esa-sceva/satcom-chunk-collection huggingface dataset:
# Efficient FPGA Implementation of an ANN-Based Demapper Using Cross-Layer Analysis
## 6 Comparison  
### Comparison to State of the Art FPGA-Based Training  
As discussed in Section 2.2, there already exist some frameworks to efficiently map the ANN training flow to FPGA. The hardware metrics of the presented works are shown in Table 1. From the shown results, we can directly tell that [22; 23; 29; 30] target applications, where the main focus is to increase the throughput of the accelerator, result in high dynamic power consumption. This would violate the requirements of our application, because many communication algorithms are implemented on power-constrained embedded systems with limited energy budget, such as smartphones or internet of things (IoT) devices. The only related work that could satisfy the constraints of our application is [31]. Although its focus is on CNNs while our ANN architecture is based on fully-connected layers, it is still comparable to our approach as it targets low-latency and low-power. Based on the presented results, they report higher power consumption (0.67 compared to 0.568 W), lower throughput (4.39 compared to 5.28 GOPS) and 67% lower energy efficiency compared to our approach.
## 3 Results and Discussion
### Effect of Current Intensity on Cell Morphology, Viability, and ROS
In this study, the mean cell diameter of untreated control cells (25.5 \(\pm\) 4.1 \(\upmu\)m) remained unchanged compared to that of the initial cells (25.1 \(\pm\) 4.2 \(\upmu\)m) owing to the short 4 h incubation duration. Notably, all electrotreated microalgal cells exhibited a significant increase in mean cell diameter, irrespective of the current intensity, compared with that of the control group. The mean cell diameter peaked at 34.2 \(\pm\) 4.0 \(\upmu\)m (34.3% higher than that of the control) at  
Figure 5: Effect of current intensity (5, 10, 20, and 30 mA) on the relative cell viability (**a**), reactive oxygen species (ROS) content (**b**), and mean cell diameter (**c**) of _Haematococcus lacustris_ after electrotreatment for 4 h. The relative value (%) is presented compared to that of the untreated control (100%). The error bars for (**a**,**b**) represent the standard deviations of four samples, and those for (**c**) represent at least 100 cells randomly measured in two independent electrochemical experiments. *\(p<0.05\) and ***\(p<0.001\). 10 mA. However, the microalgal cells treated at higher current intensities of 20 and 30 mA had smaller mean cell diameters than those treated with lower intensities of 5 and 10 mA. This reduction in volume may be associated with microscopic morphological damage, such as the extracellular release of intercellular materials through damaged cell walls. Cell wall damage may be related to reduced cell viability, as determined by staining with trypan blue [18; 30; 31] (Figure 5a). The increase in the mean cell diameter (Figure 5c) or volume expansion of the microalgal cells under beneficial electrotreatment conditions may be related to the enhanced AXT content (Figure 4). Notably, AXT in _H. lacustris_ is predominantly present in lipid bodies, mainly in the form of mono- and diesters with high fatty acid contents [43; 44]. Similar concurrent increases in cell size and neutral lipid content have been reported in microalgae exposed to oxidative stress; however, the underlying mechanisms remain unclear. [PERSON] et al. [45] observed an increased biovolume in _Chlamydomonas reinhardtii_ in response to oxidative stress caused by H\({}_{2}\)O\({}_{2}\), correlating with an elevated lipid content. [PERSON] et al. [28] reported simultaneous increases in cell size and neutral lipid content in _Chlorella_ after a similar 4 h electrotreatment. To gain deeper insight into the morphological transformations, including changes in cell size and cell wall structure, occurring in _H. lacustris_ during electrostimulation, more extensive biochemical investigations are necessary.
# Structural, Thermal and Mechanical Assessment of Green Compounds with Natural Rubber
###### Abstract
Our proposal is using a technique based on a thermomechanical treatment with the addition of BPO (peroxide of benzoyl) as a chemical agent, combined with microwave irradiation. This process, moderately energy consuming, can provide an alternative to other systems of reclaiming/devulcanizing, either from economical or environmental perspectives. The use of combined processes, thermomechanical and microwave, as a devulcanization method has been proposed and used by our group in previous experiments with ethylene propylene diene monomer rubber (EPDM) [10] and ground tire rubber (GTR) [11]. The idea behind the application of this combined process consists in breaking the crosslinking of the vulcanized rubber through mechanical action (more aggressive and therefore less specific on the disulfur bridges) for a short period of time and then heating the sample with microwaves (more selective on the bonds -S-S-). The selectivity of microwave systems stems from their ability to generate a precise, rapid and uniform temperature increase, surpassing conventional heating methods like convection or conduction. The microwave process has been used by different research groups. [PERSON] et al. used thermogravimetric analysis to study the changes that occur in rubber vulcanizates: natural rubber (NR), styrene butadiene rubber (SBR) and EPDM [12]. [PERSON] et al. analyzed the chemical and physical changes in GTR after various periods of microwave exposure [13; 14]. [PERSON] et al., in a previous work, studied the chemical structure of different types of GTR and the influence of their components and formulations on microwave devulcanization [15]. In this study, we examine the devulcanization of ground tire rubber (GTR) using a combined process applied to samples derived from two main sources: car tires and truck tires subjected to varying periods of microwave irradiation (0, 3, 5 and 10 min). The devulcanized GTR was then blended with natural rubber (NR) and underwent a new vulcanization process, simulating recycling for a novel application. The GTR was mixed with NR in proportions of 0, 10, 30, and 50 parts per hundred rubber (phr). The macroscopic properties and microstructural changes of these rubber compounds were investigated through analysis of their thermal properties, mechanical properties and morphology. The results were compared under identical manufacturing conditions with fresh natural rubber. This study aims not only to describe the behavior of these samples but also to provide insights into how the treatment affects the molecular chains of the polymers involved.
## 2 Materials and Methods
### Data Processing and Analysis
#### 2.3.2 Perceptual Evaluation Procedures  
Moreover, the recordings were perceptually evaluated by five native speakers of Hong Kong Cantonese who did not exhibit tone merging. The listeners were all born and raised in Hong Kong and spoke Hong Kong Cantonese as their only L1. None of the listeners attended the recording session or were familiar with the speakers. The speech samples collected from the production experiment were first randomised and then presented to the native listeners, who were asked to judge the tones by selecting the corresponding Chinese characters in a six-alternative forced-choice question based on their native speakers' intuition (each character representing one tone). Instead of the six tones, Chinese characters were adopted in the evaluation because the Cantonese tonal system is not explicitly taught in Hong Kong. Native speakers usually acquire the Cantonese tonal system through exposure rather than any formal instructions. Consequently, native speakers of Hong Kong Cantonese are not familiar with the tonal system and may not be able to determine the tone categories accurately.  
During the evaluation, the native listeners were allowed to listen to each stimulus as many times as they needed, and there was no time limit for the evaluation. In total, 9840 judgement trials (1968 tokens \(\times\) 5 listeners) were collected from the 5 listeners, and the judgements were further coded in two ways. They were first coded as either correct or incorrect production of tones for statistical modelling as will be described below. In addition to that, the judgements were also coded as tone numbers (such as T1, T2, etc.) to make it possible for further error analysis. To confirm the consistency among the listeners, the intraclass correlation coefficient (ICC) was calculated with the Mangold ICC calculation software (Version 2015) [41]. Tone numbers as judged by the five listeners were used in the ICC calculation, and the agreement of the judgement data was 89.5%, suggesting high inter-rater reliability among the five listeners. Thus, the judgement data from all five listeners were included in the subsequent statistical analysis.  
Generalised linear mixed-effects models (GLMMs) were used to analyse the perceptual evaluation data, with _response_ (two levels: incorrect vs. correct) as the dependent variable, _group_ (two levels: native vs. immigrant) and _tone_ as independent variables, and _speaker_ and _listener_ as random intercepts. An interaction between _group_ and _tone_ was included as the production accuracy of the six tones may vary within each group. The GLMMs were implemented with the 'lme4' package [42] in R. Likelihood ratio tests were performed to check the significance of predictors, with the threshold of _p_-values being set at 0.05.
# Real-Time Terrain-Following of an Autonomous Quadrotor by Multi-Sensor Fusion and Control
###### Abstract  
For the application of the autonomous guidance of a quadrotor from confined undulant ground, terrain-following is the major issue for flying at a low altitude. This study has modified the open-source autopilot based on the integration of a multi-sensor receiver (a Global Navigation Satellite System (GNSS)), a Lidar-lite (a laser-range-finder device), a barometer and a low-cost inertial navigation system (INS)). These automatically control the position, attitude and height (a constant clearance above the ground) to allow terrain-following and avoid obstacles based on multi-sensors that maintain a constant height above flat ground or with obstacles. The INS/Lidar-lite integration is applied for the attitude and the height stabilization, respectively. The height control is made by the combination of an extended Kalman filter (EKF) estimator and a cascade proportional-integral -derivative (PID) controller that is designed appropriately for the noise characteristics of low accuracy sensors. The proposed terrain-following is tested by both simulations and real-world experiments. The results indicate that the quadrotor can continuously navigate and avoid obstacles at a real-time response of reliable height control with the adjustment time of the cascade PID controller improving over 50% than that of the PID controller.  
Quadrotor; terrain-following; dynamic models; navigation system; multi-sensor estimation 2021
## 5 Boom Configuration Optimization
### Results  
#### 5.3.1 Cost Function Comparison  
For the boom configuration optimization, an approximation of the exact cost function will be used due to run time reasons, as mentioned in Section 5. The approximation only concerns the material and welding costs of the metal sheets and not the stiffeners.  
For the comparison of the approximated and real cost functions, the number of segments was chosen to lie between 4 and 23 (yielding lengths of the middle sections between 9001 mm and 69,000 mm). For each number of segments, 2000 valid boom configurations were randomly generated and the exact and approximated costs were calculated. The results are shown in Figure 6.  
Overall, the approximated cost function underestimates the exact costs slightly, however, it yields very good results in terms of ordering the solutions. The same holds when looking at the material and welding costs separately, see the respective graphs in the Supplementary Materials.  
The reason for the underestimated costs is two-fold. On the one hand, the material cost is underestimated since for the true cost function the segments are collected to longer plates also if they are of different thicknesses, and the final plates have the thickness of the thickest segment they span. This also leads to a certain underestimation of the welding costs, since seams of thicker plates are more expensive than of thinner plates. On the other hand, the welding costs of the true cost function include additional factors for testing certain seams using ultrasonic and magnetic particle inspections, which are not included in the approximated cost function.  
Figure 6: Comparison of cost approximations for metal sheets; the colors indicate the number of segments, starting at the bottom left with 4 segments (dark blue) to the top right with 23 segments (yellow).
## 2 Materials and Methods
### Procedure  
Motion data for the side-cutting task were collected using a Vicon motion capture system (Vicon Metrics Ltd., version 2.14.0, Oxford, UK), comprising eight cameras to track movements. Thirty-eight reflective markers (12.5 mm in diameter) were placed on each participant's body (Figure 1) [25; 26]. Kinetic data during the cutting maneuvers were gathered using an AMTI force plate (Watertown, MA, USA), positioned at the center of the runway and sampled at a frequency of 1000 Hz. Changes in biomechanical parameters were analyzed using musculoskeletal modeling (Gait 2392) (Figure 1A) [27]. Participants were instructed to perform three distinct side-cutting technique tasks, running at a speed of 4-4.5 m/s from a distance of 6 m to a force measurement platform [28]. All subjects landed on the forefoot of the right foot, with speed measured by an infrared timer located near the force plate. A 1 m-wide path, marked at a 45\({}^{\circ}\) angle, was used to guide participants during the stopping phase (Figure 1B,C). Each participant completed seven trials for each of the three conditions. A 10 min warm-up preceded the experiment, and a 2 min rest interval was provided between each side-cutting technique condition.  
Figure 1: Overview of the musculoskeletal modeling process and determination of foot forward angle during cutting maneuver. (**A**) Illustration of the placement of the 38 valid marker points in the constructed musculoskeletal model. (**B**) Schematic of lower extremity surface EMG test locations. (**C**) Schematic diagram of biomechanical testing of the side-cutting process. (**D**) Schematic representation of different angles of foot progression angle at initial contact.  
The three side-cutting tasks were defined as follows: toe-neutral (TN), where the right toe was positioned at 0 degrees relative to the sagittal plane; toe-in (TI), with the toe internally rotated 20 degrees from the neutral position; and toe-out (TO), with the toe externally rotated 20 degrees from the neutral position (Figure 1D).
## 3 Characterization of Front-End Light Source Performance
### Spectro-Spatial Characterization  
The creation of new frequencies by SPM, beyond the typical 1.7 spectral broadening factor, is intensity-dependent and therefore varies across the Gaussian input beam profile. This feature affects the spatial homogeneity of the XPW pulse spectrum, as shown in Figure 4(a), representing the measured XPW spectrum through a 0.2 mm pinhole translated across the beam, 15 cm after the second crystal. The spectral FWHM varies between 60 nm at the edges and 110 nm at the center (Fourier transform limited durations: 15 fs and 8.5 fs, respectively). However, the same measurement performed on the beam after 2 m propagation (far-field) exhibits a broad and homogeneous spectrum across the beam (Figure 4(b)). The complex spatio-temporal dynamics of this process is currently under study. In first approximation, it can be explained by cross-phase modulation of the XPW beam by the intense pump beam. It has recently been demonstrated that wavelength-dependent nonlinear focusing follows nonlinear spectral phase [32]. Consequently, extreme wavelengths, created at the highest beam intensity, may experience stronger self-focusing, leading to nonlinear wavelength-dependent propagation after the crystal that compensates the initial spatio-spectral inhomogeneity. The final spectro-spatial homogeneity is not a particular feature of the double-crystal scheme and the same results are obtained with a single crystal.  
To summarize, although nonlinear self-action is negligible for the XPW beam, SPM and Kerr focusing undergone by the pump beam confer to the XPW pulse a broad, spatially uniform, Gaussian spectrum, optimal for further amplification. The measurements presented in Figure 4 underscore the excellent spatial quality of the output beam in the far field. Figure 4(c) shows the intensity profile of the pulses  
Figure 4: Spectro-spatial distribution of the XPW beam, 15 cm after the second crystal (**a**) and propagated over 2 m (**b**). Spectral FWHM measured across the beam profile are indicated with white diamonds; (**c**) Spatial intensity distribution of the XPW beam at the focus of a 500 mm lens.  
measured at the focus of a 500 mm lens. The spatial profile is Gaussian with a beam Strehl ratio of about 0.9. The measured shot-to-shot beam pointing stability of the beam after XPW is 30 \(\mu\)rad (8 \(\mu\)rad rms). This is yet another direct advantage of the wave guided XPW setup.  
This simple and efficient XPW setup can consequently be used as a pulse shortener device, providing excellent spatial and spectro-temporal quality.
# Historical Eco-Environmental Quality Mapping in China with Multi-Source Data Fusion
###### Abstract  
Since the initiation of economic reforms and opening up, China has witnessed an unprecedented rate of development across all sectors. However, the country has also experienced severe ecological damage, surpassing that of many other nations. The rapid economic growth has come at the expense of the environment, revealing a significant lack of coordination between urbanization and eco-environmental protection in China. Consequently, there is an urgent need for a comprehensive and continuous historical dataset of China's eco-environmental quality (EEQ) based on remote sensing, allowing for the analysis of spatial and temporal changes. Such data would provide objective, scientific, and reliable support for China's eco-environmental protection and pollution prevention policies, while addressing potential ecological risks resulting from urbanization. To achieve this, the entropy value method is employed to integrate multi-source remote sensing data and construct an evaluation system for China's EEQ. Historical data from 2000 to 2017 is plotted to illustrate China's EEQ over time. The findings of this study are as follows: (1) The entropy method effectively facilitates the construction of China's eco-environmental quality assessment system. (2) From 2000 to 2017, approximately 39.7% of China's regions witnessed a decrease in EEQ, while 60.3% exhibited improvement, indicating an overall enhancement in EEQ over the past eighteen years. (3) The Yangtze and Yellow River basins experienced improved EEQ due to China's ecological restoration projects. (4) The future EEQ in China demonstrates a subtle positive trend across diverse contexts. This study departs from conventional approaches to EEQ evaluation by leveraging the advantages of multivariate remote sensing big data, including objectivity, timeliness, and accessibility. It provides a novel perspective for future eco-environmental quality evaluation.  
eco-environment quality; entropy method; remote sensing; China 2023  
1
# Effect of Fly Ash on the Properties of Ceramics Prepared from Steel Slag
## Materials and Methods  
### Raw Materials  
The raw materials used in the present investigation were steel slag, clay, feldspar, quartz, talc, and fly ash. Crushed and magnetically separated steel slag was supplied by the Shandong Iron and Steel Group. The fly ash was provided by a thermal power plant located in Huhehaote City, inner Mongolia, China. All of the other raw materials were taken from the Shandong province of China. The major chemical compositions of the raw materials were analyzed by X-ray fluorescence (XRF), and the results are shown in Table 1.  
As can be seen from Table 1, the main composition of steel slag is SiO\({}_{2}\), CaO, FeO, and MgO. Fly ash consists of 47.72% SiO\({}_{2}\) and 41.63% Al\({}_{2}\)O\({}_{3}\). In feldspar, SiO\({}_{2}\), Al\({}_{2}\)O\({}_{3}\), K\({}_{2}\)O, and Na\({}_{2}\)O are the major components. The main components of talc are SiO\({}_{2}\) and MgO. The quartz has almost no impurities. SiO\({}_{2}\) and Al\({}_{2}\)O\({}_{3}\) are the main components of clay; however, alkali metal oxides are also important.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Content (wt \%)** & **SiO\({}_{2}\)** & **CaO** & **Al\({}_{2}\)O\({}_{3}\)** & **Fe\({}_{2}\)O\({}_{3}\)** & MgO & **K\({}_{2}\)O** & **Na\({}_{2}\)O** & **TiO\({}_{2}\)** & **MnO\({}_{2}\)** \\ \hline Steel slag & 11.65 & 52.69 & 2.07 & 21.89 & 4.18 & 0.10 & 0.14 & 1.05 & 2.78 \\ Clay & 64.28 & 0.98 & 20.38 & 8.99 & 0.71 & 3.25 & 0.16 & 0.96 & - \\ Quartz & 96.5 & 0.09 & 1.85 & 0.83 & 0.11 & 0.51 & - & - & - \\ Feldspar & 65.61 & 5.98 & 15.26 & 1.33 & 0.43 & 8.65 & 2.18 & 0.18 & 0.08 \\ Talc & 61.77 & 3.57 & 0.25 & 0.23 & 34 & 0.02 & - & - & - \\ Fly ash & 47.72 & 3.57 & 41.63 & 2.89 & 0.41 & 0.62 & 0.18 & 1.82 & - \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main chemical compositions of the raw materials.
# Two-Terminal Electronic Circuits with Controllable Linear NDR Region and Their Applications
## 6 Applications  
### Negative Differential Resistance Oscillators  
The two-terminal circuits shown in Figures 3-5 can be used for constructing single-frequency NDR oscillators. Figures 6-8 show the NDR oscillators based on MCCM, MWCM, and MIWCM.  
In the oscillator circuits of Figures 6-8, capacitors \(C_{1}\), \(C_{2}\), and inductor \(L\) establish a resonant tank circuit. Capacitor \(C_{a}\) is a feedback element used to improve the start-up of the oscillator. Capacitor \(C_{b}\) serves as a noise killer at the drain of transistor \(T_{0}\).  
We show later that the NDR oscillator performance depends on the selected CM and the number of additional current sources \(I_{2}\).  
The main characteristics of oscillators are frequency of operation, phase noise, harmonic distortions, and power consumption. Designers use several merit figures combining some or all of the key features to compare different oscillators [46; 47].  
Figure 8: NDR oscillator with multiple-output improved Wilson current mirror.  
Figure 6: NDR oscillator with multiple-output cascade current mirror.  
Figure 7: NDR oscillator with multiple-output Wilson current mirror.  
The most common figure of merit (FOM) is given by [48]  
\[FOM\Big{(}f_{of}\Big{)}=PN\Big{(}f_{of}\Big{)}_{dBc}-20\log\Big{(}f_{c}/f_{of} \Big{)}+10\log(P_{dis}/1\text{mW}), \tag{22}\]  
where \(f_{of}\) is the offset frequency from the carrier frequency \(f_{c}\), \(PN(f_{of})\) is the oscillator phase noise at offset frequency \(f_{of}\), and \(P_{dis}\) is the oscillator dissipation power. The second term allows us to compare oscillators operating at different frequencies. Thus, this criterion is invariant to the oscillator frequency.  
According to (22), the less FOM, the more efficient oscillator.  
For self-excitation of the oscillator, it is necessary to compensate for the tank circuit's losses. Negative differential resistance of the oscillator's electronic circuit carries such compensation for the tank circuit losses. Therefore, the condition for self-excitation of the NDR oscillator has the following form [49]:  
\[\Big{|}R_{diff}\Big{|}<R_{Q}, \tag{23}\]  
where \(\mid R_{diff}\mid\) is the absolute value of the NDR at the operating point calculated by (19)-(21), and \(R_{Q}\) is the loaded tank circuit resistance at the resonance.  
The loaded tank circuit resistance at resonance is [50] (p. 905)  
\[R_{Q}=\rho Q_{l}, \tag{24}\]  
where \(\rho\) is the characteristic impedance of the tank circuit, and \(Q_{l}\) is the loaded quality factor of the tank circuit.