esa-sceva/satcom-chunk-collection huggingface dataset:
# Building SDN-Based Agricultural Vehicular Sensor Networks Based on Extended Open vSwitch
## 2 System Architecture
### Connection-State Processing Function
#### 2.2.2 Connection State Synchronization and Encapsulation  
The second step is that the connection state should synchronize to the user space and kernel datapath in the switch when the detected connection state changes. As shown in Figure 3, first, the connection state needs to be synchronously transmitted to the datapath by the user-kernel Netlink mechanism (see step 1 in Figure 3). When a packet arrives at a switch's ingress port, a lookup key will be extracted from the header of the packet. At the same time, the connection state should be added into the lookup key-like Import field, which can make the key match stateful rules in the datapath. Second, the connection state value detected need be synchronously transmitted to the user space for an OpenFlow table lookup in the user space (see step 2 in Figure 3). In other words, a packet sent up to the user space should remove the old connection state and add a new connection state for forming a new lookup key in user space. This synchronization and the key encapsulation mechanisms ensure that a packet always uses a real-time state to match rules.  
By the above design, the connection-state processing function can get the real-time connection state of a controller and synchronize it for packets to lookup in flow tables. Therefore, the state awareness and stateful match can be applied in many dynamically changing agricultural scenarios. For example, if the connection state between a sensor switch and controller is disconnection, packets  
Figure 2: (**a**) State transition; (**b**) tracking connection state in the situation that the link is disconnected. In ACTIVE, because the switch can’t receive any messages or even echo reply messages from the controller, it moves into IDLE. Similarly, it finally moves from IDLE to DISCONNECTION.  
can match those rules whose match fields include the disconnection state field. It can implement some services, such as self-learning function in the data plane when the controller is unavailable. Besides, if the connection state is busy, packets can be processed and forwarded into the bypass sensor node carrying a switch. If so, the bypass switch and another controller will process the packet, which achieves the load balance of controllers and improve the production efficiency in the agriculture field.
# Topological Navigation and Localization in
## 3 Topological Navigation and Localization for LHD
### Navigation  
The navigation scheme is composed of two layers of nodes that enable the path planning and autonomous hauling through the underground tunnels of the mine: the high level and the low level. The high level encompasses two modules: \"Navigation Control\" and \"Deliberative Path Planning\", while the low level is comprised of another two modules: \"Guidance\" and \"Command Executor\" (see Figure 9).
## 4 Discussion
### Influence Analysis of the Logarithmic Operation  
As described in Step 3, the initial shadow index is additionally refined with a logarithmic operation resulting in the logarithmic shadow index for further improving the capability of separating shadow against nonsm shadow. In particular, the logarithmic operation compresses the initial shadow index and expand the discrimination between pixel values of shadow and nonsmadow [24]. In this part, the impact of the logarithmic operation is analyzed by comparing the performance distinction between shadow detection results respectively by the initial shadow index and the logarithmic shadow index in several variant color spaces (i.e., HIS, HSV, CIELCh, YCbCr and YIQ) in the additional experiments with test images Tripoli-1 and Tripoli-2. Figure 8 illustrates the overall accuracies of shadow detection results by the initial shadow index and the logarithmic shadow index in the additional experiments with test images Tripoli-1 and Tripoli-2, respectively.  
As illustrated in Figure 8a,b, it can be observed that higher overall accuracies are acquired for shadow detection results in these invariant color spaces (i.e., HIS, HSV, CIELCh, YCbCr and YIQ) with the _LSI_ shadow index for both test image Tripoli-1 and test image Tripoli-2, when compared with the corresponding overall accuracies for shadow detection results with the ISI shadow index. Accordingly, relatively high overall accuracies are obtained for shadow detection results with both ISI and _LSI_ indices for test images in most invariant color spaces mentioned above, which delivers significant information that the distinction between shadow and nonsmadow is significantly expanded by the employed shadow properties against the corresponding nonsmadow (i.e., higher hue, lower intensity and dramatical decrease in _NIR_ component). Furthermore, the obvious distinction of the overall accuracy between shadow detection results with _LSI_ shadow index and the overall accuracy with ISI shadow index reveals that the applied logarithmic operation further reinforce the difference between shadow and nonsmadow for _LSI_ construction in Step 3, which contributes to a good performance of the _LSI_ shadow detection algorithm. Therefore, we finally accomplish the shadow detection of test images in various invariant color spaces based on the _LSI_ shadow index.
# A PSF-Shape-Based Beamforming Strategy for Robust 2D Motion Estimation in Ultrafast Data
## 5 Conclusions  
In this paper, a framework for robust displacement estimation in ultrafast ultrasound data was presented. It can be used as a protocolled way to beamform ultrafast data and obtain accurate estimates of the tissue displacements. The success of this new methodology is based on the following important concepts: the matching shape of the CCF peak and the interpolation function, the equal number of sample points in axial and lateral direction throughout the peak, and the use of 2D instead of 1D interpolation functions to acquire joint estimation of subsample displacements in both directions. The proposed method defines the beamforming grid based on the system's PSF to generate standardized circular-shaped CCFs which match with a 2D cubic interpolation function. The results presented in this work confirm the hypothesis; increased accuracy and precision were found for 2D motion estimation using the PSF-shape-based beamforming grid combined with 2D cubic subsample interpolation of the CCF. This was shown for a wide range of displacements or velocities present in carotid vessel wall and blood flow dynamics.  
This research is supported by the Dutch Technology Foundation STW (NKG 12122), which is part of the Netherlands Organization for Scientific Research (NWO), and which is partly funded by the Ministry of Economic Affairs. The authors want to gratefully acknowledge the support of [PERSON], MSc for his assistance in the rotating disk experiments.  
[PERSON], [PERSON], [PERSON], [PERSON] and [PERSON] conceived and designed the experiments/simulations; [PERSON] performed the simulations with support of [PERSON], [PERSON] performed the experiments; [PERSON] analyzed the data with support of [PERSON], [PERSON], [PERSON] and [PERSON]; [PERSON] is the main author of the paper; critical revisions were provided by all co-authors.  
The authors declare no conflicts of interest.
# Channel Code-Book (CCB): Semantic Image-Adaptive Transmission in Satellite-Ground Scenario
## 2 System Model  
This section introduces the network model, channel model, and proposed end-to-end semantic image adaptive transmission framework for satellite-ground communications.
# A Comparative Study for Control of Quadrotor UAVs
## 2 Materials and Methods
### System Control  
If considering the linearized model in equations from (20) to (25) in the Laplace variable domain formulation, it is straightforward that the system is unstable due to the presence of poles in the origin. Additionally, the inputs \(\mathrm{U}_{2}\), \(\mathrm{U}_{3}\) and \(\mathrm{U}_{4}\) directly affect the quadrotor's attitude, while \(\mathrm{U}_{1}\) directly affects the altitude dynamics. Figure 3 shows the proposed control system's architecture, decoupled in two parts: the inner loop performs attitude stabilization, while the outer loop is responsible for altitude control and reference attitude computation, given a 3D trajectory to be followed. Each control input signal \(\mathrm{U}_{i}\) is saturated before being given to the plant, i.e., the quadcopter. The lower and upper saturation bounds are \(\mathrm{U}_{i}^{\mathrm{LB}}\) and \(\mathrm{U}_{i}^{\mathrm{UB}}\), respectively. The propellers' capacity is assumed to be such that the absolute value of the saturated total lift force \(\mathrm{U}_{1}^{\mathrm{SAT}}\) is equal to 3 mg. Analogously, an absolute value of 1.5 mg refers to \(\mathrm{U}_{2}^{\mathrm{SAT}}\) and \(\mathrm{U}_{3}^{\mathrm{SAT}}\), while an absolute value equal to mgL refers to \(\mathrm{U}_{4}^{\mathrm{SAT}}\).  
The inner loop is intended to be sufficiently faster than the outer loop so that the UAV's attitude can be effectively stabilized. Additionally, the state variables are assumed to be perfectly known to the controllers at each sampling instant. On the other hand, it is well known that the accuracy of position estimates may not be high enough to implement position-based trajectory controllers in many real-world applications. Consequently, the outer loop is intended to ensure tracking of velocity references.  
As far as the inner loop is concerned, the choice of the best control law derives from a comparative evaluation of different linear and nonlinear controllers designed for attitude stabilization: PID, LQR, FL, SM and MPC. Both the tracking error and the controller command effort related to each controller are taken into account by means of the sum of the L\({}_{2}\) norms of state and controller command input signals. Each attitude stabilization controller is designed with simplified models but is applied to the complete nonlinear attitude system expressed by Equations (12) to (17) for the sake of the evaluation. Instead, the outer loop implements a dynamic inversion and PID-based velocity controller.
# Enhanced Antifungal Activity of Engineered Proteins via Swapping between Thiodexin H2 and H3
###### Abstract  
Thiodexins (Trxs) are proteins that act as antioxidants by facilitating the reduction of other proteins and are highly conserved in all organisms. Plant H-type Trx isoforms have different structures and perform multiple functions. Previous studies have reported that the low molecular weight AtTrx-H2 acts as a disulfide reductase and the high molecular weight AtTrx-H3 functions as an oxidoreductase and a molecular chaperone. In this study, we compared the antifungal activities of _Arabidopsis_ Trx-H2 and -H3 with engineered proteins 2N3C and 3N2C via domain-swapping between the N- and C-terminal regions of Trx-H2 and -H3. All AtTrx-H variant proteins inhibited cell growth of various pathogenic fungal strains at pH 5.2 and pH 7.2 and showed significant intracellular accumulation in the fungal cells. Interestingly, only two engineered proteins penetrated the fungal cell wall and membrane, indicating their ability to destabilize the fungal cell membrane before internalization into the cytosol. To our knowledge, this is the first study that demonstrates novel functions of plant antioxidants AtTrx-H2 and -H3 as antifungal proteins and shows their enhanced activity using the domain swapping technique.  
Keywords:Thiodexin; antifungal; swapping; _Arabidopsis thaliana_
## 4 A Look Toward Privacy in 6G Core Networks
### Sixth-Generation Identity Protections  
Sixth-Generation technology will incorporate many new technologies into the cellular ecosystem, all while inheriting methods from the 5G. User identity protections must be a major focus in shaping 6G protocols and architectures. Ref. [55] covers comprehensive topics regarding expected technologies within 6G technology, such as visible light communications, physical layer security, healthcare AI, homomorphic encryption, etc. Specific to identity protections, it states that improvements to AKA are imperative, along with improved management of subscriber identities. End-to-end encryption in 6G networks, on the user and control plane, is needed to resist eavesdropping and tracing attacks. While adding these technologies is vital, the authors do mention the technical issues and limitations that could arise due to heightened latencies, which goes against the goal of ultra-low-latency 6G networks. Various 6G use cases are also outlined in [56; 57] which show the necessity for there to be a clear definition of de-identified datasets. The lack of a standard for the architecture of these user datasets may cause privacy leaks, jeopardizing user identity protections. Federated blockchain usage is proposed in [58] as a way to manage the identities of the expected billions of connected devices. The authors present a lightweight Hardware Security Module (HSM) to store cryptographic secrets, instilling trust in devices at a fraction of the cost of traditional HSMs and enhancing security, scalability, and privacy. The presented HSMs allow for end-to-end encryption on the 6G network, and fortified security in the instance of a threat actor inside the serving network, as the HSMs exclusively control the creation and storage of the private keys. This decentralized approach to key storage elevates user identity protections and aims to ensure tamper-proof operations.
# Wind Turbine Power Curve Modelling with Logistic Functions Based on Quantile Regression
## 2 The Proposed Logistic Functions Based on Quantile Regression
### Quantile Regression  
Quantile regression (QR) provides an effective method for estimating models for conditional quantile functions [29]. Therefore, the uncertainty of wind power can be described by using the fitting curves of different conditional quantiles without imposing stringent parametric assumptions. Generally, QR can be regarded as an extension of a linear model, expressed as:  
\[P(v,\ \beta(\tau))=\beta_{0}(\tau)+\beta_{1}(\tau)v+\beta_{0}(\tau)v^{2}+\ldots+ \beta_{n}(\tau)v^{k} \tag{4}\]  
where \(P(v,\ \beta(\tau))\) is the predicted power output at \(\tau\)th conditional quantile and \(\beta(\tau)=[\beta_{0}(\tau),\ \beta_{1}(\tau),\ \ldots,\ \beta_{n}(\tau)]\) is the model parameter vector in \(\tau\)-quantile, obtained by:  
\[\hat{\beta}(\tau)=\text{argmin}\sum_{i=1}^{N}{\rho_{\tau}[y_{i}-P(v_{i},\ \beta( \tau))]} \tag{5}\]\[\rho_{\tau}(u)=\left\{\begin{array}{cc}\tau u,&u\geq 0\\ (1-\tau)u,&u<0\end{array}\right.\tau\in(0,1) \tag{6}\]  
where \(\rho_{\tau}(u)\) is the asymmetric absolute value function [29]. However, QR based methods have limitations in complex nonlinear curve fitting. Previous studies attempted to combine QR with a neural network and support vector machine to enhance its nonlinear mapping ability [35], but the fitting accuracy of the predicted CI was still unable to meet the requirements of wind farms.
## 5 Taxonomy of Technology-Enabled Smart City Applications in 6G Networks
### Holographic Communication (HC)  
HC is the next evolution of 3D videos and images that will capture data from multiple sources, providing end users with an immersive 3D experience. The global holographic display market size is projected to reach $11.65 billion by 2030 from $1.13 billion in 2020, i.e., a CAGR of 29.1% from 2021 to 2030 [97]. It requires very high data rates and an ultra-low latency. The bandwidth requirements for a human-sized hologram after data compression varies from tens of Mbps to 4.3 Tbps [98; 99]. However, a high level of compression to reduce the bandwidth requirements will lead to a high latency. To have a seamless 3D experience, holograms require a latency of sub-milliseconds [17; 100]. Consequently, there is a tradeoff between the level of compression, computation bandwidth, and latency, which needs to be optimized by the network [101]. Furthermore, the network should have high resilience in the case of HC to maintain a high QoS by assuring reliability and reducing jitter, packet loss, and latency. Considering the security requirements for HC in applications such as smart healthcare (remote surgery), the network must be secured.
# A Coordination Technique for Improving Scalability of Byzantine Fault-Tolerant Consensus
## 2 Background and Related Work
### Background: BFT-Based Consensus Algorithms  
BFT (Byzantine Fault Tolerance)-based consensus algorithms indicate a group of consensus algorithms for resolving the byzantine general problem regarding how to achieve a consensus of data in an environment where normal and malicious nodes are mixed [24]. The representative example is PBFT (Practical Byzantine Fault Tolerance) [13; 14] in the Hyperledger Fabric 0.6 (Hyperledger Fabric later changed the PBFT into Raft since version 2.0 [25]), and diverse variations of PBFT such as _Tendermint_ in Cosmos [26], _Hotstuff_ in Libra [27], and _IBFT_ in Hyperledger Besu [28] are broadly used. BFT-based consensus algorithms' characteristics are the fast finality of a transaction, which indicates that the transaction is immediately finalized once the transaction is issued by a client and validated by \(N=3f+1\) participants. However, in other consensus algorithms such as PoW and PoS, a client should wait until their transaction is contained in a new block after issuing transactions. In Bitcoin, for example, it takes 1 h to finalize transactions theoretically. In the worse case, it often takes more time when a block is forked. Despite the fast finality of BFT-based consensus algorithms, it is inevitable to decrease performance and scalability when the number of nodes is increased. This is because all participants should join the consensus process, and two over three nodes should agree with transactions by communicating with each other in four steps: _pre-prepare_, _prepare_, _commit_, and _reply_ (Figure 1). Thus, this mechanism always causes the scalability issue depending on the number of nodes [15].
## 5 Conclusions  
Aiming at the problems of traditional active-passive hybrid vibration isolation systems, such as small output force, poor bearing capacity, large power loss and inability to resist strong impacts, an active-passive hybrid vibration isolation system combining an electromagnetic active vibration isolator, rubber passive vibration isolator and magnetorheological damper was proposed.  
1. First, the overall design scheme of the hybrid vibration isolation system was introduced. Then, the electromagnetic actuator was simulated in the two-dimensional electromagnetic frequency domain to determine the basic parameters and obtain the output characteristics. Then, a three-dimensional modeling was carried out for the time-domain simulation of the electromagnetic force multifield coupling, and the power loss and heating characteristics were obtained. Finally, a dynamic stiffness test of the rubber vibration isolator was conducted.
2. In the process of adaptive control, when the system is strongly disturbed by the external environment, this will lead to a sharp increase in error signals and a dramatic change in the control coefficient, which will cause the output signal to exceed the effective working range of the actuator. Therefore, the output signal of the controller should be constrained, and the amplitude should be limited to within the saturation region of the actuator. In this paper, a suppression factor was introduced on the basis of the FXLMS algorithm to adjust the update of the control weight coefficient.
3. The active-passive vibration isolation experimental platform based on the hybrid vibration isolation system was built, and a multifrequency line spectrum active and passive vibration isolation experiment was carried out. The results show that the hybrid vibration isolation system achieved a good control effect in the time-frequency domain. In the time domain, the passive vibration isolation effect was reduced by 25%, and the active and passive vibration isolation effect was reduced by 80%. In the frequency domain, the 37 Hz, 60 Hz and 110 Hz line spectra were attenuated by 38.86 dB, 26.16 dB and 35.16 dB, respectively. Excellent robustness was demonstrated when impacts were applied.  
This paper provides a good hybrid isolation system for the realization of active and passive vibration isolation with large excitation force and large load.  
Conceptualization and methodology, Q.Z. and L.Z.; computer simulation, Q.Z. and J.S.; software and validation, Q.D., J.W. and X.Y.; experimental work, Q.Z., M.S. and X.Y.; writing--original draft preparation, Q.Z. and Q.D.; writing--review and editing, L.Z., M.S. and J.W.; supervision, J.S. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the National Natural Science Foundation of China (grant no. 51679245) and project no. H3202203008 of the Naval Aviation University Independent Project Foundation.  
Not applicable.  
All data included in this study are available upon request from the author [PERSON].  
The authors declare no conflict of interest.
## 2 Related Work
### Wake-Up Radio  
In remote wake-up control [5], a WuRx, which consumes much less power than a sensor node, is used to control the wake-up timing of a sensor node. This helps reduce each sensor node's active time and energy consumption as well. The wake-up control message is called a wake-up call (WuC). A WuC contains the address of the sensor node to be activated. When a WuRx receives a WuC indicating a communication request, it checks the address in the WuC by comparing it with the sensor node's own address, and if matched, activates the sensor node to communicate. The study in [10] shows that using WuR is more energy efficient than duty-cycling MAC protocols (e.g., X-MAC [8] and RI-MAC [11]) and ensures a real-time response as well.
# Distributed Orbit Determination for Global Navigation Satellite System with Inter-Satellite Link
## 3 Fundamental Equations for Measurement and Motion
### Equations for Measurement
\right]_{\mathbf{X}^{i*}} \tag{9}\]  
\[\mathbf{H}^{i}=\left.\frac{\rho^{ij}(t)}{\partial\mathbf{X}^{j}}\right|_{\mathbf{X}^{j*}} =-\mathbf{H}^{i} \tag{10}\]  
Similarly, GAS can be considered as a pseudo-satellite. The PR needs to be corrected by an extra tropospheric delay compared to a normal satellite. The distance measurement equation that contains orbit parameters between the \(g\)th GAS and \(ith\) satellite is derived as:  
\[\rho^{ig}(t)=\left[\rho^{g\to i}(t)+\rho^{i\to g}(t)\right]/2=d(\mathbf{X}^{i}(t), \mathbf{X}^{g}(t))+\varepsilon^{ig}(t) \tag{11}\]  
In the Equation (11), the array of state parameters of GAS \(\mathbf{X}^{g}(t)\) is known; only the state vector of the \(ith\) satellite is unknown. The reference ground coordinate is hence introduced into the satellite state by Equation (11), which overcomes the lack of the datum mark in data processing while only ISL measurements are utilized. The current linearized measurement equation, which is similar to Equation (8), becomes:  
\[z^{ig}(t)=\mathbf{H}^{i}\delta\mathbf{x}^{i}(t)+\varepsilon^{ig}(t) \tag{12}\]