esa-sceva/satcom-chunk-collection huggingface dataset:
# QoS Enabled Layered Based Clustering for Reactive Flooding in the Internet of Things
## 3 Modeling and Strategy  
This section delivers a model for flooding in an IoT network. It elaborates the exchange of query messages in the network between the different modes during interaction, and also indicates the amount of query streams and available motes [11; 20]. Furthermore, modeling of the system describes a prime knowledge of the more functionalities and the flow of queries among end-users and motes [27; 28]. Figure 3 illustrates the system model of a sender/sink mote, flooder/redundant mote, and the destination mote. Flooding is solely possible once the flooder mote is physically found between or nearby the target receiver and transmitter motes. When the geometric shape of the system is in such a state, that destination receives the flooder's transmitted signal before it ends transferring or moveson to a new link. Equation (1) represents the different controlled distances D3 and D2 and signifies the fraction of every more interval that is essential to remain not flooded for successful communications:  
\[\text{D2 }+\text{ D3 }\leq\left(\lambda\text{X}_{\text{s}}-\text{X}_{\text{f}} \right)\text{ c }+\text{ D1} \tag{1}\]  
where more duration is denoted by \(\text{X}_{\text{s}}\), i.e., the total number of legitimate motes in the network, \(\lambda\) denotes the variable allocated to the legitimate motes and it varies between 1 and 10, processing time of the flooder is \(\text{X}_{\text{f}}\), i.e., the time taken by the flooding motes to attack the network. D1, D2, and D3 denote the distances between the motes, and c stands for the speed of light, as shown in Figure 3. The flooding mote constantly observes the communication medium, and if a query packet transmission is identified, then straightaway communicates a radio signal for the purpose to induce receiver-side collision [29; 30]. The flooder is capable of sending just sufficient energy to debase the received bits of query messages and further leads to failure of cyclic redundancy codes (CRC) checks. Usually, a flooding attack ensures the following criteria: massive efficiency of energy (i.e., low power consumption), small possibility to detect (rather near to 0), attain excessive levels of DoS (i.e., disrupt communications to the desired (or maximum possible) extent) and be resistant to PHY layer anti-flooding techniques (i.e., do not allow signal processing techniques to overcome the attack). Commonly, the criteria of interest are based on the flooding scenario [19; 31]. Alternatively, the flooding scenario dictates the appropriate settings for usage [32], such as energy efficacy, will be the prime goal of the malicious motes, because of their small energy resources. According to the aforementioned criterion, a flooder mote tends to maintain the effectiveness in all cases. As such, the flooder mote may adopt some techniques which are stable with MAC layer behaviors to preserve a low possibility of detection.
# Cancer Treatment: An Overview of Pulsed Electric Field Utilization and Generation
## 4 Biological Cell Modelling
### Equivalent Circuit Model  
The equivalent electrical cell model was presented by [PERSON] and [PERSON] in 1989 [33]. Considering a mammalian cell, the internal structure of the cell is depicted in Figure 3. The plasma membrane of the cell is a perfect dielectric material; it has high resistance and extremely low thickness, being only a few nanometres (5\(\sim\)10 nm). The approximate values of resistivity and capacitance are \(10^{7}\)\(\Omega\)/cm and 1 \(\mu\)F/cm\({}^{2}\), respectively [40]. On the other hand, the cytoplasm has higher conductivity than the plasma membrane, and is modelled as a resistor \(R_{e}\). The resistivity of the cytoplasm is around 100 \(\Omega\)/cm [40]. The surrounding medium, like the cytoplasm, is of higher conductivity, and is modelled as a resistor \(R_{e}\)  
Figure 3: Basic structure of a mammalian cell.  
Overall, a cell can be modelled as a conductive sphere covered by a layer of insulating material, as shown in Figure 4.  
Applying the Kirchhoff voltage law to the circuit, the cell voltage \(V_{c}\) can be written as  
\[V_{c}=V_{m}+R_{C}C_{m}\frac{dV_{m}}{dt} \tag{1}\]  
where \(V_{m}\) is the membrane voltage and \(C_{m}\) is the membrane capacitance. If a constant electric field of magnitude \(E\) is applied to the cell with an angle \(\theta\) between the electric field lines and the perpendicular to the tangent of the point on the sphere (with radius \(r\)), the equation can be written as follows:  
\[\frac{3}{2}Er\cos\theta=V_{m}+R_{C}C_{m}\frac{dV_{m}}{dt}. \tag{2}\]  
Assuming that the initial charge of the cell is zero and integrating the equation, the cell voltage can be written as  
\[V_{m}=fEr\cos\theta(1-e^{-t/\tau_{cm}}) \tag{3}\]  
where \(f\) is a constant that equals \(3/2\) and \(\tau_{cm}\) is the membrane charging time constant:  
\[\tau_{cm}=\frac{r\varepsilon_{m}}{2d\frac{\sigma_{i}\sigma_{m}}{\sigma_{i}+2 \sigma_{e}}+r\sigma_{m}} \tag{4}\]  
where \(\sigma_{i}\), \(\sigma_{m}\), and \(\sigma_{e}\) are the conductivities of the cytoplasm, cell membrane, and cell's surrounding medium, respectively, \(\varepsilon_{m}\) is the dielectric permittivity of the membrane, and \(d\) is the membrane thickness. To create pores for a specific pulse duration \(\tau\), the electric field intensity must reach a certain critical value, which can be estimated as follows:  
\[E_{\sigma}=\frac{2V_{\sigma}}{fr\cos\theta(1-e^{\tau/\tau_{cm}})}. \tag{5}\]  
These equations can help with calculating the initial values for the critical electric field and resulting voltage pulse characteristics [37]. All of the above equations are applicable to sinusoidal AC fields with a pulse longer than 1 \(\upmu\)s, that is, a frequency lower than 1 MHz.
# Security Protection of 3D Models of Oblique Photography by Digital Watermarking and Data Encryption
## 2 Related Works  
As a professional application of digital watermarking, 3 DMOP's watermarking technology has become a research hotspot in recent years. According to the embedding location of the watermark, traditional research can be divided into two categories, i.e., algorithms based on 3D meshes [17; 18; 19; 20; 21; 22] and 3D point clouds [23; 24; 25; 26; 27; 28].
## 4 Discussion
Regarding the biological characterization, this study showed that chitosan microparticles, peptide-loaded chitosan microparticles, guar-gum films, peptide-loaded guar-gum films, guar-gum films with chitosan microparticles, and guar-gum films with peptide-loaded chitosan microparticles showed biocompatible properties. Cell permeability of relaxing peptide into the tested systems (chitosan microparticles, guar-gum films, and peptide-loaded chitosan microparticles into guar-gum films) was compared with the free peptide. Oral delivery systems showed a faster permeability than the free peptide. So, results obtained are promising regarding the overall bioavailability enhancement of carried peptide, showing that the guar-gum film with chitosan microparticles with relaxing peptide was an efficient system promoting relaxing peptide permeability, due to the increased permeability across absorptive epithelia and regarding the protection of the peptide along the gastrointestinal tract. For this purpose, the use of chitosan as one of the most effective polymers for improving the transmucosal absorption of molecules (the ability to open intercellular tight junctions), its mucoadhesive property, and permeability enhancement were shown in this study and in others [39; 40; 41; 42; 43]. Similar studies with other delivery systems with chitosan composition also showed a controlled release of protein/peptide [40; 43]. Chitosan is known to increase the effectiveness of the permeation of protein across the mucosal epithelia, and the dual functionalization with chitosan and peptide will allow a longer residence time in the intestine; also, effective penetration through tight junction was reported by [PERSON] and collaborators [41]. Therefore, the success of this delivery system accrues the oral films' composition, with chitosan and other polymers, that present mucoadhesive and permeation enhancing nature properties. When analyzing the storage stability, the results showed that the films should be kept away from humidity when stored, so an adequate packaging system must be envisaged. The moisture content in relaxing peptide-loaded chitosan microparticles into guar-gum films increased over time under accelerated degradation conditions. Therefore, the moisture content increase can indicate that stability may decrease over time due to higher water activity, which may lead to formulation stability problems and the potential growth of microorganisms. Additionally, the high moisture content may promote the migration of bioactive molecules within the delivery system, leading to a heterogeneous formulation and compromising the pharmacokinetic function of the formulation [44; 45].
## 1 Introduction
The first model is devoted to model thin SIT up to 0.6 m while using a thin sea ice product derived from SMOS (SIT\({}_{SMOS}\)) as ground truth. The second network is designed to model full-range SIT. Input data are further complemented by CryoSat-2 Fib estimates to extend the previous model, using a merged product derived from CryoSat-2 and SMOS (SIT\({}_{CS2 SMOS}\)) as ground truth. Both of the SIT models are trained during the period from 15 October to 4 December 2020, and allowed to generate weekly composite maps of Arctic thin and full-range SIT. The Arctic dataset that was used to train the full-range model was compared to the same set of observations collected over Antarctic sea ice in terms of its variable ranges and densities. Because the Arctic training data encompasses most parts of the Antarctic dataset, the prediction of Antarctic sea ice based on the Arctic model was considered to be reasonable in statistical terms. The full-range model was applied to Antarctic data in an initial attempt to provide monthly composite maps of Antarctic SIT.
## 4 Results and Discussions
### Dual Data Streaming Design
In order to make the comparison, the received Signal-to-Noise Ratio (\(SNR\)) has been calculated for fixed beams and dynamic beams separately, using values of the received power from Equation (9) for all the available days of the year as follows:  
\[ \begin{array}{l}SNR_{fix}=30+10\Big{\{}\sum_{j=1}^{M}P_{r(1,j)}\Big{\}}\ -L_{a}-N_{0}\ \text{dB}\\ i\in 2\ to\ N\\ SNR_{dyn}=30+10\Big{\{}\Big{\{}\sum_{j=1}^{M}P_{r(i,j)}\Big{\}}\Big{\}}\ \Big{]}\ -L_{a}-N_{0}\ \text{dB}\end{array}  \tag{10}\]  
where \(N_{0}\) is the average noise power. \(N_{0}\) has been obtained as \(-101\) dBm, using a noise floor of \(-174\) dBm per Hz and a bandwidth of \(20\) MHz for the Ahmedabad link. For the Guwahati link, \(N_{0}\) has been obtained as \(-104\) dBm, using a noise floor of \(-174\) dBm per Hz and a bandwidth of \(10\) MHz, as highlighted in Table 1. In a practical system, additional fixed losses (\(L_{a}\)), like noise figure, waveguide loss, connector loss, circulator loss, and  
Figure 6: Dual data streaming design for tropospheric link using a fixed-beam and a dynamically steered beam. coupling loss (measurement loss), will reduce the \(SNR\) of both the fixed beam and dynamic beam. \(L_{a}\) has been taken as approximately 10 dB for both links. Though the tropospheric channel is a Rayleigh fading channel, space and frequency diversity combining in tropo systems removes the effect of fast fading and renders the channel an AWGN channel. Hence, achievable data rates have been calculated for both beams using [PERSON]'s channel capacity theorem for AWGN channels as follows:  
\[ \begin{split} Data\ Rate_{fix}&=B\ \cdot\ \left(1+SNR_{fix}\right)\\ Data\ Rate_{dyn}&=B\ \cdot\ \left(1+SNR_{dyn}\right) \end{split}  \tag{11}\]  
where \(B\) is the channel bandwidth given as 20 MHz. Theoretically, an achievable data rate for a conventional single-beam system will be equal to the data rate of a fixed beam obtained from Equation (11), while for a dual data streaming system with two beams, the data rate will be equal to the sum of the data rates of a fixed beam and a dynamic beam obtained from Equation (11). Figure 7 shows a comparison of the theoretically achievable data rates using a conventional fixed single-beam system and dual data streaming two-beam systems on both the Ahmedabad and Guwahati links at 0530 IST and 1730 IST. Dashed lines in blue and black depict the average daily data rate for a year. It can be clearly seen that the average daily data rate for dual data stream designs is almost double that for a single-beam design, in all cases. Figure 7: _Cont._
## 3 Results and Discussion
### Modulus of Elasticity
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{4}{c}{**Modulus of Elasticity [GPa]**} \\ \cline{2-5}
**Mixture** & **Tested Value** & \multicolumn{4}{c}{**Estimated Value**} \\ \cline{3-5}  & **(Mean)** & **ACI 363** & **Eurocode 2** & **NS 3473** \\ \hline C55\_SFA15\_SF3 & 48.64 & 35.89 & 43.30 & 40.29 \\ C100\_SFA15\_SF3 & 51.29 & 36.83 & 44.23 & 41.15 \\ C100\_SFA30\_SF3 & 51.79 & 37.11 & 44.51 & 41.41 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Comparison between modulus of elasticity values obtained from tests (according to EN 12390-13) and those estimated by three different models: ACI 363 [30], EN 1992-1-1 [26] and NS 3473 [31]. Figure 6: Average modulus of elasticity and compressive strength values for HPC (730 daysafter specimen preparation); *—compressive strength values obtained on cylindrical specimens. Given Equation (10), the estimated modulus of elasticity values of concrete at the age of 730 days would be equal to 52.41 GPa (C55_SFA15_SF3), 57.36 GPa (C100_SFA15_SF3) and 54.18 GPa (C100_SFA30_SF3). It could be concluded that none of the recommended models allows the estimation of the modulus of elasticity of tested concretes with acceptable precision. Estimated values were 26-28% lower (ACI 363) or 17-20% lower (NS 3473) than the tested values. In the case of EN 1992-1-1, the values estimated from Equation (8) were 11-14% lower than those tested, but given the correction regarding used coarse aggregate and age of concrete, the recalculated values were 5-12% higher than those tested, leading to the conclusion that the C100_SFA15_SF3 mixture could be characterized by a modulus of elasticity equal to 57.37 GPa, which is highly unlikely to be obtained for concrete composites.
## 2 Materials and Methods
### Study Area and Data Source
#### 2.1.2 Software  
Remote-sensing data were processed and used to calculate the NDVI using ENVI software version 5.3.1. ArcGIS version 10.2 for desktop was used for image resampling, reclassifying, manual vectorization, NDVI calculation, random point generation, and extracting the difference value of the sample points.
# Information Criteria for Signal Extraction Using Singular Spectrum Analysis: White and Red Noise
### Low-Rank Approximation and SSA
Section 3.1 considers the case of white noise, and Section 3.2 proposes a way to transfer the methods to the case of red noise. Section 4 includes numerical studies and comparisons on artificial examples. Section 5 verifies the performance of the methods for real-world time series. Section 6 presents a summary and discussion; conclusions complete the paper.
## 3 Soil Features as a Consequence of Reduced Fertilization
### Soil Chemistry
#### 3.1.5 Soil pH  
Reduced N fertilization has a noticeable impact on soil pH, primarily due to the role of N fertilizers, especially NH\({}_{4}\)\({}^{+}\)-based types like ammonium sulfate or ammonium nitrate, in contributing to soil acidification [23]. This acidification occurs during the nitrification process. As this transformation takes place, hydrogen ions are released, leading to a decrease in soil pH [59]. Prolonged and excessive application of N fertilizers can significantly acidify the soil, adversely affecting nutrient availability and overall soil health [35].  
By cutting back on N inputs, the acidification process slows down, allowing the soil pH to stabilize or even move toward more neutral levels. This shift brings several benefits to the soil chemistry. For instance, essential nutrients like P, Mg, Ca, and K become more available in neutral to slightly acidic soils [60]. In contrast, these nutrients can become less soluble and harder for plants to absorb in highly acidic conditions. Furthermore, the reduction of N inputs can alleviate metal toxicity, as elements like aluminum [Al\({}^{3+}\)] and manganese [Mn\({}^{2+}\)] ions become more soluble in acidic soils, potentially inhibiting root growth and overall plant development [61, 62]. By stabilizing the soil pH, the toxicity of these metals can decrease, leading to healthier root systems.  
Additionally, soil pH influences microbial activity (Table 1). Many beneficial soil microbes, including N-fixing bacteria and decomposers, thrive in neutral or slightly acidic environments [45]. By maintaining a stable pH through reduced N fertilization, a more diverse and active microbial community can be fostered, further enhancing nutrient cycling and supporting soil health [45; 63].
## 3 Analysis and Discussion of Physical Modeling Results
### Fractured Reservoirs with Various Layers  
The number of fracture layers also has a decisive influence on the seismic response characteristics of an SWBR. The SWBRs of fractured reservoirs were extracted with the same dip angle and different fracture layer numbers in the Penglaiba Formation (Figure 10).  
From the seismic profile, the morphology of the low-dipping-angle fractured reservoirs in the Penglaiba Formation was the same as that of the top of the Yingshan Formation and the fourth member of the Yingshan Formation. The SWBR of the fractured reservoirs with the same dip angle showed a gradual increase in the center maximum amplitude with the increase in the number of fractured layers. From the seismic and waveform profiles, as the number of fractured layers increased, the events of the center peak of the SWBR coarsened and thickened. For the fractured reservoirs with more than 15 layers, the events showed obvious delamination. From the frequency profile, fractured reservoirs with the same dip angle had a decreasing frequency as the number of fractured layers increased.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Number** & **Dipping Angle** & **Form** & **Image** & **Waveform** & **Frequency** \\ \hline A7 & 0\({}^{\circ}\) & & & & \\ \hline A1 & 10\({}^{\circ}\) & & & & \\ \hline A2 & 20\({}^{\circ}\) & & & & \\ \hline A3 & 30\({}^{\circ}\) & & & & \\ \hline A4 & 70\({}^{\circ}\) & & & & \\ \hline A5 & 80\({}^{\circ}\) & & & & \\ \hline A6 & 90\({}^{\circ}\) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 3: Correspondence between fractured reservoirs and responses in the top of the Yingshan Formation.  
With the same frequency of the wavelet of the seismic data, the specific number of fracture layers, thickness, P-wave velocity, density, and other parameters caused interference which influenced the seismic response characteristic in the frequency profiles. In the low-dipping-angle fractured reservoirs of the Penglaiba Formation in the Tarim Basin, the frequency decreased as the number of fracture layers increased to 5, 10, 15, and 20 (Figure 10).  
When the number of fracture layers was 5-10, the events were similar to the morphology and location of the fractured reservoirs at frequency profiles greater than 25 Hz, and the events were more difficult to recognize when the number of layers was 15-20.
# Research on Equalization Strategy of Lithium Battery Pack Based on Multi-Layer Circuit
## 5 Simulation Results
### Overall Analysis  
The performance of the equalization method tested is shown in Table 5. When the multi-layer equalization circuit does not use the equalization method, the equalization time is 245.7 s and the maximum battery current is 5.04 A, which is significantly more than the 3 A allowed by this study. The proposed equalization method has a time of equalization of 268.5 s and a maximum current of 3 A, which is within the allowable range. The equalization time is 350.65 s and the maximum current is 4.93 A when the adjacent battery equalization circuit is used and the equalization strategy is not applied, surpassing the maximum permitted current. The battery pack did not reach equalization using the fuzzy control equalization approach, and the highest equalization current was 4.72 A. Despite the fact that the current was lowering, it was still above the limit. The battery pack did not attain equilibrium using the control approach based on SOC difference, and the maximum equilibrium current was 4.68 A, surpassing the maximum permitted current. To summarize, the proposed layered control method based on multi-layer equalization circuit can take use of the multi-layer equalization circuit's high equalization speed while keeping the battery current within the permissible range, which ensures both the equalization speed and the safety of the equalization process.
# A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi
###### Abstract
It is shown later in this paper that the proposed DPO-OFDM, simplified as DPO, can achieve a wide dimming range with better spectral efficiency compared to ADO and has better power efficiency compared to AHO and HDAP. It can be noted that finding the appropriate proportions of the individual components of DPO, HDAP, or any other hybrid OFDM is an important task where machine learning (ML) may be useful. This paper also focuses on the effectiveness of applying ML in selecting the components of hybrid OFDM formats. The major contributions of this article are in the following aspects. 1. A new OFDM format termed DPO-OFDM is introduced using the concepts of DCO-OFDM and PAM-DMT;
2. Mathematical expressions of the DC-bias level for the proposed DPO-OFDM are derived. The BER performance and spectral efficiency with dimming control are compared with existing optical OFDM formats;
3. A switching algorithm for the existing HDAP-OFDM is proposed where the individual components of HDAP-OFDM are switched according to a target dimming level;
4. ML regressors are used to find the appropriate proportions of the individual components of DPO-OFDM for a target dimming level. This concept is also applicable to HDAP-OFDM and other hybrid OFDM formats. The rest of the paper is arranged as follows: Section 2 reviews the literature of existing OFDM schemes. Section 3 describes the proposed DPO system. The framework of the DC-bias level of the DPO system is presented in Section 4. Section 5 provides performance results of DPO in terms of power efficiency and dimming control. In Section 6, a switching algorithm for HDAP is presented. Section 7 describes an ML-based approach for finding the appropriate proportions of the elements of DPO or other hybrid OFDM schemes for a given dimming level. Finally, Section 8 presents the concluding remarks.