esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Objective: The goal of this study was to utilize Gait Profile Score (GPS) and Gait Deviation Index (GDI), to assess its capability of differentiating between injured and non-injured runners. Design: In total, 45 long-distance runners (15 non-injured, 30 injured), diagnosed with one of the following running related injuries, patella femoral pain syndrome, iliotibial pain syndrome, and medial tibial stress syndrome, were recruited. Methods: Data were obtained from a running analysis gait laboratory equipped with eight infrared motion-capturing cameras and a conventional treadmill. Running kinematics were recorded according to the Plug-In Gait model, measuring running deviations of the pelvis and lower extremities at a sampling rate of 200 Hz. GPS and GDI were calculated integrating pelvis and lower limb kinematics. Movement Analysis Profile results were compared between injured and non-injured runners. The non-parametric two-sample Wilcoxon test determined whether significant kinematic differences were observed. Results: Total GPS score significantly differed between the injured and non-injured runners. Not all running kinematics expressed by GDI differed between groups. Conclusions: GPS score was capable of discriminating between the injured and non-injured runners' groups. This new running assessment method makes it possible to identify running injuries using a single numerical value and evaluate movements in individual joints.  
running; gait analysis; injury; kinematics; Gait Profile Score (GPS) +
Footnote †: journal: Accepted: 16 November 2021
## 3 Results and Discussion
### Species-Specific PCR for the Lactiplantiobacillus plantarum Group  
Species-specific PCR was used to further clarify the species affiliation of the isolates, which, in the other analyses, were included in the _Lp. Plantarum_ group. This method is based on the specific amplification of the _recA_ gene, which is sufficiently polymorphic to distinguish species within the _Lp. Plantarum_ group. The _Lactiplantiobacillus plantarum_ group includes _Lp. Plantarum_, _Lp. pentosus_, and _Lp. paraplantarum_. In this analysis, amplificons of different sizes in the three species were obtained: 318 bp in _Lp. plantarum_, 218 bp in _Lp. pentosus_, and 107 bp in _Lp. paraplantarum_[33].  
Of the six isolates tested, Ech1, Ph2, L1, and Cn1 gave an amplificon of the characteristic size of _Lp. plantarum_ (318 bp), while the isolates Ph3 and Ph5 gave an amplificon of the characteristic size of _Lp. paraplantarum_ (107 bp). The electrophoretically separated PCR products are presented in Figure 3. With this test, _Lp. plantarum_ ssp. _argentoratensis_ produced an unusual pattern with a weak band at 318 bp and a strong band at 120 bp [43; 48]. As such a pattern was not observed for any of the isolates from the _Lp. plantarum_ group, their possible affiliation with the _Lp. plantarum_ ssp. _argentoratensis_ subspecies was excluded. The final species identification of the sourdough isolates in this study is presented in Table 4.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Isolate** & **Identification** & **Reliability** \\ \hline Ech1 & _Lactiplantiobacillus plantarum_ 1 & 99.9\% \\ Ech3 & _Levilactobacillus brevis_ 3 & 99.6\% \\ L1 & _Lactiplantiobacillus plantarum_ 1 & 99.7\% \\ L2 & _Levilactobacillus brevis_ 3 & 97.2\% \\ El1 & _Levilactobacillus brevis_ 3 & 99.1\% \\ X2 & _Levilactobacillus brevis_ 3 & 75.1\% \\ X4 & _Levilactobacillus brevis_ 3 & 99.6\% \\ Cn1 & _Lactiplantiobacillus plantarum_ 1 & 99.9\% \\ Ph1 & _Levilactobacillus brevis_ 3 & 98.4\% \\ Ph2 & _Lactiplantibacillus plantarum_ 1 & 99.5\% \\ Ph3 & _Lactiplantibacillus plantarum_ 1 & 97.3\% \\ Ph5 & _Lactiplantibacillus plantarum_ 1 & 72.1\% \\ Car & _Levilactobacillus brevis_ 3 & 98.2\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Identification of sourdough isolates by their carbohydrate profile (processed with the Apiweb® software, BioMérieux® SA, France).
# Aerial Tele-Manipulation with Passive Tool via Parallel Position/Force Control +
## 5 Experimental Results  
In order to evaluate the proposed aerial tele-manipulation solution, and to assess the functionalities of the proposed controller in the bilateral teleoperation scheme, two experiments with fixed and movable objects were performed. In the first experiment, a human operator drives the aerial manipulator to establish a contact with a stationary target and applies force to it, receiving force feedback. In the second experiment, the human operator drives the quadrotor to establish a contact with a wheeled cart and pushes it to generate motion, while receiving force feedback.  
We encourage the interested reader to watch the video of the experiments in the multimedia attachment to this paper, cf. Supplementary Materials, to better appreciate the presented validation.
# Velocity-Aware Handover Self-Optimization Management for Next Generation Networks
## 5 Conclusions  
In this paper, a velocity-based self-optimization algorithm is proposed to adjust the HCP values in accordance with the UE speed and RSRP. The performances of HO-fixed HCP values and the proposed algorithm are investigated and evaluated. The advantages and disadvantages of the fixed HCPs are highlighted and discussed in terms of the total probability rate of HOP, HOPP, and RLF. The performance of the fixed HCPs results in the introduction of adaptive algorithms, which provides a satisfactory estimation of the HCP values. The performance of the proposed algorithm is analyzed under different mobile speeds and compared with other existing algorithms. The simulation results demonstrate that the proposed algorithm improves the overall system performance under all mobile speed scenarios and outperforms the existing algorithms by more than 70%. In future research, the proposed algorithm will be further improved by considering the traffic load of the serving BS and the target BS to increase the accuracy of the HO decision.  
Conceptualization, A.A. ([PERSON]), M.R and I.S.; methodology, A.A. ([PERSON]), M.R and M.Y.A; software, A.A. ([PERSON]), I.S.; validation, A.A. ([PERSON]), M.Y.A., and I.S.; formal analysis, A.A. ([PERSON]) and I.S.; investigation, A.A. ([PERSON]); writing--original draft preparation, A.A. ([PERSON]), M.R., I.S., and M.Y.A; writing--review and editing, I.S. and A.A ([PERSON]); supervision, M.R. and M.Y.A.; project administration, M.R.; funding acquisition, M.R. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Fundamental Research Grant Scheme (FRGS), Grant No. MMUE/170017, Under Ministry of Education, Malaysia.  
The authors declare no conflict of interest.  
Figure 8: Average probability of RLF for different algorithms.
# Detection of Forest Tree Losses in Cote d'Ivoire Using Drone Aerial Images
## 4 Discussion
### Quality of Photogrammetric Models and Maps  
The use of the Mavic Pro drone allowed us to map the dynamics of clearings in the Bossematie classified forest on test sites following a methodology already proven in several past studies [28; 32; 38]. The results of the photogrammetric processing demonstrate that the selected flight altitude and image overlap levels avoid the difficulties very often encountered in the aerial image mosaicking phase, especially in forest areas [26; 28]. The quality of the orthomosaics and of the selected digital surface models (reprojection errors between 0.551 pixels and 0.813 pixels) is sufficient to assess the changes in the forest surface with good accuracy. Indeed, refs. [19; 39] have shown that errors of 1 to 2 pixels are acceptable. These systematic errors in orthomosaics and digital surface models originate  
Figure 16: Clearing timing in the classified forests and data acquisition strategy. (**A**) Forest that appears to be intact but is already sown with cocoa beans. (**B**) Appearance of cocoa seedlings and felling of the undergrowth. (**C**) Burning of the base of large trees. (**D**) Falling or felling of standing dead trees so that cocoa trees grow better.  
from the instability of the mini-UAVs and the distortion of the digital cameras used [40]. However, image overlap levels in this study (65% and 75%, frontal and lateral) could be increased to improve the quality of orthomosaics. Indeed, several studies show high levels of overlap, such as [28] (90% front overlap), [32] (80% front overlap), and [41] (90% front overlap).  
In terms of the production of the set of maps of tree height distribution (April 2019) and tree loss (November 2018-April 2019) in the Bossematie classified forest, the validation reveals an overall accuracy of 97% and a kappa coefficient of 0.95. This indicates that these maps have satisfactory quality levels [42]. This shows the effectiveness of the method used in the detection of losses using aerial images acquired by drone.
# A Multi-Fidelity Successive Response Surface Method for Crashworthiness Optimization Problems
###### Abstract
In contrast, an iterative approach based on the successive construction of response surfaces is recommended, especially when the optimum approaches regions of the variable domain with very high gradients or even discontinuities. This approach, commonly known as the Successive Response Surface Method (SRSM), has been shown to be effective in crashworthiness applications, as demonstrated by the research of [PERSON] et al. and [PERSON] et al. [20; 21; 22]. Although SRSM has proven capable of identifying the optimal region for various crashworthiness problems, its application has some limitations. First, SRSM relies on iterative resampling, which could be a practical challenge since crashworthiness simulations are very time-consuming. Another potential drawback is the lack of continuity between successive approximations, making it difficult to incorporate information from previous iterations [14; 23]. Finally, to our current understanding, the method does not seem well suited for integrating valuable data derived from response evaluations of lower fidelity models. These models, which are comparatively cheaper to evaluate, are often available or can be generated through automated process chains. The effectiveness of such models has been shown in the work of [PERSON] et al. [24]. This paper proposes an approach that further enhances the SRSM and aims to overcome most of its existing limitations. The main contributions of this research are the following:  
* We extended the SRSM to achieve qualitatively superior optima and potentially improve its computational efficiency. This is accomplished by leveraging GP, adaptive sampling techniques, and multi-fidelity metamodeling. * Unlike conventional multi-fidelity methods (e.g., basic co-kriging), our approach is based on a method able to effectively handle complex non-linear correlations between different fidelities. We also quickly show how this method benefits from parallel job scheduling on a High-Performance Computer (HPC), enhancing its overall efficiency. The organization of this paper unfolds as follows. In Section 2, we briefly outline a common iterative process used to optimize crashworthiness problems and provide the necessary mathematical notation. Then, in Section 3, we review the key steps of the sequential response surface methodology. Section 4 then provides a brief overview of multifidelity metamodeling based on GPs and touches on its potential applications, in which we distinguish between linear and non-linear multi-fidelity approaches and emphasize the superiority of the latter through a selection of pedagogical examples. This paper continues in Section 5, where we present the workflow of our extension of SRSM based on multi-fidelity metamodeling. In Section 6, we test the proposed approach on a set of multi-fidelity benchmark functions, in addition to a crashworthiness use case. Finally, in Section 7, we outline the conclusions and consider potential future research directions.
# An Integrated Software for Computing Mechanical Properties of Crystalline Material by Means of XRD
## 2 Material Analyzing Software
### Lorentz-Polarization and Absorption (LPA) Factor
#### 2.2.1. Without Limitation of the Irradiated Area  
In the case of the Iso-inclination method without limitation of the irradiated area, substituting \(l_{1}\)=\(1/\cos\alpha\) and \(l_{2}\) = 1 into Equation (2) gives us:  
\[A=\frac{1}{\cos\alpha}\frac{\cos\alpha\cos\beta}{\cos\beta+\cos\alpha} \tag{3}\]  
In the fixed-\(\psi_{0}\) method, the following relations hold: \(\alpha\) = \(\psi_{0}\), \(\beta\) = \(\psi_{0}+2\eta\), \(\eta\) = \(90^{\circ}-\theta\). Substituting these Equations into the generalized Equation (3), we have the absorption factor for the fixed-\(\psi_{0}\) method:  
\[A=\frac{-\cos(\psi_{0}-2\theta)}{\cos\psi_{0}-\cos(\psi_{0}-2\theta)} \tag{4}\]  
In the fixed-\(\psi\) method, the following relation holds:  
\[\left\{\begin{array}{l}\cos\alpha=\sin(\psi+\theta)\\ \cos\beta=\cos(\psi+90^{\circ}-\theta)=-\sin(\psi-\theta)\end{array}\right.\]  
By substituting the relation into the generalized absorption factor in Equation (3), we obtain the absorption factor in the fixed-\(\psi\) method:  
\[A=\frac{-\sin(\psi-\theta)}{\sin(\psi+\theta)-\sin(\psi-\theta)}=1-\tan\psi\cot\theta \tag{5}\]  
In the case of the side-inclination method, by substituting \(l_{1}\) = \(1/\cos\psi\) and \(l_{2}\) = \(1/\cos\eta\) into Equation (2), we obtain the generalized absorption factor:  
\[A=\frac{1}{\cos\psi\cos\eta}\frac{\cos\alpha\cos\beta}{\cos\alpha+\cos\beta} \tag{6}\]  
In the fixed-\(\eta_{0}\) method, the incident x-rays make an angle \(\eta_{0}\) to the normal specimen, and we have \(\cos\alpha\) = \(\cos\psi\)sim\(\mid_{0}\) and \(\cos\beta\) = \(\cos\psi\)sim\(\mid\)\(\star\) where \(\eta^{\star}\) = \(180^{\circ}-2\theta-\eta_{0}\) and \(\eta_{0}\) = \(90^{\circ}-\theta_{0}\). Substituting the above relations into Equation (6), we have the absorption function:  
\[A=\frac{\sin(2\theta-\theta_{0})}{\sin\theta_{0}+\sin(2\theta-\theta_{0})} \tag{7}\]  
In the fixed-\(\eta\) method, by substituting \(\theta_{0}\) = \(\theta\) into Equation (7), we obtain the absorption function:  
\[A=\frac{1}{2} \tag{8}\]  
Since \(A\) is a constant, the absorption correction in this method is omitted.
# Compact Full Ka-Band Waveguide Directional Coupler Based on Rectangular Aperture Array with Stairs
## 4 Results
### Measurement Results  
The measured results were performed using an Agilent N5224A (Keysight Technologies, Santa Rosa, California, U.S.) network analyzer. The calibration method used is the Short-Load-Open-Thru (SLOT) method. The measured results and simulated results are shown in Figure 7. Over the full waveguide bandwidth from 26.5 GHz to 40 GHz, the measured S\({}_{11}\) magnitude and S\({}_{41}\) magnitude were below \(-\)17.46 dB and \(-\)20.82 dB, respectively. The S\({}_{21}\) magnitude varied from \(-\)2.89 to \(-\)4.26 dB, while coupling strength (S\({}_{31}\)-magnitude) changed from \(-\)2.74 to \(-\)3.80 dB. A power-split unbalance within 0.76 dB was achieved. The simulated and measured results of S\({}_{21}\) and S\({}_{31}\) are in good agreement. Some deviations between them may be caused by unexpected tolerances in fabrication, inaccurate material parameters, or loss of electromagnetic energy. The difference between simulation and measurement of S\({}_{11}\) may be caused by imperfect parameters of the transitions and loads used in the test, and the difference of S\({}_{41}\) may be caused by testing with no transitions and loads. The proposed coupler has a better performance in coupling flatness using smaller sizes compared with the couplers [5; 6; 7; 8]. The conventional ones (coupling region) need several \(\lambda\)g (\(\lambda\)g is operation wavelength of center frequency) to achieve the performance shown in Table 1, while the sample coupler (coupling region) only needs 1.35 \(\times\)\(\lambda\)g (15.82 mm) to realize tight coupling strength, full waveguide bandwidth, and better coupling flatness. The overall sizes of the coupler are 55.03 \(\times\) 20.02 \(\times\) 25.02 mm\({}^{3}\).
# Strategy Based on Two Stages for IR Thermographic Inspections of Photovoltaic Plants
###### Abstract  
Aerial infrared (IR) thermography has been implemented in recent years, proving to be a powerful and versatile technique for performing maintenance at photovoltaic (PV) plants. Its application speed and reliability using unmanned aerial vehicles (UAVs) or drones make it extremely interesting at large PV plants, due to the associated savings in time and costs. Ground-level thermographic inspection is slower and more costly to apply, although it does provide higher optical resolution, due to being conducted closer to the PV modules being inspected. Both techniques used in combination can improve the diagnosis. An IR thermography inspection strategy is proposed for PV plants based on two stages. The first stage of the inspection is aerial, enabling thermal faults to be detected and located quickly and reliably. The second stage of the inspection is done on the ground and applied only to the most relevant incidents revealed in the first stage. This inspection strategy was applied to a 100 kW PV plant, with an improved diagnosis verified via this procedure, as the ground-level inspection detects one-off thermal incidents from objects creating shade and from solar reflections. For PV modules with open circuits or open substrings, the use of one technique or another is immaterial.  
infrared thermography; aerial thermography; PV system maintenance
# Performance Evaluation of Open-Source Serverless Platforms for Kubernetes
### Related Work  
In a literature assessment of serverless performance studies by [PERSON] et al. [7], the authors show that studies of serverless platforms do exist; however, serverless as a scientific field is developing rapidly, and scientific finding and publishing cannot keep up with the speed of serverless innovation. Therefore, more studies are required to understand the effects of features and design choices on serverless platforms.  
[PERSON] et al. [8] analyzed many serverless platforms and formulated a reference architecture based on the similarities they found. This reference architecture makes it easier to discuss differences in the feature sets of serverless platforms; nevertheless, the authors argue that closed-source platforms (e.g., AWS, Microsoft, Google) limit understanding of the internal workings of these platforms.  
[PERSON] et al. [4], [PERSON] et al. [7], and [PERSON] et al. [9] have all pointed out that studies of serverless platforms largely focus on public cloud platforms, especially AWS, and neglect open-source self-hosted alternatives. [PERSON] et al. [4] further argue that studies of self-hosted serverless platforms are more complicated, as researchers have full control over the platforms under study and must set up and configure them on their own. Moreover, researchers must document all of these steps in order to ensure the comparability and reproducibility of their studies, while public cloud offerings work out of the box.  
Not only are serverless offerings in the public cloud partially a black box, they are constantly changing. Public cloud vendors are continually developing and improving their platforms in order to better satisfy their customers, which in turn makes it difficult or even impossibly to fully replicate studies on them. Furthermore, it is not possible to test a study against a specific version of a public cloud platform. A comparative study of a public serverless platform, such as that carried out by [PERSON] et al. [10], who analyzed multiple serverless frameworks for AWS, loses relevance as the platform it was tested on irreversibly changes away from the version that was studied.  
[PERSON] et al. [3] argued that serverless has potential for HPC. A study by [PERSON] et al. [11] further confirms this point, as they tested the viability of using serverless public cloud offerings instead of virtual machines (VMs) on their HPC cluster. They found that while this approach is very much valid, it performs best when running embarrassingly parallel tasks. Furthermore, it removes the complexity of having to set up VMs and application runtimes by packaging the applications and runtimes as containers. This last point has been confirmed by [PERSON] et al. [12], who investigated using Kubernetes and containers for HPC and found that it significantly improved portability and eased the installation of dependencies.
# An Improved MB-LBP Defect Recognition Approach for the Surface of Steel Plates
## 2 Surface Defects of Steel Plates
### Indentations  
The occurrence of indentations is due to inclusions in the plates during continuous casting, and pits appear on the surface of the billet, or as depressions on the surface of the roller table. The typical images of indentation are shown in Figure 3. Casting temperature, improper control of casting speed, entrapment of protective slag, etc., can cause defects on the surface and inside of the strand, especially surface flaws, pits, and buckling defects. During the heating and rolling process, it is possible to further form an indentation. The indentation seriously affects the quality of the casting blank as the indentation size varies, the direction is uncertain, and the manual inspection is difficult.