esa-sceva/satcom-chunk-collection huggingface dataset:
# Advanced Composite Materials: A Panacea for Improved Electricity Transmission
## 2 Strength and Challenges of Transmission Conductors
Aluminum conductor steel supported (ACSS), aluminum conductor composite reinforced (ACCR), aluminum conductor composite core (ACCC), and gap-type aluminum conductor steel reinforced (G-TACSR) conductors are examples of the HTLS conductors. When utilized in power transmission grids, their sag performance is one of the most significant attractive properties [39]. Figures 4 and 5 show the essential characteristics of HTLS transmission  
Figure 3: Conventional transmission conductors in the market: (**a**) ACSR and (**b**) AAAC [26]. conductors [14; 40; 41]. From Figure 4, it can be noticed that all the HTLS conductors possess higher ampacity than ACSR and AAAC conductors. Figure 4: Ampacity versus operating temperature of transmission conductors [39]. Figure 5: Coefficient of thermal expansion of conductor materials [39]. This is because they can withstand higher temperatures than the conventional conductors, and thus can transmit higher voltage. Higher current produces higher heat as a result of the joule heating (I\({}^{2}\)R). It is equally observed in Figure 5 that both Al and steel possess a greater percentage of CTE. Hence, development of transmission conductors with these alloys should be minimized if total discarding is not possible. ACCC and ACCR have the highest ampacity as well as the lowest CTE percentages in the figures. Therefore, they are the most efficient HTLS conductors. Table 1 shows pictures, advantages, and weaknesses of the available HTLS conductors. It is observed that all of them have individual benefits as well as weaknesses. Therefore, it is not yet over for researchers in the development of more robust conductors with optimal functionality. This is because one or more of the issues identified in those conductors precludes their perfect operation, maximum productivity, and efficacy as a power transmission conductor capable of addressing the entire grid crisis. Some researchers' recent works [33; 61; 62; 63; 50], which focused on the design and development of new HTLS conductors, have demonstrated that those issues ravaging HTLS conductors, as shown in Table 1, could be addressed with innovative design and development of more improved conductors. In their design and development of the robust conductor, an outer layer comprising aluminum-niobium (Al-Nb) alloy and an inner core consists of an aluminum-carbon nanotubes-niobium (Al-CNTs-Nb) composite, as shown in Figure 6. The conductor material's electrical and thermal conductivity, as well as its tribological, corrosion, and mechanical properties, gave it an edge over other HTLS con
## 2 The Symbolic Compositional Hierarchical Model
### Inferring Patterns
#### 2.3.2 Inhibition  
Inhibition in our model is a hypothesis refinement mechanism, which reduces the amount of redundant activations. An activation of a part \(P_{i}^{n}\) is inhibited (removed) when one or multiple parts \(P_{j_{1}}^{n},\ldots,P_{j_{k}}^{n}\) cover a large part of the same events in the input, but with stronger magnitude. More formally, activation of the part \(P_{i}^{n}\) is inhibited when the following conditions are met:  
\[\exists\{P_{j_{k}}^{n}\ldots P_{j_{K}}^{n}\}:\frac{|C(A(P_{i}^{n}))\backslash \bigcup_{k=1}^{K}C(A(P_{j_{k}}^{n}))|}{|C(A(P_{i}^{n}))|}<\tau_{I} \tag{8}\]  
and  
\[\forall P_{j_{k}}^{n}\in\{P_{j_{1}}^{n}\ldots P_{j_{K}}^{n}\}:A_{M}(P_{j_{k}}^ {n})>A_{M}(P_{i}^{n}). \tag{9}\]  
The \(C(A)\) represents activation coverage (Equation (6)), \(A_{M}\) activation magnitude (Equation (3)) and \(\tau_{I}\) controls the strength of inhibition. If \(\tau_{I}\) is set to zero, no inhibition occurs; the larger its value, the more activations are inhibited and propagated less between model layers. Notably, only activations with magnitude larger than that of the part \(P_{i}^{n}\) are considered in the inhibition process.  
Besides reducing the number of activations and output patterns, the inhibition mechanism can also be used for producing alternative explanations of the input. If activations of the strongest pattern which inhibits other competing hypotheses are removed from the model, the next best hypothesis is selected during inference, thus providing an alternative explanation with different pattern occurrences to appear in the model's output.
# Study of System Integral Energy Efficiency of a Hybrid Pneumatic Power System
## 3 Results
### Free Load Condition and Efficiency of Air Motor  
The air motor performance in cases of with and without exhaust from the ICE are presented. This is very important to determine the best position working area and the efficiency of our HPPS. In this case, the air motor ran at the free load condition with and without exhaust from the ICE. The value of the load cell was 0. The ICE and compressor were run at the sweet spot condition, with an ICE speed of 3800 rpm. The exhaust pressure was 27 Psi, and the temperature was approximately 350 \({}^{\circ}\)C. Following Figure 8, at the free load condition and outlet of the air tank pressure was lower than 4 bar, the air motor speed rose rapidly from 0 to approximately 2200 rpm without the exhaust condition and from 0 to 2500 rpm with the exhaust condition, when the outlet air tank pressure was increased from 0 to 4 bar. After that, the air motor speed increased from approximately 2200 to 2750 rpm without the exhaust and from approximately 2500 to 2900 rpm in the exhaust condition, when the outlet air tank pressure was raised from 4 to 8 bar.  
Figure 8: Relationship between air motor speed and inlet pressure in case of with and without exhaust at the free load condition.  
Figure 7: Pressure of the air storage tank at different internal combustion engine (ICE) speeds.  
In this test, we measured the efficiency of the air motor under two conditions for the inlet air motor, with and without exhaust from the ICE. In Figure 9, the lower line chart shows the efficiency of the air motor without the exhaust inlet condition, and the higher line chart measures the efficiency of the air motor with exhaust at the inlet condition. With the exhaust at a high temperature and pressure for the inlet condition, the efficiency of the air motor increased to approximately 30% at a pressure lower than 4 bar for the outlet air tank. Without the exhaust at the inlet condition, the efficiency of air motor dropped rapidly from approximately 38% at 4 bar of the outlet air tank pressure, to 0% at 1.5 bar of the outlet air tank pressure. With the exhaust at the inlet condition, the efficiency of the air motor reduced significantly from approximately 62% at 4 bar of outlet air tank pressure, to 0% at 0 bar of outlet air tank pressure. From 4 to 8 bar, in the no-exhaust condition, the efficiency of the air motor increased slightly from 38% to 48%. However, in the exhaust condition, the efficiency of the air motor rose considerably from 62% to 72%.
# Estimating Critical Latency Affecting Ship's Collision in Re-Mote Maneuvering of Autonomous Ships
## 2 Definition of Concepts and Terms Regarding Critical Latency  
The concept of critical latency that can cause ship collisions has been established based on COLREGs encountering situations, and the estimation technique of critical latency has been proposed using turning circles of the own ship, which can be explained in x-y plane coordinates.
## 3 Results and Discussion
### HCA Content of Coated Chicken Liver Samples
The addition of turmeric to chicken meatballs [49], black pepper to beef meatballs [97], and red chili, paprika, ginger, and black pepper to beef and chicken meatballs [98] were reported to have inhibitory effects on HCAs. Spice antioxidants may inhibit the formation of HCA by donating hydrogen atoms and transferring single electrons to decrease or quench active radicals [98]. It was determined that the total HCA content of the thyme-containing deep-fried samples was 12.09% less than the oven-cooked samples. The total HCA, MeIQx, and 4.8-DiMelQx contents of the oven-cooked samples were found to be higher than those of the deep-fried samples (\(p<0.05\)). The number of HCAs increases significantly with frying time [99]. HCA formation increases due to cooking above 150 \({}^{\circ}\)C and for more than 2 min [100]. Because the deep-fat-frying time in the current investigation was restricted to 1.5 min, it is thought that the HCA content of the samples is lower compared to the oven-cooked samples. Another factor affecting HCA formation is related to cooking loss. It has been established that an increase in cooking loss results in an increase in HCA formation, due to an increase in dry weight. The present study revealed that the cooking loss of the oven-cooked samples was higher than that of the deep-fried samples. It is hypothesized that this increased cooking loss of the oven-cooked samples led to an increase in the HCA content.
## 6 Dynamic Responses of Floating OWTs  
After analyzing hydrodynamic coefficients of floating OWTs, the Response Amplitude Operators (RAOs) would be applied to three typical motion responses, i.e., surge, heave, and pitch. In addition, the performances of floater's dynamics were compared with other published data. It is noted that the coupling motion responses were not considered in the present study. In order to analyze the characteristics of wave-load components once the mooring load is added, time histories of wave-load components at the natural frequencies of surge, heave and pitch for each floating OWT would be presented in the following sections.  
Figure 14: The mesh convergences for hydrodynamic coefficients (**a**) \(\mu_{11}\); (**b**) \(\
u_{11}\); (**c**) \(\mu_{33}\); (**d**) \(\
u_{33}\); (**e**) \(\mu_{55}\); and (**f**) \(\
u_{55}\) of the UMaine TLP wetted hull under different panel numbers.
## 3 Results and Discussion
### Metal Content
These metals play a crucial role in biomedical applications, food preservation, and environmental protection due to their ability to fight pathogens and neutralize oxidative stress. Some metals can contribute to the radical scavenging activity in assays like DPPH and ABTS. Their role depends on factors such as the form of the metal (nanoparticles or ions), their concentration, the interaction with the essential oil components and the stability of the metals in the oil. The combination of the activity of the \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Element**} & **RfD [10]**, \(\upmu\)g/kg & \multicolumn{6}{c}{**Concentration, mg/kg**} \\ \cline{3-8}  & **bw/day** & **Lemon Peel** & **Laurel** & **Clove** & **Star Anise** & **Oregano** & **Nutmeg** \\ \hline Cu & 50 & 17.61 & 6.71 & 13.03 & 1.95 & 21.44 & 2.91 \\ Zn & 300 & 77.78 & 7.69 & 17.69 & 3.43 & 15.51 & 5.24 \\ Al & 1000 & 14.14 & 28.17 & 10.17 & 15.48 & 29.73 & 23.47 \\ Co & 43 & 0.06 & 0.02 & 0.06 & 0.03 & 0.02 & 0.02 \\ Cr & 3 & 0.51 & 0.19 & 0.36 & 0.37 & 0.32 & 0.31 \\ Mn & 140 & 0.95 & 0.30 & 0.59 & 0.71 & 0.35 & 0.23 \\ Ni & 20 & 1.03 & 0.19 & 0.84 & 0.09 & 1.19 & 0.03 \\ Mg & - & 12.22 & 7.41 & 8.40 & 6.00 & 14.33 & 2.46 \\ Na & - & 30.75 & 52.99 & 35.25 & 54.66 & 46.62 & 17.61 \\ As & 0.304 & 0.48 & 0.76 & 0.34 & 0.19 & 0.38 & 0.45 \\ Cd & 1 & 0.05 & 0.05 & 0.06 & 0.01 & 0.02 & 0.02 \\ Hg & 0.571 & 0.60 & 0.71 & 0.88 & 0.47 & 0.46 & 0.27 \\ Pb & 3.57 & 0.65 & 0.42 & 0.79 & 1.52 & 0.82 & 0.62 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Metal content in essential oils. metals with the natural antioxidants present in the essential oil could lead to an enhanced free radical scavenger due to synergistic effects.
# An Information Theoretic Approach to Privacy-Preserving Interpretable and Transferable Learning
## 4 Evaluation of the Information-Leakage  
Consider a scenario where a variable \(t\) is related to another variable \(x\) through a mapping \(f_{t\to x}\) such that \(x=f_{t\to x}(t)\). The mutual information \(I(t;x)\) measures the amount of information obtained about variable \(t\) through observing variable \(x\). Since \(x=f_{t\to x}(t)\), the entropy \(H(t)\) remains fixed independent of mapping \(f_{t\to x}\), and thus, the quantity \(I(t;x)-H(t)\) is a measure of the amount of information about \(t\) leaked by the mapping \(f_{t\to x}\).  
**Definition 9** (Information Leakage).: _Under the scenario that \(x=f_{t\to x}(t)\), a measure of the amount of information about \(t\) leaked by the mapping \(f_{t\to x}\) is defined as_  
\[IL_{f_{t\to x}} :=I(t;f_{t\to x}(t))-H(t) \tag{83}\] \[=I(t;x)-H(t). \tag{84}\]  
_The quantity \(IL_{f_{t\to x}}\) is referred to as the information leakage._  
This section is dedicated to answering the question: _How to calculate the information leakage without knowing data distributions?_
## 1 Introduction
Thus, adding 1,2,3-benzotriazole (BTA), benzimidazole, pyrazole, or their derivatives to a corrosive environment, including a chloride environment, results in the formation of a chemisorptive compound [41] or a multicomponent structure on brass, which, besides copper and zinc oxides, includes polymer systems with ions Cu(I) and Zn(II) [42; 43; 44; 45; 46; 47; 48; 49; 50; 51]. This creates a protective barrier for both metal components of the copper-zinc alloy and prevents further oxidation and consequent dezincification and pitting of brass. BTA is known to be toxic [52; 53; 54], so various organic and inorganic compounds may be considered as alternatives. It was found, however, that sodium salt of glycogen and polyphosphoric acids [55], as well as chromates, molybdates, tetraborate, tungstates [56; 57], and natural aragonite [58], whose corrosion protection properties were studied, do not protect brasses as effectively as the derivatives of environmentally friendly 1,2,4-triazole. Thus, the degree of protection of \(\alpha\)-brass in hydrochloric acid solutions with 5-amino-1\(H\)-1,2,4-triazole is up to 96% [59]. The effect is accounted for by the formation of a barrier layer that includes aminotrazole-copper systems and a copper oxide (I). For neutral chloride solutions, 3-amino-1,2,4-triazole is highly effective, with the Cu-40 Zn brass corrosion inhibition effect increasing in the presence of sulphides [60] or if the inhibitor is polymerized [61]. The inhibition effect of azoles derivatives can be improved by introducing additional heteroatoms, such as S, in the structure of the inhibitor. Taking into account that mercapto derivatives of azoles are biodegradable, they seem to be the most effective and environmentally friendly corrosion inhibitors for brasses. Their effectiveness against corrosion of copper in a neutral chloride environment was demonstrated in experiments with 2-mercaptoethanol\(\mathrm{\ddot{o}  
copper very effectively. The protective effect of 5-alkylmercapto-3-amino-1,2,4-triazoleoles in a neutral chloride-borate buffer solution is most probably accounted for by the adsorption of the inhibitor from the solution and the formation of a protective nano-layer of sparingly soluble complex compounds, both on copper [67] and on Cu-20 Zn brass [68]. The critical role of the complex formation in the passivation of Cu-20 Zn brass in solutions containing various aggressive anions and a 2-mercaptoethanoldiazole additive was proved in [69]. The purpose of the paper is to study the corrosion inhibition effect of 3-mercaptoethanolalkyl derivatives of 5-amino-1\(H\)-1,2,4-triazoleole on \(\alpha\)-brass in chloride environments using polarization curves, electrochemical impedance spectroscopy, full-scale corrosion testing, and quantum chemical simulation.
# Assisted Migration Field Tests in Canada and Mexico: Lessons, Limitations, and Challenges
## 5 Limitations  
### Canada. Pinus albicualis  
There are a number of limitations to implementing an operational assisted migration program for _Pinus albicualis_. First, the major immediate challenge to this species is the pathogen _Cronortium ribicola_, which causes white pine blister rust. Genetic variation in rust resistance exists within this species, and there are numerous efforts underway to select for disease resistance and generate resistant seed for restoration. If this species is to be migrated, it makes sense to do this with rust resistant material as the disease will likely follow the species north. Current resources are probably best allocated to testing for disease resistance rather than assisted migration.  
Secondly, _Pinus albicualis_ seeds are dispersed almost solely by the [PERSON]'s nutracker (_Nucifraga columbiana_), a corvid that tears the non-dehiscent cones open and disperses the seeds into soil caches. If _Pinus albicualis_ populations are established farther north, well outside of the native range of this bird species, will the birds follow? If not, then migrated tree populations will not likely naturalize.  
Finally, the assisted migration of this species is to a large extent an ethical issue and will require careful societal consideration of issues beyond biology. In BC, public support for assisted migration within species range is considerably higher than support for movements outside the current range [67]. In addition, opportunities to conserve this species and genetic diversity in climatic refugia within the existing species range should be acted upon [68]. [PERSON] and [PERSON] [69] analyzed the ethics of _Pinus albicualis_ assisted migration and concluded that, on balance, there appear to be good reasons to justify moving this species. _Pinus albicualis_ enthusiasts may welcome this practice to increase the survival of this charismatic species. However, local people including indigenous communities who relate to subalpine and alpine ecosystems in recipient areas as they are today may resist the introduction of non-local species into those ecosystems, and such societal concerns might apply to other species. In fact, one indigenous community expressed opposition to this experiment at the time of establishment for this reason.
## 3 System Identification for Position Model
### Model Estimation  
The quality of the frequencies used can have an impact on the outcome of parameter identification; richer frequencies provide better parameter identification. There are numerous methods for generating good input signals, including step, sinusoidal, multi-sine, pseudo-binary sequence (PRBS), and others. PRBS was chosen as the system's input signal because it can generate a random series of steps produced by the shift registers and clock. PRBS is a type of excitation signal that is widely used in system identification, but adjustments may be needed on a case-by-case basis [28]. PRBS can be created using linear-feedback shift registers (LSFR). These are made up of n flip-flops that perform an exclusive or (XOR) operation on their outputs [29]. The electro-pneumatic valve receives PRBS as an input signal, and the position of FBBA is recorded in terms of angle. A seven-bit PRBS generator block diagram was used to generate 127 random binary sequences that were fed into the electro-pneumatic regulator via an MCP4725 digital-to-analogue converter.  
The input voltage generated by the PRBS signal drove the opening of the electro-pneumatic regulator, causing the FBBA to bend. The flex sensor readings were registered into MATLAB using the Arduino's A0 pin. The 7-bit PRBS was set to take 25 s to complete, with a minimum interval of 0.16 s between each random pulse.  
The input-output data were split into two sections: data for estimation and data for validation. The final data collection found a total of 5001 input and output data points were collected (see Figure 4). The sampling time is also important in improving controller performance. As a result, a sampling time of 0.005 s was chosen for SI because more data can be recorded in a given time frame, influencing the model parameter estimation process [52,53]. Estimation data ranged from 0 to 2500 samples, while validation data ranged from 2501 to 5001.
## 1 Introduction  
In 1995, [PERSON] et al. pointed out that an ensemble of photons (under certain conditions) could be treated as in a Bose condensate and has a de Broglie wavelength given by \(\lambda/N\), where \(\lambda\) and \(N\) are the wavelength and average number of photons, respectively [1]. The wavelength of those photons is determined by the \"internal structure\" of them, i.e., the de Broglie wavelength of those photons, or if it has a de Broglie wavelength at all, it is determined by the situation of its internal binding. The photonic de Broglie wavelength of multiphoton states can be measured by using an interferometer with an \"effective beam splitter\" that does not split multiphoton states into different parts. Interestingly, the experimental measurements of the photonic de Broglie wavelength of biphotons was actually earlier than the theory. People measured the photonic de Broglie wavelength of biphotons in a series of experiments with SPDC (spontaneous parametric down conversion) light [2; 3; 4]. Later on, the de Broglie wavelength of biphotons was measured intently by using a similar [PERSON]'s interferometer setup and a basic Mach-Zehnder interferometer [5; 6]. The shorter wavelength of the photonic de Broglie wavelength (compared to the constituent photons of biphotons/multiphotons states) was proposed to be used in \"quantum lithography\", optical imaging with multiphoton states (NOON states for example) to beat the classical diffraction limit [7; 8]. In 2001, [PERSON] et al. demonstrated quantum lithography in a proof-of-principle experiment using degenerate SPDC light [9].  
The major advantage of quantum lithography is the resolution enhancement. With light (in the NOON state), the wavelength of which is \(\lambda\), the resolution of quantum lithography will be enhanced \(N\)-times, as if the light with wavelength \(\lambda/N\) were used for classical lithography. Previously, the multiphotons used in quantum lithography experiments were usually composed of photons with the same wavelength (except in [4] in which the non-degenerate biphotons were studied in a Mach-Zehnder interferometer). In this paper, non-degenerate quantum lithography is reported. We design a set of experiments to study the spatial interference and diffraction of non-degenerate biphotons. The biphotons are composed of \"two photons\" with different wavelengths, and the binding between the two photons is established through an SPDC process in a nonlinear crystal. Through experimental measurements, we find that the photonic de Broglie wave is well defined in spite of the wavelength difference between the daughter photons, and their de Broglie wavelength is neither the wavelength of the signal, nor the idler photon. We show that the wavelength of the non-degenerate biphoton is determined by the sum of the momenta of signal and idler photons due to the internal binding. The non-degenerate ghost interference/diffraction is also observed.
# Research on Variable-Step-Size Adaptive Filter Algorithm with a Momentum Term
## 3 Numerical Simulation and Verification
### Example Validation  
To verify the convergence of the proposed algorithm and the optimization effect of the above conclusions on the algorithm's learning capability, the M-VSNLMS algorithm with \(\alpha=0.9\), \(\beta=0.9\), \(\gamma=0.1\), and \(\theta=0.7\) is used to identify the parameters of a dynamic system model.  
\[y(k)+a_{1}y(k-1)+a_{2}y(k-2)=b_{1}u(k-1)+b_{2}u(k-2)+v(k)+d_{1}v(k-1)\]  
Among them, when the model parameters are \(a_{1}=-0.5\), \(a_{2}=-0.2\), \(b_{1}=1.0\), \(b_{2}=1.5\), \(d_{1}=-0.8\), \(v(k)\) is Gaussian white noise with a mean value of 0 and variance of 0.01. The input signal \(u(t)\) adopts the white noise sequence. In Figure 8, the predicted results of the model are shown.  
As shown in Table 3, the true values of the estimated parameters are compared with the estimated values.  
As shown in Table 3, the identification accuracy of system model parameters is above 97%, while the identification accuracy of noise is only 0.55%, indicating a good ability to suppress noise, demonstrating the excellent system identification performance of the M-VSNLMS algorithm. In addition, the algorithm has poor performance in terms of noise model identification, indicating its good noise suppression ability.