esa-sceva/satcom-chunk-collection huggingface dataset:
# Copper Price Prediction Using Support Vector Regression Technique
## 1 Introduction  
Copper is one of the first metal products to be listed on the world's main foreign exchange markets: The London Metal Exchange (LME), Commodity Exchange Market of New York (COMEX) and Shanghai Futures Exchange (SHFE). Copper price is determined by the supply and demand dynamics on the metal exchanges, especially the London Metal Exchange. Although it may be strongly influenced by the currency exchange rate and the investment flow, the factors that can cause fluctuations in volatile prices are partially associated with changes in the activity of the economic cycle [1].  
There are many reasons for wanting to make predictions about the price of copper. On the one hand, copper, among other natural elements (e.g., silver), has a high electrical and thermal conductivity.  
On the other hand, it is cheaper than silver and more resistant to corrosion. Therefore, copper is the preferred metal option for electrical and electronic applications, both domestically and for more general industrial uses. Given the importance of the construction and telecommunications sectors in a modern economy, the changes in copper price can be perceived as an early indicator of global economic performance and have a significant impact factor on the performance of related companies [2].  
With regard to the copper market, any variation in its demand translates entirely into price fluctuations. Market participants see it as an early sign of changes in global production. Thus, it affects mining companies in their investment plans, traders, investors, agents involved in the copper mining business and governments dependent on the copper mining industry. To illustrate this, we can consider the particular case of Chile. As the world's leading copper producer and exporter, Chile produced an estimated 5.6 million metric tons of copper in 2019 [3]. The Chilean government made copper the main point of reference for the country's structural budget rule introduced in 2000, trying to reduce the exposure of fluctuations in Chile's gross domestic product (GDP) to the oscillation of the price of copper [4].  
There are several studies which currently include copper (and other metals) as one of the products of interest in the evaluations of the prediction to improve the forecasts of price, such as [5; 6; 7; 8; 9]. Our study applies a copper price prediction technique using support vector regression (SVR) [10; 11; 12]. This work explores the potential of the SVR with external recurrences to make predictions at 5, 10, 15, 20 and 30 days into the future in the copper closing price at the London Metal Exchange. The best model for each forecast interval is performed using a grid search and balanced cross-validation.  
The paper is distributed as follows: Section 2 presents the related works. Section 3 presents the proposed model. The data used and the methodology are presented in Sections 4 and 5, respectively. Section 6 shows the results and analysis. Section 7 shows the discussion. Finally, Section 8 presents the conclusions.
# Satellite Measured Ionospheric Magnetic Field Variations over Natural Hazards Sites
## 5 Results
### Explosions  
Among several natural and artificial phenomena, not only natural hazards could be responsible for acoustic waves and atmospheric gravity waves. Strong explosions and blasts, i.e., impulsive point sources, have a similar effect like powerful volcanic eruptions with an instantaneous energy release and could, therefore, generate gravity and acoustic waves too. In the recent past the devastating explosion from Beirut, Lebanon, on 4 August 2020, was detected with ionospheric total electron content (TEC) measurements from ground based Global Navigation Satellite System (GNSS) receivers [33].
###### Abstract  
Establishing high-rate secure communications is a potential application of continuous-variable quantum key distribution (CVQKD) but still challenging for the long-distance transmission technology compatible with modern optical communication systems. Here, we propose a photon subtraction-induced plug-and-play scheme for enhancing CVQKD with discrete-modulation (DM), avoiding the traditional loopholes opened by the transmission of local oscillator. A photon subtraction operation is involved in the plug-and-play scheme for detection while resisting the extra untrusted source noise of the DM-CVQKD system. We analyze the relationship between secret key rate, channel losses, and untrusted source noise. The simulation result shows that the photon-subtracted scheme enhances the performance in terms of the maximal transmission distance and make up for the deficiency of the original system effectively. Furthermore, we demonstrate the influence of finite-size effect on the secret key rate which is close to the practical implementation.  
Keywords:plug-and-play; photon subtraction; discrete modulation; continuous-variable; quantum key distribution; quantum communications +
Footnote †: journal: Applied
## 3 Results and Discussion  
### Breakthrough Curves and Particle Retention  
The breakthrough curves (BTCs) of suspended particles in sand columns under different turbidity conditions are shown in Figure 3a-d, with the normalized effluent concentrations (\(C/C_{0}\)) on the \(y\)-axis and time on the \(x\)-axis. After 2.00-10.0 h of water injection, the maximum breakthrough concentrations (\(C/C_{0\rm max}\)) were only 0.233 at 1.84 NTU (Figure 3a), 0.283 at 1.09 NTU (Figure 3b), and 0.334 at 0.540 NTU (Figure 3c). The lower effluent particle concentration indicated that more particles were retained in the porous medium. The BTCs of suspended particles showed that for an influent turbidity of 0.160 NTU, \(C/C_{0}\) remained stable at 0.800-0.950 for 72.0 h (Figure 3d). Furthermore, the \(C/C_{0\rm max}\) decreased with the increasing turbidity of the suspension, which shows that there were improvements in removal efficiency.  
Figure 3: Breakthrough curves (**a–d**) and retained particle ratios (**e–h**) for four sets of experiments. \(C/C_{0}\): normalized effluent concentration.  
After recharge experiments, the particle retention profile per centimeter of porous media showed clear particle deposition that decreased with increasing infiltration depth (Figure 3e-h). Thus, particle retention in the sand column gradually decreased effluent turbidity. Table 1 summarizes the mass recovery in the effluent (\(M_{\text{eff}}\)), the deposition in the column (\(M_{\text{d}}\)), and the injected mass (\(M_{\text{in}}=M_{\text{eff}}+M_{\text{d}}\)) for our experiments. The results showed that retained particles were uniformly distributed in the column under a turbidity of 0.160 NTU. Packing media contributed only slightly to removing suspended particles, with a total retention ratio of 22.5%. Nonuniform retention increased when the turbidity of the injected water increased, and suspended particles were removed mainly in the first layer (0.00-3.00 cm) of the column. When turbidity was 0.540, 1.09, and 1.84 NTU, the retention ratios of the first layer reached 33.8%, 30.3%, and 55.0%, respectively, while the total retention ratios reached 86.2%, 73.2%, and 85.7%, respectively. Thus, suspended particles were retained primarily in the first layer, and deposition decreased with increasing depth. Post experiment clogging at the entrance of the porous medium is shown in Figure S2. The retention of particles influences the clogging of porous media, so it is necessary to discuss the mechanisms underlying the transport and deposition processes of particles.
## 4 Discussion
### Water Management
#### 4.2.4 Transboundary Water Resources Management  
Water conflicts are becoming increasingly serious because of intensifying demands for water resources around the world [60, 61, 62]. Climate change is often seen as a sign of regional conflict in the transboundary river basins fed by snow and glacial meltwater, such as the Indus River Basin, because of the sensitivity of cryospheric water resources [63, 64, 65]. The Altai Mountains are the 'Water Tower' of a wider region, where the populations of four nations that live in the highland- to lowland-areas surrounding the Altai Mountains depend on river, stream, and lake water for economic activities. Two key river systems originate in the SAM: the Irtysh River flows from China to Kazakhstan, and the Ulungur River flows from Mongolia to China. Although these three countries have their interests,visions, and sustainable development and strategic plans, transboundary water resource management remains an outstanding issue of concern [66]. The dual pressures of ecological/environmental protection and increasing water demand for economic development will further elevate the potential for severe water shortages. Increasing uncertainties concerning cryospheric water availability related to the impacts of global warming may exacerbate the risk of regional water conflicts in the SAM.
# Fuzzy Logic in Selection of Maritime Search and Rescue Units
## 4 Case Study
### Case Characteristic  
The simulated SAR operation is the recovery of one person from the water. A man overboard incident may occur on-board any type of vessel, e.g., a passenger or merchant vessel, yacht, fishing vessel, etc. The incident has been reported over the radio to RCC.  
Operations of the search and rescue of a single person in the water require sharp lookout, as the object is small and difficult to be sighted. Vessels with a high superstructure (a high observation altitude) are considered well suited for this type of task. Another important parameter is the vessel's ability to recover the survivor from the water (including its manoeuvrability and equipment). In addition, the following are also important: time required for response, speed, facilities for providing medical assistance (rooms, medical equipment, qualified staff), etc.  
The coordinator therefore has to identify vessels in the vicinity, assess their utility according to his/her preferences and select the most favourable vessels. Assessment of sharp (precise) parameters is possible using MCDA. Fuzzy logic is used to evaluate non-sharp parameters.
## 5 Discussion
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Strategy** & **Pros** & **Cons** & **Best Suited For** \\ \hline \multirow{2}{*}{Information Gain} & Fastest Volumetric & Inefficient Paths & Speed Critical \\  & Coverage & Planning Failures & Environments \\ \hline \multirow{2}{*}{Travel Distance} & \multirow{2}{*}{Most Efficient Paths} & Slower Volumetric & Cluttered \\  & & Coverage & Environments \\ \hline \multirow{2}{*}{Rotation} & Reduce Wrist Joints & Poor Primary & Minor Factor in A \\  & Wear & Driver & Balanced Approach \\ \hline \multirow{3}{*}{Balanced} & Speed/Efficiency & \multirow{3}{*}{Not Best in Any} & \multirow{3}{*}{General Purpose} \\  & Balance & & \\ \cline{1-1}  & Robus Across & Single Metric & Exploration \\ \cline{1-1}  & Scenarios & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Summary of weighting strategy characteristics. While our approach demonstrates a robust framework for workspace exploration, its reliance on fixed fitness function weights and a simple failure-handling mechanism highlights clear directions for future enhancement. As our study shows, the optimal balance between exploration and efficiency can change during the mapping process. This suggests that the most significant future work lies in developing an adaptive weighting scheme. Such a system could dynamically adjust the fitness function, for instance, by prioritizing distance minimization when the map is sparse and then shifting focus to information gain to fill in smaller, remaining gaps as the workspace becomes better known. Furthermore, the current strategy for handling trajectory planning failures could be made more sophisticated. Future improvements could include re-attempting previously failed candidates from new robot poses or incorporating a penalty into the fitness function based on the historical frequency of planning failures for a given region. These advancements would lead to a more intelligent and resilient exploration planner.
# Fatigue Testing of Shear Reinforcement in Prestressed Concrete T-Beams of Bridges
## 5 Discussion  
The main objectives of this research were: to determine the number of load cycles to failure and to compare them with the current design approaches; the announcement of shear fatigue failure; the determination of the relevant strut inclination of the truss model in order to evaluate the stress ranges of the stirrups under cyclic shear load. The shear reinforcement ratio and the load ranges were investigated as main parameters influencing the shear resistance under cyclic loading. The following findings can be drawn from the investigations:  
1. As already shown for I-beams [40; 42; 43], the cyclic loading of prestressed T-Beams led to a successive failure of the stirrup reinforcement with the simultaneous redistribution of shear forces to adjacent stirrups, associated with a clearly visible increase in deformations and crack widths. Due to pronounced crack pattern and increase in deformation, there was a good indication of the following fatigue shear failure. The different shear crack pattern of T-beams (flexural shear crack) compared to beams with I-profile (diagonal shear cracks in the web) did not have a significant influence on the general shear fatigue behavior. With the ongoing damage process, a rearrangement of the truss model into a model with a direct compression strut was observed.
2. As a result of the successive failure of the stirrups, the stress in the adjacent stirrups increased gradually. This concerns stress ranges as well as stresses under upper load.
3. The approach, according to EC 2, for determining the strut angle for fatigue (\(cot\theta_{fat}=\sqrt{\cot\theta}\)) overestimates the actual stress ranges of the stirrups in I- and T-beams measured in the tests, and consequently underestimates the number of cycles until fatigue failure.
4. The improved proposal of \(\theta_{\text{fat}}=\theta_{\text{stat,EC2}}\)[46] was implemented in the first amendment to the guideline for the assessment of existing concrete bridges in Germany [15] with I-shaped cross sections and a shear reinforcement ratio up to 0.35%. This allowed for a verification of the shear fatigue resistance or reduction in the strengthening measures in many cases [17; 48]. Tests on I-beams with higher shear reinforcement ratios and the tests on prestressed T-Beams presented in this paper confirm that \(\theta_{\text{stat}}=\theta_{\text{fat}}\) is also reasonable for members with I- and T-cross sections with a shear reinforcement up to 0.67% [42; 43].
## 2 Materials and Methods
### Data Preparation and Geospatial Layer
#### 2.2.6 Accumulated Subsidence Depth  
The land subsidence in Yunlin County by levelling surveys ranging from 1992 to 2020 was used. The inverse distance weighting tool in ArcGIS was adopted to interpolate the land subsidence data to find the spatial and temporal subsidence characteristics in Yunlin County. According to Figure 2f, the most significant land subsidence area is situated in the Tuku Township and Yuanchang Township. The maximum accumulated subsidence depth reached 180 cm in the past thirty years from 1992 to 2020, as shown in Figure 2f.  
However, the subsidence characteristics are significantly affected by the change in environmental impacts of groundwater in the inland and coastal areas. The characteristics and trends of land subsidence were slowed in the coastal areas, while the subsidence areas are mainly in inland areas in the past 10 years. The significant subsidence area is mainly located in the central area of the Choshui delta.  
Figure 4: The buffer analysis tool in ArcGIS.
# Discrimination of Earthquake-Induced Building Destruction from Space Using a Pretrained CNN Model
## 3 Methodology
### Fine-Tuning with the Pretrained CNN Model  
Figure 3 illustrates the process of fine-tuning a pretrained CNN. The VGGNet model was pretrained with the ImageNet dataset to learn features which were transferable to further training on the target dataset. ImageNet dataset consists of 1.2 million images with over 1000 categories which could be divided into two big groups (animals and objects) and has been applied to several popular architectures, including VGGNet, ResNet, and Inception. The weights and biases were updated by  
Figure 3: Illustration of fine-tuning pretrained Visual Geometry Group (VGG)Net for discriminating collapsed buildings after an earthquake.  
retrained different convolutional blocks using the target dataset, and the output layer was replaced with two neurons which respond to the binary classification of buildings. The comparison between incremental fine-tuning was applied to determine the number of fine-tuning layers with optimal performance. When fine-tuning part of layers, the rest of weights are frozen during training in this network, meaning that they only participate in the forward propagation of the network and will not be updated via backpropagation. The learning rate determines how much weights change at each iteration, and a higher learning rate comes with faster-changing weights. The network was trained with a small learning-rate, since our dataset is small and very different from the ImageNet. The network has been trained via 200 epochs with the learning-rate equal to 0.001, momentum 0.9.
# Dual aptamer-Functionalized 3D Plasmonic Metamolecule for Thrombin Sensing
## 1 Introduction  
Since its introduction in 1990, single-stranded DNA and RNA aptamers have become important targets of diagnostic and clinical studies because of their cost effectiveness, stability, affinity, and small size [1; 2; 3; 4; 5; 6; 7; 8]. Compared to antibodies, aptamers are cheaper, less prone to stimulate unintended immunoresponses [9; 10], readily modifiable, and easily programmable. Therefore, there have been numerous attempts to engineer aptamers to act as sensors that are capable of detecting their target molecules at low concentrations and in biologically relevant settings. For example, conformational changes of aptamers upon binding of target molecules have been detected with techniques like colorimetry [11; 12], fluorescence spectroscopy [13], surface-enhanced Raman scattering (SERS) [14], and surface plasmon resonance [15; 16]. The detection sensitivity observed in these studies ranges from 45 pM to 20 \(\mu\)M. To achieve sensitivity beyond the affinity of an individual aptamer, it is possible to further engineer the binding affinity of the aptamer itself [17; 18] or combine the affinity of multiple aptamers binding to the same target at different locations [19]. To ensure detection of every molecular binding event, the initial signal can be amplified with secondary processes. By using specially designed nanostructures, the detection limit has been pushed towards the single-molecule level. Another method to increase overall sensitivity relies on gaining avidity by using two aptamers that bind to one target molecule but on different epitopes. Connecting two thrombin-binding aptamers with a single-stranded DNA linker increased binding affinity up to 10-fold, when compared to individual aptamers [20]. Here, we used the DNA origami technique [21; 22; 23; 24; 25; 26; 27; 28; 29; 30], which enables us to build dynamicnanostructures with designed shape and modifications and, thus, to implement the two crucial aspects of signal enhancement and increased avidity in one device.
# Hybrid Empirical and Variational Mode Decomposition of Vibratory Signals
## 4 Cases Studies  
To support the theoretical framework and validate the hybrid strategy for signal analysis, four comprehensive case studies are presented. These case studies are used to demonstrate the practical applicability and effectiveness of combining Empirical Mode Decomposition and Variational Mode Decomposition to enhance the estimation of harmonic vibratory components in complex signals.  
The first case study involves a signal composed of six harmonic vibratory components with closely spaced frequencies. Such a signal poses significant challenges for the conventional EMD technique, as mode mixing can lead to inaccurate decompositions. Here, the hybrid method depicted its strength by utilizing EMD to detect mode mixing, which in turn informs the VMD process about the number of harmonic vibratory components. This strategic approach ensures more precise and efficient estimation, overcoming the limitations of both standalone EMD and VMD techniques.  
The second case study focuses on a two-degrees-of-freedom mechanical system. In this scenario, a detailed comparison is conducted between the analytical estimation of harmonic vibratory components and their decomposition using the Hilbert-Huang Transform, the variational method, and the hybrid method of EMD and VMD. This analysis aims to highlight the advantages of the hybrid method in accurately capturing and decomposing the inherent oscillatory behavior of the system, providing deeper insights into its dynamic characteristics.  
The third case study examines a six-degrees-of-freedom mechanical system, where the objective is to extract the natural frequencies using different methods, including EMD, VMD, and the hybrid approach. These estimated frequencies are then compared with the analytically calculated natural frequencies. This comparison highlights the hybrid method's ability to closely match the analytically derived frequencies, showcasing its precision in estimating harmonic vibratory components in complex mechanical systems. The hybrid method proves to be more accurate and computationally efficient than standalone EMD or VMD in this scenario, reinforcing its superiority in complex signal analysis.  
These case studies not only showcase the robustness of the hybrid method of EMD and VMD in handling nonlinearity and nonstationarity but also underscore its superiority in estimating and analyzing harmonic vibratory components compared to traditional Fourier Transform techniques. By applying the mean squared error as a performance index, the case studies further highlight the accuracy and efficiency of the hybrid method. The findings reinforce the utility of the HHT and the hybrid approach in various scientific and practical applications, particularly in interpreting complex signals with significant changes in amplitude and frequency.
## 3 Numerical Modeling Procedure  
### Overview of the Study Site  
The numerical 3D model of this study was built based on the geological and geotechnical information of an underground coal mine case study in China [28]. The mine used the retreat longwall mining method; the target seam was horizontally buried at \(-600\) m depth. Instead of slicing mining, a full-seam mining technique was used to extract the 6 m-thick seam in one retreat. As shown in Figure 2, the target panel was 180 m along its dip and 2000 m along its strike. As illustrated in Figure 3, the roof structure was identified by borehole core loggings. A soft and thin layer of mudstone was located immediately above the coal seam as the immediate roof. The main roof mainly consisted of sandstone and sandy mudstone; no hard-to-cave strong stratum was found from the borehole loggings. The floor was mainly sandy mudstone.  
Rock core samples were collected on site and laboratory tests were conducted to obtain the mechanical properties of the rocks, and coefficients c1-c4 in Equation (1) were obtained accordingly. Then, based on the estimation method described in Section 2.1, the height of the CZ and FZ of this panel were estimated to be 12.7 m and 45.5 m, respectively.  
The double-yield model, an inherent constitutive model of FLAC3D, is capable of simulating material's hardening behaviors with increasing strain in compression, and a widely used approach  
Figure 3: Roof and floor strata information.  
Figure 2: Plan view of the target panel.  
to simulate the mechanical behavior of CZ consolidation [4; 17; 18; 29]. The input properties of the double-yield model were back-analyzed to match the mechanical behavior of Equation (3) by [PERSON] et al. [30].