esa-sceva/satcom-chunk-collection huggingface dataset:
# How Hydrogen (H\({}_{2}\)) Can Support Food Security: From Farm to Fork
## 6 Safety  
Using H\({}_{2}\) safely will require proper handling precautions and procedures due to its flammability and potential for explosive reactions. For example, during storage, H\({}_{2}\) will need to be contained in appropriate cylinders in well-ventilated areas away from heat sources, ignition and direct sunlight [72], a factor that is likely to pose an issue towards comprehensive use, particularly in countries such as the UK and USA which have stringent safety policies. Cylinders should also be regularly checked for damage to reduce the potential of leakage. Additionally, as H\({}_{2}\) is lighter than air, proper airflow and ventilation are also necessary to prevent the accumulation of H\({}_{2}\). Equipment, fittings and connections of any apparatus using H\({}_{2}\) will also require detectors/monitors, which can provide early warning of malfunction and H\({}_{2}\) leakage. Pressure regulators and flow meters can detect sudden pressure changes and may well be instrumental in preventing harm from faults in H\({}_{2}\)-associated equipment. It will be prudent to ensure individuals working with H\({}_{2}\) are adequately trained in the safe handling, storage and emergency procedures, with training to include recognizing the potential hazards and how to respond to incidences that may involve H\({}_{2}\) (e.g., evacuation, fires, leaks, etc.).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Product** & **Application** & **Mechanism** & **Outcome** & **Ref(s)** \\ \hline Cheese & H\({}_{2}\) gas (4\%) & Reduced mesophilic-aerobic bacteria; reduced yeast-mould & Improved shelf-life & [67] \\ \hline Eggs & H\({}_{2}\) gas (up to 3\%) & \begin{tabular}{c} Inhibited microbial spoilage; maintained antioxidant capacity; \\ reduced pH (yolk and white) \\ \end{tabular} & Improved shelf-life & [68] \\ \hline Freshwater Fish: & & Reduced microbial decarboxylase activity; Rainbow trout (_Oncorhynchus mylkiss_) & Improved shelf-life reduced biogenic amine formation; reduced protein degradation & [6] \\ \hline Seawater Fish: & & & & \\ Horse mackerel (_Trachurus trachomatis_) & & & & \\ \hline Shrimp (_Fenneropenaeus chinensis_) & \begin{tabular}{c} Reduces lipid oxidation and \\ (up to 1\%) \\ \end{tabular} & \begin{tabular}{c} Improved shelf-life and \\ purine metabolism \\ \end{tabular} & [69] \\ \hline Strawberries & H\({}_{2}\) gas (variety undisclosed) & \
\begin{tabular}{c} Increased phenolic and anthocyanin content \\ (4\%) \\ \end{tabular} &
\begin{tabular}{c} Increased shelf-life \\ (300–500\%) \\ \end{tabular} & [70] \\ \hline \hline \end{tabular}
\end{table}
Table 3: Identifies the benefits of H\({}_{2}\) application in the processing and packaging of fresh produce.
## 4 Current Research Status of Energy Management Techniques
### Global Optimal Control Strategy  
Rule-based control strategies have rules and thresholds that must be determined in advance, so they do not provide optimal solutions for different driving environments; meanwhile, the performance of such control strategies is greatly affected by changes in vehicle operating conditions. As a result, optimal control strategies have been proposed and are increasingly being studied.  
The dynamic programming technique has been employed to address the trouble of the optimal control variable trajectory [123]. [PERSON] et al. [124] depicted an approximate stochastic differential dynamic programming technique and then integrated it into an MPC framework to optimize energy utilization. Through a HIL experiment, the author evaluated the real-time feasibility of the potential of ASDDP. As to the application of medium and  
Figure 21: Control method of the wheel-driven hydraulic vehicle [118].  
heavy vehicles, [PERSON] et al. [125] introduced a hydraulic electric vehicle and debated its global optimization approach based on the genetic method. The results demonstrated that the economic performance was improved by 36.51% compared to the battery electric vehicle. Moreover, when adopting a genetic algorithm, the energy economy increased by 43.65%.  
For balancing fuel economy and drivability, [PERSON] et al. [126] studied a modified multi-objective particle swarm optimization procedure applied in a hybrid hydraulic vehicle. The results showed that the fuel economy of the traditional HHV was substantially enhanced by 18.27%. [PERSON] et al. [127] compared the improvement in fuel economy using local and global optimization techniques in a hybrid hydraulic powertrain. The results indicated that global optimization is obviously greater with regard to energy utilization. However, the author pointed out that global optimization techniques are offline. This means that they cannot be employed online, which requires them to be used in conjunction with other methods, such as local optimization methods.
# Collective Communication Performance Evaluation for Distributed Deep Learning Training
## 9 Conclusions  
In this paper, we compare and analyze distributed deep learning communication libraries in both bare metal and container environments. According to the research findings, in the parameter server approach with multi-GPU server allocation, MPI outperforms GLOO in terms of CPU-based communication, while in single GPU per container environments, GLOO exhibits superior performance. For NCCL, which is based on GPU communication, it shows excellent performance in both parameter server and all-reduce operations, except for GPU allocation constraints, and demonstrates more pronounced performance differences in all-reduce. Overall, in container environments, the multi-GPU setup within singularity containers outperforms other server environments. Based on these results, the following recommendations are suggested.  
For the parameter server method, MPI is the recommended choice for bare metal, singularity, and single-docker environments. In the cross-docker setup, using GLOO is advisable to minimize collective communication time. When employing the ring all-reduce method, it is advisable to utilize NCCL, irrespective of the server environment. Through this study, it would be useful from the user's perspective if a framework such as PyTorch had a function to select a collective communication library with minimum latency by considering the server execution environment.  
These results can serve as valuable insights for enhancing the design and implementation of distributed deep learning systems. Future research may delve into the impact of hardware and network topology on communication libraries and develop an automated framework for selecting the most suitable communication library for specific distributed deep learning environments, leveraging the findings of this study. Furthermore, additional experiments in inter-node server environments could enable a comprehensive study of distributed deep learning, focusing on overall cases of data parallelism.  
Conceptualization, J.L. and S.L.; methodology, J.L.; validation, J.L. and S.L.; writing--original draft preparation, S.L.; writing--review and editing, J.L.; supervision, J.L.; project administration, J.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Research Foundation of Korea (NRF-2023R1A2C1005750).  
Not applicable.  
Data Availability Statement: Data is contained within the article.  
The authors declare no conflicts of interest.
## 3 Applications of Crosslinked PEI
### Adsorption of Heavy Metals on a PEI Coating and Release  
The deposition of films on substrates has been used in different research areas and material productions. Some of these film-making techniques, such as spin coating, spray coating and doctor blading, have widely been known in organic photovoltaic research and material production [80; 81; 82]. The use of spin coating and spray coating methods in PEI film making has also been reported in the literature. A glutaraldehyde (GA)-mediated covalent layer-by-layer (LbL) assembly technique was reported to yield a layer with a thickness on the nanometer scale for MnCO\({}_{3}\) adsorption [83]. Spin coating was used to make a thin film of PEI on a silicon wafer substrate, which was subsequently crosslinked by immersing the coated substrate in a glutaraldehyde solution to give a coating thickness of 7.9 nm, as determined by ellipsometry [18; 83]. The crosslinked PEI coating was then immersed in water with a known concentration of Cu\({}^{2+}\) that ranged from 2 to 200 ppb for a Cu\({}^{2+}\) uptake experiment. The result has shown that the coating accumulates as much as 13, 8, and 5 wt% copper from 200, 20, and 2 ppb in artificial seawater, respectively. The selectivity of the coating was also tested by immersing it in a water sample that contained 12 ions, including Cu\({}^{2+}\). Even though Zn\({}^{2+}\) gets adsorbed quickly, Cu\({}^{2+}\) is seen to displace the adsorbed Zn\({}^{2+}\) over time and hence copper eventually accumulates preferably in the crosslinked PEI material. The demonstrated selective adsorption of copper at low concentrations from artificial seawater can have an application in water purification by sensing and extraction of copper ions from seawater [18]. In another study, nano-thin coatings of glutaraldehyde (GA)-crosslinked PEI/mesoporous diatomaceous earth particles were prepared for the selective and effective adsorption of copper from seawater. The composite material could remove Cu at 200 ppb from artificial seawater in the presence of other competing metal ions. The selectivity of the crosslinked polymer for copper was compared with that of the non-crosslinked PEI. While a trace amount of Zn was detected in the crosslinked polymer, about 30% of zinc relative to the amount of the adsorbed copper was found in the non-crosslinked PEI. The regeneration of the material for subsequent adsorption was also demonstrated by treating the coating with an acid [16]. Biological organisms such as bacteria, diatoms, and microalgae accumulate quickly on marine infrastructures if left unprotected for some time. Such growth of organisms on surfaces is known as fouling. A ship, for example, would consume 40% more fuel after 6 months due to additional hull drag from fouling if no antifouling (AF) paint is used on the body of the ship [84]. Copper compounds are traditionally used in the marine environment to control biological growth. For instance, Cu-based paints such as copper pyithione (CuPT) and Cu\({}_{2}\)O are used on ships and other marine environment infrastructures for
## 4 Experiments
### Qualitative Comparison with State-of-the-Art Methods  
#### 4.3.1 Visual Analysis on NRGD  
Figure 7 presents the qualitative comparison results on the NRGD, where GT denotes the ground truth images. As shown, our method effectively suppresses glare of various colors and shapes, significantly removing scattered glare around light sources while preserving fine details that were previously occluded by glare. In contrast, although EnlightenGAN and URetinex-Net improve overall image brightness, they fail to suppress glare and, in some cases, even amplify it. For instance, EnlightenGAN enlarges the green glare region in the third example and the white glare in the fourth example. Zero-DCE leads to blurred image details, while RUAS exhibits severe overexposure, degrading overall image quality. PSENet shows limited glare suppression capabilities but struggles with linear glare patterns, and the IAT method produces results that are nearly identical to the original images. By comparison, our method successfully suppresses the dispersed glare in the first image and the linear glare in the second image while accurately restoring the underlying details, demonstrating superior glare removal and detail recovery capabilities. Overall, these qualitative results are consistent with our quantitative evaluations, further confirming the effectiveness and superiority of our proposed method in nighttime glare suppression and visibility enhancement tasks.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Methods** & **PSNR \(\uparrow\)** & **SSIM \(\uparrow\)** & **LPIPS \(\downarrow\)** & **MSE \(\downarrow\)** \\ \hline EnlightenGAN [(20)] & 11.9049 & 0.7219 & 0.2665 & 4490.1825 \\ Zero-DCE [(50)] & 12.6071 & 0.7168 & 0.2656 & 3694.5139 \\ RUAS [(18)] & 6.3398 & 0.4290 & 0.5594 & 15,444.7054 \\ URetinex [(17)] & 13.1262 & 0.7256 & 0.2704 & 3374.2936 \\ PSENet [(51)] & 14.1257 & 0.7443 & 0.2257 & 2814.5622 \\ IAT [(21)] & 16.4169 & 0.6588 & 0.3671 & 1802.1397 \\ Ours & **31.4508** & **0.9822** & **0.0317** & **87.9677** \\ \hline \hline \end{tabular}
\end{table}
Table 2: Quantitative comparison of state-of-the-art methods on the Flare7k++ Dataset, where bold indicates the best results.  
Figure 7: Visual comparison with state-of-the-art glare suppression methods on the NRGD.
## 4 Conclusions  
The absorption properties of monolayer and bilayer graphene on a BSW platform have been studied using near-field optical microscopy technique. To the best of our knowledge, this is the first experimental demonstration of graphene-induced absorption of BSW propagation. The propagation lengths of BSWs for BML and BML+ graphene layers have been compared. The results show that propagation length in the presence of monolayer and bilayer graphene is decreased significantly (approximately 17 times and 23 times shorter, respectively) than the bare multilayer. This is due to the strong absorption of the graphene layer. This study provides an advancement in the direction of the development of BSW-based 2D integrated optical systems, in particular in-plane photodetectors.  
We acknowledge funding from Swiss National Science Foundation (SNSF) (200020_135455), from the Spanish Ministry of Economy and Competitiveness through the \"Severo Ochoa\" Programme for Centres of Excellence in R&D (SEV-2015-0522) and OPTO-SCREEN (TEC2016-75080-R), from the European Union H2020 Programme under grant agreement No. 696656 \"Graphene Flagship\", from Fundacio Privada Cellex, and from Generalitat de Catalunya through the CERCA program.  
[PERSON] performed near-field experiments, far-field experiments, data analysis and wrote the manuscript. [PERSON] performed the deposition of graphene layers on the top of multilayer platform and wrote the fabrication details. [PERSON] contributed to the interpretation of results and preparation of the manuscript. [PERSON]-[PERSON] supported the scientific discussions of the results. [PERSON] supervised the work at Barcelona Institute of Science and Technology. [PERSON] supervised and guided the work at Ecole Polytechnique Federale de Lausanne. The final manuscript is the result of common contributions and discussions. All the authors read and approved the final manuscript.  
The authors declare that they have no competing interests.
# Quantifying Auditory Presence Using Electroencephalography
## 2 Materials and Methods
### Questionnaires  
The questions related to auditory stimuli within the Presence Questionnaire and the SUS Questionnaire were selected and combined into a new questionnaire. The selected four questions were as follows:  
1. Please rate your sense of being in the virtual environment on a scale of 0 to 10, where 10 represents your normal experience of being in a place;
2. During your experience, did you often think to yourself that you were actually in the virtual environment? Please rate it on a scale of 0 to 10, where 10 represents you almost feel you were actually in the virtual environment;
3. How well could you identify sounds? Please rate it on a scale of 0 to 10, where 10 represents you could clearly identify different kinds of sounds;
4. How well could you localize sounds? Please rate it on a scale of 0 to 10, where 10 represents you could easily detect the location of each sound.  
The first two questions were chosen from the SUS Questionnaire. The first question focuses on rating the experience in the virtual environment compared to the real world, and the second question focuses on the subjective feeling of placing oneself in the virtual environment. The last two questions were chosen from the Presence Questionnaire to evaluate the realism of the sound field of the virtual environment. This questionnaire design was similar to [PERSON] and [PERSON]'s study [PERSON] and [PERSON] (1999), where they assessed auditory presence in their experiment with five questions, three to evaluate presence and the other two to evaluate the spatialized sound. In this study, detailed explanations of these four questions were given to the participants during the experiment.  
The final presence score was the sum of the answers to these four questions. As the questions suggest, the higher the score, the more the presence. In this way, the subjective assessment of presence was acquired.
# Design and Simulation of a Vision-Based Automatic Trout Fish-Processing Robot
## 3 Results and Discussion
### Results of Simulation
#### 3.2.1 Selecting the Stepper Motor of the Belly-Cutting Subsystem  
The belly-cutting subsystem is a subset of the machine in which a longitudinal incision is made from the anal fin to the fish head using a rotating blade mounted on the main arm.  
In Figures 17-19 the motion simulation results are presented for the belly-cutting subset. In these figures, the characteristics of the required stepper motor are determined. These characteristics are the required torque for cutting operations, angular velocity, angular acceleration, and energy consumption in three feeding rates. In these figures, blue dotted, green dashed, and red solid are the components in X, Y, and Z directions.  
Figure 16: Fish movement at different jack speeds.  
Figure 17: Results of ADAMS software simulation to determine the motor characteristics of the belly-cutting subset (4 fish per minute). In this figure, (**a–d**) are torque, angular velocity, angular acceleration, and required power respectively.  
Figure 18: Results of ADAMS software simulation to determine the motor characteristics of the belly-cutting subset (seven fish per minute). In this figure, (**a–d**) are torque, angular velocity, angular acceleration, and required power respectively.  
As shown in these figures, the angular velocity and acceleration around the \(Z\)-axis are maximum. Also, the required energy increases by increasing angular velocity. The maximum torque values in three capacities of 4, 7, and 10 fish per minute were 1.334 N m, 1.378 N m, and 1.431 N m, respectively. Therefore, to select the required stepper motor maximum amount of torque (10 Fish/min) was selected. By considering the design coefficient of 1.25-1.5, the required torque for the stepper motor is in the range of 1.79-2.145 N m. Therefore, a Nema 23 stepper motor (57 PH20-0.2 kg m) stepper motor with a torque 1.96 N m was selected. Considering this stepper motor, a design factor of 1.37 is obtained, which is acceptable for the device operation.  
In Figure 17b\(-\)d the angular velocity, acceleration, and energy consumption are presented, respectively. As shown in these figures, by increasing the fish feeding rate, the blades are about to penetrate the belly at higher speeds, requiring higher velocity and acceleration. As shown in these three figures, the maximum angular velocity, acceleration, and energy consumption are related to 10 fish per minute. Due to the sufficient time interval between the fish grippers, there is enough time to return to its initial position.
## 3 Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Variable** & **\begin{tabular}{c} **Win** \\ **(_n = 22_)** \\ \end{tabular} & **\
\begin{tabular}{c} **Draw** \\ **(_n = 28_)** \\ \end{tabular} & **
\begin{tabular}{c} **Lose** \\ **(_n = 22_)** \\ \end{tabular} & **H** & \(p\) & \(\eta^{2}\) \\ \cline{2-7}  & **M \(\pm\) SD** & **M \(\pm\) SD** & **M \(\pm\) SD** & & \\ \hline Distance covered (km) & 114.28 \(\pm\) 2.71 & 113.09 \(\pm\) 4.71 & 113.76 \(\pm\) 4.16 & 1.471 & 0.479 & 0.021 \\ Goals Scored & 2.18 \(\pm\) 1.01 & 0.79 \(\pm\) 0.57 & 0.50 \(\pm\) 0.60 & 34.584 & 0.001 *+ & 0.487 \\ Goals inside area & 1.50 \(\pm\) 0.86 & 0.64 \(\pm\) 0.56 & 0.41 \(\pm\) 0.59 & 21.186 & 0.001 *+ & 0.298 \\ Goals outside area & 0.45 \(\pm\) 0.74 & 0.11 \(\pm\) 0.32 & 0.05 \(\pm\) 0.21 & 7.509 & 0.023 * & 0.106 \\ Total attempts & 14.82 \(\pm\) 4.70 & 12.14 \(\pm\) 5.16 & 10.45 \(\pm\) 5.10 & 8.016 & 0.018 * & 0.113 \\ Attempts on target & 5.59 \(\pm\) 2.22 & 4.04 \(\pm\) 2.15 & 3.09 \(\pm\) 1.93 & 13.116 & 0.001 *+ & 0.185 \\ Attempts off target & 5.18 \(\pm\) 2.89 & 4.46 \(\pm\) 2.50 & 4.09 \(\pm\) 2.22 & 1.910 & 0.385 & 0.027 \\ Blocks & 3.27 \(\pm\) 2.14 & 3.68 \(\pm\) 2.53 & 4.05 \(\pm\) 1.91 & 1.462 & 0.482 & 0.021 \\ Woodwork & 0.27 \(\pm\) 0.63 & 0.21 \(\pm\) 0.42 & 0.14 \(\pm\) 0.35 & 0.502 & 0.778 & 0.007 \\ Crossbar & 0.14 \(\pm\) 0.35 & 0.04 \(\pm\) 0.19 & 0.09 \(\pm\) 0.29 & 1.635 & 0.442 & 0.023 \\ Post & 0.14 \(\pm\) 0.35 & 0.18 \(\pm\) 0.39 & 0.05 \(\pm\) 0.21 & 2.005 & 0.367 & 0.028 \\ On target outside area & 1.73 \(\pm\) 1.35 & 1.54 \(\pm\) 1.35 & 1.36 \(\pm\) 1.14 & 0.726 & 0.696 & 0.010 \\ Off target outside area & 2.18 \(\pm\) 1.37 & 1.64 \(\pm\) 1.22 & 1.50 \(\pm\) 0.91 & 3.692 & 0.158 & 0.052 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Attacking metrics and their impact on match outcomes. Regarding the distribution metrics analysis (Table 3), winning teams displayed significantly higher numbers of \"Backward Passes Completed\" and showed a tendency towards greater ball possession (with an average of over 53%) and higher passing accuracy. Although the differences in possession and passing accuracy were not statistically significant, the successful teams demonstrated a strategic use of backward passes. These findings suggest that effective ball distribution, particularly through controlled and strategic backward passes, maybe plays a crucial role in achieving match success. The analysis of defensive play metrics revealed significant tendencies among winning, drawing, and losing teams (Table 4). The Kruskal-Wallis tests showed that winning teams recovered significantly more balls (M = 38.91, SD = 5.27) compared to losing teams (M = 34.23, SD = 7.52), with a notable effect size (H = 6.430, \(p\) = 0.040, \(\eta^{2}\) = 0.09057).
# A Novel Multi-Objective Five-Elements Cycle Optimization Algorithm
## 5 Simulation Experiment and Result Analysis
### Parameter Analysis and Comparison Experiments of MOFECO
#### 5.3.1 Comparison of \(L\) and \(q\)  
In MOFECO, the value of \(L\times q\) represents the size of the population. Intuitively, large \(q\) is beneficial to maintain the diversity of solutions, while large \(L\) is beneficial to search good solutions faster but may easy to fall into local optimum. Reference [20] compares the effects of different \(L\) and  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Values** \\ \hline \(N\) & 100 \\ \(T\) & 1000 \\ \(L\) & 5 \\ \(q\) & 20 \\ \(r_{1}=r_{2}\) & 1 \\ \(\omega\) & 0.5 (for bi-objective MOPs); 0.4 (others) \\ \(\sigma_{1}\) & 0.1 \\ \(\sigma_{2}\) & 1 \\ \(\sigma_{3}\) & 1 \\ \(P_{m}\) & 0.01 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Experimental parameters.  
It can be seen from the above results that there are significant differences in those groups of different settings of \(L\) and \(q\). As shown in Table 3, some test functions have the best \(GD\) values when \(L=20\), which means a larger \(L\) value can bring better convergence; but for most functions, the MOFECO algorithm has the best convergence when \(L=5\). From Table 5 we can see that, for some test functions, especially the tri-objective functions, MOFECO has better values of \(SI\) when \(L=4\) and \(q=25\). However, considering the comprehensive performance index \(IGD\) (see Table 4), most functions have the best comprehensive performance when \(L=5\), \(q=20\). Therefore, for most of time, we recommend setting \(L=5\) and \(q=20\).