esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Case Study
### Results and Discussion
#### 3.4.4 Comparison with the Polynomial Response Surface Method and ABGPR-MCS  
The methods for solving the random reliability (the proposed framework) and the response surface reliability are completely different. Generally, the random reliability can be regarded as an exact solution, while response surface reliability can be regarded as an approximate solution.  
For the support structure of the tunnel, in order to further investigate the efficiency and feasibility of the obtained reliability indices, and considering the characteristics that the structural performance function cannot be explicitly expressed in the research problem, we use the polynomial response surface method (PRSM) to calculate the structural reliability. In the PRSM, we select sampling points using the star design method, and each calculation step needs to calculate the values of sampling points through FEM simulation.  
When the response surface method (RSM) [34] is used to calculate the structural reliability index, the calculation of the reliability index becomes an optimization problem, as shown in Formula (19).  
\[\beta=\min_{\overline{g}(x)=0}\sqrt{n^{\mathsf{T}}R^{-1}n} \tag{19}\]  
where \(\overline{g}(x)\) is the polynomial expression of the performance function; \(R\) is the correlation coefficient matrix of a random variable \(x\); \(R\) is taken as the unit matrix in this study; \(n\) represents the degenerate space vector corresponding to \(x\).  
The final solving process of PRSM can be carried out with the help of the planning solver tool in Excel 2021. The iteration results are shown in Table 4. The reliability indices of two iteration steps before and after and the change in the step size of checkpoints in Table 4 are compared. It is determined that the calculation of the PRSM is converged when the number of iterations reaches nine. Taking the average value of the reliability indices of iteration steps 8 and 9 as the result, the reliability index of the tunnel vault structure is obtained as 2.70.  
The result of tunnel structure reliability obtained using the PRSM (2.7) is close to the result obtained using the ABGPR-MCS reliability method (2.906), which shows that the proposed method is efficient and feasible.
## 5 Results
### Evaluation of the modeling results
#### 5.3.1 Qualitative comparison with previous studies
\begin{table}
\begin{tabular}{|p{56.9 pt}|p{56.9 pt}|p{56.9 pt}|p{56.9 pt}|p{56.9 pt}|} \hline
**Location and vegetation type** & **Estimating technique** & **GPP (gC/m2)** & **NPP(gC/m2)** & **NEP*(gC/m2)** & **Reference** \\ \hline Central Asia & & & & \\ Dry steppe & Field observations & 326 & [PERSON] \& [PERSON] \\ Dry steppe & & 126 & [28] & \\ Dry steppe & & 148 & [PERSON] [29] \\ Semidesert & & 90-310 & [PERSON] [30] \\ Semidesert & & 117-189 & [PERSON] et al. [33] \\ Semidesert & & 220 & [PERSON] [30] \\ Semidesert & & 114 & [PERSON] [31] \\  & & & [PERSON] [32] \\ \hline _Former Czechoslovakia_ & & & & \\ Grassland & Field observations & 664 & 481 & 18 & [PERSON] \& [PERSON] [62] \\ Grassland & & 492 & 318 & 21 & [PERSON] et al. [63] \\ \hline _Global_ & & & & \\ Grassland & Field observations & & 70-410 & [PERSON] et al. [60] \\ Grassland & & & 91-385 & [PERSON] et al. [61] \\ \hline Wyoming, USA & & & & \\ Mixed-grass & Measurements of net & & & \\ prairie & ecosystem exchange & 321 & & 14 & [PERSON] et al. [20] \\ Sagebrush steppe & & 239 & & 42 & \\ \hline Sahel, Niger & Satellite-based LUE & & & & \\ Grassland & model & 352.1 & 169.3 & [PERSON] et al. [19] \\ \hline Central & & & & & \\ Kazakhstan & & & & \\ Dry steppe & Satellite-based LUE & 243.70 & 145.61 & -0.09 & The present study \\ Semidesert & model & 211.03 & 131.30 & 13.17 & \\ \hline \end{tabular}  
*Positive NEP indicates that site was a sink for carbon, and negative NEP indicates the sites was a source for carbon to the atmosphere.  
\end{table} 
Table 4: Previous estimates of primary production (GPP and NPP) and net ecosystem production (NEP) in arid and semi-arid zones.
## 2 Materials and Methods
### Degradation Study  
Soil incubations in microcosmsSoil incubations were performed under reduced (anaerobic) or oxidized (aerobic) conditions using serum bottle microcosms to determine the degradation kinetics of \({}^{14}\)C-metolachlor.  
Anerobic incubationsMicrocosms consisting of serum bottles (60 mL) were amended with soil (10 g) and spiked with ring-labeled \({}^{14}\)C-metolachlor (specific activity of 2.37 \(\times\) 103 Bq \(\mu\)mol\({}^{-1}\), diluted with unlabeled metolachlor) in 50 \(\mu\)L of methanol to produce a final concentration of 5 mg kg\({}^{-1}\) of soil. This concentration corresponded to the recommended agriculture application rate. The metolachlor-spiked soils were agitated on a reciprocating shaker for 24 h at room temperature to ensure thorough mixing and evaporate the solvent. The soil then had 20 mL of sterile (autoclaved) and deoxygenated water added to simulate the soil flooding and saturation resulting from rainfall situations. The microcosm headspace was flushed with N\({}_{2}\) gas and immediately crimp sealed with a butyl stopper fitted with a vial containing 1 mL of 0.5 M NaOH to trap the mineralized \({}^{14}\)CO\({}_{2}\). These microcosms were incubated in a dark, temperature-controlled chamber at 25 \({}^{\circ}\)C. Sterilized soil microcosms were included as a control for each soil type. Sterilization was achieved by autoclaving the soils twice on consecutive days at 121 \({}^{\circ}\)C for 1 h.  
Aerobic incubationsThe soil microcosms were built from serum bottles as described above. Sterile distilled water was added to the metolachlor-spiked soils to adjust the moisture content to about 60% of the field water-holding capacity (WHC). The serum bottles were lightly capped with a butyl stopper fitted with a NaOH trap and stored in the dark at 25 \({}^{\circ}\)C. The soil microcosms were aerated every week by equilibrating the headspace with the atmosphere. The soil moisture content was adjusted by returning each vessel to its initial weight with sterile distilled water.
## 2 Materials and Methods  
### Materials and Reagents  
Acetonitrile, acetone, methanol, ethyl acetate, formic acid (all LC-MS grade), ammonium formate (NH\({}_{4}\)HCO\({}_{2}\geq\)99%), and ethylenediaminetetraacetic acid disodium salt dehydrate (Na\({}_{2}\)EDTA; \(\geq\)99%) were purchased from Sigma-Aldrich (St. Louis, MO, USA). Ultrapure water (LC grade 18 \(\Omega\) cm) was obtained from a MilliQ water purification system (Millipore Ltd., Bedford, MA, USA).  
Pre-weighed QuECHERS kits containing analytical-grade reagents--magnesium sulfate, sodium chloride (NaCl), trisodium citrate dihydrate (Na\({}_{3}\)C\({}_{6}\)H\({}_{5}\)O\({}_{7}\)-2H\({}_{2}\)O), and disodium hydrogen citrate sesquohydrate (Na\({}_{2}\)HC\({}_{6}\)H\({}_{5}\)O\({}_{7}\)-1.5H\({}_{2}\)O) salt--were procured from Agilent Technologies (Santa Clara, CA, USA); pre-weighed kits containing magnesium sulfate (MgSO\({}_{4}\)) and sodium acetate (CH\({}_{3}\)COONa) were obtained from Supelco (Bellefonte, PA, USA).  
For clean-up methods, pre-weighted sorbent mixtures PSA/C18/MgSO\({}_{4}\) (primary secondary amine/octadecylsilane/anhydrous magnesium sulfate) and PSA/GCB/MgSO\({}_{4}\) (primary secondary amine/graphitized carbon black/anhydrous magnesium sulfate) kits were purchased from Perlan Technologies (Santa Clara, CA, USA). Chitosan from shrimp shells, Fe\({}_{3}\)O\({}_{4}\) magnetic nanoparticles (Fe\({}_{3}\)O\({}_{4}\)MNPs), and graphene oxide dispersion in H\({}_{2}\)O (GO) were obtained from Sigma-Aldrich (Steinheim, Germany). The GO dispersion, at a concentration of 2 mg/mL, is chloride-free (purified by dialysis), consists of monolayer sheets, and has an average sheet diameter of less than 10 \(\upmu\)m.  
For the preparation of the matrix, i.e., the model wastewater according to PN-72/C-04550.09, the following components were used (all with purity \(\geq\) 98%): casein peptone, enriched dry broth, ammonium chloride (NH\({}_{4}\)Cl), calcium chloride (CaCl\({}_{2}\)), monobasic potassium (KH\({}_{2}\)PO\({}_{4}\)), dibasic potassium phosphate (K\({}_{2}\)HPO\({}_{4}\)), and sodium acetate (CH\({}_{3}\)COONa) from Sigma-Aldrich (Steinheim, Germany).
# Integrated Components and Solutions for High-Speed Short-Reach Data Transmission
## 3 Receiver for Short-Reach Transmission Systems
### Single-End Photodetector under Direct Detection  
Single-end PD, which can perform the optoelectronic conversion operation to convert the signal from electrical domain to optical domain, is considered as the key receiver component of conventional IM/DD system. Single-end PD has been applied to detect signal envelope by square law detection. The output current of single-end PD is proportional to the square modulus of signal envelop, and hence it can only be used in amplitude modulation-based transmission systems. Usually, it is based on the reversely biased p-n junctions so that output current can be very weak. In order to enhance output current and receiver responsibility, two types of single-end PD including the PIN photodiode and the avalanche photodiode (APD) are introduced. The PIN photodiode consists of the p-type layer, intrinsic layer, and n-type layer, and normally combines with a trans-impedance amplifier (TIA) to further amplify the output current from the photodiode. The APD produces a relatively larger current by introducing significant photon amplification. Through preliminary analysis, it is believed that PIN + TIA is more commonly used in short-to-medium reach transmission systems, because its amplification noise is generally smaller than that of APD. However, when the received optical power is very low, APD with high detection sensitivity may be more suitable to detect the signal than PIN + TIA. At present, most of the reported 100-Gbit/s even 200-Gbit/s short-reach transmission systems had applied single-end PD as the receiver component.
# Theoretical and Numerical Research on High-Speed Small Refrigeration Twin-Screw Compressor
## 5 Results and Analysis
### The Gas Forces of Different Rotors at the Rated Rotational Speed  
A CFD model was employed to analyze the gas forces acting on rotors with different rated speeds under identical operating conditions. Figure 8 illustrates the axial and radial  
\begin{table}
\begin{tabular}{c c c c c c} \hline \multirow{2}{*}{**Configuration**} & \multirow{2}{*}{**Radial Nodes**} & \multirow{2}{*}{**Circumferential Nodes**} & \multirow{2}{*}{**Axial Nodes**} & \multirow{2}{*}{**Mass Flow**} & \multirow{2}{*}{**Power/kW**} \\  & & **(Main/Gate Rotor)** & & & **Rate/kg\(\cdot\)s\({}^{-1}\)** \\ \hline
1 & 15 & 200/150 & 90 & 0.292 & 17.01 \\
2 & 18 & 200/150 & 90 & 0.298 & 17.09 \\
3 & 20 & 200/150 & 90 & 0.307 & 17.15 \\
4 & 20 & 260/200 & 90 & 0.311 & 17.28 \\
5 & 20 & 300/260 & 50 & 0.295 & 17.06 \\
6 & 20 & 300/260 & 70 & 0.309 & 17.23 \\
7 & 20 & 300/260 & 90 & 0.317 & 17.45 \\
8 & 20 & 300/260 & 110 & 0.318 & 17.48 \\ \hline \end{tabular}
\end{table}
Table 4: Mesh independence verification for rotating flow domains.  
Figure 7: The efficiency of the screw compressor at different clearances and different rated rotational speeds.  
gas forces exerted on each rotor configuration across various rotational speeds. The results demonstrate a significant reduction in both axial and radial gas forces with an increasing speed while maintaining a constant theoretical displacement. Notably, the main rotor experiences substantially higher axial forces compared to the gate rotor, whereas the gate rotor exhibits greater radial forces than the main rotor.  
Figure 9 illustrates the variation in the end-plate gas forces and the resulting torque acting on the rotors. The analysis reveals that, with an increasing rated speed at constant displacement, the gas forces acting on the rotors decrease significantly. Notably, the main rotor experiences substantially higher axial gas forces compared to the gate rotor, necessitating differentiated bearing selection based on their distinct load characteristics. Concurrently, the torque demonstrates a marked reduction with increasing speed, accompanied by a decreased amplitude in the torque fluctuations.  
Using the axial, radial, and end-plate gas forces acting on the 3000 rpm rated rotor as reference values, the force ratios at other rotational speeds are compared relative to the 3000 rpm baseline (Figure 10). The analysis reveals that, with the exception of the gate rotor's axial and end-plate gas forces, the force ratios exhibit consistent trends with the corresponding surface area ratios relative to the 3000 rpm configuration. This finding highlights the need for the special consideration of the force distribution on the gate rotor during the design process, particularly regarding its axial and end-plate loading characteristics.  
Figure 8: Axial and radial gas forces on the main and gate rotors at different rated speeds.  
Figure 9: The end-plate gas forces and torque on the main and gate rotors at different rated speeds.
## 2 Proposed Iterative Identification Method
The flowchart of the proposed approach is shown in Figure 1. As can be seen from Figure 1, the LSE technique is employed for parameter identification and the input modification process is used to force the estimated ground acceleration to comply with its spatial distribution along the structure. The key point of this approach is the input modification procedure as described in step 3, which converts the spatial distribution of ground motion into the additional information for parameters identification. It can also be observed that there are no complicated formulas and their derivations involved, implying the proposed approach is quite simple and can be easily realized. The accuracy of the proposed approach for the identification of structural parameters and unknown ground motion is numerically validated via a shear building model under the El Centro earthquake. More details can be found in the following section.
# Surface Motion for P-Wave Scattering by an Arbitrary-Shaped Canyon in Saturated Half-Space
## 5 Parameter Analysis
### Trapezoidal Canyon
#### 5.2.2 Incident Angle  
Figure 7 shows porosity \(n_{s}=0.3\) in the saturated half-space, and the influence of different incidence angles and dimensionless frequencies on the surface displacement. The oscillation of the displacement amplitude curve increases obviously with the increase of dimensionless frequency, and the incidence angle has a significant effect on the surface displacement. Compared with the low frequency \(\eta=1\), the amplification effect of the medium and high frequency \(\eta=4\) and \(6\) on the displacement amplitude is significantly increased, and the oscillation peak value appears near \(x/a=\pm 1\). The incidence angle has an obvious influence on the \(x\)-component displacement amplitude, and the displacement amplitude is the largest when \(\gamma_{1}=30^{\circ}\), followed by \(60^{\circ}\), \(30^{\circ}\), and \(5^{\circ}\). Consistent with  
Figure 6: Influence of porosity on the displacement response of a trapezoidal canyon (\(\eta=2\)).  
horizontal displacement, the influence of incident angle on vertical displacement amplitude is also obvious. When \(\gamma_{1}=90^{\circ}\), the vertical displacement amplitude is the largest, followed by \(\gamma_{1}=60^{\circ}\), \(30^{\circ}\), and \(5^{\circ}\). For the cases of medium and high frequency \(\eta=4\) and \(6\), when the oblique incidence \(\gamma_{1}=5^{\circ}\), \(30^{\circ}\), and \(60^{\circ}\), the oscillation of the displacement amplitude curve of the backside is significantly smaller than that of the front side of the canyon, which obviously reflects the shielding effect of the canyon. In addition, at the same dimensionless frequency, the oscillation of the displacement curve is more obvious at the boundary of the trapezoidal canyon than that of the semicircular canyon.
## 8 Summary of Key Findings
### Physical Layer Security Techniques  
Table 8 tabulates the related methods and techniques, as well as approaches that have been presented previously to ensure data transmission security in wireless sensor networks at the physical layer, shedding light on their efficiency and providing arguments (instance for some key) against safety threats.
## 2 Materials and Methods
### Data Collection and Processing  
Currently, the widely used NDVI datasets are primarily based on an advanced very-high-resolution radiometer (AVHRR), SPOT-VEGFATION, and MODIS sensors [24; 25; 26; 27]; the significant differences in sensors, spatiotemporal resolution, and vegetation indexes result in identical surface reflectance producing different NDVIs. Among these NDVI datasets, the MODIS NDVI dataset has a relatively high spatial resolution of \(250\times 250\) m and sufficient temporal resolution of 16 days, and the MODIS time series, based on a single sensor, can effectively inhibit the influence of a platform/sensor shift [28]. Therefore, the MODIS NDVI datasets from the year 2000 to 2016 were derived from NASA's Earth Observing System and used in this study. The NDVI datasets were selected only during the growing season (May-October), which represents the active status of plant growth, and the maximum growing season NDVI was chosen to represent the yearly NDVI. Pixel NDVI datasets were obtained using the maximum value composite (MVC) method, which selects the highest observation for each pixel from a predefined compositing period to represent the current period, and could minimize the effects of clouds, atmospheric conditions, and solar altitude [29].  
The climatic datasets consisting of daily mean temperature and daily precipitation data from the year 2000 to 2016 were collected from the National Meteorological Center of China. There are 17 meteorological stations in the Sanjiangyuan National Park and its neighboring regions. The spatial locations of the meteorological stations are shown in Figure 1. The inverse distance weighted technique was used to interpolate the data into raster layers [30]. For further analysis, the spatial time series of the yearly NDVI, NPP, temperature, and precipitation from the year 2000 to 2016 were generated.
## 5 Experimental Results and Discussion
### Experimental Results of Steel Cord conveyor Belt Defects
#### 5.2.1 Collection of the Defects Signals  
The scheme of the weak magnetic signals collection experiment platform is presented in Figure 8. First, the weak magnetic loading module was installed to magnetize the wire rope in the steel cord conveyor belt. Then, the operating velocity of the belt was 0.5 m/s. The signals were collected by the weak magnetic testing device and transmitted to the upper computer by the TCP/IP protocol, as presented in Figure 9. The main parameters of the weak magnetic testing device were defined. More specifically, the sensitivity of the sensor was 0.5 V/Gs, the sample interval was 0.0005 mm and the data transmission rate was 100 Mbps.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**UCI Data Sets** & **Kernel Functions** & \begin{tabular}{c} **Average Accuracy of** \\ **Conventional SDTSVM** \\ \end{tabular} & \begin{tabular}{c} **Average Accuracy** \\ **of ISDTSVM** \\ \end{tabular} & \begin{tabular}{c} **Classification Order** \\ **of ISDTSVM** \\ \end{tabular} \\ \hline Zoo & \begin{tabular}{c} Radial basis function \\ (\(C=1.65\), \(\gamma=0.25\)) \\ \end{tabular} & 95\% & 98\% & 6\(\rightarrow\)4\(\rightarrow\)1\(\rightarrow\)2\(\rightarrow\)3 \\ \hline Zoo & \begin{tabular}{c} Polynomial (d = 1) \\ \end{tabular} & 93\% & 96\% & \\ \hline Wine & \
\begin{tabular}{c} Radial basis function \\ (\(C=0.31\), \(\gamma=0.23\)) \\ \end{tabular} & 97\% & 98\% & 3\(\rightarrow\)1\(\rightarrow\)2 \\ \hline Wine &
\begin{tabular}{c} Polynomial (d = 2) \\ \end{tabular} & 97\% & 97\% & \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Classification Order** & **Kernel Functions** & **Average Accuracy of SDTSVM** \\ \hline
1\(\rightarrow\)2\(\rightarrow\)3 &
\begin{tabular}{c} Radial basis function \\ (\(C=0.31\), \(\gamma=0.23\)) \\ \end{tabular} & 97\% \\
2\(\rightarrow\)1\(\rightarrow\)3 &
\begin{tabular}{c} Radial basis function \\ (\(C=0.31\), \(\gamma=0.23\)) \\ \end{tabular} & 97\% \\
3\(\rightarrow\)1\(\rightarrow\)2 &
\begin{tabular}{c} Radial basis function \\ (\(C=0.31\), \(\gamma=0.23\)) \\ \end{tabular} & 98\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Classification results of the Wine data sets for the three classification orders using the SDTSVM algorithm with a radial basis function and a five-fold cross-validation.  
Figure 7: Diagnosis procedure flow chart of the steel cord conveyor belt defects signals.
# Survey of Smart Parking Systems
## 7 Discussion and Open Problems
### Open Problems  
The gaps, advantages, and disadvantages of SPS uncovered here allowed us to establish what the current situation is, what the points of interest and innovation are, and what new proposals can be made.  
One of the points that can be addressed among the open problems is the use of user preferences, which will make it possible to establish a selection of parking spaces in a more efficient way, as well as a choice of routes to reach these spaces according to those preferences. This feature is among the main gaps mentioned in Section 7.2.  
Open issues may also include the establishment of a multi-objective optimization that will allow working with different types of user preferences to search for parking and establish the routes mentioned above. Among the preferences to be taken into account is a distance from the parking lot to the destination, i.e., parking as close as possible to the destination (this type of preference was implemented in Reference [274]), time in finding an available parking lot, i.e., parking as fast as possible, parking avoiding congestion zones, i.e., parking in places of high availability of spaces, and parking for people with disabilities, i.e., parking near accessibility ramps.  
Another feature that can be taken into account, which will allow the disadvantages detected for the routing algorithms that do not obtain updated information (Section 7.3) to be overcome, is the use of an algorithm in real time, which will allow updated information to be obtained to establish routes to the parking spaces by taking into account variables in the context of that route, such as congestion of the traffic of an artery, streets being cut off, detours, and the occupation of parking spaces.  
In addition, to solve the problem described in Section 7.4, the algorithm must allow a new route to be calculated as it is executing the trajectory of an already established route (rescheduling route). This rescheduling will be executed after events that influence the previously established route, such as, for example, the occupation of the parking space established for the driver as they are on their way to it. If this event occurs, the system should be able to search for a new parking space according to the user's preferences and re-establish a new route to the new target location.  
Finally, as mentioned in Section 7.1, the challenge in obtaining the information about the detection of vehicles depends on the underlying infrastructure in the place where the system is going to be implemented, or on the technology that was chosen to be used according to the system to be implemented.