esa-sceva/satcom-chunk-collection huggingface dataset:
## Materials and Methods
### Experiment Design  
The performance of the threshing cylinder depends on several process parameters, such as drum speed, concave clearance and feed rate [20]. The best performance for threshing cylinder is the lowest loss rate and lowest damage rate. An excessively high loss rate means that a large amount of kernels are lost and cannot be collected into silo, and an excessively high damage rate means that there are more broken kernels, which affects the quality of corn kernels and reduces their grade.  
Pre-experiments were carried out. When the feed rate was 5 kg/s and the drum speed was 200 rpm, the un-threshed rate still did not appear. In this paper, the drum speed, concave clearance and feed rate were selected as the independent variables, while the loss and damage rate were taken as the responses. The relationship of the process parameters with the optimization objectives was established. A central composite design (CCD) was used to find the optimal values of the three parameters. In order to describe the nature of the response surface in the optimum region, a central composite design was taken six center points and five levels of each factor, and taken rotatable alpha, so the factor level encodes (\(-\)1.628, \(-\)1, 0, 1, 1.628) [21]. The process parameters and corresponding range were shown in Table 1. A five-level, three-factor central composite rotatable factorial design is shown in Table 2, which comprises 20 sets of coded conditions for the modeling of the threshing process.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Level**} & **Drum speed** & \multirow{2}{*}{**Feed rate (Fr)(kg/s)**} & **Concave clearance** \\  & **(Ds)(rpm)** & & **(Cc)(mm)** \\ \hline
1.682 & 600 & 9 & 50 \\
1 & 539.19 & 8.19 & 45.95 \\
0 & 450 & 7 & 40 \\ \(-\)1 & 360.81 & 5.81 & 34.05 \\ \(-\)1.682 & 300 & 5 & 30 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Coding of process parameters and their corresponding range.  
Figure 3: Threshing cylinder.  
Every test was repeated six times, and the total amount of frozen corn in the overall experiment with CCD was approximately 2625 kg. After each test, kernels in the collection hopper and outlets were weighed by an electronic balance. Corn kernels obtained from the outlets were known as loss grains. 2 kg of kernels were randomly weighed from collection hopper to calculate the damage rate. According to [PERSON]'s research [22], corn kernel threshing damage only included broken grains, rather than grains with stress cracks, meaning the damaged grains were picked out by an artificial eye. The formulae for the calculation of the loss rate (Lr) and damage rate (Dr) were as follows:  
\[Lr = \frac{W_{l}}{W_{t}}\times 100 \tag{1}\]  
\[Dr = \frac{W_{d}}{2}\times 100 \tag{2}\]  
In the formula, \(W_{l}\) was the weight of kernels collected in outlets, kg, \(W_{t}\) was the total weight of kernels from collection hopper and outlets in each test, kg, and \(W_{d}\) was the weight of the broken kernels in the sample kernels, kg.
## 3 Results and Discussions
### Scintillation Properties
The combination of the Gd site in the host and the Tb\({}^{3+}\) ions as luminescence center is one of the possible reasons why Tb-doped GPS has higher scintillation light yield than the other sample. According to PL emission map (Figure 3), only Tb-doped GPS shows the excitation wavelength of 310 nm unlike other samples having that of 270 nm. In our previous work of undoped GPS, it showed an emission peak at 310 nm [67]. In Tb-doped GPS, the emitted photons of 310 nm from the host has been self-absorbed and then transferred to emission by \({}^{5}\)D\({}_{4}\rightarrow{}^{7}\)F\({}_{5}\) transitions of Tb\({}^{3+}\) at 540 nm. however, the energy resolution is 30.3% considerably high and not favorable for a scintillator. On the other hand, Tb-doped LaPS is also interesting due to its better energy resolution of 16.8% and still had high scintillation light yield of 47,700 ph/MeV. For the next step, the improvement of the crystal quality is recommended in future work such as changing the crystal growth method to a more delicate way such as Czochralski-method to improve the energy resolution and the other properties.
## 4 Results and Discussion
### Effect of Porosity (\(\varepsilon\))  
Initially, the flow regime in the case of varying porosity of the medium was examined. The porosity is strongly related to the permeability of the system (Equation (21)). By increasing porosity, the permeability and the Darcy number of the porous medium increases. In the present simulations, the volume fraction of nanoparticles was set to \(\varphi=0.01\), the Rayleigh number to \(Ra=5\times 10^{8}\), and the Hartmann number to \(Ha=0\).  
In all porosity values considered, a central clockwise-rotating flow pattern was formed along the diagonal of the square enclosure, having two anticlockwise circulating regions in both the upper-left and lower-right parts of the diagonal, as shown in Figure 4. Three flow regions were formed, a hot region bounded between the left and top walls, a cold region between the right and bottom walls, and a third one along the diagonal area where temperature varies. By increasing porosity, the flow patterns intensify (higher stream function values), and the anticlockwise rotating cells tend to dominate the flow. Isotherms expand gradually, as stronger circulation favors concentration of isotherms lines. The microrotation isolines form a central vortex diagonally, increasing in length as the porosity increases. Vorticity variations are observed at the upper-right and lower-left edges of the cavity, whereas their thickness decreases and the intensity of the vorticity increases with increasing porosity.  
Figure 3: Convergence analysis for \(Nu_{ave}\) along the hot wall. Variation with \(Ra\).  
Figure 5 shows the average Nusselt number (\(Nu_{ave}\)) versus porosity (\(\varepsilon\)) for Hartmann numbers \(Ha=0\) and \(Ha=1,000\). In both \(Ha\) cases, the average Nusselt number increases with increasing porosity, as the flow intensity increases. For zero Hartmann number (\(Ha=0\)), the increase of the Nusselt number is more pronounced, highlighting the inhibitory effect of the magnetic field on the flow field and the heat distribution. The local Nusselt number along the hot wall is proportional to the temperature gradient (see Equation (35)), and higher values of the average Nusselt number indicate that an increased amount of energy was transferred from the heat source to the nanofluid and, eventually, to the porous medium.  
Figure 4: Stream function (\(\Psi\)), temperature (\(\theta\) ), microrotation (\(N\) ), and vorticity (\(\Omega\) ) contours for a range of porosities of the medium.
## 3 Description of the Proposed VLC Prototype
### Hardware Design and Implementation
#### 3.2.2 Data Rates and Communication Protocols  
Unlike indoor VLC applications where multi-Gb/s data rates are achievable due to the short distances involved and, due to the low noise conditions, outdoor applications in general and vehicular applications in particular envision significantly lower data rates. For example, the VLC system presented in [60] is able to achieve data rates up to 20 Mb/s at short-range, whereas, as the distance is increasing up to 110 m, the data rate is decreasing at 1.5 kb/s. Thus, in vehicular communication applications, the link robustness is more important than the data rate, as a lower data rate is preferable instead of a communication breakdown [17].  
Based on this consideration, the proposed prototype is designed to work at variable data rates within the 3-50 kb/s range. Thus, for medium to low noise conditions, the use of OOK modulation is considered. For low SNR conditions and extreme working conditions (i.e., fog, snow, direct sunlight exposure), the system is designed to use DSSS modulation at a frequency of 22 kHz and, thus, a 3 kb/sdata rate is achieved. Although, in this case, the achievable data rate is quite low, the use of DSSS modulation is envisioned for scenarios in which the SNR is very low or when the noise frequency is within the VLC receiver bandwidth.  
When considering the imposed requirements (i.e., modulation, coding, data rate), the VLC emitter transforms the data to send into an amplitude modulated light beam. Thus, the text message data are converted into a binary string, which is then encoded, modulated, and transmitted over the free space optical channel (as illustrated in Figure 3). For simplicity and cost constraints reasons, the system uses asynchronous transmission, with the synchronization information being located in the message header. The header also contains information regarding the modulation, the coding, the frequency, and the message length. The VLC receiver uses all of these data in the data recovery process.
###### Abstract  
This paper explores the effects of root-mean-square turbulence fluctuation velocity (\(u^{\prime}\)) and ignition energy (E\({}_{\rm{ig}}\)) on an ignition kernel delay time (\(\tau_{\rm{delay}}\)) of lean premixed n-butane/air spherical flames with an effective Lewis number \(L\approx 2.1>>1\). Experiments are conducted in a dual-chamber, fan-stirred cruciform burner capable of generating near-isotropic turbulence with negligible mean velocities using a pair of cantilevered electrodes with sharp ends at a fixed spark gap of 2 mm. \(\tau_{\rm{delay}}\) is determined at a critical flame radius with a minimum flame speed during the early stages of laminar and turbulent flame propagation. Laminar and turbulent minimum ignition energies (MIE\({}_{\rm{L}}\) and MIE\({}_{\rm{T}}\)) are measured at 50% ignitability, where MIE\({}_{\rm{L}}\) = 3.4 mJ and the increasing slopes of MIE\({}_{\rm{T}}\) with \(u^{\prime}\) change from gradual to drastic when \(u^{\prime}>0.92\) m/s (MIE transition). In quiescence, a transition of \(\tau_{\rm{delay}}\) is observed, where the decrement of \(\tau_{\rm{delay}}\) becomes rapid (modest) when E\({}_{\rm{ig}}\) is less (greater) than MIE\({}_{\rm{L}}\). For turbulent cases, when applying E\({}_{\rm{ig}}\)\(\approx\) MIE\({}_{\rm{T}}\), the reverse trend of MIE transition is found for \(\tau_{\rm{delay}}\) versus \(u^{\prime}\) results with the same critical \(u^{\prime}\approx 0.92\) m/s. These results indicated that the increasing \(u^{\prime}\) could reduce \(\tau_{\rm{delay}}\) on the one hand, but require higher E\({}_{\rm{ig}}\) (or MIE\({}_{\rm{T}}\)) on the other hand. Moreover, the rising of E\({}_{\rm{ig}}\) in a specific range, where E\({}_{\rm{ig}}\)\(\leq\) MIE, could shorten \(\tau_{\rm{delay}}\), but less contribution as E\({}_{\rm{g}}\) > MIE. These results may play an important role to achieve optimal combustion phases and design an effective ignition system on spark ignition engines operated under lean-burn turbulent conditions.  
laminar and turbulent minimum ignition energies; ignition kernel delay time; transition; flame speeds; Lewis number +
Footnote †: journal: Applied Sciences
# Horizontal Loading Performance of Offshore Wind Turbine Pile Foundation Based on DPP-BOTDA
###### Abstract  
Offshore wind power is becoming attractive in the wind-power field. With the rapid development of wind-power technology, high-power wind turbines have been implemented in practice. However, the increase in the length of the wind turbine blade causes the pile foundation to withstand a prone overturning moment. For overcoming the problems of traditional sensing technology and meeting the monitoring requirements of pile foundations, a 20 cm spatial resolution differential pulse pair Brillouin optical time-domain analysis (DPP-BOTDA) technique is used to measure a 69 m long offshore wind turbine pile under horizontal loading. From the distributed strain data collected in the test, the maximum stress location of the long pile under the horizontal load can be obtained. By analyzing the load and maximum strain (\(F\)-\(\varepsilon_{\text{max}}\)) curve, the horizontal bearing capacity of the pile foundation can exceed 900 kN, which is the maximum horizontal load of the design. The distributed displacement calculation method based on distributed strain data is proposed, according to the force characteristics of steel pipe piles. By comparing the calculated displacement data with the measured data by the dial indicators, the mean absolute percentage error (MAPE) value is only 0.03548. Results show that the 20 cm spatial resolution DPP-BOTDA technology is very suitable for the bearing capacity test of offshore wind turbine steel pipe pile foundations.  
offshore wind turbine; DPP-BOTDA; pile foundation; distributed displacement; bearing capacity +
Footnote †: journal: Applied Sciences
## 2 Materials and Methods
### Statistical Analysis  
First, descriptive statistics of the scores on the scales of the questionnaire tool were analyzed. Means with 95% confidence intervals and medians were used as measures of central tendency. Standard deviations and interquartile ranges were used to describe thedispersion of the scores. Possible deviations from normality in terms of the shape and normality of the score distribution were assessed using skewness and kurtosis. Correlation analysis was then performed using a two-tailed significance test and 95% confidence intervals between the scores on the scales of the questionnaire tool and the amount of time spent in regular physical activity and life satisfaction. [PERSON]'s or [PERSON]'s correlation coefficients were used depending on the level of measurement of the variables studied. A \(p\)-value of <0.05 was used as the threshold for statistical significance.  
Mediation analysis in the structural equation modeling approach was then used to test whether self-control, suppression, and reappraisal mediated the impact of the amount of time spent in regular physical activity on satisfaction with life. Therefore, in our analytical approach, the categorized amount of time spent in regular physical activity was the explanatory variable, the SWLS scores were the response variable, and the BSCS scores and the two ERQ subscales were the mediating variables. No violation of the model assumptions regarding homoscedasticity was found by visual inspection of the residual scatterplots. As the level of measurement of the categorized amount of time spent in regular physical activity was ordinal, the diagonally weighted least squares (DWLS) estimation method was chosen. Standardized parameter estimates for indirect, direct, and total effects were calculated and tested for significance using bootstrapped 95% confidence intervals. The accelerated bias-corrected percentile bootstrap method with 5000 resamples was used. Parameter estimates were considered significant at the 0.05 threshold if their bootstrapped 95% confidence intervals did not include zero. As all questions in the online form were mandatory, the dataset analyzed was entirely complete, eliminating the need for any methods to address missing values. The R-squared values for the mediating and dependent variables were used to assess the strength and explanatory power of the proposed model. Statistical analyses were performed using the open-source software jamovi [57], based on the R programming language [58] for statistical computing. The jamovi SEMLj module for structural equation modeling was employed to conduct mediation analysis [59]. A path diagram was created using draw.io desktop, which is a graph-drawing, open-source application.
## 3 Architecture Proposal Description
### Identifiers and Predefined Parameters  
Every cluster has an identifier called _clusterID_. When a new node joins a cluster it acquires a unique 32-bit node identifier called _nodeID_ from the CH. The first node in a cluster will be the CH and will have \(nodeID=0\)x01. Once the CH of the new cluster has contacted with other CHs in the network, it will acquire the first available _clusterID_ and, then, it will try to connect with the same type of CMs from other clusters. All nodes in a cluster have the same _clusterID_. Any new node will join the cluster whose CH is closest.  
Every new node must have the following parameters to join the proposed architecture:  
* Max_con: Maximum number of supported connections from other nodes of the distribution layer.
* Type: It identifies the type of node.
* Max_distance: It is the maximum distance to be a neighbor. It is always shorter than or equal to the coverage area radius. It can be changed by the Received Signal Strength Indication (RSSI) value or by the Signal Noise Ratio (SNR) value. It is applied only to establish connections between CHs and their CMs and between CMs, but not between CHs because CH must have as many connections with other CHs as possible. We have proved in other works [31] that although inductive and hybrid methods provide higher reliable values, we are considering a hard environment where there might not be any previous training phase.
* Position: It could be given manually or by GPS.
* It will have other parameters that vary along its existence in the architecture:
* Available_con: Number of available connections with other nodes of the distribution layer.
* E: % of energy consumption.
* L: % of available load. The load is the quantity of tasks the node is able to carry out at one time.  
Two parameters have been defined to be used for the operation of the architecture.
# Coupled-Error-Based Formation Control for Rapid Formation Completion by Omni-Directional Robots
## 3 Coupled-Error-Based Formation Control Method
: _(The Stability of the Formation Control Law Based on Coupled Error): When the proposed formation control law in (12)-(13) is employed in the multi-robot system in Figure 4, the stability of each robot can be guaranteed in the sense that coupled error \(E_{i}^{x}\) and \(E_{i}^{y}\), and the distance error \(e_{i}^{x}\) and \(e_{i}^{y}\) for \(i=1,\ldots,n\) are bounded and converge to zero asymptotically._  
Proof. : To show the stability of the multi-robot system with the proposed formation control algorithm, we choose the Lyapunov function candidate as  
\[V=\sum_{i=1}^{n}V_{i}, \tag{14}\]  
where  
\[V_{i}=\frac{1}{2}\frac{1}{(1+q)}\bigg{\{}(E_{i}^{x})^{2}+\Big{(}E_{i}^{y} \Big{)}^{2}\bigg{\}} \tag{15}\]  
Using (10), the time derivative of the Lyapunov function candidate in (15) for each robot can be described as  
\[ \begin{array}{rl}\dot{V}_{i}&=\frac{1}{(1+q)}E_{i}^{x}\dot{E}_{i}^{x}+\frac{ 1}{(1+q)}E_{i}^{y}\dot{E}_{i}^{y}\\ &=\frac{1}{(1+q)}E_{i}^{x}\big{\{}-(1+q)v_{i}^{x}+v_{i-1}^{x}+qv_{i+1}^{x}\big{\}} +\frac{1}{(1+q)}E_{i}^{y}\Big{\{}-(1+q)v_{i}^{y}+v_{i-1}^{y}+qv_{i+1}^{y}\Big{\}} \\ &=E_{i}^{x}\Big{\{}-v_{i}^{x}+\frac{1}{(1+q)}\big{(}v_{i-1}^{x}+qv_{i+1}^{x} \big{)}\Big{\}}+E_{i}^{y}\Big{\{}-v_{i}^{y}+\frac{1}{(1+q)}\Big{(}v_{i-1}^{y}+ qv_{i+1}^{y}\Big{)}\Big{\}}\end{array}  \tag{16}\]  
Substituting (12) and (13) into (16) gives  
\[\dot{V}_{i}=-k(E_{i}^{x})^{2}-k\Big{(}E_{i}^{y}\Big{)}^{2}\leq 0 \tag{17}\]  
Since \(V_{i}(0)\) is bounded and \(V_{i}(t)\) is non-increasing and bounded, it can be shown by [PERSON]'s Lemma [14; 15; 16] that the coupled errors \(E_{i}^{x}\) and \(E_{i}^{y}\) converge to zero. The Lyapunov function of the whole system in (14) can be arranged as  
\[\dot{V}=\sum_{i=1}^{n}\dot{V}_{i}\leq 0 \tag{18}\]  
In (14)-(18), it is shown that \(V(t)\) is bounded and converges to zero asymptotically for all times. This, in turn, implies that \(E_{i}\) and \(e_{i}\) in Theorem 1 are bounded for all \(i\). \(\square\)  
**Remark  
**Remark 2**. : _The finite time convergence of coupled error can ensure the string stability preventing error-propagation toward following robots as in [6]. However, since this paper focuses on fast formation completion rather than string stability, string stability is not guaranteed in this paper._
## 3 Results
The final step of the QC laser testing was to analyze emissions by PRBS signals consisting of 10-bit frames (1000010000 BIN) at the distance of 2 m. That frame was generated in the generator model 12000 Picosecond and eye diagrams were visualized on the oscilloscope screen. The registered diagrams for return-to-zero (RZ) coding format (pulsed) and non-return-to-zero (NRZ) coding format (cw laser) are presented in Figure 13, which correspond to modulation rates of 6 and 100 MHz, respectively. Although the cw laser could be modulated at a higher speed, the signal level was much lower than for the pulsed laser. Figure 11: Peak power vs. pulse frequency (pulse duty cycle). Figure 12: Registered pulses for BURST (16 triggering pulses with a repetition rate up to a frequency of 2.5 MHz (pulsed) and 40 MHz (cw)) mode operation of pulsed and cw lasers. This describes a compromise between high transmit rate (defined by modulation rate) and long data link (defined by optical power).
# Segmented Hybrid Impedance Control for Hyper-Redundant Space Manipulators
## 7 Conclusions  
In this paper, we addressed the challenge of compliance with multiple collision points in hyper-redundant space manipulators. We developed a hybrid impedance controller algorithm specifically designed to enable robust interaction and collision handling with obstacles. Additionally, our approach integrated object stabilization and both object and self-collision avoidance mechanisms, facilitating the manipulation of large objects in complex environments.  
Comparative analysis of the model both with and without impedance characteristics demonstrated the robustness of the control theory against the uncertainties associated with multi-point collisions. The practical implementation of this method further validated its effectiveness, highlighting the advantages of incorporating impedance control in enhancing the performance and reliability of hyper-redundant manipulators in dynamic settings. This work can be further enhanced by integrating machine learning techniques to dynamically adapt the impedance parameters based on the real-time conditions, enabling more precise and responsive control. Additionally, incorporating methods specifically designed to address residual vibrations, in conjunction with the current impedance-based approach, could significantly improve the overall performance and stability of the control architecture. These advancements have the potential to enhance the system robustness.  
Figure 24: Base Euler angles: (**a**) base Euler angles without impedance control; and (**b**) base Euler angles with impedance control.  
**Author Contributions:** Conceptualization, Q.H. and M.C.; methodology, Q.H.; software, Q.H. and M.C.; validation, M.C., C.B.H. and Q.H.; formal analysis, M.C.; investigation, M.C.; resources, Q.H.; data curation, Q.H.; writing--original draft preparation, M.C. and C.B.H.; writing--review and editing, M.C. and C.B.H.; visualization, M.C.; supervision, Q.H.; project administration, Q.H.; funding acquisition, Q.H. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the National Natural Science Foundation of China under Grant 12272039.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Restrictions apply to the datasets presented in this article. The datasets are not readily available because they are part of an ongoing study.  
**Conflicts of Interest:** The authors declare no conflict of interest.