esa-sceva/satcom-chunk-collection huggingface dataset:
# Detection of Geomagnetic Signals as Precursors to Some Earthquakes in China
## 3 Polarization Results and Earthquakes  
Geomagnetic data of three components (\(D/H/Z\)) were measured through a three-axis ring-core-type fluxgate magnetometer by 1s sampling rate from 2008 to 2017 in the JYG, GLM, and KSH stations. Data time series during each 30-min interval between 22:00:00 and 01:59:59 were then subjected to FFT analysis. The daily polarization energy was taken as the average spectral power over the entire period of each day, and the polarization ratios of \(Y_{ZH}\) and \(Y_{ZG}\) were then calculated. Earthquakes with the shortest epicentral distance from the observatories were selected as the seismic events and some potential earthquake precursor signatures were obtained from the ultralow-frequency (ULF) records. The Dst (disturbance storm time) index was used to describe the activity of geomagnetic field. Seismic events were selected as follows. First, selected earthquakes of magnitude greater than 5.0 in mainland China from 2008 to 2017. We then calculated the epicenter distance from each earthquake to each geomagnetic station, and finally screened out the earthquake events that have the shortest distance from KSH/JYG/GLM as analysis objects. The total number of selected earthquakes is 37, with 1 earthquake closest to JYG station, 7 earthquakes closest to GLM station, and 29 earthquakes closest to KSH station. However, only 5 out of 37 earthquakes were found to have probable signals of seismomagnetic anomalies before them. Table 1 lists the 37 earthquakes and corresponding information, and Figure 1 shows the distribution of observatories and the five earthquakes.
## 2 Materials and Methods
### SC Modeling and Alteration of SC Insertion Location  
The two SC were modeled by connecting the central region of the anterior leaflet (from the top portion of the rough zone to the medial portion of the atrial zone) and the papillary muscles [34]. The position of the SC is set as the ratio of the distance in the apical and lateral directions. Figure 2 presents the nine different SC insertion locations on the anterior leaflet. In the apical direction, the anterior leaflet centerline connecting the center point of the anterior annulus and anterior leaflet free margin served as reference for the position of the SC. With the center point of the free margin of the anterior leaflet set to  
Figure 1: Study protocol for virtual parametric MV modeling and computational simulation of MV function to determine the effect of altering the SC insertion location. A—anterior; Al—anterioral; P—posterior; Pm—posteromedial.  
zero, the center point of anterior annulus is set to one. The lateral location of the SC in the anterior view is set by the intercommissural line that connects the anterolateral (Al) and posteromedial (Pm) points. The half point of the intercommissural line located on the anterior leaflet centerline was set to zero, and the Al and Pm points were set to one.  
Several SC insertion locations were determined according to the ratio of the centerline of the anterior leaflet and half of the intercommissural line. All insertion locations of the SC were connected to the nearest node where the ratios were selected. The standard SC insertion location was set to the coordinates of 0.55 in the apical direction and 0.5 in the lateral direction. The displacement threshold for the SC insertion location (apical \(\pm\) 0.15, lateral \(\pm\) 0.2) along each anatomical direction was determined according to the normal range of the SC insertion location based on previous clinical studies [35]. A total of nine MV modes were created from combinations of apical and lateral displacements of the SC insertion location. They are named as top, center, and bottom according to the ratios (0.7, 0.55, and 0.4) in the apical direction and as narrow, middle, and wide at ratios of 0.3, 0.5, and 0.7 in the lateral direction. The SC lengths were determined according to the distance from the papillary muscle tips to the selected SC insertion nodes, with the shortest being 2.35 cm and the longest being 2.98 cm. The altered SC insertion locations were implemented to the MV models, and the corresponding MV function was computationally analyzed using our dynamic finite element analysis protocol [25; 26; 27; 31; 32].
# Gait Phase Estimation Based on User-Walker Interaction Force
## 3 Simulation
### Simulated Scenario 2  
When an elderly person uses a walker, the amplitude of the slower oscillation related to walking varies over time owing to their deteriorated abilities. Although this variation does not cause estimation failure, the accuracy can severely decrease. Moreover, the estimated gait phase may decrease instead of increase, leading to failure in gait-phase-based control. Therefore, we simulated a signal to verify the performance of the proposed adaptive rule under a sudden change in amplitude. The simulated signal \(S_{2}\) used for the simulation (Figure 4) is given by  
\[S_{2}(t)=\left\{\begin{array}{ccc}50\times\sin(2\times\pi\times t)-25&\text{ for}&20.5<t<21.5\\ 75\times\sin(2\times\pi\times t)&\text{for}&others\end{array}\right. \tag{12}\]  
Figure 4: Simulated signal with transient changing amplitude.  
Figure 3: Simulation results with different frequency combinations (**a**) \(\omega_{s1}=1\) Hz and \(\omega_{s2}=1\) Hz. (**b**) \(\omega_{s1}=1.2\) Hz and \(\omega_{s2}=1\) Hz. (**c**) \(\omega_{s1}=1.4\) Hz and \(\omega_{s2}=1\) Hz. (**d**) \(\omega_{s1}=1.6\) Hz and \(\omega_{s2}=1\) Hz. \(S_{1}\) is the simulated signal; the black solid line represents the signal with \(\omega_{s1}\) and the black dotted line represents the signal with \(\omega_{s2}\). \(\varphi_{s}\) is the phase of the simulated signal. \(\omega_{s}\) is the estimated frequency of the AO (Red) and the proposed method (Blue). \(e_{s}\) is the phase estimation error of the AO (Red) and the proposed method (Blue).  
Figure 5 shows the phase estimation results when the amplitude changed suddenly. The transient change in the input signal causes a large perturbation in phase estimation. Specifically, the phase estimation drops for approximately 0.5 s and increases again instead of monotonically increasing as expected. The behavior in the decreasing phase considerably degrades the estimation accuracy, possibly leading to the failure of gait-phase-based control. On the contrary, the estimation of the proposed method managed to mitigate the influence of the transient change by adaptively reducing the value of \(\sigma\) as shown in Figure 6. In practice, the amplitude of the input signal changes frequently, and its influence needs to be controlled.
## 3 Results  
### Analysis of Muscle Strength of Upper Body  
The effect size for each parameter was initially analyzed using the Eta Squared (\(\eta^{2}\)), which quantifies the proportion of variance attributable to the experimental effect. The statistical results for LGS, RGS, GRF time spent, GRF max, RFD, and duration of passage all showed effect sizes ranging from 0.378 to 0.831, indicating large effects. Among them, 'GRF time spent' had the largest effect size, with 83.1% of the variance, which can also be interpreted as an 83.1% reduction in experimental error [37]. Similarly, 'LGS' had 37.8% of the variance, representing the smallest effect size for the upper extremities, but still achieved a large effect size of over 0.14, as shown in Table 3.  
The analysis of upper-extremity strength in this study encompassed critical parameters such as hand grip strength, upper-extremity performance on the force plate, BPU metrics, RFD, GRF, time spent, and duration of passage. After 12 weeks of PSTP intervention, the experimental group's left-hand grip strength increased by 7.23% (an average of 3.1 kg), and the right-hand grip strength increased by 7.37% (an average of 3.2 kg), both showing significant improvement. In the post-test of upper-extremity operation BPU for the experimental group, the time of upper-extremity action on the force plate was reduced by an average of 0.82 s, the reaction force between the palm and the ground increased by an average of 663 newtons, and the duration of passage significantly increased by an average of 0.21 s. As for the control group, they did not demonstrate any significant improvements, as shown in Table 3. These findings substantiate the study's hypothesis that a 12-week PSTP can markedly enhance upper-extremity strength, particularly in the context of cl  
\begin{table}
\begin{tabular}{l c c c c c c} \hline \hline
**Parameters** & & **EG (\(n=30\))** & **CG (\(n=30\))** & **F-Value** & \(p\)**-Value** & \(\eta^{2}\) \\  & & **M \(\pm\) SD** & **M \(\pm\) SD** & **F-Value** & \(p\)**-Value** & \(\eta^{2}\) \\ \hline LGS (kg) & Pre & 42.9 \(\pm\) 1.7 & 43.2 \(\pm\) 1.3 & & & \\  & Post & 46.0 \(\pm\) 2.2 & 43.0 \(\pm\) 1.8 & 35.32 * & \textless{}0.01 & 0.378 \\ RGS (kg) & Pre & 43.4 \(\pm\) 1.5 & 43.4 \(\pm\) 1.1 & & & \\  & Post & 46.6 \(\pm\) 2.2 & 43.1 \(\pm\) 1.6 & 62.13 * & \textless{}0.01 & 0.517 \\ GRF time spent (s) & Pre & 1.04 \(\pm\) 0.11 & 1.05 \(\pm\) 0.11 & 285.28 * & \textless{}0.01 & 0.831 \\  & Post & 0.82 \(\pm\) 0.09 & 1.05 \(\pm\) 0.09 & & & \\ GRF max (N) & Pre & 617 \(\pm\) 61.8 & 621 \(\pm\) 73.5 & & & \\  & Post & 663 \(\pm\) 57.8 & 620 \(\pm\) 66.9 & 209.0 * & \textless{}0.01 & 0.783 \\ RFD (r) & Pre & 5210 \(\pm\) 492.8 & 5264 \(\pm\) 670.1 & & & \\  & Post & 5488 \(\pm\) 468.7 & 5268 \(\pm\) 665.2 & 142.1 * & \textless{}0.01 & 0.710 \\ Duration of passage (s) & Pre & 0.13 \(\pm\) 0.01 & 0.14 \(\pm\) 0.01 & 426.5 * & \textless{}0.01 & 0.880 \\  & Post & 0.21 \(\pm\) 0.02 & 0.13 \(\pm\) 0.01 & 426.5 * & \textless{}0.01 & 0.880 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Analysis of upper-extremity strength for climbing high walls.
# Analysis and Design of Protection Device for Anchor Cable Pull-Out in High-Stress Roadways
###### Abstract
[27] designed and developed an energy-absorbing damping anchor bolt that consisted of the bolt body, tray, constant-resistance energy absorption device, and specially shaped bolt nut; energy absorption and support could not only effectively guide and control the release and transformation of impact energy but also consume impact energy in the cushioning process of anchor bolts, ensuring the stability of surrounding rocks and the supporting protection system. [PERSON] et al. [28] performed shear tests on seven steel strand anchors (diameter: 15.2 mm) at angles of 0\({}^{\circ}\), 30\({}^{\circ}\), and 45\({}^{\circ}\), and believed that the stiffness of sheared anchors could be improved by increasing the shear angle. [PERSON] et al. [29] reported that anchors would experience pitting corrosion due to the long-term action of O, Cl, and S in the surrounding rock environment, reducing the outer diameter and bearing capacity of anchors and finally leading to their rupture. [PERSON] et al. [30] established the static and dynamic loading numerical model of double shear test in ABAQus/Explicit. Through static tests and dynamic tests, the effects of bolt diameter, steel yield strength and ultimate strength, dynamic load speed, and dynamic load mass on bolt displacement, shear force, and energy dissipation capacity were studied. The aforementioned studies focused on the influencing factors of the spiral structure and tensile-shear mechanical properties of anchors, in which the fracture and ejection formulas of the whole anchor with empirical constants have been deduced. Moreover, the mechanical properties of anchors have been verified to be improved by the C-shaped canal-anchor combination, NPR anchors, and spiral- and groove-type anchors. However, the dynamic evolution mechanisms of anchor wire breaking and ejection and the energy gathering and dissipation of protective devices have not been comprehensively studied. Considering the unpredictability of anchor incidents, this study is based on the approach of single-axis tension tests to infer cables' dynamics and evaluate protection device performance. Field tests in Zhangji Mine corroborated laboratory findings, offering valuable insights for understanding cable pull-out dynamics and protection device design.
## 4 Experimental Results
### Localization Initialization Step  
In the localization experiments conducted in two typical underground parking scenes, the starting points were consistently positioned near key parking berths, that is, within the coverage range of the map. This approach was implemented to ensure that the system initiated the localization initialization process right from the outset, expediting the entire localization procedure. During the experiments, the number of nodes used to calculate the global pose of the vehicle based on the initialization step was set at five. It should be  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Scene**} & \multirow{2}{*}{**Method**} & \multicolumn{2}{c}{**Memory Requirements (MB)**} \\ \cline{3-4}  & & **Strong Light** & **Weak Light** \\ \hline \multirow{2}{*}{Industrial park} & Ours & 4.4 & 2.2 \\  & Tao’s & 17.7 & 8.1 \\ \hline \multirow{2}{*}{Mall} & Ours & 22.3 & 9.6 \\  & Tao’s & 114.1 & 51.0 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Memory requirements comparison for the maps constructed by different methods.  
Figure 11: Distribution of map nodes. (**a**) Depicts the distribution of the map nodes in the industrial park’s underground parking scenes; **(b**) illustrates the distribution of the map nodes in the mall’s underground parking scene. The coordinates (41,517,770, 3,462,200) and (41,486,100, 3,455,580) correspond to the base coordinates of the map nodes in their respective underground parking scenes. For instance, if a map node of the industrial park’s underground parking scene is displayed at coordinate (30, 15) in the figure, the actual coordinates would be (41,517,770 + 30, 3,462,200 + 15).  
noted that if the starting point was positioned beyond the coverage range of the map, the holistic feature matching results between the localization nodes and the map nodes would serve as the triggering mechanism for the localization initialization step. Specifically, when a matching around-view image was detected from the map, it triggered the localization initialization step and completed the entire initialization procedure within the map block where the matched map node was located.
# Design, Implementation, and Analysis of a Block Cipher Based on a Secure Chaotic Generator
## 2 Proposed Chaos-Based Cryptosystem
### Diffusion Process and Its Inverse  
A permutation layer based on a modified 2-D cat map followed by a horizontal addition diffusion (HAD) and a vertical addition diffusion (VAD) is used to achieve the diffusion process of the proposed cryptosystem (VAD).
## 3 Mechanical Model of Overburden Rock Structure
### Top Coal Subsidence Model and Numerical Simulation
#### 3.2.1 Top Coal Subsidence Model  
The pressure exerted by the overlying main roof on the underlying coal body can be categorized into horizontal pressure and vertical pressure, and the influence differs based on the distinct locations of the MRFL above the roadway. When the fracture line is 1.5 m away from the coal pillar side, the top coal is almost equally affected by both the overhead horizontal and vertical pressures. When it is 2.5 m away, the top coal is primarily influenced by vertical pressure, with horizontal pressure having a lesser impact compared to vertical pressure, as shown in Figure 7.  
The stress analysis of the shear structure model of the top coal is carried out to explain the cause of the shear subsidence of the top coal, as shown in Figure 8.  
The shear strength \(\tau\) of the rock has the following relationship with compressive stress \(\sigma\):  
\[\tau=C+\sigma tan\varphi \tag{20}\]  
where \(tan\varphi\) represents the internal friction coefficient of rock shear and \(C\) represents the cohesive force of the rock. The data (\(\varphi\) = 24.5\({}^{\circ}\); \(C\) = 5.42 MPa) are derived from the triaxial compression test of rock samples in the study area.  
Figure 8: Top coal shear subsidence mechanical model.  
Figure 7: Top coal shear structure model.  
Equation (20) yields:  
\[\tau=5.96\ \mathrm{MPa}\]  
The top coal can withstand the maximum shear force \(T\):  
\[T=\tau\cdot A \tag{21}\]  
\[T=9.53\times 10^{4}\ \mathrm{kN}<9.97\times 10^{4}\ \mathrm{kN}\]  
The above calculation process is under the condition of unit width. Because the shear force \(Fy\) is greater than the maximum shear force \(T\) that the top coal can bear, the shear failure of the top coal occurs.
## 6 Publication Quality Assessment
### Publication Quality Assessment for Grey Literature  
The SADACO (Significance, Authority, Date, Accuracy, Coverage, and Objectivity) checklist is used to assess grey literature. The Fourth International Conference on Grey Literature, which took place in Washington, DC, in October 1999 [45], defined grey literature as \"that which is produced on all levels of government, academia, business, and industry in print and electronic formats, but which is not controlled by commercial publishers\". Grey literature encompasses a range of written materials, such as theses and dissertations, which are scrutinized by subject experts during review; conference papers, which are frequently peer-reviewed or presented by individuals with specialized knowledge; and diverse reports created by professionals working in the field. The SADACO approach proposes a mechanism for assessing the quality of grey literature. Other researchers have used a similar approach [34; 35; 36; 37; 38]. The SADACO checklist consists of 19 questions, each of which is assigned a score of 1. If the sum of the scores exceeds 50%, the source's quality will be considered acceptable; otherwise, it will be considered a failure. Figure 2 depicts the SADACO approach.  
Figure 1: Published literature quality assessment classification scheme.  
The detailed process is explained in the following Table 5.  
\begin{table}
\begin{tabular}{l l} \hline \hline
**Significance** & 1. Does it enrich or add something unique, meaningful/ informative to the research context? \\  & 2. Would the research area be lesser without it? \\  & 3. Is it integral and representative and influences the work/behaviour of others? \\ \hline
**Accuracy** & 4. Does the item have a clearly stated aim or brief? If so, is this met? \\  & 5. Does it have a stated methodology? If so, is it adhered to? \\  & 6. Has it been peer-reviewed? \\  & 7. Supported by authoritative, documented references or credible sources? \\  & 8. If the item is secondary material (e.g., a policy brief of a technical report), refer tothe original. \\ \hline
**Date** & 9. Does the item have a clearly stated date related to the content? \\  & 10. Check the bibliography: have key contemporary material been included? \\ \hline
**Authority** & 11. Associated with a reputable organization? \\  & 12. Professional qualifications or considerable experience? \\  & 13. Cited by others? (use Google Scholar as a quick check) \\  & 14. Higher degree student under “expert” supervision? \\  & 15. Is the organization reputable? (e.g., Microsoft Corporation, IBM, PSEB etc.) \\  & 16. Is the organization an authority in the field? \\ \hline
**Coverage** & 17. Are any limits clearly stated? \\ \hline
**Objectivity** & 18. It is important to identify bias, particularly if it is unstated or unacknowledged. \\  & 19. Opinion, expert or otherwise, is still opinion: is the author’s standpoint clear? \\  & 20. Does the work seem to be balanced in presentation? \\ \hline \hline \end{tabular}
\end{table}
Table 5: SADACO and relevant questions.  
Figure 2: Grey literature quality assessment process (SADACO).
## 4 Current Studies Focused on PPO Activity
### Influence on PPO Activity
#### 4.4.5 Microbial Growth and Decay  
Apart from the activity of endogenous quality degrading enzymes, spoilage microorganism reaction considerably shortens the shelf life of fruit and vegetable products, both whole and fresh-cut produce [75; 76]. Furthermore, microbial growth can be a matter of concern, with many studies considering microbial safety in minimally processed samples [77], as in the case of cantaloupe pieces [78].  
As included in some studies, the effect of enzymes and microbial growth on shelf life of minimally processed fruits and vegetables could be synergistic, as microorganisms can worsen cell integrity of tissues, provoking cell lysis, which is highly related to the increase in enzyme activity, as enzymes and substrates are easily put in contact, accelerating decay in fruits and vegetables (both whole and fresh-cut samples) [79]. On the other hand, microbial growth and enzymatic reactions can present a common starting point (i.e., cell lysis) to put some components included in cell content (such as sugar or phenols for microbial counts or PPO activity, respectively), and consequently these two adverse effects can act in parallel. As a consequence, if some techniques promote cell reinforcement are used (such as the application of calcium treatments), a combined decrease in microbial and PPO activity can be observed, as outlined below.  
This way, the effect of microbiological activity on some visual defects has been investigated in several papers that considered the relationship between psychrotrophic counts and visual decay [78]. As some authors have pointed out, the use of protective treatments seemed to be related to a direct decrease in browning, enzyme activity (such as PPO) and microbial growth [77; 80], as in the case of edible coatings applied to fresh-cut fruits and vegetables [81]. Specifically, the reduction of microbial population may result in PPO activity inhibition, on account of the fact that pectinolytic micro-organisms could break down cell walls resulting in stress-related exposure of enzymes and substrates, which also could lead to enzymatic browning. Hence, some barriers such as modified atmosphere packaging or washing treatments might contribute (besides their direct effects on browning inhibition) to reduce microbial population and therefore reduce PPO activity, improving visual quality [82; 83], as explained in many papers included in this review, although the decrease in microbial growth is not thoroughly covered in this work.