esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Computational Methods and Validation
### Stability Analysis Method
The equation can be further transformed into the following:  
\[\mathbf{D}_{j}\Delta\mathbf{q}_{j+1}=\Delta t\mathbf{C}_{j+1}\Delta\ddot{\mathbf{q}}_{j}+ \bigg{(}\frac{4\mathbf{M}_{s}}{\Delta t^{2}}+\mathbf{C}_{j+1}-\mathbf{C}_{j}\bigg{)}\Delta \dot{\mathbf{q}}_{j}+\bigg{(}\frac{4\mathbf{M}_{s}}{\Delta t^{2}}+\frac{2\mathbf{C}_{j+1}}{ \Delta t}-\mathbf{K}_{j}\bigg{)}\Delta\mathbf{q}_{j} \tag{34}\]For a sufficiently small time interval \(\Delta t\), the first term on the right-hand side of Equation (34) vanishes, yielding the following:  
\[\Delta\mathbf{q}_{j+1}=\mathbf{E}_{j}\Delta\mathbf{q}_{j}+\mathbf{F}_{j}\Delta\mathbf{q}_{j} \tag{35}\]  
where \(\mathbf{E}_{j}=\mathbf{D}_{j}^{-1}\Big{(}\frac{\mathbf{\alpha}\mathbf{M}_{j}}{\Delta t^{2}}+ \mathbf{C}_{j+1}-\mathbf{C}_{j}\Big{)}\), \(\mathbf{F}_{j}=\mathbf{D}_{j}^{-1}\Big{(}\frac{\mathbf{\alpha}\mathbf{M}_{j}}{\Delta t^{2}}+ \frac{2\mathbf{C}_{j+1}}{\Delta t}-\mathbf{K}_{j}\Big{)}\). This second-order differential equation can be transformed into a system of first-order differential equations using state-space representation:  
\[\mathbf{x}_{j+1}=\mathbf{T}_{j}\mathbf{x}_{j} \tag{36}\]  
where \(\mathbf{x}_{j}=\Big{[}\Delta\mathbf{q}_{j},\Delta\mathbf{q}_{j}\Big{]}^{\mathsf{T}}\), \(\mathbf{T}_{j}= \begin{bmatrix}\frac{2}{\Delta t}\mathbf{E}_{j}-\mathbf{I}&\frac{2}{\Delta t }(\mathbf{F}_{j}-\mathbf{I})\\ \mathbf{E}_{j}&\mathbf{F}_{j}\end{bmatrix} \). The Floquet monodromy matrix can then be expressed through multiplication:  
\[\mathbf{\Phi}=\mathbf{T}_{K}\cdots\mathbf{T}_{j+1}\mathbf{T}_{j}\mathbf{T}_{j-1}\cdots\mathbf{T}_{0} \tag{37}\]  
The stability condition for periodic solutions requires all eigenvalues \(u_{i}(i=1,2,...,2N)\) of the Floquet monodromy matrix \(\mathbf{\Phi}\) to lie within the unit circle in the complex plane, meaning the magnitude of the maximum Floquet multiplier \(u_{max}\) must be less than 1:  
\[|u_{i}|=\sqrt{\text{Re}\left(u_{i}\right)^{2}+\text{Im}\left(u_{i}\right)^{2} }<1,(i=1,2,3...,2N) \tag{38}\]  
Based on how Floquet multipliers cross the unit circle, as shown in Figure 5, three instability types exist [28]:  
* If Floquet multipliers cross the unit circle at (1, 0), the system's periodic response may undergo saddle-node bifurcation. * If Floquet multipliers cross the unit circle at (\(-1,0\)), the periodic response undergoes period-doubling bifurcation. * If a pair of complex conjugate Floquet multipliers leaves the unit circle, the periodic response undergoes secondary Hopf bifurcation.
## 4 Results
### Sensitivity Case--Maximum Available Budget for Battery Purchasing  
A sensitivity case study depends on different values of the available purchasing budget (\(\overline{IC_{B}}\)) are developed. This sensitivity analysis considers four cases, which include percentage values of the available purchasing budget based on the base case, as follows: 80%, 70%, 60%, and 50%. In Figure 8 optimal battery sizes of the four considered cases are illustrated.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Existing BESS Sizing for DC [15]** & **Proposed Method** \\ \hline Annual energy cost & \$213,486.5 & \$213,624.8 \\ \hline Annual DC cost before BESS deployment & \$206,418.0 & \\ \hline Annual DC cost after BESS deployment & \$158,672.0 & \$157,946.0 \\ \hline Annual Saving of DC & \$47,746.00 & \$48,472.00 \\ \hline Annual BESS capital cost & \$40,987.90 & \$40,943.23 \\ \hline \multirow{2}{*}{BESS size} & 352 KW & 356 KW \\ \cline{2-3}  & 374 KWh & 372 KWh \\ \hline \hline \end{tabular}
\end{table}
Table 3: Comparison results of the existing battery energy storage system (BESS) sizing for demand charges (DC) [15] and the proposed method.  
Figure 7: The monthly maximum power of class-A customer in Ontario.  
The comparison results between the annual accumulated costs of each considered case are presented in Figure 9. The results demonstrate that restricting the battery purchasing budget will limit the battery size leading to increase the global adjustment cost.  
The annual revenues of the BESS are presented in Figure 10. The results show that the achieved revenues of the battery from EPA and DR keep decreasing with a reduction in the allowable BESS budget.  
Figure 8: Optimal sizing of the BESS as a result of the sensitivity analysis on the maximum allowable budget (**a**) for power (MW) and (**b**) for rated energy (MWh).
# Factorial Design Analysis for Localization Algorithms
## 2 Related Work
### Evaluation Scenarios Reported
In [23] the authors propose two testbeds for characterizing the channel by means of the RSSI. In this scenario range-free localization algorithms such as Ring Overlapping Circle RSSI (ROCRSSI) [38] and range-based localization algorithms such as minmax [39; 40], multilateration [19] and Maximum-Likelihood [36; 41] are evaluated in an indoor area measuring 10 m \(\times\) 10 m with six RNs. These algorithms are evaluated using two testbeds where the ALE is measured by varying the number of RNs and the CDF vs. localization error. In the simulation scenarios, range-free and range-based localization techniques are evaluated in different sensing areas. In [19] the authors propose a sensing area of 1000 m \(\times\) 1000 m where the log-normal shadowing propagation model is used. In this scenario the MSE is evaluated based on noise \(\sigma_{dB}\in\{4,\ldots,12\}\) dB and node density \(\rho\in\{1,\ldots,9\}\) nodes on an area of 100 m \(\times\) 100 m. Again, the CDF is evaluated based on localization error. In [22] range-free localization techniques are also evaluated on an area of 1000 m \(\times\) 1000 m where the log-normal shadowing model is used for different propagation settings, at 2.4 GHz Wi-Fi/802.11g [42; 43] and 5.8 GHz [44; 45]. In this scenario the localization technique performance is evaluated on the basis of the ALE and the CDF, by varying the node density \(\rho\in\{0.25,0.5,0.75,1,\ldots,9\}\) and the number of RNs \(N_{rx}=\{2,4,8,16\}\) for 2.4 GHz and 5.8 GHz environments.
# Personalized Online Live Video Streaming Using Softmax-Based Multinomial Classification
## 2 Related Work
### Progressive Download Method  
The progressive download (PD) method is a widely used multimedia streaming technique (refer to Figure 1). The PD method places the file on the web server and notifies the user with the address of file. Therefore, users are enabled to download and use the media file from the provided URL where the file is located. In order to maintain a high QoE without interrupting the media through PD, the network speed from the server to the user must be higher than the media's data rate. For instance, suppose a user has a 1 Mbps video, the minimum speed of the network should be above 1 Mbps to ensure seamless video playback. In this context, the PD method is simple to implement, and does not incur any additional costs. However, the PD method has several security issues, mainly because users must download the media file directly. Accordingly, PD is more suitable for the Video On Demand (VOD) market, rather than the OTT market.  
Figure 1: Structure of the progressive download (PD) method.
# A Continuous Monitoring and Reallocation Method for Successful Decisions in Change Management
## 2 State of the Art  
### Change Management Models  
The contemporary literature contains a number of models and strategies that aim to optimize the introduction and management of changes. Historically, the first change management model was proposed in 1947 by [PERSON], who described the change management process in three stages, \"Unfreeze\", \"Change\", and \"Freeze\", as shown in Figure 1. The first stage includes recognizing the willingness to change. In this stage, there is a balance between forces that resist change and those that are positive toward change. The process of change has not started, so these forces are not yet apparent. The second stage is the process of \"Change\" that will lead to the new state. Here, the conflicting forces emerge. Initially, the forces that resist the change overcome the driving forces that are positive. All necessary actions to reduce RtC must be taken. The third stage is \"Freeze\", encompassing the consolidation of the change and stabilization in the new situation [25; 26].  
[PERSON] et al. [27] presented a six-step management model of effective change, including reorganizing employee roles, responsibilities, and relationships to solve specific business issues by breaking them into smaller units with clearly defined goals. In the final stage, the change must be monitored and adjusted. [PERSON] and [PERSON] [10] proposed an eight-step change management model that is also highly relevant to successfully implementing organizational change. The steps that must be followed are described in detail, emphasizing  
Figure 1: The three-stage model of change and force field analysis [25].  
the preparation for, participation in, and acceptance of the change by employees. The ADKAR model focuses on people's adaptation to change rather than the change itself. ADKAR is an acronym for Awareness, Desire, Knowledge, Ability, and Reinforcement, the five tangible and concrete outcomes that people need to achieve for a change to be sustainable [28; 29]. All of the above models follow a linear sequence of steps from the initiation of the change to stabilization and the establishment of the new situation. There are also approaches that consider the importance of taking action before the upcoming change. According to these methods, training, readiness for change, communication of change, and commitment to change play important roles [6; 8; 30; 31; 32].
## 3 Materials and Methods
### Radiochemistry  
#### 3.3.1 General Radiochemistry  
[\({}^{11}\)C]CO\({}_{2}\) (20-25 GBq) was produced via the \({}^{14}\)N(p,\(\alpha\))\({}^{11}\)C nuclear reaction by irradiating (30-35 \(\mu\)A for 25-40 min) 99.5%mol N\({}_{2}\) doped with 0.5%mol O\({}_{2}\) in a GE PETraceTM 800 cyclotron (GE Healthcare GmbH, Munich, Germany). Production of [\({}^{11}\)C]MeI was performed on a custom-built synthesizer as reported previously [35]. Briefly, [\({}^{11}\)C]CO\({}_{2}\) was reduced to [\({}^{11}\)C]MeOH using 1 m LiAlH\({}_{4}\) in THF (ABX, Radeberg, Germany) and the THF was removed at 100 \({}^{\circ}\)C in a stream of helium. After the addition of 4.3 M H\({}_{3}\)PO\({}_{4}\), the [\({}^{11}\)C]MeOH was distilled off at 150 \({}^{\circ}\)C and passed through a pre-heated (170 \({}^{\circ}\)C) column with alumina-supported triphenylphosphine diiodide. The resulting [11C]MeI was passed through a second column with phosphorus pentoxide and collected in a reaction vial containing the labelling precursor (**8,10** or **12**) and the corresponding solvent pre-cooled to \(-\)10 \({}^{\circ}\)C (DMF, DMA) or 20 \({}^{\circ}\)C (DMSO), respectively. [11C]Methyl triflate ([11C]MeOff) was prepared on a Synthra Melplus system (Synthra GmbH, Hamburg, Germany) using the process and chemicals specified by the manufacturer. Briefly, [11C]CO2 produced as described above was converted to [11C]methane over nickel at 400 \({}^{\circ}\)C, followed by conversion to [11C]MeI by I2 in the gas phase at 700 \({}^{\circ}\)C in a continuous flow process where [11C]MeI was trapped on a Porapak Q column. Conversion to [11C]MeOTf was achieved via reaction with silver triflate at 190 \({}^{\circ}\)C. [11C]MeOTf was collected in a reaction vial containing precursor **8a** and solvent (acetone or acetonitrile) pre-cooled to \(-\)10 \({}^{\circ}\)C. The syntheses were performed in a helium atmosphere.
# Fractal Metasurfaces and Antennas: An Overview for Advanced Applications in Wireless Communications
## 4 Fractal Metasurfaces
### Fractal Metamaterial Absorbers
#### 4.1.2 Examples of Fractal-Based MAs
In reference [58], a Minkowski inspired circular fractal metamaterial microwave absorber was proposed for multiband applications. The absorber structure consists of a novel geometry of second-order circular fractal rings printed on a grounded FR4 dielectric substrate. The fractal patch is achieved using a circular ring, called the initiator (see \(n=0\) in Figure 20a), followed by a level 1 fractal (\(n=1\)), which is then extended to an upper iterated fractal (\(n=2\)). Figure 20b shows the absortivity of the initiator and generator structures, as well as the proposed Minkowski-inspired circular fractal absorber (denoted by \(n=0\), 1, and 2, respectively). The Minkowski-inspired circular fractal MA (\(n=2\)) exhibits a greater number of absorption peaks compared to the initiator (\(n=0\)) and the generator absorber (\(n=1\)). More specifically, it offers four absorption peaks at 5.6, 11.5, 15.4, and 17.6 GHz with absortivities greater than 90%, and two peaks at 1.8 and 8.4 GHz with absorptivities greater than 80%. In [59], a triple-band metamaterial absorber was proposed for applications requiring very high compactness values. Unlike previous multiband absorbers, this implementation incorporates fractal geometry into an artificial transmission line framework (Figure 21b). The resulting large inductive-capacitive values make the element compact, approaching \(\lambda_{0}/15\) at the lowest fundamental resonant frequency. The absorber exploits the self-similarity and space-filling capabilities of fractals. The fractal perturbed element is significantly smaller due to the engineered semi-lumped circuit elements and therefore exhibits multifunctional self-resonant properties. Figure 21a shows the simulated results of the MA, displaying three distinct absorption peaks. Figure 19: Sierpinski–Minkowski fractal MA: (**a**) unit cell structure, (**b**) fabricated absorber, (**c**) measured absorption coefficient (Adapted with permission from [57], IET, 2019).
# Anti-Fouling Properties of Phosphonium Ionic Liquid Coatings in the Marine Environment
## 3 Result and Discussion  
### Preparation of Phosphonium Ion Gel Coatings  
#### 3.1.1 Preparation of Phosphonium Docusate Ionic Liquids  
The class of phosphonium docusate ionic liquids was chosen for study because it allowed a combination of the phosphonium cation, known to have antimicrobial activity and four alkyl substituents that can convey significant hydrophobicity [29; 40; 41] with the docusate anion, which has been shown to be hydrophobic and possess antimicrobial properties [9; 34]. This led to the hypothesis that the combination would produce ionic liquids and ion gels with marine anti-fouling properties similar to both biocide-containing polymers and hydrophobic SLIPS materials.  
The docusate ionic liquids were prepared via the metathesis of the known halide intermediates tributyl(vinylbenzyl)phosphonium chloride [35], trioctyl(vinylbenzyl)phosphonium chloride [35], tributyl(octyl)phosphonium bromide [35; 36], and trioctyl(tetradecyl)phosphonium bromide (Figure 2) [35; 36]. The metathesis reaction was adapted from that described by [PERSON] et al., 2020 for the metathesis of phosphonium ionic liquids [9].  
The monomers and free ionic liquids were characterized through \({}^{1}\)H and \({}^{13}\)C NMR (cation structure), FT-IR (presence of docusate through C=O stretch and vinyl groups through C=C stretch), and Mass Spectrometry (confirming presence of cation and anion structures of appropriate molecular weights) (Supplementary Section S2). The removal of halide was confirmed using a silver nitrate test.
# Potentials for Pressure Gain Combustion in Advanced Gas Turbine Cycles
## 3 Results and Discussion
### Recuperated Gas Turbine  
Figure 12 depicts the pressure ratios for the recuperated cycle. Recuperator performance was driven by the temperature difference of the cold and the hot side. More heat was transferred if cold side temperatures were low. That is why the compressor pressure ratios for the recuperated cases were small compared to the other cycles. Additionally, recuperation increased the combustor inlet temperature, which combined with the blade temperature constraint restricted the temperature ratio in the combustor. Hence, also the pressure ratios in the combustor were rather small, resulting in OPR below 11. One could expect low TET from this, since TET and OPR were coupled, but recuperation required not only low cold side temperatures, but also high hot side temperatures. In order to provide high turbine outlet temperatures, TET were similar to the simple cycle TET with isobaric combustion and the intercooled cycle TET with PGC. Only the ideal isochoric case provided a huge reduction in TET.  
Figure 13 presents SAS and heat exchanger specifications. Adding recuperation to an engine with isobaric combustion only reduced SAS mass flow by 2 PP. However, applying recuperation with PGC reduced the SAS mass flows. Here, cycles using the model of [PERSON] required a SAS mass flow of only 15%, and with the ideal isochoric combustion, a mass flow of 7.5% sufficed. In addition, the recuperated setup lead to a substantial reduction in the SAS compressor power. The power requirement for the SAS compressor was below 2.5% of the output power. That was half of the power required for the intercooled cycle. The reduced pressure gain in the combustor for recuperated cycles was responsible for this. Figure 13 depicts also the inlet temperatures to the recuperator heat exchangers. The temperature differences were in the same order for all cycles for optimum efficiency even though the TET varied between realistic PGC representation by more than 200 K. Thus, the transferred specific heat through the recuperator was almost equal for all models.  
Figure 12: Pressure ratio and TET for recuperated cycle.
# Study on Gearbox Fault Warning Based on the Improved M-IALO-GRU Model
## 4 Experimental Validation
### Analysis of Prediction Results of Normal Data of Gearbox Operation
#### 4.2.3 Comparison Analysis of Different Residuals of Different Models  
The fault alarm threshold of the model will be set based on normal data and the 3 \(\sigma\) principle following normal distribution. By using the model trained with normal samples, the residual between the actual value and the predicted value should remain within the set alarm range. Once an abnormal situation occurs, the predicted residual will fluctuate significantly and exceed the alarm threshold range, thus realizing the fault warning. The methods for calculating the threshold range are detailed in Equations (18) and (19).  
\[\text{UCL}=\mu+3\sigma \tag{18}\]  
\[\text{LCL}=\mu-3\sigma \tag{19}\]  
where \(\mu\) represents the mean of the residual between the actual and predicted value and \(\sigma\) represents the standard deviation.  
The results are shown in Figures 9 and 10. Due to the minimal threshold range determined by the IALO-GRU model, the early-warning model achieves higher precision and sensitivity in the identification of anomalous data. Further explained, the model will be better able to capture those unusual and more difficult-to-detect abnormal data. This helps to identify the abnormalities in advance, ensuring that the abnormalities are not missed. So that the model can ensure effective detection, it improves the maintenance efficiency of operation and maintenance personnel and can provide strong data support for decision-making.
# A Comprehensive Review on Mine Tailings as a Raw Material in the Alkali Activation Process
###### Abstract
Mechanical activation methods, such as grinding, thermal treatment (calculation), and alkaline fusion, are effective in increasing the reactivity of minerals, including those found in mine tailings [41]. These processes modify their mineral structure and composition, making them more amenable to subsequent chemical reactions, such as alkali activation or the formation of geopolymers. Within alkali activation technologies, the resulting materials have versatile applications, including use in paste backfilling, as construction materials at mining sites, or for designing dry landfill alternatives, rather than being discarded in tailing dams [42]. This paper aims to provide a comprehensive review of recent research focused on the alkali activation of mine tailings. Since mine tailings are considered waste, and waste-based materials typically face limitations in large-scale applications, it is necessary to establish laws and policies that facilitate the integration of tailings into construction industries. However, before such policies can be enacted, it is crucial to accumulate sufficient data regarding the practical utilization of mine tailings in construction.
# 100 Picosecond/Sub-10\({}^{-17}\) Level GPS Differential Precise Time and Frequency Transfer
## 5 DPT Time and Frequency Transfer Validations  
In this section, we first verified the accuracy of time transfer through two methods: common clock time transfer and DPT with closure baseline. Then, we evaluated the precision of long-term DPT time transfer through 30 days of continuous solutions. Finally, we analyzed the time and frequency stability of DPT.
## 4 Results and Discussion
### Land Use and Land Cover Change
#### 4.2.1 Main Land Use and Land Cover Types  
The results from the 2019 baseline LULC mapping based on Sentinel-2 (10 m) can be seen in Figure 13. In total, eight different classes were mapped, and the map shows that the area is dominated by forested areas with agricultural activities around several smaller settlements which function as a pressure regarding deforestation.  
The total area breakdown is presented in Figure 14 and shows that natural vegetation makes up roughly 93.7% in the area of interest, with more than half of that area covered by forest. The remaining part of the area is mostly anthropogenically altered or used to some extent: 4.62% is dedicated to agriculture, 1.19% of the area is sealed (settlements and primary roads) and 0.46% are made up of standing water and rivers.  
Figure 13: Dilijan National Park, Armenia: Land Cover Land Use Map 2019 based on Sentinel-2 data (10 m).  
As already mentioned above in the methodology section, two separate LULC maps for the year 2019 were produced at 10 m and 30 m resolutions from Sentinel-2 and Landsat 8 imagery, respectively. The Sentinel-2-based map was created to include the best available data (in the case of Sentinel-2) to produce a high-resolution map as a baseline for potential future monitoring activities. The Landsat 8 map was generated to achieve a better comparability between the preceding epochs, which are all based on Landsat 8 (because the first Sentinel-2 satellite was launched in 2015). Figure 15 shows both classifications side by side highlighting the area around the city of Dilijan inside the national park. On the left side, the Sentinel-2-based product at 10 m is shown and when directly compared to the Landsat 8 (right side) at 30 m resolution, it can be clearly seen that Sentinel-2 offers much greater spatial detail. On the left side even small (groups of) buildings are visible and due to the smaller minimum mapping unit, a more fragmented and detailed overview of the area is discernable.