esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Related Work  
VPD affects five main aspects: (1) pore opening, (2) CO\({}_{2}\) absorption, (3) transpiration, (4) nutrient intake at the roots, and (5) crop stress [4]. There is a complex trade-off between VPD and these factors. Plant transpiration is likely to be increased in high-VPD conditions [7]. Increasing the amount of CO\({}_{2}\) absorbed by plants can reduce the amount of nutrients, and increasing the amount of nutrients can put more stress on plants. Therefore, to achieve the best results, it is necessary to find a suitable VPD point for the plant's growth stage.  
Research on the effect of a low or a high VPD has been performed [16,28]. The low VPD (from 0.15 to 0.65 kPa) with the high-humidity treatments produced smaller fruits and thereby a lower yield compared with the low-humidity treatments [28]. The high VPD (from 1.6 to 2.2 kPa) during the hottest periods with low humidity reduced the fruit yield and their uniformity [7].  
Many studies have reported the results of coordination between these factors or the results of verifying theoretical hypotheses [5,20, 21, 22, 23, 32]. [PERSON] et al. [30] proposed a micro-fog system for regulating the VPD of a greenhouse. The system was installed during the  
Figure 10: Qualitative characteristics of tomato crops grown in soil: (**a**) fresh weight of commercial fruits; (**b**) equatorial diameter of commercial fruits; (**c**) hardness of commercial fruits; (**d**) sugar content of commercial fruits.  
summer season, and the experiments resulted in around a 12.3% increase in the marketable tomato yield per plant by regulating the VPD above 0.5 kPa. Since adjusting humidity can consume water, it is necessary to devise a water-saving plan to increase water productivity. [PERSON] et al. [5] investigated the effect of VPD regulation on water use efficiency. They reported that VPD regulation reduced the evaporative driving force for water movement and improved water use efficiency by reducing transpiration and improving photosynthesis. [PERSON] et al. [31] explored the interaction of VPD and CO\({}_{2}\) on plant water status, stomatal characteristics, and gas exchange parameters in summer greenhouses in a semi-arid area. They reported that reducing the VPD alleviated the water stress of the plant and increased the gas exchange area of the leaf, which was beneficial to the entry of CO\({}_{2}\) into the leaf. The increase in CO\({}_{2}\) resulted in promoting the photosynthetic rate and improving the water use efficiency and yield. [PERSON] et al. [32] revealed the strong effects of an increased VPD on the traits and physiological variables affecting reproductive development and yield, which outline a potential mechanism for yield decreases.
## 5 Results  
### Mechanical Properties  
Mechanical properties, such as compression strength, elastic-plastic relationship, and hardening (or softening) characteristics, can be revealed from stress-strain curves. To investigate the above items, compression results are selected for comparison. As depicted in Figure 13, the deformation paths of the rock mass are quite different and varied with joint angles. As for the horizontally jointed condition whose joint angle is perpendicular to the main loading direction, rock mass compacts heavily at the beginning. The phenomenon demonstrates that this perpendicular-jointed condition is unstable and easy to induce localized instability. As the loading continues, the rock sample shows a dense state, undergoes a temporary period of elasticity, and finally reaches the failure's peak. The peak strength of perpendicular-jointed rock mass is nearly 5.7 MPa, which decreases significantly compared with the UCS of intact rock. Turning to the 45\({}^{\circ}\) condition, there exists a similar situation in general: the rock mass with 45\({}^{\circ}\) joints experienced a similar compression mode from the beginning to the peak position, also with a peak strength of 5.7 MPa. However, the post-peak situation is different where the stress drop at 45\({}^{\circ}\) jointed condition is more moderate than that of the zero-degree case. For 90\({}^{\circ}\) jointed rock mass, the total stress-strain curve's characteristic is basically the same as that of the intact rock. When continued loading is applied, rock mass enters into the elasticity status first and then undergoes plasticity after the yield point, and finally, failure happens when the stress reaches the strength value. The biggest difference lies in the failure mode of the rock mass with a 90\({}^{\circ}\) jointed case is significantly brittle, which shows that the process of energy release should be fiercer.  
Based on the above description and practical tunnel engineering, we can obtain the following findings: If joints exist within the ground area, mechanical feedback will be greatly affected varied with the joint angle. Specifically, the perpendicular-jointed (0\({}^{\circ}\)) condition mainly affects the strength of the rock mass while the rock mass still maintains the brittle failure mode. Oblique-jointed (45\({}^{\circ}\)) condition normally produces the effect on both strength and failure mode. Parallel-jointed (90\({}^{\circ}\)) condition influences the mechanical characteristic a little, decreasing the strength slightly. Hence, we can conclude that if the tunnel is constructed in jointed ground, joint angles will affect engineering stability. In particular, the perpendicular-jointed condition is most dangerous because of its comparatively lower strength and the maintained brittle failure mode, which implies that energy will be released sharply upon failure and, therefore, threatens the tunnel structure the most.  
Figure 12: Revision of measurement error induced by discontinuous deformation via the OPFFM algorithm.
## 3 Results and Discussion
### Assessment of the Health Risks Associated with the Consumption of Aluminum from Tea Infusions
Due to its toxicity, it is essential to determine the concentration, speciation, and bioavailability of aluminum in tea extracts and to determine their modifications resulting from changes in brewing conditions. Generally, despite the high aluminum concentration in tea, its absorption in the gastrointestinal tract is low. It has been determined that only 0.1% of aluminum consumed from various sources during the day is absorbed (depending on the form in which this metal is found). If the aluminum forms found in tea are more bioavailable than those found in other dietary ingredients, then this beverage could contribute more to the daily intake of aluminum than the total amount in other foods [43]. Research shows that the primary forms of aluminum in the infusion are complexes of this metal with polyphenols, aluminum fluoride, aluminum oxalate, free Al\({}^{3+}\)- and its hydrolysates. It is worth noting that it is very difficult to determine a consistent picture of aluminum speciation in tea infusions [47]. Despite the high aluminum concentration in the tea infusion, the fact that it forms strong complexes reduces its toxicity [48]. The influence of factors such as infusion time, sugar addition, and lemon juice addition on aluminum speciation in the infusion was examined. It turns out that the extension of the extraction time and the addition of sugar do not significantly change the speciation of this metal. However, adding lemon juice to previously brewed tea modifies the form of aluminum in both black and green tea infusions. The results of this study indicate that the addition of lemon juice has a significant effect on aluminum speciation in tea infusions. The increase in the solubility of aluminum ions caused by the increase in the acidity of infusions and the change in the form of this element in the infusion increase its absorption by the body [12,39].
# IFDA: Intermittent Fault Diagnosis Algorithm for Augmented Cubes Under the PMC Model
## 5 IFDA for Augmented Cubes
In the subpath identified in this step, all nodes except the tail node are identified as fault-free. Next, based on the syndrome of the cycle, the fault-free nodes in set \(FF\) are employed to determine the unknown states of nodes in set \(F\). Finally, the Depth-First Search (DFS) algorithm is invoked for the unknown nodes to group the unknown nodes that are 0-path connected to them into a component. If this component has a 0-path connection with the fault-free nodes, it can be concluded that the nodes within this component are in a fault-free state; otherwise, they are in a faulty state and are kept in the set \(F\). **Input:** A syndrome for an \(N\)-node cycle under the PMC model, and its intermittent fault diagnosability \(t_{i}(t_{i}\leq T)\). **Output:** The set of fault-free nodes, denoted as \(FF\); the set of fault nodes, denoted as \(F\). **Step 1**: By executing the \(Cycle\)-\(Partition\) algorithm, mapping the cycle to subpaths \(\{P_{1},P_{2},\ldots,P_{s}\}\), where \(s\leq t_{i}\). **Step 2**: Determine the subpaths of Type-I according to Lemma 15 and the fault bound \(T\) in Lemma 16. If \(|P_{j}|-1\leq(t_{i}-s+1)\), then \(F=F\cup V(P_{j})\). Otherwise, move the tail node of subpath \(P_{i}\) to the set \(F\), and move the remaining nodes to the set \(FF\). **Step 3**: Based on the syndrome of the cycle, determine the status of neighbor nodes in \(F\) using the fault-free nodes in set \(FF\). **Step 4**: The DFS algorithm is invoked to partition nodes in set \(F\) that are interconnected via 0-paths into a component, denoted as \(C_{i}\); if a node has no 0-path connection to any other node, it forms an isolated component. **Case 4.1**: If \(FF=\emptyset\), the largest component constructed in Step 4 are fault-free nodes, while the remaining nodes are faulty nodes [21]. **Case 4.2**: If \(FF\
eq\emptyset\), all nodes in the component \(C_{i}\) are classified as fault-free if such a connection exists between \(C_{i}\) and \(FF\), \(FF=FF\cup V(C_{i})\); otherwise, they are marked as faulty, \(F=F\cup V(C_{i})\). **Algorithm 2** Intermittent Fault Diagnosis Algorithm (IFDA)
## 7 Risk Analysis
### Edge Gateway
#### 7.6.4 Elevation of Privilege  
1. **Component**  
_Security risk_: If the attacker finds vulnerabilities in the authentication, for example, using a brute force attack or social engineering, they may be able to find out the password of the admin account. This leads to them gaining high-level privileges to the edge gateway. This could lead to a severe safety impact, like dispatching a fake call or denying the service. In order to isolate and fix the consequences of the attack, a lot of resources are consumed. The whole system could be compromised, and the attacker could obtain access to sensitive data.  
_Security measures_: In order to mitigate the attack risk, strong access controls should be implemented to limit who can access the edge gateway. The principle of least privilege is recommended, ensuring that users only have the permissions necessary for their tasks. Also, firewalls can be deployed to filter incoming and outgoing traffic, blocking unauthorized access attempts.
## 4 Experiments
### Test Based on GNSS Signal Simulator  
The next used the Compass B3 signal collected with the GNSS signal simulator to verify the proposed aid method. The experimental facility consists of a control computer, a GNSS signal simulator, a radio frequency front end and a high-speed data collection card, as illustrated in Figure 7. The GNSS signal simulator can output radio-frequency signals of various constellations. The control computer provides the GNSS signal simulator with the functions of scene editing, downloading and running state monitoring (including simulation time, satellites state, and user trajectory). Users can customize scenes according to their necessary receiver dynamic characteristics. It also provides special  
Figure 5: **(a)** Comparison of the in-phase output; **(b)** Comparison of the tracking errors.  
Figure 6: Estimated Doppler frequency and Doppler shift rate with jerk aided PLL.  
scenes with satellite-to-receiver relative motion. After the radio-frequency signal collection, we implement intermediate frequency signal acquisition and tracking in a Matlab based software receiver.  
The test adopts the scene of satellite-to-receiver relative motion, with the initial line-of-sight velocity of 8,000 m/s, initial acceleration of 100 g, constant jerk of 10 g/s, signal power of \(-110\) dBm. We collect intermediate frequency data for a duration of 6 seconds. Taking the PRN 6 satellite signal as an example, it is difficult to obtain the correct line-of-sight acceleration, so the jerk-aided PLL based on the nonlinear tracking differentiator is verified according to the constant line-of-sight jerk of 10 g/s. The performance of jerk-aided Kalman-PLL is compared with the PLL without assistance. The results are shown in Figures 8 and 9.  
Figure 8 shows the comparison of carrier phase tracking errors. It is concluded that the PLL without assistance fails to track, but the jerk-aided Kalman-PLL can perform stable tracking with a phase tracking error of about 13\({}^{\circ}\). As shown in Figure 9, the Doppler frequency and frequency shift rate that are estimated by the PLL without assistance cannot reflect real dynamic characteristics, however, the values estimated by jerk-aided Kalman-PLL match with the receiver dynamic characteristics.  
From the test results based on the GNSS simulator, the jerk-aided Kalman-PLL can efficiently track the highly dynamic GNSS signal with constant line-of-sight jerk of 10 g/s. Meanwhile, it is concluded from Figures 2 and 3 that high precision line-of-sight jerk can be estimated with the nonlinear tracking differentiator. In result, the high dynamic Compass B3 signal can be efficiently tracked with jerk-aided Kalman-PLL in the Compass/INS integrated navigation system, by using the inertial acceleration measurements to estimate line-of-sight jerk based on the nonlinear tracking differentiator, and adjusting relevant coefficients of the process noise matrix of the Kalman-PLL.  
Figure 9: **(a)** Doppler frequency and Doppler shift rate estimated by PLL without assistance; **(b)** Doppler frequency and Doppler shift rate estimated by jerk aided Kalman-PLL.
# Vibration Energy Harvester Based on Bilateral Periodic One-Dimensional Acoustic Black Hole
## 4 Experimental Test
### Results and Discussion
#### 4.2.2 Optimal Impedance Matching of VEH with ABH  
The second value of the natural frequency of each structure is used as the frequency of the external excitation, and the impedance matching is performed under the sinusoidal  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **AlSi10 Mg** & **Iron** & **PZT-5H** \\ \hline [PERSON]’s modulus (GPa) & 74.01 & 200 & 60.61 \\ Density (kg/m\({}^{3}\)) & 2790 & 7870 & 7500 \\ Poisson’s ratio & 0.33 & 0.29 & 0.31 \\ Damping loss factor & 0.02 & 0.03 & 0.31 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameters of size and material of energy harvester.  
Figure 18: Voltage frequency response of several beams.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Structure/Natural** & \multicolumn{3}{c}{**First**} & \multicolumn{3}{c}{**Second**} \\ \cline{2-7}
**Frequency (Hz)** & **Simulation** & **Test** & **Deviation** & **Simulation** & **Test** & **Deviation** \\ \hline Traditional ABH & 18.1 & 20 & 9.5\% & 144.9 & 153 & 5.3\% \\ Model 1 & 18.2 & 20 & 9.0\% & 149.6 & 146 & 2.5\% \\ Model 2 & 16.4 & 18 & 8.9\% & 120.7 & 140 & 13.8\% \\ Model 3 & 15.2 & 17 & 10.6\% & 110.5 & 130 & 13.5\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison of natural frequency.  
excitation with an amplitude of 3 N. The output voltage and power of VEHs with an ABH in the optimal impedance matching are shown in Figures 19 and 20.  
The optimal impedance value of the traditional VEH with an ABH is 115 k\(\Omega\), the output peak voltage is 84.78 V and the output power reaches 33.63 mW. The optimal value of VEH Model 1 is 110 k\(\Omega\), the output peak voltage is 88.36 V and the output power reaches 35.62 mW. The optimal value of VEH Model 2 is 100 k\(\Omega\), the output peak voltage is 137.58 V, and the output power reaches 75.01 mW. The optimal value of VEH Model 3 is 67 k\(\Omega\), the output peak voltage is 169.16 V, and the output power is 91.52 mW. The peak output voltage of VEH Model 3 is 1.9 times that of the VEH with the traditional ABH, and the peak output power of VEH Model 3 is 2.7 times that of the VEH with a traditional ABH. The harvesting efficiency of the VEH with an ABH can be improved significantly with the number of ABH arrays.
## 5 Conclusions  
In this paper, four different models were utilized to map the ionospheric TEC in the polar regions based on GPS ground measurements for about 13 years. According to the unique temporal and spatial characteristics of the polar ionosphere, the TEC variation was analyzed considering the disturbed polar ionosphere conditions, including different phases of solar activity, polar days and nights, the WSA, and an ionospheric storm. The variations of the polar TEC during a period of about one solar cycle and the corresponding relationships with the solar activity index of F10.7 were investigated. Moreover, we tracked the evolution of the ionization patch during a geomagnetic storm.  
The SCH model had optimal mapping performance for the polar regions compared to other models. During the whole solar cycle, the SCH model had RMS errors of less than 3.0 TECU in the Arctic, while in the Antarctic the RMS errors were between 1.5 and 3.5 TECU. The polar TEC exhibited various changes under different ionosphere conditions. The TEC during the polar day was about twice as much as that during the polar night under similar levels of solar activity. During the polar night, the ionospheric TEC was related to the latitude, and the TEC increased significantly when the latitude became lower in the daytime. In the polar day over the Arctic, the TEC decreased with the decrease of the latitude at night. During the polar day in the Antarctic, the TEC values at UTC from 1:00 to 11:00 did not reach the maximum near the 12:00-14:00 LT time window, and the highest TEC was registered in the Antarctic Peninsula and Weddell Sea because of the influence of the WSA. For one solar cycle, the ionospheric TEC was strongly correlated with the solar activity levels. From 2006 to 2018, the solar activity reached its highest level in 2014, and the polar TEC exhibited the maximum in that particular year. In addition, the ionospheric TEC of the Antarctic had larger amplitude of annual variation than that in the Arctic.  
The analysis of the spatiotemporal variations of the polar ionospheric TEC and the study case of ionization patch on DOY 076 in 2015 indicate that the SCH model provides adequate resolution and accuracy to map the polar TEC variation, and it also seems to be very well suited to track some ionization patches; all this could be significant for navigation and positioning in the polar regions.  
Conceptualization, H.J. and Z.W.; methodology, H.X., H.J., and J.A.; data curation, X.X., H.Y., and C.F.; validation, H.X. and H.J.; formal analysis, H.X. and J.A.; writing--original draft, H.X.; writing--review and editing, H.J., Z.W., X.X., H.Y., and C.F. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Ministry of Science and Technology of Taiwan via grant no. 108-2116-M-001-016 and the Natural Science Funds of China (no. 41776195).  
We would like to acknowledge the International GNSS Service (IGS) and the Polar Earth Observing Network (POLENET) for providing the GPS data and the products used in our experiment.  
The authors declare no conflict of interest.
# A Hardware-Efficient Vector Quantizer Based on Self-Organizing Map for High-Speed Image Compression
## 4 Experimental Results and Discussion
### Hardware Implementation
Figure 6: Visual quality comparisons between the compressed images for **(a)** Lena, **(b)** Peppers, and **(c)** Tank. The images in each row from the left to the right are the compressed images as the sizes of pixel-block are \(4\times 4\) (the corresponding compression ratio is 16), \(4\times 8\) (the corresponding compression ratio is 32), \(8\times 8\) (the corresponding compression ratio is 64), \(8\times 16\) (the corresponding compression ratio is 128), and \(16\times 16\) (the corresponding compression ratio is 256), respectively. Figure 7: PSNR (peak signal-to-noise ratio) vs. compression ratio for Lena, Peppers, Tank.
## 3 Results and Discussion
### Simulation of Thermal Profiles Using FSC  
#### 3.2.1 Critical Heating and Cooling Rate  
The heat flow signals [mW] from FSC at increasing heating rates for HMWPA and LMWPA are displayed in Figure 4a,b, respectively. Especially for HMWPA, cold crystallization peaks become clearly visible at heating rates from 5 to 20 \({}^{\circ}\)C/s in the range of 50-150 \({}^{\circ}\)C. The subsequent melting peaks above 150 \({}^{\circ}\)C indicate melting of the formed crystalline structures. Even for a heating rate of 50 \({}^{\circ}\)C/s, a very broad cold crystallization peak and successive melting peak could be observed. For LMWPA, these cold crystallization peaks are less apparent. However, a heating rate of 100 \({}^{\circ}\)C/s shows no cold crystallization peaks for both materials and is thus adopted as the critical heating rate. For all measurements, a cooling rate of 250 \({}^{\circ}\)C/s was applied before heating at the distinct rates. Since no melting peaks emanate when heating at the critical heating rate of 100 \({}^{\circ}\)C/s, it is assumed the  
Figure 3: The recorded thermal profiles for the different printing conditions.  
materials are completely quenched at a cooling rate of 250 \({}^{\circ}\)C/s, thus fully suppressing crystallization, which supports the selection of this rate as the critical cooling rate. Note that the glass transition temperatures of both materials appear at higher cooling rates as a drop in the heat flow signal between 40 and 50 \({}^{\circ}\)C.
# Extracellular Vesicles for Regenerative Medicine Applications
## 3 Pre-Clinical Applications of EVs in Tissue Engineering and Regenerative Medicine
### Liver  
Unlike previously reviewed organ systems, the liver possesses a far greater innate ability for regeneration and repair. However, this regenerative capacity is not without limitations as liver disease and failure represent a significant burden on worldwide health. EVs represent a complementary strategy to the extensive approaches previously implemented in liver TERM. Applications of EVs in liver TERM have focused primarily on the use of hepatocyte and liver stem-cell derived EVs. Hepatocyte-derived EVs have been shown to increase hepatocyte proliferation, viability, and regeneration through the activation of stellate cells in the liver [97; 98; 99]. In addition, microvesicles derived from human liver stem cells have been shown to accelerate liver regeneration in hepatocellular rats through the means of EV-mediated RNA transfer to target hepatocytes [100].