esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Case Study: LCA Results and Discussion
### Cost Assessment  
Figure 6 shows the operating costs of the linear and circular model. The use of dregs and grits in the production of the asphalt mix generates savings (EUR 0.06), due to the partial elimination of the cost of acquiring the natural limestone (0/4 mm) by the asphalt mix producer. Dregs pretreatment in the waste manager facility generates a saving of EUR 0.28 compared to the disposal of the dregs in the landfill, while the transformation of grits in the waste manager generates savings of EUR 0.36 compared to their landfill. Thus, operations (transport, drying, and sieving) that exist between the waste producer and the alternative raw material recipient (bituminous mixture producer) do not produce more costs than the disposal of the waste in landfill.  
The circular model operations of dregs and grits as an alternative raw material generate savings of 3% and 4%, respectively, compared to the linear model operations because dregs and grits are cost-free for the bituminous mix industry and this partially saves on the cost of purchasing the fine aggregate; in addition, the waste producer saves on the disposal costs of landfilling waste.  
The costs of the linear and circular model (Figure 6) come from materials, transport, investment in equipment, rental of equipment, manpower, and energy, as shown in Figure 7. The linear and circular models have no costs arising from waste treatment, external costs, and investment in equipment. However, the value of transport and rental equipment for circular solutions is EUR 0.07 for both wastes and EUR 0.13 (for dregs) and EUR 0.09 (for grits), respectively, compared to the linear transport solution (EUR 0.32) and of the rental equipment (EUR 4.24).  
The value of manpower for grits is the same for the linear and circular model (EUR 1.65), while for dregs it is more expensive (plus EUR 0.02) when compared to the linear solution. This increase with dregs results from the material sieving operation, since the grits do not need this operation. Furthermore, the labor required in the circular grits' solution is the same as in the linear solution.  
On the other hand, circular solutions generate savings in materials (EUR 0.48 for dregs and EUR 0.49 for grits) compared to the linear solution, because wastes are cost-free for the producer in the bituminous industry and so they partially save on the cost acquisition of limestone. Also, there are energy savings in the circular solution (EUR 0.06 for dregs and EUR 0.08 for grits), compared to the linear one (EUR 0.87), because transporting dregs and grits consumes less energy than limestone. Also, the distance for transporting wastes from the circular solution (from waste producer to the bituminous mix central) is reduced by 14 km compared to the linear solution for transporting limestone.  
Figure 6: Cost by operation of linear and circular model.
# Optimization of Multilayer Absorbers Using the Bald Eagle Optimization Algorithm
## 3 Results
### Normal Incidence
#### 3.1.5 Design-5  
A 7-layer MA was designed for applications in the FR of 1-18 GHz. Design-5 has the least total thickness (6.5 mm) and RC (\(-\)18.4311 dB) as compared to a similar design (Table 6). For visual comparison, the RC versus frequency is also illustrated in Figure 9.
# Full Real-Time Positioning and Attitude System Based on GNSS-RTK Technology
## 4 Results
### Precision and Accuracy of Measurements in a Static Configuration  
To perform the static validation, the antennas were installed in different orthogonal configurations (see Table 1 and Figure 6). The general validation method of the system would start with an orthogonal configuration of the antennas parallel to the ground, where the axis formed by antennas 1-2 points to the North and the axis formed by antennas 1-3 to the East. The first angle to be applied is the yaw, rotating all of the configuration over the horizontal plane clockwise (around the \(Z\)-axis of the NED reference system) until axis 1-2 is in the final direction. The second angle to be applied is the pitch angle, rotating the entire system around the axis 1-3 until antenna 2 is in the final position. The last angle to be applied is the roll angle, rotating the system around the axis 1-2 until antenna 3 is in the final position. In the following tests, the system was installed on a roof to keep the antennas' positions fixed and to properly measure the real distances and angles. The results shown do not have any post-processing, only that the time series of each configuration were trimmed to 60 s (300 samples) so that the duration is the same for all tests.  
It can be noticed in Figure 7 how the standard deviation decreases as the distance between antennas increases, as might be expected. Since the antennas are in an orthogonal configuration with axes of equal length, the standard deviations of pitch and roll angles are expected to be similar, as shown in Figure 7. The yaw angle has a lower standard deviation in every configuration. This behavior makes sense, since, for all configurations, the pitch angle is close to zero and the yaw angle is computed as the projection of antenna 2 on the horizontal plane, which means that the variability of the measurements of this receiver on the vertical axis does not affect the yaw measurement.  
Figure 8 shows the average value of the three angles that define the attitude of the solid body (the roof) for each of the configurations. An offset was added to the roll and yaw angles to make the visualization of the three angles in a single figure easier. The roll angle offset is \(14^{\circ}\), which corresponds  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Configuration** & **Receiver Antenna Distance 1–2 [m]** & **Receiver Antenna Distance 1-3 [m]** & **Angle 2-1 and 3-1 [deg]** \\ \hline A & 6.2 & 6.2 & 90 \\ B & 5.8 & 5.8 & 90 \\ C & 5.4 & 5.4 & 90 \\ D & 5.0 & 5.0 & 90 \\ E & 4.6 & 4.6 & 90 \\ F & 4.2 & 4.2 & 90 \\ G & 3.8 & 3.8 & 90 \\ H & 3.4 & 3.4 & 90 \\ I & 3.0 & 3.0 & 90 \\ J & 2.6 & 2.6 &  
Figure 11 show the time series of the three angles for each configuration. The same scaling was used on the y-axis (except in the N configuration) to better appreciate the change in the standard deviation of the measurements.  
Figure 10: Details of the roof irregularities.  
Figure 9: Satellite image of the roof where the static tests were performed. Source: Google Maps.
## 4 Experimental Verification of the Cubic Spring  
To experimentally verify the nonlinear load-deflection curve of Figure 18 for the design of Figure 15, Equation (12) was used to make a cubic spring using an aluminum beam. Figure 25 shows a 1 mm thick, 16 mm wide, and 122 mm long aluminum beam supported by two (16 mm by 16 mm) rectangular aluminum columns or blocks at its edges. The 1 mm aluminum beam was connected to the columns by 4 bolts, as shown in Figure 25. The length of the beam that hangs free from the columns is 90 mm. The center column (16 mm \(\times\) 10 mm wide made from aluminum), shown in Figure 25, represents the piston shaft. Figure 25a shows the 1 mm thick beam supported on two 40 mm long columns, and Figure 25b shows the same beam on two 10 mm long columns.  
The FEA results of Figure 18 indicated that to have a proper cubic stiffness from a beam, it is best to make the beam and the columns as one body and not to use bolts to attach the beam to the columns, as was done in our experiment. Not properly bolting the beam to the columns can result in the beam slipping relative to the columns when loaded, thus affecting the nonlinear stiffness and creating a large hysteresis loop in the load-deflection curve.  
Figure 24: Bottom piston motion at different engine displacement inputs, linear vs. cubic springs.  
Figure 25: Experimental cubic stiffness test setup using a beam. (**a**) 40 mm end columns (**b**) 10 mm end columns.  
In the FE analysis, the substrate structure was assumed to be completely rigid. However, in the experiment, the substrate structure may not be necessarily rigid. To reach the black-colored nonlinear load-deflection plot of Figure 18, the FE results indicated that the substrate structure needed to be very rigid, the columns needed to be short and rigid, and it was preferable to weld the beam to the columns and the piston shaft and also have the columns welded to the substrate structure, as shown in Figure 26.  
The ANSYS FE results indicated that when the columns were 40 mm tall (see Figure 25a), the load-deflection curve would be only slightly nonlinear, and our experimental results indicated exactly the same thing. So, to approach the black-colored load-deflection curve, all the bolts were over-tightened to ensure no slippage occurred. The weights and a dial indicator, as shown in Figure 26, were used to obtain the experimental load-deflection data for the beam. Since the applied forces to the beam were below 25 N and the beam deflections were very small, use of a MTS test machine to acquire the load-deflection data was not recommended since it would be susceptible to sensor noise.  
Figure 27 shows the experimental load-deflection plot of the designed nonlinear stiffness beam, which is indeed nonlinear and is more strongly nonlinear than the ANSYS predictions.  
Figure 26: Test fixture used to test the beam of Figure 25.  
Figure 27: Comparison of ANSYS and Equation (12) with experimental load–deflection data.  
The experimental test of Figure 26 was repeated three times, and the data were very consistent with no hysteresis.
# Energy Efficient Routing Protocol in Sensor Networks Using Genetic Algorithm
## 3 Proposed Algorithm
### Proposed Method  
AOMDV protocol returns routes based on the minimum number of intermediate nodes regardless of their power condition. To extend the lifespan of the nodes, we introduce a mechanism that utilizes the AOMDV array of routes and optimizes the one that has nodes with the maximum amount of residual energy. To do so, a fitness function (FF) is proposed to be applied on the AOMDV algorithm producing efficient routes with the minimum number of nodes with the least energy consumption. Next, we implement the GA which includes crossover and mutation phases where more potential routes are generated.
# A Wi-Fi FTM-Based Indoor Positioning Method with LOS/NLOS Identification
## 2 Theoretical Framework  
### RTT-Based Ranging Model  
Here, TOF echo technology is used in the Wi-Fi FTM protocol and makes the RTT based ranging more convenient [18]. This new technology determines the distance according to the RTT of a Wi-Fi FTM pulse from an MT to an FT. Accordingly, it can eliminate the time synchronization errors in the time of arrival (TOA)/time difference of arrival (TDOA)-based ranging, with no need to synchronize the times of the FT and MT. The whole procedure of ranging is shown in Figure 1. It shows that a mobile phone is used as an MT to send an FTM request to FTs supporting the FTM protocol. After an FT receives the request, an Acknowledgement (ACK) signal is sent from the FT to the MT. After that,several FTM feedback signals are sent from the FT to the MT, where the mean RTT can then be calculated. The time information can be expressed as follows:  
\[t_{ACK}=t_{request}+\frac{2}{c}{\left\|p_{MT}-p_{FT}\right\|_{2}}+t_{D}+e_{NLOS} \tag{1}\]  
where \(t_{request}\) and \(t_{ACK}\) are the times for when the request was sent from the MT and when the ACK signal arrives at MT; \(p_{MT}\) is the location of the MT when the FTM request is sent; \(p_{FT}\) is the location of the FT when the MT receives the FTM request; \(t_{D}\) is standard time deviation between the MT and the FT; \(e_{NLOS}\) is the time delay error caused by the NLOS effect; and c is the speed of light. Hence, the distance can be calculated by Equation (2):  
\[\rho={\left\|p_{MT}-p_{FT}\right\|_{2}}=d_{RTT}-d_{D}-d_{NLOS} \tag{2}\]  
where \(d_{RTT}\) is the ranging result; \(d_{D}\) is the ranging error caused by standard time deviation, as shown in Equation (3); and \(d_{NLOS}\) is the ranging error caused by the NLOS effect. The ranging error \(d_{D}\) not only includes a fixed time delay error, a device error, and a start error, but also is influenced by the distance of pulse propagation and other environmental factors [35], which can be expressed as follows:  
\[d_{D}=e_{n}+\varphi(s)+\varepsilon \tag{3}\]  
where \(e_{n}\) is the constant error caused by the fixed time delay error, the device error, and the start error; \(\varphi(s)\) is the error formed by different ranging results, which can be seen as a polynomial function related to the ranging results; and \(\varepsilon\) is the system noise. It can be seen that the standard time deviation error of the equipment needs to be determined and calibrated to provide more precise ranging results.
## 3 Correlation Analysis of the Discing Core Section and the Drilling Parameters
This means that the faster the drilling rate, the more energy required. Figure 7: Monitored bit drilling pressure (a), torque (b), and specific energy (c) along complete granite core length at various drilling rates. (**a**) Drilling pressure; (**b**) Torque; (**c**) Specific energy. It is noted that the various features of drilling pressure, torque, and specific energy began at one-third (e.g., 30 mm) of core length when implementing high drilling rates (e.g., \(>\)15 mm/min.). The internal condition of the borehole is shown in Figure 9. When the rotation speed is constant, the drilling rate is too fast, and the rock in contact with the bit is not broken in time, then the bit moves forward for a distance. In order to ensure the constant rotation speed and drilling rate, the bit torque and drilling pressure will increase to input more energy for rock breaking. Especially with the increase of drilling depth, the drainage conditions become worse, which is more likely to occur. Figure 9(a) depicts test 1 and test 2 (at low drilling rates < 15 mm/min). The core comparison diagrams of drilling parameters in test 3, test 4, and test 5 are shown in Figure 9(b)-d, respectively. Drilling pressure and torque basically maintain similar fluctuation characteristics, and the wave crest of the curve roughly coincides with the position of the discs. This indicates that when discing occurs, drilling pressure and torque will increase, and the external input energy will increase sharply. When the energy reaches a peak, core fracture will occur. The peak energy can be calculated by the drilling parameter value corresponding to the disc's point. Usually, multiple discing phenomena will occur in a test, and multiple peaks will appear in the drilling parameters. In Figure 9(b)-d, surface cracks (in the red box) appear. The crack depth is very shallow, appearing only on the surface of  
Figure 8: A shaded 95% confidence interval of bit drilling pressure (**a**), torque (**b**), and specific energy (**c**) at varied drilling rates. Figure 4:0 Internal condition of the borehole. the core. There is no penetration along the radial direction, and the rock disc cannot be formed, but the drilling pressure and torque will also change suddenly at this time. Comparing the results of tests 1 and 2 with test 3, test 4, and test 5, the following effects can be inferred: under low confining pressure, when the drilling rate is high, the phenomenon of core discing occurs. The drilling rate affects the drilling parameters, and they are directly proportional. The change of the drilling parameters is an important factor resulting in core discing. It implies that the core discing phenomenon may be caused by a too-fast drilling rate, so it is necessary to judge whether there is a high stress effect in combination.
## 1 Introduction
The addition of specific lipases is needed to catalyze the lysis of fatty acids from the triglyceride [26]. Fatty acids are long hydrocarbon chain molecules with a carboxyl-terminal group [27] that can be widely used as versatile intermediates and chemicals in industrial applications such as, among others, cosmetics [28], pharmaceutical manufacturing [29], or surfactants [30]. In accordance with the above mentioned, the enzymes' capacity to hydrolyze proteins and lipids enables the production of short peptides and the release of collagen and fatty acids from retail meat waste. Protein hydrolyses containing mostly di- and tripeptides, collagen, and fatty acids have a growing demand in recent years. In the year 2022, the global protein hydrolysate market size was valued at USD 583.30 million; the size of this market is expected to increase to USD 1.14 billion by the year 2030, while growing at a compound annual growth rate (CAGR) of 8.8% [31]. The global collagen market size was accounted for at USD 9.12 billion in 2022 and is expected to expand at a CAGR of 10.2% from 2023 to 2030 [32]. The fatty acids market size is estimated to be worth USD 29.52 billion in 2022 and is forecast to a readjusted size of USD 45.56 billion by 2030 with a CAGR of 4.9% during the forecast period of 2023-2030 [33]. This increase in demand for protein hydrolysates, collagen, and fatty acids means that more sources of proteins and lipids are needed. But this increase in demand must be environmentally sustainable, so that sources such as meat waste are an alternative option to the typical raw materials used in the production of these products. Therefore, the aim of this work is the study of enzymatic hydrolysis of retail meat waste to generate added-value products and to fulfill the requirements in the EU Circular Economy Package. The study consists of three parts: (i) to optimize the production of high-quality protein hydrolysates and collagen from hydrolysis of meat waste using a protease, (ii) to optimize the production of fatty acids from hydrolysis of meat waste using a lipase, and (iii) to optimize the simultaneous production of protein hydrolysates, collagen, and fatty acids from hydrolysis of meat waste with a combination of protease and lipase. To accomplish these goals, hydrolysis of retail meat waste was carried out at different pHs, temperatures, and enzyme/substrate ratios.
# Design of Man-Machine Synergic Lunar Coring Device and Its Coring Dynamic Analysis
## 3 Man-Machine Synergic Lunar Coring Device Scheme Design
### Structure Design of the Coring Device
#### 3.2.2 Man-Machine Synergic Coring Device  
During a manned lunar mission, astronauts face many limitations and hazards [25]. Therefore, to improve the mobility of the sampling mission, this design is based on the handheld coring device, and the man-machine synergic coring device is designed, as shown in Figure 6a. The astronaut attaches the handheld coring device to the lifting device via a quick interface, and the lifting device provides the feed force for the coring process instead of the astronaut. The drive motor controls the rotation of the chassis rotation device where  
Figure 4: (**a**) Schematic diagram of the structure of the high-frequency impact module; (**b**) Schematic diagram of the structure of the rotating module; (**c**) Schematic diagram of the coring process of the handheld coring device.  
Figure 5: (**a**) Schematic diagram of the structure of the coring tube; (**b**) Comparison of Luoyang shovel-type coring tube and traditional coring tube.  
the coring tube and connecting rod are placed and turns the coring tube and connecting rod to the fixed clamping port, as shown in Figure 6b. The movable clamping device transfers the coring tube or connecting rod to the coring port, and the fixed clamping device assists, and the two work together to realize the assembling and disassembling of the coring tube and connecting rod, as shown in Figure 6c.  
A comparison of the dimensions and performance of the handheld and man-machine synergic coring devices is shown in Table 2. The man-machine synergic coring device can be used as a landing module for independent coring on the lunar surface. It can also be installed on the lander or rover for remotely operated coring, as shown in Figure 7.  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **Outline Dimension/mm** & & **Maximum Input** & **Effective Sampling** \\  & **(L \(\times\) W \(\times\) H)** & **Weight/kg** & **Power/kw** & **Depth/m** \\ \hline Handheld coring device & 400 \(\times\) 210 \(\times\) 380 & \(\leq\)25 & \(\leq\)1.5 & \(\geq\)2 \\ Synergic coring device & 820 \(\times\) 800 \(\times\) 1400 & \(\leq\)150 & \(\leq\)4 & \(\geq\)3 \\ \hline \end{tabular}
\end{table}
Table 2: Performance comparison of the handheld coring device and man-machine synergic coring device.  
Figure 6: (**a**) Overall structure of the man-machine synergic coring device; (**b**) Internal diagram of the man-machine synergic coring device; (**c**) Clamping device of the man-machine synergic coring device.  
Figure 7: Schematic diagram of the sampling pattern of the coring device. (**a**) Man-machine synergic coring; (**b**) Astronaut handheld coring; (**c**) Coring device mounted on the lander; (**d**) Coring device mounted on rover.
# Static Magnetic Fields Effects on Polysaccharides Production by Different Microsalgae Strains
## 2 Materials and Methods  
### Microalgae and Culture Conditions  
_Arthrospira platensis_ SAG 21.99 (Gottingen University, Germany), _Spirulina_ sp. LEB 18 [38] and _Chlorella fusca_ LEB 111 (Aidar and Kutner Microorganism Bank-BMA&K) were chosen to be evaluated. _A. platensis_ SAG 21.99 and _Spirulina_ sp. LEB 18 were cultivated in Zarrouk medium [39] and _C. fusca_ in BG 11 medium [40]. These microalgae were selected, since there are previous studies that show the influence of SMF on growth, but the polysaccharides were not evaluated before [16; 36; 41], besides _Spirulina_ and _Chlorella_ has been widely studied due to their high polysaccharides content [1; 7; 42].  
The _A. platensis_ SAG 21.99 assays were carried out in 1 L glass bottles, illuminated with fluorescent tubular lamps (100 \(\mathrm{\SIUnitSymbolMicro mol_{photons}}\) m\({}^{-2}\) s\({}^{-1}\)), aerated by air and maintained at 22 \({}^{\circ}\)C under a 16/8 h light/dark photoperiod. Cultures were inoculated at 0.1 g L\({}^{-1}\) and run in batch mode for 10 days. _C. fusca_ was cultured in the same devices for 15 days, but maintained at 30 \({}^{\circ}\)C, a 12/12 h light/dark cycle and 82 \(\mathrm{\SIUnitSymbolMicro mol_{photons}}\) m\({}^{-2}\) s\({}^{-1}\) for the irradiance [36; 41]. Additionally, outdoor conditions were tested in raceway tanks (4.5 L working volume) for _Spirulina_ sp. LEB 18 and C. _fusca_ LEB 111 in a greenhouse, in open PVC raceways with daytime sunlight (mean value 300 \(\mathrm{\SIUnitSymbolMicro mol_{photons}}\) m\({}^{-2}\) s\({}^{-1}\)) and the mean temperature in those days were 34 \({}^{\circ}\)C. Paddle wheels, set at 24 revs min\({}^{-1}\), were used for the mixing. The Figure 1 shows the experiment schemes developed in this study.  
Initial biomass concentration was 0.2 g L\({}^{-1}\) for _Spirulina_ sp. and 0.3 g L\({}^{-1}\) for _C. fusca_. Daily sampling allowed to follow the biomass concentration (X, g L\({}^{-1}\)), by measurement of the 670 nm optical density (UV-vis spectrophotometer, QUIMIS Q998U, Brazil) and use of DW/OD correlations established for each microalga. \(X_{\mathrm{max}}\) corresponds to the biomass concentrations obtained at the end of cultures.