esa-sceva/satcom-chunk-collection huggingface dataset:
# Integrity Analysis for GPS-Based Navigation of UAVs in Urban Environment
## 4 Discussion
If one of the three arguments (DOP, number of visible satellites and cut-off elevation) are outside of the boundaries, the integrity flag should be raised followed by the predefined mitigation measure. If the environment is known, the operational altitude of the UAV and the route can be defined before the flight in order to avoid exceeding the alert limits. If this happens anyway, UAV can ascend and decrease cut-off elevation to cope with potential GPS losses. If there is no chance to ascend because  
Figure 11: Determination of protection levels zones. Figure 12: Maps of achievable indirect protection levels (PLs) as functions of cut-off elevation and satellite visibility. Position error-based equivalents of DOP-based PLs are given in Table 7.  
of the mission requirements or environment limitations, alternative navigation sensors or systems must be activated to continue flight. Another point for discussion is how UAV acquires information for this type of integrity monitoring during the flight. Number of visible satellites and satellite elevations can be read from the broadcasted navigation message. As the cut-off elevation is dependent on both the height of buildings and altitude of UAV, it can be either estimated from visible satellite elevations or measured as the angle between UAV and the top of buildings. This can be done using additional sensor data or data extracted from an external source, such as a 3D map. Detection of this angle is out of the scope of this study but is included in the scope of future work. Suggested protection levels and operational zones will support path and mission planning either before or during the flight. Because of the variation of building heights in urban environments, transitions between the operational zones will be happening during the flight. Considering changes in urban environments, the most critical advantage of our approach against the direct usage of DOP is quick integrity update capabilities at low computational cost. Another important advantage of our approach is generality and time independency. DOP maps can be generated based on predicted DOP levels for known environments only, e.g., using scanned results. However, these maps are not available if the environment is not known or changed. DOP can also significantly change during the flight because of the movements of satellites; therefore, maps should be accounting for these changes too. The findings from the analysis of the impact of cut-off elevation and number of visible satellites on DOP coefficients are generic for any kind of urban air mobility application as these results are independent of the receiver model. However, the relationship between DOP and position error is dependent on the employed receiver model. It should be taken into account that equivalent horizontal and vertical position errors for specified DOP levels might change based on the receiver UERE.
# The Analysis of Experimental Deployment of IGLUNA 2019 Trans-Ice Longwave System
## 4 Transmitter Design  
The initial transmitter design was based on D-class H-bridge power MOSFET technology, similar to the design used in the Solec Kujawski Radio Transmitting Centre of the Polish Radio Program 1 (225 kHz; [18]). As the change to lower powers had been imposed, a new design was created, based on the C-class controlled carrier/A-class A3E-SC (analog double-sided amplitude-modulated telephony with suppressed carrier) single power MOSFET (ST Microelectronics, Geneva, Switzerland, STW20 NK50Z) transmitter [19], enclosed in a low temperature-protective casing, shown on Figure 11.  
Figure 10: The tangent of loss angle of the Glacier Palace ice in relation to the distance between the spike probes; the thick line represents the approximated exponential function, the open polygon shows the actual decrease of values for comparative purpose.  
Figure 9: The conductivity of the Glacier Paradise ice measured with increasing distance between the probes.  
Each transmitter had its own frequency generator, based on a digital switch operated in stable mode with adjustable RC circuit (adjustable air capacitor) and sockets for spike probes to measure the generated frequency. The bias voltage, changing the characteristic of the power amplifier to provide good linearity for AM, was fed by a set of built-in batteries (a similar battery pack powered the frequency generator). LF modulation signal entered the circuit through a mini-jack plug; the main power for the transmitter was provided by a laboratory power supply, mounted externally. The modulation was realized by a 6-watt modulation transformer. The antenna was coupled in-series to the final stage circuit (no antenna transformer).  
Each circuit was placed on a Styrodur base inside a plastic case. On the instrumentation panel three indicators were placed: to monitor the frequency generator voltage (as the digital switch could stop operating if the voltage dropped), the gate bias voltage and the transistor's temperature measured on the drain's heat sink. As the circuit board protruded outside the transmitter box, it was equipped with two different shields against the outside temperatures and mechanical shocks: industrial casted glass dome (meant for the Glacier Paradise transmitter) and an original Thermos tin box (meant for the surface transmitter). Both transmitters in operation are pictured on Figure 12.  
The on-site modulation control (by direct reception and demodulation) of the emitted AM signals on site was carried out using three types of mobile radio receivers, equipped with ferrite antennas for the LW range and tilted to comply with the transmitting antennas' polarization: Unitra Dana MOT 728-2 [20], Eltra Jowita 2 [21] and KUPZ/Tento Neywa 402 [22], with Jowita 2 proving best due to its high selectivity and sensitivity. Both Dana and Jowita were equipped with acoustic (after-demodulation) interfaces to microcontrollers of the 2.4-GHz system to collect telemetry and sensor data.  
Figure 11: The first specimen of the A/C-class low frequency transmitter used in IGLUNA 2019 field campaign.
## 8 Simulation Results
### Trade-Offs of Our Solution
The improvement of the light level prediction for application version 4 (multiple linear regression) decreased from 0.999752 to 0.974384 [Figure 18(a)] and the SSerr of the light increased from 0.000384 to 0.054342 [Figure 18(b)]. Figure 17: Improvement and SSerr of the prediction performed by application versions for the humidity variable ranging sample amount (Scenario #6A—ten samples, Scenario #6B—eight samples and Scenario #6C—six samples): **(a)** Improvement for humidity. **(b)** SSerr for humidity. Figure 18: Improvement and SSerr of the prediction performed by application versions for the light variable ranging sample amount (Scenario #6A—ten samples, Scenario #6B—eight samples and Scenario #6C—six samples): **(a)** Improvement for light. **(b)** SSerr for light. The results obtained from light variable prediction were different from the results obtained from humidity variable prediction. Then, we checked the behavior of the three gathered variables and used them in our performance evaluation. Figure 19 shows epochs from a data collection day where the correlation between the variables is low. Note that in epochs ranging from 3,550 to 4,900, the light variable increases a lot. Consequently, the simple and multiple linear regressions tend to worsen prediction accuracy. This explains some abnormal results when we used the light variable as independent variable.
# Upper-Bound Limit Analysis of Ultimate Pullout Capacity of Expanded Anchor Cable
## 3 Upper-Bound Solution of Ultimate Pullout Capacity of Expanded Anchor Cable
### Calculation Theory of Upper-Bound Theorem of Limit Analysis  
The upper-bound theorem of limit analysis was adopted to account for any failure mechanism with kinematic permission. Based on the virtual power theory, a reasonable upper-bound solution for the failure load of any failure model, which can be regarded as the upper limit of the actual ultimate load, can be obtained by equating the rate of work of the external force with the internal energy dissipation [24; 25; 26]. This reads as follows:  
\[\int_{A}T_{i}\dot{u_{i}}^{*}dA+\int_{v}F_{i}\dot{u_{i}}^{*}dv=\int_{A}\sigma_{ ij}\dot{e_{ij}}^{*}dv \tag{7}\]  
where \(T_{i}\) and \(F_{i}\) are the surface traction and physical force, respectively; \(\sigma_{ij}\) is the stress tensor; and \(\dot{u_{i}}^{*}\) and \(\dot{e_{ij}}^{*}\) are the virtual velocity and strain rate in the velocity field corresponding to the virtual failure model, respectively.  
In this study, the external forces were the weight of the soil included in the failure model and the weight of the expanded anchor cable, and the only source of internal energy dissipation was the soil deformation that occurred along the velocity discontinuity surfaces. The power calculation was divided into two regions (i.e., the logarithmic spiral region and the anchorage segment region), according to the different velocity fields presented in Section 2; then, the lateral resistance and end resistance could be computed, respectively.  
For each region, by equating the total rate of work carried out by the external forces with the total rate of internal energy dissipation on the velocity discontinuity surfaces, and by conducting several algebraic operations, the ultimate lateral resistance \(P_{1}\) and ultimate end resistance \(P_{2}\) were determined as follows:  
\[P_{1}=\frac{W_{1}+W_{G1}}{\dot{u}} \tag{8}\]  
\[P_{2}=\frac{\dot{W}_{D}+\dot{W}_{\gamma}}{\dot{u}} \tag{9}\]  
where \(P\) denotes the ultimate pullout capacity; \(\dot{u}\) denotes the axial velocity along the cable; \(W_{1}\) denotes the rate of internal energy dissipation of the anchorage segment region; \(W_{G1}\) denotes the rate of work carried out by the gravity of the anchorage segment; \(\dot{W}_{D}\) denotes the rate of internal energy dissipation of the velocity discontinuity in the logarithmic  
Figure 8: Idealized model for anchorage segment.  
spiral region; and \(\dot{W}_{\gamma}\) denotes the rate of work carried out by the gravity of the soil in the logarithmic spiral region.  
By summing \(P_{1}\) and \(P_{2}\), the ultimate pullout capacity of the expanded anchor cable could be obtained as follows:  
\[P=P_{1}+P_{2} \tag{10}\]
## 2 Materials and Methods
### Theory
matrix, \(B_{j,k}\)= {1,0} corresponding to the presence or absence of a link between \(j\) and \(k\) nodes. The choice of the cut-off value, which is a parameter of the model to be determined from experiments, describes the degree of electrical connection of the graph. For the calculations of the electrical properties, each link is interpreted as a channel for charge transfer whose impedance \(Z_{j,k}\) is taken to be a function of the geometry, of the link resistivity, \(\rho\), and of the intrinsic polarizability \(\varepsilon_{j,k}\) of \(j\), \(k\) amino acids as in [24,25]  
\[Z_{j,k}=\frac{l_{j,k}}{A_{j,k}\big{(}\rho^{-1}+i\varepsilon_{j,k}\varepsilon_{0 }\omega\big{)}} \tag{1}\]  
where  
\[A_{j,k}=\frac{\pi\big{(}D^{2}-l_{j,k}{}^{2}\big{)}}{4} \tag{2}\]  
is the cross-sectional area shared by the labeled amino acids, \(\varepsilon_{0}\) the vacuum dielectric constant, \(\omega\) the angular frequency and \(i\) the imaginary unit. By adopting the simplest parameter model, the value of \(\rho\) is taken to be the same for all the links, unless differently specified in the following. In this way, the tertiary structure and the interaction radius are the only relevant input parameters of the theory. The resulting impedance network preserves the features of the protein that are relevant for calculations, i.e., the amino acid positions and their electrical properties. By using Kirchhoff laws, the charge transfer inside the network is described by a set of linear equations that are solved by a standard numerical procedure. The solution so obtained provides the electrical response of the network in terms of its local currents and voltage drops, its global impedance and/or its steady-state \(I\)-\(V\) characteristics. We remark that different 3D structures produce different electrical outputs which can be compared with what was found in experiments performed in dark and in light on some opsins i.e., bacteriorhodopsin, bR, or proteorhodopsin, pR [15,16,23]. There, a marked difference of the electrical characteristics was observed because of the conformational change induced by the presence of light or other specific ligands [14,25,26,27,28,29].
## 4 Case Study
### Sensitivity Analysis
Figure 7: The result of the relationship between the weight of missed time windows and the profit and total route distance under a fixed shortest route weight. maintain customer satisfaction. With the results of this study, we can explain the situation of the logistics service provider. 1. The logistics service providers decided to increase the weight of customer satisfaction to achieve the least missed time windows. Because the time window of the request around the logistics center does not have a fixed changing trend, the shortest route distance will constantly fluctuate. 2. While increasing the weight of the shortest route can decrease the missed time windows, it will lower the profit at the same time. The logistics service providers will only receive a new request that is near the logistic center. 3. The profit and total route distance increase along with the increased missed time window weight. This is mean that the logistics service provider can receive the new request when the customer can accept a delay in their request. Finally, we changed the maximum load capacity, the total flight time, the speed, and the carrying capacity of the UAV to explore the relationship with profit. The study found that most of the changes in UAVs setting had no influence, but changing the load of the UAV can be an influencing factor in the sales and total profit of the UAV, because logistics operators can receive more requests, which are related to customers. We can discuss that the customer is a key factor in the logistics decision-making platform, not the provider investment.
# Analysis and Design of Single-Phase Unidirectional Transducers with High Directivity
## 1 Introduction  
Single-phase unidirectional transducers (SPUDT) are frequently employed in surface acoustic wave (SAW) devices to reduce bidirectional loss and to suppress triple transit echo [1, 2, 3, 4]. Meanwhile, it is found that strengthening the unidirectionality is an effective way to suppress insertion loss. As is known, the SPUDT cells are the base elements of SPUDT. DART [5], electrode-width-controlled (EWC) [6], and other SPUDT cells [7, 8] are the best-known cell types, of which the EWC-SPUDT is the most widely used. As shown in Figure 1, a traditional EWC-SPUDT cell consists of three fingers, two narrow electrodes, and one wide electrode, whose widths are \(\lambda/8\) and \(\lambda/4\), respectively. \(\lambda\) is the electric period of the gratings. The distance between the two narrow finger is \(\lambda/8\), and that between the narrow finger and the wide finger is \(3\lambda/16\). In order to describe its performance, the following two parameters are listed: the reflectivity \(|\kappa|\lambda\), and the unidirectional angle \(\theta\), which is defined as \(\theta=\varphi_{\kappa}-2\varphi_{\alpha}\), where \(\varphi_{\kappa}\) and \(\varphi_{\alpha}\) are the phases of reflection coefficient and transduction, respectively [9]. According to our calculation of a traditional EWC-SPUDT cell, \(|\kappa|\lambda\) is 1.37% and \(\theta\) is \(-83.58^{\circ}\), which are very close to the results presented in [10].  
[PERSON] et al. utilized finite element method (FEM) and spectral domain analysis (SDA) to analyze the SAW propagation characteristics under a type of triple electrodes grating (an improved EWC-SPUDT), but they failed to find how the geometric structure influences its unidirectionality and how to optimize its structure [11]. [PERSON] et al. studied the optimal design of the three fingers, including their position and width, using the periodical [PERSON]'s function method, but they did not explicate the influence of these parameters on the reflectivity and unidirectional angle [10]. [PERSON] and [PERSON] chose Cu electrodes instead of Al electrodes to achieve greater mechanical reflection [12; 13] since the density of Cu is greater than that of Al; however, they neglected the fact that the electrical and mechanical reflection caused by short-circuited gratings consisting of either Cu or Al on 128\({}^{\circ}\) YX-LiNbO\({}_{3}\) substrate are opposite and cancel each other.  
The purpose of this paper is to enhance the unidirectionality of the EWC-SPUDT and further reduce its insertion loss by improving the reflection characteristics of the transducer as much as possible, based on the premise that the minimum width of the electrodes is limited and the unidirectional angle is \(-90^{\circ}\). In addition, the design principles of EWC-SPUDT are discussed theoretically and experimentally.
# Comparison of Analytical Methods for Determining Methylesterification and Acetylation of Pectin
## 2 Materials and Methods
### Preparation of Pectin Standards with Different DM  
CP (10 g) was saponified with 0.1 M NaOH (400 mL, PH \(\approx\) 13) at 4 \({}^{\circ}\)C to remove methyl and acetyl groups. The de-esterified CP (5 g) was then hydrolyzed with 0.5 M HCl (500 mL, PH \(\approx\) 0.3) at 80 \({}^{\circ}\)C for 5 h. After centrifugation (15,000\(\times\)\(g\), 20 min), the acid-soluble and acid-insoluble fractions were separated. The insoluble material, which mainly contained HG, was suspended in water and solubilized by gradually increasing the pH to \(\sim\)7 with 0.2 M NaOH. The solution was desalted by hollow fiber membrane (MWCO 3 KDa) and freeze-dried to give the purified non-esterified HG domain (CP-HG). The CP-HG (5 g) was suspended in 2 M methanol-sulfate solution (200 mL). After stirring at 4 \({}^{\circ}\)C for 4 days, methylesterification of carboxyl group of GalA was complete. The pectin was collected and washed twice with methanol, and then with methanol-water (3:1) to remove H\({}_{2}\)SO\({}_{4}\)[27]. This high methyl-esterified pectin was termed CP-HM-HG. Pectin standards with different DM levels were prepared by mixing CP-HG and CP-HM-HG in different proportions.
# High-Performance QC-LDPC Code Co-Processing Approach and VLSI Architecture for Wi-Fi 6
## 2 Decoding Process and Parameters Calculation of the Decoder
### Co-Processing Parameter Calculation
#### 2.2.1 Calculate the Real Number of Symbols \(N_{sym}\) and the Number of Available  
Bits \(N_{subits}\)  
For the reception, the \(N_{SYM}\) needs to be computed through the following three steps. Firstly, the received symbol duration \(RXTIME\) is first calculated based on the L-LENGTH in the L-SIG field:  
\[RXTIME(us)=\left\lceil\frac{L_{\_}LENGTH+3}{3}\right\rceil\bullet 4+20 \tag{1}\]  
Secondly, the proper duration of the DF is obtained according to the total symbol duration and time of other fixed fields. Then, it can be divided by the period of the individual symbols \(T_{\_}{sym}\) to convey the symbol of the DF field \(N^{\prime}_{\_}{SYM}\).  
\[N^{\prime}_{\_}{SYM}=\left\lfloor\frac{RXTIME-T_{\_}{other\_}{fields}}{T_{\_}{ sym}}\right\rfloor \tag{2}\]  
Taking the usage of space-time block code (STBC) and extra symbol (ES) into account, the number of symbols for proper LDPC decoding \(N_{\_}{SYM}\) is finally obtained according to Equation (3).  
\[N_{\_}{SYM}=\begin{cases}N^{\prime}_{\_}{SYM}&\text{ES}=0\\ N^{\prime}_{\_}{SYM}-1&\text{ES}=1,\text{ STBC}=0\\ N^{\prime}_{\_}{SYM}-2&\text{ES}=1,\text{ STBC}=1\end{cases} \tag{3}\]  
Finally, according to the number of symbols \(N_{\_}{SYM}\), the number of bits in the PSDU and SERVICE field \(N_{\_}{pid}\) and the number of available bits \(N_{\_}{subits}\) carried by the symbols can be calculated.  
\[N_{\_}{subits}=N_{\_}{pld}=N_{\_}{sym}\times N_{\_}{deps} \tag{4}\]
## 2 Materials and Methods
### Data Processing and Statistical Analysis
#### 2.5.3 Description of the GPP-SIF Relationship and Model Evaluation  
The relationship between GPP and SIF within a daily cycle was described by a logarithmic regression model in the form of \"GPP = K \(\times\) ln(SIF) + b\". Here, K represents the regression coefficient, which reflects the sensitivity of GPP to various levels of SIF; R\({}^{2}\) is the coefficient of determination, indicating the explanatory power of SIF for GPP. For the physiological relationship between GPP and SIF (LUE-\(\Phi\)F), a univariate quadratic equation was used for regression, and the coefficient of determination (R\({}^{2}\)) was employed to characterize the LUE-\(\Phi\)F relationship. The coefficient of determination (R\({}^{2}\)) and root mean square error (RMSE) served as quality indicators for GPP estimation models based on SIF and were used to evaluate the model performance.
# Bio-Inspired Aerodynamic Noise Control: A Bibliographic Review
## 3 Leading Edge Serrations
### Aeroacoustic Performance of Leading Edge Serrations  
Theoretical, experimental and numerical studies (see Table 3) in the past have shown that leading edge serrations (with appropriate geometrical properties) is an effective technique to reduce noise emission [43], either laminar boundary layer instability tonal noise (trailing edge self-noise) in smooth inflow or turbulence-leading edge interaction noise in turbulent flow.  
Figure 4: Schematic of the leading edge serrations showing the parameters of wavelength \(\lambda\) and amplitude \(h\): (**a**) sawtooth serrations; and (**b**) sinusoidal serrations.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c} \hline
**Year** & **Author(s)** & **Type** & **Inflow** & **Bionic Ojo(c)** & \(\mathbf{R_{e}}\) **(10\({}^{\circ}\))** & **AoA (C)** & \(\mathbf{H/\alpha_{0}}\) **(\%)** & \(\mathbf{A/\alpha_{0}}\) **(\%)** & \(\mathbf{\lambda/H}\) \\ \hline
1971 & Hersh and Hayden [44] & Sawtooth & Smooth & NACA 0012 airfoil & 2 to 3.33 & 0 to 16 & 0.27, 0.54, 0.84, 1.11 & 0.55, 106, 1.66, 2.22 & 2 \\  & & & Two-blood propeller & 0.83 to 3.33 & & 0.74, 17.0 & 1.55, 3.34 & 2 \\ \hline
1972 & Amdt and Nagel [45] & Sawtooth & Smooth & Two-blood rotor & - & 3.13, 0.25 & 125, 18.75 & 3.4 \\ \hline
1973 & [PERSON] [46] & Sawtooth & Smooth & Small-scale rotor & 1.83 to 5.5 & 4, 8, 10.12 & 3.58, 10.87 & - &... \\  & & & Large-scale rotor & 9.94 to 31.8 & 6, 12, 18 & 0.61, 117, 2.39, 3.00 & 1.17, 141, 2.39 & 0.5, 1.2 \\ \hline
2010 & [PERSON] et al. [47] & Sinusoidal & Smooth & NACA 0021 airfoil & 1.2 & 0 to 12 & 2.86, 571, 11.43 & 10.71, 21.43, 42.86, 857, 1.88, 375, 75, 15 \\ \hline
2011 & [PERSON] et al. [48] & Sinusoidal & Turbulent & NACA 05-(1210) airfoil & 2, 4, 6 & 0, 5, 10, 15 & 6.67, 10 & 4, 6.67 & 0.6, 1.067 \\ \hline
2013 & [PERSON] et al. [46] & Sinusoidal & Turbulent & NACA 0012 airfoil & 1.3 to 2 & 0, 10 & 12 & 10 & 0.83 \\ \hline  & & & & & & & 0.1, 0.13, 0.17, 0.2, 0.25, & 0.3, 0.33, 0.38, 0.4, 0.5, & 0.3, 0.3, 0.3