esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Fabrication Process and Waveguide Performances
### SiN Waveguide Optical Characterization
\begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{**Waveguide**} & \multirow{2}{*}{**Si Rib**} & \multirow{2}{*}{**Si Strip**} & \multirow{2}{*}{**SiN PECVD**} & \multicolumn{2}{c}{**Si\({}_{3}\)N\({}_{4}\)**} & \multirow{2}{*}{**SiN PECVD**} & \multirow{2}{*}{**SiN\({}_{4}\)**} \\  & & & **1310 nm** & & & **1 PCVD** & **940 nm** \\ \hline dimension w \(\times\) h (\(\upmu\)m) & 0.4 \(\times\) 0.3 & 0.35 \(\times\) 0.3 & 0.7 \(\times\) 0.6 & 0.75 \(\times\) 0.75 & 0.6 \(\times\) 0.3 & 0.6 \(\times\) 0.3 \\ Propagation Loss (dB/cm) & 1.5 & 3.6 & 0.8 & 1.5 & 1.5 & 1.0 \\
3 sigma (dB/cm) & 0.45 & 0.9 & 0.3 & - & - & 0.4 \\ \hline \end{tabular}
\end{table} 
Table 1: Si and SiN waveguide properties and propagation losses. Figure 2: (**a**) SiN ring resonance shift against T. Each color represents a measurement at a different temperature, from 25 \({}^{\circ}\)C to 80 \({}^{\circ}\)C. The resonance shift with temperature allows to extract the SiN thermo-optic coefficient \(\alpha\) = 1.7 \(\times\) 10\({}^{-5}\) K\({}^{-1}\). (**b**) Measured spectrum of the Si-SiN transition insertion loss. Inset: side view of the transition with the optical mode from a BPM simulation. (**c**) Wafer mapping of the transition insertion loss (in mdB). Inset: histogram of the wafer level insertion loss. The median value is 0.09 dB and the standard deviation is 0.01 dB. dimension of the high index waveguide to lower its effective index below the effective index of the low index waveguide. Due to the large index difference between Si and SiN, index matching requires narrowing the Si waveguide down to the smallest width allowed by the design rules. In addition, our multi-level Si platform also allows narrowing the Si waveguide height to a thickness of 150 nm. Therefore, we designed a Si-SiN transition based on inverse tapers of Si and SiN using a tip width at the minimum dimension permitted by the design rule i.e., 120 nm in Si and 200 nm in SiN, with a Si height of 150 nm and a length of 150 \(\upmu\)m. A side view of the optical power profile after beam propagation method (BPM) simulation is shown in the inset of Figure 2b. From up to 90 cascaded Si-SiN transitions, we extract the single transition spectrum shown in Figure 2b. It shows a particularly flat spectrum, with a 0.09 dB insertion loss over the 1260-1350 nm range. Figure 2c, the wafer map of this measurement indicates very uniform performances of the transition with a median insertion loss of 0.093 dB and a 3 sigma of 0.04 dB. We believe this good uniformity is due to the well-controlled SiO\({}_{2}\) interlayer thickness. Included in this value is the insertion loss (measured at 0.02 dB) of the transition from 300-nm-thick to 150-nm-thick Si waveguides, which is 30 \(\upmu\)m long. The total insertion loss of the transition is comparable to the normal propagation losses of an equivalent length of waveguide.
## 4 Designing Sensors for Soft Robots
### Optic Fibre Based Pose Sensor Design
The magnets, with their reflective surfaces, are connected to the wires travelling up through the flexible module of the robot. For each of the three fibre pairs, the two fibres (for transmission and reception) are held parallel and in contact with one another, by a small plastic guide. Additional, non-moving magnets are introduced in the rigid section to ensure, by repulsion and attraction, that the moving magnets are kept as close as possible to the tips of the three fibre pairs with the pose measurement wires being kept taut.
# Vibration Properties of Dual-Rotor Systems under Base Excitation, Mass Unbalance and Gravity
## 1 Introduction
[40] employed a component mode method to the dynamic analysis of large flexible rotor systems and a two-spool test rig was used to illustrate the capability and versatility of the component mode method. [PERSON] et al. [41] investigated the critical speeds, mode shape and unbalance responses both numerically and experimentally. The results are in reasonable agreement and show the appearance of a cross-excitation between the inner and outer shafts. [PERSON] et al. [42] used a simple model of non-symmetric co-axial co-rotating or counter-rotating rotors to give analytical expression of the critical speeds, mass unbalance responses and sense of whirl. [PERSON] et al. [43] showed two methods to compute the critical speeds for a co-rotating dual-rotor system that has different advantages. In addition, the speed ratio and intershaft bearing stiffness were found out to be two important factors for the dynamic behavior of the system. [PERSON] et al. [44] examined the dynamics of a dual-rotor system both experimentally and numerically, and pointed out that taking into consideration the tilt stiffness in the system can improve the theoretical model. [PERSON] et al. [45] put forward a critical speed prediction method (similar to that of [PERSON] [43]) for a dual-rotor system based on the finite element method. Moreover, a vibration mode selection technique was presented to identify the backward and forward whirling modes. Few studies have included base motions in the dynamic behavior analysis of a dual-rotor system. [PERSON] et al. [46; 47], though, did develop a dynamic model that included mass unbalance and base motions, using the Lagrange principle and finite element method. Steady-state characteristics during stable operation, and transient characteristics during the start-up of the co-rotating dual-rotor system were investigated adequately. Constant base rotation, harmonic translation and mass unbalance were the major forces involved in the investigation. However, the counter-rotating type for the dual-rotor system and excitations from gravity were not taken into account. In a word, the synthesized influences of base motions, mass unbalance and gravity on the dynamic behavior of counter-rotating dual-rotor systems still lack in-depth investigation. Therefore, this article develops a general model for such a dynamic analysis under six degrees of base motions based on the Lagrange principle and finite element method and using Timoshenko beam elements to model the shaft. Constant base rotation, harmonic base translation, mass unbalance force and gravity were taken into account. The natural properties and harmonic responses of the counter-rotating dual-rotor system are analyzed in detail.
# Adsorption of Ammonium, Nitrate, and Phosphate on Hydrochars and Biochars
## 2 Materials and Methods
### Adsorption of NH\({}_{4}\)+, NO\({}_{3}\)\({}^{-}\), and PO\({}_{4}\)\({}^{3-}\)
#### 2.3.2 pH Effect  
In order to determine the effect of pH, 0.5 g of an adsorbent material was mixed with 100 cm\({}^{3}\) of a solution containing 100 mg\(\cdot\)dm\({}^{-3}\) of either NH\({}_{4}\)+, NO\({}_{3}\)\({}^{-}\), or PO\({}_{4}\)\({}^{3-}\). Before adding the biochar, the pH of the solutions was adjusted to lie within the range of 3 to 9. Using a PHM 84 pH metre equipped with glass REF 451 and calomel pHG 201-8 electrodes, this was accomplished. For every pH measurement, a unique experimental setup was established. The suspensions were agitated for 24 h on an agitator operating at 250 revolutions per minute and a temperature of 25 \({}^{\circ}\)C. Each sample was filtered using a paper filter with a pore size of 0.5 micrometres. The pH of the subsequent filtrate was then measured. The concentrations of NH\({}_{4}\)+, NO\({}_{3}\)\({}^{-}\), and PO\({}_{4}\)\({}^{3-}\) were measured using the previously described method.  
Equation (1) was utilised to determine the equilibrium adsorption capacity:  
\[q_{e}=\frac{V(C_{0}-C_{e})}{m} \tag{1}\]  
where \(q_{e}\) is the adsorption capacity at equilibrium (mg\(\cdot\)g\({}^{-1}\)); \(V\) is the volume of the solution (dm\({}^{3}\)); \(C_{0}\) and \(C_{e}\) are the initial and equilibrium concentrations of NH\({}_{4}\)+, NO\({}_{3}\)\({}^{-}\), and PO\({}_{4}\)\({}^{3-}\) (mg\(\cdot\)dm\({}^{-3}\)); and \(m\) is the weight of the adsorbent (g).
## 3 Data and Methods
### Research Methods
#### 3.2.3 Ef-Npp  
After the invention of ecological footprint analysis, some scholars suggested that the consumption of natural capital in ecological footprint analysis is actually the occupation of NPP [36]. By integrating NPP into the ecological footprint framework, EF-NPP was proposed by [PERSON] and [PERSON] in 2008 [21]. They refined the ecological footprint by changing the equivalence factors to NPP rather than agricultural productivity in order to achieve a more precise ecological footprint. In contrast with the traditional ecological footprint, in EF-NPP, when calculating the ecological capacity, we use a deduction of 13.4% to protect biodiversity.  
The equivalence factor is the coefficient that converts the bio-productive land into areas with the same ecological productivity, and the yield factor is the coefficient that describes the yield difference between the study area and the nation overall. The equivalence factor and yield factor in EF-NPP can show the different productivity of different land types or different areas directly. According to earlier researches, the formulas of the equivalence factor and yield factor are as follows [36; 37]:  
\[\lambda_{i}=\frac{NPP_{i}}{NPP} \tag{3}\]  
where \(\lambda_{i}\) is the equivalence factor, \(NPP_{i}\) is the average NPP of \(i\)-type bio-productive land in the study area, and \(NPP\) is the average NPP of all types of bio-productive land in the study area.  
\[y_{i}=\frac{NPP_{i}}{NPP_{i}} \tag{4}\]  
where \(y_{i}\) is the yield factor, \(NPP_{i}\) is the average NPP of \(i\)-type bio-productive land in the study area, and \(\overline{NPP_{i}}\) is the average NPP of \(i\)-type bio-productive land in China.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Bio-Productive Land** & **Consumption Item Type** \\ \hline \multirow{2}{*}{Cultivated land} & cereals, beans, potatoes, cotton, oilseeds, sugar, vegetable and \\  & melons, hemp, tobacco \\ Forestland & silkworm cocoons, fruits, chestnuts, ginkgo \\ Grassland & pork, beef, lamb, poultry, rabbit, milk, sheep, eggs, honey \\ Water area & aquatic products \\ Fossil energy land & coal, oil, natural gas \\ Built-up land & electricity \\ \hline \hline \end{tabular}
\end{table}
Table 1: Consumption items of the national hectare ecological footprint model.
# Millimeter-Wave High-Gain Dual-Polarized Flat Luneburg Lens Antenna with Reflection Cancellation
## 3 Flat Luneburg Design and Implementation
### Dual-Polarized FLLA  
The designed FLL was excited with the dual-polarized stacked microstrip patch antenna, and its simulated results are shown in Figures 9 and 10. Since the two ports of the feeding antenna are symmetrical to each other, only the results corresponding to port-1 are provided for brevity. Figure 9 shows the simulated \(S_{11}\) and gain of the FLLA comparing with the counterparts of its feed only. It can be seen that although the \(S_{11}\) of the FLLA shifted up, it was still smaller than \(-10\) dB, achieving a bandwidth of 26.1-32.6 GHz, similar to that of the feeding stacked patch antenna. Meanwhile, the gain of FLLA significantly improved comparing to that of feed only, and it varied within 16.5-19.5 dBi over the impedance bandwidth. Figure 10 provides the simulated radiation patterns on either the E- or H-plane of the FLLA under excitation of port-1 (results of port-2 are omitted for brevity), at 27, 29, and 31 GHz, respectively, which compare with those of feed only as well. The FLL concentrated the electromagnetic waves radiated by the feeding antenna into a narrow beam in both E- and H-planes, proving its 2D focusing ability. The 3 dB beam-widths in the E- and H-plane were around 16.5\({}^{\circ}\) and 16.2\({}^{\circ}\), respectively. The cross-polarization levels  
Figure 8: Investigation of air interval in-between substrate layers of FLL performance: (**a**) \(S_{11}\) and gain, (**b**) FTBR.  
Figure 7: Illustration of reflection cancellation phenomenon in a two-layer structure.  
were \(-18.5\) dB in the main lobe over the bandwidth. Meanwhile, the FTBRs were greater than \(19.5\) dB at all three frequencies, certifying that the reflection caused by the FLL was successfully suppressed.  
Figure 10: _Cont._  
Figure 9: Simulated results of the FLLA: (**a**) \(S_{11}\) and gain, comparing with those of feed only, (**b**) model with 3D radiation pattern.  
Furthermore, to demonstrate the beam scanning ability of the designed FLLA, the FLL was excited by moving the feeding patch antenna in the transverse plane either vertically or horizontally. Without loss of generality, the scanned beams in the E- and H-planes when port-1 is excited were simulated, as shown in Figure 11. The steering angles in the E-plane were 0\({}^{\circ}\), \(\pm\)7\({}^{\circ}\), \(\pm\)15\({}^{\circ}\), \(\pm\)22\({}^{\circ}\), and \(\pm\)29\({}^{\circ}\), corresponding to the feeding antenna's shifts of 0, 0.35, 0.7, 1.05, 1.2 mm in the E-plane, respectively. The steering angles in the H-plane were 0\({}^{\circ}\), \(\pm\)6\({}^{\circ}\), \(\pm\)13\({}^{\circ}\), \(\pm\)23\({}^{\circ}\), and \(\pm\)26\({}^{\circ}\), corresponding to the feeding antenna's shifts of 0, 0.35, 0.7, 1.05, 1.4 mm in the E-plane, respectively. The largest scanning angle in either E- or H-plane was determined using a criterion of 3 dB gain loss.
## 5 Simulation Results
### Turn-On Analysis  
As far as the \(T_{\text{HS}}\) turn on is concerned, if the high-side transistor is driven sharply and no damping technique is exploited, i.e., \(L_{\text{s}}=0\), the switching waveforms obtained from the time-domain simulation of the circuit in Figure 7, are shown in Figure 8 by plus markers. Indeed, both the switching current (\(i_{\text{sw}}\)) and voltage (\(v_{\text{sw}}\)) are affected by oscillations at \(f_{\text{e,on}}\approx 60.5\,\text{MHz}\). The corresponding \(v_{\text{DS}}\) voltage is not monotonic due to the \(L_{\text{s,0}}\) parasitic, which is however not sufficiently large to damp the oscillations. If an extra source inductance (\(L_{\text{s}}\)) is added, both the peak and the damping factor decrease with respect to the oscillating case, as for \(L_{\text{s}}=4\,\text{nH}\) (circle markers), \(12\,\text{nH}\) (square markers) and \(20\,\text{nH}\) (diamond markers). From such plots, it can been noticed that the higher the \(L_{\text{s}}\) is, the more the \(v_{\text{DS}}\) voltage increases during the transient as the gate current is negative for a longer time. At the same time, the \(v_{\text{sw}}\) rise time and the \(i_{\text{sw}}\) peak, which is needed to charge the equivalent low-side capacitance to \(V_{\text{PS}}\), both decrease as \(L_{\text{s}}\) increases. Finally, from the comparison of the \(4\,\text{nH}\) and \(12\,\text{nH}\) curves, it results that a higher \(L_{\text{s}}\) value does not imply a more damped oscillation. All such aspects suggest one that the optimal value of source inductance for the simulated converter is in between \(4\,\text{nH}\) (circle markers) and \(12\,\text{nH}\) (square markers), as the rise time of \(v_{\text{sw}}\) is not significantly affected by the source inductance and the oscillations are strongly reduced with respect to the oscillating case.
# An Outdoor Navigation System for Blind Pedestrians Using GPS and Tactile-Foot Feedback
## 4 Evaluation
### Experiment II: Outdoor Navigation
#### 4.2.3 Results
They also stated that there was no point in displaying 'turn left or right' and then 'forward', because it can be deduced that after turning one continues forward. This is true in all cases; the directions in E-1 can be further reduced to 7, while the E-2 path can be completed by displaying only 12 directions. The results are undoubtedly encouraging. They confirm that the prototype and its modules are operational and suggest that it is feasible to exploit GPS and tactile-foot stimulation for assisting outdoor navigation of blind pedestrians.
# Quantitative Assessment of Upper- Limb Volume: Implications for Lymphedema Rehabilitation?
## 6 Clinical Applications and Implications
### Research and Outcome Measures  
Volumetric assessment methods are essential tools in research studies focused on lymphedema. These methods provide quantitative data that can be used to evaluate the efficacy of new treatment modalities, compare different interventions, and assess the long-term outcomes of management strategies [43]. Standardized volumetric measurements can serve as objective outcome measures, facilitating the comparison of study results and the pooling of data across research centers [38].  
Furthermore, volumetric assessment can contribute to developing and refining staging systems and classification schemes for lymphedema [1, 45, 71]. By quantifying the extent of edema, researchers can explore correlations between limb volume and clinical indicators, such as symptom severity, functional limitations, or QoL measures [86]. These findings can inform the development of comprehensive assessment tools and help establish evidence-based guidelines for lymphedema management [87].  
In summary, volumetric assessment methods have significant clinical applications and implications in managing upper-limb lymphedema. Integrating accurate and reliable volumetric assessments into clinical practice can improve patient care, enhance treatment outcomes, and advance our understanding of lymphedema. On the other hand, several challenges are still open and emerging technologies might overcome barriers in a more precise volumetric assessment of upper-limb lymphedema, improving rehabilitation outcomes in people suffering from this disabling condition.
# Effective Dereverberation with a Lower Complexity at Presence of the Noise
## 1 Introduction
The Kalman filter-based dereverberation algorithm that combines the MCLP and the GSC, known as the integrated sidelobe cancellation and linear prediction (ISCLP), has also shown good performance [12]. This method not only reduces the complexity of simply cascading the MCLP and beamforming, but also improves the performance. However, in the ISCLP, estimating linear prediction coefficients with the Kalman filter needs to consider the initialization of the Kalman filter parameters [17; 18; 19]. These parameters, such as the power spectral density (PSD) of the target signal, are critical to the performance of the algorithm. Some related dereverberation methods [20; 21; 22; 23] also heavily rely on the PSD estimation of the speech signal. This paper proposes a dereverberation algorithm by combining the complex Gaussian mixture model (CGMM)-based MVDR (CGMM-MVDR) beamforming [24] and the linear prediction Kalman filter. In this algorithm, the spectral model based on the CGMM is used to estimate the time-frequency masks of the covariance matrix of the target speech and the steering vector. The covariance matrices of the target speech and noise are estimated through the time-frequency masks while considering the noise only, where the eigenvector corresponding to the maximum eigenvalue of the covariance matrix of the target speech is an estimation of the steering vector of the MVDR beamforming. At the same time, the main diagonal elements of the covariance matrix of the target speech are considered as the estimated PSD of the target speech, which are also required by the Kalman filter. Since this method can obtain a more reasonable estimation for the parameters, the performance of dereverberation is better than the ISCLP. In addition, the low-complexity version of the proposed method is proposed as well, in which the multichannel linear prediction coefficients are expressed in terms of the spatial filter and the interframe filter by using the Kronecker product. By determining the spatial filter, the Kalman filter is used to estimate the interframe filter. Since the dimension of the interframe filter is lower than that of the original multichannel linear prediction filter, the size of matrices in the Kalman filter also decreases so that the amount of calculation is greatly reduced. Experiments show that this method can effectively reduce computational complexity and obtain relatively good results. In the following parts, we arrange the paper as follows. In the Section 2, we briefly introduce the signal model of the CGMM-based MVDR beamformer and the related linear prediction model. In the Section 3, we present the proposed method by combining the CGMM-based MVDR beamformer and Kalman filter. In the Section 4, we show and analyze the experimental results. Finally, we conclude our method.
# SC-FDE Layer for Sensor Networks in Remote Areas Using NVIS Communications
## 6 Results
### CR Sweep 25 W  
Figure 10 presents the results of the CR sweep for a peak power of 25 W. The point here is that the changes compared to 12 W were not that significant. For the low CR values,  
Figure 8: 6 W SC-FDE CR sweep CDF.  
Figure 9: 12W SC-FDE CR sweep CDF.  
the increase of the performance was relevant. By contrast, the high values did not change so much.  
Results from Figure 10 show that 25 W is not worth implementing due to the higher consumption and near-identical behavior of 12 W. Comparing the three power scenarios, the BER-consumption ratio makes the 12 W the best configuration, saving the 6 W for more ideal scenarios without large multipaths or almost-null noise.