esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Diesel Power System
### Diesel Generator Automatic Control System  
#### 4.2.1 Function of Control System  
The control system belongs to the (site mast control) SMC, one of whose most important tasks is controlling the work process of the diesel generator. It consists of condition monitoring, operation scheduling, and performing the remote control instructions.  
The condition monitoring equipment monitors generator state, detect fault state, checks the generator sets regularly to ensure their operation ability, and provides operation data to the (PC monitor) PCM.  
The operation dispatching equipment is used to deal with emergencies. For example, if the working generator operation fails, another generator must be started up to ensure stable energy power. When the core control equipment (like central controller) malfunctions or a communication link disconnects, a spare controller or communication link must take over the work instantaneously and automatically [33].  
The remote control instructions come from the (PC monitor) PCM which receives data through the satellite communication. The instructions mainly include switching generators by force and adjusting the priority of generator startup.
# Ce- and B-Doped Silica Fibers for Monitoring Low-Energy Proton Beams on a Medical Cyclotron
###### Abstract  
Many medical isotopes can be produced on a small cyclotron. The alignment and profiles of low-energy proton beams from cyclotrons used for medical radioisotope production, such as the TR13 cyclotron at TRIUMF, Canada, cannot be directly quantified during dose delivery with simultaneous constant feedback and sharp spatial resolutions. Doped silica fibers are a potential solution that has been tested at TRIUMF. To measure the effects of irradiation inside an isotope production target, we attached fibers to the outside of an \({}^{18}\)O gas target and measured the light output during irradiation. Different dopants, fiber diameters, and target materials were investigated. It was found that 200 \(\upmu\)m diameter Ce- and B-doped fibers produce signals linearly proportional to the beam current. This only deviated when the target was moved such that the beam was steered into the target wall, increasing the production of prompt radiation and causing the beam current to decrease but the fiber signal to increase. With the technique described here, the beam can be monitored on the target, including its steering and its overall alignment with the target.  
Ce-doped fiber; B-doped fiber; isotope production target; nuclear medicine isotopes Article
## 4 Experiment and Results
### Experiment Results and Analysis  
#### 4.4.1 Deep Feature Extraction Results  
Our framework innovatively adapts classical architectures into an occupational health-oriented pipeline through three key enhancements. The fully connected layers of the pre-trained ResNet-50 and AlexNet models, originally trained on ImageNet, were modified to facilitate deep feature extraction, as shown in Figure 4. Specifically, the output nodes of the second-to-last layer were adjusted to 1000 to enable the extraction of deep features, while the output nodes of the final layer were set to 2 to match the requirements of the binary classification task. To implement transfer learning, the weights of the original network structure were frozen, and only the modified fully connected layers were locally trained. Through iterative optimization, the batch size was set to 32, with a total of 100 training epochs. The cross-entropy loss function was employed, and stochastic gradient descent (SGD) was used as the optimizer. As a result, 1000 deep features were extracted from each model.  
These two sets of deep features were then standardized and subjected to dimensional reduction using Principal Component Analysis (PCA). The dimensional reduction retained 20 principal components, which were chosen based on the cumulative explained variance ratio. This process ensured that the selected components captured approximately 90% of the total variance, effectively preserving the most significant information from the original features while significantly reducing the model training burden. By using 20 principal components, we successfully reduced the feature dimension while retaining the most subtle and essential characteristics of the images, thereby improving both computational efficiency and the model's generalization performance.  
Figure 4: Simplified fine-tuning model. The unmodified model layers are omitted with arrows marked with dashed lines.
# Parasitic Motions of 3-PRS Parallel Mechanisms with Two Different Branch Chain Arrangements
## 4 Conclusions  
The general 2R1T PMs not only produce motions in the direction of DOF, but they also produce parasitic motion which incomplete motion constrained in the directions of other DOFs, which results in all points of the moving platform moving in a specific direction. As an inherent kinematic feature of PMs, parasitic motion leads to complex kinematics, requires real-time compensation, and hinders calibration. To study the inherent relation between the parasitic motion and the structure of 3-PRS PMs, two improved 3-PRS PMs of different branch chain arrangements are proposed in this paper.  
(1) The parasitic motions are obtained using the closed-loop vector method according to the constraint conditions. According to Sections 2.3 and 3.3, it is known that parasitic motions are inherent kinematic features and vary with the configurations of the two mathematical models of 3-PRS PM I and II.  
(2) The obtained parasitic motions are related to the kinematic parameters and structural parameters of 3-PRS PM through analysis. When the kinematic parameters vary in a  
Figure 19: Solved results of \(S_{1}S_{2}S_{3}\).  
Figure 18: Improved 3-PRS PM II.  
relatively small range, for instance, \([-5^{\circ},5^{\circ}]\), the parasitic motions are not obvious and can be ignored. When the kinematic parameters change greatly, the amplitude is relatively large and should be taken into account.  
(3) Given the structural and kinematic parameters, the maximum and minimum of parasitic motions in the limit position are pointed out and two improved 3-PRS PMs without parasitic motions are obtained. According to Sections 2.4 and 3.4, parasitic motion can be avoided in the configuration at the design stage.  
The results show that parasitic motions have an influence on kinematic analysis, which is meaningful to traditional five-axis CNC machine tools while machining the parts of the complex structure. For the 2R1T PMs with mixed degrees of freedom, studying and clarifying the trajectory of motions is of great practical significance to the motion control, error compensation, and calibration of PMs.  
[PERSON] provided the ideas and wrote the paper manuscript. [PERSON] established the mathematical model and kinematics analysis. [PERSON] analyzed parasitic motions and data. [PERSON] and [PERSON] provided reviewing and editing. [PERSON] provided project administration and funding. [PERSON] obtained the resources. [PERSON] provided supervision. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Key Research and Development Program of Shanxi Province (Grant NO. 2022 ZDYF082). This work was also supported by the Shanxi Province Central Guidance Local Science and Technology Development Fund Project (Grant NO. YDZJSX2022A030).  
Not applicable.  
The authors declare no conflict of interest.
## 5 Results and Discussion
### Radial Configuration Results  
To verify the efficiency of the proposed solution methodology, 20 evaluations were performed for the radial configuration. The best result obtained had a cost of 108,249.36. Furthermore, this solution had a repeatability higher than 50% of the total evaluations. The best solution found for this test system corresponds to nodes 13, 25, and 30, with D-STATCOMs sizes of 258.51, 105.47, and 538.02 kvar, respectively. Note that, in this simulation, 20 individuals and 1000 iterations were set to evaluate the performance of the SSA.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Hour** & **Ind. (pu)** & **Res. (pu)** & **Com. (pu)** \\ \hline  
\hline \hline \end{tabular}
\end{table}
Table 3: Load consumption profiles per user type: residential (Res.), industrial (Ind.), and commercial (Com.).  
The best five solutions reached by the methodology proposed for the IEEE 33-node system with a radial topology are presented in Table 4. The criteria used to select the five best solutions is the lowest operating cost using SSA without considering the execution time.  
Note that the fifth result in Table 4 corresponds to a value of 108,428.91 dollars per year and defines the D-STATCOM locations at nodes 14, 10, and 30, with sizes of 180.37, 82.17, and 605.97 kvar, respectively. In this way, it can be stated that, for both the best and the worst solution, there is an optimal location at node 30. Furthermore, the difference between the two is 179.55 dollars, which means an approximate error of 0.166%. Even though this is a low error, it can be said that the gap between the two demonstrates that the solution space is large, despite the fact that they converge to a similar result.  
The processing times for each algorithm evaluation regarding the best and worst result are 2.4317 and 2.0876 min, respectively. Which is an adequate computational effort due to the complexity of the studied problem. It is also important to mention that the nodes at which the D-STATCOMs are optimally placed are numbers 30 (commercial), 25 (industrial), and 13 (industrial).
## 3 Materials and Methods
### Designing and Prototyping the Capture Rig
#### 3.2.2 Software Implementation  
We decided to use a fixed addressing of cameras to get information on the location of each camera taking the photographs. We thus defined an address nomenclature and reserved the corresponding IP addresses in the router: level 1 was 192.168.0.11x, level 2 was 192.168.0.12x, and so on, the last digit being the camera index on the corresponding level. Each Raspberry Pi ran a Python backend, including a TCP/IP server that waits for incoming commands to set the white balance and shutter time. This server also enables launching the capture, with the image data then being transferred over the same network TCP/IP connection. A semi-automatic procedure was developed that allowed the easy installation of a fresh Raspberry Pi running Raspbian, in command line and over the network (SSH), with minimum manual intervention.  
We developed the remote/client software in Unity, and tested it on both Windows and Mac OS X. The remote software implements 40 TCP/IP clients and displays a user interface allowing the operator to set capture parameters and remotely trigger cameras in synchronization. After the capture process is launched, the images are gradually displayed side-by-side on the screen for easy monitoring. Each image is then saved on disk with a file naming nomenclature that includes a timestamp and a camera index. Launching this process via WiFi allows the user to carry the laptop during capture, so as to be able to move outside of the rig's field of view.
## 2 Methodology
### Calculation of Driving Workload  
Different road, traffic and environmental conditions in work zones provide different amounts of stimulation to the driver, which determines the driver's driving workload, and the driving workload of the same driver under different road, traffic and environmental conditions can also vary. Driving workload can reflect different impacts of road and traffic conditions on drivers in real time. When the driving workload is too high, the driver cannot fully adapt to the road conditions, so he/she becomes very nervous and worried, accompanied by a busy driving operation; when the driving workload is too low, the driver's driving alertness and wakefulness are reduced, and driving fatigue is easily induced.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**Cross Slope (\%)**} & \multicolumn{4}{c}{\(-\)**2.0**} & \multicolumn{4}{c}{\(-\)**3.0**} & \multicolumn{4}{c}{\(-\)**4.0**} \\ \cline{2-13}
**Median Width (m)** & **2** & **3** & **3.5** & **4.5** & **2** & **3** & **3.5** & **4.5** & **2** & **3** & **3.5** & **4.5** \\ \hline \multirow{3}{*}{
\begin{tabular}{c} Speed \\ Limit (km/h) \\ 80 \\ \end{tabular} } & 40 & 40 & 45 & 45 & 40 & 40 & 45 & 45 & 40 & 45 & 45 & 45 \\  & 50 & 55 & 60 & 60 & 65 & 55 & 60 & 65 & 55 & 60 & 65 \\  & 60 & 70 & 75 & 75 & 80 & 70 & 75 &  
Studies have shown that fluctuations in heart rate variability (HRV) and the ratio of low-frequency to high-frequency (LF-HF) heart rate reflect the driver's sympathetic nerve activity and have a positive correlation with driving workload, which can be adopted to measure the driver's driving workload. The higher the driving workload, the lower the HRV, and LF will significantly increase, while HF will decrease. As a result, LF-HF will increase notably, and sympathetic nerve excitability will be enhanced. To finish the driving task and maintain working ability, drivers need to spend more energy; thus, their driving workload will be higher. The measurement model of driving workload is shown in Equation (7):  
\[K_{ij}=\left[\left(\frac{LF}{HF}\right)_{ij}-A_{i}\right]/V_{ij} \tag{7}\]  
where \(K_{ij}\) is the driving workload of driver \(i\) at position \(j\); \((LF/HF)_{ij}\) is the HRV of driver \(i\) at position \(j\); \(A_{i}\) is the HRV when driver \(i\) is driving normally; and \(V_{ij}\) is the running speed when driver \(i\) is at position \(j\), km/h.  
The classification thresholds of driving workload are shown in Table 3[35].
# Numerical Modeling of Temperature Effect on Tensile Strength of Granitic Rock
###### Abstract  
The aim of this paper is to numerically predict the temperature effect on the tensile strength of granitic rock. To this end, a numerical approach based on the embedded discontinuity finite elements is developed. The underlying thermo-mechanical problem is solved with a staggered method marching explicitly in time while using extreme mass scaling, allowed by the quasi-static nature of the slow heating of a rock sample to a uniform target temperature, to increase the critical time step. Linear triangle elements are used to implement the embedded discontinuity kinematics with two intersecting cracks in a single element. It is assumed that the quartz mineral, with its strong and anomalous temperature dependence upon approaching the \(\alpha\)-\(\beta\) transition at the Curie point (\(\sim\)573 \({}^{\circ}\)C), in granitic rock is the major factor resulting in thermal cracking and the consequent degradation of tensile strength. Accordingly, only the thermal expansion coefficient of quartz depends on temperature in the present approach. Moreover, numerically, the rock is taken as isotropic except for the tensile strength, which is unique for each mineral in a rock. In the numerical simulations mimicking the experimental setup on granitic numerical rock samples consisting of quartz, feldspar and biotite minerals, the sample is first heated slowly to a target temperature below the Curie point. Then, a uniaxial tension test is numerically performed on the cooled down sample. The simulations demonstrate the validity of the proposed approach as the experimental deterioration of the tensile strength of the rock is predicted with agreeable accuracy.  
thermally induced cracking; embedded discontinuity FEM; rock fracture; rock tensile strength; thermo-mechanical problem +
Footnote †: journal: Applied  
11 May 2021  
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**Compgrid:** 2021 by the author. Licence MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
## 4 Evaluation
### Evaluation Methodology
#### 4.1.2 Performance Evaluation Metrics
\[Average\;energy\;consumption=\sum_{i=1}^{n}(E_{i}-e_{i})/n \tag{11}\]  
Energy distribution. Another metric that gives an insight on the fairness of routing techniques is the energy distribution, \(\alpha\), which we define as the ratio between \(Ec_{O}\), the average percentage of initial energy consumed on the other nodes, and \(Ec_{C}\), the average percentage of initial energy consumed on the central nodes (cf., Equation (12)). \[\alpha=Ec_{O}/Ec_{C} \tag{12}\] \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Routing Technique (\(p\))**} & \multicolumn{3}{c}{**Nodes and Number of Transmissions**} & \multirow{2}{*}{\(\gamma_{p}\)} & \multirow{2}{*}{**Fairness; \(F_{p}\) (\%)**} \\ \cline{2-2} \cline{5-6}  & **n1** & **n2** & **n3** & **n4** & \\ \hline A & 12 & 12 & 12 & 12 & 0 & 100 \\ B & 13 & 12 & 12 & 11 & 0.7 & 96.6 \\ C & 24 & 8 & 8 & 8 & 6.9 & 66.7 \\ D & 32 & 8 & 4 & 4 & 11.7 & 43.9 \\ E & 47 & 1 & 0 & 0 & 20.2 & 2.8 \\ F & 48 & 0 & 0 & 0 & 20.8 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Six fictitious routing techniques for describing the working principle of the fairness metric and illustrating how it interprets fairness.
# Quantum Key Distribution in Kubernetes Clusters
## 5 Related Work  
Many works have been published on different aspects of the QKD integration in specific environments or regarding the management of QKD networks. For the scope of this paper, it is interesting to briefly discuss some papers that propose routing protocols for QKD and other attempts to integrate QKD in specific domains. The authors of [24] propose a routing protocol based on a custom version of OSPFv2. In this case, the cost function heavily relies on the key material available on each QKD link. This avoids having paths without the minimum number of keys required, but it does not consider congestion or other network peculiarities. The authors of [22] also proposed a modified version of OSPFv2, though they trace the traffic load on the various links and the cost function depends on that. Another work, discussed in [21; 35] and regarding the Chinese HCW QKD network, proposes the use of OSPF in combination with a _Quantum Key Reservation Approach (QKRA)_ based on the IntServ model. The OSPF protocol finds the shortest path between source and destination, and then the source sends a request of key reservation to all the nodes within the path. Even in this case, they assure that the key material is sufficient for the exchange, but the path may not be optimal. They also pointed out in [21; 36] that even an extended version of OSFFv2, including QoS constraints, could not be optimal for QKD networks. In general, as stated in [37], we must also evaluate the impact of a public authenticated channel on the QKD performances. This assertion is true also for the routing protocol. For example, suppose we use QKD generated keys for the authentication and the integrity of the public channel. In that case, we should also optimise their consumption to be efficient regarding the number of packets exchanged for routing purposes.  
Other works target QKD integration in various domains. It is worth mentioning the work of [38] related to the SD-QKD and introduced in Section 2.3. The authors, in that case, proposed a new programmable software network architecture based on SDN to integrate QKD in network operator infrastructures. A similar work was proposed in [39] regarding the specific domain of NFV. In this case, the idea was to manage QKD systems using an SDN controller which instructs optical switches on how to forward the traffic of the quantum channel. In this case, the NFV orchestrator was in charge of both managing the SDN controller and requesting key material to the key server. In contrast with the previous ones, our work tries to generalise the problem of the integration of QKD in software-defined infrastructures by proposing a software stack that could be easily integrated into wide adopted technologies.
## 3 Results and Discussion
### Effect of Genotype on Total and Individual Anthocyanins
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & \multicolumn{10}{c}{**Culivar**} \\ \hline \hline
**Location** & **Year** & **Can** & **Cle** & **Flo** & **Fri** & **Gar** & **Son** &
\begin{tabular}{c} _Yearly_ \\ _Mean per_ \\ _Location_ \\ \end{tabular} \\ \hline
**Norway** & **2017** & 18.2 \(\pm\) 2.5 & 5.3 \(\pm\) 1.1 & 1.4 \(\pm\) 0.2 & 27.0 \(\pm\) 3.7 & 0.9 \(\pm\) 0.5 & 7.3 \(\pm\) 1.1 & _10.0 A_ \\  & **2018** & 11.9 \(\pm\) 3.4 & 2.5 \(\pm\) 1.5 & 1.4 \(\pm\) 0.2 & 23.3 \(\pm\) 11.9 & 0.5 \(\pm\) 0.1 & 19.2 \(\pm\) 3.2 & _9.8 A_ \\  & _mean_ & _15.1 cd_ & _3.9 abc_ & _1.4 ab_ & _25.2 d_ & _0.7 a_ & _13.2 kcd_ & \\ \hline
**Poland** & **2017** & 26.2 \(\pm\) 4.4 & 7.1 \(\pm\) 0.4 & 2.1 \(\pm\) 1.7 & 25.2 \(\pm\) 3.2 & 0.9 \(\pm\) 0.3 & 5.9 \(\pm\) 0.9 & _11.2 A_ \\  & **2018** & 28.3 \(\pm\) 5.7 & 9.1 \(\pm\) 1.1 & 3.7 \(\pm\) 0.3 & 25.9 \(\pm\) 4.8 & 3.0 \(\pm\) 0.2 & 8.5 \(\pm\) 0.6 & _13.1 A_ \\  & _mean_ & _27.3 c_ & _8.1 b_ & _2.9 a_ & _25.5 c_ & _2.0 a_ & _7.2 b_ & \\ \hline
**Germany** & **2017** & 21.0 \(\pm\) 3.6 & 6.7 \(\pm\) 0.7 & 1.4 \(\pm\) 0.3 & 25.4 \(\pm\) 1.8 & 0.9 \(\pm\) 0.5 & 6.4 \(\pm\) 1.9 & _10.3 A_ \\  & **2018** & 21.2 \(\pm\) 9.6 & 9.6 \(\pm\) 6.8 & 6.2 \(\pm\) 1.5 & 20.9 \(\pm\) 3.6 & 2.3 \(\pm\) 0.7 & 6.8 \(\pm\) 2.5 & _11.2 A_ \\  & _mean_ & _21.1 c_ & _8.2 b_ & _3.8 ab_ & _23.1 c_ & _1.6 a_ & _6.6 b_ & \\ \hline
**Italy** & **2017** & - & 8.1 \(\pm\) 0.9 & - & 24.0 \(\pm\) 3.8 & 2.0 \(\pm\) 0.2 & 5.5 \(\pm\) 0.5 & _9.9 B_ \\  & **2018** & - & 7.1 \(\pm\) 1.2 & - & 7.1 \(\pm\) 2.5 & 1.3 \(\pm\) 0.1 & 2.6 \(\pm\) 1.2 & _4.5 A_ \\  & _mean_ & - & _7.6 b_ & - & _15.6 c_ & _1.6 a_ & _4.1 ab_ & \\ \hline
**France** & **2017** & 23.6 \(\pm\) 3.2 & 4.5 \(\pm\) 1.6 & 2.0 \(\pm\) 0.1 & 20.4 \(\pm\) 3.7 & 1.2 \(\pm\) 0.4 & 4.8 \(\pm\) 1.8 & _9.4 A_ \\  & **2018** & 24.3 \(\pm\) 3.1 & 7.2 \(\pm\) 1.3 & 1.8 \(\pm\) 0.4 & 14.1 \(\pm\) 3.8 & 1.8 \(\pm\) 0.9 & 3.6 \(\pm\) 1.5 & _8.8 A_ \\  & _mean_ & _23.9 d_ & _5.8 b_ & _1.9 a_ & _17.2 c_ & _1.5 a_ & _4.2 ab_ & \\ \hline
**Culivar mean over** & _21.8 c_ & _6.7 b_ & _2.5 a_ & _21.3 c_ & _1.5 a_ & _7.0 b_ & \\ \hline
**_Significance_** & _Culivar_ & _Location_ & _Year_ & _Culivar x_ & _Culivar x_ & _Location x_ & _year_ \\  & *** & _ns_ & _ns_ & ** & ** & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Effect of growing location and year on pelargonidin-3-(6-O-malonyl)-glucoside content as the mean of two picking dates in fruits of six strawberry cultivars.