esa-sceva/satcom-chunk-collection huggingface dataset:
# Mechanical Properties of Sandwich Composites Reinforced by Nanoclas: An Overview
## 2 Sandwich Composites Incorporating Nanoclays into the Core
Regarding the impact results, they are inferior to those in the open literature due to the usage of foams with different number of cells. [PERSON] et al. [25] evaluated the compression properties of a polyurethane foam incorporating variable concentrations of nanoclays (between 0 and 15 wt%), as well as other reinforcements, such as metal wires and cellulosic-based reinforcements (esparto wool, cellulose pulp and cardboard paper). The compression tests were carried out on cylindrical specimens, using a Galdabini SUN 2500 testing machine, with a 25 kN load cell at a constant speed of 5 mm/min, according to ISO 844. It was possible to conclude that the addition of nanoclays improved the compression properties of the foam and the addition of metal wires further improved these properties. In fact, the density of the foam increased with the addition of nanoclays, which increased even more with the metal wires, promoting the benefits previously reported. On the other hand, cellulosic-based reinforcements (especially the esparto wool) promoted excessive elastic buckling and, consequently, lower compression properties. In 2015, [PERSON] et al. [26] carried out high velocity impact tests in order to evaluate the effect of nanoclays content (between 0 wt% and 3 wt%) in a sandwich composed of glass fiber skins and polyurethane foam core. For this purpose, they used a gas-gun device, with a 10 g projectile and an initial speed of the projectile between 100 and 140 m/s. The best results were obtained with samples containing 0.5 wt% of nanoclays, decreasing the resistance to penetration for higher values due to the brittleness of the foam. Moreover, the agglomerations that occurred promoted weak points in the foam core [26]. To determine the effect of nanoclays content (between 0 wt% and 5 wt%) on the dynamic thermal properties of a sandwich material, in 2016 [PERSON] et al. [27] developed a study with a sandwich material composed by a pMDI (polymethylene diphenyl diisocyanate) resin core and wood strand skins. Sandwich samples were analyzed for viscoelastic properties using dynamic mechanical thermal analysis (DMTA). These dynamic tests were performed in dual cantilever mode (3-point bending) at a controlled heating rate of 5 \({}^{\circ}\)C/min, from 30 \({}^{\circ}\)C to 180 \({}^{\circ}\)C, at an oscillatory frequency of 1 Hz and an oscillation dynamic strain of 0.01%. Regardless of the storage modulus observed for 3 wt% of nanoclays being less than that obtained with neat resin, this value offered the best results. They also concluded that samples containing nanoclays showed lower crosslink density and greater rigidity than those with unmodified resin.
## 3 Result and Discussion
### Gas Chromatography-Mass Spectrometry (GC-MS) Analysis of the Optimized Red Pitaya Peel Extract
area of 14.66% followed by 9-octadecenoic acid (Z) methyl ester (11.36%), \(N\)-hexadecanoic acid methyl ester (10.50%), cyclopentacycloheptene (9.96%), 1-tetradecene (8.89%), 1-hexadecene (8.82%), oleic acid (6.17%), lauric acid methyl ester (4.93%), benzenemethanol (3.17%), linoleic acid (3.07%), octadecanoic acid (2.69%), and others. Octadecanoic acid and phenol, 2,4-bis (1,1-dimethylethyl) had been previously reported in the methanol extract of red pitaya fruit [24]. The compounds 1-nonadecene, \(N\)-hexadecanoic acid methyl ester, and oleic acid were present in the supercritical carbon dioxide extracts of red pitaya peels [25]. The phytochemical screening of the optimized red pitaya peel extract revealed the presence of chemical constituents that possess diverse biological activities. Different forms of vitamin C such as L-(+)-ascorbic acid 2,6-dihexadecanoate play a vital role as the protecting agents that shield the human skin from free radicals mediated complications. Besides, phenol, 2,\(A\)-bis(1,1-dimethylethyl) [26], 1-hexadecene [27], \(N\)-hexadecanoic acid methyl ester [28], and 9-octadecenoic acid (Z) methyl ester [29], which were among the most abundant phytochemicals in the optimized red pitaya peel extract, have also been reported to exhibit an excellent antioxidant properties. Myristic acid, which is classified as a saturated fatty acid--found naturally in animals and vegetables--is being extensively incorporated in the clinical applications for its good antifungal and antibacterial properties [30].
# Enhanced Routing Algorithm Based on Reinforcement Machine Learning--A Case of VoIP Service
## 3 The Proposed e-RLRP Algorithm
### Reinforcement Learning Used in Routing Protocol
#### 3.1.2 Reward Generation  
The mechanism for adjusting the reward value must be flexible, that is, the adjustment may not be too small that do not cause changes or too large as to induce sudden change due to a specific events. For example, if the value of the punishment after choosing a bad route is too low, the estimated value of that route will slowly decrease and probably this bad route can still be chosen for a long time. On the other hand, if the punishment value is too high, a route may no longer be chosen because of just one packet loss event. Therefore, a balance must be found between low and high rewards/punishment.  
According to Reference [40], the reward value is calculated as follows: When a node X receives a packet of node Y, an ACK is sent with the reward value to Y. To calculate the reward value, the sum of the estimated values that each neighbor has in relation to destination node Y, called \(Q_{\mathrm{dst_{bp}}}\) is divided by the corresponding number of neighbors (N). Thus, the rewardvalue is the average of the \(Q\) values of the neighbors in relation to node Y. The rewardvalue is calculated according to:  
\[\mathrm{reward}_{\mathrm{value}}=\sum Q_{\mathrm{dst_{bp}}}/N. \tag{9}\]  
Upon receiving the rewardvalue, the node Y adjusts the estimated value for node X. However if the ACK is not received, the node Y automatically set the reward value to \(-1\), that is, a punishment is generated that negatively impacts the estimated value for the route. The estimation value is defined in the next subsection.
# ChatGPT Translation of Program Code for Image Sketch Abstraction
## 4 Methodology of the M-to-PY Conversion
### M-to-PY Conversion with LLMs  
The M-to-PY conversion was the core of the study, and LLMs played a pivotal role in this process. The team used ChatGPT-4 to translate the MATLAB code into Python and eventually added it to the backend of the Skeleton App. It was proven that LLMs could understand the logic and structure of MATLAB code and translate it into Python accurately. The translated code was then tested using the test cases generated by both Bard and ChatGPT-4. The LLM was not only able to translate the code but also provided explanations and insights into its functionality and added comments to it. This was particularly helpful in understanding the complex parts of the code. The LLM was also able to identify and correct any errors in the MATLAB code, improving the overall quality  
Figure 8: The Python code produces skeleton images.  
of the Python code. The code produced by the LLM was functional, accurate, and efficient. The LLM could translate complex MATLAB code into Python, a previously challenging task for other tools and methods. This success demonstrates the potential of LLMs in programming language-to-language translation and opens new possibilities for future research and applications. The translation process was not without its challenges. The researchers encountered issues with the size of the code snippets that could be fed to the bot, differences in the data structures assumed by the bot, and inaccuracies in the translated code. However, they observed an improved quality of the translated code with each new version of ChatGPT.  
The authors developed a Skeleton App as a part of this project. This app takes an image as input and returns its sketches and a skeleton. The app was developed using the Flask framework for the backend and Bootstrap for the front end, with the assistance of ChatGPT-4's Code Interpreter and the DALL-E text-to-image generator. The app demonstrates the practical application of the M-to-PY conversion process.  
Throughout the project, the authors kept track of the progress and documented all findings. They then compared the performance of their M-to-PY converter with existing tools and created complex test cases to evaluate its performance.  
They also evaluated the performance of the Skeleton App using a variety of metrics, including the accuracy of the skeletonization, the speed of the app, and the quality of the user interface. On average, the skeleton generation took 4.32 milliseconds.  
This research provides valuable insights into the capabilities and limitations of LLMs. It demonstrates their potential in facilitating the development of practical apps. The findings will contribute to the ongoing research in this field and provide a foundation for future studies.
## 3 Results and Discussion
### Performance of the Fixed-Bed RFL
As a consequence, the temperatures of the sorbent bed change accordingly and those lead to a corresponding change of the CO\({}_{2}\) concentration at the outlet, as shown in Figure 4a. Since the adsorption is an exothermic process, temperature increases lead to less adsorption and thus concentration at the exit increases, whereas temperature decreases lead to the opposite behavior. In Figure 4b, it is also observed that the three temperatures along the bed are 3-7 \({}^{\circ}\)C higher than the inflow temperature in the initial 200 s. This phenomenon is presumably caused by fast water adsorption in the initial phase, as also illustrated in Figure 5. It is observed that the water adsorption is much faster than the CO\({}_{2}\) adsorption, related to its (much) higher concentration in the feed. The H\({}_{2}\)O capacity reaches 50% (1.5 mol/kg) of the maximum working capacity (3.0 mol/kg) in the initial 200 s, corresponding to a heat released of 110 kJ, calculated by assuming \(\Delta\)H\({}_{\text{H2O}}\) = 43 kJ mol\({}^{-1}\)[49]. Considering that the heat capacity of the sorbent is around 1.5 kJ kg\({}^{-1}\) K\({}^{-1}\), this heat release that is due to water adsorption is large enough to heat up the sorbent for 7 \({}^{\circ}\)C; so, it can well explain the initial temperature rise. Subsequently, the temperatures along the bed stabilize due to slower water adsorption (capacity increases from 1.5 to 2.3 mol/kg between 200 to 400 s). Among the initial temperature rises at the top, middle, and bottom of the bed, the temperature at the top of the bed shows a lower temperature rise because here the bed is more cooled by contact with the large gas inflow to the RFR. The air flow rate is an important parameter that determines the adsorption efficiency and economics. We studied the use of different flow rates in the RFR. For each of these runs, the maximum sorbent capacity was determined to check on possible degradation and to check on the mass balance. The results show no effect on the maximum CO\({}_{2}\) capacity with varying flowrate nor with time, implying that the measurement technique with the integration of the analyzer signal is consistent. The data also give an indication of the measurement accuracy and reproducibility. Moreover, the observed patterns between the CO\({}_{2}\) capacity and the inflow CO\({}_{2}\) concentration are very similar. This observation indicates that the minor variation of the CO\({}_{2}\) capacity (as presented in Figure A7 in Appendix A) is a result of the minor variation in the CO\({}_{2}\) inlet concentration (in line with the isotherm) and humidity.
## 4 Experimental Results
### Snake Length and Weight Coefficient Optimization  
One of the main drawbacks of snake similarity is its heavy computational cost. A sensitivity analysis is conducted to investigate the performance of snakes for different lengths [17]. The snake length has to be set at a minimal threshold to keep the connectivity. Thus, a snake that is too short cannot discover the entire topology of the network in both space and time. A short snake length may also provide cluster results in which a cluster contains links that are not all connected with each other. The connected clusters' dissimilarity (CCD) is used to evaluate the performance of the algorithm for different snake lengths and weight coefficient values. The CCD metric focuses on the inter-cluster dissimilarity between a given cluster and its neighboring cluster. It is defined by [17]:  
\[CCD=\frac{\sum_{i=1}^{K}\sum_{k=1+i}^{K}\delta_{ik}|\overline{v_{i}}-\overline {v_{k}}|}{\sum_{i=1}^{K}\sum_{k=1+i}^{K}\delta_{ik}}, \tag{48}\]  
Figure 7: Amsterdam reduced network with 208 roads [24].  
where \(\overline{v_{i}}\) is the mean speed of the cluster \(i\), \(\delta_{ik}=1\) if \(i\) and \(k\) are the indices of connected clusters and \(\delta_{ik}=0\) otherwise. This evaluation metric is to be maximized. The mean values of CCD for the 48 periods are computed using different snake lengths based on the percentage of the spatio-temporal size of the network roads (Figure 8). It is clear that the algorithm produces similar results for snake lengths bigger than 40% of the spatio-temporal size of the network of roads. Therefore, the length of the snake is set to 40%, and the weight coefficient \(\phi\) is selected to be equal to 0.7 in order to obtain the maximum mean values of CCD (Figure 9).
# Nicotinamide Adenine Dinucleotide (NAD) Metabolism as a Relevant Target in Cancer
## 8 Other NAD+-Dependent Enzymes in Cancer
### PARPs in Cancer  
PARP1, known as the guardian of DNA integrity, is the most studied member of the PARP family [84]. The PARP1 enzyme is activated in response to DNA damage, requiring high levels of NAD+ in the cell, and is thus dependent on NAMPT activity. Excessive activation of PARP1, due to the action of genotoxic agents, for example, dramatically reduces ATP and NAD+ pools, regulating sirtuin activity and, therefore, cellular homeostasis. If the DNA damage is not repairable, PARP1 promotes apoptosis through the activation of p53 under normal conditions. However, PARP1 can also regulate oncogenic transcriptional factors. Depending on the context, PARP1 has been reported to act as an oncogene or tumour suppressor [17; 84]. Most tumours overexpress PARP1 in response to increased DNA damage aggravated by radiation and chemotherapy treatment. In fact, high levels of PARP1 have been found in breast, ovarian and lung cancers and non-Hodgkin lymphoma [43; 84]. In colon cancer, PARP1 has been found to have a dual oncogenic and suppressive function [81; 85]. In addition to DNA damage, PARP1 is involved in other physiological cell processes, such as proliferation, cell cycle regulation, gene transcription, inflammation and cell fate. PARP1 regulates ERK, allowing the activation of proangiogenic and metastatic factors. PARP1 also regulates the transcription factor E2F1, which reduces apoptosis in tumour cells [86; 87]. Inhibition of PARP1 by olaparib has been tested in clinical trials for tumours of different origins. Pharmacologically, tumour cells are in general more sensitive to PARP1 inhibition than healthy cells. This sensitivity may be because tumour cells lack alternative DNA repair mechanisms. However, resistance to PARP1 inhibitors has been observed [16].
# Tunnel-Free Distributed Mobility Management (DMM) Support Protocol for Future Mobile Networks
## 6 Future Work  
Like most of the DMM-based protocols proposed, our work also focused on a single MN's handover. In future work, to further improve the dimensions of the proposed research, we will be focusing on the DMM handover issues when multiple MNs perform a handover from the same previous network to the same destination network simultaneously, rather than a single MN handover. Moreover, we are also currently analyzing the cost of the proposed approach. In future work, we intend to compare the proposed approach in terms of cost with the benchmark protocols. In addition, we also intend to undertake a performance evaluation with other mobile IPv6-based schemes using the MBB approach. We have considered this aspect in the future work for this research. For now, we have performed performance evaluations with current existing deployed protocols for mobility management.  
Figure 9: Packet loss versus \(\rho_{f}\).  
**Author Contributions:** Conceptualization, M.A., S.M. and M.Z.; Data Curation, M.A.; Formal Analysis, M.A., M.Z., N.M., K.I.; Investigation, M.A., S.M., M.Z., N.M.; Methodology, M.A., M.Z. and S.K.; Validation, M.A., S.M., M.Z.; Resources, M.A., M.Z.; Simulation, M.A., M.Z., K.I.; Writing--Original Draft Preperation, M.A., S.M., M.Z., N.M., K.I.; Writing--Review and Editing, M.A., S.M., M.Z., S.K.; Supervision, S.M.; Co-Supervision, M.Z.  
**Funding:** This research received no external funding.  
**Conflicts of Interest:** The authors have no conflict of interest to declare.
## 4 Experimental Evaluation  
### Experimental Procedure  
To verify the effectiveness of the proposed control method, multiple-scenario experiment with different desired trajectories was carried out. In the first scenario of the trajectory-tracking experiment, sinusoidal signals with amplitude 20\({}^{\circ}\) and 0.2, 0.5, 0.8, and 1 Hz frequency were given as desired trajectories. To evaluate the applicability of the proposed control method for a rehabilitation robot, a human-like pattern signal was employed as a desired trajectory in the second scenario of the experiment. The modified knee gait data profile in textbook [29], where the maximum flexion angle is set at 28\({}^{\circ}\), was used to verify the control performance. In both experimental scenarios, the system was tested under two load conditions: no load and load m = 2.5 kg.  
In all experimental scenarios, the sampling time of the discrete-time control system was \(T_{s}\) = 5 ms. All the data were recorded for ten cycles from the start time of the experiment. The data were processed by MATLAB software version R2016b. The proposed controller is also compared with the conventional discrete-time sliding mode control (DSMC) method in terms of tracking performance. The parameters of both controllers after being well-tuned are provided in Table 3.
# Non-Toxic Anesthesia for Cataract Surgery
## 3 Results  
The percentage of patients who reported not having felt the slightest pain during surgery was 20%, the same in both groups. In group 1, 40 patients (80%) graded their pain between 2 and 3, while none graded pain 4 or above; in group 2, 40 patients (80%) graded their pain between 2 and 3, while none graded pain 4 or above. Fifteen patients (30 %) in group 1 and ten in group 2 (25%) required supplemental anesthesia, to reinforce the anesthesia in group 1 another drop of Oxybuproocaine hydrochloride 0.4% was instilled, while in group 2 a focal application through a cotton bud for 10 s was applied on the incision site. No intraoperative complications were recorded in either group. The mean surgery time was 8.5 \(\pm\) 1.9 min in group 1 and 8.7 \(\pm\) 1.5 min in group 2. No epithelial defects were detected at the end of the surgery.  
No significant changes of corneal esthesiometry were observed after surgery in both groups (Table 1).  
\begin{table}
\begin{tabular}{l c c c} \hline \hline  & \multicolumn{3}{c}{**OSDI**} \\ \hline  & Pre-operative & 1 month & 3 months \\ \hline Group 1 & \(10.4\pm 1.3\) & \(18.2\pm 3.8\) & \(10.8\pm 6.6\) \\ \hline Group 2 & \(10.5\pm 1.3\) & \(15.9\pm 3.5\) & \(10.3\pm 7.2\) \\ \hline \(p\)-value & 0.64 & 0.003 & 0.87 \\ \hline  & \multicolumn{3}{c}{**T-BUT**} \\ \hline  & Pre-operative & 1 month & 3 months \\ \hline Group 1 & \(14.3\pm 3.4\) & \(6.1\pm 2.2\) & \(13.8\pm 3.2\) \\ \hline Group 2 & \(15.1\pm 4.6\) & \(11.9\pm 1.9\) & \(13.9\pm 3.9\) \\ \hline \(p\)-value & 0.88 & 0.048 & 0.98 \\ \hline  & \multicolumn{3}{c}{**Corneal Esthesiometry**} \\ \hline  & Pre-operative & 1 month & 3 months \\ \hline Group 1 & \(57\pm 25.9\) & \(58.3\pm 25.7\) & \(57.9\pm 24.8\) \\ \hline Group 2 & \(56.1\pm 30.7\) & \(57.8\pm 27.7\) & \(57.8\pm 26.5\) \\ \hline \(p\)-value & 0.75 & 0.84 & 0.94 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Changes of ocular surface disease index (OSDI) and tear break up time (T-BUT) from baseline to 3-months post-op.  
The levels of pain sensed by the patients and reported at the end of the operation were low in both groups, without any significant differences (\(p\) = 0.8). Moreover, only a few patients (20%) required additional anesthesia in order to complete surgery safely. OSDI score and T-BUT were assessed at baseline and 1 and 3 months post-op. Pre-operative OSDI was overlapping in both groups (\(p\) = 0.9), while 1 month post-operative group 2 showed healthier values (\(p\) = 0.04), and 3 months after surgery the values returned similar in both groups, with no statistical differences (\(p\) = 0.87) Table 1.  
Additionally, T-BUT showed a statistical difference 1-monthpost-op (\(p\) = 0.048) Table 1. Only two patients suffered from dry eye syndrome in group 1 one-month post-op, while none of the patients in group 2 complained of dry eye symptoms or showed signs of corneal epithelium impairment.
# A Novel Signal Design and Performance Analysis in NavCom Based on LEO Constellation
## 4 Performance Evaluation
### Communication Performance Analysis
In Figure 23, it is obvious that under the worst conditions, the BER can reach 9.47 \(\times\) 10\({}^{-11}\) in the downlink, significantly surpassing than the threshold of 1 \(\times\) 10\({}^{-6}\), while \(E_{b}/N_{0}\) has a redundancy of 13.072-23.8268 dB and \(C/N\) has a redundancy of 7.0514-17.8062 dB. From the link communication budget shown below:  
* Our proposed signal scheme is capable of meeting the communication conditions between LEOs and terrestrial locations. * The low power of the user terminal and the link bandwidth tradeoff settings of the communication signal design can provide technical support for the miniaturization of the transceiver terminal and multi-user cluster. * The scheme has the potential for expansion towards multi-orbit and multi-LEO satellite networking. Figure 22: Uplink parameters via STK. With the relative movement between the ground station and the satellite, sampling is performed every 1 min, and the 1–day period is divided into 8 coverage slots. The power received via the uplink, carrier-to-noise ratio, and bit signal-to-noise ratio (Eb/N0) were \(-\)155.607 to \(-\)144.77 dB, 3.4814 to 14.3186 dB, and 18.4299 to 29.2671 dB, respectively, and the bit error rate (BER) was 1 \(\times\) 10\({}^{-30}\). These indicators show that the sensitivity of the satellite receiver is equivalent to that of the existing GNSS ordinary receiver, the carrier-to-noise ratio tolerance is very high, and the bit error rate can be kept extremely low. In terms of the communication field, our proposal has significant worth.
## 3 Experimental Results
### Dual LO Generation
In fact, previous studies have observed linewidths in the sub-kHz range with similar hybrid integrated lasers [20]. However, due to limitations in our experimental setup, we were unable to directly measure these ultra-narrow optical linewidths in this work, which explains why the measured linewidth appears broader than the values reported in the literature.