esa-sceva/satcom-chunk-collection huggingface dataset:
# Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks
## 2 The Papers in this Special Issue
The authors extensively review these solutions and discuss open research directions in the field, such as hybrid optimization algorithms for topology management in cluster-based MANETs and the design of cooperative MAC protocols. From another perspective, existing routing protocols for VANETs often use several metrics to select the best route in a VANET. Such metrics are speed, position, distance, density, and link stability. In the fifth paper [7], the authors present an analysis of those routing protocols which are based on multiple metrics. The authors describe the most often-used metrics in various routing schemes for VANETs and their application scenarios. Their survey employs a systematic literature review methodology that allows them to study the existing high-tech routing schemes for VANETs. In their survey, the authors also confirm that speed and distance are the most accepted and flexible metrics. Many research challenges have yet to be addressed by the community. For example, it is vital to invent and test new mathematical models [8] for the flooding techniques applied to famous power-efficient routing protocols for MANETs and VANETs. This direction may assist the research community in introducing novel energy-aware flooding methods in ad-hoc networks. To conclude, we hope the reader will find this Special Issue useful for future research activities in MANETs and VANETs, as well in emerging paradigms related to these topics. **Acknowledgments:** We would like to thank all researchers who submitted articles to this special issue. We are also grateful to all reviewers who helped in the evaluation of the manuscripts and made very valuable suggestions to improve the quality of contributions. We would like to acknowledge the editorial board of Electronics, who invited us to guest edit this special issue. We are also grateful to the Electronics Editorial Office staff who worked thoroughly to maintain the rigorous peer-review schedule and timely publication.
# Navigating the Maps: Euclidean vs. Road Network Distances in Spatial Queries
###### Abstract  
Using spatial data in mobile applications has grown significantly, thereby empowering users to explore locations, navigate unfamiliar areas, find transportation routes, employ geomarketing strategies, and model environmental factors. Spatial databases are pivotal in efficiently storing, retrieving, and manipulating spatial data to fulfill users' needs. Two fundamental spatial query types, k-nearest neighbors (kNN) and range search, enable users to access specific points of interest (POIs) based on their location, which are measured by actual road distance. However, retrieving the nearest POIs using actual road distance can be computationally intensive due to the need to find the shortest distance. Using straight-line measurements could expedite the process but might compromise accuracy. Consequently, this study aims to evaluate the accuracy of the Euclidean distance method in POIs retrieval by comparing it with the road network distance method. The primary focus is determining whether the trade-off between computational time and accuracy is justified, thus employing the Open Source Routing Machine (OSRM) for distance extraction. The assessment encompasses diverse scenarios and analyses factors influencing the accuracy of the Euclidean distance method. The methodology employs a quantitative approach, thereby categorizing query points based on density and analyzing them using kNN and range query methods. Accuracy in the Euclidean distance method is evaluated against the road network distance method. The results demonstrate peak accuracy for kNN queries at \(k=1\), thus exceeding 85% across classes but declining as k increases. Range queries show varied accuracy based on POI density, with higher-density classes exhibiting earlier accuracy increases. Notably, datasets with fewer POIs exhibit unexpectedly higher accuracy, thereby providing valuable insights into spatial query processing.  
Keywords:spatial query processing; open street map (OSM); map navigation; GIS; spatial data; location processing; point of interest (POI) +
Footnote †: journal: _Algorithms_
# Investigating the Performance of Red and Far-Red SIF for Monitoring GPP of Alpine Meadow Ecosystems
## 3 Results
### Response of SIF and GPP to Environmental Factors
For \(\text{SIF}_{\text{Red}}\) and GPP, the slope of the linear fitted is approximately 1.6 times higher under cloudy weather than those under sunny weather, while for \(\text{SIF}_{\text{Far-red}}\) and GPP, it is approximately 2.5 times higher. Figure 4: Boxplots show the variation of values of \(\text{SIF}_{\text{Red}}\)/GPP and \(\text{SIF}_{\text{Far-red}}\)/GPP at different levels of environmental factors including (**a,b**) photosynthetically active radiation (PAR), (**c,d**) air temperature (Ta), and (**e,f**) vapor pressure deficit (VPD) at AR site during the 2019 (**left**) and 2020 (**right**) growing seasons with half-hourly averaged data. Red plus signs in the figure represent outliers. Figure 5: Scatter plot of the fitted relationship between (**a**) SIF\({}_{\text{Red}}\), (**b**) SIF\({}_{\text{Far-red}}\), and GPP at the diurnal scale and daily variations of (**c**) air temperature (Ta), (**d**) vapor pressure deficit (VPD), and (**e**) photosynthetically active radiation (PAR) for DOY220 and DOY227 in 2020 at AR site. The scatter points represent half-hourly averaged data, the solid line represents the fitted line of the SIF-GPP relationship, and the shaded area indicates the 95% confidence level of the prediction, where red represents DOY227, and blue represents DOY220.
# Interactions in Augmented and Mixed Reality: An Overview
## 3 Research Results
### Visual-Based Modality
#### 3.1.2 Surface-Based  
_Surface detection_ is an interaction method of the surface-based interaction context in which the geometry, position, or rotation of a surface is considered in the interaction. Telepresence, the experience of distant worlds from vantage points [92], is a field where surface detection interactions can be applied to create realistic representations of the remote world to surpass the virtual-real occlusion problem. This method is commonly based on algorithms that provide solutions in the simultaneous localization and mapping (SLAM) [93] computation problem where both the point of view of an unknown environment and the user's position in it are updated and need to be tracked [94]. It is also used in marketing applications that exploit the advantages of immersive environments, such as the IKEA app [95]. In [96], the authors state that one of the well-designed features such applications should contain, among others, is \"match between system and the real world\", which refers to scaling and positioning virtual objects in the real world properly. In engineering, a frequently used method used for interactions is the _surface analysis_ method. This method is somewhat more sophisticated than _surface detection_. It is used to analyze geometries and predict user intention of assembling different compartments [97] or interact with flexible clay landscapes to create new terrain models with _surface refinement_[98]. _Surface refinement_, another interaction method of the surface-based context, describes the techniques that alter the geometry or the material of a natural surface. [PERSON] et al. demonstrated SoftAR [99], an application capable of visually manipulating the haptic softness perception. The authors proposed that by virtually exaggerating the deformation effect of a material, it is possible to alter the haptic perception of the object's softness. Such interactions also have applications in realistic representations of mixed reality environments, such as a virtual object projecting shadow onto a natural surface or a virtual light source to illuminate an actual surface [100]. In [101], the authors present the interaction model and the techniques that lead to a successful application of instant indirect illumination for dynamic mixed reality scenes. For the placement of the 3D models in the MR environment, they used marker-based interactions.
# Computer Simulations of Dual-Antenna Microwave Ablation and Comparison to Experimental Measurements
## 4 Discussion
The nonlinear relationships between the dual-antenna electric field and the single-antenna electric field are complicated and need to be further investigated. In addition, the effects of blood perfusion on the ablation results cannot be ignored. The liver itself is a blood-rich organ [32] and is distributed with many small and large vessels. The cooling effects of large vessels [23; 45], the coagulation of small vessels [46], and the perfusion of liver blood flow all have an impact on the simulation results of the coagulation zone sizes. However, most simulations are  
Figure 8: Electric field (\(E_{\text{rms}}\)) and temperature distribution diagram in dual-antenna MWA. Figure 7: Single-antenna electric field (\(E_{\text{rms}}\)) distribution diagram. conditions. The MWA temperature may be lowered to some extent due to blood perfusion. The temperature difference was close to 30 \({}^{\circ}\)C under blood perfusion levels of 3.0 kg/(m\({}^{3}\cdot\)s) and 8.0 kg/(m\({}^{3}\cdot\)s) [38; 39]. Therefore, if the results of the ex vivo experiments are used to assess the in vivo MWA condition, this will inevitably lead to a larger coagulation zone than the actual result. There are still some shortcomings in this study. First, during the ex vivo experiments, the tissue will shrink and deform as the porcine liver is heated. Deformation can cause parallel dual-antenna deflections in the range of 1 to 3 mm. [PERSON] et al. [17] investigated the effect of this offset on the coagulation zone, but in general, an offset of 1 to 3 mm did not significantly affect the results. Second, some pig livers without large blood vessels were selected for MWA to facilitate experimental validation. However, the existence of large blood vessels will lead to the heat-sink effect, thus affecting the actual coagulation zone. Third, the ex vivo experiments were performed at a room temperature of 20 \({}^{\circ}\)C, which differs from the average human body normal temperature of 37 \({}^{\circ}\)C. The simulated results can provide a valuable reference for medical doctors, but do not fully reflect the actual in vivo situation. Furthermore, the spacing variation between two antennas can produce a specific coupling effect in the near field. How this coupling effect will affect the coagulation zone and temperature distribution still needs further study. Although only one specific MWA applicator model is involved, this study can be extended to other applicators by changing the FEM model.
## 2 Materials and Methods
### Extraction and Analyses of PhACs and Other Parameters  
All influent, effluent, and river water samples were extracted using solid-phase extraction with Oasis HLB cartridges (200 mg, 6 cc; Waters Corporation, Manchester, UK) according to the extractions method previously described in [PERSON] et al. (2016), [PERSON] et al. (2016), nd [PERSON] et al. (2018). Before extraction, the samples were spiked with 100 \(\upmu\)L of IS mixture containing 1 ng \(\upmu\)L\({}^{-1}\) diclofenac \({}^{13}\)C\({}_{6}\), hydrochlorothiazzide \({}^{13}\)C\({}_{6}\), carbamazepine \({}^{13}\)C\({}^{15}\)N, and ibuprofen-d\({}_{3}\).  
The mass of the target PhACs, antibiotics, and caffeine compounds was determined using high-performance liquid chromatography coupled with mass spectrophotometry (HPLC-MS/MS). All analyses were carried out at the Swedish Environmental Institute (IVL) laboratories using a binary Shimadzu AD20 UFLC HPLC system with automatic sample changer and column furnace coupled to an ABSciex API-4000 mass spectrometer. Samples were analysed under positive and negative electrospray ionization (ESI) mode using a Waters XBridge BEH C18 column (100 mm \(\times\) 2.1 mm with 3 \(\upmu\)m opening size). The eluents used in the mobile phase were A: 10 mM acetic acid in deionized water and B: methanol. The gradient used was a linear gradient from 0-90% methanol for 17 min, with a final plateau at 90% methanol for 4 min before a rapid return to 100% A and a final recovery and equalization of 2 min. The concentration of each analyte was quantified using an eight-point calibration curve (0, 5, 10, 20, 50, 100, 200, and 500 ng).  
Besides the target PhACs, antibiotics, and caffeine, the river water, influent and effluent samples were analysed for pH, chemical oxygen demand (COD), electrical conductivity (EC), total suspended solids (TSS), and total solids (TS). All analyses of liquid samples were performed according to Standard Methods for Examination of Water and Wastewater APHA (2016), using the following protocols: pH (4500-H and B), biochemical oxygen demand (BOD5; 5210-B), TSS, and TS (2540-B-D). The pH was measured by an electrode that measures the concentration of H ion by millivolts. The Chemical Oxygen Demand was measured by oxidizing the water sample by oxidizing agent (potassium dichromate) followed by open reflux digestion at 1500 \({}^{\circ}\)C for 2 h, then back titration for the remaining dichromate using sodium thiosulfate. The electrical conductivity of water was measured using a conductivity cell immersed in a 50 mL sample. Total solid was measured by gravimetric method, through drying the sample in an oven at 105 \({}^{\circ}\)C overnight until the crucible has a constant weight. Then, the difference in weights showed the total solids that exist in a sample (summation of total dissolved solids and total suspended solids). Total suspended solid was also measured by gravimetric method, by weighing the washed dried filter paper, then filtering the sample and drying it in an oven at 105 \({}^{\circ}\)C, the difference showing the concentration of suspended solids.
# Active Noise Control over Space: A Subspace Method for Performance Analysis
## 5 Simulation Results
### Comparison of the Effect of Different Loudspeaker Placements  
Since the loudspeaker placements effect the numbers of principal components in the subspace method, we investigate the noise reduction performance and energy of driving signals under different loudspeaker configurations. The ANC systems with two configurations are shown in Figure 5. In case 4, loudspeakers in the x-y plane have symmetric geometry with respect to the control region, so that the spatial correlation between loudspeakers is greater than that in case 3 (non-symmetry).  
Figures 8 and 9 demonstrate the noise reduction and the energy of the loudspeaker driving signals for each noise source positions. For both loudspeaker configurations, compared with the WDLS method, the proposed subspace method achieves less noise reduction and less total energy on the loudspeakers. The significantly reduced energy of the driving signals can avoid the overloading of the secondary sources and avoid the sound amplification outside the control area. In case 3, the correlation between different loudspeakers is higher than that in case 4. In case 4, the number of principal components is larger than that in case 3. Therefore, compared with Figures 8a and 9a, in Figures 8b and 9b, there are less difference between the subspace method and the WDLS method.  
of the microphone recordings are low, there are less difference between the subspace method and the WDLS method, in terms of noise reduction over the control region and energy of the loudspeakers.  
Figure 8: Noise reduction over the region using different loudspeaker setups, when the noise field generated by one primary source moving around the sphere using different methods: (**a**) case 3; (**b**) case 4.
# A Random Sampling-Based Method via Gaussian Process for Motion Planning in Dynamic Environments
## 1 Introduction
However, for local motion re-planning that has to perform efficient online planning, it is difficult for the methods based on random node sampling to balance planning efficiency and quality. This paper presents a new sampling-based method for local motion re-planning, namely, dynamic Gaussian local planner (DGLP), to fast search for high-quality smooth local paths in dynamic environments. Different from the traditional methods based on random node sampling, the DGLP utilizes our Gaussian random path sampling (GRPS) method to define a probability distribution over random paths and samples finite random paths represented by sparse nodes to improve the planning efficiency of high-quality paths. The high-quality collision-free local paths, replacing invalid partial paths, can be selected quickly using the lazy collision detection technique from the sampling paths. We also provide the path end orientation constraint (PEOC) method for smoothly merging the local re-planning paths into global paths. The paper evaluates the performance of the DGLP in simulations and experiments and the results show that the proposed method, DGLP, can perform re-planning local high-quality paths efficiently. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Planning Space** & **Method** & **Advantages** & **Disadvantages** \\ \hline \multirow{4}{*}{Statics} & Sampling-based methods with & They find multiple feasible paths. & They do not return solutions until all \\  & anytime technology & & the allowed time runs out \\  & PRM-based methods & They plan online efficiently. & They rebuild roadmaps offline if the \\  & RRT-based methods & They are very flexible and & environment changes. \\  & & can directly run online. & Planning path quality is not stable. \\ \hline \multirow{3}{*}{Dynamics} & RRT-based methods & They are very flexible and & Planning path quality is not stable. \\  & AO methods without & & Planning efficiency needs \\  & anytime technology & They plan high-quality paths online. & to be improved. \\ \hline \hline \end{tabular}
\end{table} 
Table 1: A summary of sampling-based methods. Note that the proposed method does not consider task constraints (e.g., an end effector maintains contact with a plane), and the DGLP samples only in a C-space, not in an implicit space which is a subset of a C-space and consists of all configurations satisfying the constraint. Our contribution can be summarized as follows. 1. This paper presents a sampling-based local re-planning method, namely, DGLP, which can fast converge to high-quality solutions in dynamic environments. 2. We provide the GRPS and PEOC methods to generate candidates for high-quality local paths and smoothly merge local paths into global paths, respectively. 3. The paper evaluates the performance of DGLP via simulations and experiments. The paper is organized as follows. Section 2 proposes the DGLP, including the GRPS and PEOC methods. The results and discussion of the experiments are given in Section 3. Section 4 concludes the paper and presents prospects for future work.
## 4 Conclusions  
This work analyzed acoustic emission (AE) data from a damage test performed on a cubic concrete specimen. The damage development within the structure was studied in terms of two AE-based analysis methods: \(b\)-value and natural time. These techniques were applied to three different data sets: two from the experimental test, registered independently with different acquisition systems, and one from simulating the same test using a version of the lattice discrete element method (LDEM). It was possible to conclude that:  
Figure 14: Natural time analysis versus the normalized time for AE activity registered in the LDEM.  
Figure 13: AE activity registered during the simulations: **(a)** using the increment of kinetic energy, \(\Delta E_{k}\), **(b)** with a virtual acoustic emission sensor. **(c)** Details of two typical signals for the approaches (**a**,**b**).  
* The differences in data sets due to each acquisition apparatus have significant effects on the conclusions from AE analysis methods, such as the b-value. The main reason for this likely lies in the amplitude-frequency relationship in the emission of acoustic signals, as small-amplitude events tend to generate higher-frequency waves. This hypothesis will be addressed in further detail in future work.
* The evolution of natural time global parameters was not significantly affected by the differences in the data sets from either acquisition system, indicating a critical region in normalized time at around 0.85 for both cases. Such results were also coherent with the LDEM model's simulation, not only in failure time but also in global strength and final rupture configuration.  
Conceptualization, L.F.F., A.B.C., I.I., G.N. and G.L.; Methodology, L.F.F., B.N.R.T., I.I. and G.L.; Formal analysis, L.F.F., B.N.R.T., I.I.; Investigation, L.F.F., A.B.C. and B.N.R.T.; Writing--original draft preparation, L.F.F., A.B.C., I.I. and M.S.; Writing--review and editing, L.F.F., B.N.R.T., I.I., G.L., G.N. and M.S.; Visualization, L.F.F., I.I. and B.N.R.T.; Supervision, G.N., G.L., I.I. All authors have read and agreed to the published version of the manuscript.  
This research was funded by CNPq and CAPES (Brazil), and the sponsorship guaranteed with basic research funds provided by Politecnico di Torino (Italy).  
Not applicable.  
The authors wish to acknowledge the Brazilian National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Level of Education Personnel (CAPES) and the sponsorship guaranteed with basic research funds provided by Politecnico di Torino, Italy for their financial aids in this work.  
The authors declare no conflict of interest.