esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Correlation of Phenolic Acids with TPC, Antioxidant and AChE Inhibitory Activities
ABTS: 2,2\({}^{\prime}\)-Azino-bis(3-ethylbenzothazoline-6-sulfonic acid; AChE: acetylcholinesterasecholinesterase; DPPH: 2,2-Diphenyl-1-picrylhydrazyl; FRAP: ferric-reducing antioxidant power; PCA: principal component analysis; TPC: total phenolic content. visual separation is consistent with their weak or negligible Pearson's correlations with these activities, reflecting their minor or indirect roles in contributing to overall bioactivity. Additionally, the proximity of protocatechuric acid to TPC and anti-AChE activity in the PCA plot highlights its moderate influence on these activities, even though its Pearson's correlations with TPC (\(r\) = 0.16, \(p\) = 0.66) and AChE inhibitory (\(r\) = 0.521, \(p\) = 0.12) assays do not reach statistical significance. Overall, the PCA plot visually reinforces the strong interrelations among TPC, FRAP, and anti-AChE assays, which are tightly clustered in the same quadrant, suggesting overlapping mechanisms of action and shared contributions to bioactivity. At the same time, the inverse placement of DPPH and ABTS relative to TPC and FRAP reflects their distinct role as measures of radical scavenging activity, inversely related to total phenolics. The PCA also reveals the varying contributions of individual phenolic compounds to these activities, emphasizing the complexity of interactions within the phenolic matrix and the need to consider both individual and collective effects of bioactive compounds.
## 2 Problem Description and Formulation (INS Motion Model)  
Most of the previous research on vehicle positioning does not take into consideration complex scenarios such as hard brake, sharp cornering or roundabouts. Hence, the evaluation of the performance of positioning algorithms present in most published works may not accurately reflect real-life vehicular driving experience. Moreover, as those complex scenarios present strong challenges for INS tracking, it seems essential for the reliability of the algorithms to be assessed under such scenarios:  
* Hard brake--According to Reference [20], hard brakes are characterised by a longitudinal deceleration of \(\leq\)\(-\)0.45 g. They occur when the brake pad of the vehicle has a large force applied to it. The sudden halt to the motion of the vehicle leads to a steep decline in the velocity of the vehicle, thus making it difficult to predict the vehicle coming to a stop and to track the motion of the vehicle thereafter. This scenario poses a major challenge to the displacement estimation of the vehicle.
* Sharp cornering and successive left and right turn--The sudden and consecutive change in the direction of the vehicle also poses a challenge to the orientation estimation of the vehicle. The INS struggles to accurately capture the sudden sharp changes to the orientation of the vehicle as well as continuous consecutive changes to the vehicle in relatively short periods of time.
* Changes in acceleration (Jerk)--The accuracy of the displacement estimation of the INS is affected by quick and varied changes to the acceleration of the vehicle within a short period of time. This is particularly a challenge as the INS struggles to capture the quick change in the vehicle's displacement thereafter.
* Roundabout--Roundabouts present a particular struggle due to its shape. The circular and unidirectional traffic flow makes it a challenge to track the vehicle's orientation and displacement particularly due to the continuous change in the vehicle's direction whilst navigating the roundabout. Different roundabout sizes were considered in this study.
## 2 Research on Anti-Skid Mechanisms of Asphalt Pavement
### Factors Affecting the Skid Resistance of Asphalt Pavements
#### 2.2.1 Influence of Aggregate Properties on Skid Resistance of Asphalt Pavements  
The skid resistance of asphalt pavements is primarily determined by the intrinsic properties of the aggregate particles. Both coarse and fine aggregates employed in asphalt mixtures significantly influence the surface friction performance. During the early stage of pavement service life, the asphalt binder partially covers the aggregate surfaces, which modulates the tyre aggregate interaction and subsequently affects the development of skid resistance [23]. Although the binder is present, aggregates continue to constitute the primary contact interface between the pavement and vehicle tyres and therefore play a pivotal role in the generation of friction forces. In order to achieve optimal skid resistance in pavement construction, it is essential to select coarse and fine aggregates of the highest possible quality. [PERSON] et al. [24] found that mineral specification affects the macroscopic tectonic depth of the pavement and stated that high quality stones such as sandstone, basalt, andesite, and granite have better skid resistance, abrasion resistance, and impact resistance. The aggregate surface texture structure represents the primary component of the pavement microtexture, characterised by a horizontal wavelength of less than 0.5 mm and an amplitude of 1 to 500 \(\upmu\)m. The formation of microtexture is therefore influenced by two main factors: the type of mineral composition of aggregate particles and the content of mineral components. The microtexture of aggregate is the basis of good anti-skid performance of asphalt pavement [25; 26; 27; 28; 29].  
In terms of the mineral composition of aggregate particles, aggregates with hard crystal structures and strong bonding and interlocking between crystals generally provide good wear resistance [30; 31; 32]. The assessment of aggregate mineral composition requires the application of microstructural analytical techniques, including optical microscopy and scanning electron microscopy (SEM) [31]. According to previous studies, an optimal content of hard minerals--generally falling within the range of 50% to 70%--can significantly enhance skid resistance. Moreover, aggregates with an average crystal grain size of approximately 200 \(\upmu\)m, combined with angular-shaped hard mineral grains, are typically regarded as the most favourable for improving frictional pavement performance. Aggregate abrasive resistance is the capacity of an aggregate to sustain the microtexture of the aggregate surface following exposure to a multitude of abrasive and shear forces exerted by traffic loads.
# A Very High-Resolution Urban Green Space from the Fusion of Microsatellite, SAR, and MSI Images
## 2 Methodology
### Training and Validation Datasets  
Based on the understanding of the study area, several polygons were manually generated using the GEE platform. Street View images from Google Maps were used as a reference to ensure accuracy and verify the latest conditions. As depicted in Figure 2, paddy fields were observed in North Jakarta as of July 2023.  
In total, over 100 polygons were created randomly and categorized into six distinct classes of urban green spaces: agriculture, forest, grassland, mixed, shrub, and wetland. Further details regarding these categories are presented in Table 1.  
Furthermore, the Pareto Principle was applied to split the created multiple polygons into 70% for training data and 30% for testing data.
## 5 Economic Benefits of UAV Technologies  
The UAV based remote sensing technology helps the farmers in the agricultural fields for gaining more productivity globally. There will be certain regions like South and Southeast Asia, Western and Central Europe, Central America and the Caribbean, and Southern Africa can be adapted with these kinds of new technologies without major human adaptations to increase productivity for a sustainable growing population.  
There are more economic benefits for the society that could be derived from the remote sensing technology and unmanned aerial vehicle. Especially for developing countries like India and African countries, the usage of UAV leads to reduction in damage of crops and increase yields. If farmers can be encouraged to use this technology on the commercial side, it will eventually help them to increase the production of crops. Once the farmers are producing crops on a larger scale, it will help them to export the agricultural products to other continents. This will balance the problems in the economy of developing countries through an increase in export and reduction in import of agricultural produce to some extent. Moreover, it will gradually help increase employment which will reduce poverty and improve the standard of living for people.
# Evaluation of 5G Positioning Performance Based on UTDoA, AoA and Base-Station Selective Exclusion
## 2 Signal Model  
### LTE Positioning Signal Structure  
This subsection summarizes the signal models that will be exploited for positioning.
# An Overview of Emergency Communication Networks
## 5 Sea Ad Hoc Network (SANET)
### Future Development Directions
#### 3.4.2 Space-Air-Ground-Sea Integration Networks
UAV communication can reduce the burden on ground networks and improve service capabilities in congested areas with high dynamic data traffic loads, providing high-capacity wide-area coverage; however, UAV battery capacity is limited and the network may face energy shortages. With the development of various key technologies, the construction of a space-air-ground-sea integrated emergency communication network can be divided into several aspects:  
* Integrate ground system and non-ground system: design an open and secure gateway interface to realize network interconnection and gradually optimize the delay and transmission cost of non-ground networks. * Unified planning of satellites with different orbital heights to realize networking communication: adopt the architecture mode and key technology similar to that of the ground network, and improve the networking efficiency of the space-air-ground-sea integration. * Realize the reuse and sharing of space-air-ground-sea communication network equipment and computing processing capacity: through modularization of equipment, cloud computing and processing, and other technologies, the cost of emergency rescue can be further reduced and network technical support can be provided for emergency response. The development of the space-air-ground-sea integrated network faces the following major challenges:  
* The network dynamic change speed is fast, the structure is complex, and the topology changes frequently;
* The performance of different service facilities (e.g., satellites and base stations) varies greatly;
* High construction cost and high trial-and-error cost. The space-air-ground-sea integrated network can provide ubiquitous, collaborative, and efficient information support infrastructure for various network applications. In addition, the network can take full advantage of the different dimensional networks, such as air-based backbone networks, and space-based, ground-based, and sea-based access networks, overcome the barriers that exist between originally independent networks, and truly realize the integration of the networks. In this case, ensuring reliable and efficient data transmission of the network to meet people's increasing requirements for the space-air-ground-sea integration network service has become an important goal and research focus. In the future, the space-air-ground-sea integration network will realize efficient cooperation through mutual integration; for example, through unified planning of satellites, space networking will be realized to fully utilize network advantages. Because of the development direction of the future 6G mobile communication system, the space-air-ground-sea integrated network can meet the needs of large-scale access and high-speed and low-delay data transmission of users in the whole domain.
## 2 Materials and Methods  
To avoid the rough area on the transportation road, it is necessary to make a planning map containing the roughness information and add it to the estimation function of the Hybrid A* algorithm. The method of constructing a planning map with roughness information is as follows:  
1. DSM data acquisition and generation. The raw elevation data of cutting zone is obtained by some topographic mapping methods (oblique photogrammetry, lidar scanning, etc.), and the corresponding DSM is generated.
2. Constructing the obstacle cost map of the cutting zone. Firstly, the obstacle point set in DSM is filtered by setting different terrain factors thresholds. Then the obstacle binary map is constructed by the elevation scanning method, and finally, the obstacle cost map is made from GVD.
3. Constructing the roughness cost map of the cutting zone. Firstly, removing the obstacle point set in DSM, filtering the remaining point set with another terrain threshold. Then, using the standard deviation of moving window to traverse calculation, its value is taken as the roughness value of all coordinate points within the window range. Finally, normalizing the roughness matrix to generate the roughness cost Map of the cutting zone.
4. Generating the C-MAP. Overlaying and normalizing the value matrix of obstacle cost map and roughness cost map, get the C-MAP, which is used in path planning.  
The modified parts of the Hybrid A* algorithm are as follows:  
1. Modify the \(g\)-value estimation function. The contact cost between the tire and the ground surface is added into the \(g\)-value estimation function. Consequently, the step length a dynamic value instead of a static value in the part of the node extension.
2. Modify the conjugate gradient object function. The original Voronoi term is replaced by a new roughness term to correct the path points passing through rough area.  
The primary process of map construction and modified Hybrid A* algorithm is shown in Figure 1.
# Construction of Nonblocking Wavelength/Space Switches with AWGs and WSSes
###### Abstract  
In this paper, we how to use two technologies, AWG (arrayed-waveguide grating) and WSS (wavelength selective switches), to design nonblocking wavelength/space optical cross connects. An AWG is a passive device and can route multiple wavelengths simultaneously. However, to apply AWGs, there are several issues to consider, including the wavelength conversion range, crosstalk, and switch size constraint. We show a decomposition technique for designing an AWG-based nonblocking wavelength/space switch. The decomposition is carried out in a transformed space network. The new technique is simpler in concept and more flexible in setting switch sizes. We also study another class of wavelength/space switches that are based on WSSes and compare the two approaches in terms of the scalability, switch size constraint, and number of WCs (wavelength converters) required.  
arayed-waveguide grating (AWG); wavelength selective switch (WSS); nonblocking networks; Clos networks +
Footnote †: journal: Applied Soft
## 4 Experiment and Analysis
### Experimental Settings  
In this experiment, we utilized the Adam optimizer to optimize our network. We set the initial learning rate to 0.0001 and employed a momentum value of 0.9. The batch size was configured to 8, and we ran the training for a total of 300 epochs. Our network was executed on a system running Ubuntu 20.04 with Python version 3.8, PyTorch version 1.11.0, and powered by NVIDIA RTX 3090 GPUs.  
We show the training flow of our proposed segmentation network in detail in Algorithm 1, and the algorithm pseudo-code is shown as follows.  
```
0: Augmented training sample \(\text{S}=\{\text{X}_{1},\text{X}_{2},\ldots,\text{X}_{n}\}\), where \(\text{X}\in\text{R}^{256\times 256\times 3}\)
1. Begin
2. Randomly initialize the model parameters
3. While \(\varepsilon\) have not converged do
4. For epoch = 0, 1,..., 300 do
5. The parameters were retrained on the target dataset
6. The Adam optimizer was used to update the weights, as expressed by \(\epsilon_{c+1}=\varepsilon_{c}-\alpha\times\frac{\tilde{\varepsilon}}{( \sqrt{\hat{\varepsilon}_{c}+\theta})}\) \(\alpha\) (learning rate), \(\tilde{\varepsilon}_{c}\) (the first corrected bias), \(\hat{\tau}_{c}\) (the second corrected bias)
7. The BDice loss function was used to update the weights, as expressed by \(G_{\varepsilon}\leftarrow\
abla_{\varepsilon}Loss_{BDice}(S)\), where \"BDice\" means BCE Loss and Dice Loss
8. Apply the cosine annealing strategy to adjust \(\alpha\)
9. Continuously update the weighs using the S
10. \(\varepsilon\leftarrow\varepsilon-\mu G_{\varepsilon}\)
11. End for
12. End while
13. End Output: the best weight parameter \(\varepsilon_{best}\)
```  
**Algorithm 1** The detailed training process of the RMAU-Net
## 2 Theory
### Experimental Setup  
A cylindrical phantom was used to verify the proposed approach. The structure of the cylindrical phantom contained inner and outer compartments that were separated by a tube. The materials of the phantom were distilled water, NaCl, agarose, and CuSO\({}_{4}\bullet\)5H\({}_{2}\)O. Agarose was used to solidify the phantom, whereas CuSO\({}_{4}\bullet\)5H\({}_{2}\)O was used to decrease the T1 values and then reduce the scanning time. The contrast of the phantom was prepared by adjusting the concentrations of saline. The mass ratio of distilled water, agarose, and CuSO\({}_{4}\bullet\)5H\({}_{2}\)O was 100:1:0.1. The saline concentrations were 1.5% and 0.5% for the inner and outer compartments, respectively. Conductivity values were measured a by network analyzer (Agilent 4395A, Santa Clara, CA, USA) associated with an S-parameter test set (Agilent 87511A). The conductivity values for the inner and outer compartments were 2.01 and 0.97 s/m, respectively.  
Figure 1: Simulation setup. (**a**) The birdcage coil loaded with a numerical phantom, (**b**) seven regions of phantom, (**c**) the birdcage coil loaded with the Ella model. The radiofrequency (RF) shield is not shown in (**c**).  
The in vivo experiment included a healthy 26-year-old male volunteer. The subject gave their informed consent for inclusion before they participated in the study. The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Southern Medical University (2018B030333001).  
The phantom and in vivo experiments were carried out on a 3.0T MRI scanner (Philips Achieva, Best, The Netherlands) installed in NanFang Hospital. We used the standard body coil as transmitting and receiving and applied the spin-echo (SE) sequence to obtain the transceive phase information. The 2D SE sequence parameters in the phantom experiment were TR/TE = 1000/10 ms, with 5 averages in 20 min. The acquisitions were performed in a total of five slices with a resolution of \(1.17\times 1.17\times 3\) mm\({}^{3}\) and a field of view (FOV) of \(150\times 150\) mm\({}^{2}\). For the in vivo experiment, the parameters of the 2D SE sequence were TR/TE = 1200/7 ms; 10 slices centered on the head center were scanned, with a resolution of \(1.88\times 1.88\times 5\) mm\({}^{3}\) and a FOV of \(240\times 240\) mm\({}^{2}\). This scan took 3 min.
## 3 Results
### Group 3--Use of Diode Laser in Peri-Implantitis Treatment (Table 3)
The patients enrolled in the study were assigned to one of two groups: the control group (CG) was treated with conventional surgical therapy; and the test group (TG) was treated with a combination of conventional non-surgical therapy, with the addition decontamination with diode laser (980 nm). The clinical outcomes obtained were analyzed 3 months after treatment and showed greater improvements in BOP and PPD reduction in TG if compared with CG [24]. In particular, the mean reduction of PPD for TG was 4.04 \(\pm\) 0.54 mm at baseline and 2.98 \(\pm\) 0.70 mm; in the CG, it was 3.8 \(\pm\) 1.24 mm at baseline and 3.54 \(\pm\) 0.35 mm after 3 months. BOP index was positive in 44 sites at baseline and only in six sites 3 months after laser treatment. In the CG, BOP reduction was less significative, going from 52 sites at baseline to 28 sites 3 months after conventional non-surgical therapy. The authors concluded that a 980 nm diode laser may be effective in non-surgical treatments of PiM and initial PI. The effectiveness of adjunctive laser irradiation in non-surgical peri-implant therapy was highlighted in the retrospective analysis conducted by [PERSON] [25]. The authors treated 23 infected implant surfaces with PPD \(>\) 5 mm with conventional mechanical debridement and by rinsing with sterile saline solution. Subsequently, adjunctive diode laser irradiation was performed in the pocket around the implant. All the described protocols were performed at the baseline and repeated after 7 and 14 days. After an observational period of 2 years, the authors noted an improvement of peri-implant health, with a significant reduction in all analyzed peri-implant indices (CAL, PPD, BOP and sulcular suppuration).
# Passivity-Based Control for a Micro Air Vehicle Using Unit Quaternions
## 2 Preliminaries  
### Quaternion Background  
A quaternion is basically a type of complex number that consists of four values, one of which is real, while the other three are imaginary [22; 23; 24; 25]. The quaternion space is denoted by \(\mathbb{H}\). Let \(\boldsymbol{q}\) be a quaternion expresses by:  
\[\boldsymbol{q}=q_{0}+\bar{q}=q_{0}+\left[\begin{array}{c}q_{1}\\ q_{2}\\ q_{3}\end{array}\right],\;\;q_{0}\in\mathbb{R},\bar{q}\in\mathbb{R}^{3}\]  
where \(\bar{q}\) represents the complex vectorial part of \(\boldsymbol{q}\), and \(q_{0}\) denotes the scalar part of \(\boldsymbol{q}\). Note that if \(q_{0}=0\), then \(\boldsymbol{q}=\bar{q}\), thus \(\boldsymbol{q}\in\mathbb{R}^{3}\), this implies that \(\mathbb{R}^{3}\) is a subset of \(\mathbb{H}\) in which \(q_{0}=0\).  
The quaternion basic operations are:  
* Quaternion multiplication \[\boldsymbol{q}\otimes\boldsymbol{r}=(q_{0}\,r_{0}-\overline{q}\cdot\overline {r})+(r_{0}\,\overline{q}+q_{0}\,\overline{r}+\overline{q}\times\overline{r})\] where \(\boldsymbol{r}\) is also a quaternion.
* Norm of a quaternion \(\boldsymbol{q}\) \[||\boldsymbol{q}||=\sqrt{\boldsymbol{q}\otimes\boldsymbol{q}^{*}}=\sqrt{q_{0 }^{2}+q_{1}^{2}+q_{2}^{2}+q_{3}^{2}}\] In the case that \(||\boldsymbol{q}||=1\), \(\boldsymbol{q}\) represents an unit quaternion.
* Quaternion conjugate \[\boldsymbol{q}^{*}=q_{0}-\overline{q}\]
* Quaternion inverse \[\boldsymbol{q}^{-1}=||\boldsymbol{q}||^{-1}\boldsymbol{q}^{*}\] If \(\boldsymbol{q}\) is unitary, then the inverse and the norm are equivalent.
* The derivative of a quaternion \[\dot{\boldsymbol{q}}=\frac{1}{2}\,\boldsymbol{q}\otimes\omega\] where \(\omega\) represents the angular velocity.  
Any vector in a three-dimensional space can be rotated from one reference frame to another (for example a body frame), i.e.,  
\[v^{\prime}=\boldsymbol{q}^{*}\otimes v\otimes\boldsymbol{q} \tag{1}\]  
where \(v\in\mathbb{R}^{3}\) and \(v^{\prime}\in\mathbb{R}^{3}\) are in the fixed and body frames respectively.  
Any rotation can be expressed by its axis-angle representation, which is composed by a direction vector \(\vec{e}\in\mathbb{R}^{3},||\vec{e}||=1\) and its angle \(\theta\in\mathbb{R}\), as depicted in Figure 1. This yields to a single vector \(\bar{\theta}=\theta\vec{e}\) with \(\bar{\theta}\in\mathbb{R}^{3}\).  
The Euler-Rodrigues Formula then relates this rotation vector to a unit quaternion as  
\[\boldsymbol{q}=\cos(\theta/2)+\vec{e}\sin(\theta/2) \tag{2}\]  
A logarithmic mapping can be used to change any unit quaternion to the axis-angle representation  
\[\bar{\theta}=2\ln\boldsymbol{q},\quad\hat{\theta}=\omega,\]where  
\[\ln\mathbf{q}=\left\{\begin{array}{ll}\ln||\mathbf{q}||+\frac{\overline{q}}{||\overline{q }||}\arccos\frac{q_{0}}{||\mathbf{q}||},&||\overline{q}||\
eq 0\\ \ln||\mathbf{q}||,&||\overline{q}||=0\end{array}\right.\]  
Note that (2) implies that \(||\mathbf{q}||=1\), thus the scalar part of the quaternion logarithm is zero, implying that \(\ln\mathbf{q}\in\mathbb{R}^{3}\)\(\forall\)\(\mathbf{q}\)\(|q_{0}=0\).