esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
Many factors, such as the cultivar, the environmental conditions in the orchard, the ripeness of the olives, the condition of the fruit, and the processing methods used, influence the quality of extra virgin olive oil [1]. Extra virgin olive oils contain compounds that not only play an important protective role but also have nutritional value. The antioxidant heritage extends the shelf life of extra virgin olive oil and is fundamental for its health properties [2, 3]. In Italy, the high number of olive cultivars, with around 500 registered [4], allows for the obtaining of monovarietal oils of great value, and important impacts on sensory profiles [5].  
The Leccio del Corno is a variety of olive tree that was selected for its exceptional resistance to the low temperatures near the \"Corno\" farm in the municipality of San Casciano Val di Pesa (FI) in Italy [6]. The plant is moderately vigorous with a broad crown. The leaves are medium in size and dark green. Leccio del Corno is a self-pollinating variety; Pendolino, Frantoio, and Piangente are excellent pollinators. The fruit is medium-sized and ovoid in shape (Figure 1).  
Ripening is late and scalar. The fruit is green at harvest. Leccio del Corno is a rustic plant of great adaptability with good resistance to adverse climatic and phytosanitary events. Its productivity is average and constant. Our research was focused on the Leccio del Corno variety, not only for its excellent adaptation to low temperatures but also for its remarkable resistance to the bacterium _Xyllella fastidiosa_ subsp. _pauca_[7; 8]. For this reason, the Italian Ministry of Agriculture, Food Sovereignty and Forestry (Masaf) [9], with a note prot. n\({}^{\circ}\) 0179664, dated 19 April 2024, authorized planting of the Leccio del Corno variety, which is tolerant to the _pauca_ subspecies [10], in an area infected by _Xyllella fastidiosa_ subsp. _pauca_. Use of the Leccio del Corno variety could represent a valid alternative for restoring production capacity while increasing olive biodiversity in the area infected by this bacterium. In addition, little is known about the volatile components, the sensory properties, and the antioxidant capacity of this monovarietal virgin olive oil. Therefore, our research aims to characterize the volatile chemical composition and antioxidant and sensory properties of this product in order to valorize it. The global quality of the oil is closely linked to its stability against oxidation, which depends first and foremost on the content of antioxidants. In this respect, a recent study has shown that Leccio del Corno is a variety with medium oxidative stability [11]. Given the positive characteristics found in the few existing studies on Leccio Del Corno monovarietal extra virgin olive oils [1; 12], the main objective of this study was to increase knowledge by analyzing sensory and volatile profiles related to quality and antioxidant activity.
## 4 The Dynamic Amplification Effect of Large-Scale Slope Subjected to the Non-Uniform Seismic Waves
### Numerical Simulation for Amplification Factor of SRA Considering the Scale of the Slope  
Different scale models are established to simulate the acceleration amplification effect. Configurations of models in Section 2.2 are adopted, and the value of Equation (26) is represented by the contours of the amplification factor of SRA. As shown in Figures 12 and 13, SRA are amplified from the base to the surface of the slope under the excitation of seismic waves. In the case of uniform incidence (Figure 12), the contours of amplification factor of SRA are found to have a layered distribution. Conversely, in the case of non-uniform incidence (Figure 13a-d), the amplification factor is concentrated on the slope surface. Notably, as \(L/h\) increases, the magnification factor becomes increasingly concentrated, and the amplification effect becomes increasingly evident. It can be concluded that \(L/h\) is a significant factor in the amplification effect of the non-uniform dynamic response.  
Figure 12: Contours of amplification factor of SRA with different slope scales under uniform seismic incidence. \(L=2000\) m, \(L/h=4:20\); \(h\) denotes the focal depth; \(L\) denotes the length of the slope.  
In conclusion, the amplification effect at the surface of the slope presents a distribution of concentration in the dynamic response subjected to non-uniform seismic wave incidence. This result is consistent with those of [PERSON] et al. [20], who used the ABAQUS software platform to investigate the spatial variability characteristics of the seismic response at the ground surface under the influence of a traveling wave. With increases in bottom width, the amplification area caused by the terrain scattering effect gradually expands [25]. In the numerical simulation results of this paper, the non-uniformity of the dynamic amplification effect cannot be disregarded in the case of \(L/h>4:20\). Slopes of this scale subjected to seismic wave incidence satisfy the BAP principle. Conversely, the dynamic response exhibits uniformity in the case of \(L/h<1:20\), which is in accordance with the plane wave assumption of [PERSON] principle.
# Trend Prediction of Event Popularity from Microblogs
## 3 Methodology
### Popularity Index Modeling and Weighting  
Regarding multivariate microblog data, univariate analysis cannot well reflect the systematic change of the trend of microblog popularity. Additionally, various factors have different impacts on the popularity of microblog events, so they should play different roles in popularity prediction modeling. Meanwhile, for microblog messages, those with more user interactions have greater social popularity. Therefore, the post number, forwarding number, commenting number and the total number of likes are used to model the popularity index. In the paper, the information entropy algorithm is used to assign the weight of popularity indicators. Information entropy can be used to measure the dispersion of an index. The greater the dispersion of an index, the greater the impact of the index on the comprehensive evaluation, that is, the greater the weight.  
Specifically, this paper takes the number of days of each event as the evaluation individual and the above four indicators as evaluation index. Here, in order to eliminate the dimensional differences between the evaluation indexes, this paper needs to preprocess origin data through benefit (positive) index calculation and cost (negative) index calculation, defined by Formulas (1) and (2) respectively.  
\[y_{i,j}=\frac{x_{i,j}-\min(x_{i,j})}{\max(x_{i,j})-\min(x_{i,j})}*(y_{\max}-y_{ \min})+y_{\min} \tag{1}\]  
\[y_{i,j}=\frac{\max(x_{i,j})-x_{i,j}}{\max(x_{i,j})-\min(x_{i,j})}*(y_{\max}-y_{ \min})+y_{\min} \tag{2}\]  
The symbol \(\max(x_{i,j})\) and \(\min(x_{i,j})\) represent the maximum and minimum of evaluation index, respectively. And then, the proportion of the evaluation object can be calculated by Formula (3).  
\[p_{i,j}=\frac{y_{i,j}}{\sum y_{i,j}} \tag{3}\]  
Additionally, the entropy of evaluation index is defined by Formula (4),  
\[e_{j}=-\frac{1}{\log n}{\sum p_{i,j}\log p_{i,j}} \tag{4}\]  
Figure 1: System framework of the event popularity trend prediction from Weibo platform.  
where \(n\) represents the number of evaluation index. Finally, the weight of each indicator is represented by Formula (5). Consequently, our proposal can get the time series of event popularity by index modeling and weighting.  
\[w_{j}=\frac{1-e_{j}}{\sum{(1-e_{j})}} \tag{5}\]
# Influence of Solvent Selection in the Electrospraying Process of Polycaprolactone
## 2 Electrospraying Technology
### Mechanism of Electrospraying
When, the first one has a higher viscosity, and the second one a higher electrical conductivity, the droplet size scales linearly with the flow rate of inner phase and the flow rate of the outer one. For a higher electrical conductivity of the inner liquid coupled to the higher viscosity of the outer one, the breakup process of working solutions mainly depends on the value of \(\frac{Q_{outer}}{Q_{inner}}\). On the one hand, an increase in this ratio leads to an increase of the shell materials, whereas its decrease may achieve uniform coverage of the tiny dispersed droplets. On the other hand, the obtention of a core-shell structure is related to the physical properties of the working solutions, and the flow rates used. Thus, according to [PERSON] et al., the core-shell structured droplets are only formed when the ratio of charge relaxation lengths of the inner and outer liquids (\(\frac{R_{outer}^{*}}{R_{inner}^{*}},R^{*}=(\frac{Qx_{0}}{K})^{\frac{1}{3}}\)) is less than 500, and the ratio of inertial breakup lengths of inner and outer liquids (\(\frac{r_{outer}^{*}}{r_{inner}^{*}},r^{*}=(\frac{QQ^{2}}{\gamma})^{\frac{1}{ 3}}\)) is less than 0.015 [84]. Furthermore, some authors concluded that the cone-jet of inner and outer liquids is achieved when (1) the flow rate of the outer liquid is higher than that of the inner one, (2) the outer liquid has higher viscosity and lower electrical conductivity, and (3) the surface tension of the core solution is higher than that of the shell solution one [85; 86]. The porosity of the structure can also be controlled and designed via electrospraying. During the flight process of charged droplets from the nozzle to the collector, the evaporation of the solvents leads to the solidification of the particles. This last phenomenon is also affected by many factors, including boiling point of solvents, environmental conditions (temperature, humidity, and pressure) and collection method and so on. Therefore, the phase separation process can be controlled to obtain polymeric particles with different porous structures and morphologies, to be used in various application fields.
## 2 System Architecture and Requirements
### Magnitude and Phase Errors on Cancellation  
The required resolution of the canceler depends on the desired cancellation level. In practice, the cancellation level is also severely limited by the frequency selectivity of the coupling between the TX and RX antennas. As shown in [17], considering a typical mobile platform size of 6 cm by 10 cm, a pair of planar inverted-F antennas, commonly used for mobile wireless applications, show a typical coupling of \(-20\) dB and a group delay in the order of 2 ns. For a broadband canceler, this delay results in a minimum cancellation of 20 dB over a 14 MHz bandwidth. Hence, for a broadband canceler such as the one considered in this work, it is reasonable to determine the required canceler resolution based on a target cancellation level of 27 dB.  
If the canceler is affected by a finite magnitude error (V\({}_{\mathrm{\varepsilon}}\)) and phase error (\(\varnothing\)), the resulting relative cancellation error is computed as follows:  
\[\varepsilon=-1+\cos\varnothing\pm\sqrt{\left(\frac{\mathrm{V}_{\mathrm{ \varepsilon}}}{\mathrm{V}_{\mathrm{SI}}}\right)^{2}-\sin^{2}\varnothing}, \tag{5}\]  
where V\({}_{\mathrm{SI}}\) is the self-interference signal, V\({}_{\mathrm{canc}}\) is the cancellation signal from the canceler, \(\varnothing\) is the phase error, \(\varepsilon\) is the magnitude error and V\({}_{\mathrm{\varepsilon}}\) is the residual leakage signal. The maximum magnitude and phase errors for 20, 25 and 30 dB of cancellation are plotted in Figure 4c. If a canceler architecture based on a phase shifter followed by a variable gain was chosen, the required phase and magnitude resolution for 25 dB cancellation would be 3.2\({}^{\circ}\) and 5.6% respectively. While the magnitude accuracy of 5.6% is easily achievable, a phase shifter wit better than 3.2\({}^{\circ}\) resolution is not trivial. The chosen architecture based on two quadrature vectors significantly relaxes the resolution requirements. In fact, assuming each I and Q vector to be programmable with n bits, the minimum achievable cancellation level is [28]  
\[\mathrm{SIC}_{\mathrm{dB}}=20\log\left(\frac{2^{\mathrm{n}}}{\sqrt{2}}\right) \tag{6}\]  
with n = 5 bits a SIC greater than 27.1 dB can be ensured.  
Figure 4: (a) Quadrature phase error; (b) Canceler range reduction due to quadrature phase error; (c) Cancellation in dB with corresponding output vector magnitude and phase error.  
Figure 3: (a) Canceler block design concept; (b) Canceler gain adjustment.
## 3 Results and Discussion
### Water Content, Water Activity, and Hygroscopicity of Insect Powders
The results of the modeling of the adsorption kinetics of black soldier fly powders showed that [PERSON]'s unsteady diffusion equation is suitable and satisfying for adjusting the experimental values due to the high correlation coefficient (R2) values ranging from 0.997 to 0.999 and the low root mean square (RMS) values ranging from 2.50-3.34% (Figure 1, Table 2). The effective water diffusion coefficient and equilibrium water content determined for the tested materials based on [PERSON]'s unsteady diffusion equation are presented in Table 2. The powder obtained by the IR-CD drying method was characterized by a higher equilibrium water content (it is also worth noting that its initial water content was significantly higher). In turn, the water diffusion coefficient, which characterizes the dynamics of the sorption process, was significantly higher in the case of convective drying (CD). It should be assumed that the reason for this was the higher driving force of the sorption process, i.e., the difference between the water activity of the material and the ambient relative humidity. The observed results may be related to the particle size of insect powders. The smaller particle size of the IR-CD insect powder provided greater surface area and greater availability of hydrophilic sites, like polar amino acids, as observed for superfine ground white-spotted flower chater (_Protaetia breitarsis_) larvae [52]. Furthermore, changes in hydrophilic compounds (e.g., proteins) affected the water vapor adsorption. The overheating of the material via infrared radiation is highly probable, especially in its surface layers [53]. It leads to the denaturation of proteins, which exhibit a greater ability for water and water vapor adsorption [54]. That was confirmed via the FTIR spectrum (see Figure 4), as the IR-CD-dried insect powder exhibited a better absorption level for peaks related to amide I and amide II. Thermally treated proteins show higher intensity values of infrared bands, as observed for soy glycinin [54]. \begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**Treatment**} & **Equilibrium Water** & **Effective Moisture** & \multirow{2}{*}{\(R^{2}\)} & **RMS** \\  & **Content** & **Diffusivity** & **(\(-\))** & **(\%)** \\  & **(g H\({}_{2}\)O/100 g d.m.)** & **(\(\times\)10\({}^{-11}\) m\({}^{2}\)/min)** & & \\ \hline CD & 45.48 a \({}^{1}\)\(\pm\) 2.28 & 1.40 b \(\pm\) 0.03 & 0.999 & 2.50 \\ IR–CD & 58.04 b \(\pm\) 2.67 & 1.17 a \(\pm\) 0.11 & 0.997 & 3.34 \\ \hline \end{tabular} \({}^{1}\) The same letters in columns indicate no differences between the mean values (\(l\)-test, \(p\) \(<\) 0.05).  
\end{table} 
Table 2: The parameters of water vapor adsorption kinetics modeling of black soldier fly powders processed by convective (CD) and infrared convective (IR–CD) drying methods.
# Context-Aware System for Information Flow Management in Factories of the Future
## 2 Theoretical Framework
### Industry 4.0  
The term \"Industry 4.0\" refers to the fourth IR and became publicly known in Germany in 2011 [5]. I4.0 promotes the idea of the start of a new IR, driven by the advance and convergence of various technologies that make it possible to connect the physical and digital worlds in real time [8].  
One of the foundations of I4.0 lies in the introduction of interconnected intelligent systems that enable self-sustainable production, in which people, machines, equipment and products communicate with each other [13]. I4.0 is made possible by Internet technologies to create intelligent products, intelligent production and intelligent services, since, from a communications point of view, I4.0 technologies rely heavily on the mobile internet [17]. This revolution aims to boost the competitiveness of the manufacturing sector by improving industrial procedures associated with production, engineering, the application of materials, supply chain management and the product life cycle [5].  
I4.0 incorporates various innovative concepts, such as smart factories (production is equipped with intelligent components), Cyber-Physical Systems (CPS, resulting from the combination of the physical and digital worlds, allowing real-time integration of information), new systems in the development of products and services, adaptation to human needs, among others [18].  
I4.0 is driven by four fundamental principles: [5]  
Interconnection--involves linking machines, devices, sensors and people;  
Information transparency--interconnects the physical and virtual worlds, providing contextual data in real time for appropriate decision-making;  
Decentralization of decisions--combines local and global information to increase productivity at different levels, this is possible thanks to systems that monitor and control the physical world autonomously;  
Technical assistance--uses mobile devices and robotic technology to assist in decision-making and problem-solving.  
The implementation of I4.0 faces a number of challenges in different areas, such as science, technology, the economy, society and politics. It is essential to train workers to use the new technologies. In addition, business issues related to innovation, technological components and digital transformation represent major obstacles. Another major difficulty lies in data analysis and management [19].
# Radiometric Method for Determining Canopy Stomatal Conductance in Controlled Environments
## 3 Results
### Canopy-to-Air Temperature Difference
At each wind speed, \(\Delta\mathrm{T}_{\mathrm{A}}\) calculated from H by inverting Equation (6) was compared with values of \(\Delta\mathrm{T}_{\mathrm{IR}}\) measured by the IR sensors. As incident PPF\({}_{\mathrm{o}}\) increased from 0 to 1700 \(\mu\)mol m\({}^{-2}\) s\({}^{-1}\), \(\Delta\mathrm{T}_{\mathrm{IR}}\) increased linearly from 0 \({}^{\circ}\)C to +4 \({}^{\circ}\)C at low wind speed (Figure 6A, top; 1.7 m s\({}^{-1}\)) and increased from \(-\)1 \({}^{\circ}\)C to +2 \({}^{\circ}\)C at high wind speed (Figure 6B, top; 2.3 m s\({}^{-1}\)). Although the aerodynamic \(\Delta\mathrm{T}_{\mathrm{A}}\) also increased linearly with increasing PPF\({}_{\mathrm{o}}\) (Figure 6A,B), its sign was negative at low to moderate light levels and it had a steeper response to PPF\({}_{\mathrm{o}}\) than \(\Delta\mathrm{T}_{\mathrm{IR}}\) (e.g., changing from \(-\)3 \({}^{\circ}\)C to +4 \({}^{\circ}\)C at the low wind setting; Figure 6A). The radiometric \(\Delta\mathrm{T}_{\mathrm{IR}}\) never equaled zero when \(\Delta\mathrm{T}_{\mathrm{A}}\) was zero (Figure 6) and was often opposite in sign to the aerodynamic \(\Delta\mathrm{T}_{\mathrm{A}}\) (Figure 6A,B, top). The offset correction between the radiometric \(\Delta\mathrm{T}_{\mathrm{IR}}\) and the aerodynamic \(\Delta\mathrm{T}_{\mathrm{A}}\) increased linearly with increasing PPF\({}_{\mathrm{o}}\), but did not vary with chamber wind speed (Figure 6A,B, bottom graphs; the dashed lines are the 95% confidence interval). Smaller values of the offset at high light intensities suggest that the warmer leaves at the top of the canopy play a greater role in H and reduce the differences between T\({}_{\mathrm{R}}\) and T\({}_{\mathrm{Aero}}\). This analysis suggests that \(\Delta\mathrm{T}_{\mathrm{IR}}\) cannot be used to determine H directly, that is, without correcting for the offset. Thus, the offset in part corrects estimates of H for differences between \(\Delta\mathrm{T}_{\mathrm{IR}}\) and \(\Delta\mathrm{T}_{\mathrm{A}}\) and allows Equations (6) and (7) to accurately describe the energy balance of dense canopies. Figure 6: The radiometric (\(\Delta\mathrm{T}_{\mathrm{IR}}\)) and aerodynamic (\(\Delta\mathrm{T}_{\mathrm{A}}\)) temperatures and the offset were measured at (**A**) low and (**B**) high chamber wind speed settings.
# Acute Effects of Static Stretching on Submaximal Force Control of the Ankle
###### Abstract  
Static stretching (SS) is widely used in clinical and sports settings. However, the acute effects on neuromuscular control during dynamic tasks remain unclear. This study aimed to examine the immediate effects of SS on force control using a randomized crossover design. Seventeen healthy young males performed low-range (10-30% of maximal voluntary isometric contraction: MVIC) and high-range (40-60% MVIC) isometric force tracking tasks. In the SS condition, the ankle plantar flexors were stretched for 60 s; in the control condition, the participants remained at rest. The primary outcomes included ankle dorsiflexion range of motion (ROM), musculotendinous stiffness, and the root mean square error (RMSE) of force tracking. Compared to the control group, SS significantly increased dorsiflexion ROM and reduced musculotendinous stiffness. A significant reduction in the RMSE was observed during the force release phase when participants smoothly decreased force output in the high-range task following SS (\(p\) = 0.030, \(d\) = 0.79), but no significant changes were found during the force generation phase in the high-range task or during either phase (generation or release) in the low-range task. These findings suggest that a brief SS intervention may acutely refine the dynamic force control under high neuromuscular demands. Therefore, SS may enhance motor control in tasks that involve submaximal force modulation.  
static stretching; force control; force tracking task Article  
18 May 2025  
Revised: 22 June 2025  
Accepted: 26 June 2025  
Published: 28 June 2025  
**Citation:** [PERSON];[PERSON]; [PERSON]; [PERSON];[PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON] Acute Effects of Static Stretching on Submaximal Force Control of the Ankle. _Appl. Sci._**2025**, 15, 7294  
[[https://doi.org/10.3390/app15137294](https://doi.org/10.3390/app15137294)]([https://doi.org/10.3390/app15137294](https://doi.org/10.3390/app15137294))  
**Copyright:** 62025 by the authors.  
Liconsce MDPI, Basel, Switzerland.  
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license  
[[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)).