esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluating Convolutional Neural Networks and Vision Transformers for Baby Cry Sound Analysis
## 2 Methodology
### Feature Extraction
#### 2.3.2 CQT Spectrogram  
The Constant-Q Transform (CQT) spectrogram is a valuable tool for analyzing baby cry sounds. It is particularly useful for capturing audio features at different pitch scales [38, 39], which can be essential for distinguishing the nuances in baby cries. The CQT spectrogram is computed using the following equation:  
\[CQT(cry\_recording)=|CQ(x)(f)|=\left|\int x(t)\cdot e^{-2\pi ift}dt\right| \tag{3}\]  
In the equation, \(x(t)\) represents the input audio signal, \(f\) is the frequency variable, and \(CQ(x)(f)\) is the CQT magnitude at frequency \(f\). The CQT is particularly adept at capturing the varying pitch characteristics present in baby cries, which can convey important information about the baby's needs and condition.  
Using the CQT spectrogram for baby cry analysis allows for a more detailed and pitch-sensitive representation of the cries, making it a valuable feature extraction technique for machine learning algorithms aimed at understanding and classifying baby cries.  
Figure 1: Mel spectrograms of the five classes included in the donate–a–cry dataset.
## 3 Results
### Functional Properties of Dandelion Inulin
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \begin{tabular}{c} **Functional** \\ **Characteristics** \\ \end{tabular} & **Classical Extraction** & \
\begin{tabular}{c} **Ultrasound-Assisted** \\ **Extraction** \\ \end{tabular} &
\begin{tabular}{c} **Microwave-Assisted** \\ **Extraction** \\ \end{tabular} & **Chicory Inulin** \\ \hline L & 88.16 \(\pm\) 1.84 b  & 82.81 \(\pm\) 2.10 c  & 96.25 \(\pm\) 0.64 a  & 97.82 \(\pm\) 0.37 a  \\ \hline a & 5.97 \(\pm\) 0.46 a  & 4.81 \(\pm\) 0.53 a  & 1.97 \(\pm\) 0.65 b  & 0.18 \(\pm\) 0.13 c  \\ \hline b & 15.46 \(\pm\) 0.23 a  & 10.61 \(\pm\) 0.78 b  & 4.29 \(\pm\) 0.74 c  & 0.75 \(\pm\)0.48 d  \\ \hline C & 16.58 \(\pm\) 0.38 a  & 11.65 \(\pm\) 0.92 b  & 4.73 \(\pm\) 0.70 c  & 0.79 \(\pm\) 0.45 d  \\ \hline h\({}^{\alpha}\) & 68.80 \(\pm\) 1.28 a,b  & 65.65 \(\pm\) 1.07 b  & 66.82 \(\pm\) 1.79 a,b  & 72.14 \(\pm\) 0.53 a  \\ \hline \(\Delta\)E & 22.17 \(\pm\) 0.97 a  & 19.04 \(\pm\) 0.25 b  & 4.65 \(\pm\) 1.00 c  & - \\ \hline YI & 25.05 & 18.30 & 6.37 & 1.10 \\ \hline BI & 23.53 & 17.34 & 5.63 & 0.59 \\ \hline Appearance & Faint brown powder & White powder & White powder & White powder \\ \hline Angle of repose (\({}^{\circ}\)) & 27.47 & 28.37 & 27.42 & 42.61 \\ \hline Wettability, s & 367 \(\pm\) 12 a  & 270 \(\pm\) 15 b  & 119 \(\pm\) 11 c  & 9 \(\pm\) 1 d  \\ \hline Hygroscopicity, \% & 7.0 & 6.7 & 5.3 & 3.7 \\ \hline True density (g/mL) & 1.44 \(\pm\) 0.01 a  & 1.02 \(\pm\) 0.02 c  & 1.14 \(\pm\) 0.03 b  & 1.25 \(\pm\) 0.05 b  \\ \hline Bulk density (g/mL) & 0.38 \(\pm\) 0.02 b  & 0.30 \(\pm\) 0.03 c  & 0.47 \(\pm\) 0.04 a,b  & 0.50 \(\pm\) 0.02 a  \\ \hline Tapped density (g/mL) & 0.51 \(\pm\) 0.04 b  & 0.55 \(\pm\) 0.05 a,b  & 0.61 \(\pm\) 0.02 a  & 0.61 \(\pm\) 0.03 a  \\ \hline Bulkiness (mL/g) & 2.63 b  & 3.33 a  & 2.13 c  & 2.00 c  \\ \hline Porosity, \% & 64.58 a  & 46.07 c  & 46.49 c  & 51.20 b  \\ \hline [PERSON]’s index, \% & 25 & 26 & 24 & 18 \\ \hline Hausner ratio & 1.33 & 1.40 & 1.37 & 1.21 \\ \hline Flowability & Fair & Fair & Fair & Good \\ \hline Cohesiveness & Intermediate & Intermediate & Intermediate \\ \hline Taste & Neutral & Neutral & Neutral & Neutral \\ \hline Sweetness & None & None & None & None \\ \hline \end{tabular} Notes: Values are presented as a mean \(\pm\) standard deviation of three replications. Different letters in each column show significant differences according to [PERSON]’s test at \(p<\) 0.05.  
\end{table} 
Table 4: Functional characteristics of inulin-type fructans from dandelion roots. the dandelion inulin samples were evaluated as being close to chicory inulin in terms of cohesiveness and flowability properties. Moreover, the dandelion inulin demonstrated better cohesiveness and flowability than soymilk and soymilk concentrates [32]. The bulkiness values of the dandelion and chicory inulin were in the range of 2-3 mL/g, and the values of dandelion inulin obtained by classical and microwave extractions were closer to the chicory inulin Raftiline. Its values were comparable with the bulkiness of almond gum, with values of 2.52, indicating that the powder is 'light' in nature [33].
## 3 Methodology
### PSInSAR Full Stack Processing
#### 3.2.2 PSC Extraction and Geocoding  
After coregistration, stable radar reflectors or PSC were extracted. These typically include buildings and other rigid structures with strong radar reflectivity and minimal temporal decorrelation. The identified scatterers were then geocoded using SRTM DEM, which is essential for accurate topographic error mitigation in SAR data.
# SRv6-Based Edge Service Continuity in 5G Mobile Networks +
## 4 Architecture and Procedures for MEC-Based Mobile Services
### SRv6-Based Path Allocation
#### 4.2.1 Path Allocation Procedure in Enhanced Mode  
The Enhanced Mode considers a full SRv6 5 GC network, where the gNB1 undertakes the SRv6 encapsulation process. In such a configuration, the execution of the End.M.GTP6.D behavior by an SRv6 endpoint is not needed. The gNB1 must be configured by the AMF to insert the required list of segments to tunnel the packet through the 5 GC network and reach the service container running in MEC Host1. We consider a scenario wherein, upon reaching the SR Endpoint3 node, the packet exits the core network and is delivered to the service container.  
Figure 5 shows an exemplary packet flow in the data plane. The UE sends a packet to its service instance running on MEC Host 1. When the packet reaches gNB1, the latter applies the H.Encaps.Red behavior and forwards it. Given that the segment list consists only of a single segment, the inclusion of the SRH is unnecessary; specifying the destination address within the outer IPv6 header is enough. Subsequently, SR Endpoint3 applies the End behavior, removing the outer IPv6 header before forwarding the packet to the  
designated container. A description of the control plane procedures required to configure both the gNB and the SR Endpoints can be found in Appendix A.
# Enhancing Propaganda Detection in Arabic News Context Through Multi-Task Learning
## 4 Experiments
### Dataset  
The primary objective of this study was to propose and develop a model for detecting propaganda in Arabic by leveraging the MultiProSE dataset [22]. The primary reason for selecting this dataset was that it is the first and only publicly available resource designed to support research and development in propaganda detection, making it well-suited for our proposed models in the Arabic language. The MultiProSE dataset comprises8000 paragraphs written in Modern Standard Arabic, each of which has been manually annotated across three complementary tasks. For the propaganda detection task, each paragraph was assigned a binary label (1 = True, 2 = False); for sentiment analysis, each paragraph was assigned a ternary label (1 = Positive, 2 = Negative, 3 = Neutral); and for emotion recognition, each paragraph was assigned a five-way label (1 = Happiness, 2 = Sadness, 3 = Anger, 4 = Fear, 5 = None). Table 4 provides detailed statistics for the MultiProSE dataset.
# Agile Stage-Gate Approach for Design, Integration, and Testing of a 1U CubeSat
###### Abstract  
Life cycle stages are very important for the aerospace industry. Many models have emerged for handling the processes within and across the development of new products. Developing CubeSat-based missions has shortened the required time and has reduced expenses. However, the lack of strategic planning in the design, integration, and testing of product development models has been highlighted as one of the key issues contributing to failures. The objective of this study is to propose a new hybrid model for the physical development of a product using an Agile Stage-Gate methodology focused on a 1U CubeSat (AztechSat-1). This study aims to explain the full process throughout the project timeline from conceptualization to execution. The benefits of such a model include ensuring adaptive responses to not only improve technical integration but also allow the successful validation and verification of a nanosatellite. Our theoretical approach articulates an in-depth understanding of Agile Stage-Gate methodology through experience obtained from experts and team members. Our analysis supports the expected benefits of the iterative process at every stage. Through this approach, product development could benefit from reduced times and better innovations. Nevertheless, there are also drawbacks to this method. The requirements of greater human effort, more frequent demonstrations, and a constant review process have negative impacts. Additionally, particular modifications must be made for each area of research. For educational purposes, the initial results seem to be encouraging.  
CubeSat; nanosatellite; hardware; product development; Agile Stage-Gate; hybrid model 11 September 202330 October 20239 November 202322 April 20242024111324[[https://doi.org/10.3390/aerospace11040324](https://doi.org/10.3390/aerospace11040324)]([https://doi.org/10.3390/aerospace11040324](https://doi.org/10.3390/aerospace11040324))
# Complexity Reduction of MLSE and MAP Equalizers Using Modified Prolate Basis Expansion
## 4 Conclusions  
A near-optimum orthogonal MLSE and orthogonal MAP equalizers based on BEM in the time-delay domain and using the modified version of prolate functions were first time introduced in this work. They show the same performance as the classical algorithms, but with lower computational effort. Whenever the length of the channel impulse response is greater than the number of basis functions needed in the basis expansion model, the sums and multiplications of the MLSE and MAP algorithms, as well as the execution time, are substantially reduced. The use of the MPFs as the basis expansion model offers the benefit of being robust to the particular channel realization. For an equal computational effort, our proposal presents better performance than state of the art alternatives, or conversely, for achieving a predefined BER, our proposal requires fewer operations and memory locations.  
[PERSON] was responsible for initial conceptualization. [PERSON], [PERSON], and [PERSON] declare that they have materially participated in the research, formal analysis and writing of the paper and have contributed equally to this paper. [PERSON], [PERSON], and [PERSON] read and approved the final manuscript.  
Figure 3: Performance of the equalizers [15] and the proposed 5-MPFs with 16-QAM modulation scheme.  
**Funding:** This research was funded by National Council of Science and Technology (CONACYT) No. 240813 and Grant Intel Labs \"Beyond OFDM Systems\".  
**Acknowledgments:** The authors would like to thanks for the support in this work of the National Council of Science and Technology (CONACYT) and Intel Labs.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Study on the Earth Pressure during Sinking Stage of Super Large Caisson Foundation
## 2 Overview of Changtai Yangtze River Bridge
### Soil Excavation Procedure  
The soil excavation directly influenced the sinking safety of caisson foundation, so, random soil excavation is not permitted in the sinking construction of large caisson foundation. For the caisson foundation of Changtai Yangtze River bridge, the soil excavation was carried out according to the principle as the follows, the soil is excavated from the inner compartment to external compartment. Moreover, the soil is removed from inside the compartment to the blind area of the foot blade. Besides, uniform and symmetrical soil excavation was required, and the deviation should be timely corrected. Figure 7 showed soil excavation in the field. Before the soil excavation, the elevation of mud surface is \(-30\) m and the bottom elevation of outer bulkhead is \(-31.85\) m. After soil excavation at the first stage, the elevation of mud surface is \(-32.85\) m. The soil excavation procedure was described in Figure 8 and Table 2 at the first sinking stage of caisson foundation.  
Figure 5: Layout of soil pressure sensors.  
Figure 6: Installing completion of soil pressure cell.  
Figure 7: Overall soil excavation of caisson foundation.  
The sinking resistance during the sinking process of caisson foundation includes end resistance and side friction resistance. The variation of earth pressure at the foot blade during sinking process of the caisson foundation was only focused on in this paper, As is known, at the first sinking stage of caisson foundation, the side friction resistance is close to 0, which will gradually increase with the sinking process, however, it is not easy to definitely determine the side friction resistance at certain sinking elevation. Therefore, in order to greatly reduce the influence of side friction resistance, the first sinking stage was only studied from the mud surface elevation \(-30.0\) m to the elevation \(-31.85\) m.
## 2 Results and Discussion
### Targeted Analysis of Aroma-Related Volatile Compounds
#### 2.1.3 Differentiation of Regular and Decaffeinated Coffee by Aroma-Related Volatiles  
Using the data set of 52 aroma-related volatiles from three pairs of coffee (R-R vs. D-R, R-F vs. D-F, R-VO vs. D-VO), principal component analysis (PCA) screening was conducted to visualize a potential clustering trend between the regular and the decaffeinated coffee groups. As can be seen from the PCA scores plot, a significant clustering trend was observed between the two groups (Figure 2), which indicated that the aroma-related volatile contents were able to differentiate the two types of coffee. Applying the feature selection tools, a threshold of \(p<0.1\) was set for the univariate analysis, \(t\)-test, and a threshold of variable importance in projection (VIP) score \(>0.8\) was set for the multivariate analysis, partial least squares-discriminant analysis (PLS-DA). Both approaches presented the same top 25 significant features among the 52 aroma-related volatiles (Figure 2b-d). The heatmap of the top 25 features separated the volatiles into two clusters (Figure 3). The volatiles in the upper group highlighted in blue correspond to pyrazines. Their content was higher in the regular coffees and lower in the decaffeinated coffees. The lower group featured in red outlined several chemical families, such as aldehydes, ketones, furans, pyridines, acids, pyrroles, and sulfur-containing compounds. This group showed relatively higher content in the decaffeinated coffees compared to the regular coffees.
# A New Passive Islanding Detection Solution Based on Accumulated Phase Angle Drift
## 5 Simulation Test
### Stability under System Fault  
The passive islanding detection methods are required to remain stable under the external system fault condition. The mal-operation of the islanding detection could cause the loss of the power from distributed generators, which is detrimental for system stability. The external system fault can happen on the adjacent feeders, the MV busbar, the HV side of the transformer, or the upstream transmission system.  
As shown in Figure 6, the simulation model defines the system fault located on the adjacent feeder near the utility substation. During the stability tests, different fault types with different fault resistances are applied to verify the stability of the proposed PAD solution. Generally, it is easier for this proposed solution to remain stable during high impedance faults where the system frequency is almost no change. All these faults happen at 0 s and are cleared at 100 ms. Totally, eight test cases were created and the results are shown in Table 5.  
In Table 5, the \"fault voltage\" means the minimum voltage at the fault location. The voltage measurement at the SM terminal is larger than the \"fault voltage\" due to the cable impedance. \"PAD calculation started?\" means if the calculation of accumulated phase angle drift is initiated.  
For the external solid three-phase fault with 10% Vn retained voltage, Figure 9a shows the frequency measurement and Figure 9b shows the accumulated phase angle drift respectively, under three-phase fault and the frequency oscillation after fault clearance.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Fault Type** & **Fault Voltage** & **PAD Calculation Started?** & **PAD Value** & **PAD Solution** \\ \hline AG & 10\%Vn & No & 0 & Stable \\ AG & 70\%Vn & No & 0 & Stable \\ AB & 10\%Vn & No & 0 & Stable \\ AB & 70\%Vn & No & 0 & Stable \\ ABG & 10\%Vn & No & 0 & Stable \\ ABG & 70\%Vn & No & 0 & Stable \\ ABC & 10\%Vn & Yes & 9.9\({}^{\circ}\) & Stable \\ ABC & 70\%Vn & Yes & 4.1\({}^{\circ}\) & Stable \\ \hline \hline \end{tabular}
\end{table}
Table 5: Stability of PAD solution with default settings under different system faults.  
Figure 9: (**a**) Frequency measurement; (**b**) accumulated phase angle drift under three phases fault and the frequency oscillation after fault clearance.
# Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation
## 3 Results and Discussions
### Monitoring the Heatwave Impact on Vegetation Lising LDAS-Monde
Significant anomalies could then be used to trigger more detailed monitoring and forecasting activities for a region of interest using, for example the LDAS-HRES. The Summer 2018 heatwave clearly had an impact on vegetation and soil moisture, as seen using satellite derived estimates of LAI and SSM. Those satellite estimates are very useful to monitor extreme events impacts but their use is limited by their temporal frequency of a few days at best. While microwave remote sensing provides a way to quantitatively describe the water content of a shallow near-surface soil layer, [76], the variable of interest for applications in short- and medium-range meteorological modeling and hydrological studies over vegetated areas is the root-zone soil moisture content which controls e.g., plant transpiration [68]. Similarly, estimates of above-ground biomass might be more useful than LAI for applications linked to agriculture. Integration of these satellite derived datasets into LSMs through data assimilation is, therefore of paramount importance to improve monitoring accuracy of extreme events impacts on LSVs. Not only the representation of LAI and SSM in such system would be improved but other model variables will benefit from the assimilation through biophysical processes and feedback in the model too [7, 10, 18, 77]. Figure 7: Maps of monthly anomalies (expressed in units of standard deviation) from LDAS-ERA5 analysis for July 2008, 2010, 2012, 2014, 2016 and 2018 with respect to the 2008–2018 period (from left to right) for the following variables: soil moisture form the fourth layer of soil (between 20 cm and 40 cm), drainage, runoff and evapotranspiration (from top to bottom).
## 3 Benefits of Biochar Amendment in Green Roofs
### Runoff Quality Improvement
Most studied pollutants in [71] comprising TP, TN, and organic carbon had lower loads after the application of biochar, with the exception of inorganic carbon. [PERSON], [PERSON], [PERSON] and [PERSON] [74] evaluated the ability of coconut-shell-based biochar in removing nutrients and heavy metals from GR discharge. Results from a monitoring period of more than one year confirmed the positive effects of biochar on runoff quality by reducing loads of TN, potassium (K\({}^{+}\)), calcium (Ca\({}^{2+}\)), iron (Fe), and zinc (Zn). Additionally, biochar was effective in reducing the levels of both TP and TN in GR runoff [88]. More specifically, the average annual loads of TP and TN were reduced from 130 and 3500 mg/m\({}^{2}\) to 50 and 1100 mg/m\({}^{2}\) in on-site planted GR platforms; and from 125 and 1200 mg/m\({}^{2}\) to 55 and 600 mg/m\({}^{2}\) in pre-grown mats, respectively. The impacts of biochar in the study of [PERSON], [PERSON] and [PERSON] [89] were more pronounced in the final flush at the end of the 115-day greenhouse experiment. Loads of TN and dissolved P, K, Ca, and Mg (magnesium) in the discharge were diminished by 59%, 20%, 28%, 34%, and 32%, respectively, by using unprocessed biochar. [PERSON], et al. [98] assessed the fertilizer retention performance of four GR test plots and confirmed the positive effects of biochar. They concluded that higher biochar amendment rates resulted in lower nitrogen loss rates. Consistent with the findings on pollutant loads, several studies indicated a reduction in pollutant concentrations following the application of biochar. [PERSON], et al. [99] concluded that biochar was able to delay the leaching effect of TP and enhance the retention of TN. [PERSON], et al. [100] concluded that biochar is a promising soil additive to deal with runoff quality degradation, which is a current concern for GRs. Wood biochar and olive husk biochar were both observed to have a high adsorption capacity of different heavy metals, consisting of Cd (Cadmium), Cu (Copper), Cr (Chromium), Ni (Nickel), Pb (Lead), and Zn. The addition of 5.4% \(v/v\) biochar in the study by [PERSON], et al. [101] resulted in decreased nutrient concentrations of TN and dissolved P, K, Ca, and Na in discharge from GR modules with sedum mats. However, the authors observed no impacts of biochar on nutrient loading over three years.