esa-sceva/satcom-chunk-collection huggingface dataset:
# Miniaturized Compact Reconfigurable Half-Mode SIW Phase Shifter with PIN Diodes
## 2 Design of the HM-SIW Phase Shifter
### Working Principle  
This subsection provides a qualitative perspective on the principle of structure. One method to analyze the structure is to hypothesize HM-SIW as a transmission line [45]. Despite being a high-pass filter by considering the cut-off frequency, the HM-SIW's primary mode reduces signal transmission to a band-pass. The equivalent circuit element  
Figure 4: Equivalent circuit model of a PIN diode for two different states. Using a parallel arrangement for both states, the ON state is derived from a series-to-parallel transformation. (\(L_{\text{n}}\) = 0.209 nH, \(R_{\text{on}}\) = 33.3 \(\Omega\), \(R_{\text{off}}\) = 30 k\(\Omega\), and C\({}_{\text{off}}\) = 0.1338 pF).  
Figure 3: Specification of the PIN diode placement in the reconfigurable phase shifter design. The resistor is one element to isolate RF signals with DC bias.  
of a high-pass filter with one parallel stub is modeled as a T-network high-pass filter circuit in Figure 5[24; 30]. By adding inductance to the parallel branch, it is possible to increase the phase shift when compared with the reference value. This procedure is applied in the schematic of Figure 6. The lumped element values for the high-pass filter are from an equivalent value for a Butterworth model [46]. Then diode post values can tune both the phase and amplitude values of the reference HM-SIW. This principle is applied here for phase shifting applications with parametric studies, simulation software, and concrete measurement.  
Figure 5: Qualitative circuit model analysis of (**a**) a high-pass filter equaling the HM-SIW guided transmission line and (**b**) the effect of parallel impedance posts on the SIW topology (C\({}_{1}\) = 1.061 pF and L\({}_{1}\) = 1.326 nH). Port locations are shown in Figure 1. Furthermore, Figure 4 displays the values for the diode impedance (Z diode).  
Figure 6: _Cont._  
When looking at Figure 2, the added length of lines connecting to the PIN diodes presents a constant phase shift for every branch. Additionally, they provide enough space for a diode soldering pad. The location of PIN diode stubs is tuned with full wave simulation, considering fabrication constraints and achieving a sensible phase shift for a smaller total length.
# Prediction of Phytochemical Constituents in Cayenne Pepper Using MIR and NIR Spectroscopy
###### Abstract  
The aim of the present study was to evaluate the potential of handheld near-infrared (NIR) and benchtop mid-infrared (MIR) spectroscopy for the rapid prediction of antioxidant capacity, dry matter, and total phenolic contents in Cayenne pepper (_Capsicum annuum_ 'Cayenne\"). Using NIR spectroscopy, the best-performing model for dry matter had an R\({}^{2}_{\text{pred}}\) = 0.74, RMSEP = 0.38%, and RPD of 2.02, exceeding the best results previously reported in the literature. This was also the first study to predict dry matter content from the mid-infrared spectra, although with lower accuracy (R\({}^{2}_{\text{pred}}\) = 0.54; RMSEP = 0.51%, RPD 1.51). The models for antioxidant capacity and total phenolic content did not perform well using NIR or MIR spectroscopy (RPD values < 1.5), indicating that further optimization is required in this area. Application of support vector regression (SVR) generally gave poorer results compared to partial least squares regression (PLSR). NIR spectroscopy may be useful for in-field measurement of dry matter in the chili crop as a proxy measure for fruit maturity. However, the lower accuracy of MIR spectroscopy is likely to limit its use in this crop.
## 1 Introduction
Furthermore, the proposed method mitigates spectrum fragmentation by determining the prioritized frequency bandwidth for lightpath-setup requests based on the number of FSs required by the group to which they belong. Through simulation experiments, we show that the proposed method allows for the suppression of inter-core crosstalk while keeping the blocking probability of lightpath establishment low. The contributions of this paper are as follows:  
* We propose a dynamic RCSA method that prevents the blocking of newly established lightpaths while maintaining inter-core crosstalk at a low level, even in cases where the number of available cores is limited. * The proposed RCSA method efficiently accommodates lightpath-setup requests with various numbers of required FSs through a grouping-based core allocation approach. * Furthermore, our proposed RCSA method can utilize frequency-spectrum resources by allocating the preferred frequency bandwidth to lightpath-setup requests in each group. The rest of this paper is organized as follows. In Section 2, we discuss related works. Section 3 explains the system model, assuming elastic optical path networks with multi-core fiber environments. Our proposed RCSA method is discussed in Section 4. We evaluate the performance of our proposed RCSA method through simulation experiments in Section 5. Finally, we conclude this paper in Section 6.
# Signal Source Localization of Multiple Robots Using an Event-Triggered Communication Scheme
## Nomenclature  
\(v_{i}\)Linear velocity  
\(\omega_{i}\)Angular velocity  
\(\tau_{i}\)Torque  
\(\tau_{i}\)Applied torques for the left wheel  
\(\tau_{r}\)Applied torques for the right wheel  
\(\theta_{i}\)Orientation angle  
\(A\)Adjacency matrix  
\(a_{ij}\)Element of an adjacency matrix  
\(b\)Radius of the wheel  
\(e\)State error  
\(e_{v}\)Velocity error  
\(e_{x}\)Position error  
\(F\)Force  
Figure 10: The curves for the localization errors.
# Best-Suited Communication Technology for Maritime Signaling Facilities: A Literature Review
## 3 Results and Discussion
### State of Communication Technologies
Due to the high-frequency spectrum used in 5G-NR, signals attenuate quickly over long distances, necessitating a large number of small cells and repeaters, which is not feasible in sea environments [69]. Furthermore, 5G-NR's energy consumption is significantly higher compared to other maritime communication technologies, raising concerns about sustainability and operational costs in maritime applications [70]. Additionally, the lack of standardized maritime-specific 5G-NR solutions further complicates its adoption, as existing networks are primarily designed for urban and terrestrial use cases rather than for the open seas' vast and dynamic nature [70]. These factors collectively highlight the need for more cost-effective and energy-efficient communication solutions tailored to the unique challenges of maritime environments. While hybrid approaches that integrate satellite communication with terrestrial networks and advanced maritime mesh networks are being explored, the practical deployment of these solutions remains challenging due to regulatory, technical, and economic constraints [71]. Considering the technical issues related to establishing data transmission from maritime signaling facilities, this paper emphasizes three technical criteria for establishing communication with these objects. These criteria--signal range, power consumption, and economic aspects (cost)--were selected due to their direct impact on the feasibility and long-term sustainability of remote monitoring systems in maritime environments. Signal range is crucial because maritime signaling facilities are often located in remote and isolated areas where conventional communication infrastructure is unavailable. Reliable long-distance communication is necessary to ensure continuous data transmission and effective monitoring [72]. Power consumption is another key factor, as many of these facilities rely on limited energy sources, such as solar panels. High-energy consumption would require frequent maintenance and additional infrastructure, making low-power solutions preferable for ensuring operational efficiency and system reliability [73]. Finally, cost plays a significant role in determining the scalability and practical implementation of communication technologies. While satellite-based systems provide global coverage, their high costs often make them impractical for large-scale deployment. More cost-effective solutions enable broader adoption and reduce the financial burden associated with maintaining maritime signaling networks [74]. The key technical criteria for establishing communication with maritime signaling facilities are illustrated in Figure 5.  
By analyzing the three technical criteria mentioned, a holistic understanding of communication technologies can be achieved. This analysis allows for a thorough evaluation of the technologies and their suitability for specific applications.
# Lateral Dynamic Response of Helical Pile in Viscoelastic Foundation Considering Shear Deformation
## 4 Verification of the Present Solutions
### Element Division Accuracy of Pile-Soil System  
The helical pile is divided into \(S\) units with equal thickness for the analysis of LDR. Therefore, the influence of element division accuracy of the pile-soil system on the LDR of the helical pile is firstly investigated. The number of the pile-soil system division elements is given as 20, 40, 60, and 80, respectively. The other parameters of the pile-soil system are set according to the parameters in Table 1. As shown in Figure 4, when the number of division elements approaches 80, the LDR curves of displacement, BM, and SF of the helical pile tend to be stable. In other words, if the number of pile-soil system division elements is high enough, i.e., \(S=80\) in this study, the calculation results can tend to be convergent. Therefore, unless otherwise specified, the number of pile-soil system division elements is given as \(S=80\) in the following sections.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameters** & **Symbol** & **Value** & **Unit** \\ \hline Pile diameter & \(D\) & 0.3 & m \\ Pile length & \(L\) & 4.5 & m \\ Helical extension ratio & \(D_{0}\)/\(D\) & 1.5 & - \\ Helical inclination angle & \(\varphi\) & 30 & \(\circ\) \\ Helical tooth width & \(b\) & 0.075 & m \\ Dimensionless frequency & \(a_{0}\) & 0.5 & - \\ Elastic modulus of pile & \(E_{\rm p}\) & \(2.0\times 10^{10}\) & Pa \\ Elastic modulus of soil & \(E_{\rm s}\) & \(4.0\times 10^{6}\) & Pa \\ Pile density & \(\rho_{\rm p}\) & \(2.5\times 10^{3}\) & kg/m\({}^{3}\) \\ Soil density & \(\rho_{\rm s}\) & \(2.0\times 10^{3}\) & kg/m\({}^{3}\) \\ Pile’s Poisson’s ratio & \(v_{\rm p}\) & 0.17 & - \\ Soil’s Poisson’s ratio & \(\
u_{\rm s}\) & 0.4 & - \\ Soil’s damping ratio & \(\beta_{\rm s}\) & 0.05 & - \\ External load amplitude & \(Q_{0}\) & 100 & kN \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of pile and soil.
## 3 SiN for Coarse Wavelength Division Multiplexing (CWDM) Optical Transceivers in the O-Band
### SiN-Si Hybrid Grating Fiber Coupler
Varying the various free parameters of the SiN/Si hybrid SPGC in order to minimize the insertion loss of the CWDM band led  
Figure 4: (**a**) Schematic side view of the SiN/Si grating; (**b**) SEM image of the hybrid SiN-Si grating coupler; (**c**) Simulated insertion loss of the apodised Si design (black line), the uniform SiN design (blue line), the best-performing simulated SiSiN design (dashed green line), and the best-performing fabricated SiSiN design (solid green line). (**d**) Same as (**c**), but for the measured designs. to a simulated -1 dB bandwidth of 64 nm (the ng value of 1.58 is very similar to the SiN-only grating) and insertion losses of \(-\)3.0 dB to 5.5 dB (dashed green line). This represents a significant improvement to both the Si-only and SiN-only grating couplers for CWDM applications. The solid green line in Figure 4c shows the simulated transmission spectrum of the best-performing fabricated design, as described below. The various design parameters and simulated transmission characteristics of each SPGC type are summarized in Table 2.  
For a more accurate measurement of grating coupler transmission, a fiber array with height control is used to couple the incident light in a reproducible way across the 200 mm wafer. Figure 4d shows the measured coupling efficiency for the apodised Si design (black line), the uniform SiN design (blue line) and the best-performing SiSiN design (green line). The measurements show good correspondence between the simulated and measured values, the insertion loss values are typically several tenths of dBs higher than the simulated values, which may be accounted for by taking into account reflections caused at the cladding/air and air/fiber interfaces in the measurement. Among the various SiN/Si design variants tested, the design with the lowest insertion losses over the CWDM band had slightly different geometrical parameters compared to the best-performing simulated design (See Table 2). This is presumably due to inaccuracies in the SiN/Si relative mask alignment and slight differences in the simulated and processed grating element morphology. A wafer-scale measurement over 43 dies gives a median minimum insertion loss of \(-\)3 dB with a 3 sigma of 0.46 dB and a median maximum insertion loss over the entire CWDM band of \(-\)5.8 dB with a 3 sigma of 0.77 dB. These results confirm the suitability of this type of SPGC as a reliable wafer-level characterization tool for CWDM components.
## 2 Materials and Methods
### Methods
#### 2.3.2 Sub-Pixel Coastline Extraction  
The boundary between land and water was defined using the Otsu adaptive thresholding method [65]. The Otsu method is regarded the 'gold standard in the field of thresholding', according to [PERSON] et al. (2020) [10] and has been widely used to delineate water/land boundaries [11; 29; 63; 66]. The Otsu threshold works best for bimodal histogram distributions and fails when the histogram is (close to) unimodal [67]. The processing tile generation along the OSM coastline ensures a nearly balanced distribution of land and water within the images. The sub-pixel coastline was calculated using the contour extraction method _skimage.measure.find_contour_ developed by [PERSON] et al. (2014) [68]. It uses the marching squares algorithm with linear interpolation to find an iso-valued contour in a 2D array for a given level value. The Otsu threshold was used as the level value to find the iso-valued contour in the MNDWI images. Contour extraction methods aim at finding the boundary between two classes on a two-dimensional surface. When extracting a subpixel contour from a continuous water index image, it is assumed that medium resolution pixels along the land-water boundary represent mixed pixels and that the pixel value directly represents its proportion of land and water [33]. The _find_contour_ method linearly interpolates between the water index values of neighboring pixels to draw the precise location of the waterline according to the given threshold [34]. An example of the sub-pixel contour, compared to a whole-pixel contour approach, is shown in Figure 4.  
Short coastline fragments with a length of 3 km or less were removed from the coastline dataset to reduce noise and processing effort. The minimum length of 3 km was chosen for two reasons: (i) it had to be large enough to exclude small land and water features such as ships or aquaculture ponds that have a circumference of 2 km on average [69] and (ii) it allowed for detection of features small enough to preserve interrupted coastlines, sand banks, and other features that might be of interest for understanding coastline change processes.
# A Model-Based Investigation of the Performance Robustness of the Deflector Jet Servo Valve
## 6 Further Analysis and Discussion
### Tendency Analysis of DJV Robustness against Errors
#### 6.4.3 Measures to Enhance Consistency of Product Performance  
The theoretical model has provided quantitative information for drifts of the DJV pressure indices and predictions about robustness tendency. The above analyses show that to avoid the inconsistency issues of servo valve products, the machining accuracy of the shunt wedge is worthy of more concern and a non-negative error of the deflector jet distance should be ensured.  
Specifically, a less than 1% fluctuation of the balance pressure can be expected if the width error of the shunt wedge is limited between \(-0.6\)\(\upmu\)m and \(0.6\)\(\upmu\)m. Additionally,  
Figure 28: Pressure gain robustness against deflector installation error.  
Figure 29: Pressure gain robustness against width error of shunt wedge.  
the design value of the deflector jet distance can be moderately increased to improve the robustness of the pressure indices.
## 3 Data and Processing Strategy
Owing to inter-system bias, we estimated the individual receiver clock for GPS and GLONASS. The common zenith tropospheric delay was estimated as a piecewise constant every 60 min. We used C1 and P2 code observations for GLONASS for the reference network, whereas for the rover receivers either C1 or P1 can be used with P2 observations. We divided the daily observations into 24 pieces of hourly sets, and PPP-IAR was performed using a simulated kinematic model for each hourly dataset. Daily static PPP-IAR was first performed for each rover station to attain the \"true\" ambiguity, which could be used to assess the correctness of hourly PPP-IAR in the kinematic model. The LAMBDA method was used to search for integer NL ambiguity, and the ratio test used to validate ambiguity resolution with a threshold of 2 [31]. The initial fixing time in each hourly session was recorded and analyzed. We further calculated the cumulative distribution of the initial fixing time, obtaining the fixing rate for different observation durations. To fully assess the effectiveness of the proposed method for different receiver types, we analyzed the fixing percentage as a function of the conducted stations. Since we used only one day of data to generate the IFCB corrections, to analyze its effectiveness, we also analyzed the fixing percentage on each of the 21 days.
## 3 Results and Discussion  
### Physical and Chemical Characteristics of the Selected Materials  
The powder of Apuan Alps white marble, the Portland cement, and the normalized sand are characterized by different particle-size distribution. As shown in Figure 3, Portland cement and marble powder are finer than the normalized sand.  
Before mixing, marble powder was dried at room temperature for 48 h. Chemical composition and specific gravity of the mortar components were examined before mixing (Table 4).  
Figure 3: Particle-size distribution of (**a**) Marble powder, (**b**) Portland cement, and (**c**) Normalized sand, according to EN 196-1 [53].  
In Figures 4 and 5, XRPD and TG/DSC analyses of white marble powder (M) are shown. The crystalline phases identified through XRPD are essentially calcite, and traces of quartz, feldspars, and phyllosilicates for the total sample, and muscovite, quartz, K-f feldspar, plagioclase, and pyrite for the insoluble residue (R), which amount to less than 0.2 wt.% of the total sample. TG/DSC analysis confirms that the analyzed marble powder is a calcite-rich material (loss on ignition = 44.01 wt.% in the range 105-950 \({}^{\circ}\)C).
# Smart Routing for Sustainable Supply Chain Networks: An AI and Knowledge Graph Driven Approach
## 4 Use Case
### Strategic Benchmarking of Sustainability Options  
To demonstrate the strategic decision-support capabilities of the IAES application, the enriched KG was queried to identify the best route between two production plants. The benchmark analysis focused on three scenarios: (1) the minimization of carbon emissions, (2) the minimization of costs, and (3) the minimization of duration.  
As illustrated in Figure 9, the route optimized for cost and emissions (154.88 kgCO\({}_{2}\)/kg) followed a classic intermodal configuration: road \(\rightarrow\) sea \(\rightarrow\) sea \(\rightarrow\) road. This path represents a plausible, low-carbon option leveraging high-volume maritime transport. In contrast, the fastest route utilized an air-focused multimodal chain, achieving a total duration of only 13.83 h. However, this gain in time came at a significant cost: 2753.69 EUR/kg in transport cost and 4131.06 kgCO\({}_{2}\)/kg in associated emissions. However, the input data used for this test case was based on semi-realistic values.
## 4 Detailed Design
### Social Tie Classifier System
#### 4.1.1 Nodes' Acquaintances Mechanism
NAM calculates the similarity between \(u_{i}\) and \(v_{i}\) as follows:  
\[similarity_{u_{i},v_{i}}=cos(\theta)=\frac{u_{i}\times v_{i}}{||u_{i}||\times ||v_{i}||}, \tag{4}\]  
Figure 2: History of encounters between nodes 13 and 22 in the Sassy Scenario. According to the self-reported friendship, they are not friends. However, they meet each other frequently, as shown above. where \(||u_{i}||\) and \(||v_{i}||\) represent the dot product of the vectors \(u_{i}\) and \(v_{i}\). To determine if a pair of nodes are acquaintances of each other, we set up a threshold \(\gamma\) of 0.7. If the value of Equation (4) for the nodes \(n_{x}\) and \(n_{y}\) is non-zero, and it is greater than or equal to \(\gamma\), they are acquaintances of each other. For example, taking into account the history of encounters shown in Figure 2, and data from the weeks 1 (\(u_{i}\) = (5, 2, 22, 10)), and 2 (\(v_{i}\) = (5, 1.5, 22, 10)), the FSF nodes' acquaintanceship discovery will rely on the following steps:  
* Calculate \(u_{i}\times v_{i}=(5\times 5)+(2\times 1.5)+(22\times 22)+(10\times 10)=611\),
* Calculate \(||u_{i}||=((5^{2})+(2^{2})+(22^{2})+(10^{2}))^{0.5}=24.75\),
* Calculate \(||v_{i}||=((5^{2})+(1.5^{2})+(22^{2})+(10^{2}))^{0.5}=24.71\),
* Calculate \(cos(\theta)\) according to Equation (4) = \(\frac{611}{||24.75||\times||24.71||}=0.99\). Thus, in this example, nodes \(||u_{i}||\) and \(||v_{i}||\) are acquaintances of each other. Finally, in this work, the difference between \(T_{i}\) and \(T_{i+1}\) depends on the scenario. Table 1 includes the \(T\) values used in the different scenarios evaluated.