esa-sceva/satcom-chunk-collection huggingface dataset:
# Energy Efficient Routing Protocol in Novel Schemes for Performance Evaluation
## 2 Materials and Methods
### Modified Gravitational Search Algorithm--ORS  
MGSA-ORS is a cluster-based, energy-proficient convention that guarantees even-handed energy load dissemination across the entirety of the organization's sensor hubs.  
1. The selection of cluster heads relies upon the sink distance, likelihood, and leftover energy of hubs. It describes the proposed convention's presentation.
2. The inter- and intra-cluster multi-hop station transmission favored the least energy escalated multi-bounce course.  
The probability of individuals from the clusters imparts information straightforwardly to the clusters head. The capability of CH is not just the total information; it additionally sends information to the BS by means of multi-jump directing pathways. The hub distance from the sink is the most significant determination rule. Above the inside of the cluster's correspondence is limited to the cluster's head--those are nearer to base station forestall the group heads from high mortality. The hubs impart information for diminishing the energy/information parcel by picking a reasonable method with a minimal measure of correspondence energy, which shows the delay network organization initiate grouping process cluster development. CH selection start sensor hubs look for transfer hubs for CH intra-group-directing data transmission MGSA and hand-off determination. The appropriate transfer hub determination and data communication to the sink hub is a residual energy node distance from sink setup stage and the probability of the remaining energy node distance to the CH and steady state stage are the greatest probability. Because of the above new methodology, the WSN's life will be expanded.  
The MGSA-ORS activity is isolated into adjustments, every one of which involves two stages: setup and consistent state. Clusters are coordinated during the arrangement stage, and multi-ways from each clusters portion of the CHs and BSs are chosen. The information is provided during the consistent state stage. As such, the arrangement stage span is more limited than the consistent state and progressively eases the span, concerning networks above minimization. Figure 3 portrays the proposed framework for the proficient choice of the group head and improvement of the forwarder hub determination. We design protocols for WSNs, optimization of energy consumption is the main issue and a popular solution for this issue is employing clustering techniques In the clustering scheme, the aim is to efficiently and effectively manage the WSN energy consumption by dividing the sensors into small groups called clusters. In addition, the aim is compressing data in clusters and transferring the compressed data to the base station using a limited number of sensors, namely cluster heads.
## 3 Results and Discussion
### Outlier Screening and Sample Set Division  
The MCCV method was used to eliminate abnormal samples related to the sample spectra and tea polyphenol content in this study. The number of cycles was 1000, and the threshold was set to three times the sample mean (MEAN) and standard deviation (STD). The MEAN-STD distribution is depicted in Figure 5. The samples were screened for MEAN greater than 3.069 or STD greater than 2.728 for tea polyphenol content in the range of 400-1050 nm waveband, obtaining sample numbers 17 and 70 as abnormal samples (Figure 5a); the samples were screened for MEAN greater than 4.067 or STD greater than 4.260 in the range of 1000-1650 nm waveband, and sample numbers 17 and 73 were anomalous (Figure 5b); the samples were screened for MEAN greater than 3.153 or STD greater than 2.919 in the 400-1650 nm waveband, and three samples were recognized as abnormal samples (Figure 5c).  
Figure 4: Raw spectra of fresh tea leaves in different waveband ranges. Mean \(\pm\) standard deviation of the samples from two different tea varieties. The upper and lower boundaries of the translucent areas represent \(\pm\) standard deviation. (**a**) Vis/short-wave NIR spectra (400–1050 nm), (**b**) long-wave NIR spectra (1000–1650 nm).  
Figure 5: MEAN-STD distribution of the predicted residuals of tea polyphenol content in different waveband ranges. (**a**) Vis/short-wave NIR spectra (400–1050 nm), (**b**) long-wave NIR spectra (1000–1650 nm), and (**c**) Vis/short-wave and long-wave NIR spectra (400–1650 nm). Different colors represent the predicted residuals of tea polyphenol content in different waveband ranges.  
The KS algorithm was employed to divide the sample set after eliminating the abnormal samples, and the data within the sample set were analyzed (Table 1). In all waveband ranges, the MEAN, coefficient of variation (CV), and STD of the whole set of samples were between the calibration set and the prediction set, indicating that the tea polyphenol content of fresh tea leaves had strong variability in this study. This might be caused by the wide range collection of tea leaf positions (the first leaf position to the fourth leaf position of new shoot), resulting in high heterogeneity among tea polyphenols content of fresh tea leaf samples [8; 39]. The skewness of all data set is greater than 0, which indicates that the data set do not conform to the normal and right skewed distribution. Kurtosis for both the whole set and the calibration set are less than 0, indicating that the tails of the data set are finer than the normal distribution and have fewer extreme data; the kurtosis of the prediction set is greater than 0, indicating that the tails of the data set are thicker than the normal distribution and the extreme data have a wider distribution. The range of tea polyphenol content in the calibration set covered the range in the prediction set, and the tea polyphenol content in different sample sets were evenly distributed with relatively similar MEAN and STD. Therefore, the sample set division is reasonable and suitable for establishing a robust model.
## 2 Materials and Methods
### Catalyst Preparation  
Excluding the first series of experiments, which were conducted without a catalytic material, the rest used one of two catalysts: Al\({}_{2}\)O\({}_{3}\) supported Rh-LaCoO\({}_{3}\) and Ni/Al\({}_{2}\)O\({}_{3}\). As a catalyst support, both ceramic tubes of the reactor were used so that inner ceramic tube was completely impregnated with a catalyst, whereas the outer ceramic cylinder was covered with catalytic material only on the inner surface.  
The rhodium promoted La-CoO\({}_{3}\) catalyst was prepared by wet impregnation, dissolving stoichiometric amounts of La(NO\({}_{3}\))\({}_{3}\):H\({}_{2}\)O (Sigma-Aldrich, \(>\)99.9%) and Co(NO\({}_{3}\))\({}_{2}\):6H\({}_{2}\)O (Sigma-Aldrich, \(\geq\)98%) in a water solution containing the ceramic tubes and a few drops of nitric acid [37]. The solution was completely evaporated and then the ceramic tubes were dried for 2 h at 120 \({}^{\circ}\)C. Calcination was carried out at 800 \({}^{\circ}\)C for 3 h with an air flow of 150 mL min\({}^{-1}\) and heating rate of 10 \({}^{\circ}\)C min\({}^{-1}\). The calcined ceramic tubes were further impregnated with a Rh(NO\({}_{3}\))\({}_{3}\):H\({}_{2}\)O (Sigma-Aldrich) solution using an amount of rhodium corresponding to 1 %wt., then drying and calcination were repeated. In the next section, this compound will be noted as Rh/LaCoO\({}_{3}\)/Al\({}_{2}\)O\({}_{3}\). Resulting weight hourly space velocity (WHSV) was 0.54 h\({}^{-1}\).  
The Ni-based catalyst was prepared by wet impregnation of the ceramic tubes in an Ni(NO\({}_{3}\))\({}_{2}\):6H\({}_{2}\)O (Sigma-Aldrich, \(>\)99.9%) water solution, followed by drying and calcination under the same conditions as described above. WHSV was 0.63 h\({}^{-1}\).
## 2 Materials and Methods
### Correlation Coefficient  
The correlation coefficient is another classical parameter to measure encryption quality [37; 38], where a correlation close to zero indicates secure encryption. Its procedure follows the next steps. Suppose we analyze the horizontal direction and the color red; first, randomly, a pixel of the encrypted image is chosen. It has three basic colors, and \(z_{r}\) represents the red color. Subsequently, the adjacent pixel to it in the horizontal direction is selected, and \(w_{r}\) denotes its red component. Therefore, it is possible to calculate the correlation between \(z_{r}\) and \(w_{r}\) for \(n\) pairs of pixels in the horizontal direction and the red color with Equation (20). In addition, the means computing \(\overline{z}_{r}\), \(\overline{w}_{r}\) are indicated in Equations (21) and (22). The steps are applicable to compute the correlation in other directions and colors.  
\[r_{hz_{r},w_{r}}=\frac{\frac{1}{n}(\sum_{i=1}^{n}(z_{i,r}-\overline{z}_{r})(w_ {i,r}-\overline{w}_{r}))}{\sqrt{(\frac{1}{n}\sum_{i=1}^{n}(z_{i,r}-\overline{z }_{r})^{2}(\frac{1}{n}\sum_{i=1}^{n}(w_{i,r}-\overline{w}_{r})^{2}))}} \tag{20}\]  
\[\overline{z}_{r}=\frac{1}{n}\sum_{i=1}^{n}z_{i,r} \tag{21}\]  
\[\overline{w}_{r}=\frac{1}{n}\sum_{i=1}^{n}w_{i,r} \tag{22}\]
# Experimental Study of Nanosecond Laser-Generated Plasma Channels
###### Abstract  
Generation of plasma-channels by interaction of gas targets with nanosecond laser beams was investigated experimentally. Such laser-generated plasma channels are very promising for subsequent guiding of high peak power femtosecond laser pulses, over several tens of centimeters, as required in laser wake field electron-acceleration (LWFA). The experimental setup was based on the use of a cylindrical lens (100 mm of focal length) with the aim of proposing a technical solution easy to be integrated into a compact experimental setup for acceleration of multi-GeV electron beams using high peak-power laser systems. A pilot experiment, showing production of asymmetric plasma channels over a length of several millimeters in N and Ar targets with initial neutral-gas atomic density around \(5\times 10^{19}\) cm\({}^{-3}\), is reported. Plasma effective threshold formation was estimated, along with future optimization of the optical setup for a symmetrization of such plasma channel. Scalability of this concept to several tens of centimeters is preliminarily discussed, along with the corresponding critical requirements for an optimal LWFA scheme.  
LWFA; plasma guiding; nanosecond laser; laser-plasma acceleration +
Footnote †: journal: Applied Physics Letters
# VEPO-S2S: A VESsel Portrait Oriented Trajectory Prediction Model Based on S2S Framework
## 5 Experiments
### Qualitative Analysis
#### 5.4.2 Visual Result of the Seq2 Seq Structure  
As we can see from Figure 13, VEPO-GRU-GRU is more robust compared with VEPO-BiGRU-GRU, VEPO-BiLSTM-LSTM, and VEPO-LSTM-LSTM. (a) depicts a smooth trajectory, indicating the normal navigation of a cargo ship. (b) shows a curved trajectory, possibly suggesting avoidance maneuvers by an oil tanker. Across various vessel types and motion states, all structures of the VEPO-S2S model consistently exhibit satisfactory performance. Notably, the VEPO-S2S model with the GRU-GRU structure shows better robustness.
# Bit Rate Adaptation Using Linear Quadratic Optimization for Mobile Video Streaming
## 4 Approach
### Extending LQ for Improving QoE in Mobile Streaming  
To avoid frequent bit rate fluctuation, which significantly degrades user quality of experience [18], and to continuously update the control gain parameters with optimal values while consuming feasible resources in mobile devices, we extend the basic LQ ABR, called LQE, as follows:
# Response to Sulfur Dioxide Addition by Two Commercial _Saccharomyces cerevisiae_ Strains
## 2 Materials and Methods
### Sulfur Dioxide Determination and Sulfite Resistance Assay  
Free and bound SO\({}_{2}\) were determined using an aeration, oxidation, distillation, and titration procedure described previously [35; 36]. Samples for SO\({}_{2}\) determination were taken prior to the experiment to confirm that the juice did not already contain SO\({}_{2}\), as well as on days 1, 2, 4, 5, and 9 of the fermentations. On each sampling, 10 mL samples from each replicate were combined into one 40 mL sample in order to provide the total volume required for the SO\({}_{2}\) determination procedure. Therefore, each treatment contained a single data point on each sampling day. Molecular SO\({}_{2}\) was calculated from the free SO\({}_{2}\) concentration and the pH of the juice using the Henderson-Hasselbach equation [1; 35]. Juice pH was measured using a CyberScan 1100 pH meter (Eutech Instruments Pte. Ltd., Singapore).  
The relative sensitivity of each yeast to SO\({}_{2}\) was determined using a sulfite resistance assay [37]. Autoclaved YEPD agar medium was buffered to pH 3.5 with tartaric acid and 18 mL was poured into 25 mL sterile plastic petri dishes and left to harden. In order to create a gradient of SO\({}_{2}\) concentrations, 0.5 M sodium sulfite (Na\({}_{2}\)SO\({}_{3}\)) was spread onto the plates in the following volumes: 39.99 \(\mu\)L, 59.98 \(\mu\)L, 79.97 \(\mu\)L, and 99.97 \(\mu\)L, in order to achieve Na\({}_{2}\)SO\({}_{3}\) concentrations of 1.0, 1.5, 2.0, and 2.5 mM, respectively. These plates were left to equilibrate overnight at room temperature. The following day, dilutions of each yeast inoculum containing approximately 100 CFU/100 \(\mu\)L were spread onto plates at each Na\({}_{2}\)SO\({}_{3}\) concentration (\(n=3\)) and incubated for 48 h at 28-30 \({}^{\circ}\)C before visual assessment for growth inhibition.
## 3 Simulation
### Track Dynamic Response  
Acceleration signals are fixed at a sampling frequency of 10 kHz for all simulations. Subsequently, a Chebyshev type II digital low-pass filter with a cut-off frequency of 500 Hz is applied to filter the time series. Therefore, this high sampling frequency can increase the variance of the subsequently extracted damage features [60]. Furthermore, an artificial noise equivalent to 5% of the maximum acceleration of the initial signal is included in the numerical signal to provide a more realistic depiction of the measured rail response [51]. Figure 7 presents two acceleration time series plots, where the excitation promoted by the polygonal damage for all profiles is notorious, with a substantial increase in the vertical acceleration values when compared to a passage with new wheels. In addition, the influence of the amplitude of the polygonal damage on the measured responses is quite considerable: by comparing Figure 7a and 7b, it is visible that for an amplitude A1, the maximum response is approximately 40 m/s\({}^{2}\), while for an amplitude A2, the maximum response is around 100 m/s\({}^{2}\).  
The acceleration responses are transformed to the frequency domain by applying an FFT algorithm to capture the excitation frequencies induced by each of the polygonal wheel  
Figure 7: Acceleration time series on position Acc2 for (**a**) healthy wheel and polygonal wheel with amplitude A1; (**b**) healthy wheel and polygonal wheel with amplitude A2.  
profiles (Figure 8). The excitation frequency induced by the polygonal wheels can be given by the following expression:  
\[f_{pol.}=\frac{v}{2\pi R_{w}}.n \tag{5}\]  
where \(v\) is the speed, \(R_{w}\) the wheel radius, and \(n\) is the number of harmonics. Based on Equation (5) and knowing that the adopted speed was always 80 km/h, it is possible to predict which dominant frequencies are excited for each harmonic profile (H6-8, H12-14 and H18-19). Assuming \(n\) is equal to the value of the order of the dominant harmonic in each of the profiles, a range of excitation frequencies of 50-65 Hz, 100-115 Hz, and 150-155 Hz are obtained using Equation (5), respectively. From the analysis of Figure 8, we can observe the frequency peaks for the H12-14 and H18-19 profiles around the expected values, while for the profile H6-8, a flat spectrum is obtained without showing any significant peak frequency. This can be explained by a smooth damage profile related to this harmonic group (Figure 4), which has a less evident harmonic peak than the other two profiles.
## 5 Conclusions  
In this article, we present the collocation method with a new space-time radial basis function for dealing with backward heat conduction problems. The innovative concepts of our method are addressed in detail. We conclude the findings as follows:  
1. In this article, the novel space-time radial polynomial basis function (SRPBF) is first proposed for the collocation method. Since the SRPBF is infinitely differentiable and the corresponding derivative is a smooth and nonsingular series function, the shape parameter is not required in the proposed method, which may mitigate the main issue in the conventional radial basis function collocation method for determining an optimal shape parameter.
2. We propose a new idea for collocating the source points using the inner and outer source collocation schemes. Results demonstrate that the outer source collocation scheme may obtain more accurate results than the regular inner source collocation scheme. Furthermore, results indicate that the location of the source points outside the space-time domain may be not sensitive to the accuracy while the dilation parameter ranges from 2 to 7.
3. Results of numerical examples demonstrate that our approach may obtain better solutions than those of the conventional radial basis function collocation method. Since all the collocation points are placed in the space-time domain, the one-dimensional heat conduction initial value problem is turned into the two-dimensional boundary value problem such that the heat conduction problem can be solved without utilizing the conventional time-marching techniques. It is found that the absolute error of our approach does not propagate with the simulation time. Additionally, our approach may yield better solutions than those of the radial basis function collocation method with the time-marching scheme.
4. Numerical results demonstrate that the terms of the SRPBF may not be sensitive to the computed results. Furthermore, the absent heat data on the inaccessible boundary can be recovered with high accuracy even when severely ill-posed inverse backward heat conduction problems under large noises are considered.  
[PERSON]-[PERSON] developed the conceptualization, and wrote the manuscript; [PERSON]-[PERSON] worked on the mathematical development, performed the numerical analysis, and wrote the manuscript; [PERSON]-[PERSON] analyzed the data; [PERSON]-[PERSON] worked on the data curation. All authors have read and agreed to the published version of the manuscript.  
Figure 14: The RMSE versus different noise levels.  
**Funding:** This study carried out in 2019 to 2020 (MOST 108-2621-M-019-008) was supported by the Ministry of Science and Technology (MOST), Taiwan, the Republic of China.  
**Acknowledgments:** The authors appreciate the MOST for providing financial support.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
## 7 Conclusions  
As the results show, the accuracy of trajectory tracking based on nonlinear guidance logic is suitable for hydrographic USV profile tracking, and the presented unit configuration permits very precise track following with a mean XTE of around 30 cm. This is a very good result, if we compare this performance with a traditional manned hydrographic vessel. In the authors' opinion, trajectory tracking based on nonlinear guidance logic for hydrographic measurements can be implemented on a wide variety of USVs providing correct nonlinear guidance logic and PID parameters.  
The difference between the track realized by the unit and the real sonar track can be significant and depends on wind speed and direction. This difference can be diminished using either software offsets or antenna physical displacement. The other approach is to use the RTK signal directly for navigation during the hydrographic survey.  
Conceptualization, A.S. and P.B.; methodology, A.S. and P.B.; bibliography review, A.S., P.B. and B.D.-S.; acquisition, analysis, and interpretation of data, A.S., P.B. and K.N., writing--original draft preparation, A.S. and P.B.; writing--review and editing, A.S., P.B., K.N. and B.D.-S. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the European Regional Development Fund under the 2014-2020 Operational Programme Smart Growth as part of the project \"Developing of autonomous/remote operated surface platform dedicated hydrographic measurements on restricted reservoirs\" implemented as part of the National Centre for Research and Development competition, INNOSBZ.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# Adsorption of Coxsackievirus in Sediments: Influencing Factors, Kinetics, and Isotherm Modeling
## 3 Results and Discussion
### Effect of Different Factors on Virus Adsorption
#### 3.1.4 Humic Acid  
The influence of humic acid on the adsorption of CA16 by clay is illustrated in Figure 3d. As humic acid concentrations increase, a more pronounced inhibitory effect is observed, resulting in a gradual decline in adsorption capacity. This can be explained by  
Figure 3: Adsorption of CA16 with different varied factors. (**a**) sediment particle sizes; (**b**) temperatures; (**c**) pH values; (**d**) humic acid concentrations; (**e**) initial concentrations; (**f**) error bar plot of experiments under the same condition.  
the competitive interaction between the virus and humic acid for available adsorption sites on the clay particle surface [55]. This competition reduces the availability of adsorption sites for the virus, leading to a decrease in adsorption capacity. Additionally, higher humic acid concentrations contribute to increased solution viscosity and the formation of organic colloids due to elevated molecular weight. These colloidal substances can form complex structures with the virus, impeding effective contact and adsorption onto the clay particles.