esa-sceva/satcom-chunk-collection huggingface dataset:
# An Effective Ensemble Approach for Preventing and Detecting Phishing Attacks in Textual Form
## 3 Proposed Approach
### Ensemble Classification
#### 3.7.2 Method 2: Soft Voting Ensemble Learning  
Soft voting ensemble learning (Method 2) (referred to as Soft Voting Classification in Figure 1) incorporates the class prediction probabilities associated with each base learner and integrates these predictions through averaging in order to ascertain the final classification. Ensemble learning typically employs two voting techniques: (a) hard voting [35] and (b) soft voting [3]. These methods differ in their approach to handling outcomes within the combination model. The Majority Voting method employs the outputs of the base learners to determine the final classification by considering the hard votes. Conversely, the soft voting method calculates the average decisions made by each base learner to determine the final classification. In comparison to Majority Voting, the soft voting method mitigates the impact of structural sensitivity caused by the base learners, reduces the variance of the ensemble, and gains additional information.  
Figures 2-6 show the ROC Curves for different models used. As depicted in Figure 1, Method 2 employs two base learners, specifically the DT algorithm for content-based features and the KNN method for text-based features (Tier-1 in Figure 3). The outcome of both fundamental learners is the probability that an email belongs to a specific category. In Tier 2, these probabilities are used as inputs to an Argmax function in order to determine the most probable class and perform the final classification. To be more precise, the task of detecting phishing emails can be conceptualized as a binary classification problem.
## 2 Literature Survey
### Shortest Path Routing  
The routing algorithm is determined by the shortest path and the routing decision for the O-D pair. When a new route is established and all traffic still follows the pre-existing path, this phenomenon is called \"session routing\" because a path remains in force for the entire user session. The routing metric (_i.e._, cost) is used to define the path length and can be measured in terms of hops, the mean delay, and even the extent of flow deviation. The mean delay can be used to find the fastest path for routing,and flow deviation can be applied to system optimization routing where each route has equal flow deviation.
# Automated Visual Identification of Foliage Chlorosis in Lettuce Grown in Aquaponic Systems
## 3 Research Methodology
### Ontology Model  
The complete development and details of all concepts and instances of an ontology model, 'AquaONT', is available in previous work by the authors [17]. AquaONT is a unified ontology model that represents and stores the essential knowledge of an aquaponic 4.0 system. It comprises six concepts: Consumer_Product, Ambient_Environment, Contextual_Data, Production_System, Product_Quality, and Production_Facility. In this study, two classes, 'Consumer_Product' and 'Product_Quality', are used for knowledge extraction. The 'Consumer_Product' class provides an abstract view of the type, growth status, and growth parameters of ready-to-harvest crops in an aquaponics system. Whereas the 'Product_Quality' class provides knowledge on the crop attributes related to pathology (abiotic and biotic stresses, causes, and the ways and means by which these can be managed or controlled), morphology (canopy dimensions, such as area, length, width, etc.) and foliage color. The lettuce crop is considered in this study. The crop growth and quality attributes are defined as instances of respective classes, which are extracted once the crop foliage is detected as yellow (or leaf chlorosis is detected). Figure 5 shows the hierarchical architecture of the 'Consumer_Product' and 'Product_Quality' classes, with their instances for the lettuce crop in Protege7 (an open-source ontology editor and framework developed at Stanford University) environment.
# Soriasis: From Pathogenesis to Pharmacological and Nano-Technological-Based Therapeutics
## 5 Nanotechnological Approaches for Psoriasis
### Microneedles  
Microneedle is a new drug delivery system, which consists of a base patch with perpendicular microneedles attached to bypass the stratum corneum. It is considered an intradermal drug delivery system, a new pharmaceutical form for psoriasis treatments. The patch has two parts; a base plate and the microneedles, which could be made of the same material or not. Microneedles must be strong and tough enough to perform their purpose with good mechanical resistance [154]. Moreover, the length of microneedles is between 25 to 2000 microns to assure their trespassing to the stratum corneum, but this is not long enough to activate the pain receptors in the skin, as shown below in Figure 4.  
Microneedles constitute an elegant solution to increase drugs bioavailability. The mechanism of this delivery system consists of an attachment of the microneedle patch on the skin, permitting a micro-sized channel through the skin layer. The main objective of the delivery system is helping to trespass the first barriers of the skin, allowing the delivered drug to deposit directly into the stratum corneum. This procedure improves the permeability capacity of the drug, enhancing bioavailability [155]. Due to the increasing interest in the use of microneedles, different types have been developed, with some differences in their mechanism and materials. There are four general types of microneedles: solid microneedles, coated microneedles, dissolving microneedles, and hollow microneedles. The only type that has been studied for psoriasis is dissolving microneedles. Dissolving microneedles (DMNs) are produced with biodegradable materials, allowing them to dissolve themselves once they are in the skin [156]. The loaded drug in the needles is dissolved in the matrix of a polymer. The most important feature for the use of these microneedles is the material that the needles will be made of, which has to be strengthened enough to permit the perforation of the surficial layers of skin and show biodegradability without showing any toxicity. It must be considered that the material of the needles will be in the system of the patient. Therefore, microneedles have to be dissolved, circulate through the human body, and metabolized. One interesting feature of this type of microneedle is that drug release can be controlled by choosing the materials for the needles. Table 4 summarizes examples of biodegradable nanotechnology-based treatments for psoriasis. Figure 4: (1) Application of microneedles, (2) insertion, (3) extraction. Types of microneedles: (a) solid microneedles, (b) coated microneedles, (c) dissolving microneedles, and (d) hollow mi-croneedles.
## 2 Derivation of \(e-log\sigma^{\prime}{}_{v}\) Equations for Laboratory Test Results
### Equations for the Hysteresis
#### 2.2.1 Equations for the Symmetric Hysteresis
\[\kappa=\frac{de}{dlog\sigma^{\prime}{}_{v}}=\frac{(log\sigma^{\prime}{}_{v}-h )}{2C} \tag{14}\]  
\[\kappa_{0}=\frac{(log\sigma^{\prime}{}_{\theta}-h)}{2C} \tag{15}\]  
To calculate the \(\kappa\) and \(\kappa_{0}\) for the reloading of the symmetric hysteresis, substitute \(C_{1}\), \(h_{1}\), and \(k_{1}\) from Equations (11)-(13) in place of \(C\), \(h\), and \(\sigma^{\prime}{}_{\omega}\) in place of \(\sigma^{\prime}{}_{\theta}\) in Equations (14) and (15), respectively. It should be noted that for the symmetric hysteresis, \(\kappa_{0}\) at \(\sigma^{\prime}{}_{\theta}\) on unloading curve is equal to \(\kappa_{0}\) at \(\sigma^{\prime}{}_{\omega}\) on reloading curve. It is important to note that the reloading equation (Equation (14)) is applicable only for \(\sigma^{\prime}{}_{v}\geq\sigma^{\prime}{}_{\omega}\) and is limited by the stress on the VCL. Additionally, when \(\Psi=0\), the asymmetric hysteresis becomes a symmetric hysteresis. The change in void ratio \(\Delta e\) and the secant slope \(\overline{C_{r}}(ReS)\) between the starting point of reloading \((\sigma^{\prime}{}_{\omega})\) and any point on the symmetrical reloading \((\sigma^{\prime}{}_{v})\) of Equation (8) can be calculated using Equations (16) and (17), respectively. \[\Delta e=e-e_{\omega}=\frac{(log\sigma^{\prime}{}_{v})^{2}-(log\sigma^{\prime} {}_{\omega})^{2}-2h_{1}.log(\sigma^{\prime}{}_{v}/\sigma^{\prime}{}_{\omega})} {4C_{1}} \tag{16}\]  
\[\overline{C_{r}}(ReS)=-\frac{\Delta e}{\Delta log\sigma^{\prime}{}_{v}}=\frac {log(\sigma^{\prime}{}_{\omega}.\sigma^{\prime}{}_{v})-2h_{1}}{4C_{1}} \tag{17}\]For overconsolidated clays exhibiting symmetrical hysteresis, the application of \(\overline{C_{r}}\) in the settlement calculations can be achieved by substituting \(C_{r}\) with \(\overline{C_{r}}\) (as defined in Equation (17)) and replacing \(C_{c}\) with \(\overline{C_{c}}\) (as defined in Equation (7)) simultaneously into Equation (2).
## 2 Materials and Methods  
### Non-Subsampled Shearlet Transform (NSST)  
NSST is an improvement method, based on shearlet transform combining with a non-subsampled Laplacian pyramid (NSLP). [PERSON] et al., proposed a method to implement NSST on time-domain directly [8], which divides the implementation of NSST into two steps: Multi-scale decomposition and directional filtering. In NSST, NSLP filters replace the Laplacian pyramid filters used in the shearlet transform to scale the image. The source image is decomposed into \((k+1)\) sub-bands, which have the same size of the source image, using \(k\)-class non-subsampled pyramid. The \((k+1)\) sub-bands include a low-frequency sub-band \(f_{a}^{k}\) and k high-frequency sub-bands \(\{f_{d}^{i}\,\mathrm{i}=1,2\ldots k\}\), which are represented by:  
\[f_{a}^{k}=f_{a}^{k-1}*H_{0}\Big{(}z^{2^{k-1}\,I}\Big{)} \tag{1}\]  
\[f_{d}^{k}=f_{a}^{k-1}*H_{1}\Big{(}z^{2^{k-1}\,I}\Big{)} \tag{2}\]  
where \(f_{a}^{k}\) denotes the low-frequency sub-band at resolution level k and \(f_{d}^{k}\) denotes the high-frequency sub-bands. \(H_{0}(z)\) and \(H_{1}(z)\) represent low pass and high pass filters, respectively. \(I\) is the identity matrix, and \(H_{\{0,1\}}\Big{(}z^{2^{k-1}\,I}\Big{)}\) is the kth filter after down sampling.  
The high-pass image would convolve with a directional filter, which has a large flexibility in the choice. For instance, it can be calculated simply in pseudo-polar grid with Meyer window function and translated into the Cartesian grid. The NSST coefficients can be calculated by the following equation:  
\[f_{NSST}^{kJ}=f_{d}^{k}*w^{J} \tag{3}\]  
where \(w^{J}\) denotes a directional filter in the time domain.
## 3 Results and Discussions
### Correlation between Total Phenolic Content and Antioxidant Properties  
Many reports revealed that, in general, there is a positive correlation between antioxidant abilities of plant extract and its total phenolic content [11; 39]. Phenolic compounds, including the flavonoids, phenolic acids, and phenylpropanoids contained in fruits and vegetables, act as reductones that exert antioxidant activity by giving a hydrogen atom or breaking the chain of free radicals [31; 40]. Generally, the antioxidant ability of the studied extracts followed the same ranking order with the values of TPC. In the current study, the correlations (Pearson) between antioxidant abiliitiy in terms of IC\({}_{50}\) and EC\({}_{50}\) for DPPH and reducing power, respectively, and TPC of studied _Centaurea_ extracts has been evaluated. Table 2 presents the results.  
Figure 3: Reducing power (EC\({}_{50}\), mg/mL) determined in extracts obtained from aerial part of two _Centaurea_ species (_C. kroumirensis_ and _C. sciula_) with different extraction techniques (Different letters indicate significant difference (\(p<\) 0.05)).  
The average values for IC\({}_{50}\) exhibited strong (r = \(-\)0.959) and good (r = \(-\)0.758) negative correlation with TPC in the samples for _C. sicula_ and _C. kroumiensis_, respectively. These values indicated that antioxidant ability of _C. sicula_ was strongly related to polyphenols that werer extracted in the UE sample. A good negative correlation (TPC-EC\({}_{50}\)) was recorded for _C. sicula_ r = \(-\)0.846, however for _C. kroumiensis_, a moderate correlation (r = \(-\)0.646) has been noted, which corroborate with the results that were previously discussed for the antioxidant activity of hexanic extract. It could be concluded that polyphenols present most important antioxidant compounds in _C. sicula_, whereas, the aerial part of _C. kroumiensis_ is rich in other antioxidants besides polyphenols. Overall, our findings supported the idea that a higher content of phenolic compounds reflected higher antioxidant ability and, inversely, lower TPC lessened the reducing power and DPPH scavenging activities. Additionally, a moderate positive correlation (DPPH (IC\({}_{50}\))-reducing power (EC\({}_{50}\))) (r = 0.678 and 0.676) have been recorded for _C. sicula_, and _C. kroumiensis_, respectively. These results corroborated with many reports that revealed a direct correlation between antioxidant abilities and reducing power of plant extract [32; 41].
## 2 Proposed Protection Scheme for WDM-PONs  
The proposed protection scheme for WDM-PONs based on ROAs is shown in Figure 1. In the proposed scheme, the optical amplifier unit includes three types of ROAs: ROA\({}_{1}\), ROA\({}_{2}\), and ROA\({}_{3}\). ROA\({}_{1}\) is a type of post-amplifier on the downstream path and ROA\({}_{2}\) is a type of pre-amplifier on the upstream path. ROA\({}_{3}\) enables switching between the post-amplifier and pre-amplifier so that it can be used as a backup optical amplifier for either ROA\({}_{1}\) or ROA\({}_{2}\).  
Tx\({}_{1}\)-Tx\({}_{n}\) and Rx\({}_{1}\)-Rx\({}_{n}\) in the OLT are transmitters and receivers, respectively. All downstream signals are multiplexed by a WDM multiplexer (MUX) at the OLT. The multiplexed signal is amplified by ROA\({}_{1}\) and then transmitted through port 1 to port 2 of an optical circulator (OC). The output signal from port 2 of the OC is launched into the bypass path of the 2 \(\times\) 2 crossbar optical switch in ROA\({}_{3}\) and then fed to a standard single-mode fiber (SSMF) that is connected to a 1 \(\times\) \(N\) arrayed-waveguide grating (AWG) at the remote node (RN). After being de-multiplexed at the RN, each downstream signal is connected to the corresponding optical network unit (ONU). All upstream signals from ONU\({}_{1}\) to ONU\({}_{n}\) are multiplexed by the AWG at the RN. The multiplexed signal is launched into the SSMF and then fed to the bypass path of ROA\({}_{3}\). The bypass signal is transmitted through  
\begin{table}
\begin{tabular}{c c c} \hline
**Components** & **Failure Rate (FIT \({}^{1}\))** & **MTTR \({}^{2}\) (Hour)** \\ \hline Fiber & 11,000 (per 10 km) & 12 \\ Optical Transmitter & 10,867 & 2 \\ Optical Receiver & 4311 & 2 \\ Passive Equipment & 1000 & 2 \\ EDFA & 5,000,000 & 2 \\ \hline \end{tabular} \({}^{\dagger}\) Failure in time (FIT) denotes the average number of failures in 10\({}^{9}\) h. \({}^{2}\) MITR is the mean time to repair.  
\end{table}
Table 1: Failure rates and repair times [10; 11].  
port 2 to port 3 of the OC and amplified by ROA\({}_{2}\). After being de-multiplexed by a WDM de-multiplexer (De-MUX), each upstream signal is connected to the corresponding Rx.  
In general, EDFA pumping schemes can be categorized into three arrangements, namely, forward-pumped (co-pumped), backward-pumped (counter-pumped), and bidirectional-pumped (dual-pumped) configurations [18]. The main advantage of a forward-pumped EDFA is low NF and that of a backward-pumped EDFA is high output power. Therefore, in the proposed protection scheme, ROA\({}_{1}\) adopts a backward-pumped configuration to gain high output power, whereas ROA\({}_{2}\) uses a forward-pumped configuration to acquire low NF. Moreover, ROA\({}_{3}\) is implemented such that it can switch between the backward-pumped and forward-pumped EDFA so that it can be used as a backup optical amplifier for ROA\({}_{1}\) or ROA\({}_{2}\).
# Heterogeneous Network Switching Strategy Based on Communication Blind Area Dwell Time
## 3 VLC Heterogeneous Networking Technology Research
### ACO-OFDM Channel Processing  
In the visible light channel transmission, unlike the traditional method of introducing SNR, we introduce spatial SNR on the basis of the layout of the visible light source in this article (Figure 4).  
After the operations of quadrature amplitude modulation (QAM), Hermitian symmetry, inverse fast Fourier transformation (IFFT) transformation, adding CP, and limiting operations in the transmitter, the bit stream can be transmitted in an additive white Gaussian noise (AWGN) [17] channel through digital-to-analog conversion. Analogously, the receiver side is equivalent to the inverse process of the transmitter side. Finally, we can obtain the BER by calculating the error between the output and the input bit stream at the receiver side and converting the BER into the indoor spatial distribution (Figure 5).  
Figure 4: Visible light SNR distribution.  
Figure 3: Visible light intensity distribution.
# Network Tower Sharing Analysis in Greece: A Structure-Conduct-Performance Approach
## 3 Results
### Government Policies--Conduct--New Market Structure
#### 3.3.2 MNOs Conduct
The deal also included a long-term \"Master Services Agreement\" (MSA), ensuring that both companies would be treated fairly, equitably, and in a non-discriminatory manner, while Vantage Towers would be for both Vodafone and WIND, and was the favored supplier to build 250 new sites in a period of 5 years after 2021 for each of them, i.e., 500 new sites in total. Up to the present, Vantage Towers is the leading TowerCo in Greece, managing around 5.2 thousand macro towers, more than 20 different tenants, of which two are anchored with extensive active sharing and perspectives to increase more their macro towers in the next few years. Moreover, Vantage Towers is listed in the Frankfurt Stock Exchange, even though Vodafone holds its majority ownership. Any existing commercial collocation agreements with Cosmote, Forthnet, and Digea were still valid under the same conditions that existed with Victus Networks before all passive mobile network infrastructure was passed to Vantage Towers. Both Vodafone and WIND retain access to passive mobile networks, while part of the agreement was that part of both companies' debt would pass to Vantage Towers and indirectly to Vodafone's mother company. By such an agreement, both alternative operators retained the above-mentioned benefits that forced them to proceed at the initial Joint Venture, but, moreover, (a) they were released from a large amount of debt created during their mobile network expansion, while (b) they reduced their operational cost coming from maintenance of their passive infrastructure, plus the capital cost required for expanding their mobile network to new geographical areas, as well as (c) providing them better access to financial liquidity at less cost, as a result of reducing debt, and doing better programming related to future investment.
# Immunomodulatory Properties of Probiotics and Their Derived Bioactive Compounds
## 5 Probiotic Derived Bioactive Compounds and Immunity
### Bacteriocins
#### 5.1.2 Classification of LAB Bacteriocins  
Bacteriocins of LAB are currently categorized into three major classes [97; 98] based on their size, structure, and biochemical composition (Figure 2). Class I bacteriocins (Iantibiotics) are small-sized (<5 kDa), membrane-active peptides with extensive post-translational modifications, containing uncommon dehydrated amino acids and displaying stability to heat, pH, and proteolysis [87]. Class I includes Subclass Ia, Subclass Ib, and Subclass Ic [21; 86; 87]. Class I bacteriocins use the peptidoglycan cell wall precursor lipid II as a docking molecule and induce pore formation on the target cell membrane to penetrate the phospholipid bilayer, leading to ion efflux and death. Additionally, they can disrupt the cell wall biosynthesis [92; 94]. Class II bacteriocins are small (<10 kDa), heat-stable, non-lanthionine-containing peptides that mainly cause permeabilization of the target cell membranes [87]. This group is subdivided into four subclasses, namely Subclass IIa, Subclass IIb, Subclass IIc, and Subclass IId [21; 86; 87]. Class II bacteriocins, following docking on the mannose permease of the phosphotransferase system (Man-PTS), create intrinsic channels on the target cell membrane, allowing ion diffusion and leading to cell death [87; 94]. Class III bacteriocins are larger (>30 kDa), heat-labile peptides and are subdivided into subclass IIIa (bacteriolysins) and subclass IIIb (non-lytic peptides) [21; 87]. Their antimicrobial activity correlates with their endopeptidase enzymatic activity, leading to loss of the bacterial cell wall integrity [87; 96].  
Figure 1: Bacteriocins mechanism of action.
## 3 Results and Discussion
### DPPH Activity of GV Extracts  
DPPH is a purple free radical that can be used to analyze the antioxidant activity of a sample through color change [52]. The IC\({}_{50}\) of DPPH radical scavenging represents the extract concentration at which 50% of DPPH radical scavenging occurs; the lower the IC\({}_{50}\) value, the higher the DPPH activity. The DPPH activity of GV extracts ranged from IC\({}_{50}\) values of 69-182 ug/uL and increased in a concentration-dependent manner. The highest DPPH activity was observed in the GVE (IC\({}_{50}\) = 69.4 \(\pm\) 0.4 ug/uL), followed by the GVM, while the GVW showed the lowest DPPH activity at IC\({}_{50}\) = 182 \(\pm\) 17.8 ug/uL.  
[PERSON] et al. [53] analyzed the DPPH activity of _Gracilaria corticata_ using different solvent extracts, and their results showed that the ethanol and methanol extracts had higher DPPH activity than those of the other extracts (water, chloroform, and petroleum ether) and increased in a concentration-dependent manner. Similarly, [PERSON] et al. [54] reported that methanol and ethanol extracts of _Gracilaria temustitipitata_ exhibit greater DPPH activity than water extracts. Antioxidants with DPPH activity also exhibit excellent electron-donating abilities [55]. In this study, GVM and GVE showed more effective DPPH activity  
Figure 1: Total polyphenol and flavonoid contents of _Gracilaria perrucosa_ extracts. (**a**) Total polyphenol and (**b**) flavonoid contents. GVE: _G. verrucosa_ ethanol extract; GVM: _G. verrucosa_ methanol extract; GVW: _G. verrucosa_ water extract; TA: tannic acid; QC: quercetin. Different letters (a–c) indicate significant differences (\(p<0.05\)).  
than GVW, suggesting that the antioxidants in GVM and GVE stabilized free radicals more efficiently.