esa-sceva/satcom-chunk-collection huggingface dataset:
# Constrained Optimization of FPGA Design for Spaceborne InSAR Processing
## 5 Experimental Results and Discussion
### Verification and Comparison of System Performances  
This section verifies the system performance from the perspective of accuracy and efficiency. Figure 11: \(\
abla G\) of matrix transposition schemes under the condition of \(a^{\prime}\). Figure 10: \(\
abla G\) of matrix transposition schemes under the condition of \(d^{\prime}\). By comparing the measured results with the theoretical value, the accuracy verification calculates the absolute and relative errors, as shown in Table 11. The absolute error of phase and coherence coefficient was less than 2 \(\times\) 10\({}^{-7}\), and the relative error was less than 5 \(\times\) 10\({}^{-3}\), which showed that the FPGA balanced design proposed in this paper had realized the expected algorithm with high precision. As for efficiency verification, we listed the different processing capacities of different threads to find the range of system processing capacity. Then, the processing capacity was expressed as the throughput, which would be compared with the existing research. The Formula of throughput is \(B=D/T\). \(D\) is the number of data points, and \(T\) is the entire calculation time. The throughput index \(B\) represents how fast data points are processed, so it could be a yardstick to measure the processing capacity. In terms of efficiency verification, we compared the performance of FPGA with central processors like DSP and GPU in coarse registration and interferogram generation. The experimental results are shown in Table 11. Based on the dual-channel storage structure, when the thread of the interferogram generation was 8 and the FPGA working clock was 100 MHz, the throughput of FPGA could reach 407.46 \(\times\) 10\({}^{6}\) points/s, which exceeded 386.32 \(\times\) 10\({}^{6}\) points/s of the NVIDIA GTX Titan Black GPU. When the thread of interferogram generation was 1, the throughput could reach 94.52 \(\times\) 10\({}^{6}\) points/s, which was still far beyond the processing capacity of DSP. Notably, fetching data discontinuously in the calculation process would hamper the data transfer rate of DSP/GPU, which would, in turn, affect the throughput. However, the proposed specialized structure could reduce data transfer loss of FPGA. Thus, the proposed FPGA structure had advantages in the computationally intensive process of InSAR, compared with GPU and DSP. We have pointed out that when the thread of the generated interferogram was 8, the thread of coarse registration as 1 was the balanced design. At this time, our FPGA took at least 9.24 ms to finish the coarse registration as the scheme \(g^{\prime}\). The slowest scheme took 39.75 ms as \(j^{\prime}\). The scheme \(h^{\prime}\) took 11. 16 ms as the optimum trade-off, which only increased the entire time by 1.1% but reduced the FPGA BRAM usage by 8.7%. The throughput is shown in Table 11. DSP processed an image with 512 \(\times\) 512 points in 7.182 ms, demonstrating a slight advantage over FPGA. To process a 2048 \(\times\) 2048 image,
## 4 Non-Ischemic Heart Diseases
### Hypertrophic Cardiomyopathy  
Hyertrophic cardiomyopathy (HCM) is a prevalent genetic heart condition distinguished by left ventricular hypertrophy without any other systemic or cardiac ailment capable of inducing a similar level of hypertrophy. The evaluation of myocardial fibrosis in HCM is crucial for risk stratification and prognosis prediction. The guidelines from the American Heart Association and the American College of Cardiology for the diagnosis and treatment of patients with HCM emphasized the incorporation of extensive LGE as a risk factor in stratifying the risk of sudden cardiac death. They also suggested using LGE as a criterion to assist in selecting patients for implantable cardioverter-defibrillator placement [39]. The basal to mid-interventricular septum (especially at the right ventricular insertion site) and anterior wall emerged as the most frequent sites for LGE [40]. The effectiveness and reliability of LIE-CT in assessing coronary artery disease and myocardial fibrosis in patients with HCM have been explored by [PERSON] et al. They compared LIE-CT's performance with that of CMR imaging and coronary angiography. Their findings unveiled a robust correlation between wall thickness measurements obtained from LIE-CT and those from CMR (r = 0.91). Furthermore, LIE-CT and LGE-CMR exhibited significant concordance in identifying myocardial fibrosis, with the typical pattern (patchy intramyocardial fibrosis at the right ventricular insertion site) [41]. This study showed the potential of LIE-CT as a robust alternative to LGE-CMR in evaluating myocardial fibrosis in HCM patients, especially those with contraindications to CMR imaging. The main limitations concerned diffuse myocardial LIE, which was not detected by CT due to poor contrast between the enhanced myocardium and normal myocardium.
## 7 Results and Discussion
From Figure 15, it is evident that the BS in the HTCCR protocol receives an increased number of 'C1' and 'C2' RT packets compared with 'C3' and 'C4' NRT packets. It offers an increased speed of packet delivery and is suitable for diverse classes of traffic. The average throughput of RT is 10.4% better when compared with NRT when the network is highly congested. Packets that do not reach the threshold involve a lower number of hops and hence less delay. The throughput of 'C1' is the maximum, while 'C2' involves the least delay compared with other traffic. Though 'C2' involves less delay, its throughput is reduced as reliability is not considered. Figure 14: End-to-End Delay for Varying Traffic Rates. Figure 13: Routing Overhead for Varying Percentage of Malicious Nodes.
## 5 Regulation Test of Facility
### Adjustment Test of the Temperature and Humidity Control System
#### 5.2.2 Adjustment Test of Humidity Control System
The longest time needed for the humidity to reach the set value is 80 min. After the humidity reaches the set value, the constant humidity can be maintained for a long enough time \(t_{\text{m}H}\) (between 13.67 min and 90 min). The results given in the table are only a segment of time recorded in the adjustment test. It is believed that the humidity will be kept constant longer if record is continued. This constant-humidity maintaining time is sufficient enough to carry out calibration operation under the set temperature and set humidity. Figure 16: Variation history of eight humidities and their average in control process from 57.1%RH to 80%RH under 40 \({}^{\circ}\)C. \begin{table}
\begin{tabular}{c c c c c c} \hline \(\boldsymbol{T_{\text{set}}}\) (\({}^{\circ}\)C) & \(\boldsymbol{H_{\text{set}}}\) (\%RH) & \(\boldsymbol{H_{\text{ini}}}\) (\%RH) & \(\boldsymbol{H_{\text{avg}}}\) (\%RH) & \(\boldsymbol{t_{\text{r}H}}\) (min) & \(\boldsymbol{t_{\text{m},H}}\) (min) \\ \hline
21.5 & 20 & 42.7 & 20.9 \(\pm\) 0.8 & 35.17 & 16.92 \\
21.5 & 60 & 24 & 60.1 \(\pm\) 0.2 & 23.33 & 25 \\
21.5 & 80 & 59.6 & 79.8 \(\pm\) 0.5 & 20.67 & 34.33 \\
30 & 20 & 58.5 & 20.6 \(\pm\) 1.7 & 10 & 90 \\
30 & 60 & 19.2 & 60.3 \(\pm\) 0.4 & 16.67 & 28.33 \\
30 & 80 & 60 & 80.2 \(\pm\) 0.3 & 9.67 & 22.83 \\
40 & 20 & 77.9 & 19.9 \(\pm\) 0.3 & 11.33 & 13.67 \\
40 & 60 & 35.5 & 59.7 \(\pm\) 0.3 & 80 & 23.67 \\
40 & 80 & 57.1 & 79.8 \(\pm\) 0.3 & 22.17 & 22.83 \\ \hline \end{tabular}
\end{table} 
Table 8: Time required to reach the set humidity and time in which humidity can be maintained constant. Table 9 lists the spatial distribution characteristics of the humidity the moment when the humidities at eight points and their average reached the set value in accordance with the design target error criterion \(\mid\!H-H_{\text{set}}\!\mid\)! 4%RH. As can be seen from the table, only at \(T_{\text{set}}\) = 30 \({}^{\circ}\)C, when the humidity is regulated from 58.5%RH to 20%RH, \(\mid\!H_{i}-H_{\text{avg}}\!\mid\!_{\text{max}}\) has a maximum value 2.3%RH (<4%RH), and in the other cases \(\mid\!H_{i}-H_{\text{avg}}\!\mid\!_{\text{max}}\) ranges from 0.8%RH to 1.3%RH, while all \(\sigma_{H}\) are within a range of 0.0935%RH to 0.8474%RH, indicating that the uniformity of the humidity field is good. From the perspective of all \(\mid\!H_{i}-H_{\text{set}}\!\mid\!_{\text{max}}\leq\) 2.9%RH < 4%RH, the humidities of the eight points all meet the control accuracy design target of 4%RH.
## 1 Introduction
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt}} \hline \hline
**Component CAS No./EC No.** & **Characteristics** \\ \hline Alanine 56-41-7/200-273-8 & Important source of energy for muscle tissue, the brain and central nervous system; strengthens the production of antibodies in the immune system, supports the metabolism of sugars and organic acids [31]. \\ \hline Argin 74-79-3/200-811-1 & Conditionally essential amino acid that improves immune responses to bacteria, viruses, and tumor cells, promotes wound healing and regeneration of the liver, stimulates the release of growth hormones, and is considered crucial for optimal muscle growth and tissue repair [32]. \\ \hline Aspartic acid 56-84-8/200-291-6 & This amino acid serves as a precursor for the synthesis of proteins, oligopeptides, purines, pyrimidines, nucleic acids, and L-arginine. L-aspartate is a glycogen amino acid, and it can also promote energy production via its metabolism in the Krebs cycle [33]. \\ \hline Biotin 58-85-5/200-399-3 & Vitamin B7, vitamin H, involved in a wide range of metabolic processes related to the utilization of fats, carbohydrates, and amino acids [34]. \\ \hline Calcium 7440-70-2/231-179-5 & An electrolyte and structural element that plays an important role in signal transduction pathways, where it acts as a second messenger in the release of neurotransmitters from neurons, contraction of all types of muscle cells, and fertilization [35]. \\ \hline Collagen 9007-34-5/- & Major structural protein, constitutes about one-third of the total protein in mammals [36]. \\ \hline Copper 7440-50-8/231-159-6 & Microelement incorporated into many enzymes throughout the body as an essential part of their function [37]. \\ \hline Cystine 56-89-3/200-296-3 & Pivotal for the proper utilization of vitamin B6. Increases glutathione levels in the lungs, liver, kidneys, and bone marrow, may have anti-aging effects on the body by reducing age spots, etc. [38]. \\ \hline Cystine aminopeptidase or (CAP, oxytocinase) & The physiological role of oxytocinase or CAP in pregnancy and the factors associated with increased CAP activity during pregnancy are currently unknown. A common hypothesis regarding the physiological role is that this enzyme regulates oxytocin levels in pregnancy serum and may prevent preterm labor [39]. \\ \hline Diamine oxidase (DAO) & Histamine-degrading enzyme produced in high amounts by the placenta, supposedly acts as a metabolic barrier to prevent excessive entry of bioactive histamine from the placenta into the maternal or fetal circulation [40]. \\ \hline Estradiol 50-28-2/200-023-8 & Female sex hormone, an estrogen. Estrogens stimulate the female reproductive organs and the development of secondary female sex characteristics. Stimulation of estrogen receptors present in keratinocytes and skin fibroblasts helps in maintaining skin firmness and elasticity and inhibits sebum production [41]. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Overview of biologically active substances in placenta ([24; 25; 26; 27; 28; 29; 30], further sources cited in the table).
## 4 Proposed Metrics
### Simulation Environment
If there is no route to that destination in its cache, it is time to start the route discovery mechanism to dynamically find a new route to the destination node. First, the source node sends an RREQ broadcast \begin{table}
\begin{tabular}{l c} \hline \hline
**Parameter** & **Value** \\ \hline Maximum data rate & 250 kbps \\ Discovery packet time & 10 s \\ Receiver sensitivity & \(-85\) dBm \\ Average frame length & 22 Bytes \\ MAC layer & CSMA/CA \\ Maximum number of backoffs & 4 \\ Packet loss & 1\% \\ Scenario & Static \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters for the tested scenarios. packet, which contains the identifier of the source node and that of the destination node, whose route is to be discovered; it also contains a unique identifier for the RREQ. Each intermediate node makes a copy of the received RREQ and adds its identifier. When a node receives an RREQ, it first looks in its cache to find out if it has the route to the destination node. If so, the node responds with an RREP to the source instead of forwarding the RREQ. In that RREP, the node writes all of the nodes that the received RREQ has passed through and the nodes of the route found in its cache. If the node does not find a route in its cache, it adds its address in the packet and forwards it via broadcast. Once the source node receives the RREP, it stores the route in its cache. This route will be included in the header of each subsequent packet that the node sends, so that all nodes that receive the packet will know to which next node they should resend. As with AODV, nodes can have multiple routes to a destination and choose, for example, those with the lowest hop count. Routing with ZTR is established based on parent-child links. The coordinator node is responsible for creating the network configuration, choosing the parameters and setting the maximum depth of the tree network. Nodes maintain their address information from their parent and child nodes. To send a packet in this rooted tree scheme, a node observes, based on the destination address, if it is a downward path; if so, it sends it to one of its children; otherwise, the node sends it to its parent [1]. In order to evaluate the protocols performance, the authors use an event-driven network simulator with 1% of packet loss in all the physical layer links. The MAC layer is constructed under the mechanism of non-persistent unslotted CSMA/CA [33], established by the IEEE 802.15.4/ZigBee standard, with the collision avoidance model and retransmissions. The network layer was tested with routing protocol implementations, such as AODV, DSR, the ZTR algorithm and our own protocol, MPH.
# Gap Analysis of Ambient Electromagnetic Noise Measurements Stored in the ITU Data Banks
## 4 Discussion and Recommendation
### Impact of Insufficient Geographical Coverage  
Table 1 and Figure 2 show that all measurements are in rich and highly industrialized countries, and none is in Lower and Middel Income Countries (LMIC). Therefore, if these data would be used as sole input to derive an empirical radio noise model, a strong bias towards rich, industrialized countries may be expected. This would no be a problem if the man-made noise situation in these countries could be thought representative for the entire world. However, several important parameters that influence the local man-made noise level may differ significantly between these countries and e.g., LMIC. Especially the difference in equipment quality, the electromagnetic compatibility (EMC) regime and its enforcement, the electromagnetic shielding of buildings (wall attenuation) [16] and the unwanted transmission via electricity wiring. But also when regarding other countries, the influence of people density and distribution, equipment density per dwelling is not expected to be negligible.  
Table 1 reveals that 80% of the measurements is done in Japan. Therefore, if all measurements would be processed without differentiating between the data sets of the  
Figure 8: Spectral distribution of the man-made noise measurements per country. Red dots show the frequencies at which measurement data are in the Radio Noise Data Bank.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline
**Country** & **REMR** & **RURL** & **RESD** & **CITY** & **URBN** & **INDA** & **ROAD** & **OFFC** & **Other** \\ \hline Spain & 1 & & & & & & & & \\ UK & 2 & 2 & 2 & 2 & 2 & 2 & 2 & \\ USA & & & & 3 & 2 & & & & \\ \hline \end{tabular}
\end{table}
Table 5: _Cont._  
Figure 9: Temporal distribution of the man-made noise measurements per country.  
individual countries, the Japanese radio noise environment would have a dominant influence on the empirical model. In fact--if we ignored the limited spectral coverage, which will be discussed later--the model would predict the radio noise environment in Japan, not that of the rest of the world. Of course, this is not the goal of the model.  
As Figures 3-7 show, the distribution of measurement locations each the countries also differs in quality. The geographical spread of the measurement locations is especially poor in Spain and in the USA. If we look at the number of measurement locations regardless of the country, Germany is overrepresented (79%), see Table 1. Therefore, if we would not take individual measurements but measurement locations as a basis--e.g., because of measurements at multiple frequencies in each location--the data of Germany would become dominant.
# Comparison of Heuristic Algorithms in Discrete Search and Surveillance Tasks Using Aerial Swarms
## 1 Introduction
### Search Patterns
Therefore, no absolute search performance metric is provided, and these behaviors are compared by only considering the time needed to complete the mission. Monte Carlo simulations are run varying the number of agents and targets. There have been many works in which the task is solved by partitioning the area and assigning individually those partitions to the agents. For instance, in [22], each partition is filled with zig-zag lanes, computed to be energetically efficient. However, the algorithm requires that the area is a polygon on whose boundaries the UAVs must be initially placed, restricting the initial positions. Making use of the probability that a target is located in a specific cell in [23], scores are assigned to each one, taking also into account forbidden flying zones and areas that should be avoided if possible. The scores are updated either externally or because of the findings of the agents. The agents select the cell to visit depending on that score. In this work, the area is partitioned using a Voronoi diagram, and the results are compared with other algorithms:* Lawn mower: Each agent moves in a straight line, and when it encounters an obstacle, it turns to head in a clear direction. * Raster scan: The agents move in parallel lanes north/south or east/west. * Gradient climb: This is a greedy algorithm based on the surrounding cell scores. * Randomized Voronoi: The area is partitioned with the Voronoi diagram using the agent's position as the generators. * Full algorithm: This is the same algorithm, developed in previous works, but without the Voronoi partitioning. The algorithms are compared using as a performance measurement the mean cell scores, computed along 20 runs, the most efficient algorithm being the one proposed in the work. This result seems reasonable, since the performance is measured using the same score on which the algorithm is based.
## 2 Experimental Section
### Synthesis of 1-Butyl-3-(3-trimethoxysilpropyl)-1H-imidazol-3-ium chloride [34]  
Thirty-five milliliters (192 mmol) of (3-chloropropyl)trimethoxysilane and 25.2 mL (192 mmol) of 1-butylimidazole were heated under N\({}_{2}\) at 120 \({}^{\circ}\)C. The progress of the reaction was monitored by \({}^{1}\)H NMR, and the reaction was completed after 8 h. The mixture was cooled to room temperature and 60.4 g of honey-like, orange viscous liquid was obtained (97% yield). \({}^{1}\)H NMR (300 MHz, CDCl\({}_{3}\)): \(\delta\) 0.616-0.672 (m, 2H), 0.967 (t, \(J=7.5\) Hz, 3H), 1.352 (dt, \(J=8.1\) Hz, 2H), 1.872-2.075 (m, 4H), 3.571 (s, 9H), 4.334 (dt, \(J=4.2\) Hz, 4H), 7.45 (t, \(J=1.2\) Hz, 1H), 7.568 (t, \(J=1.8\) Hz, 1H), 10.796 (s, 1H). \({}^{13}\)C NMR (300 MHz, CDCl\({}_{3}\)): \(\delta\) 5.94, 13.48, 19.51, 24.21, 32.21, 49.79, 50.75, 51.7, 121.91, 122.07, 137.84. IR (cm\({}^{-1}\)): 3128, 3044, 2943, 2843, 1560. Elemental Analysis: calculated for C\({}_{13}\)H\({}_{27}\)ClN\({}_{2}\)O\({}_{3}\)Si, C: 48.35, H: 8.43, N: 8.68; found C: 48.78, H: 8.78, N: 9.05.  
Procedure for Supporting 1-Butyl-3-(3-trimethoxysilpropyl)-1H-imidazol-3-ium Chloride on Magnetic Nanoparticles [34]  
Eleven point six grams of FeCl\({}_{3}\cdot\)6H\({}_{2}\)O and 4.3 g of FeCl\({}_{2}\cdot\)4H\({}_{2}\)O were mixed in 400 mL of degassed water. The mixture was heated at 85 \({}^{\circ}\)C, and then 15 mL of concentrated ammonia (28%) were added quickly. The heating was continued for another 30 min. After cooling to room temperature, the solution was decanted and the black precipitate was washed five times with 200 mL water. The black magnetite nanoparticles were suspended in 500 mL of ethanol (95%) and sonicated for 60 min. The resulted suspension was mechanically stirred and a solution of 100 mL ethanol (95%) containing 30 mmol of 1-butyl-3-(3-trimethoxysilpropyl)-1\(H\)-imidazol-3-ium chloride and 2 mL of concentrated ammonia (28%) were added. Stirring under N\({}_{2}\) was continued for 36 h. The modified magnetite nanoparticles were magnetically separated and washed three times with 100 mL of ethanol (95%) and then dissolved in 400 mL of methanol and stirred mechanically for 30 min. One hundred milliliters of ether were added and the modified nanoparticles were magnetically separated, washed with 100 mL of ether and dried under a vacuum of 0.2 mmHg for 24 h. Typically, 6-6.5 g of brownish-black powder could be obtained.
## 3 Results and Discussion
### Films Characterization
#### 3.1.5 ATR-FTIR Analysis  
The spectrum of neat PCL showed several characteristic bands around 3450, 2943, 2866, 1724, 1470, 1365, 1180, 1102 and 1045 cm\({}^{-1}\); in agreement with previous studies [24; 56]. Similar bands were found in PCL/ASE films and no significant differences in peaks frequency were observed with the presence of ASE. However, some increase in the absorbance value of the band appearing at 3450 cm\({}^{-1}\) was observed for PCL6 compared to neat PCL (\(0.024\pm 0.005\) to \(0.019\pm 0.006\), respectively), which was related to the O-H stretching vibration of hydroxyl groups present in the matrix due to ASE composition [57] (Figure S2). As a result, the availability of OH groups inside the polymer network due to ASE intermingling with PCL was changed [45]. In general, the obtained results suggest that there were no significant chemical bonding between the polymer matrix and ASE, in accordance with previous morphological, mechanical and barrier findings.