esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Performance Evaluation of NDVI Prediction Models  
In this study, to ensure the predictive performance and stability of the stacked model, a dataset partitioning method was employed, whereby 20% of the data were randomly assigned to the test set, with the remaining 80% allocated for the training set. Upon finalizing the model configuration, an independent 20% test set was utilized for external validation aimed at assessing the model's generalization capability on unseen data. For a comprehensive evaluation of the predictive models constructed under various SSP scenarios, multiple evaluation metrics were adopted for an integrated analysis, encompassing RMSE, MAE, and R\({}^{2}\). As illustrated in Figure S6, the experimental results reveal that, on the test set, the model exhibited outstanding performance, characterized by an RMSE as low as 0.0621, an MAE of 0.044, and an R\({}^{2}\) value reaching up to 0.927, which indicates that the model possesses minimal prediction error alongside high explanatory power, thereby validating its reliability and efficacy across different scenarios. Through this approach, a more precise understanding and prediction of various changing trends under future scenarios can be achieved.  
To comprehensively evaluate the performance of the prediction model, this study plotted the spatial distribution of the model's RMSE across China, as shown in Figure S7. The results indicate that while high RMSE values are predominantly concentrated in the eastern region, particularly the northeast, where denser data points and more pronounced environmental changes or human activities may have introduced higher errors during the  
Figure 4: VIP scores of NDVI changes influenced by different meteorological factors in China from 2001 to 2023: figures **(a–f)** represent the VIP scores of RH, SWR, SWVL1, T2m, TP, and CO\({}_{2}\), respectively, on NDVI changes.  
modeling of complex data patterns, the overall RMSE values across China remain relatively low, suggesting a high degree of regional adaptability of the models. In summary, our stacked models effectively and stably predict under various SSP scenarios, despite certain regional challenges. Nonetheless, these models exhibit outstanding predictive capability and broad applicability.
# Global Dynamics of a Predator-Prey System with Cooperative Hunting
## 5 Complete Description of the Dynamic Behaviors
### Global Dynamics of the Case \((\beta,c)\in\Lambda_{2}\)
#### 5.2.2 Scenario \((\beta,c)\in\Lambda_{2b-1}\cup\Lambda_{2b-2}\)  
We consider the global dynamics for the scenario \((\beta,c)\in\Lambda_{2b-1}\cup\Lambda_{2b-2}\). When \((\beta,c)\in\Lambda_{2b-1}\), i.e., \(\beta>1\) and \(f_{1}(\beta)<c<h(\beta)\), the Hopf bifurcation occurs at \(E_{2}^{*}\) for \(d=d^{*}\), where \(d^{*}=H(\beta,c)\) and \(d^{*}<c\) (see Theorem 5). When \((\beta,c)\in\Lambda_{2b-2}\), i.e., \(\beta>1\) and \(c=h(\beta)\), the Hopf bifurcation value \(d^{*}=c\). According to Theorem 3, \(E_{2}^{*}\) is a source for \(d<d^{*}\) and a sink for \(d\in(d^{*},F(x_{0}))\).  
**Theorem 11**.: _Let \((\beta,c)\in\Lambda_{2b-1}\cup\Lambda_{2b-2}\)._  
1. _If_ \((\beta,c)\in\Lambda_{2b-1}\)_, we can make the following statements:_ 1. _When_ \(d\in(0,d^{*})\)_, System (_3_) has a stable limit cycle (see Figure (a)a).__._  
_When \(d\in(d^{*},c]\), \(E_{2}^{*}(x_{2}^{*},y_{2}^{*})\) is globally asymptotically stable (see Figure 10c)._  
_If \((\beta,c)\in\Lambda_{2b-2}\) and \(d\in(0,c)\), System (3) has a stable limit cycle (see Figure 11a)._  
**Remark 5**.: _For the scenario \((\beta,c)\in\Lambda_{2b-1}\), Theorem 11 indicates that when the mortality of the predator is small (\(d\leq c\)), both species coexist (see Figure 10a-c). The coexistence exhibits two different forms: an oscillatory mode (when \(d\in(0,d^{*})\), see Figure 10a) and a steady mode (when \(d\in(d^{*},c)\); see Figure 10c). When \(d\) is large such that \(c<d<F(x_{0})\), through numerical simulations, System (3) has no limit cycle and there are two attractors \(E_{1}(0,1)\) and \(E_{2}^{*}\) (bistability). The separatrices of the attracting basins of \(E_{1}\) and \(E_{2}^{*}\) are the stable manifolds \(\Gamma_{1}^{s}\) and \(\Gamma_{2}^{s}\) of the saddle \(E_{1}^{*}\) (see Figure 10c). So, when \(c<d<F(x_{0})\), the coexistence of the two populations depends on the initial values. As \(d\) becomes larger (\(d>F(x_{0})\)), System (3) only has the attractor \(E_{1}\), the predator becomes extinct, and the prey survives (see Theorem 7 and Figure 6b).__For the scenario \((\beta,c)\in\Lambda_{2b-2}\), the Hopf bifurcation curve \(d=H(\beta,c)\) intersects the line \(d=c\) (see Figure 5b) so the Hopf bifurcation and the saddle-node bifurcation occur simultaneously at \(d^{*}=c\). In this scenario, the coexistence of two species exhibits only an oscillatory mode for \(d<c\) (see Figure 11a). When \(c<d<F(x_{0})\), (3) has no limit cycle, two attractors \(E_{1}\) and \(E_{2}^{*}\) (bistability) appear, and the coexistence of the two populations depends on the initial values (see Figure 11c)._
# A Novel Cloud Approach for Connected Vehicles
## 2 Related Works
### Information-Centric Networking
Additionally, the communication link is not necessarily bidirectional between two nodes (i.e., node X can be part of the neighborhood of node Y while X is not able to sense Y because they have different transmission ranges). The research on naming, routing, and security are highlighted as the first steps and the physical communication link (based on the broadcast) as the future research area [42; 46]. Our approach treats all four of these topics. ICN has been seen by some researchers as a substitute for IP architecture. For others, it is a complement to specific domains such as IOT. Concerning the internet of vehicles, none of the existing propositions take into account the current choices made in the deployment of the C-ITS in Europe or the nature of the communication, which is done over Wi-Fi with geographical routing. In [47], the authors conclude that it is necessary to bring modifications to the C-ITS if we want them to use ICN. However, with our approach, we succeeded in including ICN without modifying ITS standards.
# Design and Implementation of a Tether-Powered Hexacopter for Long Endurance Missions
## 2 Design and Analysis
### Ground Station  
The ground station contains three DC power supplies connected in series, a slip ring, a winch, a tether guider, wireless communicators, and a laptop computer which serves as a mission planner. This ground station can be powered by 220 Vac from the grid or a diesel generator.  
Two 750 W/48 V DC power supplies (RSP-750-48, Mean Well, Taiwan) and a 1500 W voltage adjustable DC power supply (KXN-3050D, Zhaoxin, China) are capable of providing maximum 15.7 A current and maximum 120 V DC voltage to the slip ring (M022A-06, Searing, China), which conducts electricity to the tether when the winch is rotating. The winch is controlled by a 100 W industrial AC servo motor (FRMS1020604D, Hiwin, Taiwan) under a constant torque mode to maintain a suitable tension of the tether. The torque reference is set according to the status of flight. The angular speed of the winch is limited under 200 rpm to protect the slip ring. A tether guider is installed in front of the winch to help tether accumulate uniformly on the spool. The winch controls are detailed in  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Reference** & **Rotors** & **Power Source** & \begin{tabular}{c} **Battery** \\ **Capacity** \\ **(mAh)** \\ \end{tabular} & \begin{tabular}{c} **Weight w/o** \\ **Battery (g)** \\ \end{tabular} & \
\begin{tabular}{c} **Altitude** \\ **(m)** \\ \end{tabular} &
\begin{tabular}{c} **Max** \\ **Endurance** \\ **(Min)** \\ \end{tabular} & **Remark** \\ \hline
[2] Wanze & 4 & 7.4 V Battery & 8000 & 119 & NA & 34 & \\
[2] Ninja & 4 & 11.1 V Battery & 2000 & 352 & NA & 15 & \\
[3] & 4 & 11.1 V Battery & 2200 & \(\sim\)359 & 1.5–2.5 & 17.8 & \\
[4] & 6 & 14.8 V Battery & 40,000 & 2000 & NA & 29.24 & \\
[6] & 4 & 11.1 V Battery & 2300 & \(\sim\)360 & NA & 19 & Releasing empty \\  & & & & & Battery only: & \\
[8] & 4 & \begin{tabular}{c} Battery \\ (voltage NA) \\ \end{tabular} & 2100 & 416 & 1–2.5 & \
\begin{tabular}{c} Battery only: \\ 14 \\ Battery + \\ magnet: 102 \\ \end{tabular} &
\begin{tabular}{c} Using magnets to \\ attach to the ceiling \\ \end{tabular} \\
[9] & 6 & 11.1 V Battery & 3471 & 3294 & NA & 36 & \\
[11] & 4 & 3.7 V Battery & 650 & 32 & NA & 31 & \\
[14] & 8 &
\begin{tabular}{c} 22.2 V Battery \\ + Fuel \\ \end{tabular} & 5200 & 19,600 & NA & 60 & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Performance of typical battery-powered UAVs.  
Appendix A. Telemetry data is received by a laptop and decoded by software \"Mission Planner\". The hexacopter is navigated manually through a radio transmitter.
## 3 Results
### Cell Cytotoxicity  
Cell metabolic activity of HepG2 and canine At-MSCs in response to LLP treatment was evaluated by MTT test. A statistically significant stimulatory effect was observed for both cell lines (\(p<0.01\) for HepG2; \(p<0.001\) for At-MSCs; Figure 1). With regards to HepG2, stimulation occurred at 100 \(\upmu\)g of LLP (\(p<0.01\)), while lower points were not different from control cultures. The 200 and 500 \(\upmu\)g LLP treatments induced a stronger effect with respect to 100 \(\upmu\)g, although no significant difference was observed between the treatments (Figure 1A). At the higher tested point (1000 \(\upmu\)g) a decrease in the effect was observed, suggesting that a plateau was reached at 500 \(\upmu\)g. A higher stimulation was observed on the At-MSCs (Figure 1B; \(p<0.001\)). The treatment with 200 \(\upmu\)g of LLP showed the stronger effect. Although no statistically significant difference was demonstrated between the treatments ranging from 100 ug to 1000 ug, a decreasing MTT signal was observed starting at 500 \(\upmu\)g, suggesting a tendency towards decrease in the stimulatory effect in response to higher LLP levels. No cytotoxic effects were observed on HepG2 and At-MSCs for the LLP concentration tested.  
The ability of LLP to maintain HepG2 metabolic activity was evaluated by MTT assay also in serum-free medium. A statistically significant increase (\(p<0.001\)) in MTT conversion was observed in the range of treatment between 200 \(\upmu\)g and 1000 \(\upmu\)g (Figure 2). Interestingly, in this range, the potency of LLP was not different in comparison to the supplementation of HepG2 cultures with 10% FBS.  
Figure 1: MTT assay on HepG2 and At-MSC cultures after LLP treatment (48 h). (**A**) HepG2: LLP treatment ranging from 100 \(\upmu\)g to 500 \(\upmu\)g/well increased the MTT signal with respect to the control (\(p<0.001\)). (**B**) At-MSCs: a statistically significant improvement of MTT conversion was observed at concentrations of LLP ranging from 100 \(\upmu\)g to 1000 \(\upmu\)g (\(p<0.001\)). Absence of a common letter means a statistically significant difference (\(p<0.001\)).
## 2 System Model
### Multisine Transmitted Signal  
The source node transmits an \(N_{t}\)-tone multisine signal \(s(t)\) with bandwidth \(B\). The tones are equally spread around center frequency \(f_{c}\) as \(f_{n}=f_{c}+\left(\frac{N_{t}-1}{2}+n-1\right)\frac{B}{N_{t}}\). The time-domain transmission signal \(s\left(t\right)\) is expressed as  
\[s\left(t\right)=\Re\left[\sum_{n=1}^{N_{t}}x_{n}e^{2\pi f_{n}t}\right]. \tag{1}\]  
with \(x_{n}(t)=a_{n}(t)e^{i\phi_{n}(t)}\) the \(n\)-th tone with amplitude \(a_{n}(t)\) and phase \(\phi_{n}(t)\). As we assume block fading to simplify the notations, we will neglect the time index \(t\) in all channel and symbol notations that are constant over a multisine signal in the remainder. In this work, we will mainly focus on multisine PSK modulation, by which each tone has equal amplitude and phase in one symbol.  
Figure 1: Multisine based simultaneous wireless information and power transfer (SWIPT) system overview.
# Congestion Control and Traffic Differentiation for Heterogeneous 6 TiSCH Networks in IIoT
## 1 Introduction
This paper presents a congestion control and service differentiation framework to support heterogeneous 6 TiSCH networks in IIoT applications. Principally, our proposed approach investigates two key research questions: first, how to achieve fair load distribution in imbalanced 6 TiSCH networks and achieve improved packet delivery performance in heavy traffic scenarios; second, how to guarantee prioritized and low delay transmissions of critical data over the non-critical in heterogeneous 6 TiSCH networks. To this end, the first question is addressed through a congestion detection and control mechanism, while the second question is addressed through a multi-queue model, both combined in the proposed congestion control and service differentiation framework to achieve load balancing and improved packet delivery for all types of traffic and enhanced delay performance for critical data. To the best of our knowledge, this is the first work to address congestion and traffic differentiation issues in heterogeneous 6 TiSCH networks. The key contributions of our proposed work can be summarized as follows  
* We introduce a congestion control approach to achieve load balancing and improve network performance in terms of packet delivery under heavy load conditions. In the proposed approach, a new joint routing metric is defined to select parent nodes considering queue occupancy along with the hop distance and link quality metrics. * To further support the functionality of the above strategy, we propose a Trickle timer reset strategy to detect overloaded nodes and to react to congestion in a timely fashion while maintaining minimum network overhead. * Moreover, we design a multi-queue model where each node uses three different queues corresponding to three traffic categories, which is the typical case in most IIoT scenarios. Each queue is given a transmission priority where packets from higher priority queues are transmitted first. In addition, we provide a stochastic mathematical model to formulate the average queue waiting time of the proposed multi-queue model. * We evaluate the performance of the proposed work through extensive discrete-time simulations and conduct performance comparisons with existing work to demonstrate its effectiveness. The results show that our proposed framework achieves improved packet delivery and low queue losses under heavy load scenarios, as well as improved real-time performance of critical traffic. The remainder of this paper is organized as follows. Section 2 discusses the problem statement and related work. The proposed congestion control method is introduced in Section 3. Section 4 presents the multi-queue model and its corresponding mathematical analysis. Performance evaluations are given in Section 5, followed by the conclusion and future work in Section 6.
## 1 Introduction
In this paper, we propose a new median filtering method based on the constraint of the linear Radon transform to separate four kinds of wavefields whether or not the events in the wavefields are parallel. We first use a new superposition algorithm of the linear Radon transform to make the energy spectrum in the \(\tau\)-\(p\) domain more focused than the traditional Radon transform so as to obtain the exact slowness value and variation of the slowness at different intercept times. Secondly, all the upgoing and downgoing P-waves and S-waves are aligned dynamically based on the variation characteristics of the wavefield slowness instead of just aligning the first arrivals in a routine VSP process. Lastly, we employ median filtering to separate four wavefields gradually according to the order of the energy spectrum from strong to weak.
# Characterization of a Novel Emaravirus Affecting Ash Species (_Fraximus_ spp.) in Europe
## 2 Materials and Methods
### Detection of the Novel Virus and Association with Disease Symptoms in Frazinus spp.  
Six specific primer pairs (Table 1) targeting the five genome segments of the novel virus discovered in diseased ash were designed using HTS sequence information from the original pooled sample (E55262 and E55268). The specificity of each segment-specific primer set was evaluated using total RNA extracted from symptomatic and asymptomatic _F. excelsior_ leaves and leaf material of four other deciduous tree species, known to be infected with putative emaraviruses: common oak ringspot-associated virus (CORaV)-infected _Quercus robur_[19; 20], maple mottle-associated virus (MaMaV)-infected _Acer pseudoplatanus_[21], fig mosaic virus (FMV)-infected _Ficus carica_[35] and aspen mosaic-associated virus (AsMaV)-infected _Populus tremula_[22].  
Following total RNA extraction, first strand cDNA synthesis was performed using random hexamer oligonucleotides. Two uL of the primer (50 uM) was added to 1 ug of RNA and topped up with to 12.5 uL with MilliQ-H\({}_{2}\)O. After 5 min of incubation at 70 \({}^{\circ}\)C and 5 min on ice, 4 uL of 5 \(\times\) RevAid buffer, 2 uL of dNTPs (10 mM each), 0.5 uL of RiboLock RNase Inhibitor (40 U/uL) and 1 uL of RevertAid Reverse Transcriptase (200 U/uL), (all Thermo Fisher Scientific, Waltham, MA, USA)) were added to the mixture. The mixture was incubated at 25 \({}^{\circ}\)C for 10 min followed by 60 min at 42 \({}^{\circ}\)C and 10 min at 70 \({}^{\circ}\)C. Quality of cDNA was checked using plant nad5-PCR, in line with [PERSON] et al. [36], as an internal control to avoid false negatives. A 25 uL PCR mixture for detection of the novel virus was prepared with: 18.5 uL of MilliQ-H\({}_{2}\)O, 1 uL of MgCl\({}_{2}\) (50 mM), 2.5 uLof 10\(\times\) PCR buffer (without MgCl2), 0.5 \(\upmu\)L of dNTPs (10 mM each), 0.25 \(\upmu\)L of both forward and reverse primers (50 mM), 0.125 units of DreamTaq polymerase (Thermo Fisher Scientific, Waltham, MA, USA) and 1 \(\upmu\)L of cDNA. PCR cycling conditions were as follows: initial denaturation at 94 \({}^{\circ}\)C for 2 min followed by 35 cycles of denaturation at 94 \({}^{\circ}\)C for 30 s, annealing at 55 \({}^{\circ}\)C for 30 s, elongation at 72 \({}^{\circ}\)C for 30 s and a final elongation at 72 \({}^{\circ}\)C for 2 min.  
Fifty-two _F. excelsior_ and 57 _F. ornus_ leaf samples, collected during the vegetation periods between 2016 and 2019, were investigated for the presence of the novel virus. Samples originated from urban locations in Germany, Northern Italy, Southern Sweden and Switzerland as listed in the Section 2.1. Suspected virus symptoms were documented and all samples were tested by RT-PCR, applying the virus segment-specific primer sets (Table 1). Twelve samples from both _F. excelsior_ and _F. ornus_ displayed no observable symptoms of virus infection.
## 3 Circulating Tumor Cells--Relevance to Skin Cancers  
### From Origin to Metastasis--CTCs as Key Players of the Process  
Although not a new concept, CTCs have returned to the attention of researchers in recent years as a result of the improvements in liquid biopsy techniques. Only recently, according to several studies, CTCs have become veritable biomarkers in a multitude of cancers [31; 32], either for the early detection of the malignancy, but more frequent for disease monitoring and therapeutic prognosis [33].  
CTCs constitute a very small fraction of cells detected in peripheral blood, compared to exceedingly higher numbers of white blood cells (WBCs) and red blood cells (RBCs). These are cancer cells, originating in the early phases of cancers from the primary tumor (even before metastatic lesions occur) and during the later stages also from metastatic lesions, circulating through the bloodstream to different target organs. In addition to the small number of CTCs in the sample (\(<\)10 cells/mL of blood), another aspect that makes the detection difficult is the short half-life of only 1-2.4 h [34]. Moreover, the high heterogeneity of CTCs is also well known; despite having the same tissue or tumor origin, two CTCs may have different molecular profiles and express different surface receptors (i.e., clusters of differentiation) [35]. Despite the abovementioned evident limitations, CTCs are the intermediate stages in metastasis [36], making them an interesting topic for oncologic research.  
The metastatic process, observable frequently in MM and also relevant for SCC, has a complex, multiple stage course, CTCs playing a major role. After the detachment from the primary tumor, CTCs are involved in the first step of intravasation, travelling with the blood flow to specific sites. Then, CTCs extravasate to bone marrow or other organs, finally disseminating and metastasizing locally (see Figure 1) [37].  
Summarizing the available literature, CTCs seem to be of interest in three different directions related to skin cancer patient management. First, CTCs were thought to help in the early detection of skin malignancies [38]; however, as a screening method, because of multiple detection and characterization limitations, there is further need for technique improvements. On the other hand, CTC's study was highly successful when performing treatment follow-ups. In this regard, the study conducted by [PERSON] et al. [39] showed the potential role of the RNA-based scoring of melanoma CTCs in providing relevant data for the early monitoring of response to specific targeted therapies. The prediction of malignant recurrence after tumor excision is an essential step in secondary prevention, with CTCs analysis gaining more ground in tumor dynamic follow-up, early assessment of therapeutic efficacy, risk of relapse [40], and real-time monitoring of the apparition of treatment resistance [41]. Lastly, CTCs might offer valuable insight related to skin cancer prognosis, with clinicians being able to make early assessments and correlations with tumor burden modifications [42].
# Cross-Entropy Method in Application to the SIRC Model
## 3 Description of the Numerical Results  
This section will present the results obtained using the cross-entropy method. For the correct comparison the same parameters for the SIRC model were used. These values are:  
\[\mu =\frac{1}{75}[\text{year}^{-1}],\quad\gamma=\frac{1}{2}[\text{year}^ {-1}],\quad\quad\alpha=\frac{365}{5}[\text{year}^{-1}],\] \[\delta =1[\text{year}^{-1}],\quad\quad\beta\approx 146[\text{year}^{-1}], \quad\sigma\approx 0.078.\]  
For optimization functions \(u(t)\) and \(v(t)\) the following restrictions have been applied:  
\[0\leq u(t)\leq 0.9,\,0\leq v(t)\leq 0.9.\]  
Restrictions were proposed by [PERSON] and [PERSON] (2007). Their value was explained by the fact that the whole group cannot be controlled. In addition, the weights used for functions have values \(\rho_{1}=2\) and \(\rho_{2}=2\)  
Now, all that's left is to propose variable values for the objective function:  
\[\alpha_{1}=10^{-3},\,\alpha_{2}=0.997,\,\tau_{1}=10^{-3},\,\tau_{2}=10^{-3}.\]  
The parameter values are adjusted using historical data like parameter mortality rate \(\mu\), which is counted as average lifetime of a host or parameters \(\alpha,\delta,\gamma\) mean the inverted time of belonging to the group \(I,R\) and \(C\). A detailed description of determining parameters along with their limitations is presented in the article by [PERSON] et al. (2019).
## 3 System Design and Implementation
### Hardware Design
#### 3.2.3 Interface Conversion Module  
The interface conversion module enables conversion between USART signals and RS485 differential signals, with automatic transmit/receive state switching. The USART to RS485 circuit (shown in Figure 8) employs the MAX485 chip as the converter, utilizing an NPN transistor to switch transmit/receive states. During data reception, TXD remains at a high level, turning the transistor on. This pulls the RE pin of the MAX485 to a low level (enabled), allowing the RO pin to output received RS485 bus data to the microcontroller. During transmission, TXD outputs a low level, turning the transistor off. The DE pin is then driven high to enable the transmit mode.