esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Dental abnormalities  
The most prevalent dental abnormalities in the present study were structural, particularly accessory cusps (18%) (Figure 1).  
Less common dental abnormalities included agenesis (1), inclusion (2), and/or rotation of the teeth (1). In a few patients, dental artefacts were found; in two cases these were associated with  
Figure 1: Accessory cusp, depicted by white arrow, found in a child affected by NF1.  
gingival hyperplasia due to the presence of neurofibroma or plexiform neurofibromas, as reported by [PERSON] et al. In two other studies, dental artefacts were accompanied by eruption difficulties [8]. For example, a dental artefact was found in association with a supernumerary tooth (8). In cases of dental abnormalities not associated with neurofibromas, a plausible explanation of these abnormalities could be consider as primitives, according to [PERSON] et al.; however, unlike the present study, they found no significant difference between children affected by NF1 and healthy controls [10].  
Periodontal status  
In this study, both gingival health and oral hygiene were evaluated. Comparative analysis indicated a statistically significant difference between the two groups with regard to maintenance of adequate oral hygiene (NF1 = 41%; Control Group = 16%). There was no such difference in gingival health, indicating no relation of this parameter to the pathology of NF1 (NF1 = 17%; Control Group = 15%). These observations were in agreement with the report of [PERSON] et al. [10]. Therefore, patients with NF1 appear to have poor oral hygiene, which may favour the progression of periodontal pathologies in adults affected by this disease. Two cases of gingival hyperplasia with a fibrous appearance were also recorded. [PERSON] et al. reported that dental artefacts were associated with gingival hyperplasia [21].  
Neurofibromas  
Neurofibromas are benign complex tumours composed of all cell types that are found in the peripheral nerves. Development of neurofibromas on or around peripheral nerves is a distinctive symptom of NF1 [1]. The tongue is the most commonly involved site, and [PERSON] et al. highlighted the presence of an enlarged tongue and fungiform papillae in NF1 [15]. This symptom occurs in 50% of cases, while gum neurofibromas occur in only 5% of cases [17]. There have been few previous reports concerning the presence of neurofibromas in paediatric patients, but the results of the present study indicated a significantly higher incidence of period neurofibromas in paediatric NF1 patients (4%) compared to the control group (0), in contrast to [PERSON] et al. [10]. Only two of the children included in the present study showed neurofibromas located on the lips (Figure 2).  
Figure 2: Multiple lips neurofibroma in NF I patient are showed.  
Another case showed multiple neurofibromas in the head and neck region, impacting the oral cavity (Figure 3).  
In fact, one child showed gingival hyperplasia and relative malocclusion on the same side in relation to these neurofibromas.
# Enhanced Integrated Satellite-Terrestrial NOMA with Cooperative Device-to-Device Communication
## Abbreviations  
The following abbreviations are used in this manuscript:  
\begin{tabular}{l l}
5G & Fifth Generation \\ AWGN & Additive White Gaussian Noise \\ BS & Base Station \\ C-NOMA & Cooperative NOMA \\ CSI & Channel State Information \\ D2D & Device-to-Device \\ FSL & Free Space Pathloss \\ GEO & Geosynchronous Earth Orbit \\ IoT & Internet of Things \\ LEO & Low Earth Orbit \\ LMS & Land Mobile Satellite \\ LoS & Line of Sight \\ MC & Medium Channel \\ MEO & Medium Earth Orbit \\ MP & Multipath Component \\ NOMA & Non-Orthogonal Multiple Access \\ OMA & Orthogonal Multiple Access \\ QoS & Quality-of-Service \\ SANCOCO-D2D & Satellite-Aided NOMA with Cooperative D2D Communication \\ SC & Strong Channel \\ SIC & Successive Interference Cancellation \\ SNR & Signal-to-Noise Ratio \\ TDMA & Time-Division Multiple Access \\ UE & User Equipment \\ WC & Weak Channel \\ \end{tabular}
# Distributed Triggered Access for BSM Dissemination in 802.11 bd V2V Networks
In addition, we also apply the MU-RTS feature of IEEE 802.11 ax to deal with the lengthened airtime caused by OFDMA transmission. The proposed scheme is aiming to solve the following challenges in BSM dissemination scenario: (1) Preventing severe throughput degradation caused by medium access congestion in saturated traffic condition, (2) Decreasing the effect of hidden node problem in high vehicle density, (3) Increasing the successful packet delivery rate in 'ACK-less' broadcast situation. The simulation results corroborate that DTA effectively deals with the aforementioned problems with enhanced BSM dissemination rate, reduced packet loss rate even under very high vehicle density and traffic conditions. The rest of this paper is organized as follows. In Section 2, the proposed DTA scheme is described in detail including the background technologies. In Section 3, mathematical analysis is proposed using the Markov chain analysis and the M/G/1 queuing theory. Simulation results of the proposed scheme are presented in Section 4. Finally, Section 5 concludes the paper.
## 5 III-V-on-Silicon Devices for Optical Sensing Applications
### III-V-on-Silicon Spectrometers for Optical Sensing Applications
#### 5.2.1 Passive Integrated Spectrometers  
Integrated spectrometers are essential components for on-chip spectroscopic systems. Arrayed Waveguide Grating (AWG) and Planar Concave Grating (PCG) are the two most commonly used dispersive integrated spectrometers. Both types of devices work on the principle of interference of multiple light paths. An AWG consists of two free propagation regions (also known as star couplers), which are connected by delay lines having constant path length increment between them. Light is split up in the input star coupler and the different contributions after passing through delay lines interfere in the output star coupler. As a result, different wavelengths are focused at different places and can therefore be guided to separate output waveguides. In a PCG, the same slab is used for de-focusing as well as focusing while the constant length increment is achieved by a curved grating. More information about theory and design of AWGs can be found in [77] and details about PCG design are available in [78]. We have demonstrated different integrated spectrometers in different silicon and silicon nitride based platforms. The performance summary is given in Table 2 with references to the original publications. Figure 24 shows measured transmission spectra--in collaboration with the University of Southampton--of an AWG and PCG in the mid-infrared wavelength range.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \multirow{2}{*}{**Device/Technology**} & **Central** & **Footprint** & **No of Channels/Channel** & **FSR** & **Insertion** & **Crosstalk** \\  & **Wavelength (\(\mu\)m)** & **(mm\({}^{2}\))** & **Spacing (nm)** & **(nm)** & **Loss (dB)** & **(dB)** \\ \hline AWG/SOI [79] & 1.55 & 0.231 & 16/3.2 & 57.6 & \textless{}3.0 & \textgreater{}25.0 \\ AWG/SiN4 [80] & 0.89 & 0.337 & 12/2 & 30 & \textless{}1.5 & \textgreater{}20.0 \\ S-AWG/SOI [81] & 1.55 & 0.079 & 4/30 & 144 & \textless{}2.0 & \textgreater{}19.0 \\ AWG/SOI [14] & 2.20 & 1.000 & 6/1.6 & 13 & \textless{}3.0 & \textgreater{}17.0 \\ AWG/SOI [82] & 2.37 & 0.439 & 7/5 & 50 & \textless{}3.0 & \textgreater{}25.0 \\ AWG/SOI [83] & 3.80 & 0.858 & 6/10 & 80 & \textless{}2.0 & \textgreater{}20.0 \\ PCG/SOI [14] & 1.55 & 0.269 & 8/6.5 & 100 & \textless{}1.5 & \textgreater{}20.0 \\ PCG/SOI [14] & 2.32 & 1.040 & 8/5 & 60 & \textless{}6.0 & \textgreater{}15.0 \\ PCG/SOI [83,84] & 3.80 & 3.060 & 8/10 & 105 & \textless{}2.0 & \textgreater{}20.0 \\ \hline \end{tabular}
\end{table}
Table 2: Representative integrated spectrometers across different platforms.
## 3 Results and Discussion
### Total Phenolic Content of Calendula officinalis Water Extract  
The TPC determined in the _Calendula officinalis_ water extract was 12.8 \(\pm\) 0.007 mg GAE/g DM.  
Using various solvents and extraction conditions, many researchers have attempted to extract phenolic compounds from _Calendula officinalis_. [PERSON] et al. [27] showed that among the tested methanolic extracts of leaves of the representative family _Asteraceae_, marigold leaf extracts have been shown to have the highest total content of these compounds (1.125 \(\pm\) 0.153 mg/g DM). A study by [PERSON] and [PERSON] [28] reported that the TPC in the ethanolic extract of marigold leaves ranged from 29.21 to 50.24 mg/g, depending on the variety. In a study by [PERSON] [29], the ethanolic extract of marigold flowers had a low TPC content of 6.19 mg/g DM. [PERSON] et al. [30] found that calendula infusion showed a TPC of 16.49 \(\pm\) 0.20 mg/g DM, while the decoction had a higher content of these compounds (19.44 \(\pm\) 0.04 mg/g DM). Water extracts of _Calendula officinalis_ flowers and leaves were studied by [PERSON] et al. [31], showing that the TPC was 72.91 \(\pm\) 2.1 mg/g and 23.1 \(\pm\) 0.8 mg/g, respectively. [PERSON] and [PERSON] [32] found a significantly lower polyphenols content ranging from 0.06 to 3.64 mg/100 g DW in an infusion of marigold flowers, depending on brewing time and temperature.  
Comparing the obtained results with the above reports by other authors, it can be concluded that the TPC in the plant extract is affected by many factors. These include the type of solvents used, their ratio, extraction time and temperature, the chemical composition and physical properties of the plant materials, and even the part of the plant used (flowers, leaves). Data available in the literature state that the chemical compounds found in plants are also influenced by the region where the plant is grown, climatic conditions (e.g., rainy and dry seasons), growing season (beginning or end of flowering), and genetic factors [27; 33]. Therefore, all these factors should be considered when comparing the TPC in an extract from a given plant. The repeatability of chemical composition is one of the main problems in using plant extracts as food preservative ingredients. Extracts of natural origin, or different batches of extracts produced by different manufacturers, can exhibit quantitative and qualitative variability.
## 2 Design Equations
### Parameters Extraction of DGS Section  
The parameters of the DGS section were extracted separately. The DGS circuit exhibits the characteristics of a parallel LC circuit. Thus, it can serve as a parallel LC resonator circuit for various purposes in a variety of components. Figure 4a,b shows the equivalent circuits of a one-pole Butterworth-type low-pass filter and its equivalent DGS circuit, respectively [13].  
The reactance of the DGS unit is as follows:  
\[X_{LC}=\frac{1}{\omega_{0}C}\left(\frac{\omega_{0}}{\omega}-\frac{\omega}{ \omega_{0}}\right) \tag{16}\]  
where \(\omega_{0}\) is the resonant angular frequency. The series inductance of the Butterworth low-pass filter can be acquired as follows:  
\[X_{L}=\omega^{\prime}.Z_{0}g_{1} \tag{17}\]  
where \(\omega^{\prime}\) is the angular frequency of the 1 st-order, one-pole Butterworth prototype low-pass filter and \(g_{1}\) is the element value, i.e., \(g_{1}=2.0\). To achieve low-pass filter response, the DGS circuit should get an equal net reactance at cutoff frequency \(\omega_{c}\) as the prototype low-pass filter at \(\omega^{\prime}=1\), i.e.,  
\[X_{LC}|_{\omega=\omega_{c}}=X_{L}|_{\omega^{\prime}=1} \tag{18}\]  
Thus, from this approximation,  
\[C=\frac{\omega_{c}}{Z_{0}g_{1}}\left(\frac{1}{\omega_{0}^{2}-\omega_{c}^{2}}\right) \tag{19}\]  
and  
\[L=\frac{1}{4\pi^{2}f_{0}^{2}.C} \tag{20}\]  
Figure 4: Equivalent circuits of one-pole Butterworth-type low-pass filter and DGS.  
Equations (19) and (20) demonstrate the lumped parameters, i.e., the capacitance and inductance of the DGS circuit. where \(\omega_{c}\) and \(f_{0}\) are cutoff angular frequency and resonant frequency, respectively.
# Multi-Scale Factor Image Super-Resolution Algorithm with Information Distillation Network
## 2 Materials and Methods
### Datasets and Evaluation Metrics  
In our experiments, we train the network by DIV2K [22], which contains 800 high-quality images. We use Set5 [23], Set14 [24], BSD100 [25], and Manga109 [26] for evaluation. There are two metrics to evaluate the performance of the SR, such as peak signal-to-noise ratio (PSNR) and structure similarity (SSIM) [27]. We calculate the values on the Y channel transformed from YCbCr space. As for the degradation methods, we use bicubic downsampling on the Matlab platform, the original HR image is downscaled to obtain the LR image. We randomly cropped into image patches with size 192 \(\times\) 192, which are used as input for network training.
## 1 Introduction
On the other hand, in order to reduce the window time, References [14; 15] proposed methods to directly extract features from raw data without any pre-processing and using them as the input to the designed classifier and they showed the possibility of classifying micro-Doppler signals without generating image data. However, since the amount of information in the input data for extracting the feature is also reduced according to the decreased  
Figure 1: The difficulties of recognizing human walking by micro-Doppler signals. The background noise should also be considered when detecting human walking on the ground. Also, recognizing background noise can provide useful information. window time, the classification accuracy may degrade. So, it should be seriously considered how to improve the classification accuracy of the corresponding classifier. To tackle this problem, in this paper, we propose a stacking method as an ensemble method of deep networks to distinguish micro-Doppler signals caused by humans walking from the background noise using radar sensors. The stacking method can be a practical approach to improve classifier's accuracy without increasing the window time. About the latest research, Reference [16] reported that a stacking deep neural network (DNN) method improves performance for acoustic signal processing. In the field of image recognition, Reference [17] reported that stacking could be a useful approach to improve performance. Also, stacked auto-encoders to detect a human fall using radar have been researched [18]. About the need to include background noise signals in this research, since the background noise has the potential to distort the micro-Doppler effects generated by human walking, we should consider the effect of background noise in a design classification algorithm for outdoor applications. Also, if the classification algorithm can classify background status, it is possible to get helpful information about environmental conditions. This paper is organized as follows. Section 2 describes the micro-Doppler signals collected in an outdoor environment and Section 3 describes the design of classifiers. Section 4 shows the experimental results and Section 5 concludes this paper.
# Multi-Objective Optimization for Plug-In 4 WD Hybrid Electric Vehicle Powertrain
## 3 The Energy Management Strategy Based on the CD-CS Mode
### CD Mode  
When SoC \(\geq\) SOC\({}_{\text{cd}}\), the vehicle operates in the CD mode, its corresponding control strategy flow is shown in Figure 5. V, T\({}_{\text{req}}\), T\({}_{\text{mmax}}\) and T\({}_{\text{isgmax}}\) are the vehicle's speed, the demand torque at the wheel, the rear-drive motor's maximum output torque and the ISG motor's maximum output torque, respectively. i\({}_{\text{fo}}\), i\({}_{\text{ro}}\) and i\({}_{\text{cvt}}\) are the speed ratio of the front final drive, the rear final drive and CVT, respectively. Their definitions are as follows: \(i_{fo}=\omega_{\text{cpt\_out}}/\omega_{w}\), i\({}_{\text{ro}}=\omega_{m}/\omega_{w}\) and i\({}_{\text{cpt}}=\omega_{\text{isg}}/\omega_{\text{cpt\_out}}\), \(\omega_{\text{isg}}\), \(\omega_{m}\) and \(\omega_{w}\) are the same as Equation (4) and \(\omega_{\text{cpt\_out}}\) is the angular speed of the CVT output shaft. T\({}_{\text{mmax\_w}}\) is the equivalent wheel torque of rear-drive motor's maximum output torque, it is expressed as T\({}_{\text{mmax\_w}}\) = T\({}_{\text{mmax}}\times i_{\text{ro}}\). T\({}_{\text{isgmax\_w}}\) is the equivalent wheel torque of ISG motor's maximum output torque, it is expressed as T\({}_{\text{isgmax\_w}}\) = T\({}_{\text{isgmax}}\times\) i\({}_{\text{fo}}\times\) i\({}_{\text{cvt}}\times\) n\({}_{\text{cvt}}\). There are three drive modes (rear motor drive mode, dual motor drive mode and 4 WD hybrid mode). In the rear motor drive mode, the vehicle is only driven by the rear-drive motor. In the dual motor drive mode, the vehicle is jointly driven by the rear-drive motor and the ISG motor. The rear-drive motor, the ISG motor and engine work jointly to meet the driving demand in the 4 WD hybrid mode. If 0 \(\leq\) T\({}_{\text{req}}\)\(\leq\) T\({}_{\text{mmax\_w}}\) is satisfied, the vehicle drives in the rear motor drive mode. When the vehicle runs at a low speed, and if T\({}_{\text{req}}\)\(>\) T\({}_{\text{mmax\_w}}\) is satisfied, the vehicle drives in the dual motor drive mode. When the vehicle speed is higher than the predetermined speed V\({}_{\text{o}}\), and if T\({}_{\text{mmax\_w}}\)\(\leq\) T\({}_{\text{req}}\)\(\leq\)(T\({}_{\text{mmax\_w}}\) + T\({}_{\text{isgmax\_w}}\)) is satisfied, the vehicle drives in the dual motor drive mode, otherwise the vehicle drives in the 4 WD hybrid mode. Regenerative braking can be employed to recover energy in the braking mode, the braking strategy will be introduced in Section 3.3.  
Figure 4: Operating mode switching strategy.
###### Abstract  
The precision of a linear object measurement using satellite techniques is determined by the number and the relative position of the visible satellites by the receiver. The status of the visible constellation is described by the Dilution Of Precision (DOP). The obtained geometric coefficient values are dependent on many variables. When determining these values, field obstacles at the receiver location and satellite positions changing with time must be taken into account. Carrying out a series of surveys as part of a linear object Global Navigation Satellite System (GNSS) measurement campaign requires the optimisation problem to be solved. The manner of the inspection vehicle's movement should be determined in such a way that the surveys are taken only within the pre-defined time frames and that the geometric coefficient values obtained at subsequent points of the route are as low as possible. The purpose of this article is to develop a software for the planning of a linear object GNSS measurement campaign to implemented in motion and taking into account the terrain model and its coverage. Additionally, it was determined how much the developed program improves DOP values on the planned route under simulated conditions. This software has no equivalent elsewhere in the world, as the current solutions for the planning of a GNSS measurement campaign, e.g., Trimble GNSS Planning, GNSS Mission Planning, or GPS Navigation Toolbox, allow the satellite constellation geometry to be analysed exclusively for specific coordinates and at a specific time. Analysis of the obtained simulation test results indicates that the campaign implementation in accordance with the pre-determined schedule significantly improves the quality of the recorded GNSS data. This is particularly noticeable when determining the position using the Global Positioning System (GPS) and GLObal NAVigation Satellite System (GLONASS) satellite constellations at the same time. During the tests conducted on the road along a three-kilometre-long route (tram loop) in Gdarsk Brzezo, the average value of the obtained Position Dilution Of Precision (PDOP) decreased by 22.17% thanks to using the software to plan a linear object GNSS measurement campaign. The largest drop in the geometric coefficient values was noted for an area characterised by a very large number of field obstacles (trees with crowns and high buildings). Under these conditions, the PDOP value decreased by approx. 25%. In areas characterised by a small number of field obstacles (single trees in the vicinity of the track, clusters of trees and buildings located along the track), the changes in the PDOP were slightly smaller and amounted to several percent.  
Global Navigation Satellite System (GNSS) mission planning software; linear object, Dilution Of Precision (DOP); satellite measurements +
Footnote †: journal: _Energies_
## 4 Approximate Prediction of Fast-Scale Instability and Adaptive Slope Compensation  
The model of a DC-AC boost inverter including its control loop is high-dimensional which makes its accurate stability analysis a real challenge at both the fast and the slow scales. Although the exact full-order switched model or the associated discrete-time model [31, 32] can be used to numerically predict and explain any king of instability that could take place in the system, it is more useful to have a simple and design-oriented expression clearly putting in evidence the impact of all the relevant system parameters affecting the stability of the system [33]. If fast-scale instability is of concern, the conventional averaged model will fail to predict this behavior because its validity is limited to frequency ranges much below the switching frequency since the switching effects are naturally eliminated by the averaging process. Fast-scale instability is a high frequency behavior requiring a model that takes into account the switching action and its related sampling effects [34]. The accuracy of the averaged model can be improved by taking into account these sampling effect. In this way, the fast-scale instability can be predicted using the frequency response of the system loop gain. However, as stated before, it is more useful to have explicit mathematical expressions that predict this behavior to appropriately select the system parameter values guaranteeing a stable behavior. A simple reduced-order discrete-time model will be enough to approximately but accurately predict the onset of this phenomenon [27]. Specifically, fast-scale instability is dominated by the fast inner current loop and its parameters although the slow outer loop parameters could appear, under some realistic conditions, in a negligible correcting term. Therefore, a reduced-order model taking into account only the main variables used in the fast current loop can be used to predict fast-scale instability and to obtain a simple design-oriented expression for selecting the right slope ensuring stability for all operating range of the duty cycle. This model will be presented below and then used to perform stability analysis at the fast scale.