esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Due to the low accuracy and precision of some FS detection methods, hypotheses H1 (RFS pattern) and H2 (FFS pattern) have to be rejected. When applying the current study's results to the electromyographical investigations in the literature, EMG peaks relative to FS of 6.8 \(\pm\) 2.8 ms for the rectus femoris, and 9.5 \(\pm\) 4.7 ms for the tibialis anterior muscles were found [4]. Based on the current study's results, it can be stated that M3 is the only method which can be used to define these EMG peaks accurately relative to FS. When using the other methods (M1, M2, or M4) to detect FS, the relative moment of EMG peaks will not be detected accurately, which can result in errors when comparing different conditions (e.g., footwear conditions). Furthermore, considering muscle activity within a defined time range relative to FS, incorrect FS detection can result in misinterpreted muscle activity relative to the gait cycle: too early--no activity during swing phase; or too late--muscle activity during mid-stance. A limitation of the current study is that only subjects' individual running velocity was investigated. Further studies should also examine whether slower and faster velocities influence accuracy and precision of the FS detection algorithms. In conclusion, these results are important when investigating running parameters which are dependent on an exact detection of FS. Individual accuracy and precision of FS detection methods were found, which are dependent on running styles and footwear conditions. Therefore, it can be concludedthat M3 can be used to determine FS in a variety of conditions, accurately (e.g., to compare the influence of footwear conditions on muscle activity, foot strike angle and stride duration in prolonged field runs). When investigating running parameters which are related to FS detection algorithms M1, M2, and M4, the results should be considered carefully. The authors would like to thank [PERSON] for proofreading the paper as a native speaker. This research was supported by Puma(r) Inc., Germany. The publication costs of this article were funded by the German Research Foundation/DFG and the Technische Universitat Chemnitz, Chemnitz, Germany, through the funding program Open Access Publishing. [PERSON] and [PERSON] conceived and designed the experiments; [PERSON] performed the experiments; [PERSON], [PERSON] and [PERSON] analyzed the data; [PERSON] contributed reagents/materials/analysis tools; [PERSON], [PERSON] and [PERSON] wrote the paper. The authors declare no conflicts of interest.
_Applied_  
_sciences_  
_Article_  
**Dynamic Core Flexion Strength is Important for**  
**Using Arm-Swing to Improve Countermovement**  
**Jump Height**  
**[PERSON] 1, [PERSON] 2 and [PERSON] 3,*()**  
1 School of Physical Education and Sports Science, South China Normal University, Guangzhou 510631, China; [EMAIL_ADDRESS]  
2 School of Physical Education and Training, Shanghai University of Sport, Shanghai 200438, China; [EMAIL_ADDRESS]  
3 Department of Health Science and Kinesiology, Georgia Southern University, Statesboro, GA 30460, USA  
* Correspondence: [EMAIL_ADDRESS]; Tel.: +1-912-478-0200 check for updates  
Received: 28 September 2020; Accepted: 23 October 2020; Published: 30 October 2020  
**Featured Application: Our results showed that the structure of kinematic and kinetic core training is essential to improve CMJ performance and dynamic core flexion strength played a more critical role in improving CMJ with arm-swing. For all movements where arm-swing is used to increase jump height, athletes can benefit from enhanced dynamic core flexion strength. The specific characteristic of the core could be the key to understand how arm-swing helps improve jump height. In addition to the broad spectrum of core strength and stability training, coaches and athletes should pay special attention to the dynamic core flexion strength during training if using arm-swing to increase jump height is important.**  
**Abstract: Background: Specificity of core strength training to sports events is crucial for performance improvement. The purpose of this study was to examine the specific relationship between core strength and countermovement jump (CMJ) performance. Methods: Twenty active college students (7 male, 13 female) participated in the project. CMJ heights with (H\({}_{\text{AS}}\)) and without arm-swing (H\({}_{\text{NAS}}\)) were estimated from vertical ground reaction force data collected using a force platform. Twelve dynamic and static core strength measurements of flexion and extension were tested using a dynamometer. The shared variance between CMJ height and core strength measurements was estimated using the square of Pearson correlation coefficients (R\({}^{2}\)). Linear regression analyses were conducted to determine which independent variables in core strength measurements were major predictors of CMJ height. Results: Significant correlations (\(p<0.05\)) were observed between all 12 core strength measurements and CMJ height with/without arm-swing. Normalized (normalized with individuals' body mass) peak torque during dynamic flexion at 180\({}^{\circ}\)per second (NPDF\({}_{180}\)) and normalized peak torque during static flexion at 120\({}^{\circ}\) (NPSF\({}_{120}\)) shared 72.0% variance with H\({}_{\text{AS}}\), and NPSF\({}_{120}\) shared 57.0% variance with H\({}_{\text{NAS}}\). Conclusion: Dynamic core flexion strength is vital for using arm-swing to improve CMJ height. The structure of kinematic and kinetic core training could be considered to improve CMJ performance for coaches as well as professional and recreational athletes.  
**Keywords:** core strength; arm-swing; countermovement jump; dynamic; static
# Digital Shearography for NDT: Phase Measurement Technique and Recent Developments
## 3 Phase Measurement Technique
### Phase Measurement Technique: Spatial Phase-Shift Shearography  
Temporal phase-shift shearography is generally only applicable to static measurements. Despite the fast temporal phase-shift algorithms that have been developed, the phase map quality and measurement range are limited and not suitable for many applications. Therefore, spatial phase-shift digital shearography (SPS-DS), in which phase-shift interferograms are obtained in different spatial positions at the same time to realize dynamic shearography measurements, was proposed. This section will describe spatial phase-shift shearography by introducing multichannel spatial phase-shift shearography and carrier-frequency spatial phase-shift shearography, respectively.
## 4 Experimental Results
### Maps Construction  
This paper constructed the maps based on the first loop of data collected from each underground parking scene. As shown in Figure 8, there were a total of six key berths in the industrial park's underground parking scene, and as shown in Figure 8, there were a total of 13 key berths in the mall's underground parking scene. Near each key berth, a certain number of nodes were selected to construct a map block. The selection of nodes followed two principles: firstly, the selected nodes' around-view images should include the two outer corner points of the key berths; secondly, to avoid excessive density, there should be a certain distance between the adjacent nodes. It was performed to improve the efficiency of the map matching and ensure the real-time performance of the entire localization system. Based on the above criteria, the map constructed in the industrial park's underground parking scene consisted of six blocks with 78 nodes. In the mall's underground parking scene, the map consisted of 12 blocks with 277 nodes. The Euclidean distance between the adjacent nodes was approximately 0.5 m. Figure 11 illustrates the distribution of the map nodes in different underground parking scenes. It is worth noting that this paper constructed two maps for each underground parking scene based on the corresponding light intensities due to the variations in the lighting conditions.  
Figure 10: Contrast of lighting intensity. The left image represents the original image with sufficient lighting. The right image, subjected to linear pixel value scaling, has had the lighting intensity reduced to 50% of the original image. The green circles in the images denote the extracted local features.  
Table 2 provides a comparison of the memory requirements for the maps constructed by the proposed method and [PERSON]'s method [32]. The proposed method reduced map memory usage by over 75% compared with [PERSON]'s method. This was because the proposed method constructed maps based on the key berths and selected a reasonable number of data nodes, resulting in a more lightweight map. In contrast, [PERSON]'s method built maps based on all the data nodes, leading to redundancy and significantly increased memory requirements for the system. Additionally, in low-light conditions, the memory usage for the maps constructed was reduced by over 50% compared with well-lit conditions. This was because the number of local features was directly proportional to the lighting conditions. As shown in Figure 10, when the lighting was strong, the number of extracted local features was significantly higher, increasing the maps' memory requirements.
## 5 Conclusions  
Although the research on SAR remote sensing mapping of rice paddies has lasted for more than 20 years, the development of operational automatic and rapid rice identification methods combined with high spatial resolution and long time-series SAR data, is still the hotspot and frontier in current rice mapping research. Therefore, this research proposes an automatic method to identify the regional rice paddies using the long time-series Sentinel-1 SAR images. By integrating 402 Sentinel-1 scenes, auxiliary data of permanent water bodies, and data on the general phenological characteristics of rice with the Google Earth Engine geospatial data cloud computing platform, the proposed method can rapidly identify the extent of rice paddies without needing local expert experience or field sample plots.  
Comparison with the field plot data, it is concluded that our proposed approach is feasible for mapping rice paddy extent at a fine resolution of 10 m, and can effectively obtain a high accuracy with the OA of 89.52%. Through a comparison of the rice products from IRRI, our rice extraction resultshave a finer resolution, and the spatiotemporal pattern of rice paddies was consistent in the Mun River basin.  
This study has contributed to rice identification approaches and regional rice mapping using time-series Sentinel-1 SAR dataset. The method developed in this study is timely, effective, and highly accurate, while the rice results obtained had a high resolution of 10 m. This approach can be expanded to other rice-cultivation countries, or even the entire Indochina Peninsula and Southeast Asia.  
The relevant codes for rice extraction are available online at [[http://www.mdpi.com/2072-4292/12/23/3959/s1](http://www.mdpi.com/2072-4292/12/23/3959/s1)]([http://www.mdpi.com/2072-4292/12/23/3959/s1](http://www.mdpi.com/2072-4292/12/23/3959/s1)), all the algorithm codes were written with JavaScript in the Google Earth Engine online Code Editor.  
[PERSON], [PERSON], and [PERSON] conceived the research and designed the experiments; [PERSON] performed the experiments; [PERSON] drafted the manuscript. [PERSON], [PERSON], [PERSON], and [PERSON] provided help with the language and reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number 41801353; the Strategic Priority Research Program of the Chinese Academy of Sciences, grant number XDA19060302, XDA19060304, and XDA23050101; the Science and Technology Basic Resources Investigation Program of China, grant number 2017 FY201401; and the National Key Research and Development Program of China, grant number 2017 YFD0300403.  
We thank [PERSON] in our laboratory for his comments on the manuscript.  
The authors declare no conflict of interest.
## 2 Instrument Design
### Antenna  
The Pickett-horn antenna design shown in Figure 4 was selected for the ELBARA II system. This design has some modifications compared with the original Pickett-horn [30]: First, the diameter of the cylindrical waveguide of the antenna feed (the rear part) is smaller, and second, a taper acting as an additional phasing section has been introduced between this waveguide and the step transition. One characteristic of the original and the modified design is the highly directive far-field pattern with an expected -3 dB beam width of 12 (\(\pm 6\)  around the antenna main direction). The antenna also provides horizontal and vertical polarization with symmetrical and identical beams with small side lobes.  
The antenna feed, consisting of the cylindrical waveguide and the taper, is fabricated by turning from two heavy-walled aluminum tubes, resulting in an accuracy better than \(\pm 10\). The waveguide of the antenna feed comprises the two receiving \(\lambda\)/4-structures to receive the horizontally (H) and vertically (V) polarized radiance. To achieve a good isolation between the two orthogonal polarization directions (better than 40 dB; see Section 3.2.1.), 6 rods parallel to the horizontal polarization (pol. filter) are mounted in between. Each of the receiving \(\lambda\)/4-structures is made of a brass rod 5.25 mm in length, clamped to the interior-conductor of the N-connectors mounted in the waveguide. The lengths of the \(\lambda\)/4-structures are fine-tuned to minimize the return losses to achieve values smaller than -20 dB (see Section 3.2.1.).  
The large antenna horn (the front part) screwed to the feed is produced from three rolled 3 mm aluminum sheets (PE100, semi-hard). The three cones 670 mm, 932 mm, and 670 mm in lengths are welded together and rigid aluminum rings (hatched) around the corresponding welding junctions and the aperture opening of the horn are attached. This measure increases the mechanical stability of the horn, as well as its rotational symmetry, which is of the order of \(\pm 1\) mm. The two rings mounted at the joints are also used to attach the horn to the structure holding the antenna (see Figure 1 and  
Figure 4: Sketch of the modified Pickett-horn antenna design. The dimensions relevant for the wave characteristics of the antenna are in units of millimeters.  
Section 2.4). The ring at the antenna aperture can be used to mount auxiliary sensors, such as an infra-red radiometer or an optical camera, to observe the scene from the same observation angle as ELBARA II.
# Simplified Derivative-Based Carrierless PPM Using VCO and Monostable Multivibrator
## 4 Performance Analysis
### PLL Error Analysis  
Under the scenario where the phase detector is digital (RS flip-flop), the PPM input signal passing through the channel is first sent to a comparator. Consequently, the power of the time-domain noise signal is equivalent to that in integrator demodulation. When considering the transfer function at the point where the output is the derivative of the information signal, after the LPF component of the PLL, the transfer function becomes a BPF, as expressed by Equation (39).  
\[H(S)=\frac{S\omega_{L}k_{b}\phi_{i}(S)}{S^{2}V_{o}(S)+S\omega_{L}V_{o}(S)+B \omega_{L}k_{b}V_{o}(S)} \tag{39}\]  
If the bandwidth of this BPF is set to \(B_{PF}\), the noise power at the output of the LPF can be determined by transforming the time-domain noise into angle-domain noise, resulting in the following expression in Equation (40). When substituting the time-domain and angle-domain relationships into Equation (40), the PDF of AWGN in forms of the angle-domain noise is obtained in Equation (41).  
\[\Delta\theta=2\pi\Delta t/T \tag{40}\]  
\[f(\Delta\theta)=\left(1/\sqrt{2\pi\sigma_{n}^{2}}\right)e^{-\left(s\Delta \theta T\right)^{2}/2\sigma_{n}^{2}\left(2\pi\right)^{2}} \tag{41}\]  
For simplicity, \(N_{o}\) replaces \(2\sigma_{n}^{2}\). In the same manner as the previous calculation of noise power, the phase noise power is given by \(N_{\theta}=N_{o}\left(2\pi\right)^{2}/\left(ST\right)^{2}\). After passing through the BPF with the bandwidth \(B_{PF}\), the noise power output, \(N_{BP}\), is attenuated and is expressed by Equation (42).  
\[N_{BP}=\frac{N_{o}(2\pi)^{2}}{S^{2}T^{2}}|H(S)|^{2}=\frac{N_{o}(2\pi)^{2}}{S^ {2}T^{2}}B_{PF} \tag{42}\]  
By using the same information signal mentioned previously, the signal-to-noise ratio in terms of power is given by Equation (43).  
\[\frac{S_{m}}{N_{BP}}=\left(k_{p}^{2}\overline{m^{2}(t)}\right)/\left(\frac{N_ {o}(2\pi)^{2}}{S^{2}T^{2}}B_{PF}\right)=\frac{k_{p}^{2}S^{2}T^{2}}{\left(2\pi \right)^{2}}\frac{\overline{m^{2}(t)}}{N_{o}B_{PF}} \tag{43}\]
## 3 Results
### Spatial Variability in 'Dry' and 'Wet' Conditions
#### 3.2.1 SMAI and LST During Dry Conditions  
In the 'dry' category, two years with different distribution of precipitation deficits from March to August are considered as examples, namely, 2007 and 2012.  
Year 2007 is characterized by deficient precipitation from April up to the beginning of August (NIMH Hydrometeorological Bulletin, 2007). In April, the monthly sum is below the norm for the whole country. In May, for eastern Bulgaria precipitation vary from 35% to 65 % of the monthly norm, while in the rest parts of Bulgaria, values are around the norm. In June, for the most part, precipitation is below the monthly norm, 13-73%. In July, precipitation everywhere is below the monthly norm. Precipitation deficit is a marker, but not a sufficient condition, to constitute the existence of terrestrial drought. Based on the 'SVAT_bg' model, having inputs from meteorological data at synoptic stations, mean monthly values of soil moisture availability at different depths along the root zone are calculated.  
SMAI for 50 cm soil depth (Figure 4a-c) for June, July, August and the corresponding LST spatial distribution for the same period of 2007 (Figure 4d-f) are compared. Visualized maps are used to show the dynamics and variability of moistening and energetic conditions. Maps of SMAI indicate that in June, the northern part of Bulgaria suffers from 'risk of drought/dry', which is transformed into severe drought conditions over the whole region in July. In August, precipitation leads to an increase of the SMAI, drought severity declines, but drought remains in the eastern parts where precipitation also stays below the norm for this month. The spatial distribution of LSASAF LST shows a similar pattern: the lower the SMAI (i.e., increased drought severity) the higher the LST. Accumulated terrestrial drought leads to increased land surface temperature, as in July 2007. Qualitative comparison of the color maps reveals a good agreement between the spatial distributions of the two indices: for the regions with low SMAI indicating dry conditions, LST values according to the MSG-based satellite product are high.  
Year 2012 is characterized by monthly precipitation below average: in March (4-50% mostly), April (50-120%), June (5-75%), July (0-80%), and August (20-120%). SMAI for 50 cm soil depth is  
Figure 4: Spatial distribution of monthly mean SMAI (50 cm soil layer) over Bulgaria in 2007 for (a) June, (b) July, and (c) August, and of LSASAF LST for (d) June, (e) July, and (f) August.  
sensitive to reflecting the lack of precipitation and the corresponding deficit in SMA. Spatial distribution for July and August 2012 indicates persistent 'drought/risk of drought' for the whole region that is consistent with the distribution of high LST values up to 35-45 \({}^{\circ}\)C in the corresponding areas. For 2012, as for 2007, there is a good correspondence in spatial variability of SMAI and LST (not here presented because of similarity with 2007).
## 4 Performance Evaluation in Edge Scenarios
### I/O-Intensive Workload
#### 4.3.2 Random Read/Write Performance  
Random read and write operations were performed on cached files, which resulted in higher performance compared to sequential read and write operations. The results are shown in Figure 4. Occlum's read and write performance remained at a low level, while Gramine experienced a noticeable performance drop when the read/write buffer size exceeded 1 MB. Unlike sequential read and write operations, Gramine's performance with smaller buffer sizes did not surpass that of the native Linux. It merely approached native performance. This indicates that with caching, Gramine cannot achieve the same read and write performance as native Linux. The results in the virtual environment show almost no difference compared to those in the native environment.  
Overall, SGX does not offer an I/O solution that balances performance and security in edge intelligence scenarios. The SGX SDK requires frequent enclave transitions for I/O operations, which introduces additional performance overhead without providing sufficient security. Occlum offers a secure file system, but its performance is too poor to be practically useful in real tasks. While Gramine achieves native performance with smaller buffer sizes in tests, it lacks comprehensive security guarantees and experiences significant performance degradation with larger buffer sizes.  
Figure 4: Random read/write performance. (**a**) Random read. (**b**) Random write.  
Figure 3: Sequential read/write performance. (**a**) Sequential read. (**b**) Sequential write.
# Finite Element Analysis of Proposed Self-Locking Joint for Modular Steel Structures
## 5 Parametric Study on the Proposed Connection
### Effect of Beams Thickness  
To quantify beam thickness on the rotational capacity of joint, models Cp4 and Cp5 were developed. Selection of beam thickness was based on the assumptions of weak beam strong column, i.e., Cp1 (thickness of \(C_{beam}\) is 6.3 mm, the thickness of \(F_{beam}\) is 8 mm) to strong beam weak column, i.e., Cp4 (\(C_{beam}\) = 12.5 mm, \(F_{beam}\) = 14 mm), column and beams having same thickness were denoted by Cp5 (\(C_{beam}\) = \(F_{beam}\) = 10 mm). While the thickness of the column for all connections were kept constant at 10 mm. Figure 9a shows that the rotational stiffness and moment carrying capacity of the joint increased significantly by increasing the thickness of beams. In joint Cp1, the ceiling beam was the critical member to carry maximum moment in the joint. After the yielding occurred in the ceiling beam, the moment-rotation (M-\(\theta\)) curve tends to descend, while in joint Cp4 and Cp5 maximum moment carried by column and joint failure was caused by local deformation of column flange as shown in Figure 9b.  
Figure 9: Effect of beam thickness (**a**) M–\(\theta\) curve. (**b**) Location of failure.