esa-sceva/satcom-chunk-collection huggingface dataset:
# Organochlorines Accumulation in Caged Mussels
## 3 Results
### OC Accumulation
In 2-year-old mussels, a similar decreasing order S4 (5.7 ng g\({}^{-1}\)dw), S3 (5.2 ng g\({}^{-1}\)dw), and S2 (5.2 ng g\({}^{-1}\)dw) was observed. Individually, DDE content varied from 2.33 to 5.77 ng g\({}^{-1}\)dw (CV = 28.2%) in 1-year-old mussels and from 1.32 to 5.05 ng g\({}^{-1}\)dw (CV = 23%) in 2-year-old mussels. DDD varied from 0.61 to 2.34 ng g\({}^{-1}\)dw (CV = 29.6%) in 1-year-old mussels and 0.84 to 3.01 ng g\({}^{-1}\)dw (CV = 36.1%) in 2-year-old mussels. The concentrations of PCBs varied from 51.48 to 136.6 ng g\({}^{-1}\)dw (CV = 31.9%) in 1-year-old mussels and 39.14 to 118.4 ng g\({}^{-1}\)dw (CV = 37.1%) in 2-year-old mussels. Average PCB concentration was undoubtedly the highest at S1, both in 1-year-old (114.8 ng g\({}^{-1}\)dw) and 2-year-old (102.8 ng g\({}^{-1}\)dw) mussels. The level of PCBs at other stations decreased in the order of S4 (69.5 ng g\({}^{-1}\)dw) \(>\) S3 (65.9 ng g\({}^{-1}\)dw) \(>\) S2 (64.3 ng g\({}^{-1}\)dw) in 1-year-old mussels and S3 (60.0 ng g\({}^{-1}\)dw) \(>\) S4 (52.7 ng g\({}^{-1}\)dw) \(>\) S2 (49.1 ng g\({}^{-1}\)dw) in 2-year-old mussels, depending on the environmental conditions in the Bay (Figure 4). Bimonthly transplanted _Mytilus galloprovincialis_ mussels from Mali Ston Bay to Kastela Bay responded quickly to changes in environmental conditions, resulting in an average 10.7-fold increase of PCBs and a 2.57-fold increase of \(p\),\(p^{\prime}\)-DDTs in 1-year-old mussels and an average 10.51-fold increase of PCBs and a 2.55-fold increase of \(p\),\(p^{\prime}\)-DDTs in 2-year-old mussels in relation to the initial values of the reference station. The intensity of changes was negligible for OCPs in both 1- and 2-year-old mussels from Kastela Bay (Figures 3 and 4). The accumulation pattern of chlorinated biphenyl (CB) congeners, CBs homologs, and chlorinated pesticides in 1- and 2-year-old mussels from Mali Ston Bay and the ones transplanted to Kastela Bay is presented in Figure 5.  
The individual contribution of chlorinated pesticides relative to the total contamination by pesticides is almost the same between Kastela Bay and Mali Ston Bay, showing no significant differences in relation to the age of the mussels. An overview of individual CB congeners in relation to total PCBs accumulated in 1- and 2-year-old mussels showed an average predominance of CB 153 and CB 138. CB homologs revealed the major average accumulation of hexachlorinated and pentachlorinated congeners in both 1- and 2-year-old mussels (Figure 5). The mussels' biometric parameters varied depending on age (size), station, and season (Tables 1 and 2). Figure 4: Variation of organochlorine pesticides (OCPs), \(p\),\(p^{\prime}\)-dichlorodiphenyltrichloroneethane (\(p\),\(p^{\prime}\)-DDTs (EDDE, DDD, and DDT)), and polychlorinated biphenyls (PCBs) during bimonthly exposure of transplanted mussels to Kastela Bay as spatial and temporal accumulation. Mussels set at S2 were not found in May.
# An Efficient Finite-Difference Stencil with High-Order Temporal Accuracy for Scalar Wave Modeling
## 5 Numerical Experiments  
### Seismic Modeling of a 2D Homogeneous Velocity Model  
In this section, we use a 2D homogeneous velocity model to examine our new stencil. The 2D homogeneous model had \(512\times 512\) grid nodes with a velocity \(v=1500\) (m/s). We set \(M=8\), \(N=8\) and a time step \(\Delta t=0.0015\) (s) for the FD methods. A Ricker wavelet with 40 (Hz) was injected as an explosion source. Figure 5 shows the snapshots of different methods with grid sampling \(h=4\) (m) and \(h=6\) (m).  
Figure 4: Stability curves of different FD methods: (**a**) stability factors varying with the Courant numbers \(r\) and (**b**) maximum stability factors satisfying \(r\leq s\) with different orders \(M\).  
Figure 5: _Cont._  
It can be seen that the TE-C method had visible temporal dispersion errors (red arrows) with the grid sampling \(h=4\) (m) and had both serious spatial (white arrows) and temporal dispersion errors with the grid sampling \(h=6\) (m). The corresponding temporal dispersion errors were reduced in the TE-R method, indicating that the new stencil had better temporal accuracy. The spatial dispersion errors were significantly reduced in the DRP-R method. Thus, the DRP-based FD coefficients could effectively mitigate the spatial dispersion with a large grid spacing.
# The Design and Deployment of an End-To-End IoT Infrastructure for the Natural Environment
## 4 Design and Deployment
### Power Supply  
Our animal tracking nodes were powered with a 10,000 mAh battery, designed to be replaced once per week. Similar to the soil nodes, we used aggressive power cycling with nodes in sleep mode most of the time. However, the amount of time that the animal tracker nodes needed to be awake was significantly extended by the duration of time that the GPS unit took to start up and then to acquire a high-quality GPS fix.
## 3 Results and Discussion
### Effect of Holding Time  
The effect of different holding times on the scandium content of anhydrous scandium chloride and hydrolysis rate of scandium is shown in Figure 4. Holding time is also one of the main factors affecting the scandium hydrolysis rate and scandium content of scandium chloride molten salt. If the insulation time is too short, ScOCl chloride is not complete, the hydrolysis rate of scandium is high, and ammonium chloride is not easy to be completely removed--seriously affecting the quality of scandium chloride molten salt and reducing the production efficiency [33; 34; 35; 36; 37].  
The hydrolysis rate of scandium decreased significantly when the time was less than 75 min. When the time was extended to 90 min, the hydrolysis rate of scandium showed the lowest value of 2.05%. Because the time was too short, the chlorination of ScOCl was not complete; On the contrary, if the time was too long, the water vapor in the inert gas tended to hydrolyze scandium chloride due to the sublimation of ammonium chloride, leading to an increase of the hydrolysis rate of scandium. Therefore, 90 min was more suitable for the holding time of removing ammonium chloride and the residual crystal water. The anhydrous scandium chloride with scandium content of 26.01% was obtained, and the hydrolysis rate of scandium was 2.05%.
###### Abstract  
Sulfur dioxide (\(\mathrm{SO_{2}}\)) is a major atmospheric pollutant and abiotic stressor. Although physiological studies on abiotic stressors have focused on fully expanded leaves, the resistance of leaf functional traits to \(\mathrm{SO_{2}}\) during individual leaf development has not been studied. Thus, this study aimed to conduct \(\mathrm{SO_{2}}\) static artificial fumigation experiments to evaluate changes in leaf functional traits and resistance to \(\mathrm{SO_{2}}\) for three common landscape tree species (_Syringa oblata_ Lindl. (_S. oblata_), _Prumus crasifera_ var. atropurpurea Jack. (_P. crasifera_), and _Ullmus pumila_ 'Jinve' (_U. pumila_) in Changchun City and ontogeny under \(\mathrm{SO_{2}}\) stress. Samples were collected on three days in autumn (1 September, 9 September, and 19 September 2019) for two different leaf stages (10 days and 40 days).  
In addition, remote sensing data were combined to explore the resistance mechanisms of broadleaf forests to different \(\mathrm{SO_{2}}\) concentration classes during different seasons on a large scale. The results showed that the chlorophyll content, leaf temperature, green-peak reflectance, and \(\mathrm{Fv/Fm}\) (maximal photochemical efficiency) at 10 days were significantly lower than that at 40 days, regardless of sampling date or \(\mathrm{SO_{2}}\) concentration. Additionally, in general the \(\mathrm{SO_{2}}\) resistance for 10 days leaves was consistently smaller than those for 40 days leaves in 3 tree species. On 9 September, 10 days leaves of the three tree species showed different leaf resistance performances under different \(\mathrm{SO_{2}}\) concentrations in the order: _P. crasifera > S. oblata > U. pumila_. Lastly, the extent of resistance decreased with increasing \(\mathrm{\rho(SO_{2})}\) classes in different seasons, and the \(\mathrm{SO_{2}}\) resistance was affected by season. We conclude that mature leaves are more resistant to \(\mathrm{SO_{2}}\) stress than young leaves are. These results will provide scientific guidance on artificial plant community construction and prevention of future vegetation degradation.  
tree species; \(\mathrm{SO_{2}}\) stress; resistance; plant ontogeny; leaf functional traits; large-scale; seasonal differences +
Footnote †: journal: remote sensing
# Spectrum Awareness for Cognitive Radios Supported by Radio Environment Maps: Zonal Approach +
Footnote †: Supported by Radio Environment Maps: Zonal Approach.  
In the paper, we discuss the concept of the REM and the problem of how to estimate the signal level accurately. We also present exemplary maps created with different interpolation methods and analyze how the choice of interpolation technique and the number of sensors affect the quality of the maps.  
The novelty of this paper can be summarized as follows:  
I. The paper proposes a zonal approach to the analysis of the quality of the signal level estimation for spectrum awareness purposes, i.e., the division of the area into zones with respect to the distance from the transmitter. It is worth noting that in most research works, the analysis is limited to the case with a group of receivers deployed on a small area which is distant from the transmitter. As a result, the signal level measured within the area varies slightly, which considerably simplifies the process of the signal level estimation. This process is much more complex if it is needed to estimate the signal level in close proximity to the transmitter or for a wider area with the transmitter inside. In the paper, we show that it is beneficial to divide such a wider area into zones and that the accuracy of interpolation techniques for such zones varies and is closely related to the distance from the transmitter.  
II. In our research work for the Inverse Distance Weighting (IDW) interpolation method, we extend the range of the power \(p\) up to 6, while in most cases this number is limited to 1 or 2. This is explained in detail in Section 3 (IDW method description) and Section 5 (the benefit of the application of IDW method with the power \(p\) higher than 2).  
III. To assess the efficiency of interpolation techniques we combine two metrics: (a) Differences between estimated values and measured values; (b) the ratio between correct and incorrect estimations. This is explained in detail in Section 5.  
The rest of the paper is organized as follows: Related works (Section 2), map construction techniques (Section 3), test scenario and exemplary maps (Section 4), analysis of the results (Section 5), and conclusions (Section 6).
###### Abstract  
In this paper, a novel ultraviolet (UV) scatter communication scheme is presented, designed to dynamically adjust the signal duty cycle to optimize on-off keying (OOK) modulation and reduce the bit error rate (BER), particularly under varying rate settings. This approach addresses the significant challenge posed by LED tailing effects, which cause signal fluctuations and increase BER in high-speed communications. This BER suppression scheme is proposed for the first time in UV communication research, enhancing communication performance without the need for additional hardware or complex algorithms. A UV communication model that incorporates both path loss and LED tailing effects is introduced, with the probability density function of the signal from transmitter to receiver derived. By varying the signal duty cycle, tailing-induced BER is effectively minimized. Additionally, a closed-form expression for signal transmission BER using a single-scattering model is provided, and the proposed UV communication system is validated through comprehensive simulations and experimental tests. The results indicate that LED tailing has a pronounced impact on BER at higher communication speeds, while its effects are less significant at lower speeds. By optimizing the duty cycle parameters for various communication rates, findings demonstrate that lower duty cycle settings significantly reduce the BER at higher speeds. This further demonstrates the excellent performance of the proposed UV communication solution for OOK-modulated optical communication.  
UV scattering communication; signal duty cycle; LED tailing Article Design and Optimization of an Ultraviolet Scattering Communication System Based on Duty Cycle Regulation  
[PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Design and Optimization of an Ultraviolet Scattering Communication System Based on Duty Cycle Regulation
# Integrating Environmental Data for Mental Health Monitoring: A Data-Driven IoT-Based Approach
## 3 Methodology  
This section outlines the methodology employed in the proposed IoT-based mental health monitoring system, which leverages big data, machine learning, and environmental sensors to monitor temperature and humidity levels in enclosed settings for managing the mental health status of residents. The system's objective is to identify correlations between environmental parameters (specifically temperature and humidity) and emotional states (particularly stress level), as well as to develop predictive models for early intervention.
# Exploiting Duplications for Efficient Task Offloading in Multi-User Edge Computing
## 6 Evaluation
### The Convergence of Distributed DETO Algorithm  
In the multi-user UDN networks, the distributed DETO algorithm is a game-based algorithm; therefore, its convergence must be guaranteed. Figure 3 shows the numerical results of the convergence behavior of distributed DETO algorithm with different number of users and servers.  
From this figure, we find that: (1) The distributed DETO algorithm always can reach a Nash equilibrium. (2) The increased number of users will contribute to increasing the convergence time. (3) In a certain number of users, the more edge servers, the lower the average latency, as the user can share more edge computation resources (taking more CPU cycles). However, since the user faces more offloading choices, which comes with the increase in convergence time. (4) The different value of the average delay between the initial step and the convergence step represents the performance gains from edge computing.
## 4 Experimental Results and Analysis  
Experiment 1 provides a controllable experimental environment. It not only has the actual spaceborne SAR dataset but also contains the complete truth data, which can be used to evaluate the system and verify the performance of the algorithm. This experiment provides us with a quantitative method to evaluate the effectiveness of the algorithm.  
Figure 6: Flowchart of the SAR-SIFT algorithm.  
Experiment 2 expanded the scope of the experiment and selected a larger experimental area, namely the parking lot of BEIJING-HYUNDAI AUTO Enterprise, which was located in the real application background during the COVID-19 pandemic. This experiment serves as a practical application context for presenting the outcomes.  
Experiment 3 also provides a controllable experimental environment, which uses RTK equipment to accurately record vehicle coordinates, and then verifies the robustness of the proposed method with higher-resolution data.
###### Abstract  
In this paper, a reweighted sparse representation algorithm based on noncircular sources is proposed, and the problem of the direction of arrival (DOA) estimation for multiple-input multiple-output (MIMO) radar with mutual coupling is addressed. Making full use of the special structure of banded symmetric Toeplitz mutual coupling matrices (MCM), the proposed algorithm firstly eliminates the effect of mutual coupling by linear transformation. Then, a reduced dimensional transformation is exploited to reduce the computational complexity of the proposed algorithm. Furthermore, by utilizing the noncircular feature of signals, the new extended received data matrix is formulated to enlarge the array aperture. Finally, based on the new received data, a reweighted matrix is constructed, and the proposed method further designs the joint reweighted sparse representation scheme to achieve the DOA estimation by solving the \(l_{1}\)-norm constraint minimization problem. The proposed method enlarges the array aperture due to the application of signal noncircularity, and in the presence of mutual coupling, the proposed algorithm provides higher resolution and better angle estimation performance than ESPRIT-like, \(l_{1}\)-SVD and \(l_{1}\)-SRDML (sparse representation deterministic maximum likelihood) algorithms. Numerical experiment results verify the effectiveness and advantages of the proposed method.  
multiple-input multiple-output radar; direction of arrival estimation; mutual coupling; reweighted sparse representation; noncircular signal +
Footnote †: journal:  
Article
# Comparison of L1 and L5 Bands GNSS Signals Acquisition
## 4 Application to GPS and Galileo Signals
### Comparison of GPS L1 C/A and L5 Signals Acquisition
#### 4.2.2 Determination of Ratio of Complexity for One Frequency Bin  
Using the total integration time of Tables 5 and 6, the parameters that depend on the integration, i.e., the processing time and the memory requirements, can be determined for the different cases. Table 8 illustrates this in detail for a sensitivity of \(-150\) dBm, where the ratio of processing time and  
memory between the L5 signal and the L1 C/A signal is given. The final metric of performance is the product of ratios. If nothing is specified, there is no assistance. Then, Table 9 complements it by adding the input memory that stores the input signal. Finally, Table 10 and Figure 12 summarize the product of ratios for all the sensitivities, considering or not the input memory. First, it can be seen that when the coherent integration time is limited to 20 ms for the L5 signal (non-coherent (NC) case), the L5 signal implementations are much more complex, with products of ratios higher than 100 without assistance. It can also be noted in Tables 8 and 9 that without taking into account the input memory, using a parallel, semi-parallel or serial implementation provides about the same performance (except for some semi-parallel that are not efficient, such as the one with nine accumulators because it requires more memory than with seven accumulators for the same processing time since \(20/9=20/7=3\)). When considering the input memory, the parallel implementation becomes more efficient, because such implementation uses a lot of memory, and therefore the input memory represents a smaller portion of it. This is more and more true as the sensitivity decreases. This is why only the parallel implementation is considered in Table 10 and Figure 12 when there is no assistance. Now, let us focus on the interesting implementations, i.e., when the coherent integration time is not limited. Without assistance, for moderate sensitivities, the L5 implementations are much more complex with products of ratios up to 50. For very high sensitivity, the product of ratios becomes much smaller, even lower than 1 for a sensitivity of \(-160\) dBm. This is mainly because the L1 C/A signal needs a very long integration time, and the input memory can even be larger for the L1 C/A signal than for the L5 signal. With assistance, the products of ratios are much smaller, between 0.1 and 4.6. Therefore, the L5 implementation can be more efficient for the computation of one frequency bin, or if it is less efficient it is by a relatively small ratio. However, remember that the number of frequency bins for unlimited \(T_{\text{C}}\) is not the actual one, and it should be much higher with very long coherent integration time (except if the assistance is very accurate, which is possible in some applications [22]).
# Coupled Vibration Analysis of Multi-Span Continuous Cable Structure Considering Frictional Slip
## 2 Nonlinear Coupled Vibration Model
### Establishment of Coupled Vibration Equations  
Coupling the equations of motion of the crane and the main cables together yields  
\[\begin{bmatrix}M_{v}&0\\ 0&M_{b}\end{bmatrix}\cdot\left\{\begin{array}{c}\dot{u}_{v}\\ \dot{u}_{b}\end{array}\right\}+\begin{bmatrix}C_{v}&C_{vb}\\ C_{bv}&C_{b}\end{bmatrix}\cdot\left\{\begin{array}{c}\dot{u}_{v}\\ \dot{u}_{b}\end{array}\right\}+\begin{bmatrix}K_{v}&K_{vb}\\ K_{bv}&K_{b}\end{bmatrix}\cdot\left\{\begin{array}{c}u_{v}\\ u_{b}\end{array}\right\}=\left\{\begin{array}{c}0\\ -F_{g}\end{array}\right\} \tag{19}\]  
where \(\begin{bmatrix}M_{v}&0\\ 0&M_{b}\end{bmatrix}=\begin{bmatrix}m_{v}&0&0&\cdots&0&0\\ 0&m&0&\cdots&0&0\\ 0&0&m&\cdots&0&0\\ \vdots&\vdots&\vdots&\ddots&\vdots&\vdots\\ 0&0&0&\cdots&m&0\\ 0&0&0&\cdots&-c_{v}&\cdots&0\\ 0&c_{1,1}&\cdots&c_{1,i}&\cdots&c_{1,n}\\ \vdots&\vdots&\ddots&\vdots&\ddots&\vdots\\ -c_{v}&c_{i,1}&\cdots&c_{i,i}&\cdots&c_{i,n}\\ \vdots&\vdots&\ddots&\vdots&\ddots&\vdots\\ 0&c_{n,1}&\cdots&c_{n,i}&\cdots&c_{n,n}\\ \end{bmatrix}\),  
\[\begin{bmatrix}K_{v}&K_{vb}\\ K_{bv}&K_{b}\end{bmatrix}=\begin{bmatrix}k_{v}&0&\cdots&-k_{v}&\cdots&0\\ 0&k_{1,1}&\cdots&k_{1,i}&\cdots&k_{1,n}\\ \vdots&\vdots&\ddots&\vdots&\ddots&\vdots\\ -k_{v}&k_{i,1}&\cdots&k_{i,i}&\cdots&k_{i,n}\\ \vdots&\vdots&\ddots&\vdots&\ddots&\vdots\\ 0&k_{n,1}&\cdots&k_{n,i}&\cdots&k_{n,n}\\ \end{bmatrix}.\]  
The basic steps for solving the forced vibration response of a multi-degree -of-freedom system are firstly, to determine the intrinsic properties of the system, then to establish the  
Figure 8: Decomposition diagram of the total stiffness matrix.  
decoupled modal equations of motion of the system and then to solve the equations according to the single-degree-of-freedom theory. If the system is subjected to a general excitation, the forced vibration response is attributed to the calculation of Duhamel convolution integrals, which not only is a cumbersome and lengthy process, but also often fails to find an analytical solution for the Duhamel integrals. Therefore, for this type of system of equations, the numerical method of stepwise integration can be used to solve the system [29].