esa-sceva/satcom-chunk-collection huggingface dataset:
# Design, Manufacturing, and Flight Testing of an Experimental Flying Wing UAV
## 3 Weight Estimation for an Electric UAV
### Weight Estimation for a Specific Payload and Endurance  
In this study, the payload is 2.5 kg and endurance is 3.5 h. We obtain the total UAV weight for a given payload and endurance. The constant 1.1 in Equation (17) assumes that the power consumption of the avionics system in flight is 10% of the cruise consumption.  
Table 1 lists the symbols from these equations and their values. The induced drag factor and zero-lift drag coefficient can be temporarily set as the empirical values obtained from the first calculation; these values are recalculated when the aerodynamic design is completed. Therefore, the total UAV weight can be expressed as:  
\[\begin{array}{ll}W_{\text{total}}&=W_{Empty}+W_{Battery}+W_{ Payload}\\ &=\rho_{Empty}S+W_{Payload}\\ &+T_{Endurance}*(\frac{1.1\sqrt{\frac{2W_{Total}^{3}}{\rho_{\text{load}}}}|1 \bigg{(}\frac{3}{\kappa_{D_{0}}^{1/3}}\bigg{)}^{3/4}-1}{\eta_{motor}\eta_{pr }/D_{0}T_{discharge}\rho_{Battery}})\end{array} \tag{20}\]  
Assuming that the payload, endurance, and empty mass density per wing surface area are given, the total weight can be estimated as:  
\[W_{\text{total}}=\frac{W_{Payload}}{(1-\frac{\rho_{Empty}}{W_{Total}/S}-T_{ Endurance}*(\frac{1.1\sqrt{\frac{2W_{Total}}{\rho_{\text{load}}}}|1\bigg{(}\frac{3}{ \kappa_{D_{0}}^{1/3}}\bigg{)}^{3/4}-1}{(\frac{1.1\sqrt{\frac{2W_{  
The payload is 2.5 kg, the endurance is 3.5 h, and the empty mass density per wing surface area is 2.44 kg/m\({}^{2}\). The estimated total weight of the electric UAV is 6.5 kg, empty weight is 2.62 kg, and battery weight is 1.38 kg.
## 4 Results and Discussion
### Indices Selection and Seasonal Variation of All Indices  
#### 4.2.1 Indices Selection  
Results of the VIP values from PLSR illustrate that the most sensitive wavebands correspond to GPP and Re (Figure 5). They are located in the NIR region (740-1350 nm) and the 620-690 nm and 1980-1990 nm wavelengths, with a VIP value \(>\) 1. The most insensitive wavebands were located at 710-730 nm, 1470-1520 nm, 1740-1790 nm, and 2100-2180 nm wavelengths, with VIP value \(<\) 0.5. Other wavebands showed moderate sensitivity to GPP and Re.  
Figure 5: The Variable Importance for a PLS Projection (VIP) values curves to gross primary production (GPP) and ecosystem respiration (Re) in the whole spectrum region.  
Based on the principles of indices and sensitive wavelength ranges selection methodologies, 11 narrowband HVIs were used for indicating C fluxes. Most of the 11 narrowband HVIs were formed by combined sensitive and insensitive bands. Eight broadband VIs were also selected for identifying the effects between broadband VIs and HVIs. VIs categories have been previously reported in the literature [58]. However, we classified the 19 indices listed in Table 2[9, 35, 36, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69] based on our study goals.
# Design, Deployment and Evolution of Heterogeneous Smart Public Lighting Systems
## 6 Deployment and Configuration of a Smart Lighting Infrastructure
### Step 1. Preliminary Design
Therefore, in this phase it is important to consider whether the cost for extending the coverage to unserved areas is reasonable with respect to the saving that can be achieved. Mesh networks allow a greater flexibility in the gateway positioning phase, because gateways need to cover only a very small subset of network devices. Moreover, since the network arises from hop-by-hop communications among devices installed on streetlights, which are close one to another, it is usually able to guarantee 100% coverage. Clearly, the number of gateways is higher than that required for LoRa networks. This is even more true considering that it is generally not kept at the strict minimum, in order to avoid bottlenecks, provide higher throughput and reduce the latency. **Phase 1.3. Choice of traffic sensors locations. ** The third step is the detection of the streets where to place vehicular traffic sensors, which are needed to implement traffic-adaptive energy saving algorithms, such as TAI or FAI [(68; 79)]. As outlined in Section 3.3, significant savings can be achieved by dynamically adapting the light intensity to actual traffic conditions. However, dynamic light dimming is allowed provided that safety conditions are guaranteed. Thus, the designer of the lighting infrastructure must identify candidate streets, perform a risk analysis and, in case, find the dimming policies capable of achieving the highest saving without affecting transport security. In this regard, it is worth observing that, to avoid confusing the drivers, the light dimming must take place simultaneously in all the interested light fixtures, which requires a low-latency communication network.
## 4 Deformation Mapping Relationship Between Long-Span,
### Characteristics of Deformation Wavelength of Long-Span, Cable-Stayed Bridges  
As the train traverses the bridge and the auxiliary pier settles, the vertical deformation of the expansive cable-stayed structure becomes more pronounced within the wavelength range of less than 200 m. Moreover, the temperature differential between the cables and beams significantly impacts the vertical deformation of the main span. Considering these factors, a thorough examination is undertaken to explore the wavelength characteristics of vertical deformation in a long-span, cable-stayed bridge. This investigation focuses specifically on scenarios involving the 5 mm settlement of auxiliary piers and a 15 \({}^{\circ}\)C temperature rise in tension cables, particularly during the train's entry onto the bridge.  
In Figure 13, the distribution of vertical deformation in each wavelength section at different locations of the long-span, cable-stayed bridge during the train's entry is depicted. As the train approaches the bridge, noticeable variations in the deformation wavelength characteristics emerge, particularly affecting the vertical deformation of the left span. Generally, the right span bears the predominant vertical deformation of the long-span, cable-stayed bridge. The auxiliary span, on the other hand, predominantly undergoes deformation in wavelengths below 200 m, with larger deformation values. Notably, the deformation cutoff wavelength in the auxiliary span is set at 400 m.  
Figure 13: The vertical deformation distribution of the cable-stayed bridge under the 8 trains.  
Figure 14 illustrates the distribution of vertical deformation in each wavelength section at different locations of the long-span, cable-stayed bridge during the warming up of cables. The figure highlights a downward deflection in the main span and an upward arching in the side spans. In the wavelength section below 200 m, it is evident that the vertical deformation is more pronounced at the location of the bridge tower. This suggests that the long-wave smoothness of the bridge tower, under the influence of the warming up of cables, is relatively poor compared to other locations. The side span and mid-span locations are primarily dominated by long waves exceeding 200 m, with deformation concentrated in the wavelength range of 400-1000 m.  
In Figure 15, the vertical deformation distribution of each wavelength section at different locations of the long-span, cable-stayed bridge is depicted when a settlement of 5 mm occurs in the left auxiliary pier. The figure illustrates that, when the auxiliary pier settle, the vertical deformation primarily occurs at the location of the left side span and the left tower. Specifically, the vertical deformation of the left side span is concentrated in the 100-450 m wavelength section, with the maximum value of the wavelength decomposition deformation occurring around 200 m. Notably, the settlement of auxiliary pier has a lesser impact on the deformation at the bridge tower position.
## Communication protocol
### Mobile Network Infrastructure  
To test new UTM concepts and use cases with UAS in a real environment, an own 4G/5G testbed was set up at the facilities in Neubiberg, Germany. The testbed is based on 3 rd Generation Partnership Program (3 GPP) Release 15 and enables a much more flexible test environment due to the free selection of equipment and network parameters compared to commercial mobile networks.  
The discussion starts with a brief summary of the main features of each 4G/5G network component, as they are essential for understanding the proposed 4G/5G concept. The setup for the evaluation testbed supports the so-called NR Non-Standalone Access (NSA) which is currently used by most mobile operators for their initial NR roll out [35].
## 3 Proposed Real-Time Data Fusion Method Based on a New Distance Metric
### Data Fusion for Object Information
#### 3.1.5 Proposed Data Fusion for Object Classification
Given the collected data, vehicle \(i\) first validates the existence of the reported object (_step 3_). If the existence is confirmed (_step 4_), the algorithm determines the class of the detected object by fusing the shared confidences (_step 5_). An example is illustrated in Figure 4. There are 3 vehicles, V1-V3, and an object \(k\) which is within the sensing ranges of them,e.g., \(\mathcal{M}_{\text{VI}(k)}=\{\text{V1,V2,V3}\}\). Unlike V2 and V3, it is impossible for V1 to detect \(k\), as the object is located in the uncertainty area of V1. Moreover, we assume that V3 fails to detect the object due to, e.g., bad weather or sensor malfunctioning. We set the confidences for each vehicle as in the tables in Figure 4. As only V2 recognizes the object, it has class confidences, i.e., \(E_{k}^{1}=\{\text{V2}\}\). In this case, through inter-vehicle communications, V1 receives the detection results, then verify the existence of the object. From Algorithm 3, V1 can derive the final outputs for existence and class as \(\{0.58,0.34,0.08\}\) and \(\{0.5,0.31,0.19\}\), respectively. We set \(h_{e}=0.5\), thus V1 is able to not only indirectly detect the presence of the object, but also find the class of the object. From the experiments in Section 5, we will show that the proposed method operates in real-time, and thus is suitable for the autonomous vehicle environment. Next, we discuss data fusion algorithm for \"_trajectory_\" type data. ```
1:Given \(M_{k^{\prime}}^{j}\), \(C_{k}^{i}\), \(\forall j\in\mathcal{M}_{i(k)}(n)\), \(S^{i}(n-1)\), \(h_{e}\)
2:Derive \(E_{k}^{k}\) based on \(M_{k}^{i}\) and \(\mathcal{M}_{i(k)}(n)\)
3:\([\mathcal{E},\mathcal{N},\mathcal{U}]=\textsc{Existence}\ (S^{i}(n-1),M_{k^{\prime}}^{j}\forall j\in \mathcal{M}_{i(k)}(n))\)
4:if\(\mathcal{E}\geq h_{e}\)then
5:\([\mathcal{C}]=\textsc{Class}\ (C_{k}^{i},\forall i\in E_{k}^{i})\)
6:endif
```  
**Algorithm 3** Decision-making for vehicle \(i\) about object \(k\)
## 3 Results
### Localization and Interaction of FaMADS1 with ABI5-5, TRAB1, and ABIS  
The coding sequence of _FaMADS1_ without stop codes was constructed in pBI221. The leaf epidermal cells with 355::GFP demonstrated green fluorescence throughout the cell. By contrast, green fluorescence was especially detected in the nuclei of leaf epidermal cells expressing the 355::FaMADS1-GFP fusion plasmids (Figure 7), suggesting that FaMADS1 was a nuclear protein.  
An online informatics survey was implemented to analyze a fragment of the _FaMADS1_ promoter sequence (1095 bp upstream from the ATG start codon). A putative domain (ABRE) for responding to ABA was found (Table S2). Therefore, two sequences (_FaMADS1_-pro1 and _FaMADS1_-pro2) of _FaMADS1_ promoter were cloned to study the interaction between FaMADS1 and ABA-related transcription factors (FaABIS-5, FaTRAB1, FaABIS, FaABIS-2, and FaABIS-3). FaABIS-5, FaTRAB1, and FaABIS interacted with _FaMADS1_-pro1, whereas ABI5-2 and ABI5-3 did not interact with _FaMADS1_-pro1 (Figure 8A). FaABIS-5, FaTRAB1, FaABIS, FaABIS-2, and FaABIS-3 also did not interact with _FaMADS1_-pro2 (Figure 8B). These results revealed that _FaMADS1_-pro1 contained the active cis-acting elements, which could interact with FaABIS-5, FaTRAB1, and FaABIS.  
To further verify the regulatory roles of FaABIS-5, FaTRAB1, and FaABIS in _FaMADS1_, a dual-luciferase assay was performed in tobacco leaves (Figure 9). FaTRAB1 could significantly inhibit the promoter of _FaMADS1_, while FaABIS-5 and FaABIS had little influence on the _FaMADS1_ promoter.  
Figure 7: Sub-cellular localization of 355::FaMADS1-GFP fusion protein in leaf epidermal cells of tobacco. Plasmids of 355::GFP and 355::FaMADS1-GFP were transformed into leaf epidermal cells by agro-infiltration, respectively. Bright field images, fluorescent field images, and the merged images of leaf epidermal cells expressing 355::GFP or 355::FaMADS1-GFP fusion protein.  
Figure 8: Yeast one-hybrid analysis of ABIS-5, TRAB1, ABIS, ABIS-2, and ABI5-3 binding to the _FaMADS1_ promoter. Auto-activation tests of p53, _FaMADS1_-pro1, and _FaMADS1_-pro2 were experimented on SD medium lacking Ura in the presence of aureobasidin A. Interaction tests between FaMADS1 promoters with transcription factors were carried out on SD medium lacking Leu in the presence of aureobasidin A. (**A**) The interaction between ABIS-5, TRAB1, ABIS, ABIS-2, ABIS-3, and _FaMADS1_-pro1. (**B**) The interaction between ABIS-5, TRAB1, ABIS, ABIS-2, ABIS-3, and _FaMADS1_-pro2.  
Figure 9: Regulatory effects of FaABIS-5, FaTRAB1, and FaABIS on the promoters of the _FaMADS1_ gene using the dual-luciferase assay. The LUC/REN ratio of the empty vector (SK) plus promoter was set as 1. Different letters above the points indicate significantly different values (\(p<0.05\)) through the LSD test.
# Experimentation Environments for Data Center Routing Protocols: A Comprehensive Review
## 5 Experimental Results
### Validation  
A complete fat-tree emulation program was developed for Mininet and Core. This program is capable of (i) generating any fat-tree with layer 3 configuration using the APIs provided by the emulators, (ii) generating the configuration files for the protocol daemons of BGP, ISIS, Openfabric, and rift-python, (iii) orchestrating the experiment, i.e., start the emulation and all the routing daemons needed, run test-cases, and finally stop the experiment (available at [69]). We use the Sybil framework mentioned above for Kathara and its distributed mode Megalos, also referred to in the repository, putting all the experimentation options together.  
The base topology for the experimentation is a \(k=4\) fat-tree, depicted in Figure 1. A common use case for all the environments was selected: the bootstrap case. This case aims to verify the expected behavior of the protocols at bootstrap, which permits verifying the correct convergence of the routing protocols configured in the fat tree. After the convergence of the protocols, there is full layer three multi-path connectivity between every pair of servers. This use case lays down a strong basis to build other use cases, e.g., a failure use case.  
The single host emulations were run on a server with 30 CPUs and 126 GB of RAM. The bootstrap case was successfully performed over all the environments in the selected topology, validating the convergence of BGP, ISIS, Openfabric, and rift-python.
# A Novel Hybrid CSP-PV Power Plant Based on Brayton Supercritical CO\({}_{2}\) Thermal Machines
###### Abstract  
A novel hybrid CSP-PV power plant is presented. Instead of the integration used in current hybrid power plants, where part of the PV production is charged into the thermal energy storage system through electrical resistors, the proposed system integrates both PV and thermal solar fields using a high-temperature heat pump. Both the heat pump and the heat engine are based on Brayton supercritical CO\({}_{2}\) thermodynamic cycles. Such integration allows for charging the molten salt storage as if a central tower receiver field supplied the thermal energy, whereas parabolic trough collectors are employed. Unlike conventional hybrid plants, where the storage of PV production leads to a decrease in power injected into the grid throughout the day, the power injected by the proposed system remains constant. The heat engine efficiency is 44.4%, and the COP is 2.32. The LCOE for a 50 MWe plant with up to 12 h of storage capacity is USD 171/MWh, which is lower than that of existing CSP power plants with comparable performance. Although the cost is higher compared with a PV plant with batteries, this hybrid system offers two significant advantages: it eliminates the consumption of critical raw materials in batteries, and all the electricity produced comes from a synchronous machine.  
B rayton supercritical CO\({}_{2}\) power cycle; high-temperature heat pump; thermal energy storage; Carnot battery; CSP-PV hybrid power plant
# Polarization Sensitive Optical Coherence Tomography: A Review of Technology and Applications
## 3 PS-OCT Applications
### PS-OCT in Vessels and Cardiac Tissue  
Birefringence of vessel walls is a promising diagnostic parameter for arteriosclerotic vascular disease accessible by PS-OCT [201]. In atherosclerosis, artery walls locally thicken and may form atherosclerotic plaque lesions, which may be categorized into stable and unstable (called vulnerable) plaques. Ex vivo scanning compared to histology as well as catheter based PS-OCT imaging of atherosclerotic artery walls have revealed altered birefringence patterns in atherosclerotic  
Figure 9: PS-OCT of tendon and cartilage. (**a–c**) First published PS-OCT images (adapted with permission from [8], Optical Society of America, 1997) showing birefringence of bovine tendon. (**a**) Fresh tendon; (**b**) Tendon after exposure to high-power laser irradiation. The banded structure appears disturbed compared to (**a**); (**c**) Color-coded intensity image; (**d**) PS-OCT optical phase retardation images at the various sites on a bovine tibia. The banded appearance in retardation images is indicative of high birefringence in some areas (adapted with permission from [188], [PERSON], 2008).  
plaques [202; 203; 204]. Examples of different plaques imaged by PS-OCT as well as corresponding histologic images are shown in Figure 10 [205].  
Information on the birefringent axis orientation provides access to fiber alignment in fibrous tissue (Figure 10a-c) [14]. Tractographic PS-OCT imaging was performed in the walls of blood vessels (Figure 10d-f) and in the mouse heart, thereby revealing fibrous layers with varying fiber orientations [69; 70]. In rabbit hearts, the geometry of the perfusion border zone was investigated using PS-OCT and tissue clearing [206], and tissue discrimination was enabled by PS-OCT in rat hearts where decreased birefringence was observed in infarcted hearts [207].
## 1 Introduction
### Communication Issues
#### 1.1.1 Connection Requirements  
Three categories are mainly identified [20]:  
* _None_. Robots are not required to communicate.
* _Event-based connectivity_. The need for regaining connectivity is triggered by particular events such as the discovery of new information or just periodically.
* _Continuous connectivity_. Every robot must be connected at all times to any other fleet member either directly or in a multi-hop manner.  
Please note that these requirements could have an impact on the fleet mobility and, in turn, on the availability of exploration strategies to be adopted. For instance, under a continuous connectivity scheme, the fleet is more restricted to move around than in other cases.
## 3 Results and Discussion
### Effect of Coir Fiber Addition on the Crystal Structure of Geopolymer Specim  
Figure 11 reveals the XRD patterns obtained for MK-based geopolymer specimen without coir fibers (MGP Control) and a geopolymer formulation with pre-treated coir fibers (MGP--1% PCF). The diffuse hump/halo peak present at the two-theta (20) range 18\({}^{\circ}\)-38\({}^{\circ}\) confirmed the transformation of the MK precursor material and the formation of geopolymer paste [14]. It is unclear as to whether crystalline zeolitic phases formed with the amorphous binder phase. The main crystalline phases identified in the two samples were hydroxysodalite, herschelite, cristobalite, sanidine, quartz (SiO\({}_{2}\)), and mullite (3 Al\({}_{2}\)O\({}_{3}\cdot\)SiO\({}_{2}\)), with hematite (Fe\({}_{2}\)O\({}_{3}\)) appearing in a small amount [14; 31]. Quartz was the most widely found phase in the formulations, having 20 at 21.5\({}^{\circ}\), 27.5\({}^{\circ}\), and 38\({}^{\circ}\). In addition to the quartz phases, mullite phases were found at approximately 16\({}^{\circ}\), 32\({}^{\circ}\), 42\({}^{\circ}\), and 58\({}^{\circ}\) 20. The crystalline phases in the MGP Control were not altered due to the presence of coir fibers that act as reinforcing elements in the geopolymer matrices. It shows that fiber and matrix phases do not react during the geopolymerization process but act as inactive fillers in the geopolymer network. Furthermore, geopolymers with coir fiber addition were more crystalline than the pure MK-based geopolymer, suggesting that the formation of amorphous phases via geopolymerization was less when fibers were added. However, comparing the intensities of the crystalline peaks of the two formulations, a decrease in the intensities of crystalline peaks at 16\({}^{\circ}\), 19\({}^{\circ}\), 27.5\({}^{\circ}\), 32\({}^{\circ}\), and 51\({}^{\circ}\) 20 were observed as coir fibers were added into the matrices of the formulation (MGP--1% PCF). On the other hand, an increase in peak intensities was seen in 28\({}^{\circ}\) and 33\({}^{\circ}\) 20. In addition, the coir-fiber-reinforced metkaacolin geopolymer composites showed new crystalline peaks at 57\({}^{\circ}\) and 59\({}^{\circ}\) 20. These differences may have contributed to improvement in the mechanical properties of the geopolymer composite.  
\begin{table}
\begin{tabular}{c c c c} \hline
**S/N** & **Sample Formulation** & **Transmission Time (\(\mu\)s)** & **UPV (m/s)** \\ \hline
1 & MGP control & 21.6 & 2315 \\
2 & MGP—0.5\% PCF & 18.4 & 2717 \\
3 & MGP—1\% PCF & 18.6 & 2688 \\
4 & MGP—1.5\% PCF & 19.4 & 2577 \\
5 & MGP—2\% PCF & 20.2 & 2475 \\ \hline \end{tabular}
\end{table}
Table 5: Ultrasonic pulse velocity (UPV) of samples.