esa-sceva/satcom-chunk-collection huggingface dataset:
# Physical-Layer Security in Power-Domain NOMA Based on Different Chaotic Maps
## 3 The Proposed C-DL-NOMA System Model
### Hyperchaotic Map
A global bit scrambling (GBS) system significantly enhances execution of image encryption. An input image, \(F\), has eight bits and an intensity value between 0 and 255. The image's intensity values are globally shuffled, bit by bit, to decrease the correlations among adjacent pixels. GBS also modifies the intensity value of each pixel, meaning it introduces pixel substitution simultaneously. GBS is achieved using the following two steps:To obtain a one-dimensional binary sequence, \(\hat{b}^{0}\), the intensity value per pixel is defined as binary digits, one by one. To obtain the index sequence, \(k^{\hat{y}}\), in ascending order, the hyperchaotic sequence, \(k\), is organized. 2. \(\hat{b}^{0}\) is globally shuffled to be a one-dimensional binary sequence depending on the index sequence, \(k^{\hat{y}};\hat{b}^{1}_{\hat{\mathbf{i}}}\ =\ \hat{b}^{0}_{\hat{k}^{\hat{y}}}\), \(i\in[1,8 mn]\). GBS is produced via a complex nonlinear relationship between the input and the encrypted images, which enhances security. The Encryption and Decryption Process are carried out in seven steps: 1. \(m\times n\) indicates the input image \((F)^{\prime}s\) size. The binary sequence, \(\hat{b}^{1}\), is achieved through GBS operation on an image, \(F\). 2. According to the first DNA coding rule, \(\hat{b}^{1}\) is encoded in a DNA sequence, \(d^{1}\). The DNA addition to each element of \(d^{1}\) is executed to obtain \(d^{2}\)[28]; \[d^{2}=\left\{ \begin{array}{l}d^{2}_{1-\hat{\mathbf{i}}}=d_{0}+d^{1}_{1}\\ d^{2}_{1-1}+d^{2}_{\hat{\mathbf{i}}}\end{array} \right.\quad\mathrm{i}\ \in[2,4 mn]\] (20) where \(++\) indicates the DNA addition process and \(d_{0}\) is a specific initial value. 3. A sequence, \(k^{\varphi}=[k_{1},k_{2},\ldots,k_{mn}]\), is reduced from \(k\), and the decimal sequence, \(k^{\varphi}\), is transformed into binary digits, \(b^{k}\). According to the third DNA encoding rule, \(b^{k}\) is encrypted into \(d^{k}\). To obtain a sequence, \(d^{3}\), DNA addition among \(d^{2}\) and \(d^{k}\) is performed. 4. A threshold function, \(f(s)\), is expressed as follows [28]: \[f(s)=\left\{ \begin{array}{l}0\,,0\leq\frac{s}{255}\leq 0.5\\ 1\,,\,0.5<\frac{s}{255}\leq 1\end{array} \right.\] (21)  
A cut sequence of \(k\), \([k_{1},k_{2},\ldots,k_{4 mn}]\), is converted to a mask sequence, \(w\), using Equation (21). The mask sequence, \(w\), and \(d^{3}\) are utilized to create \(d^{4}\). To obtain \(d^{4}_{\hat{\mathbf{i}}}\), the corresponding \(d^{3}_{\hat{\mathbf{i}}}\) is complemented. If \(w_{\hat{\mathbf{i}}}=1\), or else it is not varied. This is how the DNA sequence, \(d^{4}\), is obtained. 5. To obtain the binary sequence, \(\hat{b}^{2}\), \(d^{4}\) is decoded using the first DNA coding rule. 6. To obtain the encrypted binary sequence, \(\hat{b}^{3}\), bitwise XOR is executed between \(\hat{b}^{2}\) and \(\hat{b}^{\mathrm{k}}\). 7. The encrypted binary sequence, \(\hat{b}^{3}\), is converted to an encrypted image, \(T\). The decryption process is identical to that of encryption in reverse order.
## 4 Experimental Results
### Analysis of Toy Problem  
The method of learning independent relationships was based on the assumption that tasks were independent of each other, and the method of learning joint relationships uses the strong assumption that the tasks are related to each other. For further analysis on the difference between independent representation and joint representation, we conducted a simple experiment using the MNIST (Modified National Institute of Standards and Technology) dataset. For a task that uses binary classifying numbers, we chose two numbers (five and nine) among ten digits of MNIST data, and gave binary labels 1 and 0 respectively. For another task of noise recognition, we added some gaussian noise with \(\sigma=0.2\) to original images, and assigned binary label 1 if an image was noisy, and 0 otherwise. Figure 7 shows the example images of MNIST data. In Figure 7, the images from the top and second row indicate that 50% of images are noisy for each digit, we call this dataset p50. The third and fourth rows indicate that 10% of \"5\" images and 90% of \"9\" images are noisy, which is denoted as p10. Likewise, we made 10 different datasets by changing the portion of noise image in the \"5\" digit class from 10% to 90%. Note that, the portion of noise image in the \"9\" class changes from 90% to 10%, and thus, the total ratio of noisy data is always 50% of total data. The number of training data is 10,000, and 1000 for test data for each set. Experiments were conducted on the nine datasets and compared to change of performance. The network structure consisted of two convolutional and max pooling layer followed by one fully connected layer with 50 hidden nodes. For each experiment, we set the learning rate as 0.01, batch size as 1000, and used 50 epochs training. For each dataset, the learning was done for 20 random initializations to get average performance.  
Figure 7: Examples of noisy MNIST data with addition of Gaussian noise.  
Figure 8 shows the change of classification rate of digit recognition tasks. When the ratio of noisy data to original data was even (p50), which means two tasks are independent, our proposed method for correlated tasks was worse than those for independent tasks. On the contrary, when the discrepancy of noisy data portion between two digit classes became large, the joint representation showed better performance than the independent representation. We can also observe that the performance improvement in the p10 and p90 sets was less than that in the p20 and p80 sets. This phenomena may be due to the limited size of data in a specific joint class, such as \"digit 5\" and \"noisy\" class in the p10 set and \"digit 9\" and \"noisy\" class in the p90 set.
# Railway Wireless Communications Channel Characterization
## 4 Communication Channel Measurement Methodology and CCT Description
For example, some typical Key System Requirements from the main railway applications in terms of latency are listed in Table 3.  
In order to well understand how the system works, a sequence diagram of the communication between the parts of the systems is shown in Figure 3.  
The CCT Agent and CCT Server are in continuous communication in order to start and end the test at the hour already configured by the user, to perform the desired test, and to send the result files. However, the CCT Server communicates with the CI in the configuration and after processing the files, sending the results. Figure 3: Sequence diagram between CCT Agent, CCT Server, and CCT CI. \begin{table}
\begin{tabular}{c c} \hline \hline
**KSR** & **Max. Latency (s)** \\ \hline ETCS & 3.5 \\ CBTC & 0.1 \\ Critical Voice & 0.15 \\ Critical data & 0.1 \\ Critical Video & 0.1 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: KSR from some applications [18]. These three parts of the system allow measuring the different communication channels and analyzing their results. In this case, the measurements will be carried out on a real track in Spain.
## 2 System Description  
We assumed an enclosure with an inside round diagonal corner square shape. The corner radius \(R\) varies as \(R\) = 0.2; 0.4; 0.6 and 0.7. The enclosure was supposed to be filled with a Fe\({}_{3}\)O\({}_{4}\)-water nanofluid. The solid volume fraction \(\phi\) of the nanofluid was in the order of \(\phi=0.05\). The nanofluid Prandtl number \(Pr\) was set at \(Pr\) = 0.7. The nanofluid Rayleigh number \(Ra\) varies from \(Ra=10^{3}\) to \(Ra=10^{5}\). The nanofluid Hartmann number \(Ha\) varies from \(Ha\) = 0 to \(Ha\) = 50. The nanofluid Eckert number \(Ec\) was set at \(Ec=10^{-5}\). The thermophysical properties of the nanofluid were based on the properties of both fluid and magnetic particles, as summarized by Table 1. The enclosure was subjected to hot and cold imposed temperatures at the walls depicted by Figure 1. The other walls were adiabatic. The enclosure was also subjected to a magnetic source as depicted by Figure 1.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Therophysical Properties** & **Fluid** & **Magnetic Particles (Fe\({}_{2}\)O\({}_{3}\))** \\ \hline Density \(\rho\) & 997.1 kg/m\({}^{3}\) & 5180 kg/m\({}^{3}\) \\ Thermal conductivity \(k\) & 0.613 W/mK & 9.7 W/mK \\ Specific heat capacity \(C_{p}\) & 4179 J/kgK & 670 J/kgK \\ \hline \hline \end{tabular}
\end{table}
Table 1: Thermophysical properties of the fluid and the magnetic particles.
## 4 Conclusions  
This study examined the characteristics of urban wastewater sludge after natural drying for five years, following accelerated laboratory freeze-thaw-drying cycles and after composting (with and without the addition of zeolite). The findings of this research led to the following conclusions:  
1. The composing of sludge facilitated the stabilization of wastewater sludge while retaining essential nutrients for the agricultural sector, namely, nitrogen and phosphorus. This effect was particularly pronounced when zeolite was added to the mixture (specifically, at a volume of 2% of the total mass). In this experiment, approximately 40% of the total nitrogen was preserved, which elevated its concentration in the final product to levels comparable with low-concentration organic fertilizers. However, despite the increased nutrient concentrations, the nitrogen and phosphorus contents in the treated sludge remained lower than those in traditional mineral fertilizers used in agriculture. This indicates the need for additional processing or combined use with other nutrient sources to achieve optimal efficiency in the agricultural sector. To maintain phosphorus compounds within acceptable levels, effective aeration of the mixture was essential.
2. Both the composing and thermal treatments did not significantly affect the concentration of heavy metals in the processed sludge. In cases where heavy metals are present in the initial feedstock, additional treatment methods must be considered to enable the safe use of the final product as a fertilizer.
3. The composing of sludge can significantly reduce the concentration of petroleum products in the sludge (from 30 to 3 mg/kg), making this method viable for processing contaminated sludge. Further research is needed to establish the upper limits of permissible contamination levels.  
Conceptualization, E.G. and N.M.; methodology, E.G.; software, I.G.; validation, I.G. and N.M.; formal analysis, I.G.; investigation, E.G.; resources, N.M.; data curation, N.M.; writing--original draft preparation, I.G.; writing--review and editing, N.M.; visualization, I.G.; supervision, E.G.; project administration, N.M.; funding acquisition, E.G. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Research Moscow State University of Civil Engineering (grant for fundamental and applied scientific research, project no. 17-392/130).  
Not applicable.  
Data Availability Statement: Data are contained within the article.
## 3 Evaluation and Results
### Results  
In this subsection, we present the results acquired using the methods presented in the previous subsections. Before revealing the main results evaluating the performance of the wavelength-locking system, we will quantitatively present certain important parameters of our setup and the corresponding building blocks.  
We used the MRR6 from the same PIC that accommodates the previously investigated MRR3. MRR6 features a _FSR_ of 3.40 nm (~417 GHz), an in-through extinction ratio of \(ER_{\mathrm{in-through}}=6.84\) dB, a _FWHMs_ or bandwidths of \(B_{\mathrm{in-through}}=0.085\) nm (~10.4 GHz) and \(B_{\mathrm{in-drop}}=0.1234\) nm (~15.1 GHz) in the in-through and in-drop OTFs, respectively. With its in-drop extinction ratio \(ER_{\mathrm{in-drop}}\) exceeding 20 dB, the MRR6 proved suitable for the wavelength-locking application. The OTFs when terminated at the through port (red line), and when terminated at the drop port (purple line), are presented in Figure 13.  
Figure 12: Photograph of the experimental setup.  
Figure 13: MRR6’s optical transfer functions in the in-through (red curve) and in the in-drop (purple curve) directions.  
The exact wavelength of sidebands is determined by both the carrier wavelength and the mmW modulation-frequency setting. Given the properties of MRR6, the targeted mmW frequency of around 39 GHz and the DFB laser's tuning range, we chose a carrier wavelength of \(\lambda_{\mathrm{c}}=1563.97\) nm (\(-191.820\) THz) and mmW frequency \(f_{0}=37.8\) GHz. These two parameters are relevant to all the measurement results presented later on.
## Materials and Methods
### Electrochemical Measurements  
Electrochemical performance was investigated by a cyclic voltammetry (CV) test, galvanostatic charge/discharge (GCD) test, and electrochemical impedance spectroscopy (EIS) test. All electrochemical characterizations were carried out using a BioLogic VSP electrochemical workstation at room temperature. A three-electrode system was used to test the electrochemical performance of the prepared electrodes with platinum wire as a counter electrode and Ag/AgCl electrodes as a reference electrode. The obtained products such as MC//CC and q-MC//CC are used as a binder-free working electrode. The mass loading of active materials was about 2.5 mg in this work. All electrochemical characterizations were measured in an aqueous electrolyte of 1 M Na\({}_{2}\)SO\({}_{4}\) at room temperature. EIS was performed at open circuit potential in a frequency range from 10 to 0.01 Hz with an AC amplitude of 5 mV. The solid-state flexible ASC was prepared using the q-MC//CC as a positive electrode and carbon cloth as a negative electrode, which were assembled with polyvinyl alcohol (PVA)/Na\({}_{2}\)SO\({}_{4}\) gel electrolyte and a separator. The prepared two electrodes were wetted with the PVA/Na\({}_{2}\)SO\({}_{4}\) gel electrolyte for 10 min and then assembled face to face with a separator. The specific capacitance (Cs) was calculated from the CV curves and galvanostatic charge-discharge curves using the following equations, respectively:  
\[C_{s}=\frac{\int\,I(V)\,dV}{v\times m\times\Delta V}\]  
\[C_{s}=\frac{I\times\Delta t}{m\times\Delta V}\]  
where \(\int\,I(V)\,dV\) is the area enclosed by the CV curves, \(\Delta V\) (V) is the potential window, \(m\) (g) is the mass of electrode, \(v\) (mV s\({}^{-1}\)) is the potential scan rate, and \(\Delta t\) (s) is the discharge time.  
Figure 1: Scheme for the synthesis of g-C\({}_{3}\)N\({}_{4}\) quantum dots/manganese carbonates (MnCO\({}_{3}\)) nanocomposite on carbon cloth.
# Free Monoterpene Isomer Profiles of _Vitis Vinifera_ L. cv. White Wines
## 2 Materials and Methods
### Monoterpene Content in Varietal Wines  
Seventeen monoterpene isomers, found in common across all of the wines, were well separated in single MDGC-MS run (Figure S1A,B). Standards for rose oxide, linalool oxide, and nerol oxide were isomer mixtures due to a lack of commercial resources for the singe isomers. The enantiomeric ratio was determined by the peak area ratio from three MDGC-MS injections of each isomer standard. The elution order for these isomers was determined from previous research using the same column [21]. Of the monoterpenes quantitated, two were monoterpene hydrocarbons, _S_-(-)-limonene, and _R_-(+)-limonene; ten were monoterpene oxides, (2\(R\),_AS_)-(+)-_cis_-rose oxide, (2\(S\),_AR_)-(-)-_cis_-rose oxide, (2\(R\),_AR_)-(-)-_trans_-rose oxide, (2\(S\),_4_S_)-(+)-_trans_-rose oxide, (2\(R\),_5_R_)-(+)-_trans_-linalool oxide, (2\(R\),_5_S_)-(-)-_cis_-linalool oxide, (2\(S\),_5_S_)-(-)-_trans_-linalool oxide, (2\(S\),_5_R_)-(+)-_cis_-linalool oxide, _S_-(-)-nerol oxide, and _R_-(+)-nerol oxide; five were monoterpene alcohols, _R_-(-)-linalool, _S_-(+)-linalool, _S_-(-)-\(\alpha\)-terpineol, _R_-(+)-\(\alpha\)-terpineol, and _R_-(+)-\(\beta\)-citronellol (Table 2).  
Significant differences (\(p<0.05\)) for all of the monoterpene isomer concentrations were found among the eight varieties (Table 2). Higher concentrations of total isomers were found in Muscat and Torrontes wines (\(>\)1.2 mg/L) compared to other varieties, and the monoterpene constitutes of these two varieties were very similar. The lowest concentrations of total isomers (\(<\)40 mg/L) were found in Chardonnay and Pinot gris wines, which also had similar monoterpene profiles.  
Total monoterpene hydrocarbons, which contribute citrus-like aromas [22], were abundant in Muscat (18.7 mg/L) and Torrontes (15.1 mg/L) wines. Rose oxides, described as rose-like aroma [14], had greater concentrations in Torrontes (4.0 mg/L), Gewurztraminer (1.2 mg/L), and Muscat wines (1.1 mg/L). Linalool oxide and nerol oxide isomers with green, leafy, spicy, floral characters [23; 24], had greater quantities in wines from Torrontes (604.9 mg/L) and Muscat (405.2 mg/L), followed by Riesling wines (103.6 mg/L). Monoterpene alcohols with floral and fruity aromas [14; 25; 26] showed highest concentrations in Muscat (779.9 mg/L) and Torrontes (636.6 mg/L) wines.  
Not only did the isomer concentrations differ for all eight varieties, the monoterpene isomers with the greatest concentration in each varietal wine also differed (Figure 1, \(p<0.05\)). Total monoterpene alcohols were dominant in Gewurztraminer, Viognier, Muscat, and Torrontes wines. Total linalool oxides and nerol oxide isomers had higher percentage in Sauvignon blanc, Pinot gris, Riesling and Chardonnay wines.  
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Upper panel, Wines styles scores were represented by centroids surrounded by 95% confident regions. Bottom panel, all compound vectors were shown.
# Curcumin Innovative Delivery Forms: Paving the Yellow Brick Road' of Antitumoral Phytotherapy
## 2 Biological Actions of Curcumin
### Molecular Targets of Curcumin
#### 2.2.4 Curcumin Regulates the Activity of Enzymes with Roles in Inflammation and Cancer  
Pro-inflammatory enzymes are linked with various types of cancer. COX-2 is known to participate in uncontrolled cell proliferation and suppression of apoptosis, while inducible nitric oxide synthase (iNOS) and matrix metalloproteinase-9 (MMP-9) are involved in the formation of metastases [147; 148]. Several studies, both in vitro and in vivo, demonstrated that the inhibitory action of curcumin on COX-2 expression contributes significantly to its antitumor action [72; 80; 126]. Curcumin was also shown to inhibit the expression of MMP-9 in orthotopically implanted pancreatic [129] and ovarian [130] tumors in mice and the production of iNOS in chronic colitis [127].
## 4 Materials and Methods
### Statistical Analysis  
To test the effect of EMF on the weight loss of exposed individuals (separately: adults, larvae, and pupae) with time, general linear mixed models (GLMMs) were used, including treatment as a fixed factor (control, 1 mT, 7 mT), time as a covariate (days 1-14), an interaction treatment\"time, and experimental replicate as a random factor. The dependent variable in the model was the relative weight of insects on consecutive days, expressed as the percentage of the initial weight (on day 0). If a treatment\"time interaction was significant, slopes of weight loss over time were tested separately for each treatment group (to check if the relationship holds for each group). Then, significant slopes were compared with each other to check if they were parallel (i.e., weight loss in both groups had the same rate). Finally, for parallel slopes, intercepts were compared to check if the slopes differed from each other in their vertical position (i.e., the group means were different).  
To examine the impact of EMF on the mortality of exposed adults, 1-way general linear models (GLMs) were used, including treatment as a fixed factor (control, 1 mT, 7 mT). The dependent variables in the models were days of the occurrence of particular levels of mortality (the first dead individual, 50% mortality, 100% mortality) in particular replicates.  
To assess the influence of EMF on the time (day) to appearance of the first pupa (emerging from larvae) or adult (emerging from pupae), 1-way GLMs were used, with treatment as a fixed factor (control, 1 mT, 7 mT). To test the effect of EMF on metamorphosis success (percentages of successful metamorphoses from larvae to pupae and from larvae to adults), generalized linear models (binomial distribution, log link function) were used, including treatment as a fixed factor (control, 1 mT, 7 mT).  
To analyze the effect of EMF on the metabolic rate of exposed larvae and adults, GLMMs were used, including treatment as a fixed between-group factor (control, 7 mT), time as a within-subject factor (4 consecutive measurements of the same individual), treatment\"time interaction, individual weight as a covariate to control for its effect on metabolism and individual as a random factor. The dependent variable was the CO\({}_{2}\) production per individual per unit of time. The weight and the dependent variable were log-transformed to linearize potentially allometric relationships between weight and metabolism.  
To test the influence of EMF on the sugar content in the haemolymph of exposed adults, a GLMM was used, including treatment as a fixed factor (control, 7 mT) and replicate as a random factor.
# A Multi-Frame PCA-Based Stereo Audio Coding Method
## 3 Quantization Design Based On PVQ  
According to the properties of matrix multiplication, if the error of one point in matrix \(Y\) or \(P\) is large, the restored signal may have a large error. Therefore, uniform quantization cannot limit the error of every point in the matrix in the acceptable range with bitrate limitation. So, it is necessary to set a series of new quantization rules based on the properties of the dimensionality matrix and the rotation matrix. It is assumed that the audio signal obeys the distribution of Laplace [23], and both PCA and MDCT in the paper are orthogonal transformations. Thus, the distribution of matrix coefficients is maintained in Laplace distribution. Meanwhile, we have observed the values in reduced-dimensional matrix and rotation matrix. It is shown that most values of cells in matrix are close to 0, and the bigger the absolute value, the smaller the probability is. Based on the above two statements, the distribution of coefficients in reduced-dimensional matrix and rotation matrix can be regarded as Laplace distribution. Lattice vector quantization (LVQ) is widely used in the codec because of its low computational complexity. PVQ is one method of LVQ that is suitable for Laplace distribution. Thus, this section presents a design of quantization for reduced-dimensional matrix and rotation matrix combined with PVQ.