esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction  
A wireless sensor network (WSN) is a network of wirelessly interconnected devices that are spread over an area of interest. The constituting elements of a WSN are the sensor nodes and at least one sink node, called the base station. A typical sensor node is a micro electromechanical system (MEMS) that, despite its constrained resources in terms of power, memory, communication, and computation, is able to perform sensing, data processing, and communicating tasks. A base station is device rich in energy, computational, and communication resources that collects the data transmitted to itself, by the sensor nodes, and acts as a supervisory controller of the WSN, an access point for human interface, and a gateway to other networks [1; 2]. A WSN, based on the combinational use of its sensor nodes and its base station(s), is able to monitor the ambient conditions over wide regions of interest and send relevant information to distant destinations. This is why WSNs are considered to be the core of Internet of Everything (IoE) and support an endlessly evolving range of human activities related with industry, agriculture, surveillance and reconnaissance, smart homes, smart cities, environment and habitat monitoring, biomedical applications, military applications traffic control, fire detection, inventory control, agriculture, machine failure diagnosis, and energy management applications [3; 4; 5; 6; 7; 8; 9; 10].  
On the other hand, the aforementioned limitations of the sensor nodes in terms of their resources, and the inborn constraints of wireless communication channels, regarding power, speed, robustness, and capacity, obstruct the operation of WSNs and raise several issues that need to be addressed.  
Among them, a major subject of research is the coverage problem. It can be stated as the problem of positioning a given number of sensor nodes with a given range of sensing in an optimal pattern in order to maximize the proportion of the area covered by them and thus minimize the holes of coverage. Various methodologies for coverage maximization have been proposed [11; 12; 13; 14; 15]. In the research work presented in this article, the solution to this problem has been pursued based on two Computational Intelligence algorithms. The efficacy of these two algorithms has been investigated in comparison not only against each other but also contrary to two other well-known algorithms.  
In this context, the rest of this article is organized as follows. In Section 2, the theoretical background regarding the topic under investigation is established. In Section 3, the algorithms developed are described. Both the simulation procedure developed and the corresponding results produced are presented in Section 4. In Section 5, the performance of the algorithms developed is evaluated and discussed. Finally, in Section 6, concluding remarks are drawn and future research topics related to the area coverage problem are identified.
# Agile Stage-Gate Approach for Design, Integration, and Testing of a 1U CubeSat
## 2 Materials and Methods
### Testing Development Process
Temperature sensors were used for control and monitoring, as described in Figure 9. Table 4 outlines the positions of the sensors. \begin{table}
\begin{tabular}{c c c} \hline \hline \multirow{2}{*}{**Axis**} & \multicolumn{2}{c}{**Frequency and Levels**} \\ \cline{2-3}  & \multicolumn{2}{c}{**Random Vibration Test**} \\ \multicolumn{3}{c}{} \\  & \multicolumn{2}{c}{**(20-2000 Hz)**} \\ \hline \multirow{4}{*}{\(X\)} & 20–50 Hz & 4.000 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 63 Hz & 4.490 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 80 Hz & 5.062 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 100 Hz & 5.660\(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \hline \multirow{4}{*}{\(Y\)} & 125–200 Hz & 6.200 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 250 Hz & 5.558 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 315 Hz & 4.102 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 400 Hz & 2.998 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 500 Hz & 2.230 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 630 Hz & 1.651 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 800 Hz & 1.206 \(\times\)\(10^{-2}\) g\({}^{2}\)/Hz \\ \hline \multirow{4}{*}{\(Z\)} & 1000 Hz & 9.000 \(\times\)\(10^{-3}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 1250 Hz & 6.034 \(\times\)\(10^{-3}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 1600 Hz & 3.870 \(\times\)\(10^{-3}\) g\({}^{2}\)/Hz \\ \cline{2-3}  & 2000 Hz & 2.600 \(\times\)\(10^{-3}\) g\({}^{2}\)/Hz \\ \hline \multicolumn{3}{c}{Overall: 5.76 g rms} \\ \multicolumn{3}{c}{} \\ \multicolumn{3}{c}{} \\ \multicolumn{3}{c}{} \\ \multicolumn{3}{c}{} \\ \multicolumn{3}{c}{} \\ \multicolumn{3}{c}{} \\ \end{tabular}
\end{table} 
Table 3: AztechSat-1 random vibration profile. Figure 9: Temperature data acquisition system for AztechSat-1.
# Integrated Robotic and Network Simulation Method
## 4 A Case-Study Illustrating the Use of the IRoNS Method
### Problem Formulation  
The method workflow starts from a stated problem, which, in this context, involves cooperative robots and communication network topics. We define the comparison of control strategies as the target, including an assessment of their performance under network faults.  
This problem needs to be further specified, as stated in the method first step. It is possible to choose any combination of algorithms and parameters. In this case, for simplicity sake, we chose to work with a limited group of 10 terrestrial and homogeneous mobile robots, executing a decentralized rendezvous task. These conditions were determined by convenience and do not represent a limitation of the framework. For example, considering more and heterogeneous robots can be accommodated at the cost of increasing the simulation complexity and thus the time needed for its execution.  
In cooperative robotics, the rendezvous is a cooperative task where robots must agree on a meeting point and reach it without breaking communication links. This is a trivial problem in centralized cooperation, however it may become challenging as a consensus problem with decentralized cooperation, in which robots can only receive information through their direct communication neighborhood [34].  
From the communication network side, a decentralized solution is desired, too, given its flexibility with respect to topology and resilience to network faults, which is particularly relevant for wireless communication with a simple communication topology management. The network model is based on OMNET++/INET IEEE802.11 (Wi-Fi). Other protocols can be used if available in the network simulation framework. For example, OMNET++/INET also supports Zigbee [35] and LORA [36].
# Current Trends in Fluid Viscous Dampers with Semi-Active and Adaptive Behavior
## 3 Semi-Active Fluid Viscous Dampers
### Rheological Fluid Viscous Dampers
#### 3.1.4 Applications of ER and MR Dampers  
MR devices have been used in several engineering fields, which range from the industrial area [137; 138], where they are employed as vibration dampers in washing machines or seat dampers for commercial vehicles, to the automotive area [139; 140; 141], in which they are used as semi-active suspensions for vehicles, and to the aerospace field [142; 143; 144], where they are employed as landing gears or helicopter rotors. MR dampers were adopted in the civil engineering field to protect structures from earthquakes and wind [145; 146; 147]. In 2001, [PERSON] et al. [147] studied and developed an MR damper able to provide a maximum damping force of 300 kN. Two devices were installed in the Tokyo National Museum of Emerging Science and Innovation between the third and fifth stories, as shown in Figure 19a. MR dampers were also used for the protection of bridges from wind and seismic excitations. [PERSON] et al. [148] installed 312 MR dampers, produced by the Lord Corporation, on the 156 stay cables of the Dongting Lake cable-stayed bridge (Figure 19b) since the structure was too sensitive to vibrations induced by rain and wind. Thanks to the installation of MR devices, the vibrations of the cables and the deck were consistently reduced.  
On the other hand, ER devices did not find widespread commercialization because of their weak yield stress, low supsensibility, and low stability [149].  
In 2003, [PERSON] et al. [150] presented an ER fluid characterized by a yield strength of 130 kPa [149; 151], which was considerably higher compared to that of classic ER fluids, ranging in the order of a few kPa (e.g., the ER device presented by [PERSON] was characterized by a yield strength of 13 kPa [118]). Therefore, the new ER fluid was called giant electrobiological (GER) fluid. Its behavior was similar to the other ER fluids, with a viscosity that increased with the strength of the electric field. Devices filled with GER fluid are able to produce a high damping force with a low stiffness effect. Moreover, these devices can adapt their behavior by requiring a lower power consumption [152].  
After the study of [PERSON] et al. [150], other devices with GER fluid were presented [153; 154]. An example is the damper studied by [PERSON] et al. [153], who exploited the shear mode mechanism; experimental results showed the capacity of these systems to dissipate vibrations up to  
Figure 18: Model proposed by [PERSON] et al. [129]: (**a**) rheological model (adapted from [129]); (**b**) force–velocity response.  
90%, with a limited stiffness effect. [PERSON] et al. [154] proposed a device made of GER fluid that works with the squeeze mode mechanism; however, this system is addressed for applications in the robotic and bionics fields; therefore, further research is necessary to extend its use to the civil engineering area.
## 2 Materials and Methods
### Datasets and Data Processing  
#### 2.2.1 In Situ Measurements  
In this study, in situ data of precipitation for the 2010-2016 period were provided by the General Directorate of Meteorology (GDM) of Burkina Faso (BF), as previously used by [22]. It consists of 134 stations, which are relatively well spread over the country except for less density in the north of BF also called the Sahel zone (SH) and the eastern part of the Sudan-Sahel zone (SS) of the domain (Figure 3). All stations include a daily time series of good quality (with few missing data) over the considered period. The in situ measurements of SW\({}_{\text{in}}\) are also from the GDM with data available every 15 min for 4 stations (Figure 4). In the present study, 24 h-mean values of these radiative fluxes are used.  
Figure 2: Diagram depicting the sequential cycle of LDAS-Monde using an SEKF. The forecast step consists of propagating the analysis at previous time step to the next one using the ISBA LSM. The analysis step corrects the forecast by assimilating observations. The SEKF involves the computation of a Jacobian matrix obtained through perturbed model runs initialized by the analysis at a previous time step slightly perturbed by a small amount (\(\delta\)x\({}_{1\ldots 8}\)). The number of perturbed model runs is equal to the number of control variables (in our case, eight variables).
## 6 Conclusions  
Based on computational fluid dynamics and the discrete element method, the interactions between proppant and proppant, proppant and fluid, and proppant and fracture wall surface were considered to establish a fluid-solid coupling model of proppant transport. Through a numerical simulation of proppant transport, the effects of the fracturing fluid viscosity and proppant density on the proppant transport law were analyzed. The conclusions are as follows:  
1. As the viscosity of the fracturing fluid increases, the suspending performance of the fracturing fluid to the proppant increases, the length of the \"sand-free zone\" increases, and the proppant particles can be transported to the far position in the fracture, increasing the length of the dune. In order to achieve effective proppant placement, the fracturing fluid viscosity ratio should be maintained between 2 and 5.
2. As the proppant density increases, the height of the dunes increases and the length of the dunes decreases. The proppant tends to deposit at the fracture inlet, resulting in an increase in the static pressure of the fracture inlet. Injecting only one type of density proppant is not conducive to obtaining an effective proppant placement.
3. A novel fracturing method with variable viscosity fracturing fluid and variable density proppant was proposed. High-viscosity fracturing fluid and low-density proppant should be pumped first to increase the distance of proppant placement and increase the effective fracture stimulation area. Thereafter, low-viscosity fracturing fluid and high-density proppant are pumped to form fractures with high conductivity in the near-well zone, effectively improving the near-well zone.
4. This novel method has been successfully applied to more than 10 oil wells of the Bohai Bay Basin in eastern China, and the average daily oil production per well has increased by 7.4 t, significantly improving the performance of fracturing.  
Conceptualization, C.L., L.M. and Z.L.; methodology, C.L., L.M. and Z.L.; software, L.M. and Z.L.; validation, L.M., Z.L. and C.H.; formal analysis, L.M. and Z.L.; investigation, L.M., Z.L. and C.H.; resources, C.L., H.Y., Z.T. and J.G.; data curation, C.L., L.M. and Z.L.; writing--original draft preparation, C.L., L.M. and Z.L.; writing--review and editing, L.M. and J.G.; visualization, F.H. and C.H.; supervision, C.L. and J.G.; project administration, C.L., H.Y., Z.T. and J.G.; funding acquisition, C.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by National Natural Science Foundation of China (grant number 51704251), National Science and Technology Major Project of the Ministry of Science and Technology of China (grant number 2016 ZX05006002), and National Science Fund for Distinguished Youth Scholars (grant number 51525404).  
The authors wish to thank the State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation at Southwest Petroleum University, for providing the experimental platform and simulation software.  
The authors declare no conflict of interest.
## 4 Energy Efficiency Optimization
* In EE optimization, the optimal number of active antennas, i.e., \(\bar{N}_{x}\bar{N}_{y}\), is a non-increasing function of transmit power constraint \(p_{\max}\) and the circuit power consumption \(p_{\text{ant}}\). In particular, when the circuit power consumption is dominant, (44) reduces to \(\bar{N}_{x}\bar{N}_{y}=\mathcal{N}_{\text{LB}}\), which becomes independent of \(p_{\text{ant}}\). In this case, by substituting (40) into the constraint \(C_{2}\) of (38), we can see that the sum transmit power constraint of AP holds with equality. This means that, to control the total circuit power consumption, AP should use its maximum transmit power to reduce the number of active antennas.
## 3 The Proposed FED-XAI Framework for QoE Predictions in V2X Environments
### Feeding Models with Real Network Data  
AI-based algorithms need to be fed with real data and collecting live measurements from the MNO network is critical for the reliability of the produced output. In that perspective, the Minimization of Drive Tests (MDT) functionality is applied on TIM Radio Access Network (RAN) to acquire geolocated real data from live RAN. MDT is a 3 GPP standard feature (TS 37.320) which allows collecting geolocated radio measurements from UEs in both idle and connected states [25]. This enables UEs to periodically send a large set of measurements from Layer 2--MAC (3 GPP TS 36.321), and Layer 3--Radio Resource Control (3 GPP TS 36.331). UEs take those measurements for standard procedures, such as cell re-selection, handovers, quality reporting, etc. With MDT, UEs keep measuring the same quantities but share their measurements periodically with the network. If a Global Positioning System (GPS) receiver is enabled, UE measurements are geolocated, which allows anonymous data collection for statistical analysis. MDT paves the way for replacing traditional time-consuming drive tests, made by few test UEs, with thousands or millions of measurements, reported by most devices in the network. Moreover, MDT data come from several customers and UE types, thus allowing a realistic insight into user QoE. MDT measurements in this work mainly refer to geolocated UE throughput and data volume metrics. Examples of MDT georeferenced data from the TIM live network are reported in Figure 5 for the area around Venice, where every pixel represents 1 m\({}^{2}\) of the area, and MDT data in each pixel are averaged and normalized to all MDT data collected in all pixels.  
Most MDT data are geolocated in the sea and Venice channels too. This highlights the capability of MDT data to represent the real traffic scenario. The real radio coverage map of several cells in the 1800 MHz frequency band is reported with different colours. MDT data are completely anonymous because neither customer nor UE identity data are monitored or gathered. In particular, MDT data are only geolocated radio measurements reported by UE. The MDT data on TIM's RAN are gathered by using a Nokia system called Geosynthesis.  
Figure 4: Real and predicted values of QoE for an example UE of the test set (Figure from [24]).  
Figure 5: _Cont._
## 2 Materials and Methods
### TaqMan Assay  
TaqMan real-time PCR assay was used to discriminate SWD from other _Drosophila_ species (non-SWD) at the larval stage through the detection of single nucleotide polymorphism (SNP). This molecular diagnostic technique relies on the amplification of the polymorphic sequence Sec61 (CG9539) with specific primers (Sec61 Forward primer: TGATG-GCCACACAGGAACGAT and Sec61 Reverse primer: GTGTAGAACAGCTTGATGGG) followed by the recognition of the SNP using TaqMan probes labeled with fluorophores. The Sec61 gene from several non-SWD species including _Drosophila melanogaster_ [PERSON], _Drosophila biarmipes_ [PERSON], _Drosophila tristis_ [PERSON], and _D. simulans_ was sequenced and aligned to verify that the region of interest is conserved between non-SWD, and that the SNP is only present in SWD (Figure S1). A FAM-labeled probe was used to detect non-SWD, and a Cal Orange 560-labeled probe was used to detect SWD individuals (FAM probe seq: CCAGAACCTGCCCAAT; Cal Orange 560 probe seq: ACAGAACCTTC-CCAATC). Dry probes (Biosearch Technologies, Petaluma, CA, USA) were resuspended in nuclease-free water at a 10 uM working concentration. A 2 xqPCRbio probe mix (PCR Biosystems, Wayne, PA, USA) was used according to the manufacturer's recommendation using 1 uL of gDNA (at concentration < 1 ug/uL). The TaqMan assay reaction was performed in 96-well plates using a CFX96 thermocycler (Bio-Rad Laboratories, Hercules, CA, USA) with the following settings: 95 \({}^{\circ}\)C for 2 min and 40 cycles of 95 \({}^{\circ}\)C for 5 s (melting) and 58 \({}^{\circ}\)C for 30 s (annealing and extension). Genomic DNA from laboratory-reared samples composed of either six _D. simulans_ (all non-SWD), six _D. suzukii_ (all SWD), or a mix of _D. simulans_ and _D. suzukii_ (5:1, 4:2, 3:3, 2:4, and 1:5 SWD: non-SWD) larvae were used as our standard controls to establish a calibration curve. We obtained a linear regression between the relative fluorescence unit (RFU) values for both FAM and Cal orange 560 according to species composition that was used to determine the threshold of detection for experimental samples.
# Effect of the Sintering Temperature on the Compressive Strengths of Reticulated Porous Zirconia
## 2 Materials and Methods  
In this study, commercial polyurethane foam (SKB Tech, Seoul, Korea) samples 20 mm \(\times\) 20 mm \(\times\) 20 mm in size with pore densities of 25, 45, 60, and 80 PPI (pores per inch) were used as sacrificial polymer templates. Zirconia slurries were prepared to coat the 25, 45, 60, and 80 PPI sacrificial polymer templates.  
Zirconia slurries were prepared with a combination of a dispersant (Dolapix CE 64), thickener (Methyl cellulose) and an organic binder (Polyvinyl alcohol). The dispersant is vital to remove agglomerated zirconia particles and to prepare a uniform zirconia slurry. In previous reports, two types of dispersants were used: Dolapix CE 64 and DARVAN C-N (Vanderbilt Minerals, Norwalk, CT, USA). Dolapix CE 64 and DARVAN C-N are widely used dispersants for dispersing silicon nitride particles, alumina, and zirconia [21; 22; 23; 24]. Dolapix CE 64 is a sodium salt of a polycarboxylic acid, and DARVAN C-N is an ammonium salt of polymethacrylic acid, resulting in different mechanical properties. The dispersant selected was Dolapix CE 64 because the results when using Dolapix CE 64 were superior in previous reports.  
The samples consisted of 3 mol% yttria-stabilized zirconia (Qingdao Terio Corporation, Qingdao, China) at 67.74 wt.%, with 1.00 wt.% Dolapix CE 64 (Zschimmer & Schwarz GmbH Co., Burgstadt, Germany) as a dispersant, 1.67 wt.% methyl cellulose (Sigma-Aldrich, Darmstadt, Germany) as a thickener, 100 mL distilled water, and with 4.76 wt.% polyvinyl alcohol (molecular weight (Mn) approx. 500, Junsei Chemical, Japan) used as an organic binder. The mixed zirconia slurries were ball-milled using zirconia balls for 0, 4, 8, and 24 h. The reticulated porous zirconia specimens were prepared via the replica template method. The sacrificial polymer templates were initially soaked in a zirconia slurry until their internal pores became saturated with zirconia particles. Subsequently, the impregnated sacrificial polymer templates were squeezed to remove any excess zirconia slurry, after which the three sample sets were dried in an oven and sintered at 1400, 1500, and 1600 \({}^{\circ}\)C for three hours. The viscosities of the zirconia slurry were measured using a rotary viscometer (ViscoQC 300, Anton Paar GmbH, Graz, Austria), and the compressive strength levels of the reticulated porous zirconia specimens after processing at a size of 20 mm \(\times\) 20 mm \(\times\) 20 mm were measured with a tensile tester (RB302 Microload, R&B, Daejeon, Korea). The average particle size distributions of the zirconia were determined by a particle size analyzer (LSTM 13 320 MW, Beckman Coulter, Brea, CA, USA). The microstructures were characterized by means of scanning electron microscopy (SEM, JSM-5800, JEOL, Tokyo, Japan). The voltage was set to 20, the working distance set to 9, and the image mode was SE. The pores were characterized by means of mercury porosimetry (Autopore IV 9510, Micromerities, Norcross, GA, USA).