base Object Element (BOE) is an entity to hold a base object. The BOE can have input features as well as the output features. Each feature has associated metadata with which it presents the details on the BOEs and the operation that could be supported on this abstraction. The Composite Elements (CE) are the entities in the base ontology that will contain the collection of BOE entities. They also have features and associated metadata. Base Ontology model has an interface to the standard W3C SSN ontology and other external ontologies to express and provide interoperable features with existing systems.  
Figure 5: Developed ontology models of affective human health conditions.
# Golgi Metal Ion Homeostasis in Human Health and Diseases
## 4 Cu Ion (Cu\({}^{2+}\) and Cu\({}^{+}\)) Transporters
### Cu Transporter Trafficking  
One unique character of these Cu transporters is their translocation from the TGN to post-Golgi vesicular compartments and subsequently the plasma membrane to export excessive Cu out of the cell in response to a rising Cu level [147; 150]. This Cu-induced trafficking is reversible, as the Cu transporters are retrieved back to the TGN once the Cu level is reduced.  
Studies have identified some elements responsible for TGN-targeting and Cu-induced trafficking of ATP7A and B, yet detailed mechanisms underlying the trafficking of Cu transporters remain unknown. Deletion of transmembrane domains 3 and 4 results in mislocalization of ATP7A. Furthermore, a 38 amino acid sequence containing transmembrane domain 3 of ATP7A was found to be sufficient for Golgi localization [151]. Disease-related mutants of ATP7A and B are misfolded and degraded by ER-associated degradation (ERAD) [152]. Among the six N-terminal MBDs, MBD 5 or 6 is necessary and sufficient for the copper-induced redistribution, while the first 4 MBDs are not essential [153]. The di-leucine and tri-leucine motifs within the cytosolic C-terminal of ATP7A and B are required for their retrieval to the Golgi [154; 155].  
Phosphorylation is another factor that affects the trafficking of Cu transporters. Mutation of the phosphorylation sites prevents Cu-induced translocation of ATP7A, while mutations in the phosphatase domain result in hyperphosphorylation of the protein and cause constitutive dislocation from Golgi to the plasma membrane. These findings suggest that Cu-induced trafficking of the Cu-ATPases is associated with the phosphorylated intermediate conformations during catalysis [156; 157]. In addition, multiple trafficking factors, including clathrin, AP-1, AP-2, and Rab22, but not caveolin or flotillin, are required for ATP7A trafficking [158].
## 4 Numerical Analysis of Case Study  
### Numerical Model  
The finite difference software package FLAC\({}^{\text{3D}}\) (version 6.0, Itasca Consulting Group Inc., Minneapolis, MN, USA, 2017) is employed, and a hydraulic tunnel in China is chosen as the practice example to evaluate the method proposed in this study. As shown in Figure 6, altogether 32,349 grid points and 29,920 zones are meshed; the opening diameter \(D\) is 10 m. The distance from the right boundary to the tunnel center is 7 times that of \(D\), as well as the left and top boundary. Additionally, the bottom boundary is 60 m away from the tunnel center. The model length is 80 m along the tunnel axis, 8 times that of \(D\). The extent of the numerical model in this study can meet the requirement of computational accuracy [34]. The boundary conditions are shown in Figure 6b: The nodes on the all boundaries except the top boundary are fixed along the normal direction; the 300 m overlying rock is fulfilled by a distributed pressure on the top boundary. As shown in Figure 6c,d, all nodes and zones on the excavation boundary are served as monitoring objects and numbered in consecutive order, including 40 zones and 40 grid points.  
Figure 5: Flow diagram of the determination of installation time for the initial support: (**a**) detailed computational procedures, (**b**) graphical relationship between \(\overline{F}\) and \(x\).  
Based on the engineering report, the rock mass of this section is composed of granite with the parameters that density of rock mass is 2700 kg\(\cdot\)m\({}^{-3}\), and the deformation modulus and Poisson ratio is 8.5 GPa and 0.27, respectively. The friction angle of 40\({}^{\circ}\), the cohesive strength of 0.8 MPa are adopted in the Mohr-Coulomb failure criterion. The vertical in-situ stress is simulated by the rock self-weight, and the horizontal in-situ stress is calculated by lateral pressure coefficient \(K_{x}=K_{y}=0.4\).
## 4 Statistical Methodology for Federated Learning
### Privacy Leakage
In the context of FL, SMPC can be used to securely aggregate model updates without exposing individual contributions. For example, using additive secret sharing, each client \(k\) splits its update \(\Delta\mathbf{w}_{t}^{k}\) into shares and distributes them among the clients. The server only receives the aggregated result, which is the sum of all shares. Homomorphic Encryption: This allows computations to be performed on encrypted data without needing to decrypt them first. In FL, homomorphic encryption can be used to perform model aggregation securely, ensuring that the server does not see the raw updates from clients. Given an encryption function \(E\) and a decryption function \(D\), homomorphic encryption ensures that:  
\[D(E(a)\cdot E(b))=a+b \tag{5}\]  
Unfortunately, at the moment of writing, Homomorphic Encryption is orders of magnitude slower than non-homomorphic alternatives, making it unfeasible for large amounts of data.
# Q-Pandora Unboxed: Characterizing Resilience of Quantum Error Correction Codes Under Biased Noise
## 7 Limitations and Future Work  
This study offers a robust analysis of QEC codes under prevalent noise models, yet there are opportunities for further research due to some limitations. For example, we did not incorporate amplitude and phase-damping noise models, which arise from energy dissipation and dephasing--common phenomena in quantum systems. Modeling these necessitates moving beyond Pauli errors to density matrices and Kraus operator sums. The STIM simulator we employed is tailored for Pauli channels, omitting non-Pauli noise processes. While depolarizing noise offers some insight, directly incorporating amplitude and phase damping could alter our findings, especially regarding surface codes that counteract phase errors. Future work could integrate STIM with simulators supporting damping noise models, building on established quantum programming structures. Preliminary studies hint that our core findings might persist with these realistic noise models, but thorough assessments are crucial.  
Our study also sidestepped leakage and crosstalk noise models, which can move qubits beyond the computational basis or produce correlated multi-qubit errors. Understanding these complex noises is essential as quantum hardware advances. They require more intricate quantum error models, transcending the simplistic single-qubit Pauli error assumption. A potential approach could be tensor network representations that encaps  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multicolumn{2}{c}{**Parameters**} & \multicolumn{2}{c}{**Overhead**} & \multirow{2}{*}{**Improvement**} \\ \hline
**Distance** & **Rounds** & **\# Qubits** & **\# Gates** & \\ \hline
3 & 9 & 17 & 64 & \(\sim\)10 times \\
5 & 15 & 64 & 208 & \(\sim\)10\({}^{2}\) times \\
7 & 21 & 118 & 432 & \(\sim\)10\({}^{3}\) times \\
11 & 33 & 170 & 736 & \(\sim\)10\({}^{4}\) times \\
13 & 39 & 271 & 920 & \(\sim\)10\({}^{5}\) times \\
15 & 45 & 323 & 1144 & \(\sim\)10\({}^{7}\) times \\
17 & 51 & 374 & 1368 & \(\sim\)10\({}^{8}\) times \\
21 & 63 & 477 & 1592 & \(\sim\)10\({}^{9}\) times \\
23 & 69 & 528 & 1816 & \(\sim\)10\({}^{10}\) times \\
25 & 75 & 580 & 2040 & \(\sim\)10\({}^{12}\) times \\ \hline \hline \end{tabular}
\end{table}
Table 3: System improvement by surface code at a physical error rate of 10\({}^{-3}\) under a circuit-level noise model.  
sulate multi-qubit correlations. Merging such noise models with STIM might shed light on leakage and crosstalk effects. While analytical models offer a starting point, simulations that capture these errors' nuances might be indispensable. Future research avenues include exploring a broader spectrum of codes, refining decoders, investigating imperfect syndrome measurements, and delving into code concatenation.
## 3 Probabilistic Topology Control Algorithm
### PTC-Based FTC Algorithm
Therefore, according to the FTC algorithm, the process of the PTC based FTC algorithm can be expressed as follows:  
* Getting the optimal transmission power \(P^{*}\) based on an optimal transmission power allocation algorithm, such as the FTC algorithm [6];
* Calculating the deviations of each parameter, which are \(D_{P}\), \(D_{Q}\), \(D_{E}\), and \(D_{n}\);
* Calculating the transmission power adjust probabilities based on the parameter deviations calculated in Step 2 and the fuzzy logic system shown in Section 3.3; the transmission power adjustment probabilities of parameters are \(\rho_{P}\), \(\rho_{Q}\), \(\rho_{E}\), and \(\rho_{n}\);
* Finding the maximum transmission power adjustment probability of \(\left\{\rho_{P},\rho_{Q},\rho_{E},\rho_{n}\right\}\) and setting this probability as the transmission power adjustment probability of the AUV;
* Adjusting the transmission power of the AUV based on the probability calculated in Step 4 and the optimal transmission power \(P^{*}\) calculated in Step 1. The PTC-based FTC algorithm can be found in Algorithm 1. Figure 10: The fuzzy-logic topology control (FTC) scheme. ```
1. Training data set, \(T=(k,Prob,TP)\);
2. Maximum transmission power, \(P_{\max}\);
3. Reference degree of AUV, \(ND_{ref}\);
4. Initial probability, \(Prob_{0}\);
5. Initial \(K\), \(K_{0}\);
6. The maximum queue length, \(Q\);
7. The maximum residual energy, \(E\):
8. \(TP_{i}\Leftarrow P_{\max}\);
9. \(Prob\Leftarrow Prob_{0}\);
10. Broadcast HELLO message with current \(TP_{i}\);
11. For messages received from other AUVs, store the ID of its neighbor AUVs;
12. Calculate the number of neighbors \(ND\) in the neighbor list;
13. Calculate \(e_{ND}=ND-ND_{ref}\);
14. if \(e_{ND}<0\) then
15. \(K=K_{0}\);
16. else
17. \(K=\frac{K_{0}}{2}\);
18. end if
19. \(Prob\Leftarrow Prob-K\cdot e_{ND}\);
20. \(TP_{i}\Leftarrow FTC(ND_{ref},Prob)\);
21. Calculate the deviations \(D_{P_{i}}\), \(D_{Q_{i}}\), \(D_{E_{i}}\), \(D_{n_{i}}\);
22. Input the deviations into the fuzzy logic system to calculate the transmission power adjustment probability \(\rho_{P}\), \(\rho_{Q}\), \(\rho_{E}\), and \(\rho_{n}\);
23. \(\rho_{s}\Leftarrow\max\bigl{\{}\rho_{P},\rho_{Q},\rho_{E},\rho_{n}\bigr{\}}\);
24. Adjust the transmission power according to \(\rho_{s}\) (random decision based on the probability value). ```  
**Algorithm 1** PTC-based FTC algorithm  
Note that in this paper, the PTC algorithm is combined with the FTC algorithm; however, in practice, the PTC algorithm can be combined with other different topology control algorithms to improve the performance and reduce the transmission power adjustment ratio.
# OPERA the Radar Project
## 1 Introduction  
In Europe, the national weather services are responsible for weather observations in their own countries, but also co-operate under the umbrella of the European Meteorological Services Network, EUMETNET. The weather radar work within EUMETNET is co-ordinated by the Operational Program for Exchange of Weather Radar Information (OPERA; www.eumetnet.eu/opera), which was established in 1999. The development and activities of OPERA are described in [1]. OPERA has 30 members operating over 200 radars, mainly in C-band but some in X- and S-bands. The radars come from different hardware and software manufacturers, and some parts were developed in-house. The time span between the oldest and the newest radars in the network is more than 40 years. This makes OPERA, by far, the largest, most heterogeneous body of radar experts anywhere in the world.  
Since 2011, the OPERA data center (ODC; also known as \"Odyssey\") has created Pan-European radar composites every 15 min. This long time-series of data provides an insight to the development of central data processing methods, and also to the gradual improvement and harmonization of the incoming data from over 20 different national weather radar networks.  
OPERA produces three different composites with a horizontal resolution of 2 km--maximum reflectivity, rainrate, and hourly accumulation--which are updated every quarter of an hour (on the hour, and at 15, 30, and 45 min past the hour) and are issued approximately 15 min after the start ofdata acquisition. It also provides quality-controlled single-site radar data for the numerical weather prediction (NWP) consortia for assimilation.  
This paper is organized as follows. In Section 2, we describe the present network and processing methods. In Section 3, we highlight two of the greatest achievements of OPERA. In Section 4, we discuss the reasons for heterogenity of the data and plans for future development.
# Flexural Wave Propagation and Defect States of Periodic Slab Track Structure in High-Speed Railway
## 3 Bandgap Characteristics of Slab Track Structure
### Bandgaps
Within the frequency range below 1000 Hz, due to the coupling effect between the rail and the track slab, there is a minor deviation between the Bragg frequency calculated by the simplified formula (Table 3) and the dispersion curve. It can be concluded that the bandgaps in the CRTS III slab ballastless track structure are composed of Bragg reflections generated by the periodically distributed slabs and the periodically supported rails, as well as the local resonances produced by the bending resonance of the slabs. Table 4 presents the formation mechanisms of all flexural bandgaps within 1500 Hz. There are 11 Bragg bandgaps in the CRTS III slab ballastless track structure within 1500 Hz, all of which satisfy the condition that the unit cell size is integer multiples of \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \(n\) & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 \\ \hline
**Frequency (Hz)** & 16.5 & 66.0 & 148.5 & 264.0 & 412.5 & 594.0 & 808.5 & 1056.0 & 1336.5 \\ \hline \end{tabular}
\end{table} 
Table 3: Bragg frequencies. Figure 6: Wave modes at the band-edge when \(\kappa=0\) (red: rail, black: slab). the half-wavelength of the wave: \(L=n\lambda/2\). When the flexural wave has a relatively long wavelength, when \(n=1\) and \(n=2\), there are also in-phase and out-of-phase motions of the rail and the track slab, resulting in two Bragg bandgaps. It can be observed that the Bragg bandgap frequencies gradually increase from \(n=1\) to \(n=9\). For \(n=9\), the pinned-pinned resonance mode can be observed, i.e., the wavelength of the standing wave is twice the sleeper spacing. From the imaginary part of the dispersion curve, it can be known that the width of the Bragg bandgaps is narrow. The main reason is that the support stiffness under the slab is relatively high, the impedance difference of the track structure along the line is small, and the reflection of elastic waves is low. Additionally, there are also 10 local resonance bandgaps below 1500 Hz that are primarily generated by the resonances of the rail and the slab. For the first-order local resonance bandgap, it refers to the initial bandgap of the slab track structure which corresponds to the vertical in-phase resonance between the rail and the slab. For the second-order and third-order local resonance bandgaps, the bandgap range is from 125 Hz to 163 Hz and there is a track slab bending resonance mode at 152 Hz in the middle. It can be observed that these local resonance bandgaps are close to the Bragg bandgaps, and the two types of
###### Abstract  
Waste can be effectively reused through the production of carbonized refuse-derived fuel (CRDF) that enables further energy recovery. Developing cleaner production of CRDF requires consideration of practical issues of storage and handling. Thus, it needs to be ensured that CRDF does not pose an excessive risk to humans and the ecosystem. Very few studies indicate a wide variety of volatile organic compounds (VOCs) are present in CRDF, some of which are toxic. During handling, storage, transportation, and use of VOC-rich CRDF, workers and end-users could be exposed to emissions that could pose a health and safety hazard. Our recent study shows that CRDF densification via pelletization can increase the efficiency of storage and transportation. Thus, the following research question was identified: can pelletization mitigate VOCs emissions from CRDF during storage? Preliminary research aiming at the determination of the influence of CRDF pelletization on VOCs emission during storage was completed to address this question. The VOCs emissions from two types of CRDF: ground (loose, torrefied refuse-derived fuel (RDF)) and pelletized, were measured. Pelletization reduced the VOCs emissions potential during the four-day storage by -86%, in comparison with ground CRDF. Mitigation of VOCs emissions from densified CRDF is feasible, and research is warranted to understand the influence of structural modification on VOCs emission kinetics, and possibilities of scaling up this solution into the practice of cleaner storage and transportation of CRDF.  
Keywords:RDF; CRDF; biowaste; waste to carbon; municipal solid waste; torrefaction; pyrolysis; VOCs; emissions; mitigation; pelletization; solid fuels; biochar; occupational safety +
Footnote †: journal: materials