esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Analytical Methods for Detection, Identification, and Quantification of C-CTXs
### Analysis of C-CTXs in Fish by HPLC-MS/MS (Low-Resolution)
#### 5.2.1 First Quantification of C-CTX-1 in Caribbean Fish Using HPLC-MS/MS
* Identification of C-CTX-1 and C-CTXs congeners in Caribbean Fish  
The (U)HPLC-MS/MS methods developed using an ESI-quadrupole-linear ion trap instrument (QTRAP 4000, Applied Biosystems, Waltham, MA, USA) confirmed the presence of C-CTX-1 in Caribbean fish that tested positive for CTX in the neuroblastoma cell-based assay (CBA-N2a). This conformation was achieved by comparing the retention time and ion transitions relative to a purified C-CTX-1 standard [22; 37; 39; 108; 174] (Table 4). Based on extracted samples of a barracuda implicated in a CP and purchased in a local supermarket in Massachusetts (USA), [PERSON] et al. evaluated composite toxicities of 1.6 and 2.1 ppb in the cooked meal remnant and uncooked portion, respectively [108]. LC-MS/MS analyses confirmed the presence of C-CTX-1 identified additional putative C-CTX congeners. In this work [108], the in-source collision-induced dissociation (CID) of C-CTX-1 [M+H]\({}^{+}\)\(m/z\) 1141.6 resulted in the loss of water and a major fragment ion at \(m/z\) 1123.6 [M+H-H\({}_{2}\)O]\({}^{+}\). Therefore, three precursor/product ion transitions were selected for multiple reaction monitoring: \(m/z\) 1123.6 \(\to\)\(m/z\) 1105.6, \(m/z\) 1123.6 \(\to\)\(m/z\) 1087.6, and \(m/z\) 1123.6 \(\to\)\(m/z\) 1069.6 [108]. The toxic profiles by CBA-N2a of the cooked meal remnant and raw barracuda extracts were nearly identical, with eight well-defined peaks of cytotoxicity. LC-MS/MS analysis demonstrated that C-CTX-1 was the principal CTX associated with cytotoxic peak 4, contributing \(\sim\)60% of the composite toxicity in these two samples [108]. Patterns of ions characteristic of CTXs were observed in full-scan and product ion spectra of cytotoxic peaks 1 and 3 (\(\sim\)28% of the composite toxicity) and were attributed to protonated molecules at \(m/z\) 1159 and \(m/z\) 1143 (possible C-CTX-3/\(\sim\)4 [120]), respectively. The authors suggested that the C-CTX congener with a [M+H]\({}^{+}\) at \(m/z\) 1159 could be either a hydroxylated C-CTX-1 or an oxidised form of C-CTX-1143. Among the minor cytotoxic peaks, only peak 2 full-scan and product ion spectra were suggestive of CTX, with an abundant ion at \(m/z\) 1139 resulting from the loss of a water molecule from the protonated molecule at \(m/z\) 1157 (possible oxidised form of C-CTX-1 derivatives) [108]. The characteristic ciguatoxin MS spectra could not be confirmed for peak 6, although it accounted for 11% of the composite toxicity [108].
## 2 Sampling and Analysis Methods  
The research area was located in the center of Asia (103 deg39'-110 deg42' E, 51 deg15'-55 deg55' V). The research object was the central ecological zone of Lake Baikal (water area and coast), Barguzinskaya valley, as well as areas of industrial centers of the Baikal region affecting the lake. Sampling sites were selected based on the preliminary HYSPLIT model calculations while taking into account the sources of pollutants, prevailing winds, and the surrounding terrain. The pH value and electrical conductivity were determined in the samples of the snow cover. After filtration through a membrane filter, the concentrations of the main ions were measured. Determination of cations in atmospheric precipitation was carried out on the ContrAA800 atomic absorption spectrophotometer (Analytik Jena AG, Jena, Germany), anions--on the ICS-3000 ion system (Dionex, Sunnyvale, CA, USA). Chemical analyses were performed in the accredited laboratory of hydrochemistry and atmospheric chemistry of the Limnological Institute of the Siberian Branch of the Russian Academy of Sciences according to the methods recommended in the atmospheric monitoring networks of international programs--EMEP [53] and EANET [54]. In order to build maps, more than 400 receptor stations were analyzed, more than 180 of which were selected regularly in the monitoring mode over the past 4-6 years (Figure 1).  
located in the Angara River valley [46]. The samples taken from the ice of Lake Baikal were included in separate groups (from the twelfth to the fourteenth) due to different periods of accumulation of snow cover on the ice of the lake (two and a half months) and on its coast (four months) [55; 56].
## 1 Introduction
The results show that the proposed methodology can effectively identify the location of human-made damage and accurately estimate the degree of damage under different frequencies of sinusoidal excitation. The method has also shown a strong anti-noise property.
## 3 Research on BPL Decoding Algorithm for Polar Codes Based on Information Geometry
### Path Selection Criterion Based on Soft Information Centroid
#### 3.2.2 Path Selection Criterion Based on Soft Information Centroid  
The path selection criterion based on the soft information centroid is as follows in Figure 4:  
* First, map the \(L\) decoding results to \(L\) points on the manifold and assign weights to them;
* Then, calculate the soft information centroid of the \(L\) decoder soft information;
* Finally, make a decision based on the soft information centroid and output the decoding result.  
Unlike traditional path selection criteria that use only one decoding result as the output, this paper adopts the soft information centroid to equivalently calculate \(L\) decoding results and uses it as the output of BPL decoding. The traditional path selection criterion can be regarded as a special case of this method. Assuming that the kth decoder is the path with the smallest Euclidean distance in passing the check, then:  
\[w_{j}=\left\{\begin{array}{cc}1&j=k\\ 0&j\
eq k.\end{array}\right. \tag{17}\]
# The Car-Following Model and Its Applications in the V2X Environment: A Historical Review
## 5 Conclusions  
The informatization and intellectualization degree of the transportation systems will be significantly improved with the application of V2X and other relevant technologies. In the new traffic environment, there are changes in the characteristics of drivers' car-following behavior. A certain number of studies on the car-following models and their applications have been carried out by many scholars, and achievements have been made. In this paper, we first briefly reviewed the development process of traditional car-following models. Second, the relevant and representative studies were reviewed by dividing them into three aspects, which, respectively, are the impacts of V2X technology, the car-following models considering the impacts of V2X technology, and the applications of these models. Finally, the achievements, as well as the existing shortcomings, were summarized, and, based on this, the major issues in the further exploration were discussed. We hope the results of this paper can provide a reference for further research on the car-following model and its applications in the V2X environment, and contribute to updating and enriching traffic flow theory.  
Writing--original draft, J.H.; Writing--review and editing, [PERSON], L.C. and H.S.; Investigation, J.H., L.C. and H.L.; Visualization, H.S. and H.L.; Supervision, X.W.; Resources, X.W.; Funding acquisition, X.W. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Natural Science Foundation of Shandong Province, grant numbers ZR2020 MF082; the Collaborative Innovation Center for Intelligent Green Manufacturing Technology and Equipment of Shandong Province, grant numbers IGSD-2020-012; the Qingdao Top Talent Program of Entrepreneurship and Innovation, grant numbers 19-3-2-11-zhc; the National Key Research and Development Program, grant numbers 2018 YFB1601500.  
Not applicable.  
The authors declare no conflict of interest.
## 1 Introduction
In summary, this paper focuses on the interference problem of the 5G system to the airborne BeiDou RDSS system, and carries out the interference analysis from the signal level and the system level, respectively, on the basis of which, from the perspective of civil aviation safety, evaluates the impact of the interference of the ground-based 5G system during the takeoff and landing phases of the aircraft. In Section 2, the structure of the BeiDou-3 RDSS outbound signal and the time-domain waveform of the 5G signal are introduced, and the interference problem caused by the serious out-of-band trailing of the 5G signal waveform is clarified. Section 3 mainly analyzes the interference from the signal level, and the performance impact of 5G as an interfering signal on BeiDou capture and tracking is investigated, and the critical distance of interference at the signal level is obtained. Section 4 mainly analyzes from the system level and obtains the theoretical distance isolation with different 5G frequency isolation. Based on this, the terrestrial 5G system interference suffered during aircraft takeoff and landing is evaluated using real data from flights and employing aggregate interference as an evaluation metric. Finally, in Section 5, Based on the simulation results, conclusions are drawn to provide a reference for the future planning and construction of ground-based 5G base stations and to promote the application of the BeiDou RDSS system in civil aircrafts.
## 3 Experimental Results and Analysis
### Feature Selection Set Modeling Results  
The Pearson correlation coefficient was used to calculate the correlation between the features and between features and the target value, as shown in Figure 5. Based on experience, a Pearson correlation coefficient greater than 0.5 is considered to have a high correlation with the target. Therefore, all features with a correlation greater than 0.5 with the convective heat transfer coefficient h were selected. Thus, D, Vq, Pin, Qw, RE, and Dh were chosen as the sensitive input features for the straight channel. There was a strong correlation between Tin and h (\(-\)0.73), Pin and h (0.75), Tinw and h (\(-\)0.78), Vin and h (\(-\)0.59), pin and h (0.75), and PR and h (0.78). Therefore, Tin, Pin, Tinw, Vin, pin, and PR were selected as the sensitive input features for the hexagonal channel.  
The results of modeling the performance of five models in predicting the heat transfer coefficient under different channel shapes and feature selection methods are summarized in Table 3. Under the straight channel condition, although all models performed relatively well, the ANN model achieved the highest R\({}^{2}\) value (0.891799) and the lowest RMSE (1259.36), indicating its superior fitting ability and prediction accuracy for this channel shape. When the channel shape changed to a hexagonal channel, the performance of all models significantly improved, with R\({}^{2}\) values generally approaching or exceeding 0.99. Specifically, the optimal ANN model achieved the highest R\({}^{2}\) value (0.995199) and the  
Figure 5: Pearson correlation coefficient heat map: (**a**) straight flow channel; (**b**) hexagonal flow channel.  
lowest RMSE (79.02), demonstrating that the hexagonal channel has a substantial positive impact on enhancing the accuracy of the heat transfer coefficient prediction.  
Among the two channel shapes, the improvement effect of Pearson on most models was relatively limited. In particular, for the straight channel, the \(\mathbb{R}^{2}\) values and error metrics of some models either did not show significant improvement or even deteriorated after feature selection. In contrast, for the hexagonal channel, although the model performance remained strong post-feature selection, certain models (e.g., SVM and CATBOOST) continued to exhibit high prediction accuracy. This suggests that feature selection still holds a certain optimization value in complex structures.
## 1 Introduction
The sensor attaches to the lowest point of the shoe's lace zone, as indicated by the manufacturer. Based on an inertial measurement unit (IMU), 6 axes (3-axis gyroscope, 3-axis accelerometer), the data is provided to quantify power (P), stride frequency (SF), vertical oscillation (VO), leg stiffness (Kleg), pace, distance, and elevation during the race. Several studies were able to show the reliability and validation of the parameters presented above. Speed was shown to be valid and reliable during trail or walking [19]. Concerning P, it was reliably measured on different surfaces at sub-maximal speed [20]. The relationship between P and speed was shown to be linear for speeds ranging from 8 to 20 km/h on a treadmill [21]. The GCT and Kleg were validated by a recent study for speeds between 8 km/h and 20 km/h on an indoor track [22]. As explained at the beginning of the introduction, measures of STP variation with respect to terrain variability under ecological conditions have not yet been studied. However, several things have already been demonstrated regarding running STP. The level of the participants influences STP with lower SF and vertical stiffness (Kvert) and longer FT and SL for high performance athletes [16]. VO, SF and SL influence the economy of running on the flat [23]. Kleg, GCT, and SF are more important for high level runners in uphill racing. Conversely FT and SL decrease. These parameters affect the uphill running technique [24] and in downhill running, GCT decreases [25]. The studies cited above show that STP have an influence on performance, but these influences have often been demonstrated under stable conditions, on flat circuits or in the laboratory on a treadmill. Our study is based on the following observations, which are the lack of measurements in the field and the great interest in portable sensors by most practitioners. The main objectives were to (i) measure the variation of STP according to the typology of the terrain (ii) in an ecological condition to expose the participants in a variety of trail paths that they could find in competition and (iii) to use so-called \"low-cost\" portable sensors already used by a large majority of runners. The combination of the data collected will allow the analysis of which STP are related to the best results according to the typology of the terrain. The objective is to orientate the runners to work on certain parameters of their running technique more than others, in order to obtain better performance on a trail circuit of less than 10 km.
# Information Relaying Methods in VANET: Algorithms, Standards and Tests
## 2 Introduction
All in all, five parameters--location, direction, speed, destination and list of interests--jointly form different routing protocols for a stable cluster network, but with no efforts to the investigation and analysis of power efficiency and algorithm convergence. Our proposal, by contrast, holding the viewpoint of ensuring an efficient power and relaying network, considers a more realistic VANET topology with real centroids and a corresponding seeding criterion, implemented in a range-restricted manner. With the help of the enhanced K-means algorithm, the vehicle closest to the virtual mean center vehicle in the set is selected as a relay vehicle, and the seeding area in the initialization procedure is subject to the maximum transmission power of the relay vehicles. Speaking of the route optimization, our solution introduces connecting vehicles as a low power message dissemination node to bridge the selected cluster head and its neighbor cluster heads. To extend the scope after the trial test thinking, the base station and core network are incorporated with the potential of Third Generation Partnership Project (3 GPP) standard enhancement of the architecture. The rest of this paper is organized as follows: Section 3 gives a typical V2X radio propagation model with the help of a randomly distributed vehicle map on a four-lane highway. In Section 4, K-means-type algorithms with centroid and seeding enhancements are proposed. Through the experience of IMT-2020 organized C-V2X large-scale test, a high level location based solution with specification impact is summarized in Section 5. In Section 6, we carry out MATLAB, NS3 and Veins simulations to evaluate the performance of the proposed algorithms and the retro from the real-world test followed by corresponding analytics and speculations in Section 7. Finally, Section 8 concludes the paper.
## 4 Numerical Modelling
### Finite Element Mesh and Boundary Condition  
The interaction between the piles and the surrounding soil is modeled as frictional contact, combining normal direction hard contact with tangential friction contact. An interface strength reduction factor of 0.8 is applied [59]. Initial overburden stress is determined using the static earth pressure coefficient, with \(K_{0}=1-\text{sin}\rho\), where \(\varphi\) represents the soil friction angle. Finite element analysis is used to simulate the behavior of the pile-soil interaction, with C3D8P elements employed for the piles and C3D8R elements used for the gravel cushion layer and tunnel. In order to account for the longitudinal tunnel similarity to an infinitely long cavity, a single group of SCP pile elements is considered along the \(Y\)-axis direction, and the width of the model extends up to 112 m to eliminate boundary effects. In the \(Z\)-axis direction, the bottom of the model is situated 3.1 \(D\) (\(D\) represents the pile diameter) away from the pile ends [60]. Constraints are applied to the boundaries of the model and base, and spring-dashpot elements are included to represent viscoelastic boundaries. Within the SIS system, the effect of water pressure is implemented by adding additional mass at the top of the model, as depicted in Figure 9.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Parameters** & **Marine Clay** & **SCP** & **Immersed** & **Gravel Cushion** & **Backfill** \\ \hline Consolidation index, \(\lambda\) & 0.113 & 0.023 & & & \\ \hline Swelling index, Kr & 0.05058 & 0.0103 & & & \\ \hline Critical state parameter, \(M\) & 0.668 & 1.2 & & & \\ \hline Poisson’s ratio, \(\
u\) & 0.36 & 0.3 & 0.17 & 0.45 & 0.37 \\ \hline Density, \(\rho\) (g/m\({}^{3}\)) & 1.851 & 1.765 & 2.45 & 0.9 & 2 \\ \hline Buoyant density, \(\rho_{w}\) (g/m\({}^{3}\)) & 0.801 & 0.715 & 1.4 & 0.85 & 0.95 \\ \hline Cohesion, \(C\) (kPa) & 7.4 & 0.5 & & & \\ \hline Friction angle \(\varphi\) (\({}^{\circ}\)) & 15 & 30 & & & \\ \hline [PERSON]’s modulus, \(E\) (kPa) & 2821.83 & \(E^{*}\) & 30,000 & 20,000 & 150,000 \\ \hline Permeability, \(\kappa\) (m/s) & \(1.8\times 10^{-8}\) & \(3\times 10^{-5}\) & & & \\ \hline Coefficient of lateral pressure & 0.577 & 0.5 & & & \\ \hline Initial void ratio, \(e_{0}\) & 1.059 & 0.72 & & & \\ \hline Degree of saturation & 1 & 1 & & \\ \hline \hline \end{tabular} Note: \(E^{*}=0.6\sigma_{\text{at}}(\sigma_{\text{m}}/\sigma_{\text{at}})^{3}\), where \(\sigma_{\text{at}}{}^{\prime\prime}\) is the stress of atmospheric and \(``\sigma_{\text{m}}{}^{\prime}\) is the current average principal stress in the soil unit under consideration [46].  
\end{table}
Table 2: Material constants for modeling.
## 5 Simulation Experiments and Analysis
### Simulation Scene  
According to the Iridium constellation in Figure 2, some parameters are configured to maintain dynamic ISL updating, and the parameters are listed in Table 1[41].  
The coordinates of the two GS on Earth are (17\({}^{\circ}\) S, 31\({}^{\circ}\) E) and (48\({}^{\circ}\) N, 99\({}^{\circ}\) E), and are denoted by GS\({}_{1}\) and GS\({}_{2}\), respectively, as shown in Figure 12. GS\({}_{1}\) is the requester of interest, and GS\({}_{2}\) is the data responder. Communication between the two GSs is established via the ISLs with multiple hops [41].  
The content forward process is described as follows: When the GS\({}_{1}\) requests content, the connecting satellite nodes will first check if a copy of the content is stored in the local cache. If a copy of the content is already cached, the satellite nodes will return the content directly in response to the request. If no copy is cached, the satellite nodes forward the requested packet of interest to the surrounding satellite nodes via ISLs, and the surrounding satellite nodes will be in response to the request. If the content is not available in the entire satellite network, the request will be forwarded to the GS\({}_{2}\).  
Figure 11: The architecture of the LEO-SMC-ICN-IoT simulation platform.  
Figure 12: Two-dimensional LEO satellite constellation with ISL coverage diagram.
## 2 RS Systems
### Active  
#### 2.2.1 SAR  
Synthetic Aperture Radar (SAR) systems are side-looking radar instruments that acquire surface information in two-dimensional directions (i.e., azimuth and range). SAR sensors successively transmit pulses toward different targets on Earth; afterwards, they record the scattering echoes [41]. Generally, SAR systems have a day-and-night imaging capability and can work in all weather conditions. The platform movement and signal processing techniques allow the generation of high-resolution SAR data [41]. Despite the high-resolution data, the narrow swath and incidence angle dependencies are the main limitations of SAR sensors. SAR data are usually processed and provided in two common formats of Single Look Complex (SLC) and Ground Range Detected (GRD) for further interpretation.
# Multi-Input Attention Network for Dehazing of Remote Sensing Images
## 2 Related Work  
At present, the research on single-image dehazing falls into two categories: traditional methods and deep learning methods.
# Parameter Design for Inter-Satellite Laser Link Acquisition Under Weak Light Conditions
## 3 Analytical Model
### Mean Acquisition Time  
Acquisition time serves as a comprehensive measure of the effectiveness of parameter design. To establish a laser link, if the acquisition is not completed, the acquisition process must be repeated until the link is successfully established. Therefore, acquisition time is influenced not only by the acquisition success probability of a single scan but also by the mean acquisition time of a single link.  
The mean time for a single scan to achieve successful acquisition is \(T_{1s}=2\pi\sigma_{uc}^{2}/(D_{t}v_{t})\)[16]. The time required to scan the entire UC if the acquisition is not complete is \(T_{uc}=\pi\sigma_{max}^{2}/(D_{t}v_{t})\). According to [7], considering only the scanning process, we can calculate the mean acquisition time for multiple scans:  
\[T_{ms}=T_{1s}+\frac{P_{lost}}{1-P_{lost}}T_{uc}=\frac{\pi}{D_{t}v_{t}}\Bigg{(} 2\sigma_{uc}^{2}+\frac{P_{lost}}{1-P_{lost}}\tau_{max}^{2}\Bigg{)}. \tag{22}\]
# Dual Stimuli-Responsive Polysaccharide Hydrogels Manufactured by Radiation Technique
###### Abstract  
This paper describes the results of the radiation-induced crosslinking of polysaccharides modified with hydroxypropyl and carboxymethyl functional groups, hydroxypropylcellulose (HPC) and carboxymethylcellulose (CMC), respectively, without and with poly(ethylene glycol)acrylate (PEGDA) as a crosslinking agent, to obtain dual stimuli-responsive hydrogels. The gels were characterized in terms of water uptake and gel fraction, parameters that mainly depend on the HPC-CMC compositions, but also on the macromer crosslinker content and the absorbed dose. The swelling of hydrogels is controlled by both the temperature, due to the amphiphilic character of HPC and pH, due to the anionic functional groups of CMC. In spite of a similar degree of substitution in both cellulose derivatives, 1.4 for HPC and 1.2 for CMC, the pH response of hydrogels with an equal content of both polysaccharides is considerably higher--a reduction in swelling of up to 95% with a decrease in the pH to 2 was recorded--than the response to thermal-stimulus--wherein a reduction in swelling of less than 70% with an increasing in temperature to 55 \({}^{\circ}\)C was found. These biopolymers-based hydrogels of specific, stimuli-responsive swelling properties are anticipated in applications where a combination of two stimuli is essential and biodegradation may be required.  
hydrogel; stimuli-responsive; hydroxypropylcellulose; carboxymethylcellulose; PEGDA; radiation crosslinking; thermo-responsive; pH-responsive; swelling Article