esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Sample Preparation  
For the free analyte.  
After thawed at room temperature, serum samples were centrifuged at 8000\(\times\)g for 20 min at 4 \({}^{\circ}\)C. \({}^{13}\)C\({}_{18}\)-ZEN was added to 100 \(\upmu\)L supernatant as internal standards with final concentration of 25 \(\upmu\)g mL\({}^{-1}\), followed by a dilution with 100 \(\upmu\)L of phosphate buffer (pH 6.8, 0.075 mol L\({}^{-1}\)). Under appropriate vacuum conditions, Oasis@PRiME HLB \(\upmu\)Elution plate was pretreated by methanol and water (500 \(\upmu\)L of each) for conditioning and then loaded with the diluted samples which was allowed to slowly flow through the cartridge at a rate about 0.5 mL min\({}^{-1}\). Subsequently, the wells were washed with 500 \(\upmu\)L of water and then 500 \(\upmu\)L of methanol/water (1/1, _v/v_) to remove interferences. Finally, the analytes absorbed to the cartridge were eluted twice with 50 \(\upmu\)L of methanol each and collected. After a 1:1 dilution with water, the solution was injected for UPLC-MS/MS analysis.  
For the total (free + conjugate) analyte.  
After being thawed, centrifuged and spiked with internal standards, 500 \(\upmu\)L of the serum sample was mixed with 500 \(\upmu\)L enzyme solution containing 500 units of \(\beta\)-glucuronidase and shaken in a water-bath at 37 \({}^{\circ}\)C over night. Then the resulted solution was centrifuged (8000\(\times\)g; 20 min; 4 \({}^{\circ}\)C); and 200 \(\upmu\)L of the supernatant was loaded onto the preconditioned (as mentioned above) PRiME HLB \(\upmu\)Elution plate. The following steps were exactly the same as described above.
# Estimating Critical Latency Affecting Ship's Collision in Re-Mote Maneuvering of Autonomous Ships
## 3 Methodology
### Method of Estimating Critical Latency
#### 3.1.2 Error Evaluation of Estimated Critical Latency  
The error of estimated critical latency was evaluated using the relative distance OS-TS at Point M. This evaluation method is based on the fact that the relative distance between Point M location (\(x_{\text{OM}}\), \(y_{\text{OM}}\)) of OS and Point M location (\(x_{\text{TM}}\), \(y_{\text{TM}}\)) of TS becomes zero in an ideal case at Point M. The error can be calculated as follows:  
\[\epsilon=\sqrt{(x_{\text{TM}}-x_{\text{OM}})^{2}+(y_{\text{TM}}-y_{\text{OM}}) ^{2}}. \tag{9}\]
## 3 Methodology
### Contextual Hypergraph Construction
#### 3.1.3 Types of Hyperedges  
To capture the rich contextual information within the document, we construct three types of hyperedges:  
* **Semantic hyperedges**: They connect nodes that share significant semantic similarities. The semantic similarity between two sentences \(s_{i}\) and \(s_{j}\) is quantified by using the cosine similarity of their embeddings: \[\text{sim}(v_{i},v_{j})=\frac{v_{i}\cdot v_{j}}{\|v_{i}\|\|v_{j}\|}\] (2) A semantic hyperedge \(e_{k}\) includes all sentence pairs \((v_{i},v_{j})\) whose similarity exceeds a predefined threshold \(\theta_{s}\).
* **Narrative hyperedges**: They link consecutive sentences to maintain the narrative flow. Each narrative hyperedge connects sentences that are adjacent in the text: \[e_{l}=\{v_{i},v_{i+1}\},\quad i=1,2,\dots,n-1\] (3)
* **Discourse hyperedges**: They are formed based on the discourse role of sentences within the document structure (e.g., argumentative structure and exposition). Sentences fulfilling similar roles are grouped under the same hyperedge: \[e_{m}=\{v_{i}|\text{role}(v_{i})=R\},\quad R\in\text{Roles}\] (4) where \(\text{role}(v_{i})\) identifies the discourse role of sentence \(v_{i}\).
# Shape Optimization of Discontinuous Armature Arrangement PMLSM for Reduction of Thrust Ripple
## 5 Conclusions  
Shape optimization of the armature core was performed to reduce the detent force and back EMF harmonic components that act as thrust ripple in a PMLSM system with a discontinuous armature arrangement, degrading the operating performance of the system and preventing tooth saturation. Additionally, auxiliary teeth in a trapezoidal shape were installed to reduce the detent force generated at the ends of the armature, and an optimal shape was determined for minimizing the detent force. First, seven dimensions for the shape of the armature core were set as design parameters, and the boundary was determined. Next, five major shape parameters were derived using the fractional factorial design method. The derived main shape parameters were optimized through the multi-objective optimization based on the RSM. Through the optimization, the detent force and THD of the back EMF were decreased. The maximum value of the magnetic flux density generated by the armature core was 1.18 T, which was within the appropriate range. Subsequently, auxiliary teeth were installed to reduce the detent force generated at the end edge, and the shape was optimized. The BBD method was used to derive two shape parameters affecting the detent force among the three shape parameters; additionally, a response surface was constructed. When the optimized auxiliary teeth were installed, the end edge detent force was reduced by approximately 30% compared with the case without the auxiliary teeth. Based on the results obtained in this study, it is expected that the operation performance can be improved in the discontinuous armature arrangement PMLSM.  
[PERSON], [PERSON] and [PERSON] conceived and designed the simulations; [PERSON] performed the simulations and experiments; [PERSON] and [PERSON] analyzed the data; [PERSON], [PERSON] and [PERSON] contributed analysis tools; [PERSON], [PERSON] and [PERSON] wrote the paper. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Human Resource Training Program (S2755803) for business-related research and development of Ministry of SMEs and Startups in 2019.  
Not applicable.  
The authors declare no conflict of interest.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **Initial Value** & \multicolumn{2}{c}{**Optimized**} & \multirow{2}{*}{**FEA Result**} & \multirow{2}{*}{**Error (\%)**} \\  & & & **Estimate Result** & \\ \hline Slot Effect (N) & 0.96 & 0.74 & 0.62 & 19.4\% \\ End Effect (N) & 9.33 & 6.23 & 6.49 & 4.0\% \\ BackEMF THD & & & & \\ (\%) & 2.03 & 1.16 & 1.46 & 0.3\% \\ Magnetic Flux & & & & \\ Density (T) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 11: Optimized results.
## 5 System Implementation and Field Testing
### Testing Results  
We conducted numerous experiments to test the major functions of the proposed TPTS system. Figure 5 shows the testing field of this study. The testing field is located around Minghsin University of Science and Technology. Suppose that seven attractions (denoted as red dots) and one tourist are located in the testing field. The coordinates of the attractions were previously acquired by GPS positioning. We selected three of them for testing and defined the condition of attraction, including thenumber of sessions in one attraction, capacity of tourists, duration time in one session, and the number of visitors in the attraction. The location-based dynamic map was produced via the Google Maps API.
## 4 Traffic Filtering-Based Techniques
### Port Locking (PL)  
#### 4.3.1 PL Concepts  
PL [11; 13; 14] reduces redundant unicast traffic in HSR connected-ring networks by filtering traffic for unused DANH rings. The PL approach makes the network learn gradually the location of the destination node without the network control messages. It then prunes DANH rings that do not contain the destination node by locking corresponding rings' entrance ports.  
PL is only applied to QuadBoxes that connect to DANH rings. QuadBoxes that do not connect to any one of the DANH rings work as standard QuadBoxes. PL divides a QuadBox that connects to a DANH ring into two sides. One side, called DANH site, is connected to a DANH ring and the other side, called QuadBox side, is connected to a QuadBox ring. The DANH side of the QuadBox uses the PL approach while the QuadBox side continues working as a standard QuadBox. The reason behind dividing the QuadBox into two sides is to apply the PL approach to the DANH side only to prevent the QuadBox side from being locked. The destination node usually does not exist in the QuadBox ring. Therefore, frames sent from a QuadBox to any DANH ring without the destination node will be returned back the same QuadBox. If the PL approach is applied to the QuadBox side, then the QuadBox ring will be locked and the connection will be terminated.  
When a source node sends frames to a destination node under the standard HSR protocol, each frame is tagged with an HSR tag, duplicated and circulated inside rings of the HSR network. If the destination node exists in a ring, it will take the frame without forwarding. If not, nodes in the network will forward the frame. When a QuadBox forwards a frame inside a DANH ring using one port and the frame is returned back to the QuadBox through the other port, it means that the destination of the frame does not exist in that ring. The PL will lock these ports to prevent them from sending the frames into the DANH ring.
# Systematic Analysis of the Hydrogen Value Chain from Production to Utilization
## 2 Hydrogen Production Technologies
### Electrolysis
#### 2.3.3 Solid Oxide Water Electrolysis  
SOEL development began in the 1970s in the USA. This electrolysis technology operates with steam at temperatures between 500 \({}^{\circ}\)C and 850 \({}^{\circ}\)C. By working with higher temperatures, the required energy to decompose water into hydrogen and oxygen is drastically reduced. This energy reduction increases the energy efficiency of the process [43], which in turn decreases the hydrogen production cost since energy consumption is pointed out as one of the main factors responsible for hydrogen production cost through electrolysis.  
In SOEL, water is reduced at the cathode electrode, generating hydrogen and oxygen ions, which are further reduced at the anode electrode to generate oxygen, as in Figure 10. The SOEL cell is composed of two porous electrodes and a ceramic electrolyte. The cathode is typically produced from a ceramic and metal material, such as yttria-stabilized zirconia and nickel, while the anode is produced using perovskite materials, such as a mixed metal oxide composed of lanthanum, strontium, cobalt, and iron (LSCF) or a mixed metal oxide composed of lanthanum, strontium, and manganese (LSM). The most frequently used ceramic electrolyte is yttria-stabilized zirconia [44].  
Figure 10: Schematic representations of the working principle of solid oxide water electrolysis (adapted from [44]).  
When compared with other electrolysis technologies, SOEL presents a higher energy efficiency, high conversion efficiencies and lower hydrogen production costs [43]. This technology is most attractive when high-temperature heat sources are available, such as nuclear energy [44]. Currently, despite these advantages, it presents low long-term stability, with a stable operation lifetime of only 20,000 h, and is still not commercially available at a large production scale [43]. The research currently focuses on further developing this technology to achieve the same commercialization stage as other electrolysis technologies, increasing the technology's longer-term stability, and reducing the hydrogen production cost [44]. The opportunities and challenges faced by SOEL to reach a fully commercial state are further detailed in [48].
## 2 Materials and Methods
### Measurement Device  
In this paper, an optical displacement digital micrometer sensor (Model: Keyence LS-9000) was used to measure the radial vibration of the winding rotor, which accurately obtains the vibration displacement amplitude of the object based on the principle of laser beam shielding. In addition, LMS SCADAS Mobile was used for data acquisition. These two instruments' parameters are listed in Table 1.  
The scheme of vibration measurement is shown in Figure 10a, and the corresponding measuring device is shown in Figure 10b. To reduce the impact of ground vibration on the tests, four air mounts were installed on the four corners of the device in contact with the ground.  
The Keyence digital micrometer is mounted on the slider of the frame with 3D-coordinate feed movement, and the position of the micrometer can be adjusted according to the position of the winding rotor through the PC2 (controller software of movement). The micrometer is powered and controlled by the controller, and its parameters can be set by the PC2 (LS-Navigator). The vibration signals of the winding rotor are received by the micrometer. Data acquisition is carried out by the LMS SCADAS Mobile, and the sensitivity of the micrometer, the sampling frequency \(f_{s}\) and sampling time are set through the PC1 (LMS Test. Lab).  
During the test measurement of the winding rotor, the following steps need to be satisfied to guarantee testing precision and stability: (1) clean the outer surface of the winding rotor to remove grease; (2) the frame is moved to the measured point, then the position of the micrometer is adjusted and fixed; and (3) place a certain time before testing to eliminate vibration. During the test, the sampling frequency is 6400 Hz, and the sampling time can be determined according to the speed-up time of the winding rotor.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**ID** & **Type** & **Model** & **Sensitivity** \\ \hline
1 & Keyence digital micrometer & LS-9000 & \(\pm\)2 \(\upmu\)m \\
2 & LMS SCADAS Mobile & SCM201V & / \\ \hline \hline \end{tabular}
\end{table}
Table 1: The instruments’ parameters used in the measurement device.  
Figure 9: Relationship between the variation of the angular speed and the time in the Newmark method.
## 3 Higher-Layer Protocols: MAC & Routing
### Csma/ca  
The Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) incorporates a handshaking process to establish the communication channel between two nodes. It uses request to send (RTS) and clear to send (CTS) control packets to create a tunnel free of collisions at both communication ends. After acquiring the channel, the data packet is sent to the destination node. Finally, the sender waits for an acknowledgment control packet (ACK) that will indicate the successful reception of data packet. If no ACK is received, then a contention mechanism, typically based on a back-off scheme, randomly delays the packet retransmission. Also, a maximum number of consecutive retransmission attempts is defined. If this maximum is reached, then the packet is discarded.
## 2 Methods  
### Survey Location and Dates  
The survey was conducted in the western Zhejiang region of China, as shown in Figure 1 below. The data were collected over a specific period, from 1 January 2022 to 31 January 2022, to ensure a comprehensive understanding of customer preferences and behaviors related to electricity sale packages.  
The decision to use only one month of data was based on several considerations. Firstly, electricity consumption patterns within a single month can provide a snapshot of customer behavior and preferences that are relevant to the evaluation of electricity sale packages. Secondly, collecting data for a shorter duration allows for a more focused analysis, reducing the complexity and potential noise associated with longer-term data. Lastly, considering the practical constraints of time and resources, a one-month period was deemed sufficient to capture the essential information needed for this study while keeping the data collection process manageable. In addition, it should be noted that the main purpose of this paper is to propose a new method of recommending electricity sale packages, rather than to conduct an in-depth study of electricity consumption behavior over a long-time span. Therefore, one month's data are sufficient to support the research purpose of this paper.
# Docking Control of an Autonomous Underwater Vehicle Using Reinforcement Learning
## 3 Classical Control of the AUV for the Docking Manoeuvre  
### PID Control of the Docking of the AUV  
A combination of classical PID controllers and line-of-sight guidance can provide a realistic benchmark for the docking problem, as opposed to trajectory control, as described in [35]. On AUVs, it is common to have separate decoupled controllers for the surge velocity, depth and heading (yaw angle) [33], with the latter being ignored in this study because of the analysis of only motions in the vertical plane. Surge can be controlled by modifying the motor torque. Conversely, since the AUV considered here does not have side thrusters, depth can only be controlled through the sternplane angle. As a result, line-of-sight guidance can be used to determine the desired pitch angle to move the AUV to the target depth. A further controller can then change the sternplane angle to match the desired angle.  
Figure 1: Diagram of the docking of an AUV onto a moving platform in surge, heave and pitch.  
As shown in Figure 2, two controllers are employed: one to control the surge speed in the body-fixed frame and one to control the pitch angle. The desired speed is calculated with the simple formula  
\[u_{\rm d}=0.5u_{0}\left[1+\tanh\left(e_{x}-x_{\rm d}\right)\right], \tag{13}\]  
where \(u_{0}\) indicates the speed at the start of the docking manoeuvre (as defined by a fixed distance from the docking platform), \(e_{x}=x_{\rm r}\) is the relative horizontal distance of the AUV from the platform and \(x_{\rm d}\) is an arbitrary parameter that needs tuning and that is used to help the AUV slow down before reaching the platform. Similarly, line of sight-guidance is used to obtain the desired pitch angle:  
\[\theta_{\rm d}=\arctan\left(\frac{e_{z}}{z_{\rm d}}\right), \tag{14}\]  
where \(e_{z}=z_{\rm r}\) is the relative vertical distance of the AUV from the platform and \(z_{\rm d}\) is an arbitrary parameter that needs tuning and that is used to help the AUV turn by looking ahead. Lower values result in more aggressive manoeuvres.  
The PID controllers then apply a control signal that is given by  
\[u=k_{\rm p}e+k_{\rm i}\int_{0}^{t}e(\tau){\rm d}\tau+k_{\rm d}\dot{e}, \tag{15}\]  
where \(e\) indicates the error signal of interest [33]. The proportional term adjusts the control signal based on the current value of the error, while the derivative term takes into account expected future variations of the error and the integral term corrects for steady-state errors by looking at past values of the error.  
Furthermore, the values of the torque and sternplane angles are limited within saturation blocks to prevent them from exceeding realistic physical constraints:  
\[Q_{\rm m,min}\leq Q\leq Q_{\rm m,max}, \tag{16a}\] \[\delta_{\rm s,min}\leq\delta_{\rm s}\leq\delta_{\rm s,max}. \tag{16b}\]  
Finally, the PID controller is turned off and the simulation stopped when the vehicle is close enough to the docking point, i.e., when  
\[x_{\rm r}^{2}+z_{\rm r}^{2}+\theta_{\rm r}^{2}<l_{\eta}, \tag{17}\]  
where \(l_{\eta}\) is a measure of the prescribed docking accuracy.
# Applying Topological Information for Routing Commercial Vehicles Around Traffic Congestion
## 4 Methodology and Model Development
### Network Building  
This section presents the procedure used to design and create a dynamic network dataset and to develop an alternative route selection tool that can identify optimal routes that accommodate truck traffic. First, street and traffic data were collected and processed, and a dynamic routable network dataset was built to store road edges and junctions and their attributes for all segments of the road network. Second, historical traffic profiles were incorporated into road edges; this allowed time-dependent variables to be assigned to road edges and junctions to reflect actual traffic conditions throughout the day. Finally, truck alternative route selection criteria were defined to evaluate the network in terms of suitability for trucks.  
The first step in creating a network dataset was to create a file geodatabase to store and manage spatial and nonspatial data. Then, a line feature class and two historical traffic data tables were created and stored in the file geodatabase. The line feature class represents the road segments, while the two historical traffic tables were used to store the change in travel time throughout the day. These tables are a speed-profiles table used to store speed profiles and a street-profiles table used to store the relationships between streets and speed profiles. The times of day were grouped into 15 min intervals. Each record in the traffic profiles table has a scale factor that is multiplied by free-flow speed for each time slice. Historical traffic data (with 15 min time slices) and real-time data were obtained for each time slice.  
Historical traffic data (with 15 min time slices) and real-time data were incorporated in the network dataset. Time-dependent variables were assigned to road edges and junctions to reflect actual traffic conditions throughout the day. Finally, a network dataset was built to develop network elements and to assign values to the network attributes. After the network was built and traffic data were incorporated, all potential alternative routes were identified and evaluated using alternative route selection criteria. Routing restrictions and attributes can also be incorporated into the network analysis. Network attributes, including travel time, restricted turns, posted speeds, and one-way streets, were assigned to network elements. Figure 6 shows the network building process.