esa-sceva/satcom-chunk-collection huggingface dataset:
# Post-Digital Learning for Rural Development: A Case Study of _Open Biotec_ MOOCs in Colombia
## 1 Introduction
Besides, adopting e-learning techniques has always been challenging for these zones because teachers and students need more awareness, a low level of information and communication technology (ICT) literacy, and a lack of ICT infrastructure [51; 52]. The democratization of knowledge through massive open online courses (MOOCs) in biotechnology for the rural sector allows teachers and students to pick and choose between several freely available options. The development of online learning platforms to visualize complex biological concepts is a promising aspect that overcomes geographic barriers and helps to learn anytime, anywhere, without the presence of an instructor [53], which creates conditions for sustainable education. This research aimed to develop a virtual training route in biotechnology oriented to higher education in Antioquia, Colombia, based on the curricular design of virtual learning environments in the same area. The main aim was to consolidate an open and massive educational platform for teaching biotechnology in the Department of Antioquia. The research also aimed to contribute to developing scientific competencies that allowed for mitigating environmental impacts in the communities and increased the coverage of quality programs. This research paper presents an innovative approach to post-digital learning of biotechnology in rural areas of Colombia. The study utilized a socioeconomic diagnosis of a subregion of the department of Antioquia and the creation of MOOCs using the Action Research methodology. The paper contributes to developing sustainable learning communities with participation and collaborative action mediated by virtual tools. The paper highlights the importance of virtual, accessible, and open education in increasing the coverage of quality programs and mitigating environmental impacts in rural communities. One of the hypotheses of this study states that the design of a virtual course in biotechnology and the platform learning experience increase the degree of knowledge of students from rural areas in aspects related to this topic, and one of its main objectives is to stimulate knowledge application in solving socioeconomic and environmental problems in the region.
## 2 Materials and Methods
### System Components
#### 2.2.1 Linear Acoustic Echo Cancellers  
For linear acoustic echo cancellation, an AEC with the NSLMS algorithm was employed. The algorithm operates in the subband domain by transforming the signals with uniform single-sideband filter banks [21]. The filters' tap weights update equation for each subband is given by:  
\[\mathbf{c}(n+1)=\mathbf{c}(n)+\frac{\mathbf{x}_{N}(n)\text{sgn}(e(n))\alpha(n )}{||\mathbf{x}_{N}(n)||^{2}} \tag{2}\]  
where \(\alpha(n)\) is the step size, and \(\text{sgn}(\cdot)\) is the signum function. The performance of NSLMS was compared to that of NLMS, for which the tap weights update equation is given by:  
\[\mathbf{c}(n+1)=\mathbf{c}(n)+\frac{\mathbf{x}_{N}(n)e(n)\alpha(n)}{|| \mathbf{x}_{N}(n)||^{2}}. \tag{3}\]
# Edible Packaging: A Technological Update for the Sustainable Future of the Food Industry
## 3 Results
### Additives in Edible Films
#### 3.6.5 Antioxidants  
Antioxidants are chemical compounds that, when added to edible packaging materials, can delay the start of or slow the rate of oxidation reactions. Examples of antioxidants include tocopherols, butylated hydroxytoluene (BHT), butylated hydroxyanisole (BHA), propyl gallate, tertiary butylhydroquinone, citric acid, tartaric acid, ascorbic acid, ascorbyl palmitate, polyphenols, and carotenoids. [PERSON] et al. [105] studied the antioxidant property of blackberry powder on an arrowroot starch-based edible film. The antioxidant property of blackberry and other plant extracts is related to polyphenol and anthocyanin content, which is maintained when added to the edible film. [PERSON] et al. [106] created a cassava starch-based biodegradable film that encapsulated \(\beta\)-carotene and showed antioxidant properties. Edible packaging materials incorporated with natural antioxidants can inhibit or reduce lipid oxidation in meat products. However, edible packaging materials must be specially designed for meat products due to their specific methods of storage and processing and the increased risk of microbial contamination [7].
## 5 Negative Streamer and Leader Formation in Varying Gas Gap Lengths of CF3I-CO2  
For a 30:70% CF3I-CO2 gas mixture it was possible to record a variety of gas gap lengths between the rod-plane electrodes between 20-50 mm in 10 mm increments. This was not possible for CO2 in the 20 and 30 mm gas gap, likely because the first stage streamer formation is too long and bridges the whole gas gap between electrodes. In a CF3I-CO2 gas mixture, the first stage streamer length is much shorter than in CO2, with a higher critical reduced field strength, meaning that more energy is required for streamers to form. In Figure 10a-d, it can be shown that, under an applied negative lightning impulse voltage, a rod-plane gap insulated with CF3I-CO2 exhibits streamer and stepped leader formation across all 20-50 mm gas gaps at a pressure of 0.15 MPa.  
Figure 10: (a) CF3I-CO2 20 mm 80 kV \(-\)0.15 MPa, (b) CF3I-CO2 30 mm 110 kV \(-\)0.15 MPa, (c) CF3I-CO2 40 mm 119 kV \(-\)0.15 MPa, (d) CF3I-CO2 50 mm 132 kV \(-\)0.15 MPa. Schlieren images taken of no-breakdown events in a rod-plane electrode configuration in a 30:70% CF3I-CO2 gas mixture with a varying gas gap subjected to a negative standard lightning impulse voltage waveform. Top row—uned image with contrast. Bottom row—subtracted image highlighting areas of difference.  
Figure 9: (a) Schlieren image in CF3I-CO2 125 kV 0.1 MPa taken of no-breakdown event in a rod-plane electrode configuration with a 50 mm gas gap subjected to a negative standard lightning impulse voltage waveform. (b) Subtracted image highlighting areas of difference.  
In Figure 10a-d, it can be shown that for streamer formation to occur as the gas gap was increased so too does the applied voltage need to increase from 80 kV for 20 mm to 132 kV for a 50 mm gap. With a constant pressure of 0.15 MPa, it can be shown that as the applied voltage is increased with gap length this leads to an increased length of stepped leader channel which progresses further across the insulation gas. This indicates the distance that an electron avalanche, streamer filament and stepped leader can progress into an electronegative gas mixture is highly dependent on the applied impulse voltage in negative polarity and therefore the electric field strength. In electronegative gases such as CF3I and SF6, it is also true that the steep slope of their effective ionisation coefficients means that once the reduced field exceeds a critical reduced field strength the growth of ionisation in the leader channels is very strong which, in practical terms, means that non-uniform fields or very sharp protrusions may initiate complete breakdown of a gas insulated system.
# Fast Screening Algorithm for Satellites Based on Multi-Constellation System
## 3 Fast Satellite Screening Algorithm Based on Multi-Threshold Optimization  
In order to control the complexity of positioning settlement in multi-system positioning system, it is necessary to optimize for multi-system satellites. Firstly, the faulty stars are eliminated to ensure the positioning accuracy, and the sub-optimal constellations are selected to compress the number of permutation combinations, which ultimately achieves the purpose of maintaining the positioning accuracy while reducing the amount of computation.
# A Spatio-Temporal Encoding Neural Network for Semantic Segmentation of Satellite Image Time Series
###### Abstract  
Remote sensing image semantic segmentation plays a crucial role in various fields, such as environmental monitoring, urban planning, and agricultural land classification. However, most current research primarily focuses on utilizing the spatial and spectral information of single-temporal remote sensing images, neglecting the valuable temporal information present in historical image sequences. In fact, historical images often contain valuable phenological variations in land features, which exhibit diverse patterns and can significantly benefit from semantic segmentation tasks. This paper introduces a semantic segmentation framework for satellite image time series (SITS) based on dilated convolution and a Transformer encoder. The framework includes spatial encoding and temporal encoding. Spatial encoding, utilizing dilated convolutions exclusively, mitigates the loss of spatial accuracy and the need for up-sampling, while allowing for the extraction of rich multi-scale features through a combination of different dilation rates and dense connections. Temporal encoding leverages a Transformer encoder to extract temporal features for each pixel in the image. To better capture the annual periodic patterns of phenological phenomena in land features, position encoding is calculated based on the image's acquisition date within the year. To assess the performance of this framework, comparative and ablation experiments were conducted using the PASTIS dataset. The experiments indicate that this framework achieves highly competitive performance with relatively low optimization parameters, resulting in an improvement of 8 percentage points in the mean Intersection over Union (mIoU).  
semantic segmentation; phenology; spatial encoding; temporal encoding; satellite image time series +
Footnote †: journal: Applied Sciences  
1
Footnote 1: [[https://doi.org/10.3390/appl32312658](https://doi.org/10.3390/appl32312658)]([https://doi.org/10.3390/appl32312658](https://doi.org/10.3390/appl32312658))
## 2 Materials and Methods
### Determination of the weight of fuel necessary to perform the Hohmann transfer
Power consumption in the stable state and the available charging power of solar panels determine the energy balance of the system that is necessary to perform the manoeuvre. **Table 6.** Presentation of the fixed parameters used in the analysis of the of the energy required to tilt the satellite. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Symbol** & **Value** & **Unit** \\ \hline Weight of the satellite without fuel & ms & 4.5 & [kg] \\ Fuel weight & mf & 0.5 & [kg] \\ Weight of the satellite with fuel & msf & 5 & [kg] \\ Satellite size along the \(x\) axis & - & 0.1 & [m] \\ Satellite size along the \(y\) axis & - & 0.2 & [m] \\ Satellite size along the \(x\) axis & - & 0.3 & [m] \\ Moment of inertia & Iz & 0.021 & [kg-m\({}^{2}\)] \\ Slew rate & - & 5 & [\({}^{\circ}\)] \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Presentation of the fixed parameters used in the analysis of the of the energy required to tilt the satellite. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Symbol** & **Value** & **Unit** \\ \hline Initial orbit altitude & h\({}_{\text{p}}\) & 482 & [km] \\ Target orbit altitude & h\({}_{\text{d}}\) & 550 & [km] \\ Radius of the Earth & R\({}_{\text{Z}}\) & 6371 & [km] \\ Acceleration of gravity & g & 8.49 & [g\({}_{\text{g}}^{\text{m}}\)] \\ Gravitational constant & G & \(6.674\times 10^{-11}\) & [\(\frac{m^{2}}{kg_{\text{g}}s}\)] \\ Weight of the Earth & M\({}_{\text{Z}}\) & \(5.972\times 10^{24}\) & [kg] \\ Initial radius of the orbit & r\({}_{\text{p}}\) & 6853 & [km] \\ Target radius of the orbit & r\({}_{\text{d}}\) & 6921 & [km] \\ Velocity on the initial orbit & v\({}_{\text{p}}\) & 7626.45 & [m] \\ Velocity on the target orbit & v\({}_{\text{d}}\) & 7588.89 & [\(\frac{m}{5}\)] \\ Semi-major axis & a & 6887 & [km] \\ Velocity on the transfer orbit in perigee & v\({}_{\text{tp}}\) & 7645.25 & [m] \\ Velocity on the transfer orbit in apogee & v\({}_{\text{ta}}\) & 7570.14 & [\(\frac{m}{5}\)] \\ First increase in velocity & Av\({}_{\text{1}}\) & 18.80 & [m] \\ Second increase in velocity & Av\({}_{\text{2}}\) & 18.76 & [m] \\ Total increase in velocity & Av\({}_{\text{total}}\) & 37.56 & [m] \\ Orbital velocity & v\({}_{\text{o}}\) & 7.8 & [\(\frac{m}{5}\)] \\ Thrust force & F & 1 & [N] \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Presentation of the fixed parameters used in the analysis of the amount of fuel necessary to perform the Hohmann transfer.
# TSCH Multiflow Scheduling with QoS Guarantees:
## 3 Results
### Testbed  
Most of the papers that evaluate scheduling algorithms only work in simulation environments and experimental evaluations are limited. In this work, in order to verify the results obtained in the simulation, the topology of Figure 3 was set up in a real environment, using 10 OpenMote B nodes with the Contiki-NG operating System. In order to obtain a multi-hop network in a reduced space, the transmission power of the nodes was set to \(-15\) dBm, while the other parameters are the same as those used in the simulation. To capture the packets and obtain the throughput statistics, transmitting nodes 8, 9 and 10  
Figure 8: Packet Inter-arrival Time for each Scheduling protocol with multiple data Flows.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **SDN WISE-TSCH** & **AMUS** & **MSF** & **ORCHESTRA** \\ \hline Topology construction & SDN WISE: Beacon and Report & RPL + COAP & RPL & RPL \\ \hline Latency (Delays) & Minimum & Minimum & High & Low \\ \hline Reliability (PDR) & High reliability. & High & Low & High \\ \hline Control Packets & Medium & High & Low & Low \\ \hline Power consumption & Medium & High & Low & Low \\ \hline Multiflow Performance & High & Low & Low & Medium \\ \hline \hline \end{tabular}
\end{table}
Table 3: Summary of results with the different TSCH schedulers.  
and the destination in the Sink are connected to a Raspberry Pi. The result is the topology shown in Figure 9.
# A Comprehensive Review of Multimodal Analysis in Education
## 3 Methodologies in Multimodal Analysis
### Tools and Frameworks
#### 3.4.4 Web and Cloud Technologies  
Web-based and cloud technologies have become increasingly central to the development and deployment of MMLA systems, facilitating scalable data processing, real-time interaction, and integration of diverse services. Cloud APIs, such as GPT-4-turbo and Google Cloud Speech-to-Text, enable intelligent analysis and transcription of multimodal content at scale. Web platforms like CoTrack, MetaDash, and EZ-MMLA provide synchronous data visualisation, dashboard analytics, and multimodal data collection through browser-based interfaces. PyramidApp extends this functionality to support collaborative learning scenarios enriched with behavioural and physiological monitoring. These technologies lower the barriers for implementing multimodal analytics in diverse educational contexts and are summarised in Table 4.  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Tool** & **Purpose** & **Works** \\ \hline AI-enhanced learning assistant (AIELA) & Framework for enhancing adaptive intelligent environments through multimodal feedback mechanisms & [118] \\ Align Before Fuse (ALBEF) & Vision-language model adapted to support alignment and fusion in multimodal educational settings & [91] \\ AmbiLearn & Ambient intelligence-based framework for interpreting learner engagement and performance & [119] \\ ASSURE & Multimodal learning environments to structure content delivery and evaluation & [120] \\ CLM & Conceptual framework for analysing collaborative learning processes using synchronised multimodal data & [40] \\ Dual eye-tracking (DUET) & Methodological framework for disentangling user engagement and task performance in collaborative contexts & [40] \\ FESSA & Sentiment-aware feedback framework based on AI and multimodal sentiment analysis & [99] \\ KNIGHT framework & Personalised learning analytics model using multimodal indicators to adapt feedback and instruction & [107] \\ MaTHiSiS & Multimodal learning framework for adaptive education using robotics and affective computing Conceptual model for collecting and analysing multimodal data via mobile devices in learning scenarios & [116] \\ Mobile Multimodal Learning Analytics (MOLAM) & Theoretical framework for identifying transitions and synchrony across different modalities of learning Ontological model for representing multimodal learning events and relationships among modalities Framework for analysing writing processes in collaborative settings using multimodal evidence & [83] \\ \hline \end{tabular}
\end{table}
Table 3: Conceptual and methodological frameworks in MMLA.
## 2 Materials and Methods
### Image, Statistical, and Data Analyses  
The data obtained from the study underwent a comprehensive analysis to identify potential relationships between variables and gain a deeper understanding of the factors affecting pistachio quality and yield under different irrigation treatments.  
To perform this tasks, QGIS software (version 3.22.X, QGIS developer team 2022) facilitated the processing and visualization of remote sensing data, while the R software (version 4.3.X, R Foundation for Statistical Computing, R Core Team 2019, Vienna, Austria) facilitated image, statistical analysis, and data manipulation. The integration of these software applications and packages enabled the robust and efficient analysis of the complex data collected during the study.  
The analyses involved several R packages, including _raster_ and _rgdal_, which were sourced from the Comprehensive R Archive Network (CRAN). The packages _factoextra_ and _FactoMineR_ were used to extract and visualize the multivariate data analyses (PCA, principal component analysis), which essentially convert a set of potentially correlated variables into a smaller, orthogonal set of \"principal components\". These principal components are calculated in such a way that the first few retain most of the variation present in all the original variables.  
A correlation matrix based on Spearman's correlation was employed to evaluate these relationships using the function _cor()_ and was visualized using the package _corrplot_. In addition, with some of the most correlated variables, linear regressions were carried out in order to examine their relationship with the function _ggplot()_ in depth and were visualized with the packages _ggplot2_ and _ggpmisc_. The abbreviations for each trait used in the figures are described above.
## 4 Discussion
### Clinical Comparative Studies Evaluation  
The lack of clinical study makes it difficult to compare our results to similar studies. Most clinical studies have aimed to compare the Accuracy of digital impressions to con ventional ones: [PERSON] et al. compared the Accuracy between digital and alginate impressions in mixed dentition, showing no clinically relevant differences [39]; [PERSON] et al. found similar values of Trueness and Accuracy to this study [40], concluding that differences were clinically acceptable. [PERSON] et al. found some differences between the 3D model's superimposition, but did not suggest any conclusions about their clinical acceptability [41]. Considering that the first clinical study to evaluate the difference between digital and conventional impressions in implant rehabilitation was conducted in 2018 by [PERSON] et al., who found significant differences between conventional and digital impressions regarding implant positions [10], this is a very novel topic that should be investigated further. A 2020 review of clinical studies considered only six studies, concluding that conventional impression is more accurate than digital but underlining the lack of consensus on the clinically tolerable values of Accuracy for dental impressions [42]. Another clinical study that compared both suggests that the digital impression displayed better the interidental areas in periodonally compromised dentitions; nevertheless, their results were \"clinically not satisfactory\" [43]. Only a similar single pilot study evaluated the measurement of Trueness and Precision in five volunteers, using a Co-Cr alloy appliance fitted on a mandibular dentate arch, showing more precise values of Trueness and Precision than this study and concluding, however, that conventional impression showed significantly better values, in agreement with this study's results [44]. To the best of our knowledge, this is the first study to correlate the digital Trueness and Accuracy values with the outcomes of screwed gypsum checks on implant abutments. Our results suggest a clinical tolerance threshold value of over 100 \(\upmu\)m for Trueness and over 98% for Accuracy.
## 5 Conclusions  
In this paper, we proposed a MUVLS strategy to improve the short-term voltage stability issue through improvement in power system operation technology in a scenario where the AC load supply  
Figure 10: Voltage recovery with MUVLS at severe contingency.  
is expected to increase rapidly. When the stalled motors were tripped from the grid, the voltage entered the delayed recovery condition. The voltage recovery response is a very important dynamic characteristic of load behaviors. A method to improve the system reliability in terms of voltage and reactive power was proposed for increasing AC load penetration. The main contribution of this paper is that the applied scheme controls load shedding to mitigate the DVR caused by the power-consumption characteristics of IM loads. From the simulation results, it was possible to confirm that the power system stability is directly related to the inertial constant \(H\). In addition, a dynamic analysis of IM loads with a voltage recovery characteristic was secured to determine and verify the adequate proportion of such loads in the power system. The dynamic simulation results showed that the proposed scheme was effective under severe fault conditions, and the extensive results fully demonstrated the effectiveness of MUVLS in voltage instability conditions and that it improved short-term voltage stability. The MUVLS strategy to contribute to improving the short-term voltage stability while effectively controlling the IM loads and securing the power systems.  
Future research work will focus on development of a real-time UVLS scheme using the PMU (Phasor Measurement Unit) due to detailed monitoring of DVR events. It is necessary to study real-time measurement equipment that can accurately perform decision-making and reflect the state of severity of the power system. If applying the UVLS method based on PMU, it is possible to take adequate countermeasures in case of serious or unexpected fault within the system. PMU is used for operational preparations and DVR mitigation. In addition, electrical end-use characteristics are changing rapidly, as more loads become electronically connected. Many power electronic loads (DER, EV) have constant power characteristics with respect to voltage magnitudes, which could degrade the power system voltage stability. Therefore, it is also necessary to study their impacts on power system short-term voltage stability.  
[PERSON] conceived and designed the research, performed the system simulations, and wrote the paper; [PERSON] supervised the research and improved the system simulations and made suggestions for this research. This research received no external funding. This research was supported by Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Trade, Industry & Energy (20174030201840). The authors declare no conflicts of interest.