esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Analysis of Collagen and Elastase Inhibition Activities of GV Extracts  
Skin aging occurs naturally over time or is influenced by external factors such as ultraviolet (UV) radiation exposure [70]. Both exposure of the skin to UV radiation and the natural aging process produce free radicals, resulting in photooxidative damage and the induction of matrix metalloproteinases, including collagenase and elastase [71, 72]. Collagen and elastin are the main structural proteins that constitute approximately 90% of the dermis and contribute to the elasticity and structural support of the skin [73]. However, collagenase and elastase degrade collagen and elastin, resulting in changes in the skin, including wrinkle formation, tough skin texture, and a lack of elasticity [74]. Thus, the inhibition of collagenase and elastase activities is the predominant factor in preventing skin aging [75]. Therefore, to confirm the anti-wrinkling ability of the GV extracts in this study, their collagenase and elastase inhibition activities were evaluated.  
Figure 2: Antioxidant enzyme activity of _Gracilaria vermiculophylla_, (**a**) SOD, (**b**) CAT, and (**c**) APX activities. GVE: _G. verrucosa_ ethanol extract; GVM: _G. verrucosa_ methanol extract; GVM: _G. verrucosa_ water extract. Different letters (a–c) indicate significant differences (\(p<0.05\)).  
The collagenase inhibition activity of the GV extracts in different extraction solvents ranged from 0 to 17%, and the highest collagenase inhibition activity was observed for GVM, followed by GVE and GVW (Table 4). GVM showed a collagenase inhibitory activity of 16.4 \(\pm\) 1.0%, which was 18-fold higher than that of the lowest GVW. The elastase inhibitory activity of the GV extracts ranged from 10 to 22%, and GVM showed the highest elastase inhibitory activity at 21.2 \(\pm\) 0.2%, followed by GVW and GVE. [PERSON] et al. [76] measured the collagenase inhibition activity of the brown seaweed _Carpomitra costata_ according to solvent fractionation, and the ethyl acetate extract showed higher collagenase inhibition activity (IC\({}_{50}\) = 7.2 \(\mu\)g/mL) than that of other extracts. These results indicated that the high polyphenol content in the ethyl acetate extract affected its collagenase inhibitory activity. In this study, GVM had the highest inhibitory activity and the highest polyphenol content compared to the other extracts. These results indicate that the high polyphenol content in GVM may affect collagenase and elastase inhibition activities.
# A Cumulant-Based Method for Acquiring GNSS Signals
###### Abstract  
Global Navigation Satellite Systems (GNSS) provide positioning, velocity, and time services for civilian applications. A critical step in the positioning process is the acquisition of visible satellites in the sky. Modern GNSS systems, such as Galileo--developed and maintained by the European Union--utilize a new modulation technique known as Binary Offset Carrier (BOC). However, BOC signals introduce multiple side-peaks in their autocorrelation function, which can lead to significant errors during the acquisition process. In this paper, we propose a novel acquisition method based on higher-order cumulants that effectively eliminates these side-peaks. This method is capable of simultaneously acquiring both conventional ranging signals, such as GPS C/A code, and BOC-modulated signals. The effectiveness of the proposed method is demonstrated through the acquisition of simulated signals, with a comparison to traditional methods. Additionally, we apply the proposed method to real satellite signals to further validate its performance. Our results show that the proposed method successfully suppresses side-peaks, improves acquisition accuracy in weak signal environments, and demonstrates potential for indoor GNSS applications. The study concludes that while the method may increase computational load, its performance in challenging conditions makes it a promising approach for future GNSS receiver designs.  
GNSS; Galileo; BOC; higher-order cumulant +
Footnote †: journal: Sensors
# Weight Feedback-Based Harmonic MDG-Ensemble Model for Prediction of Traffic Accident Severity
## 3 Weight Feedback Based Harmonic MDG-Ensemble Model for Predicting Traffic Accident Severity  
To predict traffic accident severity, the weight feedback-based harmonic MDG-ensemble model undertakes three steps. The first is to pre-process the traffic data. The data are based on traffic accident information provided by the Korean Road Traffic Authority [24]. Through pre-processing, missing values and outliers are eliminated. Attributes with duplicate meanings are integrated. Based on the variables of data on very serious traffic accidents, the severity of accidents is generated as a dependent variable, and the text and numerical variables are categorized. The second step is to select variables using the mean decrease in Gini (MDG). For the extraction of the MDG coefficient, a decision tree-based learning model capable of calculating the impurity of variables is used. By using pre-processed data, the random forest classifier is modeled for traffic accident risk classification. From this, the MDG of independent variables for traffic accident severity is extracted. In the third step, traffic accident severity is predicted through a weight feedback-based harmonic-MDG ensemble. As for the weights used for modeling, the harmonic-mean-based change rate is taken into account and is used as feedback. Accordingly, a harmonic-MDG ensemble model with excellent performance was assembled. Figure 4 shows the weight feedback-based harmonic MDG-ensemble model process for the prediction of traffic accident severity.  
Figure 3: Stacking method using the performance of classification prediction result.
# Performance and Challenges of Service-Oriented Architecture for Wireless Sensor Networks
## 10 Discussion
The main problem with this approach is that the security is applied only at the message level, not the entire system. Each node should apply an encryption mechanism/algorithm to ensure that all data is generated in a secure manner. The applied algorithm should not impact or increase cost, overhead, or power consumption. The studies in [99] and [24] consider SOM architecture security requirements through a proposed generic framework that handles different security services independently as shown in Figure 13. These services support various security functionalities such as secure communications, messages protection, management trust, and access control. The SOM architectures for WSNs should provide different functionalities that support the system. However, most of the studies on SOM architectures approaches do not provide all functionalities, including:  
1. Secure executions and communications. 2. Deployment of service providers and advertisement. 3. Service consumer support to help discover/determine and register these services. 4. Support for QoS requirements. 5. Support for massive data and high level of communication load efficiently. 6. The ability to view the heterogeneities of the underlying WSNs, which are hidden by abstractions. 7. The ability to interoperate with multi-devices and systems. 8. Client application service transparency. 9. The ability to auto-modify and auto-discover mechanisms. 10. Configurable services. Therefore, SOM architectures approaches for WSNs are based on heterogeneous services or devices; the efficiency of these services is impacted due to the response time and network lifetime. The response time of these services should be improved to increase their efficiency through UDP-based SOAP without the need for HTTP [100]. SOM architecture deals with massive data, messages and event notifications that are generated from different services and shared between different components [100]. In this case, the system reliability should ensure that these messages are delivered on time and are reliable. The reliability and QoS in WSNs are achieved by using event management mechanisms. However, some issues can be addressed by using QoS mechanisms such as congestion and faults communications, which are introduced in the OASIS and SensorsMW approaches. These approaches are developed by through selecting the most suitable available network based on QoS and service level agreements. The middleware has the ability to separate the application logic from the system logic.
## 3 Description of Comprehensive Techno-Economic (CTE) Model
### Environmental Level (EL)
#### 3.5.1 \"Political, Financial, Law and Regulatory Issues\" Area  
The \"Political, Financial, Law and Regulatory issues\" area consists of four different segments. These segments have very strong relationships and mutual influences. This area defines the impact of these key external factors on the telecom business. The outputs of the area will show the resistance of telecom to the effects of its environment and its potential on the market. The CTE model defines all items in this area. The item equation \"The potential of international business visits to the state\" is as follows:  
\[PoBV=\left(\frac{UoBV_{UITD}\cdot F_{UITD}}{NoBV_{UITD}}+\frac{UoBV_{MTD}\cdot F _{MTD}}{NoBV_{MTD}}\right).0.1\]  
This equation analyzes business visitors and their activities in the telecom operator network. It has two separate parts: it analyzes the business visitor for \"up to three days\" (UTD) and \"more than three days\" (MTD). After conducting analyses, it was concluded that most business conferences and similar events last up to three days. Visitors to such events are generally larger and better consumers of telecom operators than business users who come to visit for more than three days. Factors F give us a description of the values for both items.
# Research on Bidirectional Reservation Method for Anti-Permeation Geomembrane Slack
## 3 Analysis and Comparison of Different Methods
### Cross-Notch-Type Centralized Laying Relaxation Amount Method Analysis  
#### 3.1.1 Program Design  
The bidirectional cross-groove-shaped reservation method involves excavating a cross-groove-shaped recess with a cross-shaped bidirectional intersection. To explore the reliability of the cross-recess-type bidirectional reservation method, site earth excavation and geomembrane laying tests were conducted. First, a suitable site is selected, and the test site surface is cleaned with an SD160 bulldozer to remove roots, weeds, debris, rocks, and humus from the surface layer. Second, the cross-groove shape is excavated. The basic dimensions of the preliminary excavated test area are as follows: the length of the groove in the vertical direction is 2 m, the length of the groove in the horizontal direction is 1.5 m, the width of the groove is 0.15 m, the depth of the groove is 0.15 m, and the cross-groove is surrounded by right-angle edges. Finally, the geomembrane is laid on the cross-groove using the bidirectional reservation method.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Material Type** & **Characteristics** & **Unit** & **Value** & **Standard** \\ \hline \multirow{6}{*}{HDPE Geomembrane} & Thickness & mm & 0.8 & ASTM D5199-12 [32] \\  & Fracture strength & N/mm & 21.2 & ASTM D6693M-20 [33] \\  & Elongation at break & \% & 704 & ASTM D6693M-20 [33] \\ \cline{1-1}  & Density & g/cm\({}^{3}\) & 0.940 & ASTM D792-20 [34] \\ \cline{1-1}  & Right angle tear strength & N/mm & 99.4 & ASTM D624 [35] \\ \cline{1-1}  & Carbon black content & \% & 2.2 & ASTM D3192-09 [36] \\ \cline{1-1}  & Puncture resistance strength & N & 257 & ASTM D4833M-07 [37] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Characteristics of HDPE Geomembranes.  
Figure 2: Two-way reservation methods. (**a**) Cross-notch type, (**b**) double Z cross type, (**c**) Z and notch combination type.  
To solve the problem of the bidirectional cross-shaped reservation method producing severe creasing at the intersection, setting wiping corners at the edges is proposed. The specific test program is shown in Figure 3 below.
## 2 The Overall Architecture Design of the System
### The Field Monitoring Subsystem  
The field monitoring subsystem is based on a Client/Server (C/S) architecture. The acquisition nodes regularly collect henhouse environmental information, pack it into environmental parameter data frames and send them to the gateway nodes through the wireless module UTC-4432B1 (Hangzhou Fytoo Electronic Technology CO., LTD, Hangzhou, China). The gateway nodes then process and display the data frames and forward them to the management software of the subsystem PC after the validity of the data frames is verified by CRC. The management software communicates with the gateway nodes through a wireless communication protocol based on Modbus protocol to process and display henhouse environmental temperature, humidity, CO\({}_{2}\) concentration and NH\({}_{3}\) concentration and store them in the MySQL database for convenient data management.
# A Modified Hyrax-Type Expander Is Effective for Distal Bodily Movement of the Maximally First Molar
## 7 Discussion
### Development of a Maximly Molar Distal Movement Appliance  
To date, many researchers have developed new intraoral appliances for distal molar movement [28]. The pendulum appliance is a fixed appliance for distal movement of maxillary molars that was first reported by [PERSON] in 1992 [29]; it has been shown to be capable of distal movement of maxillary molars in a relatively short period. However, with this appliance, the orthodontic force acts on the crown of the molar, which is away from the center of resistance of the tooth, making distal crown tipping likely to occur during distal movement. [PERSON] et al. [19] used a pendulum appliance to distally move the maxillary first molars and reported an average 18.5\({}^{\circ}\) distal tipping. They also noted that this appliance can also cause mesial movement of premolars and subsequent loss of anchorage, and that care must be taken to control them. Loss of anchorage during use of a pendulum appliance has also been indicated by increased incidence of labial dislocation and tipping of the maxillary incisors [29; 30].  
In the present case, a Hyrax-type expander with a Veltri Monolateral Screw(r) attached to the palate in the sagittal direction was used for distal movement of only the maxillary left first molar. For this purpose, an expansion screw, bands, and wires for connecting the abutment bands were firmly attached to the appliance to reinforce anchorage. The appliance was also designed so that the force vector of the expansion screw passed near the center of resistance of the maxillary first molar and parallel to the occlusal plane of the maxillary first molar, allowing for distal bodily movement of the maxillary first molar. [PERSON] et al. [31] and [PERSON] et al. [32] investigated the frequency of activation of the expansion screw of a maxillary expander and reported that buccal bodily movement was more likely to occur when the screw was rotated twice a week for slow expansion compared with when it was expanded twice a day. In the present case, we planned to expand the screw once every 3 days, hoping to achieve distal bodily movement of the first molar while preventing its tipping. This resulted in distal movement of the left first molar by about 4.5 mm, with limited distal tipping of +5\({}^{\circ}\). The maxillary central incisor axis could have been limited to a slight labial tilt by utilizing the expansion screw for additional anchorage to the mucosa and multiple teeth.  
These findings suggest that the appliance used in the present case for distal movement of a unilateral molar consisting of a Hyrax-type expander with a Veltri Monolateral Screw(r), with consideration of anchorage and the frequency of activation, is effective for distal bodily movement of a unilateral molar.
# In-Band OSNR Measurement Method for All-Optical Regenerators in Optical Domain
## 4 Results and Discussion
In addition, it should be seen that our method can not only be useful for measuring the output OSNR of the all-optical regenerator but also applied to estimate the OSNR degradation induced by other nonlinear devices in optical communication links, such as all-optical modulation format conversion [21,22], all-optical wavelength conversion [23], etc. To summarize, the in-band measurement method proposed here has advantages in cost and adaptability over the traditional OSNR measurement in the optical domain.
# Resource Allocation for Network Slicing in RAN Using Case-Based Reasoning
## 4 Numerical Results
### Qualified User Ratio  
QUR is the ultimate measure of performance. We tested the QUR of an additional 20 query cases with a different number of users and the results are shown in Figure 8. PQUR is the predicted QUR using the O-KNN. TQUR is the QUR from exhaustive search for those cases. HQUR denotes the QUR by the hard slicing. Hard slicing means that each service is always allocated with \(\frac{1}{2}\) of the whole bandwidth (because there two types of services in total).  
Obviously, the PQUR by the O-KNN approach has a very low prediction error with the TQUR, and is outperformed by HQUR. Therefore, the O-KNN approach is effective.
## 3 Results  
### Effect of Sodium on Methanogen Activity  
The initial sodium concentrations in the feed sludge, first-stage reactor and second-stage reactor were 1.03 \(\pm\) 0.04 g Na\({}^{+}\) L\({}^{-1}\), 2.82 \(\pm\) 0.13 g Na\({}^{+}\) L\({}^{-1}\) and 2.64 \(\pm\) 0.08 g Na\({}^{+}\) L\({}^{-1}\), respectively. The effect of sodium on the activities of methanogens in the second-stage reactor in terms of HAc consumption is shown in Figure 1. The HAc substrate was chosen to focus study on the effect of sodium on acetate-utilizing methanogens, which was reported to be more sensitive to sodium inhibition than the hydrogen-utilizing methanogens [12].  
The dose of 2318.43 \(\pm\) 64.66 mg HAc L\({}^{-1}\) was chosen as the baseline HAc concentration, under which concentration the methanogens showed the highest activity compared to the other concentrations (data not shown here). [PERSON] et al. [7] also emphasized that the diffusion limitation of low HAc concentration (500 mg HAc L\({}^{-1}\)) and the inhibition from high HAc concentration (4000-6000 mg HAc L\({}^{-1}\)) could mask the inhibitory effect of sodium.  
At sodium concentrations that are comparable with the usual sodium concentration (2.4 g Na\({}^{+}\)L\({}^{-1}\)) applied on the second-stage reactor, the activity of methanogens on HAc consumption was not significantly affected, whereas it was 17%, 67% and 93% inhibited at higher sodium concentrations at 3.2, 5.1 and 7.3 g Na\({}^{+}\) L\({}^{-1}\), respectively. At a sodium concentration added to 9.1 g Na\({}^{+}\) L\({}^{-1}\), the methanogenic activity was completely inhibited. As the sodium concentration increased from 1.3 to 9.1 g Na\({}^{+}\) L\({}^{-1}\), the HAc degradation rates decreased from 7.09 mg to 0.06 mg HAc g\({}^{-1}\)VSS. Parallel to the HAc degradation, the total methane gas production also declined from 73.27 to 2.16 mL.
# Design of an Integrated Remote and Ground Sensing Monitor System for Assessing Farmland Quality
## 3 Data Transmission Optimization Routing Protocol  
The DTORP was developed to increase the volume of data transmission and decrease and balance battery consumption in the improved UAV-WSN system. The working principle of the DTORP consists of two primary components, namely, computing the efficient communication distance and scheduling data transmission, where data transmission scheduling is separated into three separate algorithms for promoting efficient scheduling over short, medium, and long distances.
# Dual-Gratings Imaging Spectrometer
## 2 Dual-Gratings Imaging Spectrometer
### The Relationship between the Slit and Image  
Here, an SRF (spectral delta function) function is used to describe the spectral response of the spectral system. More detailed information about this method is in the article [17]. SRF is a parameter that only depends on the spectrometer. This parameter only traces the light from the slit to the image, which implicitly assumes that the light source directly illuminates the slit. Assuming that \(x\) is the spatial dimension direction, \(y\) is the spectral dimension direction, \(y_{0}\) represents the width of the slit, \(rect(y_{0})\) is the convolution of the slit, \(LSF_{S}\) is the \(y\)-line spread function of the spectral system, and \(DET(y)\) is the pixel response of the detector. Therefore, Equation (5) can be obtained as:  
\[SRF=rect(y_{0})\otimes LSF_{S}\otimes DET(y) \tag{5}\]  
Among them, \(LSF_{S}\) can be analyzed in more detail. Here, \(L1\) and \(L2\) are the band position distributions of the two spectra. \(L(y)\) is the response distribution of the imaging system, which does not consider the spectral factor. \(F_{1}(\lambda)\) and \(F_{2}(\lambda)\) are the response distribution of the filter to the wavelength, \(G_{1}(\lambda)\)\(G_{2}(\lambda)\) are the response distribution of the grating to the wavelength. \(LSF_{S}\) is as shown in Equation (6).  
\[LSF_{S}=\frac{1}{2}[F_{1}(\lambda)\otimes G_{1}(\lambda)\otimes F_{1}(\lambda )\otimes L1+F_{2}(\lambda)\otimes G_{2}(\lambda)\otimes F_{2}(\lambda)\otimes L 2]\otimes L(y) \tag{6}\]  
In Equation (6), \(\frac{1}{2}\) represents the two bands occupying half of the energy respectively. Each of the bands needs to pass through the filter twice. The two spectra are separated by different spatial distributions \(L1\) and \(L2\). \(L(y)\) represents the aberration effect of the system without considering the spectrum.
## 5 Experimental Analysis
### Hyperparameters  
_What is the magnitude of the influence that the hyperparameter settings can have on baseline performance?_  
Hyperparameters tuning plays an essential role in eliciting the best results from many algorithms. The choice of hyperparameters is crucial for reproducible end-to-end training [17]. However, the optimal hyperparameter configuration is often not consistent in related literature, and the range of values considered is often not reported. Sometimes, a high level of stochasticity appears due to random seeds [9]. It is difficult to assess the performance of high-level algorithmic ideas without understanding lower-level choices, as performance can be heavily influenced by hyperparameters tuning and implementation-level details, making it hard to attribute progress in representation learning and deep reinforcement learning. Thus, it slows down further research [53; 54; 55]. Furthermore, poor hyperparameter selection can be detrimental to a fair comparison against baseline algorithms.  
In two mobile robot navigation challenges, we investigate three sets of hyperparameter choices for the kernel number in each convolutional layer and the corresponding pooling layer of the classic autoencoder neural network. The specific settings are shown in Figure 4, the total number of neural network hyperparameters in these three configurations are 1.8k+, 87.9k and 789.0k, respectively.  
**Results:** The evaluation criteria such as \(GTC\), \(GTC_{mean}\), \(KNN\)-\(MSE\) and average total reward can been seen in Table 3. The related learning performance of DQN and PPO methods is shown in Figure 5. The experiment results show that the effects of neural network hyperparameters are not consistent across algorithms or environments. However, the neural network hyperparameters do significantly affect learning performance, especially in the early stage of training. The performance of learnt latent feature representations is also related to the selected DRL algorithm. Usually, neural networks with more hyperparameters and deeper layers can show better function approximation and feature extraction ability. However, the vanishing gradients problem, exploding gradients problem and overfitting problem are easier to be encountered [56].  
Figure 4: Three sets of hyperparameter configurations of the encoding network with increasing trainable parameters. The input image is encoded using the pre-trained encoder to obtain the latent representation, which the RL agent then uses to output the actions.  
Figure 5: The influence of the SRL network configurations in mobile robot 2D navigation task.