esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Modeling
### Parameter Fitting  
Model parameters were fitted using the Levenberg-Marquardt (LM) algorithm and the tensile experiments discussed in Section 2.3. Only one set of parameters was fitted, without making any distinction between the LT and HT materials. The parameters were also shared among the bainite, LCM and MA phases. In total, nine parameters needed to be fitted.  
First, the experimental data were resampled in order to have a reduced number of data points at a common sampling rate for all the experiments. Then, an initial set of parameters was assigned based on literature data. Most parameters (\(C_{1}\), \(\psi\), \(\beta\), \(C_{2}\) and \(\sigma_{\text{imb}}^{2}\)) were taken from [PERSON] (2017), while the typical value of 0.5 was used for \(\alpha\), the Hall-Petch constant was set to 10.0 (which is close to the values fitted in ([PERSON] _et al._, 2018)), \(c_{p}\) was set to 5.0 (between the values for cubic and spherical particles in ([PERSON] _et al._, 2018)) and \(n\) was initially set to 10 (a value typically used in VPSC simulations). These parameters were fitted using the LM algorithm, which reached convergence after approximately 20 steps. Each step required running a minimum of a simulation for each fitting parameter, with an additional simulation with the new parameters. After the algorithm finished, additional perturbations were manually applied to the fitting parameters and the fitting process was repeated, in order to find solutions that correspond to lower local minima.
## 4 Performance Analysis of the Strengthened Walls
### Failure by Bed-Joint Slide  
The failure by bed-joint slide of the strengthened masonry walls is different from the typical shear-compressive failure. The UHPC layers and the reinforced polymer mortar layer strengthened the masonry significantly, but they did not cover the bottom parts of the walls effectively. Meanwhile, the bottom parts of the walls resisted the maximum shear forces and moments. Therefore, the bottom parts became the weakest and the failure by bed-joint slide was triggered.  
During the procedure of the bed-joint slide, the strain of the reinforcing bars at the bottom of the W3 was larger than that of the reinforcing bars in other parts, as shown in Figure 15a. Figure 15 also shows the strain of all the reinforcing bars and the UHPC was far less than their ultimate strain during the procedure. Therefore, the strengthening layers had not taken full effect and the failure by bed-joint slide was premature.  
Figure 14: The interface between the strengthening layers and the masonry substrate: (**a**) The coarse interface between the UHPC layer and the masonry substrate; (**b**) The smooth interface between the reinforced polymer mortar layer and the masonry substrate.  
Figure 15: Strain of the strengthening layers: (**a**) Strain of the reinforcing bars of W3, the gauge position is illustrated in Figure 3b; (**b**) Strain of the UHPC of W2, the gauge position is illustrated in Figure 4.  
The bed-joint slide is more prompt for squat walls for which the in-plane shear deformation is dominant. For the slender walls, there is significant compressive stress caused by the in-plane bending deformation and normal to the bed-joints. The compressive stress is favorable for preventing the premature bed-joint slide. Therefore, better energy dissipation ability could be expected when the UHPC layers are applied on slender masonry walls.  
To prevent such a premature failure mode, strengthening scheme should be designed at structural level: the joints among adjacent strengthened walls, like the bottoms of the W1S, W2, and W3, should be strengthened simultaneously. Such a scheme can strengthen the walls more effectively. More importantly, it can improve the seismic performance of the entire structure because it improves the structural integrity.
# Methane Gas Density Monitoring and Predicting Based on RFID Sensor Tag and CNN Algorithm
## 2 RFID Sensor Design  
### Communication Mechanism  
The RFID system generally consists of an RFID tag and an RFID reader. Figure 1 shows the basic communication flow based on the electronic product code (EPC) generation2 (G2) protocol [36]. Within the communication distance, the reader first sends the Select instruction by carrier wave (CW) to the tag to change the tag's status. The reader then sends the Query instruction to the tag and the tag responds with its RN16. After that, the reader sends the ACK instruction to obtain the ID information and CRC code of the tag. Finally, Req_RN is sent by reader to acquire the Handle response of the tag.  
From the information discussed above, we found that there is no direct instruction for processing sensor information; hence, we have to adjust this communication flow. In general, the sensor data are stored in the non-volatile memory of the tag chip, but it exhibits long response time and high power consumption during the read/write process [20]. Thus, in this paper the sensor data is embedded into the identification (ID) information of the RFID tag. In this way, the time for reading and writing the sensor data into the non-volatile memory can be avoided, resulting in lower power consumption and response time compared with the traditional method. Figure 2 shows the comparison of the ID information between the traditional method and the proposed method.  
Anti-collision technology is common in the field of RFID systems. However, in the field of environment monitoring of underground mines, the position of the RFID sensor tag is fixed. The number of the RFID sensor tag and the density of the RFID reader are not as much as in the field of supply chain or health monitoring. Hence the anti-collision problem is not a serious issue in the application of underground mine monitoring. As for our design, we propose the Q algorithm in EPC Gen2 protocol [36] for RFID tag anti-collision and the reader-coverage collision avoidance arrangement (RCCAA) method [37; 38] for RFID reader anti-collision.
## 4 Conclusions  
This work predicted the well-to-wheel CO\({}_{2}\) emission of gasoline vehicle and electric vehicles for China, Europe, Japan and World Average through year 2040 under eight different driving conditions. An experimentally validated vehicle dynamic model was employed to calculate the gasoline and electricity consumption of CV and EV. The key conclusions are as follows:  
1. The CO\({}_{2}\) emission decreases over the years for both CVs and EVs, due to the increased engine efficiency and increased fraction of renewable energy in the power grid, respectively.
2. For all the countries/regions studied, CVs have higher CO\({}_{2}\) emission than EVs from year 2018 to 2040.
3. For all the countries/regions studied, China has the highest CO\({}_{2}\) emission for EVs, followed by Japan, the world average, and the EU. Their differences are determined by CO\({}_{2}\) emission of electricity supply chain.
4. The difference of CO\({}_{2}\) emission from CVs and EVs is smaller under highway conditions, compared with those under urban driving conditions. For instance, the CO\({}_{2}\) emission from CVs is 23% higher than that of EVs in China in year 2018, and decreases to 17% in year 2040 for China-fast driving conditions.
5. For urban driving conditions, e.g., New York City Cycle, the carbon emission gap between CVs and EVs in China is 59% and 56% in year 2018 and year 2040, respectively. However, electricity regeneration during braking is found to be effective in reducing carbon emission for EVs under urban driving conditions.  
Conceptualization, X.D. and B.W.; Formal analysis, B.W. and Q.N.C.; Methodology, X.D. and B.W.; Resources, H.L.Y. and Q.N.C.; Validation, X.D. and B.W.; Visualization, X.D. and H.L.Y.; Writing--original draft, X.D.; Writing--review and editing, H.L.Y. and Q.N.C. All authors have read and agreed with the final manuscript.  
This research was funded by China Postdoctoral Science Foundation Grant No. 2016M600313, as well as Talent Plan Research Supporting Funds from Shanghai Jiao Tong University.  
The authors declare no conflict of interest.
## 4 Results and Discussion
### Example of Engineering Application of the Charts of Influence Zone  
For the case study by [PERSON] et al. [30] an application of the critical line's equation is demonstrated. The study concerned a region in China named Liangshuijing. In the project area, the soil consists of light yellow and hard plastic-like red clay with an average thickness of 9.6 m, and the bedrock mainly consists of light grey, thin-layered, and moderately weathered limestone. The 2.0 m \(\times\) 2.0 m independent foundation under the column was adopted in the project. The basis depth is 2.0 m, the clay weight \(\gamma\) = 18.2 kN/m\({}^{3}\), \(c\) = 53 kPa, \(\phi\) = 28 deg. There is an oval cavity with a semi-major axis of 0.3 m and a short half-axis of 0.25 m under 5.0 m of foundation. There are no fillings in the cavity. Based on these data, we introduce a case of utilization of the critical lines with a dry condition to determine stability.  
Assuming that the cavity's centerline coincides with the footing centerline (Figure 13), the coefficients \(q\) in Table 5 is determined using \(b_{0}\) = 2.1; \(b_{1}\) = 0.25; \(b_{2}\) = \(-\)0.003 based on the shear strength parameters shown above. As a result, the calculated critical boundary is \(Y_{\text{cri}}\) = 6.75 where \(X\) = 0. The stability condition is expressed by comparing the (\(h\)-\(D\)/2)/\(H\) = 1.26 obtained from the provided geometrical conditions (\(h\) = 5 m, \(D\) = 0.5 m, and \(H\) = 3.25 m) to the critical value \(Y_{\text{cri}}\) of 6.75. This comparison shows that the cavity is involved within the unstable zone and agrees with the results by [PERSON] et al. [30], who estimated an unstable condition based on their calculated stability factor such as 0.982 \(<\) 1.0. Even though the comparison with our method is indirect, it can reach a similar conclusion about the state of stability, which is one of our objectives.
## 3 Results
### Antibacterial Activity  
The highest inhibition of the NPs was observed against _K. pneumoniae_, _E. cloacae_, and _P. aeruginosa_. Their inhibition zones varied between 9 mm and 22 mm and were almost double those of _E. coli_, _E. faecalis_, and _S. aureus_, which varied between 3 mm and 12 mm (Table 1). The inhibition was about double for each bacterium at the highest NP concentration (5 mg/mL) to the lowest concentration (0.5 mg/mL). The MIC varied between 0.2 mg/mL against _E. cloacae_ and _K. pneumoniae_ and 1 mg/mL against _E. faecalis_ (Table 2). For _S. aureus_, the MIC was 1 mg/mL and for _P. aeruginosa_ 0.3 mg/mL. The MBC was lowest (0.5 mg/mL) to _P. aeruginosa_ and highest (1.5 mg/mL) to _S. aureus_ (Table 2).  
\begin{table}
\begin{tabular}{l l l l l l l} \hline \hline \multirow{2}{*}{**NPs Concentration (\(\mu\)g/mL)**} & \multicolumn{4}{c}{**Zone of Inhibition (mm) Against Bacteria**} \\ \cline{2-7}  & _K. pneumoniae_ & _E. cloacae_ & _P. aeruginosa_ & _E. coli_ & _E. faecalis_ & _S. aureus_ \\ \hline
0.5 & \(10\pm 1.6\) & \(11\pm 1.5\) & \(9\pm 1.6\) & \(6.5\pm 2.4\) & \(3\pm 1.5\) & \(6\pm 1.4\) \\
1 & \(12\pm 1.5\)
## 4 Conclusions
\begin{tabular}{l l l}
**Symbol** & **Unit** & **Description** \\ \(A_{\rm cross}\) & mm\({}^{2}\) & cross-sectional area between the tantalum foil and the vapor capillary \\ \(A_{\rm foil}\) & mm\({}^{2}\) & area of the tantalum foil, excluding the cross-sectional area with the vapor capillary \\ \(A_{\rm pyro}\) & mm\({}^{2}\) & area of the pyrometric measuring spot \\ \(A_{\rm tot}\) & mm\({}^{2}\) & total area of the tantalum foil \\ \(BPP_{\rm min}\) & mm\(\cdot\)mrad & beam parameter product \\ \(d_{\rm fiber}\) & \(\mu\)m & diameter of the optical fiber \\ \(d_{\rm focus}\) & \(\mu\)m & diameter of the transversal laser beam profile in the focal position \\ \(d_{\rm key}\) & \(\mu\)m & diameter of the keyhole opening \\ \(d_{\rm in}\) & mm & inner tube diameter of the refractory probe \\ \(d_{\rm out}\) & mm & outer tube diameter of the refractory probe \\ \(d_{\rm spot}\) & mm & minimum spot size of the pyrometric measuring beam \\ \(d_{\rm weld}\) & mm & welding distance traveled by the laser beam \\ \(\delta\) & K & convergence threshold for self-consistent temperature calculation \\ \(E_{\rm dist}\) & J/mm & energy per unit length \\ \(\xi\) & - & temperature calibration coefficient \\ \(c\) & - & emissivity coefficient \\ \(f_{\rm HS}\) & kHz & frame rate used for the high-speed recordings \\ \(f_{\rm pyro}\) & kS/s & sampling rate of the pyrometer \\ \(f_{\rm rot}\) & Hz & rotation frequency of the shutter disk used for synchronization \\ \(f_{\rm sample}\) & kS/s & sampling rate used by the FPGA controller for data acquisition \\ \(f_{\rm vib}\) & Hz & vibration frequency of the melt pool or the vapor capillary, respectively \\ \end{tabular} \begin{tabular}{l l l} \(F\)WHM & nm & height of the wall sample \\ \(h\) & mm & height of the weld sample \\ \(l\) & W/mm\({}^{2}\) & intensity \\ \(l_{\rm key}\) & W/mm\({}^{2}\) & threshold intensity of the laser beam required to enable a deep welding process \\ \(l_{\rm pyro}\) & W/mm\({}^{2}\) & intensity of the heat radiation in the wavelength interval detectable by the \\  & & pyrometer \\ \(l\) & mm & length of the weld sample \\ \(l_{\rm key}\) & mm & length of the keyhole in the direction of the laser beam axis; keyhole depth \\ \(L_{\rm K}\) & \(\mu\)m & thickness of the Knudsen layer \\ \(\omega\) & rad/s & angular velocity of the shutter disk during the synchronization experiments \\ \(P\) & W & laser power \\ \(q\) & W/mm\({}^{2}\) & heat flux \\ \(R\) & mm & radius of the shutter disk used during the synchronization experiments \\ \(r\) & mm & radius of the notches at the outer rim of the shutter disk \\ \(S\) & W/mm\({}^{3}\) & spectral energy density \\  & & straight slope of the translation between pyrometric voltage signal and \\ \(s\) & K/V & temperature difference \\ \(T\) & K & absolute temperature \\ \end{tabular}
## 5 Conclusions
### Theoretical Implications  
First of all, the current study applied the PRT in the ISFR context for the first time. This study focused on the perceived risks of ISFR, and it adopted four types of perceived risks, which included psychological, quality, financial, and time risks. These risks are among the six types of perceived risks which were suggested by [PERSON] [24] according to the research background. The result of the principal component analysis indicated that the four risks were successfully extracted, and the result of the SEM revealed that the psychological and quality risks had statistically negative effects on AT. This study presents theoretical contributions by empirically identifying the negative predictors of AT towards ISFR.  
Secondly, the current study successfully applied a comprehensive framework that merged the PRT and the TAM in the context of ISFR. The TPB might not be able to fully predict consumer behavior, because it was limited to only three predictors. As a result, this study successfully incorporated this theory and the PRT in the context of ISFR. This study is not like the previous study, which focused on pro-environmental behavior [16].  
Lastly, the present study empirically proved the moderating role of novelty seeking in the relationship between perceived risks and AT for the first time. The extant studies have a limitation in regard to identifying the moderating role of novelty seeking only in a positive relationship [74, 75]. An individual who seeks novelty is more willing to try new products/services as well as take risks, so this study hypothesized that novelty seeking weakens the negative effect of perceived risks on attitudes. The result of the multiple group analysis revealed that the moderating role of novelty seeking was discovered in the relationship between psychological risk and AT. The path coefficient of the consumers with a high level of novelty seeking was specifically less negative than the path coefficient of the consumers with a low level of novelty seeking, which presents the theoretical contributions as empirically finding that the moderator weakened the negative effect of perceived risks in the context of new technology acceptance behavior.
# An Internet of Things (IoT) Application on Volcano Monitoring
## 3 IoT Thermometers Network
### Software  
For the network operation, a communication protocol was developed. In this protocol, there is no possibility for a collision among messages, since no element of the network transmits simultaneously to another. For this reason, a single channel is used. When the communication process starts, the gateway and the repeater have both the same configuration parameters (SF and BW), but thermometers are configured with a different SF. The process can be summarized as follows: When an acquisition has to be done, the gateway communicates only with the repeater and test if it is available. If so, the gateway sends the temperature acquisition command to the repeater and keeps waiting a specific time for the returned raw data. Any message that the gateway sends will be received and decoded by the repeater, but not by the thermometers, since they are configured with a different SF (see Appendix A). The repeater, in charge of resending the instruction to the end devices, changes its parameter configuration to match the thermometer configuration so that communication between them is possible. The repeater sends them the temperature acquisition command and keeps waiting for their answers. Thermometers receive the command, perform the corresponding tasks, and send the information back to the repeater in their turns (thermometer 1 waits one second and transmits, thermometer 2 waits two seconds and transmits, and so on). The repeater receives the raw data, returns to initial parameter settings, and transmits the information to the gateway, who stores it (Figure 6).  
In order to manage the network properly, a software development had to be made. The set of programs and scripts developed involves several technologies and program languages such as: Python, C, and HTML, running each one in different devices in the network. Some scripts are executed using Linux cron, which is a background process manager that is able to run processes at regular intervals, which can be scheduled.  
The compiled programs and written scripts are listed in Table 5.
## 2 Literature Review
### Green Ship Routing and Scheduling Problem
[36] proposed a hybrid multicriteria ship route planning method based on an improved particle swarm optimization and genetic algorithm generated in order to obtain the Pareto frontier and to make a decision tradeoff among the minimum navigation time route, fuel consumption route, navigation risk route. In fact, most real-world problems have several objectives. Therefore, a multi-objective approach is essential to solving the GSRSP following the review of the literature mentioned above. This problem often has to be considered for different objectives, such as distance, time, emissions, profit, revenue, etc. [5] We found that most multi-objective approaches to solving the GSRSP focus on generating Pareto solutions by taking into account the trade-off among several objectives. The advantages of taking non-dominated solutions from Pareto fronts in the maritime transport applications are as follows:  
The Pareto approach provides decision-makers (maritime regulators) with several alternative solutions associated with objective functions. It provides more choices for the decision-maker to consider and find the best balance among objectives based on their needs [33; 37]. Maritime regulators can use the Pareto fronts to both make short-term decisions and devise long-term strategies to be defined based on the behavior of these frontiers [38]. This method is more realistic, particularly when decision-makers (maritime regulators) are undecided about the weights or when a trade-off relation among objective functions is not established a priori [33]. In addition, the selection of a unique optimal solution from a set of Pareto solutions, which results in less computational effort for the proposed multi-objective approach [32]. Based on this literature review and the merits of the Pareto fronts, most researchers offer various methods to obtain the Pareto fronts in maritime transport applications. However, it is clear that relatively few studies have investigated solutions for the green ship routing and scheduling problem (GSRSP), and no articles have studied the GSRSP with berthing time conditions (GSRSP-BT).
## 2 Related Work and Technologies
### XBee868 LP/ZigBee  
ZigBee communication technology uses a low data communication rate, low power consumption, and operates with a wireless network protocol aimed at computer applications and remote control. It has a low power specification based on the IEEE 802.15.4--2003 Wireless Personal Area Networksstandard, whose distance does not exceed 150 m [41]. The XBee 868 LP (Low Power) is designed to provide a long-range radio frequency connection with significant performance and low power consumption. The modules have 30 channels between the frequencies 863 MHz and 870 MHz in the \"Listen Before Talk\" mode, which frees them from a work cycle. In [42], the authors refer that the Xbee868 LP module is the first Radio frequency (RF) module in the industry to use Listen Before Talk and Adaptive Frequency Agility (LBT + AFA) techniques. The module \"listens\" to the environment before communicating. If disturbed, it automatically changes channels in a matter of microseconds, which does not affect its overall performance. With Surface Mount (SMT) technology, the XBee 868 LP is compatible with the XBee ecosystem. The configuration is also carried out with the free software XCTU, a platform common to all products in the XBee ranges. Point to point, point to multipoint and DigiMesh networks are supported. The XBee868 LP module allows communications up to 4 Km [42].  
In [41], the authors show how a network of sensors can be implemented to monitor the doors of a building using ZigBee.
## 4 Discussion  
### Potential Sources of the Sediments  
The Beibu Gulf is a semi-closed gulf located northwest of the SCS and connected with the SCS through the southern end of the gulf and Qiongzhou Strait, which is located between Hainan Island and the Leizhou Peninsula (Figure 1). The Red River (Song Hong River) provides the major riverine discharge into the gulf, along with some smaller coastal rivers [29,30]. Discharge from the Pearl River, about 400 km to the northeast, may reach the gulf through Qiongzhou Strait [31]. Additionally, coastal erosion also is a significant source of sediments; amounts of suspended particulate matter (SPM) from the west area of Hainan Island can even be transported to the center of the Beibu Gulf [18]. Geologically, Cambrian to recent strata are outcropped in the land area around the Beibu Gulf. The granitic rocks, as the dominant rocks, occupy more than 60% of the area west of Hainan Island [32]; the basic igneous rocks of the Tertiary and Quaternary periods compose the basement of the Leizhou Peninsula; and Paleozoic sandstone and shale are widely exposed in the coastal areas of the Guangxi province, People's Republic of China [33]. In most of the Beibu Gulf surrounding land areas, the solid rocks are unevenly mantled by Quaternary alluvium, regolith, or deeply weathered rocks [33]. The Red River drainage system has considerable differences in its lithologies, including metamorphic rocks, limestone, granitoid rocks, felsic rocks, and ultramafic rocks [25]. The sediments derived from these different rocks are intensively mixed within the Red River estuary. The variation in rock types surrounding the Beibu Gulf inevitably resulted in differences in material composition and geochemical characteristics across these source areas, and this variability offers a valuable opportunity to trace and identify the different origins of sedimentary materials in the study area.