esa-sceva/satcom-chunk-collection huggingface dataset:
# How to Make Sense of Team Sport Data:
## 4 Research Aspects
### Research Challenges
In the analysis of collective behavior, researchers are interested in detecting the way animals achieve consensus in stable groups with stratified social relationships [71]. When analyzing collective behavior biologists want to determine factors directing the movement of, for example, birds flocks or fish shoals. In both cases the group formation decreases the risk of predation and thus increases the fitness of a single individual. Consequently, the required analysis possibilities overlap and allow the transfer of developed techniques from one domain to the other helping to solve challenges. Context-aware analysis is another important aspect when exploring team sport data. Analysts might have identified interesting patterns and want to explore them in-depth enriched with context information. Movement is more than just \(x\)- and \(y\)-coordinates: entities are motivated to \begin{table}
\begin{tabular}{c c c} \hline \hline
**Statistic** & **Brazil** & **Germany** \\ \hline Goals & 1 & 7 \\ Possession & 52\% & 48\% \\ Shots & 18 & 14 \\ Duel Quota & 51\% & 49\% \\ Packing & 341 & 402 \\ IMPECT & 53 & 84 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistics of a real-world game: Brazil vs. Germany (2014 FIFA World Cup). move by intrinsic and extrinsic contextual factors. Context-aware analysis means that insights into group dynamic behavior are enabled by incorporating collective movement models in the analysis process. We thereby even incorporate research from the field of collective animal movement [72; 73; 74; 75; 76; 77]. Finally, experts want to explain why, when and how specific movement behavior is expressed because of tactical behavior. Tactical behavior, in our understanding, represents the overall effort practiced on the field to eliminate the factor of luck as much as possible. Analysts want to retrieve explanations of observed cooperative movement patterns in reaction to competitive movement patterns by enhanced visualizations. Another open issue is tracking external influences as coach advices and the corresponding team reactions. The challenges arising with team sport data are not only concerning the analysis of movement itself. Technical challenges as efficient data storage, querying, and processing arise as well. Improved tracking techniques and devices led to an increase in data volume gathered from team sports as well for wildlife observations in behavioral biology. Large datasets and in some cases vast amount of individuals tracked require new and efficient handling methods. The need for novel streaming technologies that allow real time analysis enabling analysts and coaches to gain information even, for example, during the halftime break is increasing. Consequently, creating a encompassing view of team sport data, integrating trajectories, time series, similarity search, high dimensional data, text, and video image processing/analysis will be the major challenge promising large synergy effects and real insights.
## 3 Outage Rate Analysis
### Outage Probability versus Transmit Power \(P_{t}\)  
Figure 3 shows the outage simulation results with increasing transmit power \(P_{T}\) for 20 dB to 60 dB for the SNR threshold \(\gamma_{th}=10^{-3}\). Also, we set \(l=30\) m, \(\Delta_{t}=15\) m, \(n=4\), and \(\sigma=8\) dB. In the figure, the black solid line represents the outage probability of the non-cooperative (SISO) transmission, \(p_{out}^{nt}\) in (14). Also, the blue solid and red dotted lines correspond to MRC and SC (i.e., \(P_{out}^{mrc}\) and \(P_{out}^{sc}\) in (17) and (20)), respectively. The triangle and circle markers indicate the results with independent (\(\rho=0\)) and same shadowing channels (\(\rho=1\)), respectively. Lastly, the square-markers represents the simulation results with \(0<\rho<1\).  
First, the theoretical curves show excellent correlation with the simulated curves, which verifies our analysis in Section 3. Also, as expected, when the correlation \(\rho\) of the log-normal shadowing increases, the outage performance becomes worse. For example, at \(P_{out}=10^{-3}\), the gap between \(\rho=0\) and \(\rho=1\) is about 7 dB, while the results with \(0<\rho<1\), indicated by the curves with the squares, exist in between the curves with the circles and triangles. However, all of the cooperative schemes (even with \(\rho=1\)) perform significantly better compared to the non-cooperative transmission, because the cooperative transmission can benefit from the micro-diversity gain regardless of \(\rho\) that determines the degree of the macro-diversity. Indicated by the slopes in the high SNR regime, the performance gap between the cooperative and non-cooperative algorithms would be larger, as the transmit power \(P_{T}\) increases. In addition, when comparing the two combining techniques, for the same \(\rho\), MRC outperforms SC, because \(\gamma_{mrc}\geq\gamma_{sc}\) always holds [2].
## 2 Theoretical Analysis of CBIS
### Basic Concept of the CBIS
#### 2.1.1 The Inerter System  
The inerter system used in the CBIS described herein is the TVMD, which is first applied in practice [39]. The damping enhancement effect and mass amplification effect of the TVMD have already been verified by researchers [5; 15; 16; 19]. Figure 1 shows the mechanical schematic of the inerter and the TVMD. The resisting force \(F_{\text{in}}\) of the inerter is proportional to the acceleration difference between its two ends:  
\[F_{\text{in}}=m_{\text{in}}\big{(}\ddot{u}_{2}-\ddot{u}_{1}\big{)}=m_{\text{ in}}\ddot{u}_{\text{d}} \tag{1}\]  
where \(u_{1}\) and \(u_{2}\) are the displacement of the inerter two ends, respectively. The resisting force and acceleration difference ratio \(m_{\text{in}}\) is the apparent mass [19], having the same unit of the real mass. With the help of different mechanisms, the inerter can achieve an apparent mass much larger than its real mass. The authors of [39] demonstrated an inerter with a ball screw mechanism applied in practice, achieving an apparent mass of 5400 tons with an actual mass of 560 kg.  
Assuming the damping coefficient and tuning spring stiffness of the TVMD are \(c_{\text{in}}\) and \(k_{\text{in}}\), respectively, the resisting force \(F_{\text{is}}\) of the TVMD can be expressed as:  
\[F_{\text{is}}=k_{\text{in}}(u_{\text{is}}-u_{\text{d}})=m_{\text{in}}\ddot{u}_{ \text{d}}+c_{\text{in}}\dot{u}_{\text{d}} \tag{2}\]  
where \(u_{\text{is}}\) and \(u_{\text{d}}\) are the displacement differences at two ends of the TVMD and the inerter, respectively.
# Resource Mapping Allocation Scheme in 6G Satellite Twin Network
## 1 Introduction
Although this method can reduce the transmission time, it is difficult to distinguish the resource for different functions such as computing, interaction, and storage. The multi-objective dynamic on-demand allocation approach can provide a shared resource pool for multiple services simultaneously. Although this method can balance multiple optimization objectives, the multi-objective optimization method only finds the approximate optimal solution. This equilibrium comes at the cost of increased energy consumption. The artificial intelligence allocation method can select the bias of the resource allocation strategy by setting factors to complete the optimization search for the multi-objective problem. However, the multi-level, jointly nested, and diverse computing resources of the communication-twin-computing integration network need to achieve globally optimal cross-system scheduling. Existing artificial intelligence algorithms can only learn and evolve in existing systems. It is difficult to realize the optimization of other systems through its learning. In order to simulate a 6G satellite twin network, the main contributions of this paper are as follows. 1. For the first time, the integrated relationships among the communication system, the twin system, and the computing system are theoretically analyzed and modeled. For the factor association analysis problem across systems, across dimensions, and across topologies, a hypergraph hierarchical nested kriging model that enables heterogeneous topological connection is introduced for the first time. A hierarchical unified feature description method is realized. 2. In the communication-twin-computing integration network model, the basis function matrix of the local flexible connection of the global network is established. The connection optimization of huge heterogeneous systems is realized, which provides a supportive way to realize the cross-dimensional collaboration of heterogeneous systems. 3. For the first time, a theoretical analysis method that can achieve joint objective optimization of complex heterogeneous systems is proposed. The common requirements of computing, storage, and interaction are also considered to achieve a multi-objective coordinate between function utilization, load balancing, and cost for heterogeneous systems. A cross-platform network simulation architecture with function isolation is proposed for the first time and the effectiveness of the algorithm is verified through experiments. The rest of this paper is organized as follows. The related work is described in Section 2. The hypergraph hierarchical nested kriging model and the flexible coefficient autoregressive based on the basis function matrix model are given in Section 3. Section 4 analyzes a multi-constraint multi-objective genetic resource allocation optimization scheme. A large-scale network simulation architecture according to the functions is presented in Section 5. The simulation results are illustrated in Section 6. Finally, Section 7 concludes the paper.
## 3 System Design
### Transmission Mechanism
#### 3.2.3 Security Mechanisms and Reliability Assurance at the Protocol Layer  
For security, SRT supports end-to-end security mechanisms via AES-128/256 encryption algorithms. Key exchange is handled using a preshared key (PSK) mode, which ensures the confidentiality and integrity of data transmission [58]. The cryptographic handshake employs a four-way handshake protocol. This involves the Caller sending an INDUCTION request with encryption capability negotiation information, followed by the Listener responding to the INDUCTION, confirming encryption parameters and session ID. Subsequently, the Caller sends a CONCLUSION request containing the PSK-derived session key, and finally, the Listener responds to the CONCLUSION, establishing the encrypted channel. To adapt to complex security environments involving multiple venues and public networks, our system independently negotiates encryption keys for each link. This design ensures that even if one node is compromised, the security of the entire link remains unaffected.
# Timing and Frequency Synchronization Using CAZAC Sequences for OFDM Systems
## 2 Related Works
[33] presented the challenges/problems for supporting multipath transmission with possible solutions and then reviewed recent research efforts related to the concurrent multipath transmission protocol and the multipath transmission control protocol. In the same year, [PERSON] et al. [34] considered a finite-time velocity-free rendezvous control method for multiple autonomous underwater vehicle systems with intermittent undirected communication. In the same year, [PERSON] et al. [35] proposed a waveform in which the orthogonal basis functions were constructed from cyclically shifted versions of the zero autocorrelation (ZAC) sequences. They deduced the relevant properties and found that this waveform was also suitable as a synchronization signal, since the modulation symbols could be chosen to obtain the ideal periodic autocorrelation function (PACF) and low PMEPR. Based on the above literature search, we found that the previous synchronization algorithms usually detect only one correlation peak. This can easily cause false synchronization and large timing errors in a low SNR. In this paper, the proposed synchronization algorithms require the detection of multiple correlation peaks, and the distance between adjacent correlation peaks should be equal. These are the main improvements of the proposed algorithms over previous ones.
# An Update on Polyphosphate In Vivo Activities
## 7 Extracellular PolyP
The findings with polyP/FXII also suggest that pharmacologic interference with polyP offers the unique opportunity for blocking thrombosis and inflammation (thrombo-inflammation) without affecting physiologic haemostasis at vascular injury sites (safe anticoagulants) [90; 117]. The concept of interference with polyP-triggered coagulation seems to have arisen in blood-sucking insects. Sand flies express proteins in their saliva that allow feeding mammalian blood without triggering brady-kinin-mediated itching and FXIIa-mediated clotting. These proteins, PdSP15a and PdSP15b expose a positively charged helix that binds to the polymer and neutralises polyP procoagulant and proinflammatory activities [118]. The blood circulating histidine-rich glycoprotein (HRG) binds to polyanions such as DNA, RNA, and polyP. HRG has been shown to inhibit polyP procoagulant activity by interfering with FXII contact activation [119]. The underlying mechanism for antagonising FXII activity is a competition between HRG and FXII for binding to polyP. Reduced FXII binding to polyP results in defective FXII contact activation and aPTT prolongation [120; 121]. PolyP injection in HRG-deficient (\(Hrg^{-/-}\)) mice consistently triggers excess fibrin formation [122; 123]. Vice versa, the reconstitution of \(Hrg^{-/-}\) mice with HRG restores excess polyP-driven thrombosis in an FXII-dependent manner [119]. The data are consistent with HRG operating as an endogenous FXII regulator by binding to the contact activator polyP. In addition to procoagulant platelets and activated mast cells, polyP is released from mammalian astrocytes and has a role in neurotransmission. Astrocyte-polyP activates neurons and provokes calcium-mediated signalling [124]. PolyP is increased in human and mouse astrocytes and cerebrospinal fluid amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Targeting secreted polyP in ALS/FTD astrocytes prevents motoneuron death, indicating that polyP released by ALS/FTD astrocytes is a critical factor in neurodegeneration and a potential therapeutic target for interference with the diseases [125]. Intracellular polyP also has chaperone activities in the central nervous system and restores incorrect protein folding, suggesting a role of polyP in amyloidogenic processes and disease states [126; 127]. Indeed, polyP improves degenerative neuronal diseases where misfolded protein aggregates seem to mediate the pathology, such as [PERSON]'s, [PERSON]'s, and [PERSON]'s disease [18; 128]. Together, the data highlight the importance of polyP in the central nervous system, which is awaiting future studies.
## 2 Materials
### System Setup  
This study employed a laser scanning system developed in-house by the authors' organization, with the overall hardware configuration illustrated in Figure 2. The entire system is orchestrated by a Siemens control box, which regulates the servo motors driving the carrier table. Integrated sensors emit pulses at predetermined intervals, signaling the scanner's controller to initiate data acquisition. The detailed parameters of the laser scanner are provided in Table 1. To align with the precision requirements of the scanner, the carrier table was designed with a minimum step resolution of 1 \(\upmu\)m and an adjustable range.  
The coordinate system for the point cloud data was defined by the laser scanner. The origin corresponded to the first point captured during the data acquisition process. The x-axis aligned with the laser line emitted by the scanner, the y-axis represented the direction of the carrier table's linear movement, and the z-axis corresponded to the surface height of the object being measured. The resulting output was a file containing only the  
Figure 1: Different types of magnetic tiles and their distribution within the motor.  
Figure 2: The hardware setup of the laser scanning system.  
z-axis data and the corresponding luminance information. Luminance is, in fact, a form of radiative information, which is related to the power of the reflected laser beam. Hence, it is often referred to as \"intensity\" [68]. The equation for the reflected laser beam intensity is as follows:  
\[P_{r}=\frac{\pi P_{r}p}{4\mathcal{R}^{2}}\eta_{a}\eta_{s}\cos(\theta) \tag{1}\]  
where \(P_{r}\) represents the received signal power, with larger values corresponding to higher reflected intensity; \(P_{l}\) denotes the transmitted signal power; \(\rho\) indicates the reflectance of the target, which reflects the surface characteristics such as color and roughness; \(\mathcal{R}\) stands for the distance between the laser profilometer and the target; \(\eta_{a}\) represents the atmospheric transmission factor; \(\eta_{s}\) signifies the system transmission factor; and \(\theta\) denotes the incident angle.
###### Abstract  
In microgrids, paralleled converters can increase the system capacity and conversion efficiency but also generate zero-sequence circulating current, which will distort the AC-side current and increase power losses. Studies have shown that, for two paralleled three-phase voltage-source pulse width modulation (PWM) converters with common DC bus controlled by space vector PWM, the zero-sequence circulating current is mainly related to the difference of the zero-sequence duty ratio between the converters. Therefore, based on the traditional control ideal of zero-vector action time adjustment, this paper proposes a zero-sequence circulating current suppression strategy using proportional-integral quasi-resonant control and feedforward compensation control. Firstly, the dual-loop decoupled control was utilized in a single converter. Then, in order to reduce the amplitude and main harmonic components of the circulating current, a zero-vector duty ratio adjusting factor was initially generated by a proportional-integral quasi-resonant controller. Finally, to eliminate the difference of zero-sequence duty ratio between the converters, the adjusting factor was corrected by a feedforward compensation link. The simulation mode of Matlab/Simulink was constructed for the paralleled converters based on the proposed control strategy. The results verify that this strategy can effectively suppress the zero-sequence circulating current and improve power quality.  
three-phase voltage-source PWM converter; paralleled converters; zero-sequence circulating current (ZSCC) suppression; zero-vector duty ratio; proportional-integral quasi-resonant (PIQR) control; feedforward compensation Article
# A Novel Routing Scheme for Creating Opportunistic Context-Virtual Networks in IoT Scenarios +
## 5 SACAR Algorithm Description
### Complexity Analysis  
In this subsection, a complexity analysis for the proposed SACAR algorithms is provided. Since the main idea behind each version of the algorithm is the same, i.e., every time the parameter \(\omega_{t}\) is triggered, each node in the scenario gets the list of neighbors and performs specific tasks with them, we deeply analyze the SACAR-IR approach with the focus that the same explanation can be adopted for the rest of the algorithms.  
Let us then refer to Algorithm 3. Each node in the scenario \(d_{i}^{x;y_{i}}\in\mathcal{D}\) (Line 2) must obtain the list of neighbors (Line 6) and perform a set of tasks for each neighbor every time the parameter \(\omega_{t}\) is triggered. Since such tasks take at most \(\mathcal{O}(\log n)\), e.g., for searching in a list of previous connections (Line 8), the full process of managing the set of neighbors \(\mathcal{N}_{i}\) of a particular node \(d_{i}^{x;y_{i}}\) takes \(\mathcal{O}(|\mathcal{N}_{i}|\cdot\log n)\), being \(\mathcal{O}((|\mathcal{D}|-1)\cdot\log n)\) in the worst-case scenario. Furthermore, if we repeat the process for each node in the network, the resulting complexity of SACAR-IR is \(\mathcal{O}(|\mathcal{D}|\cdot(|\mathcal{D}|-1)\cdot\log n)\) every time \(\omega_{t}\) is triggered. Eventually, the complexity of SACAR-OCVN, SACAR-HC, and SACAR-Hybrid is the same as the one for SACAR-IR since the difference among them (see the pseudocode of Algorithms 4-6) is the set of functions to be executed between neighbors, taking all of them \(\mathcal{O}(\log n)\) at most.  
Once SACAR algorithms have been described and their complexity has been analyzed, an estimation of resource consumption on the nodes that apply SACAR algorithms is performed in the next section.
## 4 Architecture
### Technologies
#### 4.2.2 Encryption  
Elliptic Curve Cryptography (ECC) is a key-based technique for encrypting data, which has been widely used due to its security level and reduced key sizes when compared to other algorithms (e.g., Rivest, Shamir, and Adleman--RSA), see [44] for an overview. We applied ECC to generate the cryptographic keys, with a pair of public and private keys generated for each system's user; the public key is used for encryption/decryption of a legal order. Any governmental agency wishing to monitor a user must also have a pair of public/private keys and use the public key to identify a governmental representative's access to the license plate database.
## 2 Data and Methods
### Study Area and Data
#### 2.1.2 Global Geopotential Models  
In order to facilitate the estimation of errors of the geoid, this study introduces multi-generation, GOCE-derived GGMs solved by the direct and time-wise approaches: the  
Figure 1: The study area is identified by a red dotted rectangle, and the solid red line represents the Kuroshio current. The Kuroshio passes through the Luzon Strait, and the majority flows northward along the east coast of Taiwan into the East China Sea. Then it flows out of the East China Sea from the Tukara Strait, and finally flows eastward offshore near 35\({}^{\circ}\) N, becoming the Kuroshio extension.  
GO_CONS_GCF_2_DIR_R4 (DIRR4), GO_CONS_GCF_2_DIR R5 (DIRR5), and GO_CONS_GCF_2_DIR_R6 (DIRR6); and the GO_CONS_GCF_2_TIM_R4 (TIMR4), GO_CONS_GCF_2_TIM_R5 (TIMR5), and GO_CONS_GCF_2_TIM_R6 (TIMR6) [9,19]. Table 1 summarizes detailed information about these GOCE-derived GGMs. Figure 2 shows the error-degree variance in geoid height calculated by different GOCE-derived GGMs. It shows that the period of the assimilated data was extended with the development of the generation, and the supplement of data improved the modeling accuracy. The accuracy of the direct solution model was higher than that of the time domain solution model. With the update of the GOCE gravity data and the update of the solution method, the error of the time domain solution model showed a significant downward trend, while in the direct solution model, the accuracy of DIRR5 was higher than that of DIRR4, but the accuracy of DIRR6 was higher than DIRR5 before order 170, and lower than DIRR5 when the order was greater than 170. This may be due to the parameters set in the solution of these two models. While different from the data used, this result did not mean that the accuracy of DIRR6 was lower than DIRR5. Regarding the error of the GOCE satellite gravity field model, ESA has issued a related report that used externally measured GPS/leveling data to evaluate the accuracy of the multigeneration gravity field model. The results showed that the accuracy of the DIRR6 was better than that of the DIRR5 [20].