esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussion
The best design to reduce the surface fatigue index is the wheel design with optimized fatigue, and is followed by the wheel design with optimized wear and fatigue, wheel design with optimized wear, and the existing wheel design in the order listed. The surface fatigue indexes of the wheel designs with optimized fatigue, optimized wear and fatigue, and optimized wear have been reduced by 65.8%, 52.8%, and 17.9% respectively. As the shape of the wheel flange where a contact occurs in a curved section is smoother than that of the existing profile, lateral pressure is reduced in the case of the optimized wheel profile. Therefore, Figure 15 shows the derailment coefficients of wheel profiles, and that the derailment coefficients of the optimized wheel profiles have been reduced by approximately 13% when compared to that of the existing wheel. Figure 6:5 Wear number of wheel profile. As shown in Figure 16, the lateral displacement of the wheel shaft with optimized wheel profile after it has passed through a curved section is almost the same as that of the existing wheel. Accordingly, we can say that there is no change in the stability of the railway vehicle. The wear number, surface fatigue index, derailment coefficient, lateral pressure, and vertical force as the results of the optimization are put in order and shown in Figure 6:6  
The inclination of the optimized profile is less steep that that of the existing profile. The lateral pressure has decreased and the vertical force has increased minorly. Figure 6:7 Surface fatigue index of wheel. Figure 6:8 Derailment quotient of wheel.
# Implementation and Evaluation of a Serious Game for Working Memory Enhancement
## 5 Results
### Enjoyment  
The same approach was followed regarding the EGameFlow questionnaire [42], and for each of the eight dimensions (concentration, clear goal, feedback, challenge, autonomy, immersion, social interaction and knowledge improvement) we also calculated descriptive measures of central tendency where the mean value was the most significant one. We calculated the mean values for each Likert-type item. The mean values of the eight dimensions are presented in Figure 7.  
As indicated by the results of the analysis, the players' opinions were positive, since the mean value for the \"Concentration\" dimension is 4.96. Furthermore, a mean value of 5.91 for the \"Clear Goal\" dimension and a mean value of 4.65 for the \"Feedback\" dimension were awarded. Moreover, the mean value for the \"Challenge\" dimension is 4.25, while for the \"Autonomy\" dimension it is 4.06. It could be deduced that the game offers social interaction and immersion since the mean values are 3.7 and 3.07, respectively, but this kind of game does not include interaction between users and immersion is low by design. Furthermore, players believe that the game improves their knowledge since the mean value is 4.32.  
Figure 6: USE questionnaire mean values.  
Figure 7: EGameFlow questionnaire mean values.  
The users' answers to the open-ended questions revealed positive and negative issues:  
* Easy to use
* Does not require any previous knowledge
* Helps in WM improvement  
* Slow pace/progress
* Too many steps before changing level
* Difficulty should be more adjustable  
Overall, most participants reported that they were motivated by WM improvement and they were willing to complete that goal. They also took the whole process seriously towards this direction. The game was easy for them to use and they familiarized with the environment immediately. Yet, due to the fact that most of them were in a good status regarding WM, they often found the progress of the game very slow, thus they started feeling bored until they moved to the next level which was more challenging.
# The Antimicrobial Effectiveness and Cytotoxicity of the Antibiotic-Loaded Chitosan: ECM Scaffolds
## 2 Materials and Methods
### Measurement of Antimicrobial Activity Duration  
To test the duration of the antimicrobial activity of the chitosan:ECM scaffolds with and without antibiotics, 6 mm discs of each scaffold were incubated for up to 24 h in 500 uL of tryptic soy broth, with the supernatant being collected at 1, 2, 3, 4, 8 and 24 h. At each timepoint the entire 500 uL volume was collected and replaced with fresh tryptic soy broth. Thus, each time point represents the release of antimicrobial components between these time points and not the accumulated concentration over time allowing the duration of antimicrobial effectiveness to be measured. Two assays were used to measure the antimicrobial duration a growth kinetic assay and an agar well diffusion assay.  
To perform the growth kinetic assay, log phase aliquots of either _Staph. Aureus_ (ATCC 29213) and _E. Coli_ (ATCC 25922) were prepared at a density of \(3\times 10^{8}\) CFU/mL and 100 uL was added to the well of a 96-well plate. To each bacterial culture, 100 uL of chitosan:ECM scaffold supernatant was added and mixed thoroughly. The plate was then incubated at 37 \({}^{\circ}\)C for 18 h with absorbance at 600 nm measured every 20 min using a Spectramax M2 plate reader (Molecular Devices, San Jose, CA, USA). Bacterial aliquots supplemented with 100 uL tryptic soy broth were used as positive controls for bacterial growth while tryptic soy broth alone was used as a negative control. All assays were completed in triplicate. The natural log of the absorbance was calculated and used to plot growth curves for each experimental group. The slope of the curve over the exponential growth phase was calculated by linear regression. Where no exponential growth was seen the slope was calculated over the entire 18 time period and slopes that were not significantly different from zero were assumed to show no growth while slopes that were significantly different were assumed to show bacterial growth that did not reach the exponential phase. The lag time was calculated by extrapolating the growth rate line back to the initial ln OD value at time zero.  
The agar well diffusion assay was performed in a similar way to the Kirby-Bauer antibiotic sensitivity test. In this case, tryptic soy agar plates (100 mm) were prepared by as before with tryptic soy 100 uL of bacterial suspension (\(1.5\times 10^{8}\) CFU/mL) spread across the plate to form a lawn culture. Using a sterile 6 mm biopsy punch a core of agar was removed from the plate creating a well. The wells were placed on the plate using a template to ensure 24 mm center to center spacing between each well. To each well 100 uL of chitosan:ECM scaffold supernatant was added, and the plates were then cultured overnight at 37 \({}^{\circ}\)C. Soluble antimicrobial agents diffused into the agar from the well creating a zone of inhibition which was then measured using calipers. Each combination of scaffold was tested in triplicate and the average zone of inhibition calculated.
# Enhancing Efficiency of Electromagnetic Simulation in Time Domain with Transformation Optics
## 5 Results from 1D and 2D Non-Uniform Grids and Their Efficiency
To analyze the increasing rate of the computational cost due to cell resolution, the \(C\) for the cases of uniform grids and non-uniform grids as functions of cell sizes are shown in Figure 6. Two power functions are used to fit the curves. According to the results, we obtain that the increasing rates are the cell size ratio to the power of \(-3.55\) and \(-1.86\), respectively. For the uniform cases, the power term being close to \(-4\) is expected since the FDTD algorithm deals with both the space (three dimensions) and time (one dimension); all the numbers of cells in the three directions and also the number of time steps increase proportionally with the inverse of cell size. On the other hand, for the non-uniform cases, the cost is increased mainly due to the cell number only in the \(x\) and \(z\) directions; although the \(S\) becomes lower when the cell size is smaller than 2.5 nm, the iteration time in one time step is reduced more than that in the uniform case (because the cell number is reduced). Therefore, we obtain that not only the cost is always lower than that in the uniform case with the same cell resolution, but the increasing rate is also two orders slower. Figure 6: Computational cost \(C\) from the cases of uniform grids vs. cell size (blue dots) and the cases of non-uniform grids vs. central cell size (red dots), respectively, and the curve-fitting power functions for the cases of uniform grids (blue dashed curve) and the cases of non-uniform grids (red dashed curve), respectively. Real metals, such as gold or silver, are usually considered dispersive mediums and their optical properties can be described with the Drude model, as indicated in Equation (10). However, the plasma frequency is close to the wave frequency of the optical regime and the damping coefficient is not negligible. Since sub-wavelength structures in real metals could exhibit enhanced transmission due to the excitation of surface plasmons [1], a sub-wavelength aperture in a real metal film associated with the properties is often considered for the more extensive purposes [37]. Since the metals are dispersive, the simulation of the EM wave interaction with the metallic structures requires the auxiliary differential equation, as shown in Equation (11), in the EM field updating scheme. With the proposed coordinate-transformation method for the simulation with non-uniform grids, the dispersive medium becomes anisotropic. Although the metal film in our current study is PEC, we have already employed an artificial dispersive medium with sufficiently high plasma frequency and zero damping coefficient to approximate the film (see Section 3), and obtained the accurate transmission spectrums with efficiency. Because the implementation for the real metal films is the same, we believe that this method should also be valid in the study of the light transmission for the case of real metals with accuracy and efficiency.
# TAB Series-Resonant DC-DC Converter and Multi-Phase-Shift Based Global Optimization Modulation
## 1 Introduction
While the structural coupling of the three-port converter causes the control variables of each port to be interactive. The two equivalent two-port converters are likely to have different optimal operating points of the control variables on the common port when the range of the voltage and transfer power is different. Hence, it is important to propose a unified global optimization modulation based on the multiple controllable variables. It is helpful to reduce power loss and increase efficiency. In this paper, a topology-level power decoupling TAB converter and its optimized multi-phase-shift modulation are proposed. The innovation and contribution are below. (1) In terms of the topology, a topology-level power decoupling TAB isolated resonant dc-dc converter is proposed in this paper. A resonant capacitor is added to the three-winding transformer to realize the power decoupling at the topology level. The converter realizes the power decoupling only by setting the hardware parameters and without adding an additional controller. Hence, the decoupling effect of the converter is improved and the complexity of the control system is significantly reduced. (2) Meanwhile, different from the inductor-type topology, the energy storage component of the proposed converter is the series-resonant tank, which significantly reduces the current stress and increases the utilization rate of the hardware. (3) In terms of the modulation, the existing TAB converters generally use the single-phase-shift modulation. In this paper, the optimized multi-phase-shift modulation for the TAB converter is proposed. With the increase of the controllable degree of freedom, the performance of the converter is correspondingly improved. On this basis, the RMS value of the transformer current is minimized and the power loss in the entire voltage and power range is accordingly reduced, thus ensuring the high efficiency of the converter.
# The Architecture of the Access Protocols of the Global Infocommunication Resources +
## 4 Discussion
In turn, the AD on the terminal device side supports the standard interface, and on the base station side all the interfaces of available radio networks. Advantages of the proposed centralized approach to selecting the last mile access radio network:  
- Simple and inexpensive terminal devices--less stringent requirements for hardware and software resources of terminals than with a decentralized approach;  
- The volume of service traffic is less than in the case of a decentralized approach;  
- As terminal devices can be not only smartphones (people), but also smart things;* Corresponds to the national 5G launch programs, which involve: combining the resources of Telecom operators in the last mile, forming telecommunications ecosystems, and focusing on simple and inexpensive terminals [17];
* Meets the requirements for future infocommunications formulated in the Future Network concept of IEEE 3001 [18].
# Numerical Simulation of the Influence of the Baihetan Reservoir Impoundment on Regional Seismicity
###### Abstract  
The Baihetan Reservoir is built for hydropower in China. The rise of the reservoir water leads to a series of earthquakes in the surrounding area. This study proposes fully coupled equations of pore-viscoelasticity and a parallel partition mesh model to study the short- and long-term effects of the Baihetan Reservoir and further calculate the changes in stress, pore pressure, and Coulomb failure stress with time on the major faults. Based on the calculation results, impoundment increases regional seismicity, which is consistent with the seismic catalog. The reservoir impoundment causes an increase in pore pressure in the crust, primarily enhancing Coulomb failure stress beneath the reservoir center. This effect extends to approximately 60 km in length and 20 km in width at a depth layer of 5-10 km. Seismicity varies greatly among different faults. Coulomb failure stress increases on the northern part of the Xiaojiang Fault and Zhaotong-Ludian Fault, and decreases on the southern part of the Xiaojiang Fault and Zemuhe Fault. The Coulomb failure stress is highly correlated with the number of earthquakes along the Xiaojiang Fault. The influence of the reservoir on the local seismicity is mainly limited to several months, and it has a slight effect later on. The focal depth of the induced earthquakes increases while the magnitude decreases. The earthquakes caused by the impoundment all have a small magnitude, and the \(M_{\rm s}\)4.3 Qiaojia earthquake on 30 March 2022, was more likely a natural event.  
reservoir; pore-viscoelasticity; finite element numerical simulation; coulomb failure stress; seismicity
## 5 Result and Discussion
### Efficiency Comparison  
The efficiency of the IMs can be gauged by comparing the dispersion \(\beta_{D\,|\,IM}\) obtained from the PSDMs shown in Equation (3). The lower value of dispersion, the more efficient IM is. While considering max acceleration as demand parameter, EDA, A95, PGA, ASI and SMA are considered more efficient measures since they have lesser dispersion \(\beta_{D\,|\,IM}\) (Figure 8) than other IMs and all of these top five IMs are acceleration-type IMs. EDA, A95, and PGA are the three most efficient IMs with the value of dispersion 0.247, 0.254, and 0.256, respectively.  
However, HI > VSI > \(S_{v}\) (\(T_{1}\)) > \(S_{a}\) (\(T_{1}\)) > \(S_{d}\) (\(T_{1}\)) > PGV > SMV top the ranking of the most efficient while considering max displacement as EDP. Apart from \(S_{a}\) (\(T_{1}\)) and \(S_{d}\) (\(T_{1}\)), all are velocity-type IMs. HI and VSI are the two most efficient IMs (max disp. as EDP) with 0.290 and 0.312, respectively. D\({}_{\rm rms}\), PGD and PGV/PGA are the three least efficient IMs for both cases of EDP. Two of them, PGD and D\({}_{\rm rms}\) are displacement-related IMs.
# FSM-BC-BSP: Frequent Subgraph Mining Algorithm Based on BC-BSP
## 3 Proposed Method
### Overall Design
Utilizing the hash, vertices with the same key are grouped together, and the value within each group undergoes an extension of graph information. By extending the k_subgraphs, candidate (k + 1)_subgraphs are derived. To obtain the specification encoding of the candidate (k + 1)_subgraphs, hashing is again performed according to the specification encoding. The remainder of the vertex is identified, and this information is sent as part of the message. This iterative process ensures the systematic generation of candidate frequent multi-subgraphs, effectively building upon the results of the previous stages. 4. In the third iteration, the focus shifts to frequent counting, culminating in the identification of frequent subgraphs. When a vertex receives messages from the previous super step, these messages contain the same specification encoding intended for that vertex. However, due to potential hash conflicts, a vertex may receive messages with multiple different specification encodings. Consequently, each vertex must process these received messages by regrouping them based on the differences in the specification encoding. To address this, messages can be regrouped through rehashing, and, subsequently, frequent counting is performed within each group. This entails applying the MNI support calculation method for frequent counting. If the frequency counts surpass a predefined threshold, the pertinent information is stored in the HDFS. Following the frequent counting phase, hash coding is applied to the specifications of the identified frequent subgraphs. The resulting hash values correspond to the IDs of specific vertices, and this information is transmitted through messages. This iterative process ensures the systematic identification and storage of frequent subgraphs meeting the specified support threshold. The iterative process involves \(2n\) super steps, aligning with the second iterative step for the generation of candidate subgraphs. The subsequent \(2n+1\) super step process aligns with the third iterative step, involving the calculation of support for candidate subgraphs. This iterative cycle continues until the specified number of iterations is reached or no more frequent subgraphs are generated. The systematic and consistent execution of these super steps ensures the effective generation and evaluation of candidate subgraphs, leading to the identification and storage of frequent subgraphs that meet the specified support threshold. This iterative approach allows for flexible and scalable adaptation to different graph mining scenarios and ensures the comprehensive exploration of the graph data.
## 3 Case Study
### Feature Selection  
In the NBI data, numerous features correlate with bridge conditions, but not all data are necessary for the feature selection database. In this study, bridge feature data are selected based on prior research, which includes the basic structural information of the bridge, traffic volume, and bridge age, as shown in Table 1. The detailed descriptions of these features can be found in Ref. [19]. Since the study addresses bridge deterioration over time and does not account for maintenance and reconstruction measures during the operational phase, the features for bridge reconstruction and structural rehabilitation lengths are set to 0, indicating that no maintenance or reconstruction measures have been taken for these bridges. Existing studies have concluded that these feature sets are closely related to the future condition rating of the bridge, and a modified Relief algorithm was used to determine the appropriate feature sets.  
A Pareto chart illustrating feature importance is shown in Figure 4, which indicates the degree of influence of features on bridge condition. It can be seen that bridge age, average daily truck traffic, material type, and skew have a significant effect on bridge condition. In contrast, the number of approach spans does not have a significant effect.  
\begin{table}
\begin{tabular}{l l l l} \hline
**No.** & **Bridge Features** & **No.** & **Bridge Features** \\ \hline
1 & Toll & 11 & Bridge roadway width, curb-to-curb \\
2 & Lanes on the structure & 12 & Deck width, out-to-out \\
3 & Average daily traffic & 13 & Deck structure type \\
4 & Skew & 14 & Type of wearing surface \\
5 & Kind of material & 15 & Type of membrane \\
6 & Type of bridge & 16 & Deck protection \\
7 & Number of spans in main unit & 17 & Average daily truck traffic \\
8 & Number of approach spans & 18 & Future average daily truck traffic \\
9 & Length of maximum span & 19 & Deck area \\
10 & Structure length & 20 & Age \\ \hline \end{tabular}
\end{table}
Table 1: Characteristic values of bridges in the United States.  
When training an Elman neural network, it is first necessary to classify the bridge features. Thus, it is essential to select bridge features that have a significant impact on bridge condition. If too few features are selected, they cannot represent the entire dataset; however, if too many features are chosen, the amount of neural network training data cannot be guaranteed. Therefore, this study will apply the following four different types of feature parameter combinations for Elman neural network training and prediction. The accuracy of the prediction results is shown in Table 2. It can be seen that classifying the data through six features yields the highest prediction accuracy. Consequently, this study will select six features for data classification, as shown in Table 2, including bridge age, average daily truck traffic, type of material, skew, deck structure type, and type of bridge.
# Anomaly Detection Method Considering PLC Control Logic Structure for ICS Cyber Threat Detection
## 4 Experiment and Evaluation  
Section 4 conducts experiments and validation on the proposed anomaly detection method that considers the PLC control logic structure. Section 4.1 describes the PLC control logic dataset used in the experiments. Section 4.2 explains the experimental environment, performance metrics, and models used. Section 4.3 evaluates the proposed method using various performance metrics. Additionally, this section attempts to answer the following research questions.  
* How does the embedding process preserve the structure and context of control logic?
* How does the proposed method detect cyber threats that existing ICS anomaly detection systems fail to identify?
* What makes the proposed method more effective than existing PLC control logic tampering detection studies?