esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
### Stabilization of Graphite
#### 4.1.5 Impact of Dispersant on Final Cell Performance  
The qualification of electrode dispersions is subject to a conflict of objectives. On the one hand, the electrode dispersions are to be adapted to the inkjet printing process. The aim is to fully exploit the advantages that result from the change in production process and the associated design freedom, such as design integration and possibilities for individualization [47]. On the other hand, the electrical competitiveness compared to conventional state-of-the-art compounds has to be ensured. Therefore, the amount of inactive materials, such as additives, in an electrode dispersion has to be as low as possible. This also applies to the addition of acids or alkalis, even if the amount is marginal. The results showed that, for the examined graphite dispersions, no addition is required, as the dispersions were stable throughout the entire investigated pH value range. This demonstrates that the stability of the analyzed graphite dispersions with PVP is not highly influenced by the pH value.  
PVP has a hydrophilic and hydrophobic tail group. Thus, it exhibits both polymer and dispersant properties. Because of these characteristic properties, PVP can also inherit the function of the binder, which is indispensable for adhesion and cohesion in an electrode. In various studies, binder materials that are based on PVP have already been successfully used in conventional electrode production [48; 49; 50]. In addition, it is expected that the PVP content can be further reduced by using spheric instead of flaky nanoparticles due to the significantly smaller specific surface area (BET).
# Towards Lunar In-Situ Resource Utilization Based Subtractive Manufacturing
###### Abstract  
In recent years, space agencies, such as the National Aeronautics and Space Administration (NASA) and European Space Agency (ESA), have expanded their research activities in the field of manufacturing in space. These measures serve to reduce limitations and costs through fairing size, launch mass capabilities or logistic missions. The objective, in turn, is to develop technologies and processes that enable on-demand manufacturing for long-term space missions and on other celestial bodies. Within these research activities, in-situ resource utilization (ISRU) and recycling are major topics to exploit local resources and save transport capacity and, therefore, costs. On the other hand, it is important to carefully consider which items can be brought and which must be manufactured on the Moon. Consequently, on-demand needs in future space missions are considered regarding frequency, raw material and required manufacturing processes according to investigations by ESA and NASA. In conclusion, manufacturing in space state-of-the-art shows a strong focus on additive processes, primarily considering semicrystalline or amorphous plastics. The subtractive processing of metallic or ceramic materials, in turn, currently represents a research gap. Consequently, an approach for in-situ resource utilization-based subtractive manufacturing in space is presented to supplement the existing processes. The latter uses a high-pressure jet of water, with regolith simulate as abrasive in suspension, being directed at the workpiece, which is moved to separate metal and glass. Proof-of-concept results are presented, including suitable process windows, achieved cutting geometries, as well as the effects of parameter variations on the system technology and consumables used. The focus of the investigations supplements the general requirements for the design of machine tools for space applications with inertial process-specific boundary conditions as a step towards higher technology maturity.  
in-situ resource utilization (ISRU); subtractive manufacturing; in-space manufacturing +
Footnote †: journal: Applied Sciences  
0
Footnote 0: Copyright** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)]([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/))).
# Enhanced Hybrid Algorithms for Inverse Problem Solutions in Computed Tomography
## 3 Description of Optimization Algorithms
### The Hybrid Algorithm  
The hybrid algorithm considered in this paper is a combination of a metaheuristic algorithm with a deterministic one--in this instance, an ABC algorithm is connected with either the Nelder-Mead method or the Hooke-Jeeves method, respectively. The functioning of the hybrid algorithm is as follows: The metaheuristic algorithm searches for an approximate solution with a limited population size and number of iterations. The solution found by the metaheuristic algorithm is then used as the starting point for a deterministic algorithm. This approach aims to eliminate the limitations of both types of algorithms. Metaheuristic algorithms tend to slow down the decrease in the fitness  
Figure 4: Hooke–Jeeves algorithm’s block scheme.  
function's value as their iterations progress. As a result, metaheuristics often require a significant amount of time to provide satisfactory results. On the other hand, deterministic algorithms can often deliver satisfactory results in a short time; however, achieving this requires a good starting point, which is often unknown in many cases. The hybrid approach aims to minimize the time required while maintaining the quality of the solution found, compared to a metaheuristic approach that runs for a significantly longer period.  
The deterministic algorithm may require more than one point to be used; in that case, additional points should be generated either by running the metaheuristic algorithm multiple times to provide the required amount of points. Otherwise, additional points can be created by modifying the original point--that is the approach used in this paper while deploying a hybrid approach with the Nelder-Mead algorithm.  
While the Hooke-Jeeves algorithm requires only a single solution as a starting point, the Nelder-Mead method requires a simplex, as described in the Section 3.3. We decided to create such a simplex by combining the original point with the points created using the following formula:  
\[x_{i}=\left(x^{(1)},x^{(2)},\ldots,x^{(i)}+0.05\cdot\left(ub^{(i)}-lb^{(i)} \right),x^{(i+1)},\ldots,x^{(k)}\right),\;\;i=1,2,\ldots,k \tag{25}\]  
where \(k\) is the number of dimensions of the task, \(x=(x^{(1)},x^{(2)},\ldots,x^{(k)})\) is original solution found by the metaheuristic algorithm, and \(ub,lb\) are upper and lower boundaries of the task. Equation (25) can be summarized by saying that, for the \(k\)-dimensional task, additional \(k\) points are generated, with each of them being the same as the original point but with one dimension shifted by 5% of the search space for a given dimension.
## 3 Model Description
### Maintenance Situation Description  
To reduce the probability of equipment failure in the production process, each unit of the system is detected at the end of each production lot size \(Q\). The appropriate maintenance strategy is determined according to the unit state and the structural characteristics of the unit. In the proposed system, due to the parallel relationship between unit 2 and unit 3, when only unit 2 or unit 3 fails, the whole system is still in regular operation at this time, and there is no need for a maintenance operation. Considering different operations at the end of the cycle, the system has the following twenty-three situations shown in Figure 5. In Figure 5, \(N\) represents no maintenance, \(P\) represents preventive maintenance, \(C\) represents corrective maintenance, and the subscript \(i\) represents unit \(i\). For example, \(P_{1}C_{2}\) represents that unit 1 needs preventive maintenance, unit 2 needs corrective maintenance, and unit 3 does not need maintenance.  
According to Figure 5, the probability of each maintenance situation can be calculated. For example, the situation \(N\) contains three areas. The first is \(\left\{(x_{1},x_{2},x_{3})\middle|x_{1}\in\left[0,D_{p}^{(1)}\right),x_{2}\in (0,\infty),x_{3}\in\left[0,D_{p}^{(3)}\right)\right\}\), in which the system can maintain regular work and does not need maintenance regardless of the state of unit 2. The second is \(\left\{(x_{1},x_{2},x_{3})\middle|x_{1}\in\left[0,D_{p}^{(1)}\right),x_{2}\in \left[0,D_{p}^{(2)}\right),x_{3}\in\left[D_{p}^{(3)},D_{f}^{(3)}\right)\right\}\), in which the system is regular even if the state of unit 3 exceeds the preventive maintenance threshold. Similarly, the third is \(\left\{(x_{1},x_{2},x_{3})\middle|x_{1}\in\left[0,D_{p}^{(1)}\right),x_{2}\in \left[0,D_{p}^{(2)}\right),x_{3}\in\left(D_{f}^{(3)},\infty\right)\right\}\). Its probability is described as  
\[p(N)=\int_{0}^{D_{p}^{(1)}}\int_{0}^{\infty}\int_{0}^{D_{p}^{(3)}}s(X)dx_{1} dx_{2}dx_{3}+\int_{0}^{D_{p}^{(1)}}\int_{0}^{D_{p}^{(2)}}\int_{D_{p}^{(3)}}^{D_{ f}^{(3)}}s(X)dx_{1}dx_{2}dx_{3}+\int_{0}^{D_{p}^{(1)}}\int_{0}^{D_{p}^{(2)}} \int_{D_{p}^{(3)}}^{\infty}s(X)dx_{1}dx_{2}dx_{3}. \tag{12}\]  
Figure 5: Division of maintenance situations.  
Similar to Equation (12), the probability of each situation can be calculated to prepare for modeling.
## Characteristics and Selection of Near-Fault Ground Motions  
### Characteristics of Near-Fault Ground Motions  
Currently, the area within 20 km from the fault rupture surface is regarded as a near-fault field in this study. Because of the directivity effects, fling step effects, and hanging wall/footwall effects contained in the near-fault earthquakes, near-fault seismic records and far-fault records have significantly different characteristics [36; 37].  
When the rupture is exactly on the fault toward the site, and the ruptured velocity is close to the S wave velocity, the directivity effects occur. Researchers classify the directivity effects as forward directivity effect, neutral directivity effect, and reverse directivity effect. Among them, the forward directivity effect is due to the accumulation of energy in front of the propagating rupture, which tends to aggravate the damage of the infrastructures, therefore, the directivity effect usually refers to the forward directivity effect. The seismic records with the directivity effect can be seen as a bidirectional velocity pulse at the beginning with obvious characteristics of long-period and short duration [36], as shown in Figure 1.  
The relative movement of two plates of fault produces the static deformation field, and there is a permanent ground displacement [38] in the time history curves of displacement near the fault, which is called the fling step effect. This permanent ground displacement causes a single pulse of velocity, which is generally parallel to the fault. The hanging wall/footwall effect refers to the phenomenon that the site located in the hanging wall is closer to the fault than the site located at the same distance from the footwall, and therefore the ground motion amplitude of the hanging wall is larger.  
This paper mainly studies the pulse ground motions caused by the directivity effect which aggravates the structural damage.
## 3 System Model and Security Goals
### IoT-Based System Model
#### 3.1.3 IoT-Based Sensor Nodes  
Sensor nodes are low-power equipment that performs restricted computation and communication processes. IoT-enabled sensor nodes collect and transmit the real-time data of the patients. Sensor nodes connect to the server through the wireless access point.
# Attention Transfer Reinforcement Learning for Test Case Prioritization in Continuous Integration
## 8 Conclusions  
ATRL-TCP is a TCP technique specifically designed for CI. Its core innovation lies in the analysis of feature information from the test case set to be prioritized, dynamically adjusting the prioritization strategy based on the richness of the available information. By integrating diverse information sources and learning from reward signals, ATRL-TCP achieves enhanced stability and performance. Unlike existing prioritization strategies, ATRL-TCP can dynamically shift its attention based on dataset characteristics, enabling a more comprehensive consideration of information during prioritization. This prevents the model from being misled by individual test case features into local optima.  
Experimental results demonstrate that ATRL-TCP outperforms existing methods such as RETECS and PRM across four different datasets. As the CI cycles increase, the model receives more feedback, further improving its performance. These findings indicate that the proposed approach exhibits strong generalization capabilities across diverse CI scenarios. In addition, this study explores the impact of historical information and error rates on model performance. The evaluation of execution efficiency demonstrates that ATRL-TCP is an efficient and competitive TCP technique.  
Future work: Although the proposed method shows strong generalization, feature extraction from test cases is still limited. We plan to expand our research by incorporating additional information, such as code changes and defect severity, to improve the TCP strategy. Additionally, we aim to explore relationships between different projects or software versions, which may reveal patterns or dependencies in cross-version testing. This could lead to applying transfer learning to guide TCP, using knowledge from one project or version to enhance prioritization in others.  
Conceptualization, Q.S. and Y.Y.; methodology, Q.S. and Y.R.; validation, Q.S., X.L. and Y.Y.; investigation, Q.S.; resources, Q.S.; data curation, Q.S.; writing--original draft preparation, Q.S.; writing--review and editing, Y.R.; visualization, X.L.; supervision, R.Q. and C.H.; project administration, Q.S. All authors have read and agreed to the published version of the manuscript.  
This research is supported by the National Key R&D Program (Grant #2022 YFB4501904).  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors are grateful to the Beihang University.  
The authors declare no conflicts of interest.
# Review of Dew Point Evaporative Cooling Technology for Air Conditioning Applications
## 4 Dew Point Evaporative Coolers Research
### Experimental Studies of DPICE Performance
[PERSON] [15] performed the water-absorbing experiment, considering few that may be used to form a heat and mass exchanger. The heights of capillary rise for textile fiber (with rough and smooth surface), kraft paper (waxing, aluminum coating), non-woven fabric, and aluminum film were measured. The aluminum-coated kraft paper achieved the highest values of capillary rise, equal to 13 cm after 120 min. The rather new study of appropriate materials for creating wet channels in indirect evaporative coolers was performed by [PERSON] et al. [16]. They experimentally examined a few different fabrics (textiles) and compared them to Kraft paper a few different fabrics (textiles). The results allowed them to establish the two most suitable fabrics for the construction of indirect evaporative coolers. Those are Coopass(r) bird eye mesh fabric and Bamboo charcoal(r)+Coolmax. Evaporative cooling materials are mostly studied for application in direct evaporative coolers. [PERSON] et al. [17] experimentally studied the selected organic cooling pads like eucalyptus fibers (EF), ceramic pipes (CP), yellow stone (YS), dry bulrush basket (DBB), and Cyprus marble (CM). They found the cooling effectiveness of EF and CP to be the highest. It was underlined that the materials analyzed are locally available and the advanced machinery is unneeded to produce it. [PERSON] et al. [18] investigated two different cooling pads, curtain fabric and raw cotton fabric, as an evaporative cooler filling. The results show that certain fabrics allow lower supply air temperatures to be obtained. [PERSON] [19] tested three natural fibers (palm fibers, jute, and luffa) for direct evaporative cooling, the performance of which was compared to the commercial wetted pad. They analyzed a few performance indicators, which were: cooling efficiency (jute achieves the highest); material performance (commercial wetted pad has the highest sale deposits); and cooling efficiency degradation (luffa has the lowest). It was found out that luffa and jute (after treating the surface to obtain higher mold resistance) may be chosen as a wetted pad alternative solution. Due to nozzles, the exchanger becomes complicated [12]. Additionally, the hydrophilic coating needs to be ensured [20], therefore commercially available porous materials are still being improved. In Table 2 selected studies in which experiments were conducted are summarized.
# A Secure and Scalable Authentication and Communication Protocol for Smart Grids
## 5 Results
### Discussion on Smart Grid Security Standards and Real-World Applicability  
To ensure our proposed protocol complies with smart grid security standards, we evaluated its cryptographic overhead on high-performance (Core-i7) and resource-constrained (ESP32) hardware. The results indicate that while computational efficiency varies between these platforms, the protocol is sufficiently feasible for low-power embedded devices typically utilized in smart grid environments. This aspect is particularly important, given that a smart grid embodies edge devices such as smart meters, sensors, and remote terminal units (RTUs) with limited processing capabilities. Additionally, our protocol conforms to the fundamental principles of the IEC 62351 protocol, which serves as the security standard for power system communication. The incorporation of ECDSA for authentication, ECDH for secure key exchange, and AES-256 for encryption combined with HMAC for data confidentiality and integrity, respectively, is consistent with the requirements outlined in IEC 62351-3 (secure transport), IEC 62351-5 (SCADA security), and IEC 62351-8 (role-based authentication). Given that IEC 61850-based systems often necessitate lightweight yet secure cryptographic implementations, our findings suggest that the proposed protocol can seamlessly integrate into smart grid infrastructures with minimal computational overhead. By demonstrating its adaptability to real-world constraints, our study offers a scalable and secure solution for authentication and communication within smart grid systems.
# A Novel Soft Robotic Exoskeleton System for Hand Rehabilitation and Assistance Purposes
## 2 Development of the SEG Device
### Description of the Employed Soft Actuator  
One of the most crucial elements for SEGs is the utilization of soft actuators due to the fact that they perform the necessary movement in the SEG configuration. For the purposes of this work, a previously developed soft robotic actuator was utilized based on research from a previous study [28]. In that research, the processes of design, development, and fabrication were presented in-depth. More specifically, the employed actuator is a soft actuator fabricated with silicone rubber compound and reinforced with Kevlar fiber. Moreover, the kinematics of this actuator was designed to imitate the locomotion of earthworms, such as Lumbricus Terrestris [29; 30; 31]. Thus, it has a double half-tubular structure configuration, which enables a potential angular range from \(-180\) to \(180\) degrees (extension to flexion). Furthermore, the overall structure of the actuator was developed to be comparable to an average human finger in terms of dimensions and offer multiple degrees of freedom (DoF) in order to reproduce the physical movement of a human finger (i.e., two DoF for the thumb and three DoF for the rest). However, the comprehensive advantage of this actuator is the modular 3D-printed external cover. To elaborate, the soft actuators were assembled with 3D-printed rings constructed by rigid polymer (i.e., PA12), enhancing the structural integrity of the object and allowing the free extension/flexion motion of the actuator. Moreover, the existence of the rings could offer physical constraints to avoid the undesired angles depending on the rings' geometry and reinforce the safety of the SEG. Finally, the last advantage of the proposed actuator is the integration of a one-axis soft flex sensor inside the actuator's structure, providing real-time data for the motion and position of the actuator. The motion of the actuator is performed through the pressured air inside the half-tubular structures, with each structure inflated for each motion direction; for example, for bending movement, the upper half-tubular structure is inflated. Therefore, the actuator's motion could be fully controllable with an electro-pneumatic control system. Figure 3a,b show the 3D design and physical model of the actuator's silicone rubber double half-tubular core. Also, Figure 3c portrays the configuration of the developed actuator for the SEG application.
# A Portable Non-Motorized Smart IoT Weather Station Platform for Urban Thermal Comfort Studies
## 4 Efficiency and Performance of the Proposed Weather Station Platform
### Test 4: Data Sampling Rate  
This section examines the time interval between two consecutive measurements using the server time.  
Figure 10 illustrates the distribution of time intervals between consecutive data sets under two scenarios and across all chosen locations, showing the minimum, maximum, mean, and median values. Overall, irrespective of the scenario and location, the developed edge device prototype can measure data at an average interval of 5 to 7 s. The variations in the selected locations under the two scenarios might be due to changes in environmental conditions and variations in cellular reception.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Scenarios**} & \multicolumn{6}{c}{**‘On the Move’**} & \multicolumn{6}{c}{**‘Stop and Go’**} \\ \cline{2-9}  & **Part 1** & **Part 2** & **Part 3** & **Part 4** & **Part 5** & **GCU to** & **M8 to** & **M8 to** & **Residential** & **Commercial** \\ \hline Mean & 1.3 & 1.0 & 1.5 & 2.9 & 2.9 & 1.9 & 2.8 & 2.5–2.9 & 2.5–2.7 \\ \hline Min & 0.1 & 0.6 & 0.4 & 0.4 & 0.6 & 0.3 & 0.4 & 0.3–0.7 & 0.3–0.8 \\ \hline Max & 4.6 & 2.4 & 4.1 & 6.5 & 4.6 & 5.5 & 6.9 & 4.3–8.7 & 4.0–7.8 \\ \hline Std & 1.1 & 0.4 & 1.0 & 1.0 & 0.9 & 1.1 & 0.8 & 0.8–1.3 & 0.8–1.1 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Latency test results with minimum, maximum, mean, and standard deviation values for the selected location under the two scenarios.