esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion and Conclusions
It was concluded that the electric field value decreased as the damping time and distance increased. After forming the channel of the 15 kA LEMP sprout, the electric field value created in 0.5 \(\upmu\)s in the conductors located on the 15 m high pole of the overhead line 70 m away was determined to be 2.4 kV/m. It was observed that the effect on the line disappears over time. The electric field produced on the pole of the line 500 m away by moving in the shape of a traveling wave on the same line was calculated to be 0.3 kV/m. The results support [PERSON]'s perspective on the matter and clarify the indirect coupling effects of LEMPs on energy transmission lines and facilities. The combination of the Rusck approach and the Heidler wave equation can be used to evaluate the indirect LEMP performance of overhead power lines with high accuracy, thereby avoiding significant losses of accuracy. This study is unique from other studies in the literature as it utilizes electromagnetic field functions based on accelerating loads rather than the traditional dipole approximation, thus presenting graphical results that do not require interpolation. LEMPs are a complex natural phenomenon. The more realistically we can model this impulse mathematically, the better we can prevent transient damage to electrical facilities. These models will facilitate the pre-determination of surge current values to protect energy transmission lines exposed to LEMPs, thus aiding in the selection of appropriate levels for protective devices. Additionally, we believe that these mathematical models will gain importance in harnessing the energy of LEMPs in future studies. Conceptualization, T.C., H.F.C. and S.O. ; methodology, T.C., H.F.C. and S.O. ; software T.C., H.F.C. and S.O. ; validation, T.C., H.F.C. and S.O. ; formal analysis, T.C., H.F.C. and S.O. ; investigation, T.C., H.F.C. and S.O. ; resources, T.C., H.F.C. and S.O. ; data curation, T.C., H.F.C. and S.O. ; writing--original draft preparation, T.C., H.F.C. and S.O. ; writing--review and editing, T.C., H.F.C. and S.O. ; visualization, T.C., H.F.C. and S.O. ; supervision, T.C., H.F.C. and S.O. ; project administration, T.C., H.F.C. and S.O. ; funding acquisition, T.C., H.F.C. and S.O. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The raw data supporting the conclusions of this article will be made available by the authors on request. The authors declare no conflict of interest.
## Appendix A Computational Complexity
### Conventional Scheme C  
In the case of the conventional scheme C, its complexity is based on the computations of (6), (18) and (19). The number of operations in (6) is the same as that in the conventional Scheme A. From (18), \(\sum_{k\in\mathcal{S}_{f}}|\tilde{H}_{l}(k)|^{2}\angle Y_{l}(k)\) requires \(3N_{f}\) real multiplications and \(2N_{f}-1\) real additions, whereas \(N_{f}-1\) real additions are needed for calculating \(\sum_{k\in\mathcal{S}_{f}}|\tilde{H}_{l}(k)|^{2}\). For each CP subcarrier, \(\angle Y_{l}(k)\) is performed, and the summation over \(k\in\mathcal{S}_{f}\) requires \(N_{f}(8N_{b}-10)\) real flops. Then, the number of operations in (18) is \(N_{f}(8N_{b}-4)-1\) real flops. Estimating SFO \(\hat{\xi}\) in (19), it follows that calculating the quantity \(\sum_{k\in\mathcal{S}_{f}}k|\tilde{H}_{l}(k)|^{2}\angle Y_{l}(k)\) needs \(N_{f}\) real multiplications and \(N_{f}-1\) real additions because some intermediate results in (18) are already available, whereas \(\sum_{k\in\mathcal{S}_{f}}k^{2}|\tilde{H}_{l}(k)|^{2}\) requires \(N_{f}\) real multiplications and \(N_{f}-1\) real additions. Thus, it is concluded that \(8N_{f}N_{b}-2\) real flops are needed in the conventional Scheme C.
## 3 Principle of the Proposed Eios-TPS
### Modulation Strategy in the Medium and High-Power Range When \(k>1\)  
Under medium and high-power operating conditions in the buck mode, mode D is selected as the backup optimized mode. By applying the same approach to solve mode D, the optimal duty-cycle combination is obtained as follows:  
\[\left\{\begin{array}{l}D_{1}=\sqrt{\frac{p}{2(k-1)}}\\ D_{2}=k\sqrt{\frac{p}{2(k-1)}}\\ \Phi=\frac{1}{2}\sqrt{\frac{(k-1)p}{2}}\end{array}\right. \tag{9}\]  
where the intrinsic relationship among \(D_{1}\), \(D_{2}\) and \(\Phi\) can be expressed as:  
\[\Phi=\frac{-2+D_{1}+k}{2(-1+k)} \tag{10}\]  
For \(k>1\), in mode D, the conditions of \(i_{L}(t_{0})>0\) and \(i_{L}(t_{2})<i_{L}(t_{3})\) are always satisfied. Therefore, switches \(S_{1}\) and \(S_{2}\) can achieve ZVS, and after \(S_{5}\) and \(S_{6}\) achieve ZVS, \(S_{7}\) and \(S_{8}\) can also achieve ZVS. The ZVS conditions are defined as \(i_{L}(t_{1})<0\) and \(i_{L}(t_{2})>0\). As shown in Figure 8a, the ZVS region of mode D is enclosed by the planes \(i_{L}(t_{1})=0\), \(i_{L}(t_{2})=0\), as well as the coordinate planes, forming a closed space. The magenta curve represents the optimal trajectory of mode D, located entirely within the ZVS region. Under this optimized operation, the transmitted power range for mode D is \([2(k-1)/k^{2},1]\).
## 4 Global Error Model Verification by Numerical Simulations
### First Case Analysis: \(\Delta A_{\mathrm{s}}\) Equals \(\Delta h_{\mathrm{s}}\)
#### 4.1.1 Colored Region  
The results presented in Figure 10a were calculated by Equation (18); Figure 10b shows latitude deviation \(\Delta\psi\) for all global locations when \(\Delta A_{\rm s}=\Delta h_{\rm s}=0.1^{\circ}\). In Figure 10a, all points on the contour line labeled as \"1\" had \(\mathrm{d}\psi/\Delta A_{\rm s}=1\). In Figure 10b, all points on the contour line labeled as \"0.1\" had \(\Delta\psi=0.1^{\circ}\), which yielded \(\Delta\psi/\Delta A_{\rm s}=1\).  
Figure 11: The results obtained for the first case, where \(\Delta A_{\rm s}=\Delta h_{\rm s}\): (**a**) TDRLON; (**b**) the total increment of longitude \(\Delta\eta\) when the independent variable changed by \(0.1^{\circ}\).  
Figure 10: The results obtained for the first case, where \(\Delta A_{\rm s}=\Delta h_{\rm s}\): (**a**) TDRLAT; (**b**) the total increment of latitude \(\Delta\psi\) when the independent variable changed by \(0.1^{\circ}\).  
The colored areas in Figure 10a,b indicate that the contour line distribution patterns displayed in these figures were consistent, meaning that \(\mathrm{d}\psi/\Delta A_{\mathrm{s}}\approx\Delta\psi/\Delta A_{\mathrm{s}}\). Consequently, it could be determined that \(\Delta\psi\approx\mathrm{d}\psi\).  
The contour line distribution patterns presented in Figure 11a,b were also consistent, indicating that \(\Delta\eta\approx\mathrm{d}\eta\).  
Further research indicated that when \(\Delta A_{\mathrm{s}}=\Delta h_{\mathrm{s}}\
eq 0.1^{\circ}\), for example, \(\Delta A_{\mathrm{s}}=\Delta h_{\mathrm{s}}=0.5^{\circ}\) or \(\Delta A_{\mathrm{s}}=\Delta h_{\mathrm{s}}=3^{\circ}\), the global error model remained valid in the colored region.
## 3 Effects of F-T Cycles on the Mechanical Properties and Microscopic Parameters
### Effect of F-T Cycles on Particle Morphological Characteristics
#### 3.2.3 Effect of F-T Cycles on Particle Abundance Percentage and Average Particle Abundance  
Particle abundance refers to the ratio of the short axis-to-the long axis of the particles, that is the ratio of the minimum diameter-to-the maximum diameter extracted by IPP, which shows the geometric shape of particles [39]. Its value is between zero and one. The particles tend to be elongated and equiaxed when the abundance value tends to zero or one, respectively. The particle abundance percentage and average particle abundance (C) versus F-T cycles are shown in Figure 6 and Table 4.  
Figure 6a displays that the largest proportion of particles was that whose abundance was in the range of 0.4-0.6; the second were 0.2-0.4 and 0.6- 0.8; the least were 0-0.2 and 0.8-1 in S0; this indicated that most of the particles tended to be equiaxed. As F-T cycles continued, the particles of S0 whose abundance was from 0.4-0.6 increased, while particles with an abundance of 0.2-0.4 and 0.6-0.8 decreased, and 0-0.2 and 0.8-1 basically remained unchanged. From Figure 6b, the particle abundance percentage change of S2 in each interval was similar to that of S0, implying that more particles tended to be equiaxed after F-T cycles. Comparing Figure 6a with Figure 6b, the particles of S2 with abundance of 0.4-0.6 were more than those of S0 in the same abundance interval, indicating that the addition of cement could multiply the number of equiaxed particles and increase the ability of soil to resist deformation under F-T cycles.  
From Table 4, the C of S0 fluctuated from 0.444-0.490, while the C of S2 was from 0.478-0.516. The C of S2 was larger than that of S0, indicating that the incorporation of cement could make the  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multicolumn{8}{c}{**F-T cycles**} \\ \cline{2-9}  & **0** & **1** & **2** & **3** & **4** & **5** & **6** & **8** \\ \hline S0 & 0.486 & 0.451 & 0.477 & 0.479 & 0.444 & 0.490 & 0.452 & 0.475 \\ S2 & 0.511 & 0.498 & 0.502 & 0.515 & 0.516 & 0.478 & 0.514 & 0.516 \\ \hline \hline \end{tabular}
\end{table}
Table 4: C under F-T cycles.  
Figure 6: Particle abundance percentage under F-T cycles: (**a**) S0 and (**b**) S2.  
soil tend to develop in an equiaxed manner. Therefore, the soil properties tended to be stable and the influence of F-T on C could be reduced.
## 3 Construction of the Optimization Objective Function  
### Description of Optimal Time-Shock Planning Problem  
By discretizing the motion trajectory to be executed by the robot arm in a Cartesian space, a sequence of spatial positional matrices \(T_{i}\) can be obtained, and the spatial positional sequence can be converted into a sequence of robot-arm joint positions \(p_{i}=[p_{1,i}p_{2,i}\cdots p_{N,i}],i=0,1,2,\cdots,n\) using inverse kinematics. \(N\) denotes the number of joints in the robot arm, and \(i\) denotes the time node \(t_{i}\). The joint position-time node sequence is:  
\[Q\ =\ [(p,t_{i})|i\ =\ 0,1,\cdots,n] \tag{17}\]  
The joint trajectory profile can be obtained by interpolating the above joint position-time node sequence with polynomial or spline functions. The former improves the execution efficiency of the arm, and the latter ensures that shocks are minimized during the execution of the motion trajectory, optimizing two conflicting kinematic performance metrics. The less that joint shocks and drive torque fluctuations occur, the smoother the arm motion.  
In this regard, by constructing trajectory profiles for each joint of the robot arm using a five-order B-spline function and by using both joint motion time and shocks as optimization metrics, the optimal time-shock planning problem for the robot arm can be generalized as a multi-objective optimization problem as follows:  
\[\begin{array}{l}f_{1}(x)\ =\ \sum\limits_{i=\ 0}^{n-1}\bigtriangleup t_{i}\ =\ T\\ f_{2}(x)\ =\ \sqrt{\frac{1}{2}\int_{0}^{T}(I(t))^{2}dt}\end{array} \tag{18}\]  
Figure 6: Partial function convergence curve: (**a**) function F1; (**b**) function F5; (**c**) function F7; (**d**) function F10; (**e**) function F13; (**f**) function F17.  
Considering the motion constraint for the robot arm, the following constraint is defined:  
\[\left\{\begin{aligned} &|V(t)|\leq V_{max}\\ &|A(t)|\leq A_{max}\\ &|J(t)|\leq J_{max}\end{aligned}\right. \tag{19}\]  
The weight method is also used to convert the multi-objective optimization problem into a single-objective optimization problem, and the penalty function method is used to convert the constrained problem into an unconstrained problem.  
\[\begin{aligned} F(x)&=k_{1}f_{1}(x)+k_{2}f_{2}(x)+ \sum\limits_{\begin{subarray}{c}n=1\\ n=1\end{subarray}}^{num-N}\xi_{n}f_{penalty}^{(n)}\\ f_{penalty}^{(n)}&=\left\{\begin{array}{l}1,max(|N(t)|)>N _{max}\\ 0,else\end{array}\right.\\ \xi_{n}\text{: Penalty function weight}\end{aligned} \tag{20}\]  
To satisfy the requirements for the continuous jerk trajectory, each joint trajectory third-order curve must be at least geometrically continuous, and since the \(k\)th order B-spline curve has the property of \(\mathbb{C}^{k+1}\) continuity, it is required that \(k\geq 4\). Therefore, the interpolated curve is constructed using the five-order B-spline function.
# Micro-Satellite Systems Design, Integration, and Flight
## 4 Attitude Control System (ACS) Development  
One of the key functions of a satellite is to manage angular momentum. The subsystem that handles this function is called the attitude control system (ACS). For Alpha, the ACS system must be able to stop tumbling, stabilize spinning, and orient the satellite. See Table 5 below.
## 4 Conclusions  
In this paper, four 3D-CNN model architectures were used to predict and classify lemon hyperspectral images in search of their freshness (bruises). The most important results obtained in this study are summarized next to conclude:  
1. The input dataset was small and the use of specific augmentations helped in generalizing the model's prediction. Thus, we used two kind of data augmentation in this work: RandomHorizontalFlip and Color Jitter.
2. There were limitations in the case of GPU memory resources and they were solved by accumulating gradients of smaller batches. With this method, we were able to train the networks with batch size 8, which is useful in the training phase.
3. Using 3D-CNN layers helps us extract useful information from the 3D structure of concatenated hyperspectral images and leverage the spatial information within nearby pixels of the images and spectrums, thus having a double spectral-spatial classification.
4. The best result is achieved from models with Residual Connections such as ResNet. These connections enhance the flow of gradients in these models. As a result, the model can be deeper without suffering the degradation problems like vanishing gradients and deeper models provide higher generalization power.
5. Using exponential schedulers instead of a fixed learning rate helps to dynamically adapt the learning rate based on the epoch number. Furthermore, this scheduler enhances the process of finding an optimal point on our loss function by using big steps at the start of training and reducing the step sizes as we converge in the following epochs.  
Figure 17: Receiver Operation Characteristic (ROC) curve for each model (Micro averaged on all classes and for each class): (**a**) ResNet, (**b**) DenseNet, (**c**) ShuffleNet, and (**d**) MobileNet.  
* 6 Changing the architecture of the models in order to make them more efficient, like ShuffleNet and MobileNet, will sacrifice their performance and generalization power in complex tasks like 3D-CNN classifications in favor of their simplicity.
* 7 The easiest label to distinguish in our dataset is Class 1 (8 h after bruising). Both Class 0 (healthy, un-bruised) and Class 2 (16 h after bruising) labels are harder to distinguish and need more powerful networks like ResNet and DenseNet to be correctly classified.  
Conceptualization, R.P.; methodology, S.S. and M.H.R.; software, M.D.; validation, S.S. and M.H.R.; formal analysis, R.P. and S.S.; investigation, R.P.; writing--original draft preparation, R.P.; writing--review and editing, J.I.A.; visualization, S.S.; supervision, M.H.R.; project administration, R.P. and S.S.; funding acquisition, R.P. and S.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data is unavailable due to privacy or ethical restrictions.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
# Discrimination of Spatial Distribution of Aquatic Organisms in a Coastal Ecosystem Using eDNA
## 3 Results  
### Meta-Barcoding  
In total, 3,066,013 paired-end reads from the 19 samples were generated on the Illumina MiSeq(tm) platform, of which 98.5% passed Q30 (Phred quality score \(>\) 30) for improving accuracy of sequences in this study (Supplementary Materials). Each sample yielded paired-end reads ranging from 21,101-299,305 reads (mean: 161,369 reads), which was similar to the amount of reads in the previous study [36], and all samples exhibited saturation of the number of OTUs by rarefaction curve analysis. Gamma-diversity was 352 OTUs produced with a cutoff of 97% similarity. The resulting 352 OTUs were classified into 19 genus-level taxonomic groups (those representing \(<\)0.04% abundance were not plotted). Uncultured and non-assigned reads were discarded.
# Downdraft Assessment of Glass Curtain Wall Buildings with a Radiant Floor Heating System
###### Abstract  
The present study aims to evaluate whether downdraft can be prevented by applying a radiant floor heating system in glass curtain wall buildings. A radiant floor heating system does not directly supply heat to cold air, but does so via heat exchange with a cold airflow. Assessing whether a downdraft is prevented is, thus, necessary. For this assessment, a radiant floor heating system was applied to perimeter zones with different window types modeled using a computational fluid dynamics (CFD) simulation. The relationship between the radiant floor heating system and the windows was examined via an assessment of the resulting downdraft by considering the radiant heat exchange effect between the window and the floor. The assessment was conducted by utilizing a CFD simulation. The simulation results show that the temperature difference between the air supplied through the radiant floor heating system and the air descending along the cold surface of the window increased when the radiant floor heating system was applied to a narrow area with a high temperature. Furthermore, the airflow velocity increased with the heat exchange. The airflow re-entered the window side, and the downdraft in the occupied area exceeded the strict value specified by the standards. Conversely, if heat were applied according to the indoor thermal output by widening the radiant heat area of the radiant floor heating system, a downdraft could occur as a result of a blocking failure prior to the influx of the cold air into the occupied area caused by low surface temperatures. Therefore, applying a radiant floor heating system is advantageous in a perimeter zone without causing airflow inducement at the window side with acceptable surface temperatures.  
Keywords:downdraft; thermal comfort; radiant floor heating system; CFD +
Footnote †: journal: Applied Sciences
###### Abstract  
Variable machine efficiency (VME) and maintenance activities (MA) are critical factors often unexplored in job scheduling problems. This paper introduces a new problem termed the job-shop scheduling problem with variable machine efficiency and maintenance activities (JSSP-VME-MT), wherein, unlike the traditional JSSP, machine efficiency and maintenance activities are explicitly incorporated into the scheduling process. The study proposes a novel memetic algorithm (MA) underpinned by a variable neighborhood descent (VND) local search strategy to address this complex problem. This methodology demonstrates significant improvements, achieving mean makespan reductions ranging from 2.22% to 5.77% across diverse problem instances with varying numbers of machines and jobs. Key contributions include the development of an encoding scheme to model maintenance activities and machine-specific constraints, along with the design of a hybrid metaheuristic framework combining global exploration and local refinement. This work provides a foundation for future comparative studies, algorithm enhancements, and practical industrial applications. The approach offers a scalable and flexible solution to job-shop scheduling challenges involving dynamic efficiency and planned maintenance activities.  
Keywords:Job-Shop Scheduling Problem (JSSP); Memetic Algorithms (MA); Variable Machine Efficiency (VME); maintenance activities; Variable Neighborhood Descent (VND) +
Footnote †: journal: Applied sciences
###### Abstract  
Quantitative assessment of movement using motion capture provides insights on mobility which are not evident from clinical evaluation. Here, in older individuals that were healthy or had suffered a stroke, we aimed to investigate their balance in terms of changes in body kinematics and muscle activity. Our research question involved determining the effects on post- compared to pre-sensorimotor training exercises on maintaining or improving balance. Our research hypothesis was that training would improve the gait and balance by increasing joint angles and extensor muscle activities in lower extremities and spatiotemporal measures of stroke and elderly people. This manuscript describes a motion capture-based evaluation protocol to assess joint angles and spatiotemporal parameters (cadence, step length and walking speed), as well as major extensor and flexor muscle activities. We also conducted a case study on a healthy older participant (male, age, 65) and an older participant with chronic stroke (female, age, 55). Both participants performed a walking task along a path with a rectangular shape which included tandem walking forward, right side stepping, tandem walking backward, left side stepping to the starting location. For the stroke participant, the training improved the task completion time by 19 s. Her impaired left leg had improved step length (by 0.197 m) and cadence (by 10 steps/min) when walking backward. The non-impaired right leg improved cadence when walking forward (by 15 steps/min) and backward (by 27 steps/min). The joint range of motion (ROM) did not change in most cases. However, the ROM of the hip joint increased significantly by 5.8 degrees (\(p\) = 0.019) on the left leg side whereas the ROMs of hip joint and knee joint increased significantly by 4.1 degrees (\(p\) = 0.046) and 8.1 degrees (\(p\) = 0.007) on the right leg side during backward walking. For the healthy participant, the significant changes were only found in his right knee joint ROM having increased by 4.2 degrees (\(p\) = 0.031) and in his left ankle joint ROM having increased by 5.5 degrees (\(p\) = 0.006) during the left side stepping.
# Speed Bump and Pothole Detection Using Deep Neural Network with Images Captured through ZED Camera
### Our Proposal  
A relevant problem detected in studies such as [14; 17; 18; 20; 21] was that their systems focused on detecting well-marked speed bumps; for this reason, they presented difficulties during the detection of unmarked speed bumps. Our system is capable of detecting marked and unmarked speed bumps with a balanced success rate. This is an important aspect in the Mexican environment because many speed bumps are not marked. Also, the way that our system processes the images differs from most current convolutional networks because it does not perform a stride in the convolution layer in order not to under-sample and thus hide detailed information about the input image. Although the amount of processing at the input is greater than in other architectures, we tried to use the fewest number of network layers so as not to compromise the processing speed of the deep network. In contrast to various works in the literature, our proposal manages to detect both speed bumps and potholes [2] for car traffic, and the work methodology that we follow is illustrated in the flowchart of Figure 1.  
In this article, we propose the use of a deep neural network without strides or pooling but with a \"batch normalization\" layer to classify images that contain a pothole or speed bump, as well as those that do not. This is in conjunction with a manually labeled database obtained from ZED camera videos on avenues in the city of Celaya, Guanajuato, Mexico, in order to help autonomous driving systems and human drivers prevent road accidents due to speed bumps and humps.