esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Analytical Determinations
#### 2.5.3 Oxidative Stability  
Grapeseed oil was fortified with the EGPs derived from the RP and WP under the optimal ultrasound-assisted extraction (UAE) conditions. Concentrations of 10%, 20% and 30% of the EGPs from both the RP and the WP were used to fortify the oil, and its oxidative stability was compared with that of the control (grapeseed oil only). As a benchmark, BHT was used as a synthetic antioxidant at a concentration of 200 ppm, aligning with the maximum level permitted by the Codex Alimentarius 2023 [19]. The optimized EGPs were mixed with grapeseed oil using ultrasonic treatment at an amplitude of 25% for 2 min and 30 s split into 30 s cycles. Subsequently, the samples were homogenized with an Ultra Turrax T-25 (Janke and Kunkel, Staufen, Germany) at a speed of 12,000 rpm for 5 min. The samples (3 g each) were then analyzed for their oxidative stability using the official Rancimat method at 110 \({}^{\circ}\)C and using an air flow of 20 L/h. Oxidative stability was measured according to the induction time (IT), which indicates the time passed (expressed in hours) before the conductivity of water (\(\upmu\)S/min) begins to increase due to the formation of secondary compounds derived from lipid oxidation. The Antioxidant Activity Index (AAI) was calculated using the following formula (Equation (2)):  
\[AAI=\frac{IT\:of\:oil\:with\:antioxidants}{IT\:of\:oil\:without\:antioxidants( control)} \tag{2}\]
# Reliability and Validity of the Portable KForce Plates for Measuring Countermovement Jump (CMJ)
###### Abstract
Nevertheless, due to their high cost and the need for specialized software programs to analyze the data, Apple Inc. (Cupertino, CA, USA) recently launched the My Jump 2 application, which was developed by [PERSON] [15]. It calculates jump height by recording a high-speed video using smartphones' and tablets' ability to record a high image resolution, and therefore, the flight time of a jump exercise could be manually evaluated via the video frames of take-off and landing positions [16; 21]. The app has been proven valid for different sports populations, such as sports science students and young recreational athletes [22; 23], the elderly [24], and trained athletes [25]. The aim of the present study was to test the reliability and validity of a portable force platform (the KForce Plates system by Kinvent) for the evaluation of CMJ in collegiate professional athletes compared to the validated application My Jump 2 [16; 21]. The portable Kforce plates have recently been confirmed to be valid and reliable only for assessing single-leg and dynamic balance and not for measuring CMJ. Our thesis was that CMJ assessment in the sports field could be the best option to observe sports performance, limp asymmetries, neuromuscular fatigue, and the efficacy of training protocols. We hypothesized that the CMJ measurements (jump height and flight time) via the portable lightweight Kforce plates would be reliable and valid in the laboratory environment and also in the sports field. A group of collegiate professional athletes performed a CMJ on the Kforce plates and the My Jump 2 application concurrently between days 1 and 7.
# Common-Ground Photovoltaic Inverters for Leakage Current Mitigation: Comparative Review
## 2 Classification of Common-Ground Converters  
Several CG converters have been reported in the literature. These converters can be classified into two categories:  
- Current-source CG converters (CSCG);  
- Voltage-source CG converters (VSCG); this category can be further classified as follow:  
(a) Bucking VSCG;  
(b) Boosting VSCG;  
(c) Buck/boost VSCG. Table 3 lists the converters that belong to each of these categories and illustrates the following characteristics for each converter:  
- Number of semiconductors (switches and diodes) and number of passive components (capacitors and inductors) along with their values adopted in the reported experimental results of each converter: this can imply the size, cost, complexity, and efficiency of these converters;  
- Its capability to offer continuous input current is an important feature for the proper and efficient operation of maximum power point tracking (MPPT) in PV systems [31; 32];  
- Input/output voltage gain (for VSC converters): high boosting gain is an important feature in PV converters. This can significantly reduce the capacitance required for power decoupling; in addition, this reduces the required number of series-connected PV modules for grid-tied systems;  
- Number of available voltage levels (for VSCS converters): this can help to determine the required filter size; a higher number of voltage levels implies reduced filter size [33; 34; 35];  
- Number of semiconductors conducted during positive and negative half-cycles of output inverter voltage. Asymmetric inverter operation through using an inequal number of semiconductors in the current path during positive and negative half-cycles can produce DC current components [14; 15];  
- The reported efficiency for each converter: this implies the total losses for each converter; these losses can be varied according to the converters' structure and switching mechanism. In the following sections, the features and limitations of the converters belonging to each of the above groups are discussed.
## 3 Experiment and Results
### Entropy Function Selection  
The entropy functions for EEG identification are set as Entropy_Approximate (\(A\), \(m\), \(r\)), Entropy_Fuzzy(\(A\), \(m\), \(n\), \(r\)), Entropy_Sample(\(A\), \(m\), \(r\)) and Entropy_Spectral (\(A\)), where \(A\) is the input matrix. Based on EEG acquisition frequency, \(F_{8}\) = 1000 and segment length of each sample \(N\) = 1000; the data reconstruction dimension is \(m\) = 2. For fuzzy entropy index gradient \(n\), we set \(n\) = 4; while for spectrum entropy, the Pburg algorithm was selected for power spectrum estimation, and the spectrum estimation order is 7. The entropy tolerance \(r\) has direct influence on the entropy value. Too-large tolerance would let in redundant signals that interfere with genuine features. If the selected \(r\) value is too small, feature sensitivity is increased so that the entropy value is disordered by the noise. Proper \(r\) is needed for feature stability and the quality of classification index.
# The Design of an Energy Harvesting Wireless Sensor Node for Tracking Pink Iguanas
## 2 The Pink Iguana Tracking Problem  
The existence of the new isquana species was reported to Science in 2009 [5]. Since then, pink isquana rapidly became a flagship species, internationally recognized in Science, Arts, and Society [6]. The species, which has substantial evolutionary legacy [7]), is endemic to Wolf Volcano on the Isabela island (Galapagos, Ecuador), at altitudes ranging from 600-1700 m asl. It lives in syntopy with a population of _C. subcristatus_, another endemic species of isquana, and the two species do not hybridize. There are several issues that threaten the existence of pink isquanas. These include the small population size (census \(N=192\); \(Ne=90.7\)), the limited area of distribution (less than 25 km\({}^{2}\)) depicted in Figure 1, the possible competition with synoptic species, and finally the presence of introduced predators (feral cats and black rats). In 2012, this species was included in the International Union for Conservation of Nature (IUCN) Red List, under the category Critically Endangered [8].  
The difficult access to the site limits the duration of field studies. Thus, current knowledge about the reproductive biology of both the syntopic species in Wolf Volcano is scarce. Ultrasound and hormonal surveys, performed when the species are sexually active, indicate that only a few _C. marthae_ females reproduce, with _C. marthae_ showing a smaller clutch size than _C. subcristatus_[9]. Since 2005, no hatchlings, only one juvenile, and a few subadults was observed. This strongly suggests that population recruitment may be non-effective. For these reasons, the Galapagos National ParkDirectorate, the legal authority that governs the biodiversity of Galapagos islands, is considering a head-start program to increase the number of pink iguanas.  
The habitat of pink iguanas is found on the top and along the slopes of Wolf Volcano, a harsh environment characterized by small craters, canyons and thick vegetation. The area includes tropical dry shrub land at the top of the volcano and tropical dry forest along the slopes. Temperature at the highest altitudes may range from approximately 10 \({}^{\circ}\)C (night) to 35 \({}^{\circ}\)C (day). Vegetation may be impacted by droughs. It must be noted that the harsh terrain and difficult logistics of the area do not allow the use of long-term traditional radio-tracking techniques. Attempts to use GPS devices on land iguanas were carried out in the early 2000 s, and proved unsuccessful mainly due to the large size of the smallest GPS equipment available and difficult logistics. However, the advance of technology and miniaturization of components allows us to devise small devices that better fit the requirements of a pink iguana monitoring scenario.
# ISAC towards 6G Satellite-Terrestrial Communications: Principles, Status, and Prospects
## 4 Development Trend and Key Technology of ISAC towards 6G ISTNs  
### Future Application Scenario  
In ISAC, signals are used to realize the sensing functions such as detection, localization, identification, and imaging. It obtains information about the surrounding environment, allocates communication resources intelligently and precisely, and enhances the user experience [89]. The satellite-terrestrial integration network will involve the deep integration of space-based, air-based, and ground-based networks to realize the access and application of unified terminal equipment to satisfy different users. satellite-terrestrial ISAC can further sense the ground conditions, thus better elucidating the city operation, environmental changes, and other information. It provides intelligent decision-making for overall satellite-terrestrial deployment, realizes dynamic deployment of resources, and optimizes the efficiency and performance of the system. This section considers three potential application scenarios of satellite-terrestrial ISAC and proposes a satellite-terrestrial network architecture for ISAC.
## 2 Results and Discussion
### Identification of Peptides in Viscera Extracts  
As previously described, the salmon viscera extracts obtained through PLE-assisted extraction resulted the most interesting sample in terms of in vitro antioxidant capacity. Their TEAC and ORAC values not only stand out against the other salmon byproducts studied here, but also in comparison with previously investigated PLE protein extracts from sea bass and sea bream viscera. For this reason, PLE protein extracts from salmon viscera were selected for the identification of antioxidant peptides. Control viscera extracts were also screened in order to compare peptides extracted through PLE and under stirring conditions. Only peptides with a confidence percentage \(\geq\) 90% have been reported. A total of 137 peptides were identified in the PLE viscera extracts (Table 1). In contrast, 67 peptides were identified in the viscera control extracts (Table 2). Despite using the same viscera sample, only five peptides matched in both extracts (color marked in both tables). These data show that the extraction conditions used for PLE-assisted extraction influence the peptides obtained from salmon viscera. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Protein of Origin of the** & **Sequence** & **Obs MW** & **Obs \(m/z\)** & **Theor z** \\
**Identified Peptide** & & & & \\ \hline Collagen alpha-2(I) chain & GESGPTGNGGPVGA & 1155.52 & 578.77 & 2 \\ Collagen alpha-2(I) chain & GPAGPHGPG & 842.4 & 422.21 & 2 \\ Collagen alpha-2(I) chain & SGETGSAGITGPAGPR & 1413.68 & 707.85 & 2 \\ Uncharacterized PE-PGRS family protein & GGNGGAGG
## 4 Acoustic Field Reconstruction
### Methods for 3D Reconstruction
With this in mind, plane wave \(\Phi_{\mathbf{k}}\) is defined as follows:  
\[\Phi_{\mathbf{k}}(\mathbf{r})=F(k_{z})e^{-j\big{(}k_{x}x+k_{y}y+k_{z}(z-z^{+}) \big{)}}, \tag{8}\]  
where \(F\) is the amplitude of wave, \(z^{+}\) is the plane of the virtual source and \(\mathbf{k}=\{k_{x},k_{y},k_{z}\}\) is the wave number whose component \(k_{z}\) is defined as follows:  
\[k_{z}=\left\{ \begin{array}{ll}\sqrt{k^{2}-(k_{x}^{2}+k_{y}^{2})}&\text{if }(k_{x}^{2}+k_{y}^{2})\leq k^{2}\\ -j\sqrt{(k_{x}^{2}+k_{y}^{2})-k^{2}}&\text{if }(k_{x}^{2}+k_{y}^{2})>k^{2} \end{array} \right., \tag{9}\]  
with \(k^{2}=\|\mathbf{k}\|^{2}=k_{x}^{2}+k_{y}^{2}+k_{z}^{2}\). The work of [PERSON] [31; 38; 39] on the SONAH method showed that it is relevant to define the projection functions \(\Psi\) according to the waves defined in Equation (8):  
\[\Psi_{n}(\mathbf{r})=\kappa\Phi_{k_{n}}(\mathbf{r}),\quad\kappa=\sqrt{\frac{ \Delta k_{x}\Delta k_{y}}{2\pi k^{2}}}. \tag{10}\]  
\(\Delta k_{x}\) and \(\Delta k_{y}\) result from the discretization of the wave number and therefore from the choice of the number of projection functions used. It is also shown that a good choice of function \(F(k_{z})\) is obtained with  
\[F(k_{z})=F_{0}\sqrt{\frac{k}{|k_{z}|}}. \tag{11}\]  
It is interesting to note that it is possible to calculate matrix \(\mathbf{A}^{H}\mathbf{A}\) and vector \(\mathbf{A}^{H}\boldsymbol{\alpha}\) to avoid choosing the number of \(N\) functions retained. Therefore, as [PERSON] shows for the SONAH method [31],  
\[\Big{[}\mathbf{A}^{H}\mathbf{A}\Big{]}_{ij}=\sum_{n}\Phi_{k_{n}}^{*}(\mathbf{ r}_{i})\Phi_{k_{n}}(\mathbf{r}_{j})\frac{\Delta k_{x}\Delta k_{y}}{2\pi k^{2}} \underset{ \begin{subarray}{c}\Delta k_{x}\to 0\\ \Delta k_{y}\to 0\end{subarray} }{\longrightarrow} \frac{1}{2\pi k^{2}}\int_{-\infty}^{\infty}\int_{-\infty}^{ \infty}\Phi_{k}^{*}(\mathbf{r}_{i})\Phi_{k}(\mathbf{r}_{j})dk_{x}dk_{y}, \tag{12}\]  
\[\Big{[}\mathbf{A}^{H}\boldsymbol{\alpha}(\mathbf{r})\Big{]}_{i}=\sum_{n}\Phi _{k_{n}}^{*}(\mathbf{r}_{i})\Phi_{k_{n}}(\mathbf{r})\frac{\Delta k_{x}\Delta k _{y}}{2\pi k^{2}}\underset{ \begin{subarray}{c}\Delta k_{x}\to 0\\ \Delta k_{y}\to 0\end{subarray} }{\longrightarrow} \frac{1}{2\pi k^{2}}\int_{-\infty}^{\infty}\int_{-\infty}^{ \infty}\Phi_{k}^{*}(\mathbf{r}_{i})\Phi_{k}(\mathbf{r})dk_{x}dk_{y}. \tag{13}\]  
This calculation procedure makes it possible to define a formulation which allows the linking of calculated pressures to the measured pressures without discretizing the number of waves and the number of projection functions. However, it should be noted that the process of numerical calculation of the integrals involved in Equations (12) and (13) gives rise to spatial discretization.
# A Proactive Approach to Extended Vehicle Routing Problem with Drones (EVRPD)
## 4 Materials and Methods--Implementation of the EVRPD Model
### Dedicated Genetic Algorithm
#### 4.2.1 Dedicated Representation of Individuals for the EVRPD  
This algorithm used an appropriate representation of individuals for the EVRPD, which, considering the knowledge of the problem, reduced the number of unfulfilled constraints during the operation of the algorithm. Everyone in the population was determined by customer index j\(\in\)C which was assigned to a specific drone d\(\in\)D. Thus, it was a two-dimensional representation with delivered shipments and parcels s\(\in\)S assigned in pairs (_j_, _d_). The proposed representation is shown in Figure 3. It should be emphasized that the index s has been included in Figure 3 to better demonstrate the proposed representation. In practice, the pair (_j_, _d_) was enough to code an individual.  
Figure 1: Diagram of model implementation using AMPL and MP solver.  
Figure 2: Block diagram of the proposed dedicated genetic algorithm (DGA).  
Using this representation, the number of unfulfilled constraints was reduced. This representation of an individual meant that only the following constraints were not fulfilled: constraint (5)--the drone's payload; constraint (9)--the drone's run was executed within the required time; constraint (14)--take-offs were only from the allowed number of MH points. Therefore, in the developed genetic algorithm (Figure 2) for the generation of individuals, corrections were proposed that eliminated individuals who did not fulfill constraints (a)-(c). A detailed description of individual DGA elements is presented in Sections 4.2.1 and 4.2.4.
###### Abstract  
Accurate assessment of net primary production (NPP) can truly reflect the carbon budget balance of the forest ecosystem. In this study, the boreal ecosystem productivity simulation (BEPS) model was used to simulate the NPP of Saiharba mechanized forest farm in 2020, and the influencing factors of NPP were analyzed. The meteorological, forest cover, leaf area index (LAI) and other data required for the model, as well as the data for verifying, were from field surveys or downloaded from different sources. The results showed that: (1) Within the scale of the flux tower, the diurnal variation of NPP reached a maximum in June. The monthly average peak value of latent heat flux was in June, and the sensible heat flux was in March. The temperature of the understory canopy was mostly higher than that of the overstory canopy and air temperature. (2) At the regional scale, the total NPP in the study area in 2020 was 4.25 \(\times\) 10\({}^{11}\) g C a\({}^{-1}\), with an average of 564.71 g C m\({}^{-2}\) a\({}^{-1}\). The annual average NPP of silver birch (_Betula platphylula_) was the largest, and the total NPP of northern Chinese larch (_Larix principis-ruprecchiti_) was the largest. (3) NPP was highly sensitive to LAI. Topographic factors had effects on NPP. The average value of NPP was relatively high in the shady slope and the gentle slope.  
BEPS model; artificial forest farm; flux tower; spatio-temporal analysis Article
# Real-Time Visual Feedback in Singing Pedagogy: Current Trends and Future Directions
## 3 The Oscillatory Subsystem  
In addition to \(p_{\rm sub}\), singers must learn to master vocal fold tension, extension and adduction, as these are crucial to intonation, vocal registers and phonation types. These parameters can be visualized by means of an electroglottograph (EGG), an electrolaryngograph (ELG) and an inverse filter unit. Both EGG/ ELG can show vocal fold contact variations in real-time [37; 38], while an inverse filter can provide feedback of variations in glottal airflow [33].
## 5 Use Cases
### Spatial Patterns and ADR Clustering: Interactive Geographic Map  
Following [PERSON] et al.'s [23] emphasis on contextual sensitivity in policy design, this interactive map visualizes spatial distributions of ADR and cancellation rates across geographic regions. The implementation aligns with [PERSON] and [PERSON]'s [22] analysis of meta-organizational frameworks, particularly in how regional decision-making structures influence market outcomes.  
The spatial map highlights regional disparities and clustering effects:  
* Geographic insights: identifying regions with high ADR and low cancellation rates as benchmarks for stable markets.
* Spatial dependencies: visualizing spatial autocorrelation to support econometric models of cancellations.
* Policy recommendations: highlighting areas for targeted interventions based on regional market conditions.
# A Termination Criterion for Probabilistic Point Clouds Registration
## 1 Introduction  
Point clouds registration is the problem of finding the transformation (mostly a rigid transformation) that best aligns two point clouds, usually called the source and target point clouds.  
One of the first approaches to this problem, and still one of the most used, is Iterative Closest Point (ICP) [1; 2; 3], which aligns two point clouds by minimizing the sum of distances between corresponding points, where corresponding points are nearest neighbouring points. Probabilistic Point Clouds Registration (PPCR) [4] is a variant of ICP that uses a probabilistic model to improve the robustness against noise and outliers, one of the most relevant problem of local registration algorithms. Much like ICP, it is an iterative algorithm that repeatedly tries to improve a solution, until a stopping criterion is satisfied.  
The experiments show that it outperformed most state-of-the-art local registration algorithms in this field. However, these experiments have been performed using a large fixed number of iterations as stopping criterion. Instead, we think that, to be of practical utility, an iterative algorithm should autonomously decide when to stop. Indeed, using a fixed number of iterations on one hand does not guarantee that the best solution have been found; on the other, it could result in an excess of computation time, because the solution have been found earlier.  
Despite the relevance of the topic, very little research has been conducted on finding the best termination criterion for point clouds registration algorithms. Moreover, many commonly used techniques have parameters to fine tune to each specific application [5].  
For these reasons, we propose an improvement of PPCR, analyzing different termination criteria and finding the best one. Furthermore, we demonstrate that the chosen solution is as effective as using a very large number of iterations but, at the same time, results in fewer iterations and, therefore, less computational time. The experiments have been conducted on the IRALab Point Clouds Registration Benchmark [6], which is composed of many different point clouds from different environments. We used the same set of parameters for every experiment, to prove that it is generic enough that it does not need to be fined tuned to different environments.