esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### DEMATEL Method  
The decision-making trial and evaluation laboratory (DEMATEL) method was initially developed to solve complex and intertwined problems by the Science and Human Affairs Program of the Battelle Memorial Institute of Geneva. This study used the DEMATEL method for five reasons: (1) it can analyze the impact of relationships between complex factors; (2) it can create an impact relationship map (IRM) that can be used to visualize the relationship between factors, clearly illustrating one's effect on another; (3) the alternatives can be ranked, and these weights can be measured through a six-step derivation process to get the cause-and-effect relationships between elements [28]; (4) factors affected by other factors are assigned a lower priority, whereas factors that affect others are given higher priority [29]; and (5) lastly, a similar methodology was conducted by [PERSON] et al. [30] with notably positive results, wherein they performed a reprioritization of the system failure modes by applying the DEMATEL method to the defects observed in the turbocharged engine. Their experiment covered the disadvantages of the traditional risk priority number (RPN) method for the failure mode and effects analysis (FMEA) defect of the said engine. This DEMATEL method, however, has two primary disadvantages: (1) the factors are only ranked according to the relationship between them, and (2) a relative weight cannot be assigned to each expert evaluation [31].  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Researcher** & **Collaborator** & **Category C1** & **Category C2** & **Category C3** \\  & **(Matched with R1)** & **(Matched with R2)** & **(Non-Matched)** \\ \hline Category R1 & 1.1, 2.1, 4.2, 3.2, 3.3 & 1.4 & - \\ (matched with C1) & (matched) & (non-matched) & \\ \hline Category R2 & - & 2.2, 2.3, 2.4, 3.1, 3.4 & 2.5 \\ (matched with C2) & - & (matched) & (non-matched) \\ \hline Category R3 & & & 1.2, 4.3 \\ (non-matched) & & - & (non-matched) \\ \hline Category R4 & - & 4.4 & 4.1, 1.3 \\ (non-matched) & & (non-matched) & (non-matched) \\ \hline \hline \end{tabular}
\end{table}
Table 4: An example of a reliability table where elements are matched by researchers and collaborators.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Step** & **Procedures** \\ \hline
1 & Create an appropriate category that contains the attributes of the first element \\
2 & Create a new category if the following element is different from the first element \\
3 & Distribute the following elements into similar categories \\
4 & Combine and detach existing categories as needed to create new ones \\
5 & Repeat until all elements are classified \\
6 & Place all unclassifiable elements in the miscellaneous group \\
7 & Repeat classification until the elements in the miscellaneous group account for less than 5\% of the total \\ \hline \hline \end{tabular}
\end{table}
Table 3: The classification procedures of bootstrapping content analysis.
# Enhanced Electrokinetic Remediation for the Removal of Heavy Metals from Contaminated Soils
###### Abstract  
The electrokinetic remediation of an agricultural soil contaminated with heavy metals was studied using organic acids as facilitating agents. The unenhanced electrokinetic treatment using deionized water as processing fluid did not show any significant mobilization and removal of heavy metals due to the low solubilization of metals and precipitation at high pH conditions close to the cathode. EDTA and citric acid 0.1 M were used as facilitating agents to favor the dissolution and transportation of metals. The organic acids were added to the catholyte and penetrated into the soil specimen by electromigration. EDTA formed negatively charged complexes. Citric acid formed neutral metal complexes in the soil pH conditions (pH = 2-4). Citric acid was much more effective in the dissolution and transportation out of the soil specimen of complexed metals. In order to enhance the removal of metals, the concentration of citric acid was increased up to 0.5 M, resulting in the removal of 78.7% of Cd, 78.6% of Co, 72.5% of Cu, 73.3% of Zn, 11.8% of Cr and 9.8% of Pb.  
contaminated soil; metal; citric acid; EDTA; electrokinetic remediation +
Footnote †: journal: Applied Sciences
## 2 Related Work
In terms of formalization, the basic operations of relational algebra can easily be expressed in the form of a conjunctive query; i.e., a rule. Consider the Prolog rule of r1(X,Z) :-r2(X,Y),r3(Y,Z,c) with X,Y,Z variables; c is a constant This rule corresponds with: (1) an equi-join operation between relations r2 and r3 because r2(X,Y) and r3(Y,Z,c) share a common variable (namely, Y); (2) a selection operation (the last attribute of the relation r3 must be equal to the constant c); and (3) a projection operation of the attributes X and Z, if one sees r1 as the relation resulting from the query. Prolog has a strong theoretical basis related to first-order logic, but it also incorporates several very practical features that are needed to write code. It integrates several operations that are not related to first-order logic; for example, it is possible to define input/output operations in rules or queries in order to write or read data streams. This type of operation is executed when it is reached in the execution tree. Data structures such as lists of elements can also be used to facilitate the concrete development of programs. The use of Prolog to aggregate data was briefly discussed in an example presented in [16]. The example given in [16] is short and does not deal with all cases of aggregations. Based on the information provided in [16], the short communication presented in [1] introduces the idea of a more complete query pattern to represent the aggregations of data warehouses and shows applications for geo-referenced data. Datalog can be viewed as an alternative to Prolog for databases [17]. Datalog provides a query language for deductive databases. Prolog proposes a top-down evaluation of the rules (from the head of the rules to their body) whereas Datalog usually implements a bottom-up evaluation (from the body of the rules to their head); the latter method is considered to be more suitable for data batch processing. The Datalog reasoning process  
Figure 1: Evaluation tree #1. Figure 2: Evaluation tree #2.  
can be optimized by methods rewriting the rules at the run-time (see the methods of magic sets in [18]). The Datalog Educational System is an advanced implementation of Datalog that proposes extensions for computing aggregation operations (such as GROUP BY functions) [19; 20]. The contribution of this paper was to show how to natively use the Prolog language to implement in-memory data warehouses. In the present paper, the first idea presented in [1] was extended to illustrate more advanced queries that highlighted the advantages of using Prolog for creating data warehouses. The coupling between data aggregations and advanced Prolog features was shown (recursive integrity constraint checking, a numeric constraint solver, graph-based calculations and data format conversions). In the present paper, SWI-Prolog was used, which was the current reference version for this language [21].
###### Abstract  
Attention-deficit hyperactivity disorder (ADHD) is primarily diagnosed using set criteria and checklists. However, authors have indicated that such criteria and checklists are subjective. In this study, data from the gyroscope and accelerometer in a smart watch were used to analyze the movements of children with ADHD. This study cohort comprised 15 children with ADHD and 15 age- and sex-matched control participants. The children with ADHD and controls wore the watches on their non-writing hands simultaneously in class. The recordings of one patient and one control were tracked for 2 h daily for three consecutive days with desk and seated class activities. We compared the measurements of variance and the zero-crossing rate (ZCR) of the gyroscope and accelerometer between the children with ADHD and controls. All average variance and ZCR values of the three axes (\(x\), \(y\), and \(z\)) in the gyroscope and accelerometer were higher in children with ADHD than in the controls. Significant differences in average variance values on the \(y\)-axis (\(p<0.001\)) and ZCR values on all three axes (\(x\), \(p=0.005\); \(y\), \(p=0.003\); and \(z\), \(p=0.004\)) of the gyroscope were observed. Similarly, significant differences in the average variance values on the three axes (\(x\), \(p=0.001\); \(y\), \(p<0.001\); and \(z\), \(p<0.001\)) and ZCR values on the \(z\)-axis (\(p=0.006\)) of the accelerometer were observed. The proposed method is a promising tool to objectively analyze the movements of children with ADHD at school.  
ADHD; gyroscope; accelerometer; smart watch +
Footnote †: journal: Applied Sciences
# Effect of Temperatures on Polyphenols during Extraction
###### Abstract  
Background: Polyphenols are a set of bioactive compounds commonly found in plants. These compounds are of great interest, as they have shown high antioxidant power and are correlated to many health benefits. Hence, traditional methods of extraction such as solvent extraction, Soxllet extraction and novel extraction technologies such as ultrasound-assisted extraction and subcritical water extraction (SWE) have been investigated for the extraction of polyphenols. Score and Approach Generally, for traditional extractions, the total phenolic content (TPC) is highest at an extraction temperature of 60-80 \({}^{\circ}\)C. For this reason, polyphenols are regularly regarded as heat-labile compounds. However, in many studies that investigated the optimal temperature for subcritical water extraction (SWE), temperatures as high as 100-200 \({}^{\circ}\)C have been reported. These SWE extractions showed extremely high yields and antioxidant capacities at these temperatures. This paper aimed to examine the relevant literature to identify and understand the mechanisms behind this discrepancy. Results: Thermal degradation is the most common explanation for the degradation of polyphenols. This may be the case for specific or sub-groups of phenolic acids. The different extraction temperatures may have also impacted the types of polyphenols extracted. At high extraction temperatures, the formation of new compounds known as Maillard reaction products may also influence the extracted polyphenols. The selection of source material for extraction, i.e., the plant matrix, and the effect of extraction conditions, i.e., oxidation and light exposure, are also discussed. The overestimation of total phenolic content by the Folin-Ciocalteu assay is also discussed. There is also a lack of consensus in TPC's correlation to antioxidant activity.  
polyphenols; antioxidant; bioactive compounds; pressurised liquid extraction; subcritical water extraction; solvent extraction; thermal degradation
# A Deep Learning Approach to Estimate Soil Organic Carbon from Remote Sensing
## 4 Experiments and Results
### Additional Assessment of Extremely Randomized Trees for SOC Estimation  
Having settled on extremely randomized trees (ERTs), we attempted to evaluate if the models based on ERTs can generalize across the globe (i.e., CHLSOC and LUCAS datasets). To do so, each fold in our 10-fold cross-validation procedure was created using 100% of two datasets, as well as 90% of the third dataset. The remaining 10% of the third dataset was used for evaluation. Once again, in Tables 5 and 6, we present results with and without elevation. Additionally, in Figure 6 are represented regression lines for each dataset.  
required to split an internal node (min samples split), and the seed for the random number generator (random state).  
The parameter ranges are defined as follows: n estimators ranged from 100 to 200 in increments of 25; max features ranged from 91 to 130 in increments of 10; min samples leaf ranged from 1 to 9 in increments of 2; min samples split ranged from 2 to 8 in increments of 2; the random state ranged from 0 to 4 in increments of 2.  
After the grid search, the optimal combination of the hyper-parameters for the extremely randomized trees model was identified as follows: \"n estimators\" set to 100, \"max features\" set to 121, \"min samples leaf\" set to 1, \"min samples split\" set to 2, and \"random state\" set to 4.  
Once the map was generated, we used the CORINE dataset to create a validity mask for our SOC map.
## 4 Results and Discussion
### Mechanical Performance
#### 4.4.3 Fracture Observations  
Visual inspection of fractured tensile bars revealed distinct failure modes. SLA samples exhibited brittle failure with clean cracks and minimal plastic deformation. In contrast, FDM ABS showed significant necking and ductile failure, while PLA exhibited limited necking. These observations align with the measured mechanical properties and provide additional insights into material behavior under stress.  
Figure 3: Strain curves for FDM (PLA, ABS) and SLA resin. SLA exhibits brittle fracture at 4.4% strain, PLA shows moderate plasticity, and ABS demonstrates extended ductility up to 8.7% strain.
# User-Information-Aware D2D Multicast File Distribution Mechanism
###### Abstract  
There are a large number of redundant transmissions in current D2D multicast content delivery systems, which seriously reduces the utilization efficiency of resources. This paper designs a novel user-information-aware D2D video distribution mechanism. More specifically, by predicting users' video requests, the video can be pushed to potential service requesters while distributing video for service requesters. Firstly, the willingness of potential requesters to accept the pushed video is estimated based on the users' interests, the popularity of the videos and the residual-energy of the users' devices, and the user-demand-aware clustering algorithm is proposed. Secondly, considering social and interference information, the utility metric of D2D multicast is proposed to measure the value of content distribution service. Finally, this paper proposes a D2D video distribution mechanism to optimize the utility value. Simulation results show that the proposed mechanism significantly improves throughput, energy and spectrum efficiency compared to the traditional distribution mechanism.  
D2D; multicast communication; content distribution; user information aware; social aware +
Footnote †: journal:  
_Article_  
User-Information-Aware D2D Multicast File Distribution Mechanism
## 3 Application for Failure-Recall Data with DCLNN Method
### Function of DTW  
The use of DTW to warping time series can improve the prediction accuracy and reduce the mean square error. If the prediction effect of two time series is poor when using the neural network for the first time, the result is not obviously improved after using DTW. However, the result will have a significant improvement after DTW preprocessing if one of the time series is relatively good for prediction. Table 5 concludes all RMSE values when using different time series as referenced data for DTW pre-processing and warping data for prediction using DCLNN.  
Figure 18a is obtained from each column in Table 5. It is clear to see that the MSE is smallest when choosing the third escalator as the reference time series in DTW preprocessing. Figure 18b shows the RMSE improvement of DCLNN prediction after using different escalator data as the reference time series in DTW pre-processing. Similarly, the RMSE improvement of the third escalator is best compared to others. Meanwhile, the result in Figure 18b shows that almost all MSE of the data sequences with different data sequences as referenced can be improved after DTW preprocessing. However, for the third escalator, the RMSE variation is negative. The main reason is that the data quality of the third escalator is best according to the CSI indicator. After DTW is preprocessed with other data as referenced data, the data quality is not as excellent as the third data itself. Therefore, for data with high quality, it is not recommended to use DTW for data preprocessing, otherwise it will reduce the data quality and increase the prediction error.  
Figure 17: Result comparison. (**a**) Comparison of different methods. (**b**) Comparison of RMSE with different methods.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **\# 1** & **\# 2** & **\# 3** & **\# 4** & **\# 5** & **\# 6** \\ \hline RMSE & 384.87 & 112.78 & 3.9 & 397.12 & 25.3 & 53.18 \\
**\#1 referenced** & 384.87 & 18.43 & 6.81 & 442.35 & 25.91 & 52.26 \\
**\#2 referenced** & 225.41 & 112.78 & 6.85 & 125.17 & 12.40 & 52.48 \\
**\#3 referenced** & 25.12 & 16.81 & 3.9 & 30.37 & 9.3 & 7.66 \\
**\#4 referenced** & 117.56 & 32.26 & 10.65 & 397.12 & 11.23 & 43.24 \\
**\#5 referenced** & 48.43 & 13.78 & 5.86 & 241.17 & 25.3 & 47.77 \\
**\#6 referenced** & 119.11 & 117.85 & 2.95 & 61.46 & 25.44 & 53.18 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Statistics of RMSE.
# Precise Orbit Determination for GNSS Maneuvering Satellite with the Constraint of a Predicted Clock
## 1 Introduction
These approaches are rather effective to handle maneuvers of satellites in the low Earth orbit (LEO) because of their quick movement and good geometry conditions. [PERSON] et al. showed that the piecewise constant acceleration model contributes to centimeter-level orbit accuracy for the maneuvering LEO satellites [14]. [PERSON] et al. and [PERSON] et al. analyzed the performance of different thrust models applied for the maneuvering of BDS GEO satellites and showed that the instantaneous velocity change model results in the best precision of 2-5 m [16; 17]. The kinematic POD is an alternative method that is not affected by satellite maneuvers since only observations are employed in this method without any force models. [PERSON] et al. compared the kinematic and dynamic POD solutions, identified the maneuver thrust force model of BDS satellites and showed that the root mean square (RMS) of the kinematic POD solution with respect to the precise orbit products is less than 0.1 m in the along-track and cross-track directions and larger than 1.0 m in the radial direction [9]. The bad geometry conditions and large position dilution of precision (PDOP)in the radial direction cause the large orbit error in this direction. [PERSON] et al. proposed a reverse point positioning (RPP) method using single-frequency code observations to determine the BDS GEO orbits during maneuvers [18]. The orbit accuracy of this method is about 0.92 m, 2.74 m and 8.30 m in the radial, along-track and cross-track directions, respectively, which is a little worse than that of broadcast ephemeris. Considering the strong correlation between clock offsets and the radial component of satellite position, [PERSON] et al. corrected the satellite clock offsets using the measurements of satellite station two-way synchronization (SSTS), bringing improvement to the POD and orbital recovery for the maneuvering BDS satellites. However, the SSTS measurements are not released to the public [19]. Considering that GNSS satellites are generally equipped with atomic clocks that are usually not affected by orbit maneuvers and have high stability and accuracy for short-term prediction [20], we propose a kinematic POD method, the clock-constrained reverse precise point positioning (RPPP), to improve the orbit solutions during maneuvering periods. By constraining the clock offsets with the prediction model, the performance of RPPP during maneuvers can be further improved. This contribution starts with a brief review of maneuver handling in GNSS POD. Next, the clock prediction model and basic mathematics about clock constraining are introduced, based on which the processing scheme of the proposed method is demonstrated. Then, the proposed method is tested on different data sets and the experiment results are analyzed and compared to evaluate the performance of this method. Finally, a summary and conclusions are presented.
# _CoVSCode_: A Novel Real-Time Collaborative Programming Environment for Lightweight IDE
## 5 Major Technical Issues and Solutions
### Smooth Transition in Real-Time Collaboration Sessions  
As specified in _Design Objective_\(C\), the system should support unconstrained and flexible real-time collaboration where programmers can join and leave a real-time collaboration session at any time. When an ongoing session accepts a new member, the server should deliver the latest source code to the member, and meanwhile, ensure the smooth transition of the session. After the new member joins, all session members should continue their work based on a consistent copy of the source code. To achieve the smooth transition in a reliable way, the following mechanism is deployed:  
* When a client requests to join an ongoing real-time collaboration session, the client sends a _REQUEST_ message to the server.
* When the _REQUEST_ message arrives, the server broadcasts an _INIT_ message to all existing clients in the session.
* Upon receiving an _INIT_ message from the server, the client temporarily prevents new local editing operations, and sends back an _OK_ message to the server.
* After receiving _OK_ messages from all existing clients, the server further broadcasts a _COMPLETE_ message to all clients, which signifies the completion of the procedure.
* When the _COMPLETE_ message arrives, a client resumes editing work immediately. Particularly, for the incoming client, the latest source code copy will be transmitted from the server to the client, following the _COMPLETE_ message.  
A graphical example is presented in Figure 5, which illustrates how the above mechanism works when a programmer (_D_) joins a session with three existing programmers (_A_, \(B\) and _C_).  
Figure 5: A graphical example illustrating the transition when a member joins the session.  
In a real-time collaboration session, each client-server communication is based on a WebSocket connection, which is essentially a FIFO communication channel. When all clients in the session have received the _COMPLETE_ messages, the entire session reaches a temporary state where (i) there is no message being transmitted, and (ii) all clients have executed the same editing operations, holding consistent source code copies. Eventually, the incoming client receives the latest source code, and all clients continue programming work based on a consistent source code copy as if a fresh session has been started. In addition, when a client leaves a session, the mechanism is relatively simple--the client simply sends a leaving request to the server, and the server removes the client from the member list. For both joining and leaving, notification messages will be sent to all existing clients.