esa-sceva/satcom-chunk-collection huggingface dataset:
# Photogrammetric Measurement and Analysis of the Shape Profile of Pneumatic Artificial Muscles
## 5 Analysis
### Shape Profile Analysis  
#### 5.1.1 Profile Average Diameter  
The average (mean) diameter is easily calculated from the raw shape profile data (Figure 13), and is the simplest representation of a shape profile for analysis. The mean diameter of the entire length of each traced outline is calculated. With the average defining a single diameter value for each profile, the resulting assumed cylindrical profile is in contrast to the complex curvature of the measured profile (Figure 14b). The average profiles result in average diameters that are about 10% below the maximum diameter due to the dramatic decrease in diameter at each end of the PAM in proximity to the end-fittings. The average diameter was calculated for the entire contraction range of the PAM at each pressure (Figure 15a). The results suggest that the radius is nominally independent of internal pressure. Closer inspection of the average diameters, however, reveals small increases in diameter with pressure. This is especially apparent in the zero-contraction state, where the diameter swells by about 0.5 mm from 20 psi to 100 psi. This appears to capture the affect of tensile stretching of the braid, a phenomenon that had not previously been captured. Stretching of the braid has often been ignored with a rigid braid assumption, but has also been accounted for--without the benefit of having quantitative data--in some modeling efforts [1; 27]. Further investigation of the apparent increase of the braid diameter at fixed length states with increases in pressure warrants further investigation in future work.
# Design of Tunable Broadband Graphene-Based Metasurface with Amplitude-Phase Modulation
## 3 Unit Design of Proposed Graphene-Based Metasurface
Additionally, when the metasurface was hit by a TM polarizing wave, the transmission amplitude of the unit 1 approached 0.5 around 95 GHz. The phenomenon reveals that half of the electromagnetic wave energy passed through the metasurface. This is one of the reasons that the reflection amplitude of the two units for electromagnetic waves decreased in the 92.5-99.3 GHz band. Secondly, Figure 4c shows that the phase of coding unit \"1\" and coding unit \"0\" mutated around 95 GHz. When the metasurface unit reflected an incident electromagnetic wave, the phase and amplitude changes interacted with each other, leading to the phenomenon that the amplitude decreased and then increased in the 92.5-99.3 GHz band for both types of coding units. In addition, due to the insertion of feeder posts and perforated structures, there was a certain reflection loss in the unit within that frequency band. As the frequency changed, the reflection pattern also changed, resulting in a sudden decrease in reflection amplitude. In Figure 4c, the phase relationship between the two coding units is depicted, revealing a phase difference between the units in the non-shaded region (75-91.5 GHz and 99.3-115 GHz). In summary, the proposed graphene metasurface unit can be effectively coded for joint amplitude-phase modulation within the frequency bands of 75-91.5 GHz and 99.3-115 GHz.
# Electrochemical Biosensors Based on Conducting Polymers: A Review
## 2 Preparation of Sensitive Materials
### Strategies for immobilizing Biological Sensing Elements into Conducting Polymers
Thus, a polymer film containing biomolecules is formed at the electrode surface. Entrapment is an interesting technique since it leads to a strong adhesion between biomolecule and polymer film in a single step. Additionally, this strategy includes the possibility of controlling the amount of entrapped biomolecules simply by controlling the thickness of the electrodeposited polymer film. Entrapment generally leads to biosensors with a good sensitivity and a long lifetime. On the contrary, entrapment can generate problems associated with inaccessibility of the embedded biomolecule. Additionally, some conducting polymers require very acidic conditions or high oxidation potential during the electropolymerization process to be prepared but these conditions are not favorable to biomolecules [80]. It is also important to note that supporting electrolytes are usually used during the electropolymerization process to increase the conductivity of the monomer solution. Besides, the electrolytes tend to compete with the biomolecules for the polymer doping sites, and so reduce the amount of biomolecule entrapped which is a problem especially for costly biomolecules. A solution to this problem is the use of biomolecules as counter-ions during the growth of the conducting polymer film to allow a more efficient entrapment as previously done with polypyrrole and GOx enzyme [81]. To enhance the incorporation of enzymes into polymers during their electropolymerization, it is also possible to use sinusoidal voltages as evidenced by [PERSON] et al. who developed dopamine biosensors based on tyrosinase entrapped into PEDOT film [82].
## 2 Experimental Section
### Experimental Equipment
\begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Material Number** & **\#1** & **\#2** & **\#3** & **\#4** & **\#5** \\ \hline Screen size range (mm) & 0.653–0.855 & 0.527–0.653 & 0.377–0.527 & 0.177–0.265 & 0.140–0.177 \\ Particle diameter (mm) & 0.744 \(\pm\) 0.061 & 0.632 \(\pm\) 0.046 & 0.454 \(\pm\) 0.046 & 0.235 \(\pm\) 0.025 & 0.164 \(\pm\) 0.015 \\ Bulk density (kg/m\({}^{3}\)) & 1579 \(\pm\) 2.1 & 1498 \(\pm\) 2.7 & 1500 \(\pm\) 2.3 & 1420 \(\pm\) 0.5 & 1471 \(\pm\) 3.3 \\ Static voidage (\(\cdot\)) & 0.344 \(\pm\) 1.7 \(\times\) 10\({}^{-3}\) & 0.378 \(\pm\) 2.0 \(\times\) 10\({}^{-3}\) & 0.377 \(\pm\) 1.9 \(\times\) 10\({}^{-3}\) & 0.410 \(\pm\) 1.6 \(\times\) 10\({}^{-3}\) & 0.389 \(\pm\) 2.2 \(\times\) 10\({}^{-3}\) \\ Sphericity (\(\cdot\)) & 0.979 \(\pm\) 0.031 & 0.966 \(\pm\) 0.055 & 0.970 \(\pm\) 0.058 & 0.903 \(\pm\) 0.162 & 0.992 \(\pm\) 0.037 \\ Angle of repose (\(\cdot\)) & 24.1 \(\pm\) 0.23 & 23.3 \(\pm\) 0.15 & 26.2 \(\pm\) 0.11 & 24.3 \(\pm\) 0.30 & 23.8 \(\pm\) 0.12 \\ Hausner ratio (\(\cdot\)) & 1.011 \(\pm\) 0.8 \(\times\) 10\({}^{-3}\) & 1.039 \(\pm\) 1.1 \(\times\) 10\({}^{-3}\) & 1.035 \(\pm\) 0.3 \(\times\) 10\({}^{-3}\) & 1.077 \(\pm\) 0.8 \(\times\) 10\({}^{-3}\) & 1.058 \(\pm\) 0.3 \(\times\) 10\({}^{-3}\) \\ Material mass (kg) & 2/2.5/93.5/4 & 2/2.5/93.5/4 & 2/2.5/93.5/4 & 2/2.5/93.5/4 & 2/2.5/93.5/4 \\ Geldart particle type (\(\cdot\)) & D & B & B & B \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Physical properties of materials and Geldart particle type. Figure 2: Microscopic photograph of experimental particles. According to the Geldart classification method [33], #1 was class D particles, and #2-#5 were class B particles, where #2 was very close to the BD boundary. According to common knowledge in the field of fluidization, the main characteristic of class B and D particles is that there is no obvious expansion before the fluidization occurs. Additionally, the minimum bubbling velocity and the minimum fluidization velocity are the same; in other words, there is almost no particulate fluidization process in the fluidized bed.
# Data Security-Based Routing in MANETs Using Key Management Mechanism
## 4 Simulation Environment and Performance Metrics
### Simulation Environment  
The proposed model is implemented on the NS2.33 simulator using Ubuntu 16.04. Initially, the existing C++ code is modified to implement the trust-based scheme. Thereafter, various scenarios are generated and implemented in Tool Command Language (TCL) to run the simulation. The source code mainly involves a hello packet and the transmission of receiving RREQ and RREP packets (refer [36, 37]). Hello packets are used to carry the values of the parameters needed to work out on the dynamic trust of the neighbor node, while the RREQ and RREP packets are used to carry the trust values for mutual authentication. RREQ packets are used to request and RREP packets are used to send the trust value between communicating pair nodes. The simulation is achieved by using online libraries and by re-using code, modifying the AODV member functions. The modified code allows the AODV to carry the trust information (refer [38, 39]). NS2 script is used to build the network scenario and CBR is used as a traffic generator. A number of nodes, speeds, cover areas, and simulation times are used as parameter types to test the proposed scheme. A wireless channel, using 802.11 as the MAC protocol, is used to run the proposed scheme. Table 1 shows the simulation parameters.  
Figure 6: Proposed data-communication framework.
## 2 Combined Seal Structure and Material Parameters
### Combined Seal Structure Operating State  
As shown in Figure 2, the combined sealing structure in this study comprises three distinct operating states: installation, inflation, and deflation. Figure 2a shows the installation process of the combined sealing structure. During this process, the gasket is placed into the groove of the piston, then the O-ring is deformed and installed in the groove. Finally, the steel shell moves 6 mm downwards to the station at the speed of V\({}_{0}\) = 6 mm/s, and the rubber O-ring is compressed.  
The inflation state of the combined sealing structure is shown Figure 2b. The steel shell initiates inflation after moving 2 mm downwards to the lower station at the speed of V\({}_{1}\) = 2 mm/s. The exposed boundary of the upper half of the O-ring is subjected to gas pressure and moves downward. On the other hand, the deflation state of the combined sealing structure is shown in Figure 2c. In this state, the steel shell initiates deflation after moving 2 mm upwards to the upper station at the speed of V\({}_{2}\) = 2 mm/s. The exposed boundary of the lower half of the O-ring is subjected to gas pressure and moves upward to contact with the gasket. The function of the gasket is to optimize the stress characteristics of the O-ring.  
Under the function of gas pressure, the O-ring is in close contact with the piston groove and the surface of the steel shell. There are two primary sealing surfaces based on the operating state of the combined sealing structure. The contact surface between the left side of the O-ring and the steel shell is denoted as contact surface I, while the contact surface between the right side of the O-ring and the piston is denoted as contact surface II.  
Figure 2: Three operating states of the combined sealing structure: (**a**) installation; (**b**) inflation; (**c**) deflation.
# Design of Infinite Impulse Response Filters Based on Multi-Objective Particle Swarm Optimization
## 2 Methodologies and System Description
### Band-Pass Filter  
The core of a band-pass filter is also represented through mathematical formulas like transfer functions and difference equations, as mentioned in Section 2.1. The frequency response of a band-pass filter is a crucial characteristic that describes how the filter affects the amplitude of signals at different frequencies.  
However, a band-pass filter focuses explicitly on two frequency points: the lower cutoff frequency \(\omega_{l}\) and the upper cutoff frequency \(\omega_{h}\). The design aims to allow signals within these frequency ranges to pass through while attenuating signals outside this range. The filter's bandwidth (\(B_{h}\)) is given by Equation (5), and the center frequency (\(\omega_{c}\)) is given by Equation (6) [15].  
\[B_{h}=\omega_{h}-\omega_{l} \tag{5}\]  
\[\omega_{c}=\frac{\omega_{h}+\omega_{l}}{2} \tag{6}\]
## 3 Results and Discussion
### Measurement Results
#### 3.2.1 Reflection Coefficient and Impedance Bandwidth  
Figure 19 depicts the measured S\({}_{11}\) for the BSA in free space, including on the human chest and arm phantoms. Simulated and measurement results are in good agreement. The BSA was tested on two human bodies with two diverse weights of up to 65 and 110 (in kg), and it performed similarly to that measured in the free space. Initially, the BSA was almost flat when placed on the chest. The flatness of the body, the air gap between the body and the BSA, and any layers between the body and the BSA created a similar condition to the free-space scenario. The air gap was kept around 5 mm. Similarly, for the second round of testing, the BSA was wrapped around the arm while retaining the same air gap as before. The measured S parameter showed that the impedance bandwidth was not significantly altered. Bending of the BSA and body humidity (sweating) are two other situations that could cause changes in performance. In these two conditions, the lower and upper frequency bands were still covered by the BSA, and no significant variations in the reflection coefficient (S\({}_{11}\)) were observed.  
The investigation was conducted at several locations under bending conditions. The BSA was measured in free space as well as on polystyrene cylinders with a dielectric constant of \(\varepsilon_{\mathrm{r}}\approx 1\) and diameters of \(D\)\((\mathrm{in\leavevmode\
obreak\ mm})=100,\leavevmode\
obreak\ 80,\leavevmode\
obreak\ 70, \leavevmode\
obreak\ 60,\leavevmode\
obreak\ \mathrm{and}\leavevmode\
obreak\ 50\). The different diameters produce different curvatures, which were used to see if the required frequency range is maintained whilst bending. Therefore, there was a slight shift in the resonance frequency. As illustrated in Figure 20, the measured S\({}_{11}\) shows that the antenna is matched well within the desired frequency bands.  
Figure 19: Measured S\({}_{11}\) of the BSA in free space and on-body (chest and small and large size arm diameter of 50 mm and 100 mm, respectively).  
The humidity of the body may have a big impact on wearable antennas. As indicated in Figure 21, the proposed work investigated the case when the BSA was dampened by moisture by applying water on the textile layer until it was fully saturated. The damp condition had a significant impact on S\({}_{11}\). Water evaporation from the entire substrate may take up to 3 h. The results show that after 1 h and 2 h, the center frequency is still shifted and that after 3 h, the BSA returned to dry conditions with a room temperature of 26 \({}^{\circ}\)C and a 30% air humidity.  
Figure 20: Measured S\({}_{11}\) of the BSA under bending with different cylindrical curvatures (D (dia, in mm) : 50, 60, 70, 80, and 100).  
Figure 21: Measured S\({}_{11}\) of the BSA in wet situations (dry, after 1 h (1 Hz), 2 h (2 Hrs), and 3 h (3 Hrs)).
# Analysis of Coastal Zone Data of Northern Yantai Collected by Remote Sensing from 1990 to 2018
## 3 Results
### Characteristics of Coastline Changes
#### 3.1.2 Spatial and Temporal Variation Characteristics of the Coastline  
The end point change rate (EPR) and linear regression rate (LRR) were used to study and analyze the coastline changes of counties and municipalities in the northern region of Yantai from 1990 to 2018. Figures 6 and 7 show that the coastline generally shows a trend of growth extending to the sea, but the trend of coastline changes in different counties and municipalities is different. The coastline changes in Laizhou, Longkou, Penglai, and Zhifu are more noticeable.  
From 1990 to 2018, the average annual variation EPR and LRR of the coastal areas in northern Yantai were 6.34 m/a and 7.34 m/a, respectively, and the growth of coastal sediment was dominated by seaward siltation. The annual variation rate of the coastline in each county and municipality ranged from large to small in the following order: Laizhou > Penglai > Longkou > Zhifu > Fushan > Laishan > Mouping > Zhaoyuan. Among them, the annual variation rate of the Laizhou coastline was the largest an EPR of 33.67 m/a and an LRR of 39.37 m/a. The maximum deposition rate of the coastline in the study area also appeared in the coastal section and is located around the northern aquaculture area of Tushan Town, Laizhou with an EPR of 168.88 m/a and an LRR of 200.48 m/a, and the maximum erosion rate of the coastal section was \(-6.37\) m/a (EPR) and \(-5.83\) m/a (LRR). The Zhaoyuan coastline had the smallest annual variation rate with an EPR of \(-1.91\) m/a and an LRR of \(-1.37\) m/a. The maximum deposition rate of the Zhaoyuan coastline was 7.73 m/a (EPR) and 9.56 m/a (LRR), and the maximum erosion rate was \(-4.93\) m/a (EPR) and \(-4.67\) m/a (LRR). The maximum erosion rates of the coastline in the study area were \(-43.27\)m/a (EPR) and \(-47.41\) m/a (LRR). In the past 30 years, the coastline of Laizhou, Penglai, Longkou, and Zhifu has become the fastest-changing area of the coastline of the Jiaodong Peninsula due to the continuous influence of human activities, such as reclamation, artificial island construction, dam construction, and port construction.  
Human activities are irreversible and destructive to coastline changes, and it is difficult to restore the original natural coastline [33]. From the changes in the coastline of different regions, we can see that human activities have the greatest impact on the changes in the coastline. Especially from 2010 to 2015, the flooding of the Laizhou aquaculture area, construction of the Longkou artificial island, coastal construction of Penglai and Zhifu, and expansion of port terminals have made great changes in the coastline. However, since 2015, due to the public's awareness of a series of problems caused by the destruction of the coastline and reduction of marine resources, various departments have strengthened the control of coastal areas, increasing the control coastline changes and protection of the marine ecological environment.
# Drone Deployment Algorithms for Effective Communication Establishment in Disaster Affected Areas
## 4 Experiments and Results  
We conducted various experiments using the terrain data of the landslide-affected region of Pettimudi, Kerala, India, for drone deployment to establish communication. We considered homogeneous drones with similar parameters. The various parameters we used (environmental and drone specific) are shown in Tables 2 and 3.  
We fix \(H_{max}\) as 2 km. The disaster affected area of Pettimudi is obtained from Google Maps. We consider base stations at diagonally opposite corners, with the first at (9.9913888888888, 76.931666666667) and the second at (10.027500000002, 76.968 the data structure _HeightMatrix_ (_H_). We use the altitude of the nearest point in the matrix for missing altitude data of any point.  
We apply the region-filling algorithm for the area and obtain the coverage and drone positions, as shown in Figure 17. It is found that sixteen drones are needed to cover the region effectively. The various parameters, specific to Pettimudi, found are shown in Table 1 of Appendix A.
## 2 Strengthening Techniques
### Local Strengthening  
Due to the masonry's limited tensile and shear strength, most techniques address this issue by adding specific types of reinforcements on the external surfaces of the walls or within the interior. This reinforcement is capable of withstanding tensile stresses, delaying the occurrence of cracks, restricting their propagation, and increasing the deformation capacity of the material [3].  
When a wall loses its mortar and contains voids, the most common repair method is the repointing and injection of a fluid with some type of binder agent, such as cement- or lime-based grouts [3; 24; 25]. It is important to note that compatibility must be considered, since this is an irreversible intervention [25]. the presence of multi-leaf (two or three leaves) walls in historical buildings is frequent. If the leaves are weakly connected, the carrying capacity of the wall under lateral and axial forces decreases. The strengthening of these walls is carried out using grout injection or introducing transversal metallic bars (sometimes post-tensioned) or fibres to connect the leaves [3; 24; 25; 26; 27; 28].  
Applying a reinforcing layer to the surfaces is another frequently employed technique. One of the typical reinforcements comprises a steel mesh embedded in mortar or concrete [3; 24; 29]. This technique increases the IP and OOP resistance capacity of the element [3]. The mass increment, irreversibility and possible mechanical incompatibilities are considered factors when applying concrete layers.  
In recent years, fibre-based materials have gained popularity as a reinforcement applied to surfaces given their high tensile strength [3; 30]. The most frequent fibres are made from a variety of materials, including carbon, glass, basalt, aramid, polymers, and even natural fibres [3; 31]. Two primary systems are commonly used for reinforcement. Fibre-reinforced polymers (FRP) are fibre sheets or strips where the fibres are embedded in a resin matrix, which are then bonded to masonry using an epoxy binder [3]. In textile-reinforced mortar TRM, fibres are arranged to form a mesh that is applied to masonry with cement- or lime-based mortar [3; 30]. These systems significantly improve the OOP and IP response of these structural elements [3; 30; 32; 33; 34].  
Internal reinforcement serves as an alternative when surface interventions are not permitted due to concerns about their impact on the structure's aesthetics [3]. This technique involves drilling vertical holes along the height of the wall to introduce steel bars. The bars can act as passive elements or be post-tensioned (active elements) [35]. If properly executed, the wall can resist both IP and OOP actions [3].
## 1 Introduction
Using the most predominant environmental impact indicator, global warming potential (GWP), the impact per unit volume of the concrete mixes varied between 110 and 600 kg eq CO\({}_{2}\)/m\({}^{3}\), as shown in Figure 3. Assuming the results from these values have a normal distribution, the mean value would be around 320 kg eq CO\({}_{2}\)/m\({}^{3}\) while the standard deviation would be around 90 kg eq CO\({}_{2}\)/m\({}^{3}\). This is indicative of large discrepancies that could challenge the original argument that these concrete mixes cause less environmental impact compared to OPCC. Nonetheless, the absolute values communicated for the OPCC using the same indicator (GWP) were found to also vary widely. Upon reviewing 80 mixes from 20 papers, the mean value was found to be around 370 kg eq CO\({}_{2}\)/m\({}^{3}\) with a standard deviation of around 110 kg eq CO\({}_{2}\)/m\({}^{3}\), as shown in Figure 3. Therefore, this systematic review paper was presented in order to critically examine each stage of the LCA studies carried out by researchers in the domain of green concrete in order to identify the sources of the discrepancies. [PERSON] [60] attributes these large discrepancies to the uncertainties involved in the current use of LCA methodology. [PERSON] [61] claim that the source of these uncertainties are modelling choices by the user of the system boundary, FU and source of data. On the other hand, [PERSON] [27] differentiates between the uncertainties due to the nature of the inventory data used and those from choices such as the impact allocation and FU. The first affects the precision of the results due to the fact that the elements included in the study include a percentage of uncertainty, while the latter affects the reliability of the study. Hence, in this paper, which is the first of its kind to systematically tackle the sources of discrepancies in concrete LCA studies, the same categorization will be followed. Hence, the objective of this review was to provide the concrete LCA user with a coherent, state-of-the-art guide to avoid the sources of reliability error and to solve the issues caused by the sources of uncertainty. Figure 3: A review of the values for the equivalent kg CO\({}_{2}\)/m\({}^{3}\) of: (**a**) 80 Ordinary Portland Cement Concrete (OPCC) mixes and (**b**) 300 mixes of all 5 concrete types studied from the literature.