esa-sceva/satcom-chunk-collection huggingface dataset:
# Optimal Design and Hybrid Control for the Electro-Hydraulic Dual-Shaking Table System
## 4 Experimental Results
### Servo Valve Tests  
The servo valve experiment tests are performed to test performances of the developed servo valves. As is mentioned in Section 2.3, in order to obtain better consistency and performance of valves, the valve controller as the electric part of the valve is designed to realize the displacement close-loop control of the three-stage servo valve shown in Figure 3c and has several tunable parameters: the offset of pilot valve and main valve spool, displacement feedback gain, velocity feedback gain and feed-forward gain. During the tuning of valve tunable parameters, first the offsets of the pilot valve and main valve spool are tuned to reduce the offset of valves' output displacements under the static constant input signals; then, the displacement feedback gain and velocity feedback gain are tuned to obtain a better dynamic response performance under step input signals; at last, the feed-forward gain is tuned to further improve the dynamic performance of the servo valve. The step signal is given to servo valves simultaneously and the step response signals of the servo valves are compared. The parameters of valve controllers are tuned until the servo valves have approximately similar step response times and overshoots under the same step signal. For the frequency characteristic, 10% of full span random signals are given to servo valves before and after tuning the parameters of valve controllers, respectively. The magnitude frequency characteristics and phase frequency characteristics estimated are shown in Figure 14.  
From Figure 14, it can be seen that before tuning valve controllers, the performances of servo valves are different from each other and the minimum magnitude frequency width is less than 60 Hz, which can influence the control system precision significantly. After tuning valve controllers, the performances are approximately the same and the magnitude frequency width is more than 100 Hz, which indicates that the developed servo valves with parameter-tunable valve controllers can improve the servo valves' performances significantly. The experiment results for all servo valves in three directions are similar, so in Figure 14 only the four servo valves in \(X\) direction are listed for simplicity.
## 3 Results and Discussion
### Flexural Behaviors of Specimens with Carbon Grids  
#### 3.2.1 Load-Deflection Relationship  
In all specimens reinforced with the biaxial warp-knitted and cross-laminate structured carbon grids, cracks were initially observed at the center of each specimen. Furthermore, multiple cracks continuously developed toward the ends of the specimens, thereby significantly reducing the stiffness due to the transfer of tensile stress to the carbon grid (Figure 9). Subsequently, the maximum load was reached by mortar crushing in the mid-span of the specimen. Although the load in most specimens was reduced in stages after reaching the maximum load, specimens G2 and G3, which were reinforced with the biaxial warp-knitted structured carbon grids, exhibited a sharp load reduction.  
In the case of specimens reinforced with the biaxial warp-knitted structured carbon grids, specimen G2, with the highest tensile capacity, exhibited the largest crack formation and maximum loads (Table 6). The load of the specimens reinforced with the biaxial warp-knitted structured carbon grids decreased to approximately 11 to 14% of the maximum  
Figure 8: Damage observed in the carbon grids of specimens: (**a**) J5; (**b**) G1; (**c**) G3; and (**d**) G2.  
Figure 9: Relationship between the load and mid-span deflection for specimens reinforced with: (**a**) biaxial warp-knitted; and (**b**) cross-laminate structured carbon grids.  
load upon completion of the experiment owing to the fracture of the longitudinal strands and residual deformation of the carbon grid (Figure 9a).  
In the case of specimens reinforced with the cross-laminate structured carbon grids, the crack formation load did not significantly differ depending on the type of carbon grid. Furthermore, the maximum load did not increase in proportion to the tensile force by the longitudinal strands (Table 6). In addition, specimen J2 had a smaller longitudinal strand spacing (50 mm) than specimen J3 with the 100 mm spacing, and exhibited an increase in stiffness after crack formation and maximum load due to the increase in the number of strands (Figure 10).
# Nanoencapsulation of Essential Oils as Natural Food Antimicrobial Agents: An Overview
## 7 Applications of Nanoencapsulated Natural Antimicrobial Agents
### Aqueous Food Systems  
The two most common beverage systems are divided into carbohydrate-based products and dairy-based products. Carbohydrate-based products, such as juices and soft drinks, normally contain a certain amount of carbohydrates, but no or only a small amount of protein and lipids. A problem with the application of antimicrobial agents to carbohydrate-based products is the incorporation of hydrophobic compounds into the food system. Diary-based products such as milk generally contain large amounts of proteins and fats, so the interactions between antimicrobial agents and these complex food compounds and their stability during pasteurization can be a serious challenge for the food industry. Nanoencapsulation technology can be used to solve these problems. In this context, zein-encapsulated nisin and thymol oil showed better bacteriostatic effects than free antimicrobial agents after 4 h [154]. The use of nanoencapsulated thymol essential oil resulted in a prolonged effect on _Listeria monocytogenes_ within seven days of shelf life at 32 \({}^{\circ}\)C, making the number of bacteria lower than the detectable limit in skim milk [82]. In juices, both tea tree oil and cinnamaldehyde nanoemulsions showed concentration-dependent inhibition of microbial load on inoculation [117]. Juices containing minimal concentration of nanoencapsulated terpene showed retarding microbial growth (1.0 g/L of terpene) or complete inactivation of microbes (5.0 g/L of terpene), while minimizing sensory properties [117].
## 2 Materials and Methodology
### Extraction of Image Features  
Here, VGG16 was used as a feature extractor because of its simplicity, and its architecture is illustrated in Figure 3. To extract features, the source model was entirely copied excluding the last classification layer and the copied layers were frozen. Freezing the layers ensures forward propagation while disabling backpropagation during training. Note that, for investigation purposes in this study, VGG16 was considered due to its architectural simplicity. VGG16 has five convolutional blocks, where the first block has two convolution layers with 64 filters each, the second block has two convolution layers with 128 filters, and the third block has three convolution layers with 256 filters, while the fourth and fifth blocks have three convolution layers each with 512 filters. All filters in the convolution layers have same size (i.e., \(3\times 3\) size). The top layers are three FC layers where the first two (FC1 and FC2) have 4096 neurons, while FC3 has 1000 neurons. In order to enhance computational efficiency, VVG16 has a \(2\times 2\) max-poling layer after each convolution.  
Figure 3: Architectural illustration of VGG16 model.  
Figure 2: Methodology process.  
Given an input denoted as \(I_{0}\), this can be represented as tensor \(I_{0}\in\ R^{ABC}\), where \(A\) is the height of the image, \(B\) is the width of the image, and \(C\) represents the colour channels. The layers of the pretrained VGG16 can be expressed as series of functions \(F_{L}\ =\ f_{1}\to\ f_{2}\to\ f_{3}\to\ \ldots\ \to f_{n}\). Moreover, let us assume that \(Y_{1},Y_{2},Y_{3},\ \ldots,\ Y_{n}\) are respective outputs from each layer in the model, then the intermediate \(k\)-th layer's output can be computed from function \(f_{k}\) and learned weights \(w_{k}\) through \(X_{k}\ =\ f_{k}(X_{k-1}:w_{k})\).  
Note that each convolution layer learns different image features, whereby one layer may learn edges, another may learn horizontal lines or vertical lines, and the lower layers learn complex and generic features as the image propagates into deeper layers [15; 16; 17]. Therefore, in order to decide a specific layer to use for the extraction of features, we ensure the image passes through all feature extraction layers, which ensures that all relevant features learned by each layer were collected and ready for classification. As such, the decision now is between FC layers, although a study for facial recognition using deep learning features and support vector machines showed that the immediate FC layer after the last convolution layer yields strong discriminatory features [11]. Here, we tried to exploit discriminatory features from the first two FC layers of the VGG16 and compared different classification algorithms. Each classification algorithm was tried on both FC layers' features.
###### Abstract  
For improving the adaptability of a tracked vehicle equipped with a symmetrical suspension system on complex hilly terrain, based on the coupling method of multi-body dynamics (MBD) and discrete element method (DEM), an MBD-DEM coupling model was built and verified to explore its dynamic behaviors on soil. Firstly, according to the basic parameters of the tracked vehicle equipped with a symmetrical suspension system, a corresponding MBD model was built in Recurdyn V9R4 software. Based on the Euler-Lagrange method, the mathematical structure of the symmetrical suspension system was analyzed, and a corresponding mathematical simulation model was built in Matlab2016/Simulink to verify the MBD model. Secondly, based on the DEM theory and the parameter of the soil in a hilly area, a granular pavement model was built. Then, based on the coupling method of MBD and DEM, the corresponding MBD-DEM coupling model was built. Finally, using the MBD-DEM coupling model, the dynamic behaviors of the tracked vehicle equipped with a symmetrical suspension system under horizontal condition, the climbing condition and the obstacle crossing condition were obtained and discussed. The study results show that the proposed MBD-DEM coupling model could be used effectively to analyze the dynamic characteristics of the tracked vehicle. In addition, according to the analysis of the dynamic characteristics of the proposed tracked vehicle, the tracked vehicle equipped with a symmetrical suspension presents good adaptabilities under various working conditions.  
symmetrical suspension; MBD-DEM coupling; the Euler-Lagrange method; discrete element method; dynamic characteristics
# An Aerobic Degradation Model for Landfilled Municipal Solid Waste
## 2 **Stoichiometric Equations**
### Aerobic Hydrolysis of Organics  
The biodegradable organics in MSW mainly include sugars, celluloses, lignins, proteins, and fats. Celluloses, sugars, proteins, fats, and methane bacteria are used as limiting substrates to establish anaerobic biodegradation models [40; 41]. Here, with reference to their research methods, rapid degradation cellulose (abbreviated hereafter as RDC: C\({}_{6}\)H\({}_{10}\)O\({}_{5}\)), slow degradation cellulose (SDC: C\({}_{6}\)H\({}_{10}\)O\({}_{5}\)), total sugar (C\({}_{6}\)H\({}_{10}\)O\({}_{5}\)), fat (C\({}_{55}\)H\({}_{104}\)O\({}_{6}\)), protein (C\({}_{46}\)H\({}_{77}\)O\({}_{17}\)N\({}_{12}\)S), ammonia (NH\({}_{3}\)), and microorganisms (referring to aerobic bacteria, nitrifying bacteria, and denitrifying bacteria) were adjusted to be limiting substrates.  
The aerobic hydrolysis of organic matter refers to the redox reaction between organic matter and oxygen. Microorganisms that undergo aerobic hydrolysis can be represented by C\({}_{5}\)H\({}_{7}\)O\({}_{2}\)N [42; 43], a relationship that has since been widely used by scholars and which will be used here.  
Regarding the heat release, degraded glucose, fat, and protein release heat amounting to 16.73 kJ, 37.64 kJ, and 16.73 kJ per gram, respectively [44]. From this, the amount of heat generated per mole of organic matter can be determined, and the stoichiometric formulae are written as follows:  
RDC oxidation equation:  
\[\mathrm{C_{6}H_{10}O_{5}+4O_{2}+\frac{2}{5}NH_{3}=\frac{2}{5}C_{5}H_{7}O_{2}N+4 CO_{2}+\frac{21}{5}H_{2}O+\Delta Q_{1}} \tag{1}\]  
SDC oxidation reaction equation:  
\[\mathrm{C_{6}H_{10}O_{5}+4O_{2}+\frac{2}{5}NH_{3}=\frac{2}{5}C_{5}H_{7}O_{2}N+4 CO_{2}+\frac{21}{5}H_{2}O+\Delta Q_{2}} \tag{2}\]  
Total sugar oxidation reaction equation:  
\[\mathrm{C_{6}H_{10}O_{5}+4O_{2}+\frac{2}{5}NH_{3}=\frac{2}{5}C_{5}H_{7}O_{2}N+4 CO_{2}+\frac{21}{5}H_{2}O+\Delta Q_{3}} \tag{3}\]  
Fat oxidation reaction equation:  
\[\mathrm{C_{55}H_{104}O_{6}+58O_{2}+4 NH_{3}=4C_{5}H_{7}O_{2}N+35 CO_{2}+44H_{2}O+ \Delta Q_{4}} \tag{4}\]  
Protein oxidation reaction equation:  
\[\mathrm{C_{46}H_{77}O_{17}N_{12}S+34.25O_{2}=3C_{5}H_{7}O_{2}N+31 CO_{2}+9 NH_{3 }+H_{2}SO_{4}+13.5H_{2}O+\Delta Q_{5}} \tag{5}\]  
where \(\Delta Q\) represents the heat released by the biochemical reactions of various organic substances. The heat released by RDC, SDC, total sugar, fat, and protein were 2575.8 kJ/mol, 2575.8 kJ/mol, 2575.8 kJ/mol, 30,616 kJ/mol, and 20,698.8 kJ/mol, respectively.
## 3 Energy Trading in Local Energy Market  
In the recent energy trading literature of LEMs, three types of market platforms have been reported widely: P2P, community-operated (CO), and transactive energy (TE), which offer new mechanisms and models for energy trading locally. In P2P markets, direct dealing of energy trading between the market's participating players without any intermediary is executed to provide price incentives to the participants for engaging them in energy trade markets. In CO markets, co-located energy prosumers/consumers effectively trade their surplus/deficit energy within the defined community group. Grid services are the main target of TE markets to balance supply and demand in an autonomous way using price signals [85]. Although these LEM platforms lack consensus on their meaning, and there are differences between the market types, trading mechanisms, size variability, and operational scales, these can still be used interchangeably in some forms. The scope, modeling assumptions, objectives, and market mechanism were the major attributes studied in [86]. A P2P energy trading using a cooperative game theory with a priority-based approach in LEC was proposed in [87]. The prosumer participation mechanism and market flexibility framework in P2P energy trading was proposed in [88]. In [89], user preferences in a community-based LEM were defined using auction-based clearing approaches. In [90], community formation and multi-level energy trading networks were proposed in LEMs. A decentralized decision-making approach under uncertainty in a community-based energy market design was proposed in [91]. By adopting varying prices and competitiveness of LEMs, a path toward a fully TE system was proposed in [92]. A comprehensive review was presented in [93] to link the future of TE with LEMs. Table 3 illustrates the wealth of literature available for characterizing various market stakeholders, system components, and the primary and secondary purposes of P2P, CO, and TE market trading platforms when applied across different application domains. In P2P and CO markets, DSOs and prosumers are the major stakeholders. The DSO organizes the LEM and is responsible for distributing and managing the energy from different generation resources to market participants, whereas prosumers sell excess energy to consumers for financial reward and to balance system resources and needs. Energy cost and welfare maximization have proven to be the major purposes of these energy trading platforms. To analyze these trading platforms in more detail, different operational, financial, and constraint-based characteristics of P2P, CO, and TE in an LEM need to be explored further. The application areas and corresponding characteristics of P2P-, CO-, and TE-based LEMs, considering multiple factors, including network type, geographical aspects, market design, financial aspects, participation, network topology, and trading mechanisms, are summarized in Table 4. From Table 4, it can be concluded that P2P-, CO-, and TE-based energy trading platforms exhibit valuable cross-combinational characteristics. Unlike P2P
# RCA-PixelCNN: Residual Causal Attention PixelCNN for Pulsar Candidate Image Lossless Compression
## 3 The Proposed Methods
### Arithmetic Coding  
The most commonly used entropy coding algorithm employed in this paper is the arithmetic coding. When encoding each pixel in the image, it is necessary to know the probability distribution of the pixels. The image's pixel sequence is then transformed into a binary sequence. Based on the size of the probabilities, pixels are assigned different numbers of coding bits. The arithmetic coder assigns fewer bits to pixels with higher probabilities and more bits to pixels with lower probabilities. Another reason for choosing arithmetic coder is its progressive coding approach, which aligns well with our progressive probability model. Based on the pixels that have already been encoded, the model predicts the probabilities of pixels to be encoded next, resulting in higher compression efficiency. The decoding process follows a similar pattern. Initially, pixels that were encoded earlier are decoded, and then subsequent pixels are decoded conditionally one by one.
## 2 Basic Theory of Nonlinear Lamb Waves  
### Mode Selection of Lamb Wave  
Ultrasonic Lamb waves as one kind of guided waves propagating in a homogeneous and isotropic thin-plate structure [23]. When propagating in a plate structure, the ultrasound's frequency and wavenumber along the propagation direction need to satisfy the dispersion equation of Lamb waves [24]. Lamb waves propagation has dispersive and multi-mode aspects. The propagation velocity of Lamb waves is related not only to the elastic constant and material density, but also to the wave frequency and plate thickness. Figure 1 shows the dispersion curves for Lamb wave propagation in a 2-mm-thick aluminum plate.  
The basis of defect detection in a plate is choosing the appropriate mode of Lamb wave. For a plate of given thickness, there are at least two modes of Lamb wave at a particular frequency. In practical ultrasonic testing, different Lamb wave modes have different response behaviors to defects, and this attribute will directly affect the detection results. Figure 1 shows that only two kinds of Lamb waves, S\({}_{0}\) and A\({}_{0}\), can be excited in the frequency range less than the cutoff for the A1 mode. In this frequency range, the A\({}_{0}\) mode shows more serious dispersion characteristics than the S\({}_{0}\) mode. In addition, the group velocity of the S\({}_{0}\) mode is always greater than that of the A\({}_{0}\) mode, ensuring that it will be the first wave packet to reach the receiving destination. Moreover, it is suitable for detecting micro-scale damages or micro cracks buried in the interior of a large-scale structure [13]. Hence, an appropriate excitation method should be selected to generate a single S\({}_{0}\) mode.  
Figure 1: Lamb wave dispersion curves in an aluminum plate: (a) phase velocity; (b) group velocity.
# Plate Size Effects in Gravelly Soil Based on In Situ Plate Load Tests and Finite Element Analysis
###### Abstract  
The average contact stress-settlement behavior observed in plate load tests provides essential data for reliable foundation design. However, the test plate is often smaller than the actual foundation, requiring size extrapolation to interpret in situ plate load test results accurately. This study combines in situ plate load test results in gravelly soil with finite element analysis to evaluate test plates of varying sizes. The findings suggest that the coefficient of subgrade reaction for gravelly soil foundations can be effectively estimated using [PERSON]'s extrapolation method for the coefficient of subgrade reaction in clay. Although variations in test plate diameter may alter the shape of the average contact stress-settlement curve, the overall pattern of change remains consistent. The average contact stress-settlement relationship in gravelly soil can be represented by a three-phase linear model, corresponding to the elastic, yield, and failure stages. Additionally, while the elastic limit load in gravelly soil remains unaffected by plate size, the ultimate bearing capacity increases with larger plates before stabilizing.  
Keywords:plate load test; size effect; coefficient of subgrade reaction; gravelly soil Article
## 4 Fault Location Principle
### Single Line Positioning Formula  
At point F on the MN line, a single-phase ground fault occurs. The traveling wave ranging device at section M measures the modal time difference \(\Delta t_{\text{R}}\) between the line-mode and zero-mode waves, while \(\text{d}_{\text{c}}\) represents the distance from point F to section M. With \(t_{1}\) and \(t_{0}\) denoting the arrival times of line-mode and zero-mode traveling wave heads at the M section ranging device, respectively, Formulas (20) and (21) are known.  
\[\begin{cases}t_{\text{R1}}=\frac{d_{\text{c}}}{v_{1}}\\ t_{\text{R0}}=\frac{d_{\text{c}}}{v_{0}}\end{cases} \tag{20}\]  
\[\Delta t_{\text{R}}=t_{\text{R0}}-t_{\text{R1}}=\frac{(v_{1}-v_{0})}{v_{0}v_{1 }}d_{\text{c}} \tag{21}\]  
In a single cable line, the distance between the fault point and the ranging device is shown in Formula (22).  
\[d_{\text{c}}=\frac{v_{0}v_{1}}{v_{1}-v_{0}}\Delta t_{\text{R}} \tag{22}\]