esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 CCFD Self-Interference Suppression Performance  
The basic system model of CCFD is illustrated in Figure 2. During the reception of the Signal of Interest (SOI), due to the long distance between the transmitter and receiver, the signal experiences path loss during spatial transmission, resulting in low received signal power and high demands on receiver sensitivity. In contrast, for the Self-Interference Signal (SIS), since the transmitter and receiver are located at the same communication node and are spatially very close, the received signal power is at least 100 dB higher than the SOI [32]. This significantly degrades the quality of the SOI reception.  
In the CCFD communication mode, although it is possible to transmit and receive signals simultaneously at the same frequency, the target signal is affected by self-interference from the local high-power transmitted signal. This interference prevents the communication system from effectively extracting the valuable signal. Therefore, effectively suppressing system self-interference is a key technical challenge that must be addressed to realize the CCFD framework [33].  
Currently, extensive research is being conducted on CCFD self-interference suppression techniques. Based on the location of self-interference suppression, these techniques can be broadly categorized into spatial-domain (antenna-domain) self-interference suppression, analog-domain self-interference suppression, and digital-domain self-interference suppression [34]. Analog-domain self-interference suppression can be further divided into radio frequency (RF) and intermediate frequency (IF) self-interference suppression, with RF-domain suppression being the primary focus. A detailed schematic diagram is provided in Figure 3.  
Figure 2: Basic system model of Co-time Co-frequency Full Duplex (CCFD).
## 2 Materials and Methods
### CLQ Evaluation Method  
#### 2.2.1 The Definition of CLQ  
This study defined the CLQ from four aspects, including soil fertility, natural conditions, construction level, and cultivated land productivity. Soil fertility is the foundation of crop growth and is the most critical indicator used to measure the CLQ [44; 45]. The natural conditions of cultivated land can reflect some of the background properties that are closely related to the CLQ [27; 33]. Cultivated land is a semi-artificial and semi-natural ecosystem; thus, the impact of construction level on the CLQ cannot be ignored [15; 17]. The productivity capacity of cultivated land is the most direct manifestation of the CLQ [46] and should be taken into account.
# Ground Control System Based Routing for Reliable and Efficient Multi-Drone Control System
## 4 Performance Evaluation  
We conducted various experiments to evaluate GCS-routing performance, and selected two MANET PRPs: DSDV and OLSR, as comparison protocols. RRP end-to-end delay is very large due to frequent route establishments before data transmissions [37]. Thus, since high control rate is essential for drone networks, RRPs are inappropriate and were not considered for performance evaluations. On the other hand, PRPs update routing tables periodically, so they have a relatively short end-to-end delay compared to RRPs. We implemented GCS-routing, DSDV, and OLSR on real drones and GCS, and evaluated GCS-routing performance in various experiments. We then conducted simulations to support the experiment results, thoroughly verify GCS-routing performance, and evaluate GCS-routing from more diverse perspectives. The evaluations and simulations focused on throughput stability and network disconnection time, which significantly affect drone control through a network.
## 3 Applications of NMR in polysaccharide Research
### Biomedical Applications
also employed ROESY and \({}^{13}\)C NMR techniques to distinguish the difference between d- and l-hamnose in polysaccharide motifs. They did this to understand the specific functions of these sugars better [57]. [PERSON] et al. analyzed the water-soluble polysaccharides made by _Acetobacter xylinum_. They also found novel insights into the pathways of polysaccharide biosynthesis [58]. [PERSON] and [PERSON] used NMR to study the reactivity of derivative polysaccharides, advancing vaccine production through molecular characterization [59]. [PERSON] et al. used advanced NMR technology to elucidate the structure of _Streptococcus pneumoniae_ capsule polysaccharides, providing potential applications in disease prevention [60]. [PERSON] et al. fully analyzed the polysaccharides of the _Streptococcus pneumoniae_ 15F serotype capsule using advanced NMR technology, demonstrating its effect on immunological applications [61]. [PERSON] and [PERSON] gave approval for NMR to analyze the capsule polysaccharides used in vaccines. They linked the structural features to the quality of the drugs [62]. This research shows that NMR plays an important role in making progress in different fields, ranging from cancer treatment to vaccine development and polysaccharide biosynthesis. Through detailed structural and functional analysis, NMR has become an indispensable tool for combining basic research with practical biomedical innovations.
## 1 Introduction
Due to the ambiguity of the pros and cons of pavement performance, simple comparison methods such as the equipartition and weighted evaluation methods cannot fully consider the various factors in the evaluation process, nor can they reflect the degree of influence of various factors on the final evaluation, and the reliability of the evaluation is not high. The fuzzy comprehensive evaluation method solves the problem of fuzziness and uncertainty in judgment. Most fuzzy comprehensive evaluation methods use the analytic hierarchy process to determine the weight. The analytic hierarchy process is a subjective weighting method which judges the importance of an index based on experience to calculate its weight value, so it has the characteristics of significant subjectivity. The entropy weight (EW) method is an objective assignment method that depends on the discreteness of the data itself. It combines multiple indexes to comprehensively score samples to achieve comparison between samples. This method can reduce the influence of subjective factors on weight assignment to a certain extent. [PERSON] et al. [48] used an improved entropy weight-analytic hierarchy process to calculate the comprehensive weight coefficients of various evaluation indexes and established a preventive maintenance evaluation model for bitumen pavement. This idea can also be applied to the optimization of bituminous mixtures. In this study, bituminous mixtures with four different polymer products were prepared in the lab. A suite of laboratory tests was conducted to evaluate the high-temperature rutting resistance, low-temperature cracking resistance, moisture resistance and fatigue resistance of these four types of bituminous mixture. Based on experimental results, combined with material cost analysis, a fuzzy comprehensive evaluation method was employed to quantify the performance grades of the polymer-modified bituminous mixtures. Among them, the weights were calculated and determined using a comprehensive weighting method combining analytic hierarchy process and entropy weights. Finally, a bituminous mixture for the middle layer of the bitumen pavement in the toll plaza that is suitable for seasonally frozen regions in Northeast China and slow traffic load conditions was recommended.
## 4 Results  
### Within-Case Analysis  
#### 4.1.1 Case 1  
The interview was focused on just one warehouse, specifically the one located in Liscate (MI), which was the most important for flows and size (for further information on the 3 PL and warehouse features, see Table 3). As stated by the interviewee, this warehouse is owned by the 3 PL and was built specifically for the specific 3 PL's needs.  
The interviewee was asked to comment on the importance of the warehouse features (see Table 2) and rate the relationship with the performance indicators (see Table 4) to understand the most important warehouse features.  
1. Location. This category was not considered crucial by the interviewee. In the interviewee's eyes, this is not a key category due to the externalization of the transport function, so for the typical warehousing function that the 3 PL company uses, the location may not impact as much as it does in other 3 PLs. Indeed, according to the interviewee, location affects mainly the \"delivery\" part of the logistics service, specific aspects such as \"delivery lead time\" and \"on-time delivery\". Using the Kano model, the interviewee rated this relationship as \"attractive\" (A). This means that improving the quality of the location will exponentially increase the quality of the delivery service. The relationship between the location features of a warehouse and the flexibility of the logistics service offered is interesting: the interviewee saw a strong influence due to the ability of the location to ensure the possibility of having access to skilled labour to meet customer demand in the place in which the warehouse is located. In this way, it becomes relevant for 3 PLs to place their buildings considering strategic locations, especially close to industrial areas and logistics hubs.
2. External Areas. Extending the spaces in front of the loading and unloading areas is significant for a good service level (e.g., flexibility). Likewise, the number of loading bays is important for the 3 PL's service accomplishment (i.e., to speed up the receiving and shipping operations). However, these elements are rated \"must-be\" (M), taken for granted--the interviewee expects all warehouses to be equipped with these features. Moreover, they are not represented as crucial elements for the service level.
3. Building. The shape and size of the building are important for a good level of service in terms of timing (\"delivery\"), efficiency, and accuracy. The shape determines the exploitability of the building and its performance, but, as for the external areas, these elements are considered \"attractive\" (A)--their presentation improves the quality of the service provided.
4. Internal Areas. Since this firm mainly carries out warehousing services, the manager emphasised the importance of having suitable rooms, appliances, and utilities to be effective and productive in every task. So, this category is considered \"attractive\" (A) for productivity, order processing costs, and warehouse utilisation.
## 3 Results and Discussion
### Adsorption Mechanism of FD&C Red 40 Dye  
The adsorption mechanism of FD&C Red 40 dye on the surface of CS-TiO\({}_{2}\)-GLA beads can be proposed based on the adsorption sites available on the adsorbent surface. Different interactions can occur at the solid-liquid interface, and electrostatic interactions are considered the main form of adsorption. These can occur between the positively charged groups (\(-\)TiOH\({}_{2}\)+, \(-\)NH\({}_{3}\)+, and \(-\)OH\({}_{2}\)+) on the surface of the beads and the negatively charged sulfonate groups (\(-\)SO\({}_{3}\)\({}^{-}\)) of the dye. Two types of interactions involving hydrogen atoms can be included: dipole-dipole interactions and Yoshida-type hydrogen bonding. Dipole-dipole interactions can occur between the nitrogen and oxygen atoms of the dye and the hydrogen atoms on the surface of the beads, while Yoshida interactions can occur between the -OH groups of the beads and the aromatic rings FD&C Red 40 dye. Additionally, an n-\(\pi\) interaction may exist by delocalizing the free electron pair of the oxygen and nitrogen atoms in the polymer matrix with the \(\pi\) orbital of an aromatic ring of the dye [17, 28, 42].  
The GO-compact systems can perform hydrogen bonding via the carboxylic and hydroxyl groups present on its surface with the oxygen and nitrogen atoms of FD&C Red 40 dye. As far as electrostatic interactions are concerned (in the pH range of 3 to 7), the oxygenated groups of GO (carboxylic and hydroxyl) are in their neutral or protonated form so that at acidic pH, the number of positive charges on GO increases, which favors the adsorption of FD&C Red 40 dye by the attractive electrostatic force [36]. In turn, the \(\pi\) electrons of GO can undergo strong \(\pi\)-\(\pi\) interactions with the benzene rings of FD&C Red 40 dye [47], increasing the removal of the dye from 17.3% to 96.7% even at pH 7.
## 3 Case Study Analysis of Online PD Monitoring in Power Transformers
### Transformer A
#### 3.1.1 Results of Online Monitoring of Partial Discharges
The confusion matrix (Table 3) was then calculated, and the selected agreement metrics, that is, the Accuracy Index and the Jaccard Index, were determined. The confusion matrix indicates that both methods simultaneously detected PD pulses in 59.2% of cases (TP). At the same time, 16.4% of cases were observed in which the UHF method detected pulses (FP) while the AE method did not. In 17.9% of the cases, the opposite was true, i.e., the  
Figure 5: PRPD pattern of UHF PD pulses recorded on 18 October 2023, at 9:30 a.m., in the tested ‘Transformer A’. pulses were detected only by the acoustic emission method. In 6.4% of cases, both methods simultaneously detected no pulses (TN), which may indicate either a lack of PD activity or a limitation in the sensitivity of both systems. The Accuracy Index (0.656) suggests that the two methods agreed in about 65.6% of cases, a moderately high convergence of results. The Jaccard Index (0.633) shows that the agreement between the results of the two methods, taking into account cases of detection by at least one of them, is 63.3%. These results suggest that UHF and AE methods are largely complementary, but their performance in simultaneously detecting PD pulses may be limited by differences in detection mechanisms or their susceptibility to interference.
# BDS-3 Triple-Frequency Timing Group Delay/Differential Code Bias and Its Effect on Positioning
## 2 Data and Methods
### Triple-Frequency Satellite TGD/DCB Correction Model for BDS-3  
The satellite clock offset needs to be corrected for SPP and PPP using broadcast satellite clock and precise satellite clock, respectively. Notably, the clock offset in the BDS-3 broadcast ephemeris is based on the B3I frequency and the precise clock products offered by IACs are based on a combination of B1I and B3I IF [29]. Therefore, the BDS-3 broadcast ephemeris clock and precise clock products contain a part of the UCDs, expressed as:  
\[dt^{s}_{brdc}=dt^{s}+b^{s}_{B3I} \tag{14}\]  
\[dt^{s}_{pre}=dt^{s}+(\alpha_{B1 IB3I}\cdot b^{s}_{B1I}+\beta_{B1 IB3I}\cdot b^{ s}_{B3I})=dt^{s}+b^{s}_{IF_{B1 IB3I}} \tag{15}\]  
where \(dt^{s}_{brdc}\) and \(dt^{s}_{pre}\) are the satellite clock offset in the broadcast ephemeris and precise clock products, respectively.  
Different linear combinations will result in different noise amplifications. Dual-frequency IF combinations are mainly in the range of 2\(\sim\)4, but B2a/B3I, B2b/B3I, B2a/B2 band B1I/B1C combinations have amplification factors reaching unacceptable values of 9.43, 14.29, 27.47 and 77.38, respectively, and these frequency combinations are not suitable for positioning. For the triple-frequency, linear combinations, namely, B1I/B2a/B3I, B1C/B2a/B3I, B1I/B2b/B3I and B1C/B2b/B3I, are selected for the data processing in this paper. Table 1 provides statistics on the main characteristics of the triple-frequency models with different frequency combinations of BDS-3. The combinations 0-3 of the table are defined for convenience; for example, IF123-0 represents the B1I/B2a/B3I triple-frequency IF123 combination.  
Table 1 shows that the IF combination amplifies the observation noise but eliminates the ionospheric influence. The noise amplification factor for the new frequency, B1C/B2a combination, is 2.588, which is smaller than that of the old frequency combination, B1I/B3I, with an amplification factor of 3.527. The remainder of the combinations has noise amplification factors between these values, which means that the new frequency combination has a minor observation noise. The differences between the four noise amplification factors of IF123 are insignificant. These values range from 2.5 to 2.9. For UC, the noise amplification factors are all 1; however, UC cannot eliminate the effect of the ionospheric delay. Therefore, the parameters to be estimated for UC include the receiver position, clock offset, tropospheric parameter and ambiguity parameter as well as the ionospheric parameter. Moreover, the IFB parameter needs to be estimated for IF1213 and UC123 due to the UCDs.
# An Improved High-Resolution Network-Based Method for Yoga-Pose Estimation
## 4 Experiments and Analysis of Results
### Experimental Results for the COCO Dataset
#### 4.1.4 Experimental Verification and Analysis  
The experimental results of this section on the COCO calibration set are shown in Table 1. The results show that the SEPAM_HRNet model achieves higher accuracy than the original HRNet model with the same number of parameters as the HRNet model and with lower computational complexity. Compared with other recent human pose-estimation models, such as hourglass [2], CPN [39], CPN + OHKM [39], simple baseline [3], PRTR [35], and DistilPose-L [32], the SEPAM_HRNet model obtained 9.2, 7.5, 6.7, 5.7, 3.2, and 1.7 percentage points improvement on mAP, respectively. Compared to the HRNet [4] model, the SEPAM_HRNet model improved by 1.7 percentage points on mAP and 3.1 percentage points on AP50, while the other validation criteria remained comparable to the HRNet model. The experimental results are shown in Figure 6a.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Models** & **Backbone** & **Input\_Size** & **Params** & **GFLOPS** & **AP** & **AP.5** & **AP.75** & **AP(M)** & **AP(L)** \\ \hline Hourglass & Hourglass & 256 \(\times\) 192 & 25.1 M & 14.3 G & 66.9 & - & - & - & - \\ \hline CPN & & 256 \(\times\) 192 & 27.0 M & **6.2 G** & 68.6 & - & - & - & - \\ CPN + OHKM & ResNet-50 & 256 \(\times\) 192 & 27.0 M & **6.2 G** & 69.4 & - & - & - & - \\ Simple baseline & & 256 \(\times\) 192 & 34 M & 8.9 G & 70.4 & 88.6 & 78.3 & 67.1 & 77.2 \\ \hline PRTR & & 256 \(\times\) 192 & 57.2 M & 10.2 G & 72.9 & - & - & - & - \\ PRTR & HRNet & 384 \(\times\) 288 & 57.2 M & 21.6 G & 73.1 & 89.4 & 79.8 & 68.8 & 80.4 \\ DistilPose-L & & 256 \(\times\) 192 & **21.3 M** & 10.3 G & 74.4 & 89.9 & 81.3 & 71.0 & 81.8 \\ \hline HRNet & & 256 \(\times\) 192 & 28.5 M & 7.1 G & 74.4 & 90.5 & 81.9 & 70.8 & 81.0 \\ HRNet & 384 \(\times\) 288 & 28.5 M & 16.0 G & 75.8 & 90.6 & 82.5 & 72.0 & 82.7 \\ SEPAM_HRNet & & 256 \(\times\) 192 & 28.8 M & 7.0 G & **76.1** & **93.6** & **83.7** & **73.3** & 80.1 \\ SEPAM_HRNet & & 384 \(\times\) 288 & 28.8 M & 15.8 G & **77.6** & **93.6** & **84.7** & **74.7** & 81.8 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Performance comparison of COCO val2017. Comparison between SEPAM_HRNet and other methods on the COCO validation set. The notation “-” indicates that no reported results were available.  
In Figure 6a, the vertical axis represents the accuracy rate, the horizontal axis represents the computation amount, and the circle size corresponds to the model's parameter amount. It can be observed that the SEPAM_HRNet model proposed in this paper outperformed the recent human pose-estimation model, in terms of accuracy.
## 4 System Evaluation and Analysis
### Effect of Network Lifetime on Dynamic Network  
In this simulation, we emulated the dynamic mobile network environment; that is, the mobile devices could move randomly throughout our network. We compared the reschedule time of the active slots when a new device joined the network (1-50 nodes in order). The comparison results are shown in Figure 10. According to system definitions, DISCO and our proposed WQS methods can append the newly moving node in the demanded row computed by the first step. Thus the system can reschedule the active slots in a very short time. That is why the system time of DISCO and WQS methods is equalized to zero in Figure 10. By contrast, EQS must reconfigure the slot structures of the entire process again. The computation time is considerably longer than that of the other two methods.
## 6 Numerical Tests and Discussion  
### Simulation Setting  
All tests are coded with MATLAB 2016a and run on an Intel Core i7-5500U personal computer with 16 G memory. We use LOLP and EPNS as the reliability indices.  
In the test cases, the MCS method and traditional CE-IS method are compared with the DRCE-IS method in a modified IEEE-RTS 79 system. The data of the original IEEE-RTS 79 system can be acquired in [42]. The loads at all buses are expected to be perfectly positively related.  
Four wind farms are integrated into the modified system. We arbitrarily connect them to Bus 1, 2, 13 and 21, respectively. Each of them includes 50 3 MW-WTGs of the same type, whose parameters are shown in Table 1[43].  
WTGs may work under operation, derated or failure states. \(\lambda_{f}\), \(\mu_{f}\), \(\lambda_{d}\), \(\mu_{d}\), \(\lambda_{df}\) and \(\mu_{df}\) are the transition rates between any two of the three states, as shown in Figure 4. Theoretically, the WTG can transition from any of the three states to another, as shown by Figure 4. However, according to the \"partial failure mode\" developed in Page 26-27 of [44], WTGs are always restored to the operation state rather than the derated state in the actual repair process, so it is difficult to obtain \(\lambda_{df}\) and \(\mu_{df}\) by statistics. Hence, the transfer between the derated and failure states is always omitted. We also employ the assumption and set \(\lambda_{df}\) and \(\mu_{df}\) as zero here.  
Under the assumption, the probabilities of failure and derated states are derived by:  
\[\theta_{d}=\frac{\mu_{f}\lambda_{d}}{\lambda_{d}\mu_{f}+\mu_{d}\mu_{f}+\lambda _{f}\mu_{d}},\theta_{f}=\frac{\mu_{d}\lambda_{f}}{\lambda_{d}\mu_{f}+\mu_{d} \mu_{f}+\lambda_{f}\mu_{d}}, \tag{48}\]  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **Value** & **Parameter** & **Value** \\ \hline \(\lambda_{f}/(\text{a}^{-1})\) & 7.96 & derated ratio & 60\% \\ \(\mu_{f}/(\text{a}^{-1})\) & 58.4 & \(v_{cl}/(\text{m}/\text{s})\) & 3 \\ \(\lambda_{d}/(\text{a}^{-1})\) & 5.84 & \(v_{r}/(\text{m}/\text{s})\) & 10 \\ \(\mu_{d}/(\text{a}^{-1})\) & 43.8 & \(v_{\alpha}/(\text{m}/\text{s})\) & 25 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Reliability parameters of the 3 MW-WTGs.  
Figure 4: Three-state model for WTG.  
where \(\theta_{f}\) is the failure probability and \(\theta_{d}\) is the derated probability, which are consistent with the notation in (37).  
According to the data in Table 1, we can calculate \(\theta_{d}\) and \(\theta_{f}\), which are 0.1050 and 0.1074, respectively.  
According to the practical experience in the wind farms in Northwest China [43], the output of WTGs under derated state is set as 60-70% of its real-time maximum available output. Hence, we set the derated ratio as 60%, shown in Table 1.  
Wind speed data at Bus 1, 2, 13 and 21 are extracted from the historical data of four areas in Northwest China from 1 January to 31 December in 2013. The areas are Ganhekou, Changma, Liuyuan and Mazongshan. The wind speed PDFs are shown as curves in Figure 5. The data can be referred to by DOI: 10.13140/RG.2.2.29281.97125.