esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Molecular Mechanisms of Omega-3 Fatty Acids in Cancer
### Oxidative Stress and n-3 PUFA  
Oxidative stress arises from a disruption in the equilibrium between the generation of ROS and the protective mechanisms of the antioxidant defense system. ROS possess the capability to inflict damage upon lipids, nucleic acids and proteins, thereby perturbing their respective functionalities. This phenomenon is implicated in the onset and/or progression of numerous diseases, rendering it a prospective focal point in conditions such as atherosclerosis, chronic obstructive pulmonary disease, Alzheimer's disease, cancer and dermatological disorders, among others. Despite the promising therapeutic potential demonstrated by numerous small molecules acting as antioxidants in preclinical investigations, outcomes from clinical trials have been underwhelming. This discrepancy is primarily attributed to the complexity of pharmacokinetics and the multifaceted pathways through which ROS operate, which remain unaffected by the employment of singular antioxidant agents [93; 94; 95; 96].  
PUFAs may act as antioxidants by regulating the antioxidant signaling pathway and modulate inflammatory processes. The influence is through the hepatic lipid metabolism [97], physiological responses of other organs such as the heart [98], regulation of platelet homeostasis and lower risk of thrombosis [99; 100], modulation of neurodegenerative diseases [101] and skin damage [102; 103], among others.  
[PERSON] et al. studied the effect of EPA and DHA on hydrogen peroxide (H\({}_{2}\)O\({}_{2}\))-induced DNA damage response in human aortic endothelial cells. Through immunofluorescence staining, they showed that a marker of DNA damage was significantly reduced in the cells treated with EPA and DHA. The H\({}_{2}\)O\({}_{2}\)-induced activation of a kinase orchestrating the DNA damage response was significantly reduced with EPA and DHA treatment. Both compounds attenuated DNA damage regardless of the DNA damage response. Furthermore, n-3 PUFA reduced intracellular ROS levels under both basal conditions and H\({}_{2}\)O\({}_{2}\) stimulation. Additionally, mRNA levels of antioxidant molecules were significantly elevated with EPA and DHA treatment. Silencing of nuclear factor erythroid 2-related factor 2 (Nrf2) notably abolished the increases in mRNA levels of antioxidant molecules and the reduction in intracellular ROS [104].
###### Abstract  
Space-based communications at the very high frequency (VHF) band for air traffic management is a new technology application under development that requires energy-efficient architectures to mitigate the power limitations of satellite platforms. The usage of high-efficiency radiofrequency (RF) transmitters can help reduce the power consumption, but nonlinearities concerning the amplified signal in wide fractional bandwidth systems are a problem to solve. This paper proposes a high-efficiency (RF) power amplifier (PA) for satellite communications at the VHF band that aims to reduce the envelope distortion inherent to wide fractional bandwidth multicarrier polar-mode transmitters. Its design is based on a solution called hybrid-coupled switching voltage PA in combination with gallium nitride (GaN) high electron mobility transistor (HEMT) technology. The developed VHF PA prototype delivers up to 95 W from a 28 V power supply, with a drain efficiency about 80% within the 118 MHz to 138 MHz operating band. To test its linearity performance, operating in a polar-mode configuration, a GaN-based wideband envelope amplifier (EA) has been developed to modulate the RF PA supply port. This EA improves its power efficiency by combining it with a slow envelope power supply (SEPS). Some measurements have been taken for a 100 W peak envelope power (PEP) and 10 MHz (maximum carrier spacing) four-tone digitally-modulated test signal, where any distortion product is attenuated 46 dB below the average power of the amplified signal without applying any digital predistortion (DPD) technique.  
radio frequency; power amplifier; EER; polar transmitter; high efficiency; VHF; envelope amplifier; switchmode amplifier; multicarrier; satellite; GaN HEMT +
Footnote †: journal: Electronics Letters  
doi:10.3390/electronics12183866
## 3 Improved Radial Movement Optimization (IRMO) Algorithm
### IRMO Algorithm  
Based on the radial movement algorithm (RMO), the enhanced radial movement optimization (IRMO) is a global optimization algorithm. The phenomena of a set of particles travelling in a search space that continuously contracts with algebra to find the overall optimal solution can be summed up as the IRMO algorithm. By setting a more strict and reasonable objective function expression F and variable value range, the IRMO algorithm starts to randomly generate multiple particles, denoted as the first-generation particle swarm \(X_{i}^{1}\). The objective function expression F evaluates the fitness of each particle and takes the best particle as the first-generation central particle, recorded as \(Center^{1}\). When generating a new generation of particle swarm \(Y_{i}^{k}\), The IRMO algorithm not only relies on the central particle alone, but also determines that some particles directly inherit the particle information of the adjacent generation according to the control parameters \(h_{1}\) and \(h_{2}\). As generations continue to update the position information of particles, the search space continues to shrink, and its center will move towards the direction of the global optimal solution. By the end of the set generation, the search space has approached a point, and the corresponding particle position information is recorded as the global optimal position. The objective function value is the global optimal solution. Figure 10 shows the implementation of the IRMO algorithm [23].  
Figure 10: Schematic diagram of radial movement of particle swarm in IRMO.
## 4 Collision Avoidance Decision-Making Method
### Collision Avoidance Mechanism  
The collision avoidance mechanism is defined as a rule between the ship motion vector and the collision avoidance effect [20]. It refers to the relationship between the OS's velocity vector and collision avoidance results under the limits of ships routing in TSS waters and be shown through the following steps.  
Step 1: If a TS enters the OS's ship domain within the time \(T_{s2}\), the time of the TS from the current time to enter the OS's ship domain (TESD) is obtained from Figure 7. In addition, the TS's CRI is obtained via Section 3.2, and the TS's details, as well as the CRI's value \(CR\) are logged. Furthermore, it is important to keep a record of how many TSs (\(N\)) of this type there are.  
Step 2: If \(N\
eq 0\), use the TS information saved in Step 1 to find the TS with the highest CRI value. This is the most dangerous TS, and the CRI value of which ship is logged as \(CR_{max}\). Step 3: Determine the direction of the OS's course altering based on the most dangerous TS, as indicated in Figure 8.  
Figure 8: The judgment of direction of course alteration.  
Figure 7: Flowchart for TESD (\(T_{\text{BS}}\)) computation.  
Step 4: Increase the course alteration angle at 1\({}^{\circ}\) intervals based on the results of the third step's judgment. Furthermore, judge whether the OS can clear all of the TSs, and obtain the minimal course alteration angle that can clear all TSs. As indicated in Figure 9. The OS's course-altering angle should not be too large due to the high traffic flow in the seas of the TSS and the traffic lane limits. In this study, when the OS's course altering angle (\(\beta\)) reaches 45\({}^{\circ}\) to the port or starboard side, it is still impossible to clear all TSs, which shows no acceptable maneuvering scheme can be obtained.  
Step 5: Start the collision avoidance maneuver if a feasible course-altering angle is determined in Step 4. Determine whether the distance between the OS and the fairway's boundary line is smaller than DIS during the diversion process. If it is less than \(DIS\), the OS plans to sail along the fairway's boundary in the general direction of traffic flow to avoid leaving the traffic lane.
## 3 Results
### RCTs (Laser)
 } & \multirow{2}{*}{**Problem**} & \multirow{2}{*}{**Intervention/Comparison**} & \multicolumn{2}{c}{**Clinical**} & \multirow{2}{*}{**Outcome**} \\  & & & & & & Er,Cr:YSGG laser \\  & & & & & assisted conventional \\  & & & & & periodontal therapy is \\
**[PERSON] et al. **, **2016**[33] & RCT & 60 patients with & Test: SRP + Er/Cr:YSGG & CAL, PPD, BOP, PI; & more effective in \\ \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Articles** & **Type of Study** & **Problem** & **Intervention/Comparison** &
\begin{tabular}{c} **Clinical** \\ **Indices/Follow-Up** \\ \end{tabular} & **Outcome** \\ \hline \hline [PERSON] et al., 2015 [39] & RCT & 20 patients with chronic periodontitis & Test 1: diode laser & CAL, PPD, PI, PBI; Control: SRP & 3 months & The 6-week evaluation revealed a statistically significant increase in CAL in the laser groups compared to the control group \\ [PERSON] et al., 2015 [39] & RCT & 20 patients with chronic periodontitis & Test 2: SRP + PDT & CAL, PPD, PI, PBI; Control: SRP & 3 months (\(p\) < 0.05). Additionally, Test 2 with the laser group showed a higher PPD reduction than the other treatment methods (\(p\) < 0.05). \\ \hline
**[PERSON]** & RCT & 20 patients with chronic periodontitis & Test SRP + PDT ( diode laser) & CAL, PPD, BOP, PI, GR; 3 months & The adjunctive effect of aPDT did not warrant improvements on clinical parameters. \\ \hline
**[PERSON]** & RCT & 22 patients with severe chronic periodontitis & Test SRP + PDT ( diode laser) & CAL, PPD, GR, BOP, GI, VPI; 6 months & While there were notable clinical benefits with both methods for treating severe chronic periodontitis, the PDT did not yield any further advantages over full-mouth ultrasonic debridement alone. \\ \hline
**[PERSON] et al., 2013 [41]** & RCT & 24 patients with chronic periodontitis & Test SRP + PDT ( diode laser) & CAL, PPD, SBI, GBI, Control: SRP & In terms of clinical factors, a single PDT session may be applied in conjunction with scaling and root planing for the nonsurgical treatment of chronic periodontitis. \\ \hline
**[PERSON]** & RCT & 25 with generalized chronic periodontitis & Test: SRP + LLT Control: SRP & CAL, PPD, PI, GI; Control: SRP & LLLT as an adjunct to nonsurgical periodontal treatment has a positive impact on clinical parameters. \\ \hline
**[PERSON]** & RCT & 40 patients with chronic periodontitis & Test: SRP + diode laser Control: SRP & CAL, PPD, BOP; 3 months & There was a significant improvement in clinical parameters in the test group (SRP + laser) as compared to the control group (SRP alone). \\ \hline
**[PERSON]** & RCT & 40 patients with chronic periodontitis & Test: SRP + diode laser Control: SRP & 40 patients with chronic periodontitis & After 6 months of evaluation, the high-intensity diode laser has not shown any additional benefits compared to the conventional periodontal treatment. \\ \hline \hline \end{tabular}
\end{table} 
Table 2: _Cont._The results suggest that lasers as an adjuvant therapy to scaling and root planing can provide better clinical outcomes, although in 35% of cases it appears to provide no additional improvement (secondary outcome).
# Fuzzy Logic-Based Performance Enhancement of FSO Systems Under Adverse Weather Conditions
## 3 Fuzzy Modeling for Enhancing Receiver Performance in FSO System
### Fuzzy Rule Base and Inference Mechanism  
After establishing the fuzzy inputs and output membership functions, the decision-making logic is implemented. In this study, the [PERSON] [22; 26] method is used as a fuzzy inference technique. Therefore, the IF-THEN rules are used to represent relationships between variables. A fuzzy IF-THEN rule is illustrated as follows: if the \"rain\" is low (LR) and the \"distance\" is low (LD), then the \"threshold should be Th8\". If the \"rain\" is low (HR) and the \"distance\" is high (HD), then the \"threshold should be Th1\". The truth tables related to a fuzzy rule based on the proposed system for (rain; distance) and (fog; distance) are tabulated in Tables 3 and 4. These rules are shown as a fuzzy inference diagram in Figure 7, tuning the inputs accordingly.  
Figure 6: Membership functions for the fuzzy set of the output \(\Delta_{\textit{threeFLC}}\).
## 3 Results
### Packet Loss Rate and LQI Analysis of Local Self-Organizing Network  
Figure 6a shows the overall packet loss of 1800 packets transmitted by the terminal of the local self-organizing network, Figure 6b shows the packet loss of the local self-organizing network for each unit area of stumpage, and Figure 6c-h show the variation of LQI of the local self-organizing network with distance for different unit areas of stumpage.  
Analyzing Figure 6a, we find that the packet loss rate is only 1.78% in the sample of 1800 packets, and analyzing Figure 6b, we find that the packet loss is positively correlated with the number of standing trees per unit area: the larger the number of standing trees, the more serious the packet loss. Through analysis, it is concluded that the packet loss rate  
Figure 6: (**a**) Overall packet loss for 1800 packets. (**b**) Packet loss for each unit area of stumpage; (**c**) LQI with 0 m\({}^{3}\)/hm\({}^{2}\) unit area of stumpage; (**d**) LQI with 66.9 m\({}^{3}\)/hm\({}^{2}\) unit area of stumpage; (**e**) LQI with 115.6 m\({}^{3}\)/hm\({}^{2}\) unit area of stumpage; (**f**) LQI with 149.3 m\({}^{3}\)/hm\({}^{2}\) unit area of stumpage; (**g**) LQI with 190.5 m\({}^{3}\)/hm\({}^{2}\) unit area of stumpage; (**h**) LQI with 236.4 m\({}^{3}\)/hm\({}^{2}\) unit area of stumpage.  
of the local self-organizing network terminal meets the reliability requirements of different firefighting environments.  
Analyzing Figure 6c, we find that the change in LQI with the change in distance in the open environment is relatively weak; the LQI of the three links is only about 15, and the link quality is reliable. Comparing Figure 6d with Figure 6e,\(f\), the LQI becomes more affected by the transmission distance of the links when the standing wood accumulation per unit area reaches about 100 m\({}^{3}\)/hm\({}^{2}\).  
Analyzing Figure 6g,h, we find that in an extreme environment where the number of standing trees per unit area is very large, the LQI can still be stabilized at about 180 at a distance of 1 m, at more than 140 within a distance of 7 m, and about 125 beyond 7 m. From the analysis, it is concluded that the link quality decreases slowly with increased distance in the forest area without shading; in the forest area with shading, the link quality is more affected by shading. Even in the extreme case of severe shading, the local self-organizing network can still maintain good link quality.
# Static and Moving Target Imaging Using Harmonic Radar
## 4 Synthetic Aperture Radar (SAR) Imaging
### Moving Aperture SAR Imaging  
#### 4.2.1 Experimental Setup  
The first set of SAR images was obtained from a moving aperture. Data were collected in an anechoic chamber to reduce environmental effects and multipath. A diagram illustrating the setup is shown in Figure 11.  
The antennas were manually moved along a 3-m (10-foot) aperture with a 5-cm (2-inch) step size. This yields \(K=121\) aperture positions for the synthetic aperture. The target(s) remained stationary while the antennas were moved along the aperture, as shown in the coordinate system in Figure 11. The aperture was centered at \(x=0\) and spanned from \(x=-1.5\) m to \(x=+1.5\) m. The radiating apertures of the antennas were located at \(y=0\). Targets were placed in one of two positions, A or B. The coordinates of points A and B are presented in Table 2.  
\begin{table}
\begin{tabular}{c c c} \hline
**Position** & \(x\)**-Coordinate (m/ft)** & \(y\)**-Coordinate (m/ft)** \\ \hline A & 0/0 & 4.57/15 \\ B & \(-0.91/-3\) & 3.66/12 \\ \hline \end{tabular}
\end{table}
Table 2: \(x\)- and \(y\)-coordinates of target positions.  
Figure 11: Test setup for moving aperture SAR imaging.  
As seen in Figure 12, the transmitter and receiver hardware were physically located close to each other. For this reason, the receiver was placed in a metal box and surrounded with absorbing foam to suppress leakage from the high power transmitter into the receiver.  
To move the antennas along the aperture, the transmit and receive antennas were attached to a plastic cart on wheels. Two lines of duct tape were placed along the track to keep the antennas in proper alignment and to monitor the antenna position while in motion. Photographs of the cart, duct tape track, and antennas are shown in Figure 13.  
Figure 12: Photographs of the harmonic SAR system.  
Figure 13: Photographs of the antennas mounted on the plastic cart and the duct tape track.
## 1 Introduction
This paper focuses on the optimization of the latent space using evolutionary algorithms and then proposes a novel hybrid evolutionary algorithm, called the improved crisscross optimization (ICSO) algorithm, to optimize random latent vectors so as to enhance the quality and diversity of generated images. On the one hand, the original quality fitness and diversity fitness are balanced by normalization. Simultaneously, since the discriminator gradient has a certain influence on the diversity of generated images, a gradient penalty is introduced to constrain the discriminator gradient. On the other hand, based on the traditional crisscross optimization algorithm, ICSO is proposed by incorporating the local optimal solution and the global optimal solution from PSO. The contributions of this paper are summarized as follows:Based on the original crisscross optimization, this paper introduces a fusion strategy of local and global optimal solutions from the particle swarm optimization, and proposes an improved evolutionary algorithm--improved crisscross optimization. This algorithm is specifically designed to optimize the latent space of generative adversarial networks, thereby enhancing the quality and diversity of generated images. 2. This study proposes the normalization to balance the quality and diversity of generated images, ensuring that both are effectively considered in the fitness. Meanwhile, it introduces a gradient penalty mechanism for the discriminator, which constrains the discriminator's gradients to enhance the stability and performance of the model during adversarial training. The rest of this paper is organized as follows: Section 2 introduces the related work. Section 3 introduces ICSO in detail, including objective function and improved crossover optimization. In Section 4, a comparison of ICSO versus its competitors in terms of generated sample quality using mainstream architectures on the different datasets is made. Moreover, ICSO is compared with classical GANs to verify the diversity of ICSO. And ICSO is also applied to StyleGAN3, a mainstream network model, to validate its applicability in industry. The conclusion of this paper is presented in Section 5.
## 4 Experiments
### Implementation Details  
Network setting. The numbers of channels of the backbone model are set to \(64\)-\(64\)-\(64\)-\(64\)-\(128\)-\(128\)-\(128\)-\(256\)-\(256\)-\(256\), where each module comprises a GCN and a TCN. In the salient posture frame selection set, the filter window is configured with a length of 8, and the polynomial order is set to 2. The hyperparameters defined in Equation (4), i.e., distance and prominence, are set empirically to values of 7 and 0.0001, respectively.  
Training. The SGD optimizer is employed with a momentum of 0.9 and a warm-up phase is introduced for 5 epochs at a learning rate of 0.1 to enhance training stability. The learning rate is decreased by a factor of 0.1 at epochs 20, 35, 45 and 55. We also implement a weight decay of 0.0004. For two large datasets, the batch size is 64.  
Data processing. Following [26], we first interpolate each sequence into \(f=100\) frames in which the first and last frames remain the same. This strategy reduces the use of a lot of computing resources. To augment the data during training, we utilize random rotation following the method in [33].  
Evaluation metric. Following the instructions of [16; 32; 34], we use the accuracy metric to evaluate the performances of different methods on NTU RGB+D 60 and NTU RGB+D 120. The metric is calculated by  
\[\text{Accuracy}=\frac{1}{M}\sum_{i=1}^{M}\mathbf{1}(g_{i}=y_{i}) \tag{18}\]  
where \(M\) is the total number of samples, \(\hat{y}_{i}\) represents the prediction of the \(i\)-th sample, \(y_{i}\) is the ground-truth of the \(i\)-th sample and \(\mathbf{1}(\cdot)\) denotes the indicator function.
# Plenty of Room at the Bottom: Nanotechnology as Solution to an Old Issue in Enhanced Oil Recovery
## 4 Nanocatalysts
### Inhibition of Formation Damage  
One of the problems that should be addressed is the deposition of unstable polar heavy hydrocarbons such as asphaltenes. The presence of asphaltenes in heavy oil can lead to the adsorption and deposition onto the rock matrices, affecting formation properties such as porosity, permeability, and wettability [174; 175]. Nanomaterials have been proposed as a way to inhibit the asphaltene deposition, minimizing the possibility of damage in the rock formation and wells as well as upgrading heavy oils and reducing their viscosity [135; 174]. The function of nanoparticles is to adsorb the asphaltenes and then adsorb onto the porous media, delaying the precipitation of asphaltenes [7; 174].  
Figure 44: Effect of the absolute permeability and injection flowrate on the recovery of Ni nanoparticles and the outlet concentration. Figure reproduced from Ref. [170].
# Modeling and Analysis of RFI Impacts on Imaging between Geosynchronous SAR and Low Earth Orbit SAR
## 2 Accurate Modeling of SINR in the Presence of RFI
### Gains in Mismatched Filtering  
RFI signals from other SAR systems usually have a different Frequency Modulation (FM) rate from the disturbed SAR system and, as a result, they can be mismatched and defocused. Even so, RFI from the SAR systems could still obtain certain gain. Generally, the gain is much smaller than that of matched filtering due to the chirp signal form of RFI. To evaluate the image SINR accurately, we discuss the gains obtained in mismatched filtering.  
According to the digital signal processing theory and the principle of stationary phase (POSP), when mismatched filter is adopted on two chirp signals with a time domain amplitude of 1, different pulse width (\(T_{p1}\) and \(T_{p2}\)) and FM rate (\(k_{1}\) and \(k_{2}\)), and the  
Figure 2: Time series of GEO SARs and LEO SARs.  
sampling rate satisfies the Nyquist Sampling Theorem for both signals, the output can be written as  
\[s(t)=1/\sqrt{|k_{2}-k_{1}|}\text{rect}\big{(}t/T_{p}\big{)}\exp\Big{\{}-j\pi k_{ r}t^{2}\Big{\}} \tag{7}\]  
where \(k_{1}\
eq k_{2}\), \(k_{r}\) and \(T_{p}\) are the FM rate and pulse width of the output signal, and they can be written as (8) and (9), respectively. Details are given in Appendix A.  
\[k_{r}=k_{1}k_{2}/|k_{2}-k_{1}| \tag{8}\]  
\[T_{p}=\min\big{(}k_{1}T_{p1},k_{2}T_{p2}\big{)}/k_{r} \tag{9}\]  
Obviously, the pulse width \(T_{p}\) after mismatched filtering is related to the smaller bandwidth and FM rate of the two chirp signals.  
Moreover, the amplitude gain obtained in mismatched filtering can be expressed as  
\[G_{mismatched}=f_{s}/\sqrt{|k_{2}-k_{1}|} \tag{10}\]  
where \(f_{s}\) is the sampling rate [39]. Note that the gain in this paper refers to that in digital signal processing in particular.