esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Dissolved Trace Elements
#### 3.2.5 Uranium  
The mean dissolved U concentrations (Figure 3) at site 1 were significantly higher than at all other sampling sites. The mean concentration there was 18.1 \(\pm\) 15.1 \(\upmu\)g/L, which was lower than pre-treatment measurements with concentrations ranging between 36 and 232 \(\upmu\)g/L [19; 20]. In January 2019, the activity concentrations of \({}^{238}\)U and \({}^{234}\)U were additionally measured and were 77.5 \(\pm\) 4.2 and 87.5 \(\pm\) 4.5 mBq/L, respectively, corresponding to a uranium mass concentration of 6.3 \(\pm\) 0.3 \(\upmu\)g/L. The \({}^{234}\)U/\({}^{238}\)U activity ratio was 1.13 \(\pm\) 0.08, a value typical for dissolved natural uranium. In all other sampling sites, the mean concentrations of dissolved U did not exceed 1 \(\upmu\)g/L. In the oxidized condition as present in the MIW, U occurs as readily soluble and mobile UO\({}_{2}\)\({}^{2+}\), forming complexes in the prevalent neutral conditions [43; 44].  
The lower mean concentrations in the following sampling sites can be explained by the sorption of U(VI) on Fe-oxide minerals as well as organic materials, thereby reducing environmental transportation [45]. The SA-WQG for aquatic life does not include this element, and international guidelines for concentrations of U in freshwater systems for the protection of aquatic life are scarce. Water quality guidelines for the protection of aquatic life in Canada include U and introduce a maximum short-term concentration of 33 \(\upmu\)g/L and a long-term concentration of 15 \(\upmu\)g/L. Although the international comparison is difficult because the toxicity of metals depends on many factors such as climate, geological soil composition, and water composition, the highest concentration measured (66 \(\upmu\)g/L) clearly  
Figure 3: Mean \(\pm\) SD uranium content in sediments and dissolved U concentrations in water of sampling sites along the course of mining-influenced water.  
surpassed all limits and the mean concentration also exceeded the long-term concentration limit of 15 \(\mathrm{\SIUnitSymbolMicro\text{$\text{$\text{$\text{$\text{$\text{$\text{$ \text{$\text{$\text{$\text{$\text{$\text{$\text{$\text{$\text{$}}}$}$}$}}$}}}}}}}\)/L. Therefore, dissolved U levels at site 1 must be considered toxic for aquatic organisms.
# Degree-Constrained Minimum Spanning Hierarchies in Graphs
## 2 Notations and Definitions
#### Hierarchies  
The generalization of trees is based on graph homomorphism. The homomorphic mapping of nodes between a tree \(T\) and a graph \(G\) can be used to define an eventually non-elementary tree in \(G\). To simplify, let us suppose undirected graphs but the definition in digraphs is trivial.  
**Definition 1** (Hierarchy).: _Let \(G=(V,E)\) be an arbitrary graph and let \(T=(P,F)\) be a tree. Let \(h:P\to V\) be a homomorphic function that associates a node \(v\in V\) to each node \(p\in P\). The application \((T,h,G)\) defines a hierarchy in \(G\)._  
**Definition 2** (Image of a hierarchy).: _The sub-graph defined by the set of nodes and edges in \(G\) associated by \(h\) to \(T\) is the image of the hierarchy._  
Since a node \(v\in V\) can be associated with several nodes in \(P\), a hierarchy can contain multiple occurrences of a node and an edge. A hierarchy can be considered as a \"non-elementary tree\" in \(G\). Certain nodes in the hierarchy can eventually be branching nodes; they are the node occurrences corresponding to the branching nodes of the tree \(T\). Figure 1 illustrates with discontinuous lines a hierarchy in a graph and the associated tree. The  
\begin{table}
\begin{tabular}{l l} \(G=(V,E)\) & : undirected graph given by node set \(V\) and edge set \(E\) \\ \(\{n,m\}\in E\) & : edge between nodes \(n\) and \(m\) \\ \(c(n,m)\) & : cost associated with the edge \(\{n,m\}\) \\ \(d(v)\) & : degree of the node \(v\in V\) in \(G\) \\ \(D(v)\) & : degree bound of \(v\in V\) (positive integer) \\ \(M\) & : the highest degree bound in \(V\) \\ \(V_{m}\subseteq V\) & : the subset of nodes with degree bound \(m\) \\ \(T=(P,F)\) & : tree with node set \(P\) and edge set \(F\) \\ \(H=(T,h,G)\) & : hierarchy defined by a homomorphic function \(h\) \\  & between tree \(T\) and graph \(G\) \\ \(\Theta(v)\) & : the set of nodes in \(P\) (in \(T\)) corresponding to \(v\in V\) \\ \(v^{i}\) & : i-th occurrence of \(v\in V\) in a hierarchy (in \(\Theta(v)\)) \\ \(G_{A}=(V,A)\) & : directed graph, equivalent to \(G\), two arcs \((a,b)\in A\) and \\  & \((b,a)\in A\) correspond to the edge \(\{a,b\}\in E\) of \(G\) \\ \(\Gamma^{-}(a)\) & : the set of predecessor nodes at the node \(a\) in \(G_{A}\) \\ \(\Gamma^{+}(a)\) & : the set of successor nodes at the node \(a\) in \(G_{A}\) \\ \end{tabular}
\end{table}
Table 1: Notations.  
labels of the nodes in \(T\) are the labels of the corresponding nodes in \(G\). Dotted lines with arrows indicate the associations between these nodes. Some nodes of \(G\) (namely the nodes \(c\) and \(d\)) participate on different levels of the hierarchy as shown in the labeled tree \(T\).  
Hierarchies generalize trees. Trees are special hierarchies without repetition of nodes (when the mapping \(h\) is injective), and therefore, inherit the properties of hierarchies. Note that the image of a hierarchy can contain cycles in \(G\) but the hierarchy itself preserves the structure of a tree. Hierarchies allow the exact definition of the optimum in the case of capacity-like constraints.
## 4 Experiment
### Real Signal Experiment  
#### 4.3.1 Experimental Data  
Following the network parameter setting guidelines specified in Section 4.2.1, in the real bearing vibration signal, the reconstruction performance of the ISTA-Net network proposed in literature [48] and the ADMM + K-SVD-based CS method in literature [35] are compared with the ADMM-1 DNet network algorithm proposed in this paper. To ensure the fairness of the algorithm reconstruction experiment, the parameters of the CS method based on ADMM + K-SVD are also optimized by the embedded program. The whole reconstruction process is described in Section 2.3.  
Two authoritative bearing experimental data sets are used in the experiment: the bearing experimental data set (CWRU) [64], published by CASE Western Reserve University, and the bearing experimental data set (XJTU-SY) [65], published by Xi'an Jiaotong University. Figure 8 shows the test rigs and the bearings used for the two datasets. The CWRU vibration data was collected using accelerometers, which were attached to the housing with magnetic bases. Accelerometers were placed at the 12 o'clock position at both the drive end and fan end of the motor housing. Four types of bearing data at the drive end were selected as sample signals in the dataset with a signal frequency of 12 kHz, a motor load of 1 HP, and a fault diameter of 0.007\({}^{\prime\prime}\). In the XJTU-SY, two accelerometers of type PCB 352C33 are positioned at 90\({}^{\circ}\) on the housing of the tested bearings, i.e., one is mounted on the horizontal axis and the other is mounted on the vertical axis. In the dataset, the horizontal outer ring fault signal is selected as the sampling signal at 40 Hz, the signal sampling frequency is 25.6 kHz, and a total of 32,768 data points are recorded in each sampling, i.e., 1.28 s, with a sampling period of 1 min. In order to fully simulate the outdoor working environment of mechanical equipment, Gaussian white noise with an SNR of 30 dB is added to all signals.  
Considering the limited number of equipment fault signal acquisitions, we expand the data set by sliding window sampling and take 1024 sampling points as a signal sample unit. Then, the training set and the test set for each signal are set to be 1200 and 240 sample units, respectively. The dataset name and fault type are shown in Table 2. Normal represents the normal state; BA, OR, and IR, respectively, represent the ball, outer ring, and inner ring  
Figure 7: Algorithm \(L_{S}\) Settings and Reconstruction \(T_{\text{test}}\) Relationship.  
faults; and the number after # represents the orientation of the fault point. MIX includes four kinds of mixed faults: inner ring, outer ring, rolling element, and cage.
# A General Calibration Method for Dual-PTZ Cameras Based on Feedback Parameters
###### Abstract  
With the increasing application of dual-PTZ (Pan-Tilt-Zoom) cameras in intelligent unmanned systems, research regarding their calibration methods is becoming more and more important. The intrinsic and extrinsic parameters of dual-PTZ cameras continuously change during rotation and zoom, resulting in difficulties in obtaining precise calibration. Here, we propose a general calibration method for dual-PTZ cameras with variable focal length and posture under the following conditions: the optical center of the camera does not coincide with the horizontal and pitch rotation axes, and the horizontal and pitch rotation axes are not perpendicular to each other. We establish a relationship between the intrinsic and extrinsic parameters and the feedback parameters (pan, tilt, zoom value) of dual-PTZ cameras by fitting and calculating previous calibration results acquired at specific angles and zoom values using [PERSON]'s calibration method. Subsequently, we derive the intrinsic and extrinsic parameter calculation formula at arbitrary focal length and posture based on the camera's feedback parameters. The experimental results show that intrinsic and extrinsic parameters computed using the proposed method can better meet precision requirements compared with the ground truth calibrated using [PERSON]'s method. The average focal length error is less than 4%, the cosine similarity of the rotation matrix between the left and right cameras is more than 99.8%, the translation vector error is less than 1%, and the recalculated Euler angle errors are less than 1 degree. Our work can quickly and accurately obtain intrinsic and extrinsic parameters during the use of the dual-PTZ camera.  
Keywords:dual-PTZ cameras; calibration method; feedback parameters; variable focal length and posture +
Footnote †: journal:
## 7 Discussion
It might be interesting to evaluate what would be the effect of applying federated machine learning techniques to make routing more efficient as the models can be updated locally. This does not solve the issue of storage. From our perspective, high mobility and energy constraints create intermittent mobility, which is part of the features for which DTN is designed; therefore, performance evaluation should focus on storage and computing capabilities. This last aspect, as stated in the previous section, depends on how light the designs and implementations are made. Finally, we did find several works on different applications to support agriculture, natural disasters, smart cities, and communication in rural areas. Some of them are over TCP. Nonetheless, most of the experiments did not dig deep into the transport layer itself but rather in the overall functioning and performance of the applications. The projects that describe applications of DTN to support services, such as email, web caching, texting, and voice mail stated its feasibility. The positive side is the low cost of creating the infrastructure, which is a crucial element when it comes to providing Internet access to rural communities, especially of low income. In this sense, most of the experimental settings were performed in these kinds of scenarios. The negative side is the low throughput, not higher than 2.5 Mbps, which might be too low for a good user experience nowadays, even for asynchronous services. On top of this is the fact that the availability of the service for one depends on the cooperation and proper functioning of all the nodes in network. The presence of greedy nodes can affect the overall performance of the network. Applications of DTN for environmental monitoring using massive sensors either applied to vegetation, climate, or fauna demonstrated its potential. In this case, the lower requirements in terms of data to be transferred and the energy consumption of sensors help to overcome some of the limitations of nodes, such as storage. Solutions for the lack of storage include implementations, like throwboxes [29] or the manual replacement of storage cards. This last one might be feasible if the size of the coverage area is manageable and if the necessary logistic is coordinated with the stakeholders. In cases of natural disaster, applications are somehow similar in terms of technical implementations, and so, it looks like a good fit for DTN, especially taking into consideration broken or a lack of infrastructure. In any of these cases, the best way to ensure that the communication is fully available requires a backbone of DTN nodes. This scenario raises the potential of using DTN combined with MANET, so that the first one takes over whenever the route to the destination is not available. As mentioned in the previous section, the use of this technology in combination with other technologies in city areas where telecommunication infrastructure is not an issue does require a standard and user-friendly framework so that it can pass from the experimental phase to market adoption.
## 3 Methodology
### IQR  
The Interquartile Range, commonly abbreviated as IQR, is a robust measure of statistical dispersion or spread in a dataset. It specifically describes the range within which the central 50% of values lie when the data are ordered from the lowest to the highest value. By focusing on the middle 50%, the IQR effectively eliminates the influence of extreme values or outliers, making it a particularly valuable metric in datasets that may contain such anomalies.  
Mathematically, the IQR is the difference between the third quartile (Quantile75) and the first quartile (Quantile25). It can be represented by the formula  
\[\text{IQR}=\text{Quantile75}-\text{Quantile25} \tag{19}\]  
Given that Quantile75 represents the value below which 75% of the data fall, and Quantile25 represents the value below which 25% of the data fall, their difference (IQR) encapsulates the range of the middle 50% of the data. This range is particularly significant in statistical analyses as it provides insights into the variability and spread of the central portion of the dataset, excluding potential outliers.  
In many statistical applications, the IQR is used in conjunction with other metrics, such as the median, to provide a comprehensive understanding of the data distribution. Moreover, the IQR is frequently employed to identify outliers. Observations that fall below Quantile25 \(-\) 1.5 \(\times\) IQR or above Quantile75 \(+\) 1.5 \(\times\) IQR are typically considered outliers, as they lie outside the range expected for the central bulk of the data.
# Lagrangian Modeling of Marine Microplastics Fate and Transport: The State of the Science
## 3 Physical Properties and Processes  
### Physical Properties  
The behavior and transport of microplastics mainly depend on major physical properties including the size, density, and shape [44; 66; 96; 99] of the particles. Microplastics are identified in varied sizes and shapes, and denser particles normally settle faster even with similar shapes and sizes [44]. Moreover, larger particles in terms of size but with the same density experience an increase in the ratio of the gravitational force applied on the particle to the fluid viscous resistance, which results in higher settling velocities and faster settling [61]. In addition, the shape of microplastics can affect their movements and settling velocity as well [100]. It has been observed that elongated particles such as films and fibers, known as larger particles, settle faster than smaller, circular particles [96]. Microplastics come in various regular (e.g., spherules, cylinders, and beads) and irregular shapes with different geometries (pellets and fibers). Regular shapes usually belong to primary microplastics while irregular shapes often can be seen among the secondary particles as a result of degradation [99]. Moreover, the physical properties of microplastics undergo changes due to the impacts of different processes and ambient factors such as algae invasion [101], salinity [102], UV index [103], temperature [103], and Stokes drift generated by wave action [104]. For instance, unlike freshly emitted particles, the edges of microplastics become smooth during aging as a result of mechanical degradation since they are under polishing imposed by other fragments [105]. Different equations used in the reviewed models for modeling hydrodynamic aspects (including microplastics' physical properties) pertinent to the transport of microplastics have been summarized in this study in Table 2.  
Figure 1: The structure of Lagrangian particle-tracking models in the simulation of microplastics’ physical properties, physical transformation processes, physical transport processes, and numerical methods.
# Chaotic Time Series Forecasting Approaches Using Machine Learning Techniques: A Review
## 4 Forecasting of Chaotic Time Series in Various Applications
### Oil and Gas  
The global prediction method uses a BPNN model for forecasting the gas emission rate in the Hegang Nanshan mine located in China [83]. The proposed model showed better step, accuracy, and stability predictions. The improved Duffing oscillator chaotic traffic prediction model in [85] was developed for coal gas' traffic flow prediction for a coal mine. The proposed approach can also increase signal detection accuracy. The chaos RBFNN method in [12] predicts the intake airflow of the gasoline engine. The coal mine ventilation systems' management technology reported in [17] can predict the gas concentration in Jining, Shandong, China. As a result, the system can provide reliable assurance for mine safety production.
# A Survey of Precision Formation Relative State Measurement Technology for Distributed Spacecraft
## 2 Research Status of the Precision Formation of Distributed Spacecraft Project  
### TechSat-21  
TechSat-21 (Technology Satellite of the 21 st Century) [3] is a program that was developed by the US Air Force Research Laboratory in 1998 to validate synthetic radar technology. The project consists of an 8-16 formation of small satellites to form a large virtual satellite; the satellites are distributed in a polar orbit of 800 km. The virtual satellite uses electromagnetic wave interference to complete relative state measurements and meet the requirements of rapid mission-formation shape transformation. The GPS relative measurement payload weighs 4 kg, with a power consumption of about 50 W. Figure 1 shows the schematic diagram of the virtual satellite's sparse aperture, which is a distributed SAR system with multiple transmissions and multiple receivers that is mainly used for ground motion indication and ground elevation measurement. The relative position accuracy is required to be 1-10 cm in order to maintain the formation's large and effective radar aperture [4].  
The project achieved remarkable results in the early stages. Due to the level of technology, as well as cost constraints, the project was forced to end in 2003, but it has demonstrated a new breakthrough in spacecraft formation flight technology.
# Compact Quad-Port MIMO Antenna with Ultra-Wideband and High Isolation
## 2 Design of UWB Antenna Unit
### Design Procedure
At this time, the three main parameters affecting the minimum resonant frequency of the antenna (patch length, patch width, patch and ground clearance) are not changed, so the minimum resonant frequency in the working band only has a slight frequency deviation, but the bandwidth has been expanded to a certain extent, the absolute bandwidth is 2.97 GHz (3.21-6.18 GHz), and the relative bandwidth is 63.26%. The second step is to change the signal line to a stepped feed structure, as shown in Figure 3c, the reduction in the feed gap increases the minimum resonant frequency of the antenna from 3.21 GHz to 3.69 GHz, and also extends the surface current path of the radiating patch, so that the current can flow smoothly in a larger area, which improves the bandwidth characteristics and increases the upper resonant frequency to 14.27 GHz, the absolute bandwidth is 10.58 GHz, the impedance bandwidth reaches 117.82%, and there are two resonant frequencies: 6.08 GHz and 7.74 GHz. In order to further expand the bandwidth of the antenna, the third step will be two pieces of ground extended to connect together, forming the effect of the surrounding ground, as shown in Figure 3d. At this time the antenna can be approximated as a rectangular slit antenna. The reflection coefficient curve in Figure 4 shows that the antenna works in the range of 1.86-15.49 GHz, which covers the UWB communication band specified by FCC, and there are four resonance points: 2.5 GHz, 7.16 GHz, 9.31 GHz, and 14.32 GHz. The absolute bandwidth of 13.63 GHz and the relative bandwidth of 157.12% is achieved, which is 1.3 times the step CPW-fed antenna (Second Step), 4.6 times the conventional CPW-fed antenna (First Step) and 9.7 times the conventional microstrip wire-fed antenna (Ref. Antenna). The next step is to embed the \"T\" shaped metamaterial [22] into the radiating patch, as shown in Figure 3e, which is to optimize the impedance matching and increase the upper resonant frequency of the operating band. In Figure 4, it can be seen that the upper resonant frequency of the operating band is effectively widened to 15.69 GHz, which is 1.8 GHz higher than that in the third step, and there are four resonance points: 2.39 GHz, 7 GHz, 9.4 GHz, and 14.48 GHz, which have a slight frequency shift compared with the four resonance points of the antenna in Figure 3d. The overall operating area of the antenna is 1.83-15.69 GHz, the operating bandwidth reaches 13.86 GHz, and the relative bandwidth is as high as 158.22%. Considering that the antenna sample needs to be connected to the detachable SMA adapter during the laboratory test, the antenna structure in Figure 3e is selected to be perforated at appropriate positions, which will have almost no effect on the performance parameters of the antenna, and finally, the final structure of the UWB monopole antenna is obtained as shown in Figure 3f.