esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 System Architecture  
### Mechanical Design  
The proposed proof-of-concept machine has as its main design characteristics reliability, cost efficiency, modularity, and short-time measurements; it is shown in Figure 4.  
The machine consists basically of a 3D Cartesian robot that moves two sets of measurement electrodes (electrical and ultrasonic) along the X-Y-Z coordinates.  
To ensure quick 3D movements of the electrodes, without undesirable vibrations, the moving system is assembled on a sturdy base with an outer structure.  
The \(X\)-axis is performed by an electric linear actuator, SMC LEFS32A-700 R5 CP18, [11], with a high-precision ball screw and a moving car, reaching a positioning precision of 0.02 mm. Figure 5 shows a detailed view of the X-DOF.  
The \(Z\)-axis is performed by an electric linear rod actuator, SMC LEF32 DB-450 BF-R5 CP18 [12], with a positioning precision of 0.02 mm. To ensure total alignment, the actuator is constrained by two more vertical Misumi SX2 RL28 linear bearing guides [14]. To perform the fine search of the stone surface, along Z, an ultrasonic digital limit sensor Telemecanique XX512A1 KAM8 [17] is used. Figure 6 shows a detailed view of the Z-DOF.  
Figure 4: Proof of concept—automatic machine. 1-Linear Actuator SMC LEFS32A-700 R5 CP18 [11]; 2-Linear Actuator SMC LEF32 DB-450 BF-R5 CP18 [12]; 3-Linear Actuator SMC LEFS6 RJ-75S-R5 CP18 [13]; 4-Linear Bearing Guide MISUMI SX2 RL28 [14]; 5-Ultrasonic kHz Transducer [15]; 6-Metallic Electrodes; 7-Bosch 45 \(\times\) 45 Structural Profiles; 8-Inductive Digital Sensors, Telemecanique XS612B2 PAL01M12 [16]; 9-Ultrasonic Digital Sensor Telemecanique XX512A1 KAM8 [17].  
Figure 5: X-DOF. 1-Linear Actuator SMC LEFS32A-700 R5 CP18 [11]; 2-Linear Bearing Guide MISUMI SX2 RL28 [14]; 3-Inductive Digital Sensors, Telemecanique X5612B2 PAL01M12 [16].  
Figure 6: Z-DOF. 1-Linear Actuator SMC LEF332 DB-450 BF-R5 CP18 [12]; 2-Linear Bearing Guide MISUMI SX2 RL28 [14]; 3-Metallic Electrodes.  
The \(Y\)-axis moves the ultrasonic sensors and is implemented by a short linear electric actuator SMC LES16 RJ-75S-R5 CP18 [14] and its symmetric SMC LES16 LJ-75S-R5 CP18 [18]. They have a short motion range and can achieve a positioning precision of 0.05 mm, being ideal for making the ultrasonic transducers contact with the block and back away to avoid damage without interfering with the system.  
Finally, four inductive digital limit sensors, Telemecanique XS612B2 PAL01M12 [16], are used to perform the home and to limit the linear actuators X and Z. Figure 7 shows a detailed view of the Y-DOF.
## 4 Results of the Sensitivity Analysis to Setup Parameters
### Stochastic Results  
The PDF distributions and the partial sensitivities obtained from the stochastic analysis are shown in the top and bottom panels of Figures 13-15 for the flow rates in the healthy, aneurismatic, and coarctated aortas, respectively. Significant variability of the results is present for all the outlet sections during the systolic part of the cardiac cycle, \(t/T\in[0.1,0.35]\), whereas variability is lower during the diastole. During the systole, the main parameter affecting the stochastic variability of the flow-rate waveform is \(SV\), followed by the period \(T\). The parameter \(T\) becomes the most important in the diastolic phase for the flow-rate waveforms in DA and in BCA, followed by \(SV\). However, it should be noted that Sobol indexed in diastole is computed over a total variability of the quantity of interest more than one order of magnitude lower than the one in systole. Finally, the parameter \(L/D\) and interaction effect between the parameters always have a negligible impact on flow-rate variability.  
Figure 12: Effect of \(SV\), \(T\), and \(L/D\) on the deterministic \(\Delta p\) waveforms between \(\Gamma_{\rm AA}\) and \(\Gamma_{\rm DA}\): (a) healthy aorta, (b) aorta with aneurysm, and (c) aorta with coarctation.  
Figure 14: PDF of the waveforms of the flow rate (top panel) and relative Sobol indexes (bottom panel) at the four outlets of the aneurysmatic aorta: (**a**) DA, (**b**) BCA, (**c**) LCCA, and (**d**) LSA.  
Figure 13: PDF of the waveforms of the flow rate (top panel) and relative Sobol indexes (bottom panel) at the four outlets of the healthy aorta: (**a**) DA, (**b**) BCA, (**c**) LCCA, and (**d**) LSA.  
As for the PDFs and Sobol indexes for the differential pressure waveforms shown in Figure 16, the stroke volume is still the main parameter affecting result variability in the systole, with a significant effect of \(T\) as well and negligible ones for \(L/D\) and interactions. During the diastole, again characterized by a lower variability in terms of differential pressure, \(SV\) is the main parameter when dealing with healthy and anerismatic geometries, whereas the period \(T\) is the most effective for the diastolic phase in the coarctated aorta.  
Figure 16: _Cont._  
Figure 15: PDF of the waveforms of the flow rate (top panel) and relative Sobol indexes (bottom panel) at the four outlets of the coarctated aorta: (**a**) DA, (**b**) BCA, (**c**) LCCA, and (**d**) LSA.
# Improved Durability of Wood Strand-Based Panels Using Guayule
## 2 Materials and Methodology
### Testing of the Specimens
#### 2.4.1 Termite Methodology  
The laboratory methods for evaluating the termite resistance of wood-based materials followed the AWPA standard E1-23 Laboratory Methods for Evaluating the Termite Resistance of Wood-Based Materials [31]. This standard was followed for evaluating the termite resistance of treated and untreated WSB panels. A total of seven (7) specimens per treatment plus one additional specimen for operational mass loss were used. Additionally, eight (8) SYP softwood thin-wafer specimens were used as the test control for the termite resistance test, and these specimens had an average dimension size of 2.54 \(\times\) 2.54 \(\times\) 0.635 cm\({}^{3}\). There were two different control groups within this test--SYP softwood thin-wafer control specimens and WSB control specimens--that we manufactured as stated earlier in this manuscript. Overall, there were 40 specimens (32 pine WSB specimens and 8 pine control specimens). Before starting the termite tests, all pine WSB and control specimens were oven dried at 40 \({}^{\circ}\)C for 7-10 days until a constant weight was achieved to obtain the initial oven-dry weights. Each individual test specimen was placed into sterilized glass jar containing 150.00 g of oven-dry sterilized sand and 30.00 milliliters (mL) of deionized water, and then inoculated with 1.00 g of termites (-400 termites). A single-choice (no-choice) test procedure was used. Overall, approximately 35.00 g of native eastern subterranean termites (_Reticuliternes flawipes_) from a single colony was obtained from Dorman Lake Field Test Plots, Starkville, MS, USA. All jars were placed in a Blue M Dry Type Bacteriological Incubator (Blue M Electric Company, Blue Island, IL and New Columbia, PA, USA) set at 28 \({}^{\circ}\)C and monitored for four weeks (28 days). The mass of each pine WSB specimen and pine control specimen was taken before and after termite exposure to obtain mass loss values in oven-dry conditions.  
After the final weights were recorded, four (4) different people conducted visual rating scores on all specimens as part of the analysis. In the AWPA E1-23 [31] standard, section 7 requires that each specimen block is examined and visually rated using their rating system of the following values: 10 = sound, 9.5 = trace, surface nibbles, 9 = slight attack up to 3%, 8 = moderate attack (3-10%), 7 = moderate to severe attack (10-30%), 6 = severe attack (30-50%), 4 = very severe attack (50-75%), and 0 = complete failure (100%) [31].
## 1 Introduction: Name Disambiguation and Collocation
### What name metadata ought to include  
Name metadata ought to exist in discreet name metadata records that are easily machine readable, sharable, and updateable. In the library domain, name metadata exist as \"name authority records.\" These records are created cooperatively by librarians and shared openly on the internet. With one exception, the standards for these records prescribe creating a main heading that is unique from other names in the database. This uniqueness is achieved by, for example, adding additional data to the heading, such as birth and death dates, and by qualifying or spelling out names represented by initials. An example of such a heading is:  
[PERSON] ([PERSON]), 1880-1956.  
The one exception is the practice of creating \"undifferentiated name authority records.\" These are single records for more than one person that shares the same name. Sometimes it is impossible to differentiate multiple people with the same name because of a lack of information about the person. In this case the Library of Congress advises, \"An undifferentiated personal name is called for... as a last resort after all the possible additions to a new personal or to an existing personal name to break a conflict have been exhausted\" [11]. The Library of Congress' rules do not allow for undifferentiated names for corporate bodies; to make these names distinctive, qualifiers, such as location, are added to the authoritative form of the name. Table 1 lists the most useful metadata attributes that could be included in name metadata records to assist with both manual and automatic name disambiguation and collocation.
## 3 Results and Discussion
### MD Simulation of CH\({}_{4}\) Desorption and Diffusion in Coalbed  
In Section 3.1, we analyzed the adsorption of CH\({}_{4}\) and H\({}_{2}\)O on the surface of coal molecules using DFT calculations. However, the results in Section 3.1 are from a static point of view. They provide limited information for the dynamic desorption and diffusion process of CH\({}_{4}\) in a coalbed with the presence of fracturing fluid, which is crucial in coalbed gas extraction processes. In this section, we use MD methods to simulate the desorption and diffusion of CH\({}_{4}\) with and without the presence of H\({}_{2}\)O.
# GNSS Interference Monitoring and Detection (GIMAD) System +
## 2 Use Case and System Requirements  
Airports are critical infrastructures where satellite-based navigation applications are needed to be particularly protected. RFI detection and monitoring campaigns have already been conducted around several airports around the world. For example, at Newark's airport in the USA, the Ground Based Augmentation System (GBAS) was affected due tothe presence of jammers onboard vehicles passing through the highway near the airport [2]. The jammer device made the GBAS reference receiver lose track of GPS satellites, thus impacting GBAS operations. As a result, the Spanish Air Navigation Service Provider (ENAIRE) has brought out the risks that such interferences may cause and the real need for a monitoring system for early detection of RFIs.  
In order to protect GNSS availability and thus airport operations, International Civil Aviation Organization (ICAO) RFI masks have been devised in order to provide the maximum recommended interference levels [3]. For a similar purpose, there are also European Geostationary Navigation Overlay Service (EGNOS) v3 masks. However, RFI monitoring campaigns have demonstrated that these masks are not always fulfilled. For example, infractions of such RFI masks have been observed at Frankfurt airport in Germany [4] including violations of the ICAO SARPs CW interference thresholds.  
For that reason, both ICAO and EGNOS RFI masks have been adopted in the design of the GIMAD system, covering the frequency range from 800 to 1900 MHz.  
Considering the outcomes of RFI detection campaigns at international airports, an operational use case has been devised by the Spanish ANSP (ENAIRE), as illustrated in Figure 1 shows that when a jammer is detected by any of the monitoring stations in the monitoring network, the station shall send an alarm message to the central processor. In the case in which the power of the transmitter is high enough to be detected by more than one monitoring station, the central processor shall provide the accurate position of the interference source. In parallel, the central processor shall also trigger an alarm inside the ATC HMI (Air Traffic Control Human Machine Interface) warning about the presence of an undesired interference. In some cases, the Air Traffic Control Officers (ATCOs) can send warnings to the pilots reporting the unreliability of GNSS signals. As a consequence of alarms, the ANSP as well as national authorities are informed of the events with the objective of localizing and dismantling the interference source.
# Improved Low-Complexity, Pilot-Based Channel Estimation for Large Intelligent Surface Systems
## 2 System Characterization
### LS Channel Estimation  
For an optimal system, accurate channel estimation is essential. One of adopted methodologies for LIS channel estimation involves the utilization of pilot signals, commonly known as training sequences, followed by channel estimation based on the received data and the understanding of training symbols, in a LIS system with \(T\) transmitting antennas and \(R\) receiving antennas. The received signal can be represented by (1). The matrix \(\mathbf{H}\) is considered to be random. Simultaneously, it is expected that any estimator of \(\mathbf{H}\) will provide an estimate of a specific realization of the random matrix that corresponds to the current block of the received data.  
To estimate the channel matrix \(\mathbf{H}\), it is necessary to broadcast \(N\geq T\) training signal vectors \(\mathbf{S}_{1},\mathbf{S}_{2},...\mathbf{S}_{N}\).  
According to the least squares algorithm \(\mathbf{S}\) and received data, the realization of channel matrix can be estimate using the LS:  
\[\mathbf{H}_{LS}=\mathbf{Y}\mathbf{\hat{S}} \tag{9}\]where \(\mathbf{H}_{LS}=S^{H}\Big{(}S\,S^{H}\Big{)}^{-1}\mathbf{Y}\) is the pseudoinverse of \(S\)[24]. \(S^{H}\) is the Hermitian (conjugate transpose) of \(S\).
# Adaptive Visual Servoing Control for Hoisting Positioning Under Disturbance Condition
## 2 Literature Review
In the process of visual servo control using the whole photometric image information as a dense feature, the redundancy of visual information makes the convergence domain very small. [PERSON] [30] proposes an analytic visual servo based on Gaussian mixture to expand its convergence region. When the initial position is far away, it can still achieve stable speed control and converge to the desired position. In the motion control of a wheel robot based on a visual servo, the center position of the visual system is mostly the same as the center position of the robot body, but some settings that deviate from the center position of the robot are conducive to its motion, which will bring deviation to the visual system, resulting in the convergence failure of the visual error. In order to solve this problem, [PERSON] [31] designed a motion tracking method based on visual servo, which deviated from the center of the robot body, to solve the influence of the translation of the uncalibrated camera on the parameters of the visual system. In the visual servo control of most mobile robots, the trajectory and the desired position image must be given. [PERSON] [32] designed a positioning control scheme based on monocular vision, defined the image reference frame by using the visual target and plane motion constraints, proposed the attitude estimation algorithm of the robot relative to the image of desired pose, and constructed the updated rate of unknown feature parameters. However, when the visual target and motion constraint parameters change, the reference frame will change and the control precision will be affected. This paper researches the hoisting positioning technology based on visual servo control under the disturbance condition and focuses on solving the following two puzzles: (1) the correlation between visual error and disturbance is not considered or well resolved; (2) the disturbance has a great influence on the control stability, but it is difficult to model. In this paper, the visual error model is defined by the image error of a feedback signal based on dynamic equations containing disturbance. To solve the problem of the disturbance term being difficult to model, the nonlinear disturbance observer is employed to obtain equivalent disturbance and an adaptive control algorithm, while disturbance compensation is proposed. The organization of this paper is as follows. Section 3 depicts the problem description, including dynamics modeling, and IBVS modeling. In Section 4, we describe the visual servo control based on adaptive sliding mode control (SMC), then propose the control law with disturbance compensation, and give the stability analysis based on [PERSON]'s theory. Simulations are conducted in Section 5, which depicts the superiority of the proposed method against the other methods. Section 6 represents the experimental results of two projects with different initial positions. Finally, Section 7 contains a summary and outlook.
## 2 Methods
### Fluorescence Cross-Correlation Spectroscopy (FCCS)  
FCCS measurements were performed using a ConfoCor 3 system combined with an LSM 510 META (Carl Zeiss, Jena, Germany) through a C-Apochromat 40\(\times\)/1.2 NA Korr UV-VIS-IR water-immersion objective (Carl Zeiss). The confocal pinhole diameter was adjusted to 73 \(\upmu\)m. The eGFP and mCherry were excited at 488 and 594 nm, respectively, and emission signals were detected using a 505-540 nm bandpass filter for eGFP and a 615-680 nm bandpass filter for mCherry after the short and long wavelengths were divided through a 600 nm dichroic mirror. Measurements were performed in a cover glass chamber (#155411, Thermo Fisher Scientific, Waltham, MA, USA). The obtained fluorescence autocorrelation functions for eGFP and mCherry, \(G(\tau)\)s, from which the lag time (\(\tau\)) was analyzed using a one-component three-dimensional diffusion model including the one-component triplet state, is given by Equation (1):  
\[G(\tau)=1+\frac{1}{N_{x}}\left[1+\frac{T}{1-T}\exp(-\frac{\tau}{\tau_{\text{ triplet}}})\right]\left(1+\frac{\tau}{\tau_{\text{D}}}\right)^{1}\left(1+\frac{ \tau}{\left(1/s\right)^{2}\tau_{\text{D}}}\right)^{\frac{1}{2}} \tag{1}\]  
where \(\tau_{\text{D}}\) is the diffusion time of molecules, \(N_{x}\) is the average number of fluorescent molecules (eGFP-tagged and mCherry-tagged proteins are shown as \(N_{g}\) and \(N_{r}\), respectively) in the detection volume defined by the beam waist \(w_{xy}\) and the axial radius \(w_{x}\)\(s\) is a structure parameter representing the ratio of \(w_{\rm xy}\) and \(w_{\rm z}\), \(T\) is the blinking fraction, and \(\tau_{\rm triplet}\) is the blinking time. The \(G(\tau)\) values of the samples were measured for 100 s. Following pinhole adjustment, the structure parameter was determined and fixed before measurements using a 10 nM ATTO488 and 10 nM Alexa Fluor 594 solution as a standard. Counts per molecule (CPM) were calculated as the mean fluorescence intensity of GFP and mCherry divided by \(N_{\rm g}\) and \(N_{\rm r}\), respectively. The cross-correlation functions (CCFs) of the two fluorescent proteins were measured after mixing 10 nM eGFP-tagged hACE2 and 300 nM mCherry-tagged S1 subunit for 1 min; then, the CCFs were fitted using Equation (1) with \(T\) = 0.  
The relative cross-correlation amplitude was calculated using Equation (2), as previously reported [26]:  
\[RCA:=\frac{G_{\rm c}(0)-1}{G_{\rm r}(0)-1}=\frac{N_{\rm c}}{N_{\rm g}} \tag{2}\]  
where \(G_{\rm r}(0)\) is the autocorrelation function of the red channel with mCherry at \(t\) = 0, \(G_{\rm c}(0)\) is the CCF between eGFP and mCherry channels at \(t\) = 0, and \(N_{\rm c}\) is the average number of interacting molecules.
## 4 The Influence of System Parameters on Response Characteristics
### The Effect of Lever Mechanism on the Amplitude of Primary System  
The mass ratio \(\mu=0.1\) and inerter-mass ratio \(\beta=0.1\) are selected for the two cases. The value of the amplification ratio \(L\) is greatly related to the maximum amplitude of the primary system. The amplitude-frequency response curves of the primary system with different values of \(L\) are given in Figure 8. As we can see, the larger the amplification ratio is, the lower the amplitude and the wider the distance between the two resonance peaks are.
## 4 Results and Analysis of Impact Tests  
### Stress Uniformity Verification of Prismatic Sample  
In addition to the condition that the SHPB system must satisfy a one-dimensional stress state, the other experimental principle that must be satisfied is that the dynamic stress and strain distributed in the bars and the specimens must satisfy stress uniformity assumption during the impact tests, that is, the stress distribution on the cross sections of the samples should be uniform. Numerous experimental studies have shown that the cylindrical specimen with the same diameter as that of the bars used for the impact test has been proved to satisfy the stress uniformity assumption [5]. However, it is still not clear whether the prismatic specimens can be used for the SHPB impact test, so we need to check their stress uniformity. In this work, taking the specimen G1-A as an example, the comparison of the transmitted wave curve and the stacking curves of the incident and reflected waves can be plotted based on the wave voltage versus time curve of the specimen, as presented in Figure 7. Clearly, the stacking curve of the incident and the reflected stress wave agree well with the transmitted stress wave, indicating that the stress is balanced and the prismatic specimens are available for impact tests. Similarly, we can also plot the stress balance verification diagrams of the pre-holed specimens when the air pressure is 0.45 MPa. As an example, Figure 8 illustrates the curves of wave voltage versus loading time and the stress-loading time curves of different waves of the specimen G2-A. We find the superimposed amplitude of the incident and reflected waves is larger than the amplitude of the transmitted stress wave, suggesting that the amplitude of the propagating stress wave attenuates when it passes through the opening. Nevertheless, it is observed that the superimposed amplitude of the incident and reflected waves are nearly coincident with the amplitude of the transmitted stress wave before the peak. Thereby, the stress balance condition is satisfied before the peak point. In brief, the processed prismatic samples applied for impact tests satisfy the assumption of stress uniformity.  
Figure 8: Impact test results of specimen G2-A: (**a**) wave voltage–loading time curves, and (**b**) stress–loading time curves of different waves.  
Figure 7: Impact test results of specimen G1-A: (**a**) wave voltage–loading time curves, and (**b**) stress–loading time curves of different stress waves.