esa-sceva/satcom-chunk-collection huggingface dataset:
# Strength Characteristics and Slope Stability Analysis of Expansive Soil with Filled Fissures
## 2 Morphology and Filling Characteristics of Fissues in Expansive Soil
This was in the form of a film or lens, and the local thickness was more than 10 cm. [PERSON] [36] conducted engineering geological mapping and statistics of structural surface morphology on the channel slopes of the Nanyang section of the South-to-North Water Transfer Project, and found that the fissures had a certain direction, and the fissures were clear and smooth, with waxy luster and scratches, and were mostly filled with clay. At the foot of some landslides, long-large fissures were exposed along the slope with a slow dip angle. The dip angle was 7\({}^{\circ}\) to 17\({}^{\circ}\). The length were generally more than 20 m and the thickness was even more than 40 cm. [PERSON] [37] made statistics on the occurrence of fissures in Nanyang expansive soil, and found that the soil fissures were dominated by slow and medium dip angles, both of which accounted for 96.7% of the total fissures, while steep dip angle fissures were very few in number, accounting for only 3.3% (Table 1). At the same time, the inclination of the fissure had a correlation with its extension scale. The longer the extension of the fissure, the higher the proportion of the slow inclination fissure. Long-large fissures often extended more than 2 m in length, and the longest reached nearly 100 m. Many long-large fissures were rich in low-strength filled clay and formed weak structural planes. They often directionally penetrated the slope with a small inclination angle, which controlled the stability of the expansive soil slope. When this kind of filled fissure was developed in the slope and the tendency was the same as that of the slope, the impact on the slope stability was very significant. A large number of on-site landslide investigations showed that the expansive soil landslides were basically cut out along the fissures at the leading edge, forming the lower edge of the sliding surface. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Fissure Classification**} & \multicolumn{2}{c}{**Slow Dip Angle**} & \multicolumn{2}{c}{**Medium Dip Angle**} & \multicolumn{2}{c}{**Steep Dip Angle**} \\  & \multicolumn{2}{c}{**(\(\leq\) 30\({}^{\circ}\))**} & \multicolumn{2}{c}{**(30\({}^{\circ}\)–60\({}^{\circ}\))**} & \multicolumn{2}{c}{**(\(\leq\) 60\({}^{\circ}\))**} \\ \cline{2-7}  & **Count** & **Proportion** & **Count** & **Proportion** & **Count** & **Proportion** \\ \hline Long-large fissure & 917 & 66.7\% & 449 & 32.7\% & 8 & 0.6\% \\ Large fissure & 345 & 37.2\% & 528 & 56.8\% & 56 & 6.0\% \\ Small fissure & 15 & 14.0\% & 78 & 72.9\% & 14 & 13.1\% \\ Total & 1277 & 53.0\% & 1055 & 43.7\% & 78 & 3.3\% \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Statistical table of fissure dip angle of Nanyang expansive soil [37].
## 4 Proposed Scheme
### Selective Forwarding  
The second technique is called _selective forwarding_. The idea is that one can suppress unnecessary data transmission by exploiting the property of max function. Suppose at \(j\)th frame a sensor received a packet which needs to be forwarded to the parent of the sensor. Assume that the sensor has kept history of the maximum score among all the received data up to \((j-1)\)th frame. Suppose the score contained in the packet received at \(j\)th frame is less than the maximum score over all the packets which have been received and forwarded by the sensor prior to the \(j\)th frame. Since the sink needs to retrieve only the maximum score data, this packet will be eventually discarded at the sink. Rather than wasting resource to forward data to the sink, the sensor can silently drop the packet. This is called the selective forwarding. The max operation make such technique particularly simple, since it is easy to store the history of the maximum data.  
Let us denote the maximum among the scores which Node \(i\) has been successfully received for forwarding up to frame \(t\in\mathbb{Z}_{+}\) by \(z_{i}(t)\). We define \(z_{i}(0)=F_{X_{i}}(x_{i})\). Suppose at frame \(s\in\mathbb{Z}_{+}\), the node has received the data \(z\) requested for forwarding. In case where \(z_{i}(t)>z\), Node \(i\) will discard the data, and if \(z_{i}(t)\) already has been transmitted, the sensor will go idle: otherwise the sensor will proceed to transmit \(z_{i}(t)\). In case where \(z_{i}(t)\leq z\), Node \(i\) updates \(z_{i}(s)\) to \(z\), and this data will be queued for transmission. A flowchart in Figure 4 illustrates the above procedure of selective forwarding. Note \(z\) in the flow chart denotes the received data (score). Also note that a sensor may receive data while attempting to transmit, and the procedure shown in Figure 4 captures such aspect combined with the selective forwarding.  
Figure 5 illustrates an example of selective forwarding. There are four sensors with ID 1, 2, 3 and 4. The packet contains data with a format \((i,y_{i})\) where \(i\) is sensor ID and \(y_{i}\) is the score of the sensor. At frame \(k\), Sensor 3 transmits the packet with data \((3,0.9)\) to Sensor 1. At frame \(k+1\), Sensor 1 forwards the data \((3,0.9)\) to its parent, Sensor 4. At this frame Sensor 1 updates \(z_{1}(k)\) to the forwarded data 0.9, assuming \(z_{1}(k-1)<0.9\). At frame \(k+2\), Sensor 2 transmits data (2,0.7) to Sensor 1. However the score 0.7 is less than \(z_{1}(k)=0.9\), Sensor 1 silently drops the packet and remains idle at frame \(k+3\). In this specific example only 3 packets have been transmitted using selective forwarding instead of 4 packets. Suppressing unnecessary packet transmissions will help reducing the contentions in upstream traffic to the sink, which will likely to reduce latency. This is demonstrated later in Section 5.
# Integrating IP Mobility Management Protocols and MANET: A Survey
## 3 MANET Routing Protocols  
MANET is defined as a set of mobile devices that can communicate with each other using radio channels. It does not require an existing infrastructure to operate. MANET is a dynamic network where mobile devices can freely move, causing disruption and inconsistency in the network. Moreover, MANET is a self-configured network that does not require centralized components for its management. Mobile devices can organize themselves and cooperate with each other to guide network packets to their final destinations. A MANET node plays the role of both an end system and a routing router.  
There are several surveys of MANET routing in the literature. The most recent surveys concentrate on particular MANET aspects, such as power efficient routing [20], hybrid routing mechanisms [21], congestion awareness and adaptive routing [22], or ant colony-based routing [23]. A comprehensive and detailed survey was published by [PERSON] and [PERSON] [24], however, for the purpose of this  
Figure 5: Cellular IP Architecture.  
Figure 6: Handoff-Aware Wireless Access Internet Infrastructure (HAWAII) hierarchy based on domains.  
paper, the focus is only on the major classification of MANET routing. For a more detailed review, please refer to the above-mentioned papers.  
MANET routing can generally be classified into reactive and proactive routing; however, these can be further divided to include categories such as hybrid routing, hierarchical approaches, geographical systems, multi-path, multicast, and geocast categories [25]. Reactive and proactive routing, AODV and DSDV, respectively, are the most commonly used routing systems when integrating MANET with the internet. Therefore, the AODV and DSDV are introduced as representative for the reactive and proactive routing in the following subsections. Figure 7 shows the adopted taxonomy for MANET routing categories in this paper.
# Coreference Resolution for Improving Performance Measures of Classification Tasks
## 3 Methodology
### The Techniques Used to Create the Input Vectors
#### 3.3.1 Term Frequency-Inverse Document Frequency  
Nowadays, the classification of text documents is used in various areas of computer science. Algorithms dealing with this task usually need to represent the input text as a vector with a fixed size [27]. The simplest method for creating word vectors from documents is TF (term frequency) [28], which is calculated according to (1):  
\[tf_{i,j}=\frac{n_{i,j}}{dl_{j}} \tag{1}\]  
where:  
* \(n_{i,j}\) is the number of terms I in the document \(j\);
* \(dl_{j}\) is the number of all terms in the document.  
However, the above-mentioned method is not reliable, as the most important words will usually be words with frequent occurrences, e.g., pronouns, conjunctions, prepositions, particles, or articles, unless they have been removed as stop words. Simultaneously, a document also can contain words that describe the essence of the text much better, and those words may not be marked with the TF method.  
Therefore, the IDF (inverse document frequency) method is a method (2) where \(idf_{i,j}\) is determined by a logarithmic calculation. The method involves dividing the number of all documents N and the number of documents in which the word \(i\) occurs. Priority is given to words that are specific to a small subset of documents.  
\[idf_{i,j}=log\frac{N}{|(j:i\in j)|}\, \tag{2}\]  
If the word does not exist in the corpus, the denominator is adjusted to the form \(|(j:i\in j)|+1\), so the division by zero does not occur. Subsequently, the TF-IDF method, which is the improved product of the TF statistic and the IDF statistic, has the following form (3):  
\[TFIDF_{i,j}=tf_{i,j}\times idf_{i,j}, \tag{3}\]  
There are many formulas for calculating the TF-IDF, as there are also other parameters that can affect the vector itself [29]. More advanced keyword extraction methods include the KEA (keyphrase extraction algorithm) [30] or TextRank [31], in which the similarities of individual word subsequences are heuristically evaluated. Another popular algorithm is RAKE (rapid automatic keyword extraction) [32], the main advantage of which is that it can work with an article regardless of the corpus.
# Passive Power Line Communication Filter Design and Benchmarking Using Scattering Parameters
## 5 PLC Filter Design, Simulation, and Evaluation
### Proposed Filter Evaluation and Comparison to Other Commercially Available Filters
#### 5.3.2 PLC Filter Impedance Estimation  
Table 3 summarizes the PLC modem current consumption in transmit mode (sending frequency beacons in 35-95 kHz) while being connected in turns at the input and output of the filter. The filter impedance estimation method is shown in Figure 13d.  
The measured modem's power consumption is 0.42 A when transmitting over a resistive impedance of 1 \(\Omega\).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Filter Number**} & \multirow{2}{*}{**Rated** **Current [A]**} & \multirow{2}{*}{**Power Consumption** [W]**} & \multicolumn{2}{c}{**Insertion Loss [dB] at 50 kHz**} & \multirow{2}{*}{**Insertion Loss Gap for Blocking the PLC**} \\  & & & & **Datasheet Value** & & **Filter Energized with** \\  & & & & **2000 W Load** & & \\ \hline Proposed filter & 30 \({}^{*}\) & 0.597 & \(-\)130 \({}^{*}\) & \(-\)120 & 0 \\ \hline Filter 1 & 25 & 0.524 & \(-\)40 & \(-\)32 & 53 \\ \hline Filter 2 & 45 & 0.033 & \(-\)40 & \(-\)7 & 59 \\ \hline Filter 3 & 25 & 0.215 & \(-\)20 & \(-\)28 & 55 \\ \hline \hline \end{tabular} \({}^{*}\)Designed and simulated value.  
\end{table}
Table 2: Filter comparison based on measured and datasheet values.  
Figure 24: Filter 3 insertion loss measurement using PLC filter online insertion loss test setup version 2.
# Output Power Smoothing Control for a Wind Farm Based on the Allocation of Wind Turbines
## 3 Power Smoothing Control Strategy
### Control Strategy for the PWTs
The reference current was compared with the actual current and the difference is input to the current PI loop, as shown in Figure 6. Then the reference \(d\)-axis voltage \(U^{*}_{ds}\) and \(q\)-axis voltage \(U^{*}_{qs}\) were achieved from the current PI loops. The reference \(\alpha\)-axis voltage \(U^{*}_{as}\) and \(\beta\)-axis voltage \(U^{*}_{qs}\) in the two-phase static frame were obtained according to the inverse Park transformation. The space vector pulse width modulation (SVPWM) method [29] was adopted here to generate the PWM signal of the generator-side converter (\(S_{u}\), \(S_{b}\), \(S_{c}\)). The complete control diagram of the PWTs is presented in Figure 6.
###### Abstract  
Accurate characterization of subsurface geological structures, particularly those obscured by strong coal-seam reflections, is essential for hydrocarbon exploration in subtle reservoirs. Enhancing seismic resolution remains a pivotal technical challenge in addressing this demand. Here, we present a multitrace reflectivity inversion method guided by geological sparsity principles. This method establishes quantitative relationships between sparse inversion operators and the spatial positions of stratigraphic boundaries. Specifically, by integrating prior geological knowledge, such as stratigraphic boundaries and stable sedimentary structures, as constraint operators within the sparsity matrix, this method results in a geologically interpretable and robust inversion framework. Subsequently, we validated this method through synthetic data and field applications in a carbonate fracture-cavity reservoir in the Ordos Basin of western China. The enhanced seismic resolution demonstrates that our method effectively restores shielded reservoir reflections beneath coal seams. Clearer than conventional sparse inversion techniques, the coherence attribute of the enhanced seismic resolution reveals distinct fracture-cavity geometries. Moreover, integrated analyses of well logs, fracture-cavity characterization, and drilling production data further confirm the accuracy and reliability of the inversion results. In conclusion, this method effectively leverages accurate geological structural information to enhance localized seismic resolution, thereby providing robust support for the exploration of subtle hydrocarbon reservoirs.  
Keywords:multitrace reflectivity inversion; sparsity; geological-guided; high-resolution processing; coal-covered reservoirs +
Footnote †: journal: Applied sciences
## 2 Working Principle and Modeling  
### Working Principle  
The working principle of the proposed HFAM is shown in Figure 5. The HFAM is mainly composed of an RD, a CD, a sleeve, a liquid replenishment mechanism, and other connecting mechanisms. The amplification function is achieved using the area difference between the RD and the CD. The RDs [20] and the CDs [21] are diaphragms characterized by a significant linear deformation range and small elastic deformation influence. The RDs exhibit larger volume deformation than the CDs, with the same area. Consequently, the RD is installed at the small diameter end of the HFAM, and the CD is installed at the large diameter end of the HFAM.  
The sleeve chamber is filled with liquid, and the sleeve has holes at both ends, featuring a small diameter end of 16 mm and a large diameter end of 32 mm, resulting in a diaphragm area ratio of 1:4. Shaft 1 serves as the input end, connected to the VCM on the left end and linked to the RD on the right end. Shaft 2 serves as the output end, connected to the CD on the left end and attached to the load on the right end. A liquid replenishment device is incorporated to ensure timely replenishment of the liquid in the HFAM without disassembly. The upper end of the sleeve is matched with the head of the liquid replenishment shaft and sealed with O-rings to prevent leakage. The middle section of the liquid replenishment shaft is equipped with an external thread and is connected to the internal thread of the sleeve cover. A through-hole is opened in the middle of the liquid replenishment shaft to  
Figure 4: Structural diagram of the flexible piston hydraulic amplification mechanism.  
connect the sleeve chamber and the pressure measuring connector. The upper end of the pressure measuring connector is connected to the check valve. The mechanisms are used to expel the gas in the HFAM. Specifically, by pressing the check valve while rotating the liquid replenishment shaft clockwise. When there are no bubbles and only liquid flows out from the check valve, it indicates that the gas in the HFAM is completely expelled.
## 3 Evaluations at SPring-8 Angstrom Compact Free-Electron Laser (SACLA)
### Stability of the Focused Beam  
The stability of the focused beam was assessed in terms of size, position and profile, as shown in Figure 4. The shot-to-shot positional displacement of the focused pulses was less than the measured beam size because the profile measured using the knife-edge scanning method is an average of many pulses. As shown in Figure 4a-c, the beam sizes and profiles in both the vertical and horizontal directions were maintained for over 13.5 h after the alignment of the mirrors. Regarding the focus position in the same evaluation, the positional displacement observed was about 2.5 um and 0.4 um in the vertical and horizontal directions, respectively, as shown in Figure 4b,c. The evaluation results for the focal size, position and profile show sufficient stability for most of the XFEL experiments in which a sample is destroyed via ablation using an extremely intense single pulse.  
Figure 4: Measured stability of focused beam. (**a**) Time dependence of focused beam size. Root-mean-square deviation was 28 nm and 9 nm in the vertical and horizontal directions. (**b**) Focused beam profiles observed during stability evaluation, in the vertical direction and (**c**) horizontal direction.
## 4 System Model and Problem Formulation
### Problem Formulation  
For waste management in large-scale WSN scenarios, there are usually multiple data collection points (DCPs) scattered in different geographic areas. In this case, using a single data collector vehicle (DCV) for data collection from these locations is challenging and inefficient, since it will take a long time for the single DCV to traverse all DCPs, resulting in the incursion of delays and an energy-hole problem, creating operational bottlenecks in the network. In the context of waste management, this can create operational bottlenecks that can result in environmental hazards including air pollution, as most of the bins will have been overfilled before the deployment of waste collectors. Therefore, multiple DCVs will be required in such a situation to handle the scalability issues associated with a single DCV. However, employing multiple DCVs comes with additional challenges including costs and complexity of the network, thereby necessitating the need to create a balance between costs and delays by determining the optimal number of DCVs to stabilize network operations. One of the objectives of this study is to achieve this target to guarantee network stability and timeliness so that the data will not be useless. To this end, the DCVs are expected to follow the trajectory through optimal DCPs to minimize the data collection time and optimize energy consumption. We present the problem description in Figures 5 and 6, which show an optimal point selection and path planning and computation with a single DCV and with multiple DCVs, respectively.  
Figure 5: Optimal point selection and path computation with a single DCV.
# Stability Analysis of Lane-Keeping Assistance System for Trucks under Crosswind Conditions
## 2 Materials and Methods
### Simulation Model
#### 2.1.2 Road Model and Crosswind  
According to GB/T 41796-2022 [17], the test road is designed as a straight and curved composite road. In this study, the vehicle is driving straight in the first 4 s, then from 4 s to 20 s is the curved part, which is divided into fixed curvature and variable curvature. The curvature radius of the fixed curvature part is 500 m, the variable curvature part is the connection section of the straight and the fixed curvature part of the bend, and its curvature changes linearly with the length of the curve, gradually increasing from 0 to 0.002 m\({}^{-1}\) (the rate of change is less than 4 \(\times\) 10\({}^{-5}\) m\({}^{-2}\)). The test road is shown in Figure 2, where \(S_{0}\), \(S_{1}\), and \(S_{2}\) are the straight part, the variable curvature part, and the fixed curvature part, respectively, the road width, \(d\), is 10 m, and the road adhesion coefficient is 0.85.  
Since the step crosswind has simple mathematical properties and permits analysis of the vehicle's response to a linearized equation of motion [18], in this study, a step crosswind was selected for simulation. Figure 2 presents the direction of the crosswind, where the wind velocity was 40 km/h. In the simulation, from t = 0-4 s, the vehicle was on a straight road; from t = 4-6 s, the vehicle was subjected to a crosswind for 2 s, and from t = 6 s to the end, the crosswind was removed from the simulation. Throughout the entire process, the relevant parameters of vehicle lateral stability will be observed.  
Figure 1: Control strategy flowchart for simulation.
# Physicochemical Properties and Sensory Attributes of Yanggaeng Treated with Citrus Peel Powder
## 3 Results and Discussion
### Color Values of Yanggaeng  
Figure 1 shows the external feature and Table 6 displays the colorimetric values of CP-added Yanggaeng. The \(L^{*}\) values were 43.50 for CON, 32.90 for CP2, 28.13 for CP4, and 26.63 for CP6. The CON group exhibited higher \(L^{*}\) values than the groups with added CP. Moreover, there was a statistically significant reduction in \(L^{*}\) values as the concentration of CP increased (\(p<0.0001\)). Generally, the \(a^{*}\) and \(b^{*}\) values exhibited a noticeable dose-dependent increase after CP treatment. The \(a^{*}\) values in Yanggaeng samples were \(-0.80\) for CON, 4.87 for CP2, 7.97 for CP4, and 9.00 for CP6. The CON group showed the lowest \(a^{*}\) value, whereas the CP group displayed the highest \(a^{*}\) value, with significant differences observed between the Yanggaeng groups (\(p<0.0001\)). Regarding the \(b^{*}\) values, they were 3.23 for CON, 19.97 for CP2, 20.03 for CP4, and 20.57 for CP6. The CON group exhibited the lowest \(b^{*}\) value, whilst CP6 showed the highest \(b^{*}\) value, indicating significant differences among the Yanggaeng groups (\(p<0.0001\)). Consistent with these observations, [PERSON] et al. noted that adding peel powder from citrus mandarin to pan bread resulted in reduced \(a^{*}\) and \(b^{*}\) values compared to the control group [14]. The presence and concentration of carotenoid pigments in food can affect its overall color and lightness. Foods such as carrots [37; 38] and sweet potatoes [39], which have high concentrations of carotenoids, tend to have brighter and more vibrant colors [40]. Accordingly, treatment with CP influenced the colorimetric properties, and this effect was likely attributable to the carotenoid pigments found in citrus fruits.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & \multicolumn{4}{c}{**Treatments (\%)**} \\ \cline{2-5}  & **CON1**  & **CP2** & **CP4** & **CP6** \\ \hline DPPH free radical scavenging rate (Inhibition \%) & 20.01 \(\pm\) 7.32 b  & 25.49 \(\pm\) 5.42 ab  & 26.90 \(\pm\) 4.99 ab  & 33.17 \(\pm\) 5.96 a  \\ \cline{2-5}  & 18.70 \(\pm\) 1.15 d  & 24.05 \(\pm\) 0.17 c  & 27.02 \(\pm\) 0.30 b  & 30.54 \(\pm\) 0.44 a  \\ \cline{2-5}  & 3.75 \(\pm\) 0.75 d  & 29.13 \(\pm\) 1.94 c  & 84.50 \(\pm\) 1.06 a  \\ \hline \hline \end{tabular}
\end{table}
Table 4: Antioxidative activity of Yanggaeng made with citrus peel powder.