esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Physical Stress  
The HRV parameters from the ECGs were used to assess user stress during task performance under the different instruction methods. Statistical analysis results for all HRV parameters are demonstrated in Table 1. For time domain characteristics, the RMSSD and SD1 were significantly affected by the instruction approach (\(p<0.05\)). The m-RR, m-HR, SDHH, RMSSD, HRV triangular index, TINN, SD1, ApEn, and SampEn were significantly affected by task complexity (\(p<0.05\)). Statistical analysis of the interaction effects indicated that m-RR, m-HR, SDHH, RMSSD, TINN, and SD1 were all significantly different depending on whether the instruction was paper- or AR-based and whether the task was simple or complex (\(p<0.05\)). Figure 14 shows the significant interaction effects of the instruction methods and task complexity on m-RR interval, m-HR, SDHR, RMSSD, TINN, and SD1. The results revealed that for the paper group, performing the complex task resulted in significantly lower m-RR, RMSSD, and SD1 values and higher m-HR, SDHR, and TINN values compared to the simple task. However, using AR-based instruction for either the complex or the simple task did not yield any significantly different results (\(p>0.05\)). Comparing paper-based and AR-based instructions for the complex task showed a statistically significant difference (\(p<0.05\)). Figure 13: The interaction effects of task complexity and instruction method on NASA-TLX subscores. Arrows indicate a greater perceived load. Error bars represent a 95% confidence interval. Columns connected with lines and “**” marks are significantly different from each other. For the frequency domain variables of HRV, task complexity had statistically significant effects on LF, HE, and the LF/HF ratio (\(p<0.05\)). Interaction effects between instruction methods and task complexity significantly influenced LF, HF, and the LF/HF ratio (\(p<0.05\)). Figure 15 shows these interaction effects on LF, HF, and the LF/HF ratio, respectively. Pairwise tests revealed that performing the complex maintenance task using paper-based instruction resulted in higher HF/LF ratios and LF values and lower HF values compared to the simple task (\(p<0.05\)). No significant change was seen in LF, HF, or the LF/HF ratio when using AR-based instruction for either simple or complex tasks (\(p>0.05\)). However, there was a significant difference between AR and paper-based instruction for  
Figure 14: Interaction effects of instruction approaches and task complexity on m-RR interval, m-HR, SDHR, RMSSD, TINN, and SD1. Error bars represent a 95% confidence interval. Columns connected with lines and “**” marks are significantly different from each other. the complex task (\(p<0.05\)), but no significant difference was found for the simple task (\(p>0.05\)).
## 2 Materials and Methods
### Short Chain Fatty Acids Assay  
The amounts of fecal short-chain fatty acids (SCFAs) were measured by solid-phase microextraction coupled to gas chromatography and mass spectrometry (SPME-GC-MS) to evaluate the microbial metabolic activity. Fecal samples (0.1 g) were weighted and suspended into 5 mL of deionized water by vortexing. 1.5 mL of fecal suspension was added into 10 mL vial with 0.5 g of NaH\({}_{2}\)PO\({}_{4}\)[19]. Acetic acid, propanoic acid and butyric acid (Sigma-Aldrich, WGK Germany) were used as external standards in order to control the daily variation of instrument and sample preparation. The SPME fiber used was 75 \(\upmu\)m CAR/PDMS, Fused Silica (Supelco, Bellefonte, PA, USA). The SPME-GC-MS analysis was carried out with Thermo Trace 1310--TSQ 8000 Evo equipped with an autosampler (Thermo Scientific, Wilmington, DE, USA). Compounds were separated by Supelco fused silica capillary column SPB-624, (30 m \(\times\) 0.25 mm \(\times\) 1.4 \(\upmu\)m) under a carrier gas (helium) 1 mL/min with a splitless mode. The oven temperature program was as follows: 40 \({}^{\circ}\)C hold for 2 min and then 5 \({}^{\circ}\)C/min rise until 200 \({}^{\circ}\)C, hold for 10 min. A voltage of 70 eV was set in the EI. The system was operated using Xcalibur 4.0 (Thermo Scientific, Wilmington, DE, USA). Compounds were identified by the NIST library [20] and quantified by comparison to external standards. To optimize the SPME analysis, five commercial fibers were screened: 50/30 \(\upmu\)m DVB/CAR/PDMS, 65 \(\upmu\)m PDMS/DVB Stableflex, 65 \(\upmu\)m PDMS/DVB Fused Silica, 100 \(\upmu\)m PDMS and 75 \(\upmu\)m CAR/PDMS. 75 \(\upmu\)m CAR/PDMS was evaluated by comparison of SCFA standard runs as the most suitable for SCFA detection and chosen for the analysis.
## 2 Experimental Work
### Experimental Device and Loading System  
The two sets of test specimens were ultimately determined to be single-span planar steel frames with a single floor (3888 mm height and 3800 mm span), based on the site dimensions and practical application requirements of the key laboratory hall of structure and underground space at Anhui Jianzhu University. The FW-1 and FW-2 connector groups denote the hooked bolt and pendulums Z-panel connector groups, respectively. This test utilized an American MTS servo loading system with a stroke of 250 mm. A quasistatic loading system was used for this test. A horizontal, low-circumferential reciprocating load was given to the column's highest point. The loading plate served as a link between the actuator and the frame column (as shown in Figure 10). The steel frames were constructed of hot-rolled Q235 H-beams. More precisely, the beam section measured HM244 mm \(\times\) 175 mm \(\times\) 7 mm \(\times\) 11 mm, and the column section measured HW200 mm \(\times\) 200 mm \(\times\) 8 mm \(\times\) 12 mm, which were all supplied by Anhui Fu Huang Steel Structure Co., Ltd. (Hefei, China).  
According to the interstory displacement angle index, 5 mm, 6 mm, 7.5 mm, 8.6 mm, 10 mm, 12 mm, and 15 mm cycles of 3-turn loading and 30 mm, 40 mm, 60 mm, 75 mm, 90 mm, and 105 mm cycles of 2-turn loading were taken into consideration, and they can be found in GB50011-2010 \"Code for Seismic Design of Buildings\" (as shown in Figure 11) [26]. The end of the test was marked by (1 or 2):  
1. When the core components (beam, column, connectors) showed apparent damage.
2. The bearing capacity of the member was reduced to 85% of the ultimate load.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Specimen** & **Sectional Dimension** & **Thickness** & **Yield Stress** & **Ultimate Stress** & **Elongation** \\  & **(mm)** & **(mm)** & **(N/mm\({}^{2}\))** & **(N/mm\({}^{2}\))** & **Elongation** \\ \hline Steel beam flange & HM 244 \(\times\) 175 \(\times\) 7 \(\times\) 11 & 11 & 263.4 & 401.6 & 25.2\% \\ Steel beam web & HM 244 \(\times\) 175 \(\times\) 7 \(\times\) 11 & 7 & 275.3 & 411.3 & 22.3\% \\ Steel column flange & HW 200 \(\times\) 200 \(\times\) 8 \(\times\) 12 & 12 & 289.5 & 435.4 & 24.7\% \\ Steel column web & HW 200 \(\times\) 200 \(\times\) 8 \(\times\) 12 & 8 & 278.2 & 409.8 & 20.8\% \\ Q345 & & 10 & 376.6 & 510.1 & 19.6\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: Mechanical properties of steel.  
Figure 10: Schematic of test working conditions.
## 5 Conclusions and Discussion
### Outlier Tolerance
Therefore, the proposed method is suitable for engineering practice where the outliers commonly exist. In addition, when there are too many outliers (more than 35%), the PCFWE method gives a warning to check the environment noise or equipment malfunctions.
# Influence of Soil Parameters on Detecting Voids behind a Tunnel Lining Using an Impact Echo Method
## 2 Experimental Outline  
### Experimental Design  
When inspecting the voids behind tunnel linings using the IE method, a vibration signal was excited using a hand hammer, and the reflection wave responses from internal flaws, material layers or other interfaces were recorded (Figure 1).  
Figure 2 provides sketches describes how voids behind the tunnel lining and the concrete plate are detected with the IE method, and similar principles can be found in the different cases. Therefore, the second case (Figure 2b) was employed to model the ineffective contact between the soil and the tunnel.  
Figure 1: Sketch of measurement principal using the impact echo (IE) method.  
Figure 2: Sketch describing the detection of voids behind (**a**) the tunnel lining and (**b**) the concrete plate using the IE method.  
It should be noted that the laboratory experiment was a principal test rather than a model one. Regulation of the NDT result contributed by the soil parameters was given more attention than the tested values. Furthermore, the similarity coefficient was not considered in the principal test. An empty box was pre-embedded to model the poor contact between the soil and concrete plate.
## Research Frontier  
From 2019 to 2021, researchers summarize requirements and solutions for several wireless network communications from the perspective of privacy preservation. Research topics include content dissemination in VSNs [42], traditional cryptographic technologies for IoV and VANETs, authentication protocol for radio-frequency identification devices (RFID) [43], as well as an authentication protocol for both VANET security standards and 5G security features [44]. Comprehensive review articles are also published to present the advantages and disadvantages of existing solutions [34], the characteristics of different VANET wireless network communications (including vertical handover, data dissemination and collection, gateway selection, etc.) [16], and the comparison of different authentication and privacy schemes [85].  
There are two refreshing articles. [PERSON] et al. mentioned software-defined networking (SDN), which can bring flexibility and programmability to vehicular networks. Features of SDN-based VANETs are summarized, and their architecture modes, protocols, access technologies, and potential technologies are demonstrated [86]. [PERSON] et al. embarked on the existing cyberattacks on self-driving cars. They analyze the attacks, describe the countermeasures undertaken by the governments and the manufacturers, and discuss how ICVs guarantee resilient operation under cyberattacks [87].  
In other words, researchers are seeking different solutions to ensure vehicular security and privacy.  
Cluster 4: VANET system; back-off mechanism; vehicular networking perspective
# Leaking Gas Source Tracking for Multiple Chemical Parks within An Urban City
###### Abstract  
Sudden air pollution accidents (explosions, fires, leaks, etc.) in chemical industry parks may result in great harm to people's lives, property, and the ecological environment. A gas tracking network can monitor hazardous gas diffusion using traceability technology combined with sensors distributed within the scope of a chemical industry park. Such systems can automatically locate the source of pollutants in a timely manner and notify relevant departments to take major hazards into their control. However, tracing the source of the leak in a large area is still a tough problem, especially within an urban area. In this paper, the diffusion of 79 potential leaking sources with consideration of different weather conditions and complex urban terrain is simulated by AERMOD. Only 61 sensors are used to monitor the gas concentration within such a large scale. A fully connected network trained with a hybrid strategy is proposed to trace the leaking source effectively and robustly. Our proposed model reaches a final classification accuracy of 99.14%.  
source tracking; multi-class classification; AERMOD; fully connected network; hybrid training strategy +
Footnote †: journal:  
0023
## 3 Numerical Examples
### Multi-Bubbles
#### 3.2.1 5 Bubbles  
The whole solution domain is a 15 mm \(\times\) 15 mm \(\times\) 25 mm hexahedron. There are 5 bubbles set in the hexahedron. Figure 7 shows 3D mesh grid of 5 bubbles. Table 3 shows the coordinates of each spherical and radius.  
\begin{table}
\begin{tabular}{c c c c} \hline
**Nodes** & **CFEM** & **XFEM** & **Relative Error** \\ \hline
1 & 24,986.10 & 25,011.4 & 0.10\% \\
2 & 25,262.10 & 25,304.2 & 0.17\% \\
3 & 24,638.90 & 24,704.4 & 0.27\% \\
4 & 24,680.60 & 24,704.7 & 0.10\% \\
5 & 25,268.40 & 25,343.1 & 0.30\% \\
6 & 24,596.60 & 24,646.4 & 0.20\% \\
7 & 23,587.80 & 24,521.7 & 3.96\% \\
8 & 24,887.50 & 24,959.3 & 0.29\% \\
9 & 24,987.70 & 25,010.3 & 0.09\% \\
10 & 19,976.10 & 18,419.6 & \(-\)7.79\% \\ \hline \end{tabular}
\end{table}
Table 2: Contrast of the results of nodes near interface.  
Figure 6: Single bubble potential distribution at \(x=7.5\) mm.  
Compared with the CFEM, improved XFEM greatly simplifies the mesh. Table 4 compares the number of nodes and elements generated by two methods, as well as the calculation time cost on the same computer. Select the section with dense bubbles to draw the potential map. The potential sectional at \(y=10\) mm and \(x=7.5\) mm of XFEM is shown in Figure 8.  
Among the 1159 nodes, the maximum relative error is 7.93% and the average relative error is 1.04%. Ten nodes near the boundary of the sphere are selected to compare the calculation results. The comparison is shown in Table 5.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Node Number** & **Element Number** & **Calculation Time** \\ \hline CFEM & 2407 & 12,997 & 4 min 43 s \\ XFEM & 1159 & 5626 & 34 s \\ \hline \hline \end{tabular}
\end{table}
Table 4: Contrast of number of nodes and elements in 5 bubbles.  
Figure 8: (a) 5 bubbles potential diagram at \(y=10\) mm; (b) 5 bubbles potential diagram at \(x=7.5\) mm.  
Figure 7: (a) 3D 5 bubbles mesh grid of CFEM; (b) 3D 5 bubbles mesh grid of XFEM.
# Bond Fatigue of TRC with Epoxy Impregnated Carbon Textiles
## 3 Results  
### Reference Tests  
The results of the reference tests with different anchorage lengths are displayed in Figure 4. Here, one can see the reached maximum stress and the related measured anchorage length per specimen.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Anchorage Length**} & \multicolumn{3}{c}{**Number of Tested (Evaluated *) Specimens at Load Level \(\sigma_{\text{min}}/\sigma_{\text{max}}\) [\%]**} \\ \cline{2-6}  & 30/90 & 30/95 & 50/70 & 50/85 & 50/90 \\ \hline \(1a\) & 4 (3) & 4 (2) & 4 (2) & 4 (2) & 4 (3) \\ \(2a\) & 4 & 4 (3) & 4 & 4 & 4 (3) \\ \(3a\) & 4 & 4 & 4 & 4 & 4 \\ \(4a\) & 4 & 4 & 4 & 4 & 4 \\ \hline \hline \end{tabular}  
* If different to number of tested specimens.  
\end{table}
Table 1: Experimental program.  
Additionally, the average tensile strength (grey line) and the range of variation of this material combination (grey area) can be seen. These values were determined in tensile tests according to [23].  
It is clearly visible that the maximum textile stress increases with increasing anchorage length. However, the increase stops at the anchorage length of \(3a\), and the specimens with \(4a\) anchorage length reach nearly the same values as the ones with \(3a\). One may assume that an anchorage length of \(3a\) is sufficient to transfer the maximally possible bond force of this material combination and that longer anchorage lengths do not lead to higher loads. None of the specimens failed due to textile rupture, but rather by spalling in the reinforcement layer. Therefore, the maximally reached values are lower than the tensile strength. However, the values are quite close to the range of variation of the tensile strength, and therefore, the results are considered acceptable for the moment.
## 1 Introduction
A collaboration of space syntax with GIS-based methods to study the morphological evolution of cities offers new perspectives to the development of urban morphology studies. Incorporating space syntax in GIS provides some important advantages to both GIS and urban morphology research. There are also some important recent discussions within the GIS-based research community on how spatial models developed within GIS correspond to the way human beings perceive and act in their environment [11]. In particular, this study investigated the morphological evolution of street networks in the case of Famagusta city by using space syntax and GIS-based methods throughout the historical phases. The research is intended with the need of understanding built environments in terms of the spatial growth to understand the physical configuration and socio-economic preferences about space proxemics during the historical periods. Meanwhile, configurational studies have addressed centrality by way of a spatial development using spatial examination [12; 13; 14; 15], wherein the street network (demonstrating the streets as segment lines) is the main component. As a result, the first hypothesis leads to the second one: If the spatial configuration affects the location of socio-economic activities, then they affect the evolution of the city during the historical periods. This study might be generalized through the systematic application of the space syntax method and effective theories of natural movement to other cases worldwide, in which the predictive capacity of space syntax analysis provides an amazing procedure for predicting the spatial growth and evolution of cities. It contributes to an evaluation of spatial configuration effects on locations of socio-economic activity and the level of vitality of city centers.
# Upgrading the Hydrogen Storage of MOF-5 by Post-Synthetic Exchange with Divalent Metal Ions
## 4 Conclusions  
Mixed-metal MOF-5 was synthesized using the post-synthetic exchange technique. The parent MOF-5 and the metal exchanged materials with 0.5 M concentration of metal ions (Ni-MOF-5, Co-MOF-5, and Fe-MOF-5) exhibited hydrogen capacities of 1.46, 1.53, 1.53, and 0.99 wt%, respectively. The metal-exchanged Ni-MOF-5 and Co-MOF-5 showed slightly higher hydrogen uptake (about 5%) in comparison with the parent MOF-5; however, the Fe-MOF-5 showed a decrease in the hydrogen uptake due to partial complex formation with less crystalline nature. The Sips model was found to be excellent in describing the hydrogen adsorption isotherms with a correlation coefficient of approximately 1. The unique hydrogen uptakes of Ni-MOF-5 and Co-MOF-5 show that mixed metal nodes are still capable--with the unsaturated accessible site--of interacting with hydrogen. Further improvement in hydrogen uptake may be achieved by optimizing the preparation conditions including the reaction time, temperature, and metal concentration.  
The following are available online at [[https://www.mdpi.com/article/10.3390/app112411687/s1](https://www.mdpi.com/article/10.3390/app112411687/s1)]([https://www.mdpi.com/article/10.3390/app112411687/s1](https://www.mdpi.com/article/10.3390/app112411687/s1)), Figure S1: PXRD of Co-MOF-5 and Ni-MOF-5 (metal exchanged in 1 M and 0.25 M concentrations), Figure S2: SEM image and EDS mapping, Figure S3: The EDX analysis, Figure S4: SEM image and EDS mapping, Figure S5: The EDX analysis of the Co-MOF-5 sample, Figure S6: FT-IR spectrum of MOF-5 (as-synthesized, Figure S7: FT-IR spectrum of Ni-MOF-5, Figure S8: FT-IR spectrum of Co-MOF-5, Table S1: Hydrogen adsorption in mixed-metal MOFs.  
Conceptualization A.M.P.P.; formal analysis, A.M.P.P. and I.H.A.; methodology, A.M.P.P. and I.H.A.; writing--original draft preparation, A.M.P.P. and I.H.A.; writing--review and editing, A.M.P.P. and I.H.A.; supervision A.M.P.P. and I.H.A. All authors have read and agreed to the published version of the manuscript.  
This research was funded by King Abdulaziz City for Science and Technology through NSTIP, grant number 14-ENE2278-04.  
Not applicable.  
The data are contained within the article.  
The authors declare no conflict of interest.
# 5G Support for Industrial IoT Applications--Challenges, Solutions, and Research Gaps
## 12 Conclusions: Consolidated Challenges and Research Gaps  
The major challenges regarding 5G support for industrial IoT can be grouped into the following categories.  
* proving that QoS metrics meet requirements in real-life: latency, jitter, loss, throughput, and availability, and the reliability of these metrics;
* interoperability of various network elements and segments; conformance testing;
* meeting security requirements and addressing privacy concerns;
* scalability: meeting high density, mass IoT, and URLLC criteria together;
* providing effective device-to-device solutions not only device-to-cloud;
* exploiting the capabilities of Multi-access Edge Compution, in other words, the mobile edge-cloud;
* effective and economical NFV and SDN solutions;
* large scale deployments, network and endpoint operations and maintenance;
* standardization to be fast, and creating firm interfaces as well as allowing for evolution;
* utilizing emerging technologies, such as distributed ledgers and smart service contracts--for multi-stakeholder environments to ensure flexible, safe and secure data management;
* take advantage of AI technologies when addressing challenges of network, service and resource management issues;
* deployments of private campus networks.  
Each Section of this paper has been concluded with \"lessons learned\" and \"research gaps\" to summarize the main take-away messages in relation to the given aspect of 5G-supported Industrial IoT challenges, solutions, and research gaps.  
**Author Contributions:** Conceptualization: P.V.; methodology: P.V., J.P., A.F., D.B., D.H., F.J., G.S., D.F., M.M., and L.T.; investigation: P.V., J.P., A.F., [PERSON], D.H., F.J., G.S., D.F., M.M., and L.T.; writing-original draft preparation: [PERSON], J.P., A.F., D.B., D.H., F.J., G.S., D.F., M.M., and L.T.; writing-review and editing: P.V.; funding acquisition: P.V. All authors have read and agreed to the published version of the manuscript.  
**Funding:** Parts of the research presented in this paper has been supported by the BME-Artificial Intelligence FIKP grant of Ministry of Human Resources (BME FIKP-MI/SC). The research has received funding from the EU ECSEL JU under the H2020 Framework Programme, JU grant nr. 826452 (Arrowhead Tools project, [[https://www.arrowhead.eu](https://www.arrowhead.eu)]([https://www.arrowhead.eu](https://www.arrowhead.eu))) and from the partners' national funding authorities.  
**Acknowledgments:** The authors would like to thank the PhD course entitled \"5G Networks, Services and their Synergies with Industrial IoT\" that has conceived many ideas and collaboration related to this article at BME.  
**Conflicts of Interest:** The authors declare no conflicts of interest.