esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Theoretical Section  
### Mechanical Properties and Fabrication Defects of Laminate Structures  
The bending strength of the laminate determines the thickness required to build a specific component. Figure 1 shows how the flexural strength of GFRP structures vary with Gc based on the results of estimation equations in ISO 12215-5 [6] and the rules of two classification societies--Lloyd's Register (LR) [9] and _Registro Italiano Navale_ (RINA) [10]--in comparison to bending test results (according to ASTM D790) of actual GFRP laminates with 4- to 12-ply woven roving cloth with a weight per unit area of 570 g/m\({}^{2}\)[16]. The bending strength improves as Gc is increased. However, the experimental results are generally larger than the theoretical values owing to the safety margin included in the standards and classification rules. The test results indicate that the bending strength begins to decrease when Gc increases above 50 wt.% [6]. This is because a high Gc increases the probability of defects and resin-poor regions. The measured bending strengths of some samples with a Gc of 30-35 wt.% showed a significant decrease, which is likely because these specimens were taken from a heterogeneous section of laminate. In other words, to ensure the desired physical performance of laminate parts, the actual Gc should correspond to the design value. The fabrication quality is also important; Figure 2a shows the typical lamination defects that appear in fiber-reinforced composites, and Figure 2b shows inner defects in a carbon fiber-reinforced laminate detected by computed tomography (CT).  
Figure 1: Variation in laminate flexural strength with Gc as determined by international rules and material tests.  
Figure 2: Defects in fiber-reinforced plastic laminates: (**a**) Schematic of common lamination defects [18]; (**b**) X-ray CT image of defects in carbon-fiber-reinforced plastic laminate [19].
# ECG Signal Classification Using Interpretable KAN: Towards Predictive Diagnosis of Arrhythmias
## 4 Experimental Results and Analysis
### Experimental Evaluation Metrics  
We use multiple performance metrics (including \(F1\) score, AUC, accuracy (\(Acc\)), precision (\(P\)), and recall (\(R\))) to compare the experimental results. These comparison metrics are consistent with the research of [PERSON] et al. [23]. The basic result of calculating all performance metrics is a two-dimensional confusion matrix, which represents true positives (_TPs_), true negatives (_TN_s), false positives (_FPs_), and false negatives (_FN_s). The calculation formula for each performance metric stands for the following equations:  
\[Acc=\frac{TP+TN}{TP+TN+FP+FN} \tag{10}\]  
\[P=\frac{TP}{TP+FP} \tag{11}\]\[R = \frac{TP}{TP+FN} \tag{12}\] \[F1 = 2\times\frac{P\times R}{P+R} \tag{13}\]  
Among them, _TP_ represents the number of actual positive results, _TN_ is the number of actual negative results, _FP_ is the number of false positive results, and _FN_ is the number of false negative results. In addition to _TPR_ (True Positive Rate) and _FPR_ (False Positive Rate), the AUC (Area Under the Curve) score can also be calculated through the receiver operating characteristic (ROC) curve.
## 2 Experimental Data
In Section 3 the calibration procedure of the conversion models based on the cited experimental data is described. The mean value of the compression strength evaluated on the 28 drilled cores is equal to 25.26 MPa, the standard deviation is 3.4 MPa, thus, the coefficient of variation of the core compressive strength is equal to 0.13. Regarding the RH tests, as has been previously described, the rebound index has been measured on each one of the 28 investigated walls. It has been evaluated that the mean value of the 28 measured rebound indexes is equal to 42.55 and the standard deviation is 1.9, thus, the coefficient of variation of the rebound index is equal to 0.04, showing that the dispersion of the acquired rebound indexes around the mean value is quite low compared to that of the core strength. The coefficient of variation and the standard deviation of the rebound index, which are representative of the repeatability of the test results, exhibit rather low values compared to the usual accepted ones (see [9,20]) and make the author confident about the representativeness of the acquired rebound values. Indeed, if a Gaussian distribution is assumed for the rebound measurements and the adopted values are assumed equal to the average value of the nine readings, the obtained value of the coefficient of variation [9] enables the true measurement to be estimated with an accuracy level lower than 6% and with a 95% confidence level. The high value of the coefficient of variation of core strength highlights the high variability of the measurements. Based on this observation, it is possible to create a database of several possible combinations of the available data, for each of which a different value of the coefficient of variation of concrete strength would be expected. This approach enables the impact of the chosen points on the calibration procedure of the conversion model for the same building to be investigated. It would also shed light on the advantages and limitations of the RH tests with reference to ordinary practical applications, where the number of extracted cores may be highly limited by economic and logistic reasons. The objective is to verify the influence of the properties of the dataset on the calibration procedure also varying the chosen conversion model. Thus, the datasets here are considered to have been obtained by collecting a huge number of combinations of the available data, which have been obtained by varying the number of experimental results that compose the dataset considered in the calibration procedure. It is worth noting that the core strength \(f_{core}\) must be converted in the in-situ concrete strength \(f_{c}\) in order to take into account the influence of the height/diameter ratio of the core. For the present investigations, the ratio is equal to 2, the core diameter is 100 mm and a correction term, which considers the damage due to the drilling procedure, in accordance with [21] and the in-situ concrete strength, is assessed in accordance with the following relationship:  
\[f_{c}=1.06\,f_{core} \tag{1}\]
## 3 Results and Discussion
### PDP Measurements  
Figure 3 shows the polarization curve of the CS in a 3.5 wt% NaCl solution. It can be seen that both the cathode and anode branches move toward the more negative and corrected areas around the blank curve, indicating that PCA-GLU simultaneously affects the anode and cathode poles during the corrosion process [21]. However, the cathodic corrosion potential significantly decreases, indicating that PCA-GLU is a mixed-type corrosion inhibitor but is more inclined toward cathodic corrosion inhibitors.  
Figure 2: FT-IR of glutamic acid (a), citric acid (b), and PCA-GLU (c).  
The corrosion current density and corrosion rate of metals in solution with different concentrations of PCA-GLU were calculated, as shown in Table 1. The corrosion rate is calculated as follows:  
\[\eta=\frac{I_{0}-I}{I_{0}}\times 100\% \tag{1}\]  
where \(I_{0}\) and \(I\) represent the values of the corrosion current density after no addition and the addition of the erosion inhibitor.  
According to Table 1, it can be found that after the addition of PCA-GLU, the corrosive current density shows a significant tendency to decrease, and the rate of corrosion inhibition rises significantly [22]. At the same time, the current platform is found on the polarization curve caused by polymer adsorption on the carbon steel surface, which results in the formation of a corrosion membrane. Based on the similarity of the Tafel diagram, the change in polymer concentration only alters the corrosion potential, indicating that the inhibitory mechanism of PCA-GLU on carbon steel does not change [23]. Table 1 shows that the corrosion inhibition effect increases with the increase in the PC-GLU concentration, reaching its maximum value at 400 mg/L, which indicates that PCA-GLU slows down corrosion through adsorption. When the concentration of PCA-GLU was 500 mg/L, we found that its effect decreases instead of remaining unchanged. This situation may be caused by the formation of \"semimicelles\". When the concentration of the polymer exceeds its critical concentration, the adsorbed molecules are easily desorbed and return to the solution [24; 25; 26].
# AVSS: Airborne Video Surveillance System
## 3 Design of the Proposed System  
The purpose of this section is not only to provide a detailed description of the system design, but to give an instruction to build the system from available parts. Here, our guideline to build a fleet starts with the instructions to build a programmable UAV. Three main components of the system are the UAVs, a server, and the fleet platform. The fleet platform is a software we developed to integrate multiple UAVs for an easier management. The concept of the UAVs and the server is both hardware and software, which will be fully covered in this section. In short, the UAVs act as probesthat collect information of a designated area of interest, the server gathers, processes, and presents the information from UAVs, and the fleet platform provides a network and management. Overview of the proposed system is shown in Figure 1. As shown in the figure, the server and the UAVs establish a network through which the data is delivered. The UAVs create a multi-hop network, which allows an extended range of command delivery from the server to the UAVs, and vice versa. A usual surveillance scenario of our system is as follows. First, the user inputs mission details, including the mission area, the duration, and the number of UAVs to be deployed, into the surveillance server. After that, the surveillance server processes the mission details into smaller missions for each UAV. The mission for each UAV is passed to the fleet platform to perform soundness check of the mission. The fleet platform delivers the mission to the UAVs through the network of the fleet platform. The UAVs are dispatched afterwards, and they perform the mission provided by the server. During the mission, the data from the UAVs is delivered to the server. Fleet platform resolves problems that may occur during flights, which can be both a mechanical failure or an event worth noting: examples are a battery shortage or an video anomaly. The structure of the system is shown in Figure 2. The figure illustrates the connection between the three components of the system and the modules that consist the components.  
Figure 1: A simple component representation of AVSS.  
Figure 2: The structure diagram of AVSS.
# Agreement Technologies for Coordination in Smart Cities
## 2 Background
### Coordination Models
In addition, the benevolence assumption of distributed problem-solving agents needs to be dropped: coordination mechanisms now have to deal with _autonomous_, self-interested behaviour--an aspect that is usually out of the scope of models from the field of distributed computing. Approaching agent design in open systems from a _micro-level_ perspective means designing an intelligent software entity capable of successful autonomous action in potentially hostile (multiagent) environments. In this context, coordination can be defined as \"a way of adapting to the environment\" [12]: adjusting one's decisions and actions to the presence of other agents, assuming that they show some sort of _rationality_. If the scenario is modelled within a quantitative framework, we are still concerned with multi-attribute utility functions, where only some attributes are controlled by a particular agent, but now there are different utility functions for each agent. The most popular way of characterising a problem of these characteristics is through (nonconstant sum) _games_[13]. Coordination from a micro-level perspective boils down to agents applying some sort of \"best response\" strategy, and potentially leads to some notion of (Nash) equilibrium. From a macro-level perspective, coordination is about designing \"rules of the game\" such that, assuming that agents act rationally and comply with these rules, some desired properties or functionalities are instilled. In the field of game theory, this is termed _mechanism design_[13]. In practice, it implies designing potentially complex interaction protocols among the agents, which shape their \"legal\" action alternatives at each point in time, as well as institutions or infrastructures that make agents abide by the rules [9]. From this perspective, instilling coordination in an open multiagent system can be conceived as an act of _governing interaction_ within the system. If the environment is such that agents can credibly commit to mutually binding agreements, coordinating with others comes down to negotiating the terms of such commitments. This is where the link to AT becomes evident. _Norms_ and _organisations_ define and structure the interactions that may take place among agents. The shape of these interactions depends on the particular case, but often they can be conceived as _negotiating_ an agreement for a particular outcome of coordination. In addition, depending on the agents' interests, information and structured _arguments_ can be provided to make agents converge on such an agreement. Norms and trust can be seen as a priori and a posteriori measures, respectively, that make agents comply with the constraints imposed by norms and organisations.
# Climate Warming Dominates Vegetation Productivity in the Hanjiang River Basin, China
## 4 Discussion  
### Seasonal Pattern of Vegetation Productivity in the HJRB  
From 2000 to 2020, the GPP in the HJRB displayed a significant increase, consistent with previous research on NDVI in the same region [39; 40; 41]. The spatial distribution of GPP in the HJRB revealed higher values upstream than downstream, with elevated values in the northern and southern regions compared to the valley. However, the patterns of GPP growth did not follow the same distribution; significant growth areas were concentrated near the valley, the middle reaches close to the Danjiangkou Reservoir, and in the downstream mountainous regions, including certain farmland areas. Located in a subtropical monsoon region with average annual temperatures above 0 \({}^{\circ}\)C, the HJRB experiences pronounced annual temperature fluctuations. Precipitation concentrates between June and September, resulting in distinct seasonal variations. The seasonal trend of GPP primarily depends on climate factors such as temperature, precipitation, PET, and SSD. In contrast to climate factors, GPP reaches its peak in August, while most climate factors peak in July, indicating a lag in the response of GPP to climate factors. Furthermore, a slowdown in the growth trends of GPP is observed in both the upstream and downstream regions of the HJRB in June and from April to June. This slowdown is mainly attributed to winter cultivation practices in the upstream Hanzhong Plain, HJRB Valley, and downstream Jianghan Plain and Nanyang Basin, where winter crops like rice and wheat are harvested. The downstream area, characterized by extensive cropland, exhibits more significant and prolonged slowdown trends compared to the upstream. Despite significant variations in seasonal precipitation within the HJRB, the overall seasonal drought conditions remain relatively stable. As the temporal scale increases, the seasonal variation of the SPEI index in the HJRB becomes more stable, with the average SPEI12 remaining steady around 0 throughout the year. This indicates that despite the evident temperature rise over the past 21 years, the long-term hydrometeorological conditions in the HJRB have remained relatively stable. SPEI1 and SPEI3 are lower in February to May compared to other months, suggesting a lack of spring precipitation that affects vegetation growth.  
Figure 10: Relative contributions of climate factors to vegetation productivity in the HJRB from 2000 to 2020.
# A Comparative Study on the Laser Welding of Ti6 Al4V Alloy Sheets in Flat and Horizontal Positions
## 3 Results
### Mechanical Behavior  
Static tensile tests showed that, irrespective of the welding position used, specimens fractured through the weld metals in welds with the lower heat input (2.5 kW and 20 mm/s), and through the base metals in welds made with higher heat input (2.2 kW and 8 mm/s).  
Figure 8 shows the static tensile properties of the laser welds made using four welding conditions. It can be seen that, when a lower heat input (2.5 kW, 20 mm/s) was employed, comparable tensile strengths and specific elongations were achieved for flat welds and horizontal welds: these welds fractured through the base metals owing to the higher strengths of the weld metals compared to that of the base metal. The yield strengths of the flat welds made with the higher heat input (2.2 kW, 8 mm/s) were similar to those made with the lower heat input. By contrast, the yield strengths of the horizontal welds decreased by about 25 MPa when the higher heat input conditions were used.  
In addition, marked decreases in specific elongation could be seen in both flat and horizontal welds when the higher energy input was used. Such deterioration in ductility was more significant for horizontal welds than for flat welds in these cases.
## 4 Conclusions  
This work introduced a new cryogen-free, high-speed pyroelectric receiver for absorption spectroscopy measurements in the THz range. To demonstrate its performance, absorption spectroscopy measurements were carried out on a reference gas cell with NH\({}_{3}\) using a tunable THz QCL at approximately 4.75 THz as the light source. Absorption spectra were successfully recorded without deforming the shape of absorption features for laser tuning frequencies up to 281 Hz. Measurements at higher tuning frequencies were possible as well, up to 1 kHz without deformations, but a faster optical chopper would be required to be able to quantitatively analyse the detected absorption spectra. A single absorption feature of NH\({}_{3}\) recorded using a tuning frequency of 201 Hz was analysed to determine the pressure inside the cell. The result was in excellent agreement with the pressure obtained with frequency-comb-based Fourier-transform spectroscopy. This demonstrates that the pyroelectric receiver can be reliably used as an alternative to helium-cooled bolometers for absorption spectroscopy measurements in the THz range, with its main advantages being the compactness, relatively low cost, and room-temperature operation.  
Conceptualisation, J.R.W., J.K. and J.-P.H.v.H.; methodology, J.R.W. and J.-P.H.v.H.; validation, J.R.W. and U.M.; formal analysis, J.R.W. and U.M.; investigation, J.R.W. and U.M.; resources, X.L., L.S., M.B., J.K. and J.-P.H.v.H.; data curation, J.R.W.; writing--original draft preparation, J.R.W., M.B., J.K. and J.-P.H.v.H.; writing--review and editing, all authors; visualisation, M.B., J.K. and J.R.W.; supervision, K.-D.W. and J.-P.H.v.H.; project administration, J.-P.H.v.H.; funding acquisition, L.S. and J.-P.H.v.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Leibniz Gemeinschaft (grant no. K54/2017).  
The data presented in this study are available on request from the corresponding author due to privacy.  
The authors would like to thank [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], [PERSON], and especially [PERSON] (all PDI) for their valuable contributions to fabricating the used THz QCL, [PERSON] (INP) for the technical support, and [PERSON] (INP) for performing the frequency-comb-based Fourier-transform spectroscopy measurements.  
Author [PERSON] was employed by the company WiredSense GmbH. Author [PERSON] was employed by the company Laser Components Germany GmbH. The  
Figure 7: Standard deviation of the noise of absorption spectra recorded with the bolometer (at a tuning frequency of 11 Hz) and the pyroelectric receiver (at a tuning frequency of 201 Hz) as a function of the total measurement time.  
remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
# A Combined Method for Preparation of Landslide Susceptibility Map in Izmir (Turkije)
## 3 Materials and Methods
### Statistical Analysis
#### 3.3.2 Analytical Hierarchy Process (AHP)  
The AHP, a multi-criteria decision-making method, involves matrix-based binary comparison of the contribution of various factors, providing a flexible and understandable way to analyze complex problems [106]. AHP is beneficial as it has the ability to handle both qualitative and quantitative criteria [107]. Regardless of data type, use of AHP functions is feasible because the basic input is given by the user. Answers to questions such as \"How important is parameter A compared to parameter B?\" represent expert decisions. The relative importance of the parameters was converted into a nine-point continuous rating scale. It was then entered into the binary comparison matrix (Table 3).  
At the beginning of the analysis, using the importance values in the Table 3, a binary comparison matrix was created between the parameters that cause landslides. However, pairwise comparison is subjective and the quality of results is highly dependent on expert  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Statistics** & **Value** \\ \hline Total number of pixels & 2,908,836 \\ \(-2\)logL0 & 27,433.052 \\ \(-2\)log(likelihood) & 23,025.032 \\ Pseudo-R\({}^{2}\) & 0.1607 \\ Goodness of fit & 207,434.51 \\ Area under the ROC curve & 0.727 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of statistics of the logistic regression model.  
\begin{table}
\begin{tabular}{c l l} \hline \hline
**Importance** & **Definition** & **Explanation** \\ \hline
1 & Equal importance & Contribution to objective is equal \\
3 & Moderate importance & Attribute is slightly favored over another \\
5 & Strong importance & Attribute is strongly favored over another \\
7 & Very strong importance & Attribute is very strongly favored over another \\
9 & Extreme importance & Evidence favoring one attribute is of the \\  & & highest possible order of affirmation \\
2, 4, 6, 8 & Intermediate values & When compromise is needed \\ Reciprocals & Opposites & Used for inverse comparison \\ \hline \hline \end{tabular}
\end{table}
Table 3: Scales for pairwise comparisons [108].  
judgment. The consistency rate is used to control this expert decision. Equation (4) shows how to calculate the consistency ratio [109].  
\[\text{CR}=\text{CI}/\text{RI} \tag{4}\]  
\"RI\" is the average of the consistency index that arises depending on the order of the matrix given by [PERSON] [109]. \"CI\" in Equation (5) is the consistency index.  
\[\text{CI}=(\lambda_{\text{max}}-\text{n})/(\text{n}-1) \tag{5}\]  
Here, \"\(\lambda_{\text{max}}\)\" is the largest or fundamental eigenvalue of the matrix and can be easily calculated from the matrix and \"n\" is the order of the matrix.