esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
In this research, we propose a low-cost navigation system that is based on a multi-epoch double-differenced pseudorange observations (MDPO) algorithm. MDPO requires that only two satellites be visible to locate a rover position, and unlike the conventional TOA or TDOA navigation algorithm, it also can deal with the bias of the satellite and user clocks at the same time. The numerical simulations for the considered mission scenarios demonstrated that the position error of the rover can be predicted theoretically by using the Total GDOP and receiver observation errors, with an expected exception that systematic errors induce additional user position error. It also demonstrated that the rover position can be determined within several tens of meters with a probability of 95% (2 drms) within a one-minute observation using two low lunar orbits and lunar DEM information.  
Conceptualization, T.T. and S.N.; methodology, T.T.; software, T.T.; validation, T.T., T.E., and S.N.; formal analysis, T.T.; investigation, T.T. and T.E.; resources, T.T.; data curation, T.T.; writing--original draft preparation, T.T.; writing--review and editing, T.T., T.E., and S.N.; visualization, T.T.; supervision, T.T., T.E. and S.N.; project administration, T.T. and S.N.; funding acquisition, N/A. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
[PERSON] (Nakasuka-Funase laboratory at the University of Tokyo) is kindly acknowledged for his technical support in satellite orbit simulation. [PERSON] (same) is kindly acknowledged for his technical advice in lunar GNSS systems.  
The authors declare no conflict of interest.
# A Hybrid User Mobility Prediction Approach for Handover Management in Mobile Networks
## 5 Experimental Results  
In this section, we carried out a series of simulations to investigate the impact of the proposed approach. Our main objective was to evaluate the performance of the proposed mobility model and to then analyze the impact of the prediction on HO-related costs. In the following, first, we describe the mobility data that we used for our experiments and the approaches with which we compared our method. Next, we provide the results regarding the mobility model performance and its effect on HO procedure optimization.
# Clustering Approach for Reliable Wireless Communication
## 5 Conclusions
In regard to the clustering design, although the \(k\)-medoids method allowed us to use a more accurate correlation metric, its performance improvement was still limited. This is because the main drawback of the clustering algorithm was not the distance metric used, but the disregard for the correlation between clusters when assigning the sequences to users. It was demonstrated that, for clustering conception, the \(k\)-medoids algorithm leads to acceptable and close results to the ones achieved with the \(k\)-means algorithm. An additional BER analysis implies the comparison of the Rayleigh and Rice fading effects across the performance of the system. Rice fading gives reasonable results because of its capacity to emulate line-of-sight (LoS) transmission. Furthermore, testing QPSK modulation schemes with BSs that have two or four antennas showed lower BER and clustering gains that are noticeable at lower SNR values. Without using a sequence allocation mechanism that evaluates the correlation between clusters, it was shown that using a higher correlation threshold to obtain a higher number of clusters can marginally improve the performance of the system. The clustering approach has the main benefit of having a low probability of allocating highly correlated (or the same) sequences to different users, but it is limited in its ability to ensure good correlation properties for MUSA codewords to minimize the probability of interference in a communication system. As a result, the BER performance can be enhanced. Future work will involve investigating the appropriate selection of clusters that ensures a low correlation between clusters used to assign sequences to various users. Additional validation scenarios will include different modulations and coding schemes and an analysis of other spreading codes used in CD-NOMA. C.F. and M.-G.B., conceptualization and writing--original draft; I-M.M., R.-F.T. and C.F., writing--review and editing; I-M.M., funding acquisition and supervision; C.F., M.-G.B. and R.-F.T., data curation; I-M.M., methodology; C.F., software; I-M.M. and M.-G.B., resources and investigation. All authors have read and agreed to the published version of the manuscript. This work was funded by a grant (no. 14/2022) from the Academy of Romanian Scientists, Ilfov 3, 050044 Bucharest, Romania, by the 2023-2026 Sectoral Plan for Research--Development of the Ministry of Agriculture and Rural Development--ADER 2026, project contract no. ADER 6.3.13/2023, \"Smart viticulture based on IoT--premise for climate change management techniques\". Authors would also like to thank Vodafone Innovation Hub from National University of Science and Technology Polytechnic Bucharest and Infovista, France, for their logistic support used in this research. Not applicable. The data that support the findings of this study are available from all corresponding authors upon reasonable request. The data are not publicly available due to privacy and ethical concerns. The authors declare no conflict of interest.
## Experimental Results
### Comparative Study of Ground-Level and Above-Ground Deployment  
As noted in Section 2, to our knowledge, none of the experimental results presented in the literature consider the case where nodes are deployed at ground level. For this evaluation, we conducted two sets of experiments. In the first set of experiments, six sensors were linearly deployed on the ground with a fixed distance of 3 m between them. In the second set of experiments, sensors were linearly deployed but, in this case, each sensor was deployed on a support of height 57 cm. In both experiments, channel 26 of the IEEE 802.15.4 standard was used by sensors for communication. However, note that Section 5.3 presents in detail the evaluation of the impact of the communication channel in a WSN with nodes deployed on the ground surface. Nodes were configured to use a transmission power of 0 dBm and an application payload of 82 bytes was added as user data for each packet transmitted in the network. As discussed in Section 5.2, we further evaluated the impact of the packet size on the link quality.  
Figure 5 presents the PRR and RSSI values on forward and backward links of pairs of nodes (1,2) and (3,4) as a function of time, when nodes were deployed at ground level and at height. From node 1's point of view, related to node 2, the forward link is the link \(1\to 2\) and the backward link is the link \(1\gets 2\). We considered nodes located at different position in the network, but with the same separation distance of 3 m. This allowed analyzing and comparing not only the temporal properties of the links in the two deployments, but also some spatial properties.  
Figure 5: Variation of PRR and RSSI values over time on wireless links 1–2 and 3–4, with the same distance of 3 m, in two different deployments: one with sensors deployed at ground level (labeled “Ground”) and another with sensors deployed on a support of height 57 cm (labeled “Height”).
## 4 Experiment and Results
### Results  
The efficiency of 3D reconstruction and the quality of the model are critical for damage assessment of buildings after an earthquake and also take into account the hardware requirements for implementing the work. On the basis of the above experiments, we quantitatively analyzed and compared the results of three indicators of statistical time consumption, video memory consumption, and visual modelling of different methods. For  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Reinforced Concrete** & **Masony Buildings** & **3D Model** & **Classification of Damage** \\ \hline \hline
**Grade0: Negligible to slight damage** & **(no structural damage, slight non-structural damage)** \\ \hline
**Grade1: Moderate damage** & **(slight structural damage, moderate non-structural damage)** \\ \hline
**Grade2: Substantial to heavy damage** & **(moderate structural damage, heavy non-structural damage)** \\ \hline
**Grade3: Very heavy damage** & **(heavy structural damage, very heavy non-structural damage)** \\ \hline
**Grade4: Destruction** & **(very heavy structural damage)** \\ \hline \hline \end{tabular}
\end{table}
Table 1: Detailed description of buildings with different damage level.  
AA-RMVSNet and \(D^{2}\)HC-MVSNet, _numdepth_ was set to 192 and _interval_scale_ was set to 1.06.
## 3 Suspension Design and Modelling
### Modelling of the Hydroneumatic Suspension
#### 3.2.3 Model of Damping Pipe  
The damping force of the suspension system is mainly derived from the pressure loss generated by sudden changes in the flow cross-section. The pressure loss between the hydraulic chamber and the oil tank is composed of the partial pressure loss and the pressure loss along the pipe.  
Hydraulic chamber pressure \(P_{2}\) can be expressed as:  
\[P_{2}=\rho\bigg{(}\frac{Q}{A_{c}}\bigg{)}^{2}\{\xi_{1}[0.5+0.5\,\text{sign}(v )]-\xi_{2}[0.5-0.5\,\text{sign}(v)]\}+\lambda\frac{l}{d}\frac{\rho V_{c}^{2}}{2 }\,\text{sign}(v) \tag{4}\]  
\[Q=A_{2}v \tag{5}\]  
\[V_{c}=\frac{Q}{A_{c}}=\frac{A_{2}v}{A_{c}} \tag{6}\]  
where \(\rho\) and \(V_{c}\) are the density and flow velocity of the oil, \(Q\) is the flow rate, \(A_{c}\) is the sectional area of damping pipe, \(\xi_{1}\) and \(\xi_{2}\) are the pressure distribution coefficient of oil outflow and inflow, \(l\) and \(d\) are the length and diameter of damping pipe, \(v\) is the velocity of the piston relative to the cylinder.  
\(\lambda\) is the flow restriction coefficient along the pipe:  
\[\lambda=\left\{\begin{array}{ll}\frac{80}{Re},&Re<2000\\ \frac{0.3164}{Re^{d.25}},&2000\leq Re\leq 10^{5}\end{array}\right. \tag{7}\]  
the Reynolds number is defined as:  
\[Re=\rho\frac{V_{c}d}{\mu} \tag{8}\]and the sign function is given as:  
\[\text{sign}(v)=\left\{\begin{array}{ll}1,&v>0\\ 0,&v=0\\ -1,&v<0\end{array}\right. \tag{9}\]  
where \(\mu\) is the oil kinematic viscosity. The associated initial values of hydropneumatic variables are listed in Table 1.
# Integrated Photonics for IoT, RoF, and Distributed Fog-Cloud Computing: A Comprehensive Review
## 3 Radio-over-Fiber (RoF) for IoT and Fog Computing
RoF can be used for vehicular, mobile, and broadband wireless computer communications, and the network infrastructure can be used for fiber transport to the building and the home services.
# Will the Use of Pharmacogenetics Improve Treatment Efficiency in COVID-19?
## 7 Atazanavir (ATV)  
Atazanavir is an established protease inhibitor used for the treatment of AIDS, with good oral bioavailability, efficacy, and safety profiles [3; 10]. Usually, this drug is administered in combination with ritonavir or other antiviral drugs in highly active antiretroviral therapy despite the fact that concomitant use with ritonavir reduces the efficacy of atazanavir [25; 96]. When compared to other protease inhibitors, atazanavir is less expected to cause lipodystrophy [10]. The results of in vitro and ex silico studies have suggestedthat atazanaavir can mediate SARS-CoV-2 major protease inhibition [25; 97; 98]. Atazanaavir repressed SARS-CoV2 replication in human epithelial pulmonary cells (A549) [3]. This drug has been found to be metabolized by CYP3A and act as an inhibitor of CYP3A and UGT1A. The results of pharmacogenetic studies carried out on HIV patients suggest the impact of polymorphisms within _UGT1A1_, _CYP3A4_, _CYP3A5_, and _SLC03A1_ genes on the efficacy of atazanaavir [10]. The Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline concerning this drug mentions several polymorphisms in _UGT1A1_, such as a variable dinucleotide (TA) repeat within the gene promoter region (rs8175347, alleles _UGT1A1*28_, *36 and *37) and the SNPs rs4148323 (_UGT1A1*6_) and rs887829 (_UGT1A1*80_) [3; 99]. Carriers of TA repeats within the _UGT1A1_ gene promoter region can be normal metabolizers (NMs), intermediate metabolizers (IMs), or poor metabolizers (PMs). Individuals with one or two copies of the *1 allele may metabolize atazanaavir more quickly than individuals with one or more copies of the *3, *6, or *7 alleles [10; 10]. Variants within _UGT1A1_, _UGT1A7_, _UGT1A3_, _APOE_, and _APOC3_ genes have been suggested to be also associated with toxicity and ADRs [50; 101; 102]. Individuals carrying two alleles with decreased function (PMs) were found to be more likely to develop jaundice. In such patients, alternative therapy should be considered as side effects may cause nonadherence [25; 99]. Moreover, homozygous carriers of the _UGT1A1*28_ allele appear to be predisposed to severe hyperbilirubinemia [103]; this risk is intermediate in _UGT1A1*28_ heterozygotes [104]. For carriers of _UGT1A1*28/*28_, *28/*37, *37/*37, and -364 TT, the CPIC guidelines recommend counseling on the possibility of developing hyperbilirubinemia before the initiation of the therapy [99]. _UGT1A1_ genotyping performed in COVID-19 patients who are treated with atazanaavir could improve therapy tolerability [3]. Atazanavir is also metabolized (to a lesser extent) by the P-gp efflux pump encoded by the multidrug resistance 1 (_MDRI_) gene. Homozygotic carriers of rs1045642 CC alleles, which appear to raise plasma levels of this drug, are at increased risk of hyperbilirubinemia and severe jaundice. Finally, _ABCA1_ (rs542671182), _APOC3_ (rs2070668, rs2854116, rs2854117), _APOA5_ (rs 662799 and rs3135506), and _APOE_ (\(\epsilon 2\) and \(\epsilon 3\) haplotypes) gene polymorphisms increase the risk of dyslipidaemia [105].
# Geographic Routing Decision Method for Flying Ad Hoc Networks Based on Mobile Prediction
## 2 Related Work
### Reactive Routing  
Reactive routing is an on-demand routing mechanism where nodes do not actively maintain routing information but instead discover paths through flooding control messages when data transmission is needed, thereby saving computational resources and communication traffic. The advantage of this method is that it reduces network overhead, but it also brings higher route discovery latency.  
AODV (Ad hoc on-demand distance vector) [18] is a classic representative of reactive routing protocols. It discovers neighboring nodes by sending Hello packets in fixed time slots, but when communicating with the target node, it must perform a route discovery process to find a path. To improve the efficiency of route discovery and reduce latency, [PERSON] et al. proposed a method called DOA (DSR over AODV) [19] that combines AODV and DSR (dynamic source routing). This method uses AODV for reactive routing within clusters and DSR for maintaining a complete routing table between clusters. This scheme combines the advantages of two protocols, but still has certain limitations in complex network environments.  
Most reactive routing protocols do not fully consider the issues of multi-path selection and optimal path selection. To this end, [PERSON] et al. [20] proposed the AO-AODDV (arithmetic optimization ad hoc on-demand multi-path distance vector ) protocol, which enhances the effectiveness of multi-path routing protocols through arithmetic optimization to reduce latency during data transmission. However, the protocol still faces high latency in route discovery and poor link stability in high dynamic environments. To further improve the quality of path selection, [PERSON] et al. [21] proposed the Enhanced-Ant-AODV protocol, which uses the ant colony algorithm to comprehensively consider factors such as node reliability, congestion, hop count, and remaining energy to optimize routing selection and improve service quality. However, in high dynamic scenarios, the fixed Hello packet mechanism still struggles to adapt to rapidly changing network environments. In addition, routing protocols based on natural heuristic algorithms have slow convergence speeds and face issues such as increased latency, high communication overhead, and energy consumption.  
Unbalanced energy consumption may lead to the failure of routing paths, thereby shortening network stability. The ECaD (energy-efficient connected aware data transmission) scheme [10] attempts to reduce energy consumption by prioritizing the selection of high-energy nodes for route discovery. [PERSON] et al. [22] introduced the Q-learning algorithm EAQ-AODV (energy-aware Q-learning ad hoc on-demand distance vector), which selects cluster head nodes through a reward mechanism and dynamically adjusts routing strategies based on environmental changes and historical experience to optimize the routing process and reduce energy consumption.
## 4 Numerical Calculation of Slopes Based on Weibull Parameter Random Distribution Model
### Slope Stabilization Measures
#### 4.4.1 Research on Slope Stability Based on the Theory of Singular Point Mutation  
As shown in Figure 13a-c, the fourth-order polynomial fitting results for the dissipated energy, plastic zone, and displacement variation curves under the support effect are presented. These figures illustrate the changes in dissipated energy during the excavation of the slope. As excavation progresses, the dissipated energy between 1195 m and 1240 m gradually increases. When excavation reaches the pit bottom, the maximum dissipated energy value reaches 540,650 MJ/m\({}^{3}\). The plastic zone volume at this stage is 103,022 m\({}^{3}\), and the displacement is 12 cm. As shown in Table 6, the analysis indicates that due to the support effect, dissipated energy in the lower part of the excavation significantly decreases. The results in Table 6 show that the bifurcation eigenvalues for dissipated energy, displacement, and plastic zone volume are all \(\Delta>0\). Based on the strength reduction method, the safety factor of the slope is calculated to be 1.31, indicating that under supported conditions, the safety factor of the slope is significantly improved, and the slope remains stable.  
Figure 12: Slope support model diagram. (**a**) Anchor cable frame beam plane schematic diagram; (**b**) anchor cable frame beam cross-sectional schematic diagram; (**c**) support schematic diagram.
## 2 Materials and Methods
### Procedure
#### 2.3.3 fNIRS Measurement  
Converging evidence from neuroimaging in children, neuropsychological patients, and healthy adults indicates a supportive role of the left lateral prefrontal cortex (LPFC) in executive-control conditions on tasks in the memory and language domains [28; 29; 30; 31; 32; 33; 34]. The left lateral prefrontal cortex (LPFC) hemodynamic response was measured using a wearable and continuous-wave single-channel functional near-infrared spectroscopy (fNIRS; probe size: \(58\times 28\times 6\) mm; PortaLite, Artinis Medical System, The Netherlands).  
The PortaLite device constantly emits light at 760 and 850 nm wavelengths between a transmitter and three aligned receivers (three independent channels), placed at 30, 35, and 40 mm from the transmitter. The measure of light attenuation is used to calculate the concentration changes in cortical oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) at the two wavelengths, allowing for theoretical penetration distances from 1.5 to 2 cm [35]. Light penetrates deeper for farther distances between the source and the detector. The sampling frequency of the system was 50 Hz. The PortaLite device is suitable for children [30].  
In the current study, the transmitter and the three light sources were laterally attached to the left forehead and were tightly fixed in a customized headband, see Figure 2. The detection optode was positioned above the supra orbital ridge of the children's left side [36]. The spatial position of Fp1 was marked by a 64-electrode electroencephalogram cap which is suitable and standard to preschool children, and the probe was positioned over the participant's prefrontal cortex at Fp1 according to the International 10-20 system of electrode placement [37]. The optode had a slightly twisted joint in the middle, and therefore, it was adjustable to the curvature of the forehead. It was attached to the skin by double-sided tape to hold it firmly. The optode was wrapped with a dark opaque medical bandage to prevent signal contamination by ambient light.  
Figure 1: The flow path of the 1-back task. The subjects were required to judge whether the position of the current square was the same as that of the square presented before.
###### Abstract
This problem holds significant application value in wireless sensor networks and other communication networks, especially in constructing virtual backbone networks. For heuristic algorithms, [PERSON] et al. [11] proposed a greedy starting point-based ACO algorithm and improved its global optimization capability in solving MCDSP through pheromone correction strategies and dynamic initialization strategies. [PERSON] et al. [12] introduced a greedy adaptive search algorithm to solve the MCDSP while employing tabu strategies to reduce cycling phenomena in local search. [PERSON] et al. [13] proposed a variable-depth neighborhood search algorithm that effectively solves the MCDS problem by combining efficient neighborhood structures, tabu search, incremental evaluation methods, and search pruning strategies, demonstrating good solution quality and computational efficiency. [PERSON] et al. [14] proposed a greedy algorithm to solve the MCDS problem, employing a grid-checking strategy in the local search phase to help reduce the cycling problem while using a vertex adaptation mechanism to help the algorithm escape the local optimum. However, there are relatively few heuristic algorithms designed to tackle the MCDS problem. Therefore, we introduce a local search algorithm to address this problem. Firstly, we propose three simplification rules to reduce the original graph, which effectively decrease the search space for our algorithm. Subsequently, we adopt a greedy strategy to construct an initial solution. Furthermore, we propose a method based on a two-level configuration checking strategy and a tabu strategy to avoid cycling problems. Additionally, a perturbation strategy and vertex weighting strategy are introduced to help the algorithm effectively escape the local optimum when encountered. Finally, we integrate the two-level configuration checking strategies, tabu strategy and perturbation strategy, as well as two scoring functions, _Cscore_ and _Mscore_, to propose two effective vertex selection rules and a novel algorithm. Experimental results demonstrate that, compared to renowned algorithms such as the ant colony optimization algorithm (ACO) [11], the ant colony optimization algorithm with pheromone correction strategy (ACO + PCS) [11], the greedy randomized adaptive search procedure (GRASP) [12], the variable-depth neighborhood search algorithm (VDNS) [13], and the multi-start local search algorithm (MSLS) [14], the local search algorithm we proposed achieves superior results. The remainder of this paper is structured as follows: Section 2 introduces relevant concepts; Section 3 provides a detailed description of the framework of the proposed algorithm and the specifics of the related strategies; Section 4 presents a comparative analysis of the experimental results of the algorithm proposed in this paper against other algorithms on two sets of instances; Section 5 offers a discussion and analysis of the experimental part; and finally, Section 6 concludes the paper.