esa-sceva/satcom-chunk-collection huggingface dataset:
# Factors Affecting the Stability of Loess Landslides: A Review
###### Abstract
Changes in pore water pressure, particularly in terms of permeability, strain, and static liquefaction, caused by loess landslides are key factors contributing to the damage caused by loess landslides [13; 29; 30]. In the formation of landslides, the unique volumetric properties of the loess are critical [4]. General experiments often lead to multiple interpretations of the results, ignoring the complexity of the actual situation. Because of complex geological settings, using one geophysical survey may lead to less trustworthy results and interpretation errors [3; 31]. Target properties can be acquired by assuming certain conditions. However, these properties may only reflect certain characteristics. They cannot reflect all scenarios in a dynamic environment. All possible scenarios must therefore be considered. Currently, using a single method cannot provide comprehensive understanding of subsurface properties. For example, electrical resistivity tomography (ERT) can determine the type and composition of the landslide by analyzing resistivity anomalies. However, it cannot specifically reflect the mechanical properties of loess landslides [32]. Many studies have focused on the parameters that impact the stability of loess landslides. Some studies argue that direct testing of parameters under specific conditions does not adequately determine their impact. The need for further research is highlighted by the lack of definitive evidence. For example, an increase in resistivity cannot always be explained by a decrease in the water content of the soil matrix. Moreover, resistivity raised by cracking exceeds that only resulting from a decrease in soil water content [33]. This paper provides a systematic review on the studies of loess landslides from 1980 to 2023, with a specific focus on studies in China in the last 9 years. The stability of landslides is influenced by many parameters and factors, and some of them can be derived by geophysical methods, while others only be acquired by multidisciplinary and integrated approaches. This paper also provides a comprehensive overview of recent research on the monitoring and prevention of loess landslide hazards. Additionally, the paper highlights the significant challenges of data processing and improving equipment based on previous studies. It also presents visual representations of the data and findings through graphsand diagrams. This work can provide a foundation for future research and improve the methods and techniques for monitoring loess landslides.
# Effect of Whole Body Vibration Conditions on Lower Limb Muscles during Sling Exercise
## 1 Introduction
The sonic vibration method generates sound waves using a speaker mechanism, and generates vertical vibration on the vibration platform using sound wave fields. The advantage of this method is that the precise control of the frequency and amplitude is possible in units of 1 Hz and 1 mm using a sonic actuator [13]. Research on the effects of WBV on muscular function has been conducted over the last ten years. According to [PERSON] et al. [14], the peak torque of the external and internal rotations of the shoulder joint increase significantly during a vibration exercise at 30 Hz. [PERSON] et al. [15] reported an increase in the muscle activation as a result of conducting WBV at 26 Hz for 60 s. [PERSON] et al. [16] divided menopausal women into a WBV group, resistance exercise group, and control group. When examined for knee extensor strength, there was an improvement in the WBV group, but no significant difference in the other two groups. [PERSON] et al. [17] reported that during push-up plus exercises with a sling, compared to the exercise without vibration, that with a vibration at 0-90 Hz it increased the activation of the serratus anterior, with the highest increase at 50 Hz. As described here, research on the methods for improvement in the training effect has been actively underway. However, there have been few studies on the most effective vibration frequency for each muscle and the most appropriate exercise method combining unstable surface and WBV. Therefore, the change in muscular functions showing differences according to various vibration frequencies of WBV needs to be investigated. In this regard, this study aims to investigate the impact of vibration and an unstable environment, such as that with a swing, on the activation of lower limb muscles during the performance of a Bulgarian split squat (BSS).
# Estimating Hardness of Cosmetic Cream Using Electro-Mechanical Impedance Sensing Technique
###### Abstract  
This study investigates the application of electro-mechanical impedance (EMI) sensing technology to evaluate the hardness of cosmetic creams. Traditional methods, like penetration resistance testing, can be intrusive and disrupt continuous monitoring by impacting internal structures. To overcome this limitation, a piezoelectric sensor is embedded in cosmetic creams to capture EMI signals. This experiment explores varying wax content levels in the creams, establishing correlations between conventional hardness values and EMI signals. The results demonstrate a positive relationship between wax content, hardness values, and the magnitude of EMI resonance peaks. This study emphasizes a robust correlation between established hardness metrics and EMI signals, showcasing the potential of non-destructive testing to drive advancements in cosmetic industry practices.  
cosmetic cream; hardness; electro-mechanical impedance; piezoelectric 3
## 3 Results  
### InSAR Regional Deformation Rate Result and Landslide Hotspot Map  
The displacement rate map in the slope direction over the TGRA from Wanzhou County to Yunyang County is shown in Figure 4. Approximately 93% of the PSs show displacement rates within 10 mm/yr to \(-\)10 mm/yr, which indicates an overall stable environment of the study region.  
The output of PSI-HCA is shown in Figure 5a, all the remaining spots have displacement rates at a slope direction over 10 mm/yr. (\(>\)10 mm/yr. or \(<\)\(-\)10 mm/yr).  
In general, a total of 310 landslides in this region covered an area of 32.16 km\({}^{2}\). Engineering remedial works were already performed for 58 landslides. According to the first step (PSI-HCA), 52 out of 310 landslides remain in an active status, which accounts for nearly one sixth all landslides, and a total of 11 controlled landslides were diagnosed as suspected unstable landslides.  
Table 2 shows the results of our entire procedure. After combining the field investigation and ground monitoring data, two of the suspected active controlled landslides were confirmed to be active with some obvious deformation features that are continuously developing. The other nine showed different levels of surface deformation, but generally were not as strong as the former two landslides. Continuous attention should be kept on these nine suspected active landslides and periodic field investigations or even ground monitoring instruments are highly recommended depending on the trend of their development. The field investigation and engineering remedial work validation process are presented in following sections. For the 58 landslides under engineering remedial works in this area, 47 (81.0%) were inactive, which corresponds to 82.0% of the controlled landslides area.
# Microwave Planar Resonant Solutions for Glucose Concentration Sensing: A Systematic Review
###### Abstract
While sensitivity can be enhanced by active circuitry techniques [33; 34; 35; 36], selectivity seems only to be addressable by acquisition of redundant information by means of multi-sensor or multi-parameter measurements [37; 38; 39; 28; 31]. The advancements in machine-learning techniques cast growing optimism on these multi-parameter fusion approaches [40; 41; 42; 43], which could lead to considerable gains of selectivity and robustness [44; 45; 46; 38]. In this framework, looking at the literature, one can find up-to-date reviews of planar microwave sensors for general dielectric permittivity measurements [47; 48; 49], electromagnetic sensors for general biomedical [50; 51] or industry [52] applications, and multitechnology sensors for glucose sensing in both health and industry contexts [28; 29; 53; 54; 55; 56; 57; 58], but not a specialized review of planar microwave resonant glucose sensors. Considering the attention raised by this specific kind of sensor and the number of references available, the latter seems convenient. This manuscript offers a systematic review of the available approaches to glucose sensing, regardless of the application scenario, with the specific focus on planar resonant methods. A new classification scheme based on the sensing parameter, suitably adapted for this sensing paradigm, is proposed, and the review is thereby organized accordingly. To ease the understanding and comparison of the different approaches involved, the computation of a normalized relative sensitivity to glucose is proposed, which is especially convenient for discussion involving different sensing parameters. The manuscript is organized as follows. Section 2 outlines the fundamentals of this sensing technique and its development from the early stages to the current attempts. It also discusses the categorization possibilities and the finally proposed classification criterion, as well as the calculation of a general sensitivity. Sections 3-6 review the different available works within each category, whereas Sections 7 and 8 show the discussion of the current state of this technology and draw the main conclusions of the study.
# Study on Actuator Line Modeling of Two NREL 5-MW Wind Turbine Wakes
## 4 A Single NREL 5-MW Turbine Case
### Numerical Model  
The wind turbine is placed in a domain of 1890 m \(\times\) 1260 m \(\times\) 468 m. Details are shown in Figure 7, which shows that the mesh is refined by three steps in a rectangular region. The size of the cell outside the refinement zone is approximately 24 m; therefore, the inner zone mesh size is nearly 3 m. In addition, the regions behind the blade tip and root are important for ascertaining an accurate wake structure, so these parts are refined by the smaller mesh, which is indicated in Figure 8. In order to reduce the artificial reflections and oscillations, the refined ratio is set to 2 and three levels are adopted to avoid a large refinement ratio. Meshes are generated by blockMesh and snappyHexMesh in OpenFOAM. The wind turbine and the tower are set by topoSet.  
The wind flow is steady. The inflow and outflow boundary conditions of \(U\) are set by the fixedValue and inletOutlet, respectively, and zeroGradient and fixedValue are used correspondingly for the pressure \(p\). All others are defined as the slip boundary. The Reynolds-averaged Navier-Stokes (RANS) equations using the shear stress transport (SST) \(k-\omega\) turbulence model are considered in this model. The pressure-velocity coupling solver application uses the combined the Pressure-Implicit split-operator (PISO) and the semi-implicit Method for Pressure-Linked Equations (SIMPLE) algorithms, which be can be abbrtivated as PIMPLE. The number of times that the algorithm solves the pressure equation and momentum corrector in each step is 2. The solver for \(p\) is GAMG (Generalized geometric-Algebraic Multi-Grid) and for others is smoothSolver, which is a solver that uses a smoother. The numerical schemes are set as Euler for the time marching schemes, which is first-order implicit, with the Gauss liner for the gradient term, and Gauss linerUpwind for the divergence term. Besides, the time-step size is set corresponding to a blade rotation of 1 degree and the data is saved every five time steps. To obtain a relatively stable state, the simulation is calculated for 20 revolutions of the wind turbine. The Glauert model is chosen as the tip loss model.  
Figure 7: _Cont._
# PLI-VINS: Visual-Inertial SLAM Based on Point-Line Feature Fusion in Indoor Environment
## 3 Point Line Feature Processing  
For point features in indoor environments, the Shi-Tomasi algorithm is used to detect corner points in this paper, and then the KLT optical flow algorithm [28] is used to track and match feature points, and RANSAC-based pair geometric constraints [29] are used to identify internal and external points and eliminate outliers. For line features in indoor scenes, an adaptive threshold line segment extraction algorithm is proposed to process line features. Subsequently, LBD and KNN were used to describe and match the line features, and the existing line feature outliers were identified by matching the Hamming distance and angle of the line segment. Figure 2 shows the comparison between the traditional LSD and KLT optical flow and the proposed algorithm in the EuRoC datasets factory scenario.
## 2 Materials and Methods
### Description of Numerical Study
#### 2.2.2 Rectangular Shape Membrane Specim  
Despite the experience that the cross section of the impedance tube is almost always a circle, an additional study with a rectangular shaped membrane was performed. The reason was that in the realization of building structures one seldom encounters circular-shaped membranes. The change in shape should introduce additional resonant areas into the membrane response. For this purpose, a model of an impedance tube with dimensions in the cross section of 100 \(\times\) 125 mm with a membrane thickness of 0.5 mm (PTFE foil) was created. The tension, Young's modulus, Poison's ratio, structural loss factor and density of the PTFE was set similar to the case with one membrane. Again, six absorption properties of termination were simulated (\(\alpha_{1}\) = 1.0; \(\alpha_{2}\) = 0.9; \(\alpha_{3}\) = 0.7; \(\alpha_{4}\) = 0.5; \(\alpha_{5}\) = 0.2; \(\alpha_{6}\) = 0.1), to see the impact of the termination on the resulting \(nTL\), \(\tau\) and \(\alpha\), respectively. For this specimen case, only the ASTM, ISO and Mobility based methods were compared. The generated mesh resulted to 106,430 DOF with maximum size of mesh element \(\cong\) 0.049 m (Figure 3b). It should be mentioned that the upper frequency limit, or the cut-off frequency, is 1372 Hz for this case.
# Beyond Mitigation: New Metrics for Space Sustainability Assessment +
## 3 Proposed Approach Towards the Definition of a Space Sustainability Index
### Performance-Related Efficiency
#### 3.3.2 Data Rate Efficiency  
We define the efficiency \(e_{rate}\) as:  
\[e_{rate}=\begin{cases}ratio_{users}&\text{if }ratio_{users}\leq 1\\ 0&\text{if }ratio_{users}>1\end{cases} \tag{16}\]  
where the ratio \(r_{users}\) is defined as the number of subscribers \(N_{sub}\) divided by the number of serviceable users \(N_{users}\):  
\[ratio_{users}=\frac{N_{sub}}{N_{users}} \tag{17}\]  
The number of serviceable users \(N_{users}\) can be defined as:  
\[N_{users}=\frac{N_{sat}T_{sat}I_{add}\eta_{serv}\zeta_{div}}{B_{user}} \tag{18}\]  
where \(N_{sat}\) represents the number of satellites in a constellation and \(B_{user}\) is the bandwidth allocated to each user; \(\eta_{serv}\) is the service load, i.e., the amount of data that is being used or required by each satellite at a given time; \(\zeta_{div}\) is the overbooking factor which refers to oversubscription which is when a provider allocates more customers than can be served at the same time; \(\eta_{addr}\) is the addressability, i.e., the percentage of satellite capacity effectively utilized for serving customers and \(T_{sat}\) is the average throughput of each satellite and the maximum data rate per satellite, \(T_{max}\), assuming multiple beams and only the downlink path from space to earth.  
The Simpson distribution \(f_{u}(\epsilon_{u})\) is used to model the density of a user having a particular minimum elevation; it is defined between the minimum elevation of the User Terminal (UT), \(\epsilon_{UT}\), and the maximum elevation, \(\pi/2\), by:  
\[f_{u}(\epsilon_{u})=\frac{2(\epsilon_{u}-\epsilon_{UT})}{(\pi/2-\epsilon_{UT })^{2}} \tag{19}\]  
Therefore, \(T_{sat}\) will be calculated as the following integral:  
\[T_{sat}=\int_{\epsilon_{UT}}^{\pi/2}f_{u}(\epsilon_{u})T_{max}(\epsilon_{u}) \,d\epsilon_{u}\]
## 5 Discussion of the Results
### The Buckling Coefficient \(K_{u}\)
#### 5.3.2 Hole Position Varying Along \(y\)-Axis  
Figure 18 shows the change in \(K_{u}\) as hole position parameter \(e_{y}/b\) is enlarged from 0.5 to 0.9 with the BCs of 4S, for different \(d/b\) from 0 to 0.7, different plate aspect ratios \(\beta\) from 1 to 4, and different \(e_{x}/b=0.5\), 1.0, 1.5, and 2.0. The center of the hole is halfway between nodal cross lines when \(e_{x}/b=0.5\) and 1.5, and the center of the hole is at the nodal cross line when \(e_{x}/b=1\) and 2. It could be noticed that for a small hole \(d/b\) (e.g., \(d/b=0.1\) and 0.2), there are little effect of the hole location \(e_{y}/b\) on \(K_{u}\), and the effect becomes more pronounced as hole size \(d/b\) increases. When \(d/b\geq 0.2\) in Figure 18a\(\sim\)d, it can be seen that the curves are very similar irrespective of \(\beta\), that is: with the increasing of \(e_{y}/b\), \(K_{u}\) will decrease dramatically as \(e_{y}/b\) is enlarged, especially when \(d/b\geq 0.4\). Take \(\beta=3\), \(e_{x}/b=0.5\) and \(d/b=0.6\) for example, as \(e_{y}/b\) is enlarged from 0.5 to 0.65, \(K_{u}\) decreases from 3.28 to 2.20, this decline is very severe. The curves with \(e_{x}/b=1\) in Figure 18e\(\sim\)g are also very similar, and the law of changes are similar to curves with \(e_{x}/b=0.5\) (Figure 18a\(\sim\)d). What's different is that for curves in Figure 18e\(\sim\)g, when \(e_{y}/b\) is less than 0.575, \(K_{u}\) is bigger than 4 which is the \(K_{u}\) of plate without a hole. The law of changes in Figure 18h\(\sim\)j are between figures discussed above.  
Figure 19 shows the change in \(K_{u}\) as hole position parameter \(e_{y}/b\) is enlarged from 0.05 to 0.95 with the BCs of 3S1F, for different \(d/b\) from 0 to 0.7 and different plate aspect ratios \(\beta\) from 1 to 4. It can be seen that the \(K_{u}\) of plates with BCs of 3S1F is much less than those with BCs of 4S, especially when \(\beta\) is bigger than 1. The figure also shows that when the hole size \(d/b\) is smaller than a specific value (for \(\beta=1\): 0.1; \(\beta=2\): 0.1; \(\beta=3\): 0.3; \(\beta=4\): 0.4 ), there is a little effect of the hole position \(e_{y}/b\) on buckling coefficient \(K_{u}\) and the \(d/b\) effect becomes more pronounced as \(d/b\) increases.  
Over all, for a small hole size, there is little effect of the hole position \(e_{y}/b\) on buckling coefficient \(K_{u}\) regardless of the BCs (4S or 3S1F), and becomes more pronounced as \(d/b\) increases. The plate's stability improves as the hole places near the middle of the plate for 4S and the simple support edge for 3S1F in \(y\)-axis.  
Figure 17: \(K_{u}\) vs. \(e_{x}/b\) for perforated rectangular plate (\(\beta=1,2,3,4\)) with the BCs of 3S1F.  
Figure 18: _Cont._  
Figure 19: _Cont._
# Identification of Blackberry (_Rubus fritticosus_) Volatiles as _Drosophila suzukii_ Attractants
## Results
### The Attractivity of Individual R. fruiticosus Volatiles on D. suzukii  
All 33 commercially available volatile compounds were individually tested for their attractivity to female _D. suzukii_ using a two-choice bioassay at volumes corresponding to the estimated volume present in ten _R. fruiticosus_ berries (Table 1). These assays identify six significantly attractive compounds: acetaldehyde, hexyl acetate, camphene, linalool, myrtenol and _L_-limonene (Figure 4). The mean proportion of flies choosing the treatment over the control ranged from 67% to 69% for these volatiles and there was no significant  
Figure 3: Results from two-choice preference tests of different blackberry conditions. Barplots in blue show the attractivity (=the proportion of flies that chose the treatment vs. the control side) of the blackberry condition. Attractivity was tested against a 50:50 distribution, shown as a horizontal dotted line (binomial GLMM, _FDR_ corrected posthoc tests, mean \(\pm\) SE, **: \(p\) < 0.01, ***: \(p\) < 0.001). Barplots in red depict the choice factor (=the proportion of flies that made a choice (choosing either the treatment or control container) vs. those that made no choice (remaining in the middle container)).  
difference in the level of attractiveness among these six compounds. One compound, 2-heptanol, had a strong tendency towards a repellent effect, with 65% of the flies choosing the control side, although this repellent effect was strictly speaking marginally non-significant after _FDR_ correction (\(p\) = 0.051).  
Acetaldehyde, hexyl acetate, linalool and myrtenol had the highest choice factor with an average between 71% to 78% of flies making a choice. The average choice factor of 54% and 58% for camphene and \(L\)-limonene was significantly lower than that of the other four attractive compounds. Except in comparison to acetaldehyde, \(L\)-limonene did not have a significantly lower choice factor (\(p\) = 0.07). Beta-myrcene was the compound where the lowest percentage of flies made a choice (choice factor = 42%), while it was the highest for \(p\)-cymen-8-ol (choice factor = 89%) (Figure S1). However, for \(p\)-cymen-8-ol, this high choice factor was not paired with high attractiveness.