esa-sceva/satcom-chunk-collection huggingface dataset:
# Heuristic Routing Algorithms for Time-Sensitive Networks in Smart Factories
## 4 Improved Genetic Algorithm to Solve TT Flow Routing Problem
### Description of GATTRP
#### 4.3.2 Population Initialization  
We initialized a population with an initial chromosome number of \(U_{0}\) and we set the maximum population size allowed throughout the iteration as \(U_{max}\) and the maximum number of iterations as \(I_{max}\). The gene segments of \(U_{0}\) chromosomes were randomly initialized and the fitness of individuals on each chromosome was calculated.
## 2 Principe of SOA-Induced Nonlinearity, FFE-Based LUT and 2 nd-Order VNLE  
### SOA-Induced Nonlinearity  
The nonlinear pattern effect induced by SOA comes from the gain saturation, where the SOA gain is defined as the ratio of output power \(P_{out}\) to input power \(P_{in}\). The amplification principle of SOA is based on stimulated emission. As \(P_{in}\) increases, the carriers in the SOA active region deplete and gain saturation occurs [23]. The SOA gain \(G\) can be described as:  
\[G=G_{0}e^{\frac{P_{out}}{P_{sat}}}(\frac{G-1}{G}) \tag{1}\]  
where \(P_{sat}\) is defined as the saturated output power of 3-dB gain compression and \(G_{0}\) is the small-signal gain as \(P_{in}\) is much smaller than \(P_{sat}\). For a small signal, we have \(P_{in}\ll P_{sat}\) and \(G=G_{0}\) can be derived. When \(P_{in}\) increases to exceed \(P_{sat}\), the gain is saturated, and the gain saturation induces self-phase modulation (SPM), which is the reason why the pattern effect appears. Therefore, \(P_{sat}\) divides the linear and nonlinear regions of SOA.  
Because the signal is modulated, the instantaneous input power of SOA changes to time-variant and the instantaneous gain \(G\) is related to time, which can be written as:  
\[G(t)=\frac{G_{0}}{G_{0}-(G_{0}-1)e^{-E(t)/E_{sat}}} \tag{2}\]  
with  
\[E(t)=\int_{-\infty}^{t}P_{in}(\tau)d\tau \tag{3}\]  
where \(E(t)\) is the fractional energy of an input pulse, and \(E_{sat}\) is the pulse energy when SOA is saturated. For the leading-edge of a single pulse whose energy \(E_{in}\) is larger than \(E_{sat}\), the gain is not saturated and can be expressed as:  
\[G_{1}=G(-\infty)=G_{0} \tag{4}\]  
Otherwise, the SOA operates in the nonlinear region for the trailing-edge gain, which can be represented as:  
\[G_{2}=G(\infty)=\frac{G_{0}}{G_{0}-(G_{0}-1)e^{-E(t)/E_{sat}}} \tag{5}\]  
Therefore, from the perspective of the time-domain signal waveform, the pulse shape is distorted from rectangle to jagged. Additionally, the edge of a pulse affects the former and latter symbols spontaneously and thus, the pulse shape of the current symbol is also related to the several adjacent symbols before and after.
# Regional Seismic Damage Simulation of Corroded RC Frame Structures: A Case Study of Shenzhen City
## 7 Conclusions  
A regional seismic damage simulation method for corroded coastal RC frame structures is proposed in this study. Through statistical analysis of experimental data and numerical simulation of typical corroded RC frame structures, the reduction rules of key mechanical parameters are obtained for the THA-based regional seismic damage simulation. Some conclusive remarks can be drawn as follows:  
1. The experimental data of 73 slender RC components with different degrees of corrosion are collected to obtain the reduction rules of component backbone curve parameters (i.e., initial stiffness, peak displacement, peak carrying capacity, and ultimate carrying capacity). Such results can be useful in simulating the response of corroded RC components or structures.
2. Pushover analyses of 20 corroded RC frames are conducted based on the obtained reduction rules of component backbone curve parameters. The simulated results indicate that both the degree of corrosion and proportion of corroded components can greatly affect the interstory mechanical properties of corroded RC frame structures.
3. The regional seismic damage simulation method of corroded RC frame structures is proposed based on the multi-degree-of-freedom (MDOF) model and the nonlinear time history analysis. The reduction rules of interstory mechanical properties obtained through pushover analyses of corroded RC frame structures are used to determine the parameters of the MDOF model.
4. The proposed method is demonstrated through a case study of RC frame structures in Shenzhen city. Two corrosion scenarios are assumed for the studied area. The simulated results show that RC buildings along the coastline are affected by airborne chloride-induced corrosion and severe seismic damage can be observed in the M7.5 earthquake scenario. Moreover, some buildings that are far from the coastline can also experience severe seismic damage due to corrosion caused by irregular use of sea sand as constructional material.  
Conceptualization, C.X.; Data curation, Y.L. and J.H.; Funding acquisition, C.X. and D.L.; Investigation, X.D., Y.L., and J.H.; Project administration, X.L. and D.L.; Resources, D.L.; Supervision, X.L. and D.L.; Writing--original draft, C.X. and X.D.; Writing--review and editing, C.X. and Q.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Scientific Research Fund of the Institute of Engineering Mechanics, China Earthquake Administration (grant no. 2017D01), the National Natural Science Foundation of China (grant no. 51520105012; 51708361), and the Intellectual Innovation Program of Shenzhen Science and Technology Innovation Committee (grant no. JCYJ20180305123919731).  
The authors declare no conflict of interest.  
Figure 17: Distributions of building seismic damage results (M6.5): (**a**) Corrosion scenario I; (**b**) Corrosion scenario II.
###### Abstract
U-Net is another popular semantic segmentation network that has shown impressive improvement in land types [20; 21; 22]. U-Net has higher segmentation accuracy, but, with the rise in generative models, it has become possible to retain more detailed information. Additionally, Pix2 Pix, a general framework for image translation based on the conditional generative adversarial nets (CGAN), has demonstrated remarkable results on numerous image translation datasets [23; 24]. Image translation is the process of converting an image representation into another representation by identifying a function that allows cross-domain conversion of images. In this study, we utilized the image segmentation method of Pix2 Pix and combined the feature selection method to pre-extract features of satellite images, resulting in better accuracy compared to a single method. We propose a F-Pix2 Pix semantic segmentation method that identifies forest/non-forest and needleleaf/broadleaf forest types in the study area using image-to-image translation. Our approach integrates regional and forest-specific features to enable accurate identification of forest types and provides a basis for estimation of carbon sources and sinks. This method is valuable for managing ecosystems and restoring ecology in Yunnan Province and has the potential to contribute to forest carbon sinks, thereby helping to mitigate climate change. We chose a time interval of 2005-2020, using Landsat and GF as data, both of which showed stable performance, proving the generalization of our algorithm. We use 2005 as the benchmark year to prepare for the next step of carbon sink estimation and also to prepare for Chinese Certified Emission Reduction (CCER) transaction. In summary, our main contributions include:  
* We proposed a method of F-Pix2 Pix to achieve image-to-image translation in remote sensing imagery semantic segmentation. It performed well, surpassing the existing products. * We applied transfer learning domain adaptation to semantic segmentation and solved the class imbalance problem in the needleleaf and broadleaf forest identification in the study area. * This method can be used for multi-source images and has strong generalization, which provided the possibility of long-term monitoring and also provided a foundation for accurate estimation of carbon sinks.
# Low-Cost RSAC and Adsorption Characteristics in the Removal of Copper Ions from Wastewater
## 2 Materials and Methods
### Thermodynamic Study of the Adsorption of Copper Ions by RSAC  
The thermodynamic equations are as follows (Equations (8) and (9)):  
\[\mathrm{\Delta G^{0}}=\mathrm{\Delta H^{0}}-\mathrm{T\Delta S^{0}}=-\mathrm{ RTInK_{0}} \tag{8}\]  
\[\mathrm{ln}\,\mathrm{K_{0}}=\mathrm{\Delta S^{0}}/\mathrm{R}-\mathrm{\Delta H^ {0}}/\mathrm{RT} \tag{9}\]  
In Equations (8) and (9), T is the thermodynamic temperature (K), \(\mathrm{\Delta H^{0}}\) is the enthalpy change of adsorption (kJ/mol), \(\mathrm{\Delta G^{0}}\) is the free energy of adsorption (kJ/mol), \(\mathrm{\Delta S^{0}}\) is the change in entropy of adsorption [J/(mol\(\cdot\)K)], R is the molar volume constant 8.314 J/(mol\(\cdot\)K), and K\({}_{0}\) is the adsorption partition coefficient, usually taken as the Langmuir constant \(\mathrm{K_{L}}\). Using the isothermal adsorption experimental data of RSAC particles at different temperatures, the adsorption equilibrium coefficient K\({}_{0}\) was calculated [21]. A straight line could be fitted by using the inverse of the temperature 1/T as the horizontal coordinate and lnK\({}_{0}\) as the vertical coordinate for the graph.
# Economic Feasibility of Underground Pumped Storage Hydropower Plants Providing Ancillary Services
## 2 Methodology
### Electric Power System Data  
The economic feasibility of UPSH plants is obtained considering the historical hourly values of the prices in the day-ahead and ancillary services markets in the Iberian electricity system during a period of three years (2016-2018). The main objective of this work is to estimate the maximum income from selling energy (turbine mode) and the minimum cost for purchasing energy (pumping mode) while participating in the day-ahead and balancing markets. The following markets and services for the mentioned years have been studied: (i) the day-ahead market; (ii) the upward secondary regulation; (iii) the upward deviation management; and (iv) the tertiary regulation (upward and downward).  
The overall amounts of energy managed in secondary regulation, deviation management and tertiary regulation in 2018 were 2592, 2358 and 3301 GWh, respectively. The purpose of the secondary regulation service is to maintain the generation-demand balance, automatically correcting deviations with respect to the anticipated power exchange schedule and the system frequency deviations. The objective of the deviation management service is to resolve the deviations between generation and demand which could appear in the period between the end of one intraday market and the beginning of the next intraday market horizon. Finally, the purpose of the tertiary regulation service is to resolve the deviations between generation and consumption and the restoration of the secondary control band reserve used. These ancillary services are managed and remunerated by market mechanisms in the Iberian electricity system.
# Network Theory and Switching Behaviors: A User Guide for Analyzing Electronic Records Databases
## 1 Introduction  
Information and Communication Technologies (ICTs) are major players in society nowadays. The ubiquitous presence of Internet-connected computer systems (via smartphones, tablets, wearable devices) in daily life allows us to virtually obtain all kinds of information, and at the same time, a lot of information about human behavior is systematically stored in databases [1; 2; 3]. Among others, health and medical services have been radically transformed by the ICT progress over recent decades. In this regard, a pivotal role has been played by health care databases, which contain information about individuals' health and related behaviors [4; 5; 6; 7; 8; 9; 10; 11]. ICTs allow continuously and automatically updating administrative databases as soon as an event takes place (the prescription of a drug made by a physician, medical procedures, diagnoses information, records of health services, etc.).  
In this paper, we will focus on analyzing electronic health records database data related to drug prescription and, specifically, drug switching. Traditional methods employed for investigating drug-switching behaviors are often unable to determine the actual switching pattern. Here, we propose the use of network theory to improve the analyses of these kinds of data. A previous contribution on this topic [12] was limited to advocating the application of network theory for investigating switching behaviors. Therefore, we provide a step-by-step user guide, along with a ready-to-use Python script for obtaining an adjacency matrix from raw data.
## 6 Conclusions  
With the emergence of cloud-based technologies, organization-specific security requirements for enterprise are changing. The traditional approach of addressing cybersecurity and physical security separately is no longer sufficient to protect an enterprise network. DNS is a crucial part of every network architecture. However, the traditional DNS architecture is vulnerable to cyberattacks. DoH is a privacy and security enhancement technology that uses HTTPS as an encryption technique for DNS queries. While DoH protects the data associated with the DNS query from DNS assaults, it also can be exploited by hackers to launch DoH tunneling attacks. Our research proposed a system that can be applied to enterprise networks as a security operation system. Our approach used the Transformer architecture as a classifier method to detect malicious DoH. Although the Transformer architecture is more complex than other Supervised Machine Learning models, it showed a significant improvement in the number of labeled data used. The results show that the Transformer model also achieved a very high accuracy of 0.994 but only needed a small number of labeled data, only 20% compared with other research. This advantage of the Transformer architecture makes it more suitable in malicious DoH tunneling detection because, in practice, labeling a large amount of encrypted network traffic is very complex work and requires many resources.  
Conceptualization, T.A.N.; project administration, M.P.; supervision, M.P.; writing--original draft, T.A.N. All authors have read and agreed to the published version of the manuscript. This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2020R1F1A1076795).  
Not applicable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Model**} & \multicolumn{2}{c}{**Number of Instances in Training**} & \multirow{2}{*}{**Precision (Layer 1/ Layer 2)**} & \multirow{2}{*}{**Recall (Layer 1/ Layer 2)**} & \multirow{2}{*}{**F1-Score (Layer 1/ Layer 2)**} \\  & **Data (Layer 1/ Layer 2)** & & & \\ \hline RF [15] & 233,427/53,928 & 0.92/0.93 & 0.92/0.93 & 0.92/0.93 \\ C4.5 [15] & 233,427/53,928 & 0.92/0.93 & 0.92/0.92 & 0.92/0.92 \\
2D CNN [16] & 233,427/53,928 & 0.91/0.91 & 0.91/0.91 & 0.91/0.91 \\ XGBoet [17] & 233,427/53,928 & 0.94/0.94 & 0.94/0.94 & 0.94/0.94 \\ Transformer (our work) & 233,427/53,928 & 0.99/0.94 & 0.99/0.994 & 0.99/0.994 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Model evaluation.
# Increase of _Trichoderma harzianum_ Production Using Mixed-Level Fractional Factorial Design
## 1 Introduction
### Characteristics Factor for the Production of Spores of the Trichoderma harzianum
Using the substrates wheat straw, broad bean straw, vegetable husks, teff straw, and rice husk in a one-factor-at-a-time design, the rice husk was the one that presented the highest performance with a production of \(5.0\times 10^{8}\) CFU.g\({}^{-1}\)[5]. Growth phases in Trichoderma beyond 21 days of incubation have been found, which could indicate that as the incubation period increases, spore production will also increase. \begin{table}
\begin{tabular}{c c c c} \hline
**Factor** & **Operation Range** & **Optimal Value** & **References** \\ \hline \multirow{3}{*}{pH} & 3.8–6.0 & 6.0 & [4] \\  & 5.0–8.0 & 5.8 & [6] \\  & 2.0–6.0 & 4 & [39] \\ \hline \multirow{3}{*}{Substrate} & Rice husk, sugar cane, coffee husk, corn cob. & Rice husk & [5] \\  & Rice grains, sorghum, birdseed, broken corn, rice straw. & Rice grains & [40] \\  & Rice grain, wheat grain, sorghum grain, sesame husk. & Sesame husk & [41] \\ \hline \multirow{3}{*}{Incubation period} & 5–7 days & 5 days & [4] \\  & 14–18 days & 27.8 days & [6] \\  & 5–15 days & 31 days & [24] \\ \hline \multirow{3}{*}{Inculum concentration} & 0.1\%–10\% & 12\% & [6] \\  & 10\%–15\% & 13.9\% & [42] \\  & 5\%–10\% & 5\% & [43] \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._However, beyond 28 days, the growth is affected, being 28 days, the period in which the highest production was obtained [6]. The authors [34] found a maximum spore production of \(7.3\times 10^{8}\) CFU.g\({}^{-1}\) with an incubation period of 5 days. It is necessary to use an adequate inoculum concentration for good sporulation in the fungus [45]. Using the inoculum size of 5% and 10% in their experiment, they achieved the highest number of spores, \(5.9\times 10^{8}\) CFU.g\({}^{-1}\) with the 5% inoculum [46]. With values of 0.1% and 10%, the predictive model of the authors determines that the highest point of production would be achieved with an inoculum concentration of 12% [6]. In this investigation, five factors were considered: three quantitative and two qualitative. Originally the \"Biotechnological Company\" had operated with the factors in the levels without air, humidity at 50%, temperature of 25 \({}^{\circ}\)C, pH of 4, and rice grain as substrate. With the aim of increasing spore production, new levels and factors were evaluated, considering the characteristics of the process, the current state of literature, and experience. In the case of the quantitative factors, values were taken both above and below the operation, and in the case of the qualitative factor, according to local availability and the facilities.
# Modification of PLA Scaffold Surface for Medical Applications
## 3 Results and Discussion
### Analysis of the External Surface of the Membrane  
#### 3.4.1 Scanning Electron Microscope  
The morphologies of membranes MI and MII and the surface modification textures were examined. Surface 1 (S1) and Surface 2 (S2) formed during the preparation of the scaffold. S1 was from the glass primer side, and S2 was from the air side. The fractures on surfaces S1 and S2 were examined. The scanning area was approximately 10 mm\({}^{2}\) for each surface and the fractures.  
The SEM images (Figure 6) show the morphology of the PLA membranes obtained by wet phase inversion. S1 had small pores. Moreover, the layer observed on the surface of the unmodified membrane, which covered most of the pores and the surface itself, was very rough. After modification, most of the pores were exposed, and the surface itself appeared to be smoother. The fractures of the membrane had numerous small pores, and slight differences in the image before and after modification were observed, since two separately obtained samples were imaged. In contrast, the pores on the surface of S2 were much larger  
Figure 5: The results of the durability tests of plasma modification in an Ar + CO\({}_{2}\) mixture with an exposure time of 60 s and a discharge power of 20 W.  
than the pores located in the deeper layers. The pores on the surface of S2 were mostly covered, so this surface could be treated as being solid. After the plasma modification, numerous large depressions were observed on S2.  
Based on the obtained SEM images of the PLA membrane MII (Figure 7), it was found that S1 contained many more pores than S2. After the plasma modification, the area of the pores increased, suggesting a slight melting of the membrane surface. In the fracture of the sample, more pores were close to the membrane surface, and the surface itself has numerous large depressions. That could increase the capillary forces, reducing the water contact angle of the surface. This modification is very beneficial considering the use of the membranes for medical purposes, as it would simplify the penetration of liquid into the membrane. The fractures of the unmodified membrane and the membrane after modification looked similar, and slight differences may have been a result of the fact that they were two separate samples. S2 before and after modification was almost solid, and the use of barrier discharge plasma slightly smoothed it.  
Figure 6: The morphology of Membrane I (MI) obtained before and after plasma modification.  
SEM testing of the materials after modification with DBD plasma showed that this method did not damage the pores in the membrane fractures. After the process, slight flooding of the pores on S1 was observed in the materials obtained by the wet and dry methods. The surfaces appeared less rough but contained more deep pores. Such topography can facilitate the diffusion of substances through the outer surface. During plasma modification, the pores close to S2 were slightly melted.
## 4 Results
### Round-Trip Time  
The time between request and response from the client to server, measured in milliseconds, represents the round-trip time of the network. RTT can be affected by distance, transmission medium, number of network hops, traffic levels, or server response time.  
In this study, the main difference between encrypted and non-encrypted file transmission is the size of the document. Figures 6 and 7 represent the different RTT times of non-encrypted and encrypted files, respectively.  
Figure 8: Non-encrypted file throughput.  
Figure 6: Non-encrypted file RTT.  
Figure 7: Encrypted file RTT.
# Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector
## 2 Cookies and the Rising Threat of XSS Vulnerabilities: A Literature Review  
Cross-site scripting (XSS) attacks are a type of security vulnerability that can occur in web applications. They allow attackers to inject and execute malicious scripts in HTML pages, which can cause sensitive information to be stolen or altered. One of the most significant consequences of XSS attacks is cookie theft. Cookies are small pieces of data that web applications store on a user's computer to maintain session state. Attackers can steal cookies to gain unauthorized access to a user's account and perform actions on their behalf. To protect against these attacks, researchers have proposed several methods to mitigate XSS vulnerabilities and prevent cookie theft. These methods include input validation,output encoding, and the use of secure cookies with HttpOnly and Secure flags. By implementing these measures, web application developers can reduce the risk of XSS attacks and ensure the security of user data. The growing threat of XSS vulnerabilities in web applications has prompted the development of various detection and prevention techniques. The study authors presented in [27] have proposed a scheme based on artificial neural networks to detect XSS attacks, achieving high accuracy and detection probabilities. A survey of existing XSS detection and defense methods has been carried out in [28], highlighting the need to improve prevention strategies. The authors of [29] have presented a multilayer prevention technique that combines API authentication and encryption to protect against XSS attacks. In [30], the prevalence of persistent XSS on the client side has been identified, highlighting the need for more comprehensive mitigation strategies. These studies have underscored the urgency of addressing the growing threat of XSS vulnerabilities in web applications. Table 1 summarizes the methodologies, results, and limitations proposed in the work on analyzing cookie vulnerabilities against XSS attacks.