esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Scattering Parameters
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Ref.**} & **Unit Cell Technique** & **Phase Control Device** & **Frequency (GHz)** & **Polarization** & **Phase Range** & **Gain (dBi)** & **Aperture Efficiency (\%)** & **Bandwidth** & **Beam Scanning Capacity** \\ \hline \multirow{2}{*}{[1]} & PCB stacked patch & PIN diode & 5.4 & LP, CP & 1 BIT & 17 & 28.5 & 8.5 & E and H \\  & Double O-slot patches & PIN diode & 29 & LP & 2 BIT & 19.8 & 15.9 & 16.2\% & E and H \\  & Microstrip vivaldi & PIN diode & 13.6 & LP & 1 BIT & 22.3 & 25.6 & 1.9\% & E and H \\  & Square-ring patch & PIN diode & 5.75 & CP & 1 BIT & 14 & – & 2.5\% & E and H \\  & Circular patch & PIN diode & 12.1 & LP & 4 BIT & 14.6 & 16.4 & – & E and H \\  & & & & & & & & & plane \\  & H- and I-shape coupling slot & PIN diode & 12.5 & LP & 1 BIT & 17 & 14 & 9.6\% & E and H \\  & & & & & & & & plane \\  & Hexagonal & & & & & & & & \\  & meander shape & PIN diode & 16.5 & LP & 1 BIT & 24.5 & 19.8 & 19.4\% & E and H \\  & & & & & & (sim) & (sim) & (sim) & E and H \\  & & & & & & & & plane \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameters of WBMUC. Figure 4: (a) Theoretical scattering parameter of the proposed unit cell. (b) Phase shift. electromagnetic waves. The phase difference between the 2 states is kept at 180\({}^{\circ}\), illustrating the feasibility of a 1-bit proposed design.
## 1 Introduction
An outlier identification and exclusion process is proposed on the set of probabilistic outlying observations to maintain the reliability and the integrity of the positioning solution. Moreover, this paper is also presented as a concise tutorial for a better understanding of the proposed estimation algorithm in both theoretical and mathematical aspects. The rest of the paper is organized as follows. Section 2 recalls the idea of the robust estimation theory and proposed robust estimators are reviewed. Section 3 introduces the theory and the application of the LSE model for GNSS positioning and details of the classic outlier detection exclusion process. In Section 4, mathematical and theoretical aspects of the robust MM estimation theory are presented. Details of the custom designed software receiver for performance analysis is presented in Section 5. The proposed estimation algorithm for multiconstellation positioning is explained in Section 6. Section 7 deals with the outlier detection and exclusion process in detail. In Section 8, a detailed discussion is provided related to key modifications in the original statistical estimation procedure and a very similar GNSS positioning scheme [18], based on the robust statistics, is analyzed and compared with our proposed estimation scheme. Results of the proposed estimation algorithm are analyzed and discussed against LSE and WLSE algorithms for several field and simulation tests in multiple scenarios and environments in Section 9. A conclusion is drawn in the last section with future enhancements.
## 3 Results and Discussion
### Analysis of Performance of the Final ANN Model
#### 3.3.2 Uncertainty Analysis  
In addition, uncertainty analysis was performed to quantify the uncertainty of the ANN model during prediction. Nineteen classes of the target LBC were introduced, ranging from 0 to 9.5 MN with a resolution of 0.5 MN. The corresponding data in each level were deduced, and then used to compute the standard deviation. Figure 11 presents the 70%, 95% and 99% confidence intervals, together with the average curve, for the prediction of LBC using ANN, respectively. In this figure, the numbers of data points in each class are also indicated. When the LBC is lower than 4 MN, a low level of uncertainty is achieved. However, where the LBC is greater than 4 MN, the level of uncertainty is almost tripled. This is attributable to the fact that for an LBC lower than 4 MN, there are a high number of data points in each class--for instance, there are 105 data points between 0.5 and 1 MN. On the contrary, not many data points are distributed when the LBC is greater than 4 MN. Such an investigation could point out the current limitations of the model. In future research projects, more data points should be considered in order to obtain reliable representation, especially for classes greater than 4 MN.  
\begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Data Used** & **RMSE (kN)** & **MAE (kN)** & **Error Mean (kN)** & **Error StD (kN)** & **R2** & **Slope** & **Slope Angle (\({}^{\circ}\))** \\ \hline Training & 217.717 & 139.685 & \(-\)1.712 & 218.062 & 0.989 & 0.980 & 44.429 \\ \hline Testing & 294.424 & 191.878 & \(-\)7.358 & 295.445 & 0.975 & 0.975 & 44.263 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of performance of the ANN model.  
Figure 10: Regression graphs between actual and predicted load-bearing capacity (LBC) using (**a**) training and (**b**) testing data.
_Appl. Sci._**2015**, \(5\), 761-769; doi:10.3390/app5040761  
_Applied sciences_  
**ISSN 2076-3417**  
www.mdpi.com/journal/applsci  
_Article_  
**MHz Repetition Rate Yb:YAG and Yb:CaF\({}_{2}\) Regenerative Picosecond Laser Amplifiers with a BBO Pockels Cell**  
**[PERSON]\({}^{1}\), [PERSON] \({}^{1,*}\), [PERSON] \({}^{1,2}\), [PERSON]\({}^{1}\), [PERSON] \({}^{1}\) and [PERSON] \({}^{1,2}\)**  
\({}^{1}\) Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Institut fur Strahlenphysik, Bautzner Landstr. 400, Dresden 01328, Germany; E-Mails: [EMAIL_ADDRESS] (F.B.); [EMAIL_ADDRESS] (M.L.); [EMAIL_ADDRESS] (F.R.); [EMAIL_ADDRESS] (D.A.); [EMAIL_ADDRESS] (U.S.)  
\({}^{2}\) Technische Universitat Dresden, Institut fur Kern- und Teilchenphysik, Zellescher Weg 19, Dresden 01069, Germany  
* Author to whom correspondence should be addressed; E-Mail: [EMAIL_ADDRESS]; Tel.: +49-351-260-3049; Fax: +49-351-260-13049.  
Academic Editor: [PERSON]  
_Received: 31 August 2015 / Accepted: 28 September 2015 / Published: 12 October 2015_  
**Abstract:** We present picosecond Yb:YAG and Yb:CaF\({}_{2}\) regenerative laser amplifiers with ultra-high repetition rates in the MHz range. A maximum pulse energy of 40 \(\upmu\)J was obtained at 20 kHz while we achieved around 1 \(\upmu\)J at 1 MHz. We demonstrated a pulse duration of 2.1 ps for Yb:YAG and 4.8 ps for Yb:CaF\({}_{2}\) when seeded by a mode-locked Yb:KGW fs-oscillator without pulse stretching or phase compensation.  
**Keywords:** high repetition rate; regenerative amplifiers; picosecond lasers; ytterbium-doped laser materials
## 3 Preliminary Results  
Before the beginning of the experimental campaigns, a relative measurement of the four temperature sensors was carried out. For this purpose, they were placed inside a climatic chamber during a 24 h cycle, with the temperature varying between 10 \({}^{\circ}\)C and 35 \({}^{\circ}\)C and the relative humidity between 50% and 80%. The results obtained by the four devices were similar.  
Subsequently, an evaluation of the behavior of the test cells was carried out without any passive cooling measures having been implemented. Air temperature, radiant temperature and air infiltration were measured. Figure 6 shows the results of the temperature measurements taken between 15 th May and 4 th June, inside the two test cells and outside. The temperature inside of the two cells was very similar, showing that they were under similar conditions. Indoor temperature is always higher than outdoor temperature, both during day and night.  
Figure 7 shows the mean radiant temperature and the temperature of dry bulb. It was found that, for each of the cells, there are no relevant differences between those values, proving that the impact of the radiation emitted by the interior surfaces is not meaningful. Thus, an identical performance in both was proven.  
Figure 8 shows the air change rate per hour (RPH) in cells C1 and C2 resulting from performing 11 and 14 measurements, respectively. The results show some variability, not only when comparing the punctual values obtained for the different measurements, but also when evaluating the mean values for the two cells (2.29 h\({}^{-1}\) for C1 and 2.42 h\({}^{-1}\) for C2). However, the variability obtained was expected, since measurements carried out by other authors, using the same technique and CO\({}_{2}\) as the tracer gas, point in the same direction [21]. For the reasons previously presented, it was considered that the obtained differences were acceptable. The very high values obtained in this test suggest the existence of significant infiltrations in the cells, probably due to the lack of sealing of the connecting joints between the walls and the ceiling.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Campaign** & **Passive Cooling Techniques** & **Duration** \\ \hline \multirow{3}{*}{5} & **Phase II** & \\  & Painting of the opaque envelope with reflective paint and natural & \\  & cross ventilation by wind action for 24 h & \\  & Painting of the opaque envelope with reflective paint and natural & \\  & cross ventilation by wind action during the night period & \\  & Painting of the opaque envelope with reflective paint and natural & \\  & ventilation by chimney effect for 24 h & \\ \hline \hline \end{tabular}
\end{table}
Table 2: _Cont._  
Figure 6: Air temperature between 15 th May and 4 th June, inside the two test cells and outside: (**A**) Variation in time; (**B**) Box-plot representation.
# Evaluating the Efficiency of Physical and Cryptographic Security Solutions for Quantum Immune IoT
## 5 Evaluation Approach for Quantum Immune Security
### Implementations for IoT Key Exchange Scenario  
To enable energy efficiency measurements, we implemented the physical layer secrecy coding approach and modeled it as well as crypto algorithms and IoT platforms for the simulator.
## 2 Theoretical Background
### Seismic Performance Assessment  
#### 2.2.1 Intensity and Damage Measure  
For the engineering structures, the IDA-based fragility analysis can be expressed by the intensity measure (IM) as cumulative absolute velocity (CAV), cumulative absolute displacement (CAD), arias intensity (AI), spectral acceleration (\(\mathrm{S_{a}}\)), spectral displacement (\(\mathrm{S_{d}}\)), peak ground acceleration (PGA), etc. In this study, the PGA has been being used to express the IM in IDA. PGA is used today in most cases because of its connection with the inertial forces and for the specific types of structure like concrete gravity dam (stiff structure) to evaluate the maximum dynamic force [22]. As IDA is involved in performing a series of dynamic analyses of a structural model under a set of GMs, each GM is scaled up to a range of IM. The EQs are scaled to such a level of force to excite the structure through the IDA method so that the structure experiences an ultimate collapse after showing the elastic to inelastic behavior. The structural response can be presented by the IDA with scaler IMs and damage measure (DM) used as an engineering demand parameter (EDP). Generally, the maximum inter-story drift, the separate peak story drift, peak floor acceleration and damage index are used as EDP. The relative displacement of the CGD is used in several types of research previously for seismic assessment such as [PERSON] et al. [23], [PERSON] [24] and [PERSON] [25]. Therefore, this study also has been followed the crest displacement as an EDP for the IDA curve, from where the fragility analysis has been carried out. For the seismic design of the hydraulic structure, the specification combining with the international and Chinese two level of intensity approach has been adopted here as (1) a maximum design earthquake (MDE) and (2) a maximum credible earthquake (MCE). The limit states are taken as the serviceability limit state (with a slope of 0.8 Ke in IDA) and the safety limit state (with a slope of 0.2 Ke in IDA), which is determined here from the IDA curve [26; 27]. The Ke is the slope of each IDA curve that is determined according to the two different levels of structural response.
## 3 Results and Discussion
### Inclination of the Soil Slope
#### 3.2.4 Horizontal Stress on the Slope Face  
Figure 15 represents the influence of the slope inclination on the horizontal stresses at the slope face at the middle point of the slope during construction stages and after applying footing pressure. It is clear from the figure that as the slope inclination increases, the horizontal stress at the slope face increase in both construction and loading stages. The percentage increases in the horizontal stresses at the slope face range from 16% to 43%.
# Heart Murmur Quality Detection Using Deep Neural Networks with Attention Mechanism
## 6 Discussion
### Findings about Other Characteristics' Effect  
In this section, some findings regarding the association between other labels and murmur quality through the result in Section 5.5 are discussed. The lower usefulness of \"Pitch\" may be because the frequency-domain features reflected by \"Pitch\" are already embodied in the log-Mel spectrograms and are easily extracted by the neural networks. And the \"Grading\" label represents the loudness features of the murmur, which are less relevant to the murmur quality, leading to the lower usefulness of \"Grading\". However, extracting time-domain features from log-Mel spectrograms is harder for neural networks compared to extracting frequency-domain features, and the \"Timing\" label reflecting time-domain features can make up for this, thus improving the model performance. The \"Shape\" label proved to be less effective than the \"Timing\" label when it comes to fitting the newly extracted features of the neural network, despite it also reflecting temporal characteristics, resulting in little improvement of only 0.3%. Also, the greater performance gain for the \"Blowing\" murmur than for the \"Harsh\" murmur with \"Timing\" or \"Shape\" labels feeding might suggest that the \"Blowing\" murmur is more related to time-domain features than the \"Harsh\" murmur.  
This phenomenon illustrated that for the murmur quality detection problem, the joint use of different classes of labels may have a facilitating effect. It inspired us to explore multi-label classification tasks in future work, which may help the model extract heart sound features better than single-label detection tasks. Meanwhile, when designing the model, correctly using both time-domain representations and spectrograms may have better results than using only spectrograms.
# Hybrid Window Decoding for Joint Source Channel Anytime Coding System
## 2 Preliminaries
### Sketch of the SC-RA-Based JSCAC System  
Figure 1 shows the encoding and decoding structures of the SC-RA-based JSCAC system [17], which is composed of the upper half part (source code) and the lower half part (channel code). Therein, the white circles represent the parity bit nodes (PNs) with a fixed degree of 2; the black and gray rectangles indicate the source syndrome nodes (SNs) and channel check nodes (CNs) with degrees of \(A^{sc}\) and \(A^{cc}\), respectively; while the black and gray circles denote the source and channel information bit nodes (INs) with degrees of \(Q^{sc}\) and \(Q^{cc}\), respectively. Each SN or CN is causally and exponentially connected to the former INs with an exponential rate of \(\lambda\) and a coupling length of \(\gamma\). The exponentially distributed edge connections of source code and channel code are depicted by line thickness in Figure 1, which can also be written as [21]:  
\[P_{r}(k)=\frac{e^{-k\lambda}(1-e^{-\lambda})}{1-e^{-\gamma\lambda}}, \tag{1}\]  
where \(k=j-i\) is the distance between the \(j\)-th SN (CN) with the connected \(i\)-th IN (\(j\geq i\)). The exponential rate of \(\lambda=\lambda^{sc}\) (or \(\lambda^{cc}\)) and the coupling length of \(\gamma=\gamma^{sc}\) (or \(\gamma^{cc}\)). The larger the parameter \(\lambda\), the faster the error probability decays with increasing decoding delay. When \(\lambda^{sc}=\lambda^{cc}=0\), then \(P_{r}(k)=1\), which is equal to the uniform distribution. The uniform distribution has a slow decline rate over the decoding delay, which is undesired in  
Figure 1: Encoding and decoding structures of the SC-RA-based JSCAC system [17]. Reproduced with permission of [17], _Copyright ©_2020, _IEEE_.  
the anytime transmission. The source code rate and channel code rate can be calculated with the following equation [22]:  
\[R=\frac{L}{L+\frac{Q}{A}(L-\gamma+1+2(\gamma-\sum\limits_{i=0}^{\gamma}(\frac{i}{ \gamma})^{A}))}, \tag{2}\]  
where \(L\) is the chain length. For the source code rate \(R^{sc}\), \(Q=Q^{sc}\), \(A=A^{sc}\), \(\gamma=\gamma^{sc}\); and for the channel code rate \(R^{cc}\), \(Q=Q^{cc}\), \(A=A^{cc}\), \(\gamma=\gamma^{cc}\). As \(L\rightarrow\infty\), the asymptotic code rates of the SC-RA-based JSCAC system are \(R^{cc}\rightarrow\frac{A^{cc}}{A^{cc}+Q^{cc}}\), \(R^{sc}\rightarrow\frac{Q^{cc}}{A^{cc}+Q^{cc}}\).
## 2 Materials and Methods
### Search Strategy  
In November 2022, electronic searches were conducted in the following databases: PubMed (National Library of Medicine), Web of Science (Clarivate Analytics), and Scopus (Elsevier). These comprised both MeSH and free-text terms. The following search strategy was applied: ((\"bone tissue engineering\" [MeSH Terms] OR (\"tissue\" [All Fields] AND \"engineering\" [All Fields] AND \"mandible\" [All Fields]) OR \"bone tissue engineering\" [All Fields]) OR (\"tissue scar-folds\" [MeSH Terms] OR (\"tissue\" [All Fields] AND \"scaffolds\" [All Fields]) OR \"tissue scaffolds\" [All Fields] OR (\"tissue\" [All Fields]) AND \"scaffold\" [All Fields]) OR \"tissue scaffold\" [All Fields]) OR (\"mandible reconstruction\" [MeSH Terms AND] \"engineer-ing\" [All Fields]] OR (\"reconstructive\" [All Fields] AND \"surgical\" [All Fields] AND \"pro-cedures\" [All Fields]) OR \"mandible reconstruction\" [All Fields] OR \"reconstruction\" [All Fields]) OR (\"bone morphogenetic proteins\" [MeSH Terms] OR (\"bone\" [All Fields] AND \"morphogenetic\" [All Fields] AND \"proteins\" [All Fields]) OR \"bone morphogenetic pro-teins\" [All Fields] OR (\"bone\" [All Fields] AND \"morphogenetic\" [All Fields]) AND \"pro-tein\" [All Fields]) OR \"bone morphogenetic protein\" [All Fields]) OR (\"bone marrow cells\" [MeSH Terms] OR (\"bone\" [All Fields] AND \"marrow\" [All Fields] AND \"cells\" [All Fields]) OR \"bone marrow cells\" [All Fields]) OR (\"intercellular signaling peptides and proteins\" [MeSH Terms] OR (\"intercellular\" [All Fields] AND \"signaling\" [All Fields] AND \"peptides\" [All Fields] AND \"proteins\" [All Fields]) OR (\"growth\" [All Fields]) AND \"factors\" [All Fields]) OR \"growth factors\" [All Fields])) AND (\"mandible\" [MeSH Terms] OR \"mandible\" [All Fields]) OR (\"mandible\" [MeSH Terms] OR \"mandible\" [All Fields]) AND (\"critical sized defect\" [All Fields])). The retrieved references were exported to the EndNote software 20.5 (Windows) (Clarivate Analytics, Philadelphia, PA, USA) to identify the duplicates.  
Searches were limited to studies in the English language. The reference lists of the articles identified from the initial search were screened for further relevant studies. No restrictions were imposed on the date or the type of publication.
## 2 Materials and Methods
### Part A
#### 2.2.3 Extraction and Quantification of Total Soluble Phenols  
Total soluble phenols (TSP) were extracted from apple slices post-VI by combining the sample (2 g) with an 80:20 methanol: water solution acidified with 2% HCl 2 N (20 mL). This mixture was shaken at 80 rpm for 60 min in a 360\({}^{\circ}\) rotating mixer (RML-80 PRO, Huzhou City, China) and centrifuged at 6000\(\times\)\(g\) for 10 min at 4 \({}^{\circ}\)C (Hermle Z32 HK, Wehingen, Germany) [22]. TSP quantification followed the Montreau method [23] with modifications, using 2 N Folin-Ciocalteau's reagent (FCR), and spectrophotometrically measured at 750 nm in an Accuris Microlate reader (SmartReader MR-9600, Denver, CO, USA). The extract (12 \(\mu\)L) was mixed with FCR (12 \(\mu\)L), sodium bicarbonate solution (7.5 mg/mL, 116 \(\mu\)L), and dH\({}_{2}\)O (164 \(\mu\)L) in a 96-well microplate. TSP content was informed in mg of gallic acid equivalent per 100 g of fresh apple weight, derived from a gallic acid reference curve (R\({}^{2}\) = 0.998).
## 3 Experiments and Analysis
### Experiments and Analysis
Therefore, we take the data reconstructed by eight-step PMP as the reference standard. By comparing and analyzing the data of Column 548, Lines 378-408, 432-462, and 555-591 shown in Regions A-C in Figure 7a, which are the \"bridge of nose\", \"tip of nose\", and \"jaw\" parts of the face model, the reconstructed details of the above area after correction by the method are closer to the reconstructed results by eight-step PMP than those of the traditional color PMP. The comparison experimental results show that the detail accuracy of the proposed method is better than that of the traditional color PMP. To further compare the measuring accuracy between the traditional single-shot color PMP and the proposed method, by the difference method, the restored result of the eight-step PMP was chosen as the quasi-truth value to calculate height error distribution of the above two methods. Figure 8a shows the height error distribution by traditional single-shot color PMP. Figure 8b shows the height error distribution by the proposed method. It is  
Figure 6: The experimental results: (**a**) wrapped phase of measured object; and (**b**) reconstructed object. Figure 7: (**a**) The 547 th column data of the reconstructed result; and (**b–d**) zooms in of Regions A–C in (**a**). observed that the height error distribution of the proposed method is smaller than that of single-shot color PMP. To quantitatively compare and analyze the measurement errors of the traditional color PMP and the proposed method, the mean absolute error (MAE) and the root of mean square error (RMSE) of these methods are calculated. By traditional color PMP, the MAE is 0.2683 mm and the RMSE is 0.3453 mm. By the proposed method, the MAE is 0.1992 mm and the RMSE is 0.2546 mm. It is obvious that the measurement errors of the proposed method are smaller, and the measuring result is closer to that of the eight-step phase-shifting algorithm. The comparison of MAE and RMSE proves the validity of conclusions. The experiments and analysis sufficiently proved that the proposed method has a good feasibility and validity in the measurement of 3D shape. In this work, we use a set of complementary deformations to extract the background. Because it has a \(\pi\) shifted phase between red and blue channels and the interplay of them is lower, the background image is obtained with smaller errors. These complementary deformed patterns can effectively suppress random errors in the measuring process due to the feature of inverse phase between the red and the blue channels. Therefore, the proposed method has better measuring accuracy than the method of single-shot color PMP after the gray imbalance correction. It must be pointed out that there are some shortcomings of the proposed method for measuring colored objects. Because the captured deformed pattern is also modulated by the color of the object, some errors are introduced to result in lower measurement accuracy. However, it is single-shot so that it has higher speed and less sensitivity to mechanical disturbances, and it also has a good application prospect in real-time measurement.