esa-sceva/satcom-chunk-collection huggingface dataset:
## 7 Results of Simulations
### Influence of DT Adaptation on Performance of ED
The levels of the Tx power selected for the analyses are characteristic of real OFDM communication systems, such as WLAN (100 mW) and 2G-5G wireless mobile systems (1 W for the mobile device, 10-15 W for macro base stations). Figures 6 and 7 suggest that, for a specific SNR at the location of SU and for ED of signals with an equal sample quantity \(N\) impacted by an equal NU variation (\(\rho\)), the detection probability will be higher in the cases where PU transmits with a larger Tx power and vice versa. This is a consequence of a lower Tx power, which results in lower energy at the location of SU that further results in a lower signal detection probability. The results presented in Figure 7 also show that the larger DT adaptation range (higher DT factor \(\rho^{\prime}\)) results in a better detection probability and, consequently, the better performance of the ED process. It is shown that, for the larger range of NU fluctuations (a higher NU factor \(\rho\)), better ED performance can be accomplished only if the larger range of DT adaptations are used. This enables the appropriate adjustment of the threshold to the larger NU variations. However, an uncontrolled setting of the DT adaptation range to some arbitrary high or low value can lead to the selection of too low or too high ED thresholds. This might lead to extreme ED sensitivity or misdetection (Figure 5). In both cases, the detection probability will be degraded. Hence the DT range must be adapted according to the level of the NU variations. This means that the higher expected NU variation should be followed by a higher DT adaptation range and vice versa. Additional analyses have been performed for the MA systems affected by the same NU variation (\(\rho=1.02\)). Figure 8 presents the results of the analyses, where it was assumed that every OFDM modulation (QPSK or \(16/64/256\) QAM) for a specific level of Tx power (10 W or 100 mW) can obtain SNR equal to \(-15\) dB or higher at the location of SU. The simulation results present distinctions among the detection probabilities for MA systems transmitting with versatile Tx powers, while using the same OFDM modulation. The higher detection probability will involve the sensing of the OFDM modulated signals transmitted at a higher Tx power for the same false alarm probability. This leads to the conclusion that the Tx power adaptation in MA systems largely influence the detection probability, even when the NU variation is constant (Figure 8). Figure 8: Interdependence between detection and false alarm probability for ED of signals in MA systems transmitted with two Tx powers and four different OFDM modulations.
# Context-Aware Gossip-Based Protocol for Internet of Things Applications
## 6 Effects on Application Requirements
### Comparative Assessment Results
#### 6.4.3 Saved Rebroadcasts  
The performances in terms of percentage of saved rebroadcasts are shown in Figure 8 for all five protocols (Equations (10)-(12), gossiping, and FELGossiping) for networks with \(50\) to \(250\) nodes. As anticipated, the performance in terms of this metric shows the inverse behaviour relative to the performance in terms of the percentage of rebroadcast nodes, as shown in Figure 7, because it measures the percentage of bandwidth utilisation. The performance of the MFWFs constructed for critical and bandwidth-intensive IoT applications (see Equations (10) and (12), respectively) prove equally suitable, as the bandwidth utilisation is substantially reduced, with a savings of almost \(90\%\) of rebroadcasts. FELGossiping performs comparably well relative to the constructed equations (Equations (10) and (12)), thus confirming this protocol's adequacy for bandwidth-intensive IoT applications. The MFWF constructed for energy-efficient IoT applications (see Equation (11)) also performs relatively well, considerably reducing the bandwidth utilisation as the number of nodes  
Figure 7: Percentages of rebroadcast nodes for the three constructed protocols, the traditional gossiping protocol, and FELGossiping with an increasing number of nodes in the network.  
in the network increases. Similar to what was reported for the percentage of rebroadcast nodes, the bandwidth utilisation of each protocol is relatively stable across different numbers of nodes in the network.
# Exploring ISAC: Information-Theoretic Insights
## 5 Network ISAC with Sensing Distortion
### One-to-Many Communication (Broadcast Channels) with Tx Sensing
#### 5.1.2 Results
The scheme in [5] is based on a block Markov strategy (see Figure 8) where the Tx uses the generalized feedback signals in a block and its own transmitted signal in the same block to identify correlated compression information for both Rxs to improve their decoding. It then sends this update (compression) information in the following block, where the correlation allows the Tx to send part of the compression information as common information that is simultaneously useful for both Rxs, which is more efficient than sending individual information to the Rxs and thus is an improvement over no-feedback communication. Technically speaking, the common information is created using distributed compression techniques a la Gray-Wyner [29]. Decoding is performed backward, starting from the last block, where first the refinement information is decoded and then used to facilitate decoding of the previous block. Both the inner bounds and the outer bounds are expressed with the help of _auxiliary random variables_. Examining the details of the proof of the inner bound in [64], the auxiliary  
\[rCIR_{0}+R_{k} \leq I(U_{k};Y_{k}),\quad k=1,2, \tag{36a}\]1 Block Markov coding structure. random variables \(U_{0},U_{1},U_{2}\) are easily identified with the different types of codewords used in the code construction. The auxiliary random variables \(V_{0},V_{1},V_{2}\) are identified with codewords compressing the feedback signals and the auxiliary codewords corresponding to \(U_{0},U_{1},U_{2}\). The \(U_{k}\) auxiliary random variables however again point to a superposition structure given the Markov chains \(U_{k}\)\(\
eg\)\(\
eg\)\(X\)\(\
eg\)\(\
eg\)\(Y_{k}\). More from a technical perspective, the auxiliary random variables allow the obtaining of inner and outer bounds that can be expressed as single-letter optimization problems. On the negative side, these optimization problems often still have high computational complexities.
# Advantages and Limitations of Current Microgravity Platforms for Space Biology Research
## 3 Ground Microgravity Analogues
### Neutral Buoyancy  
Neutral buoyancy occurs when a mass immersed in a medium displaces a mass of equal weight (Figure 2b). In this case, the buoyancy force will balance the gravity force. If an object has neutral buoyancy in a liquid, it will neither sink nor float, but will remain stationary. Neutral buoyancy facilities have been used since the mid-1960s at the Johnson Space Center to test procedures, to develop hardware, and for astronaut training. Astronauts use the Neutral Buoyancy Facility to practice in-flight procedures, such as extravehicular activities, and for in-flight simulations.  
Neutral buoyancy has also been used in single cell organisms (Table 2). In particular, it has been used to prove the existence of statolith-independent graviperception. By matching the density of the medium to the density of the cell, scientists were able to abolish gravity-driven swimming in both Euglena and Paramecium. In these organisms, it is thought that the entire cell works as a statolith, and the mechanical stress exerted by the cell on the different faces of the cell wall is translated into positional information. It is still not clear to what extent a similar mechanism is also active in higher plants, but plants lacking sedimenting statoliths partially retain the ability to respond to gravity. Submergence has been used to study graviperception in higher plants, but the possible influence of the gas-related stress response even in semi-aquatic species makes the results difficult to interpret [45; 46].
# Carrier-to-Noise-Threshold Filtering on Off-Shore Wind Lidar Measurements
## 3 Data Analysis
### Wind Speed Dependence on Carrier-to-Noise-Ratio
The full line is a direct comparison between the difference in wind speed between 90 m and 126 m, without accounting for the difference in wind speed between the two levels. For the dashed line the wind shear between 90 m and 126 m has been accounted for by extrapolation of the wind speed at 90 m to 126 m by use of the logarithmic wind profile, before forming the difference between the individual observations. It can be observed that the standard deviation has a minimum at CNR \(\sim\) -19 dB, then it increases for decreasing CNR threshold values until a CNR of \(\sim\)29 dB and, thereafter, remains near constant as the CNR threshold is further decreased. The comparison should ideally be performed with cup-anemometer and wind lidar measurements at the same height, but such measurements were not available here. By extrapolating the cup-anemometer measurements from 90 m to 126 m by assuming a logarithmic wind profile, the effect on the wind shear from the atmospheric stability is unaccounted for. Furthermore, the comparison is between point measurements for the cup anemometer with range averaged measurements for the wind lidar, which are not directly comparable.
## 2 Materials and Methods
### Gene Expression Analysis by qRT-PCR  
For gene expression quantification of selected genes, NSCs were supplemented with medium containing the tested products at two or three non-cytotoxic concentrations for 24 h (h). After that, neural toxicity was induced with H\({}_{2}\)O\({}_{2}\) for 24 h. After the incubation period, cells were collected in lysis buffer to proceed with the RNA extraction. Total RNA was extracted using RNeasy kit (Qiagen, Venlo, The Netherlands) and treated with DNAse-I to remove any contamination from genomic DNA. RNA quality and quantity were checked in a Nano-Drop spectrophotometer, and cDNA was synthesized. Finally, quantitative PCR (qPCR) was performed in a real-time PCR machine (QuantStudio 5, Applied BioSystem, Madrid, Spain). To perform raw data analysis, we used the 2\({}^{-\Delta\text{CCI}}\) method to calculate the gene relative expression ratio of NRF2, NGF, BDNF, VEGF, CASP9, BAX and BCL2 to H\({}_{2}\)O\({}_{2}\)-treated control (C). Actin (ACT) was used as a reference housekeeping gene. The sequences used for the primers of each gene are shown in Table 1.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Gene** & **Primer Sequence** \\ \hline Actin & 5\({}^{\prime}\)-ACAGAGCCCTGGCCTTTG-3\({}^{\prime}\) \\  & 5\({}^{\prime}\)-CCTTGCCACATGCCGAG-3\({}^{\prime}\) \\ \hline NRF2 & 5\({}^{\prime}\)-ACATCCAGTCAGAAACCAGTG-3\({}^{\prime}\) \\  & 5\({}^{\prime}\)-CGTAGCCGAAGAACCCTAT-3\({}^{\prime}\) \\ \hline NGF & 5\({}^{\prime}\)-CGGACCAAATAACAGTTTTACC-3\({}^{\prime}\) \\  & 5\({}^{\prime}\)-TGTGATCAGAGTCTAGAACA-3\({}^{\prime}\) \\ \hline BDNF & 5\({}^{\prime}\)-GCTCTGTGATTATTGTG-3\({}^{\prime}\) \\  & 5\({}^{\prime}\)-ACACATCCAGTGTCCTCG-3\({}^{\prime}\) \\ \hline VEGF & 5\({}^{\prime}\)-GTACAAGATCCCGACGACG-3\({}^{\prime}\) \\  & 5\({}^{\prime}\)-TTCTGATCAGGTCTTCTGGTG-3\({}^{\prime}\) \\ \hline CASP9 & 5\({}^{\prime}\)-GCCCAAGCCTTTTTCATCC-3\({}^{\prime}\) \\  & 5\({}^{\prime}\)-GTCCTCAAACCTTCCTGGAAAC-3\({}^{\prime}\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Gene sequences used for qRT-PCR.
# A Novel Procedure of Enhancing the Throughput of a Mode-2 Sidelink Based on Partial Sensing
###### Abstract
The key contribution of this study is that it proposes a novel procedure for the enhancement of the throughput of each P-UE that participates in mode-2 sidelink communication with partial sensing. The proposed technique employs additional UE, denoted the roadside unit (RSU), which aligns the partial sensing window of each P-UE to combine all of the aligned sensing results. Subsequently, the combined sensing results are transmitted from the RSU back to each P-UE to be shared by all the P-UEs. Based on the proposed technique, the throughput of each P-UE can be increased almost to that achieved in full sensing, while the merit of power saving is still maintained, as in the case of partial sensing. The remainder of this paper is organized as follows. Section 2 introduces sensing-based mode-2 communication. Section 3 introduces the procedure to combine all the partial sensing results of the method presented in this paper. Section 4 presents the simulation results, and Section 5 concludes the paper.
## 5 Simulations and Performance Evaluations
### Different Data Transmission Rates between MEC-NBS and C  
As shown in Figure 9, we measured the total time consumption by the system in completing all tasks under the 3 schemes with different data transmission rates between C and MEC-NBS. In simulations, we increase the \(s_{k}^{\text{NBS2C}},\forall k\in\mathcal{K}\) from 10 to 40 MB/s, while other settings are listed in Table 1, except fixed values \(M=60\), \(R=6\), \(K=6\), \(\phi_{k}=2.4\times 10^{6}\) MBPS, \(s_{k}^{\text{C2 NBS}}=80\) MB/s, \(s_{k}^{\text{B2 NBS}}=s_{k}^{\text{NBS2 BS}}=30\) MB/s, \(\forall k\in\mathcal{K}\).  
Figure 8: \(f\) gained by the 3 schemes with the increase of \(s_{k}^{\text{C2 NBS}}\), the data transmission rates between C and MEC-NBS, \(k=1,2,\dots,K\).  
Similar to the data transmission rates between C and MEC-NBS, \(s_{k}^{\text{NBS2C}},\forall k\in\mathcal{K}\) impacts the time consumptions of transmission processes in further offloading and data caching. Although the curves of our scheme and OMEC are not very smooth, we can still notice that the overall trend of the curves are decreasing. Similarly, the curve of NMEC is still unchanged because further offloading and data caching are disabled.
# Review of Land Surface Albedo: Variance Characteristics, Climate Effect and Management Strategy
## 4 Climate Feedback and Management Strategy for Surface Albedo  
Surface albedo plays an essential role in understanding and controlling climate change. Various surface albedo datasets have been widely used to survey slow climate change, such as those for land degradation [155], rapid surface dynamics [15] and extreme disaster events, such as forest fires [156]. These variances in surface albedo have a significant effect on the carbon trade-off [29; 157], and many management strategies have been implemented to mitigate greenhouse effects, such as afforestation [158] and the application of high-albedo materials for pavement and roofs in urban areas [159].
# A PMSG Wind Energy System Featuring Low-Voltage Ride-through via Mode-Shift Control
## 3 System under Consideration
### Currents' Reference Generation
#### 4.2.1 During MPPT Mode  
For the optimal operation of variable speed wind turbine power systems, MPPT is mandatory. Hereby, the optimum relationship-based (ORB) sensorless MPPT approach is applied [45; 46; 47]. In this method, instead of relying on mechanical sensors to measure wind and generator speeds, parameters are calculated from available electrical parameters at the generator output terminals. For every wind speed, there is a peak power \(P_{MPP}\), which corresponds to an optimal DC power at rectifier output \(P_{r-opt}\), i.e., corresponding to an optimal rectified voltage value \(V_{r-opt}\) and current \(I_{r-opt}\), as shown in (35):  
\[P_{r-opt}=\eta\ P_{MPP}=V_{r-opt}I_{r-opt} \tag{35}\]  
where \(\eta\) is the conversion efficiency from the generator to the rectifier DC-side and is assumed to be a fixed value.  
The rectified current in the considered system is the boost converter current Ib. Thus, using the sensorless ORB technique, the optimum relationship between the rectifier output voltage \(V_{r}\) and boost chopper current \(I_{b}\) is recorded in a lookup table for different wind speeds. In the MPPT mode, the boost current reference is determined according to the ORB sensorless approach to guarantee maximum wind power extraction. On the other hand, the GSC should guarantee DC-link voltage regulation, grid synchronization and grid current control to achieve a high level of quality and unity power factor. Thus, the reference of grid current \(d\) component \(I_{d}^{*}\) is determined via the DC-link voltage regulation loop, while the grid current \(q\) component reference \(I_{q}^{*}\) is set to zero to allow only the harvested active power to be injected into the grid.
## 2 Material and Methods
### Instruments Monitoring System
VWSG for BP# 2 is also installed at five levels (A to E) in four numbers per level (Figure 6). The connected VWSG to the steel cage and electrical lead wires from the sensors coming to the top, have been illustrated in Figures 7 and 8. The pile head displacement has also been analyzed using dial gauges and LVDTs, resulting in a reading with 0.01 mm accuracy mounted on stable reference beams and protected from direct sunlight and disturbance of personnel in the whole system. Settlement measuring through the use of proper leveling techniques has also been implemented as a useful backup to check the reference beams' movement. Vibrating wire load cells, strain gauges, retrievable extensometers, and LVDTs have been automatically logged by applying a Micro-10x Datalogger and Multilogger software at the 3-minute spacing for precise control during load/unload stages. Only accurate level readings are manually considered. Briefly, the pile movement monitoring system, such as pile top and bottom settlements, has been monitored using the vertical scale rule fixed to the pile top observed by tunnel boring machine (TBM) for correction purposes. On the other hand, LVDTs and GSEs mounted to the reference beam accompanied by a plunger pressed vertically against a glass plate fixed to the pile's top. The vertical scales have been provided to monitor any movement in the load test. Indeed, strain gauges are manufactured in Geokon, USA. VWSG principles in strain measurement were presented due to the frequent natural vibration of taut wire restrained at both ends and varied with the square root of wire tension. Indeed, this change of tension in the wire has shown all the strain alterations in the structural steel member where the gauge is mounted. Moreover, all strain gauge has been mounted to two end blocks as arc-welded to the main reinforced bar at a proper level. The signal cables of the picked-up sensors fixed to the strain gauges have been tightly tied in the reinforced bars to the top of the piles terminated in a multiplexer box and observed using a Micro-10 Datalogger. Figure 6: Vibrating wire strain gauges and tell-tales’ extensometer arrangement in BP# 2.
# Improved Control of Forest Microgrids with Hybrid Complementary Energy Storage
## 2 Operation Mode and Coordination Control of Microgrid in Forest Area  
### Structure of the Forest Microgrid  
The forest microgrid adopts a DC bus due to the advantages of flexible control, low line loss, and high conversion efficiency, which determine it to be a more ideal connection pattern than its AC counterpart. Therefore, it is conducive to the flexible access of renewable energy and the realization of intelligent power supply in remote forest areas.  
In this paper, the forest microgrid, which is composed of the biomass power unit, the wind power unit, and energy storage units, adopts multiple energy sources in complementary forms. As the microgrid is designed for remote forest areas, which are hard to access by the utility grid, it operates in islanded (off-grid) mode. Moreover, radiation topology is adopted by the system with simple structure and low construction cost, as is shown in Figure 1.  
When the system operates normally, the wind power unit provides green energy to support the microgrid. The biomass power generation unit generally operates in hot  
Figure 1: System structure of DC microgrid with wind turbine, energy storage, and biomass energy.  
supercapacitor, which cooperates with the biomass unit or batteries, is utilized to eliminate fast power disturbance of the system, based on its characteristic of fast charging and discharging. In addition, the battery energy storage system is an emergency power supply unit, which can realize bidirectional power flow through the DC/DC converter. According to the operation characteristics of each unit, the operation mode of the forest DC microgrid can be divided into the following four parts.
# The HD-Domain Metalloprotein Superfamily:
### HD-Domain Hydrolases: The PDE Subfamily
#### 1.3.2 HD-Domain PDEs Acting on Cyclic Mononucleotides  
cAMP- and cGMP-specific PDEs (also referred to as PDEases) are essential regulators in cyclic nucleotide-dependent signal transduction in diverse physiological processes including immune response, neuronal activity, hypertension, and inflammatory response [30; 31; 52]. Currently, 21 genes encoding human PDEases have been identified and classified into 12 families according to their substrate specificities, pharmacological properties, and tissue localization [31; 53]. These are further divided into three groups: cAMP-specific (PDE4, PDE7, PDE8, and PDE12), cGMP-specific (PDE5, PDE6, and PDE9) [31; 41], and dual-specific (PDE1, PDE2, PDE3, PDE10, and PDE11) [31].  
All PDEases are dimeric and have a conserved catalytic carboxy terminal domain as well as a variable regulatory amino terminal domain [30; 54]. However, PDEases are also active as monomers; therefore, the functional significance of dimerization remains unknown [54]. On the basis of their binding affinity for divalent metal ions, PDEases are distinguished into two classes: Class I in mammals and flies and Class II in yeast and protozoans [55]. The most extensively studied are Class I PDEases, in which two metal ions (e.g., Zn and Mg) are octahedrally coordinated, forming a somewhat unconventional bimetallic site [30] Although the canonical motif suggests the binding of a single metal ion (M1) in the HD motif, stabilization of the second metal ion (M2) is accomplished via the aspartate of the HD motif and five water molecules, one of which is bridging M1 and M2. The bridging water molecule has been suggested to be a hydroxide, which can nucleophilically attack the phosphodiester bond [30]. In the crystal structures, the identity of M1 and M2 is often found to be Zn and Mg, respectively (Figure 4) [30]. Class I PDEs are active with either Mn or Mg but not with Zn. Therefore, although Zn can bind in the M1 position with high affinity, it cannot stimulate activity by itself or has inhibitory effects [31].  
The substrate specificity in PDEases is afforded by a so-called \"glutamine-switch\" mechanism in which [30] a conserved glutamine in the vicinity of the active site can adopt two different orientations. In one orientation, it can form a bidentate hydrogen bond with the adenine ring (cAMP-specific) or two hydrogen bonds with guanine ring and two hydrogen bonds with neighboring alanine and tryptophan residues (cGMP-specific) [30; 31]. In the dual-specific PDEases, the conserved glutamine has higher rotational flexibility and no orientation constraints, allowing it to adopt orientations for both substrates.