esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Existing methods for measuring the spatial information of area maps fail to take into account the diversity of adjacency relations and the heterogeneity of adjacency distances among area objects, resulting in insufficient measurement information. This article proposes a method for measuring area map information that considers the diversity of the node-edge and Gestalt principles. Firstly, this method utilizes the adjacency relations between the Voronoi diagram of area objects to construct an adjacency graph that characterizes the spatial distribution of area objects in area maps. This adjacency graph serves as the information representation of area maps. Secondly, the method selects four characteristic indicators, namely geometric information, node degree, adjacency distance, and adjacency strength, to represent the diversity of nodes and edges in the graph that affect spatial information. Finally, nodes in the adjacency graph are taken as the basic units, and the spatial information of area maps is comprehensively calculated by integrating the four characteristics that represent spatial information. To verify the validity and rationality of the proposed method, a dataset of continuously simplified area maps and a dataset of artificially simulated degrees of randomness were designed to evaluate the performance of the existing method and the method proposed in this paper. The results indicate that the correlation between the measurement results obtained by the method proposed in this paper and the degree of disorder is as high as 0.94, outperforming the existing representative methods. Additionally, the correlation between the measurement results of this method and the degree of simplification reaches \(1\), indicating that the variation range of the measured values is more consistent with the cognitive assumptions based on artificial simulations compared to the existing methods. The experimental results show that the method proposed in this paper is an effective metric approach for representing spatial information in area maps.  
information content; entropy; vector; area object; area map; spatial distribution; adjacency graph +
Footnote †: journal: Applied Sciences
# Miniaturized Compact Reconfigurable Half-Mode SIW Phase Shifter with PIN Diodes
## Appendix A  
It should be noted that all diode states can prepare for a phase shift from 15\({}^{\circ}\) to 55\({}^{\circ}\). More phase shift is possible by cascading the structures without extra loss in the wave transition. The main dissipation in the signal is from the microstrip to SIW transition, including the port matching mechanism. This appendix provides a cascaded structure similar to the proposed design. For this study, simulation software is used only to elaborate on the capabilities of a HM-SIW phase shifter. The updated structure has a length of L\({}_{\text{new}}\) = 73 mm, as illustrated in Figure 1.  
It is achieved that the operating frequency of this cascaded phase shifter is 4.8 to 7.4 GHz for the extended design. It is the result of a simple transforming property of the design of the structure without additional geometric optimization in the simulation medium. In CST software, only a copy-transfer operation is utilized to create a simple extended feature for this purpose. With proper tuning of the cascaded structure, it is possible to achieve a similar frequency band. Scattering parameters are shown in Figure 2 for both reflection and coupling coefficients. Only two scenarios, all diodes OFF and all diodes ON, are considered here for the sake of brevity. Within the assigned frequency bandwidth, the coupling value was less than \(-2\) dB, and the reflection coefficient of the two ports was less than \(-10\) dB.  
A similar diode feature is added to the design. Moreover, the number of diodes has increased to six in this extended design. The purpose of a cascaded phase shifter based on the proposed HM-SIW is to show the capability of the microwave device to achieve higher phase shifts. The increased number of diodes also leads to more phase shifts. As shown in Figure 10, the extended structure achieved the maximum value of phase shift. Now, it is possible to have up to \(120^{\circ}\) of phase shift. By cascading three phase shifters, the ultimate transmission phase shift value would be \(180^{\circ}\).  
Figure 10: The maximum achieved phase shift value is presented using an extended reconfigurable structure with six diode posts integrated with a HM-SIW transmission line.
## 2 Monitoring Protocols and Methods
### Regulatory Aspects
#### 2.7.2 Regulations Governing Injection Monitoring
As concentration and flux are likely to vary throughout the day, measuring at different times may show whether the CO\({}_{2}\) contribution is variable over time--probably indicating a near-surface origin--or not, and thus potentially indicating another contributing endmember. * \"Anomaly\" mode (M + 3\(\sigma\)): This mode is activated if 5 different locations of the 35 show CO\({}_{2}\) gas concentrations >7.3% vol. and CO\({}_{2}\) fluxes >9.5 cm\({}^{3}\cdot\)min\({}^{-1}\cdot\)m\({}^{-2}\). Another configuration that may indicate massive leakage, is if 1 location shows a CO\({}_{2}\) concentration >50% vol. or if the CO\({}_{2}\) flux is >100 cm\({}^{3}\cdot\)min\({}^{-1}\cdot\)m\({}^{-2}\). Regardless of how the \"anomaly\" mode is reached, the measurements are repeated, to check the durability of the gas signals. A soil-gas sample is also taken for laboratory measurement of the \(\delta^{13}\)C isotope ratio of the CO\({}_{2}\). A target value of \(-\)33.6% was calculated as a reference, corresponding to the mean value between the mean \(\delta^{13}\)C isotope ratio measured in the soil in 2008 and 2009, and the \(\delta^{13}\)C isotope ratio of the CH\({}_{4}\) produced by the Lacq natural gas field. This carbon-13 isotope ratio has no regulatory significance and as the \(\delta^{13}\)C isotope ratio is measured in the laboratory, there may be a delay in knowing that the threshold was exceeded. If the values are confirmed, more measurements are made at neighbouring monitoring points to determine if the CO\({}_{2}\)-level increase is confined to a small area (where the anomaly is defined), or if the increase occurs at a wider geographic scale suggesting a leak from the reservoir. * \"Normal\" mode: None of the above defined threshold levels is reached.
## 5 Robust Failure Mode Definition and Formulation of Multiple Resource Replacement Strategies
### Formulation of Multiple Resource Substitution Strategies  
Targeting the cloud resource node failure problem proposed in Section 5.1, this paper aims to develop a robustness enhancement strategy for CMNs that involves adding redundant nodes.  
For the supply chain modeling and robustness problem, [PERSON] [48] took the smartphone supply chain as an example and put forward three different robustness optimization strategies: enterprise internal operation management, cooperative management between enterprises, and a regional development strategy. Inspired by this, and combined with the characteristics of cloud manufacturing, this paper proposes three kinds of robustness improvement strategies: internal resource replacement, external resource replacement, and internal-external integration replacement.  
1. Internal replacement strategy: The cloud service provider \(Si\) will internally provide replacement resources \(Rj\) for \(Ri\) (noted as \(Ri\)-\(Si\) and \(Rj\)-\(Si\), respectively). If \(Ri\)-\(Si\) fails, \(Rj\)-\(Si\) will replace it to complete the processing of cloud manufacturing tasks. Although the tasks will be completed, the cloud task time will be increased due to the different resource types, and additional working hours will be incurred.
2. External replacement strategy: The cloud service provider \(Sj\), \(Sk\)... etc. will provide the same type of resources \(Ri\) as \(Ri\)-\(Si\) (recorded as \(Ri\)-\(Sj\), \(Ri\)-\(Sk\)... etc.). When the resource \(Ri\) fails, the strategy will comprehensively select the best cloud service provider based on multiple factors, such as resource quotation and the distance between service providers. It will then request alternative resources from them to replace the failed \(Ri\)-\(Si\) to complete the cloud manufacturing task. Since the resource types are the same, this does not add additional task time; however, the transfer of resources and information among different service providers will generate additional logistics transportation costs and time.
3. Internal-external integration replacement strategy: This strategy is the combination of the previous two strategies. When a cloud resource fails, this strategy first looks for a replacement resource within the service provider; if no replacement resource is found or its replacement resource also fails, it continues to seek the same type of resource from other service providers. The logical flow of these three strategies is shown in Figure 4. In addition, in the complex network model, node failure is reflected by removing the failed resource node and all the edges connected to the node. After selecting the corresponding resource replacement strategy, the optimal alternative resource node under the current strategy is first determined. If this replacement node is already in the original network, all connected edges belonging to the failed node will be directly linked to the replacement node; if it is not already in the original network, the replacement node should first be added to the network, then be linked similarly.
## 4 Conclusions  
1. Surrounding rock radial grouting can significantly improve the tunnel's initial support. The effects decrease when the grouting range exceeds 4 m. Therefore, the radial grouting should be controlled within the range of 4.0 m to 4.5 m during the design.
2. Curtain grouting effectively reduces external water pressure, and the external water pressure of the grouting area is 23% greater than that without curtain grouting. Therefore, curtain grouting benefits the stress of the tunnel lining structure by slowing down the infiltration of external water pressure.
3. Curtain grouting can effectively strengthen the self-stability of surrounding rocks and control the deformation settlement by approximately 33%. However, there is no significant change in the stress of the initial support.
4. If without curtain grouting, the safety reserves of the secondary lining are 25% and 20%, respectively. These are higher than those with curtain grouting in terms of axial force and bending moment.
5. When curtain grouting is adopted, the initial support of the first layer and the initial support of the second layer have different pressure-sharing proportions to the surrounding rock. When the water pressure has not increased, the sharing proportion of the initial support for the first layer is large, and after the water pressure increases, the initial support of the second layer increases by a large proportion.  
Conceptualization, X.Z. and Y.D.; methodology, Y.D.; software, Y.D.; validation, B.Z. and X.Z.; formal analysis, Y.D.; investigation, Y.D. and B.Z.; resources, X.Z.; data curation, Y.D. and B.Z.; writing--original draft preparation, Y.D.; writing--review and editing, Y.D.; visualization, B.Z.; supervision, X.Z.; project administration, X.Z.; funding acquisition, Y.D. All authors have read and agreed to the published version of the manuscript.  
The work was financially supported by the open fund project of the cultivation base of the State Key Laboratory of Mountain Bridge and Tunnel Engineering (Serial number: CQSLBF-Y16-1), project name \"Study on anti-external water pressure structure type and safety early warning system of the water-rich tunnels in mountain ridge\"; Chongqing Transportation Scientific and Technological Projects (serial number: CQJK2015-03), project name \"On groundwater protection and limited discharge countermeasures of Chuntianmen extra-long tunnel of Nanchuan-Liangjiang Expressway\"; and the open fund of the provincial co-construction State Key Laboratory of Mountain Bridge and Tunnel Engineering (SKLBT-2110), project name \"Research on mechanical properties of tunnel lining crack repair in the cold area based on the characteristics of Nano-CC grouting material\", jointly funded.  
Not applicable.  
The authors declare that they have no conflict of interest to report regarding the present study.
## 2 Theoretical Derivation of the Two Dimension Tire Model
### Flexible Beam on an Elastic Continuous Sidewall Beam Tire Model  
The schematic diagram of the flexible beam on an elastic continuous sidewall beam tire model is shown in Figure 2. The bending deformation of the flexible belt and the pre-tension axle force resulting from the inflation pressure was considered. Additionally, the sectional stiffness of the sidewall radial spring and the bending feature of the continuous sidewall beam were added to enrich the one-dimensional tire model. \(u_{r}\) and \(u_{sr}\) are, respectively, the horizontal displacement of the flexible belt beam and the continuous sidewall beam at time \(t\) at point \(\theta\); \(EI\) and \(E_{s}I_{s}\) are, respectively, the bending stiffness of the flexible belt beam and the continuous sidewall beam; \(\rho A\) is the density per line of the belt beam and \(m_{s}\) is the density per rad of the continuous sidewall beam; \(k_{r1}\) and \(k_{r2}\) are the radial stiffness of the sectional sidewall spring model; \(R\) and \(R_{s}\) are, respectively, the belt radii and sidewall ring radii; \(F_{N}\) is the pre-tension force due to the inflating pressure and \(F_{N}=PRb\), where \(P\) is inflation pressure; and \(b\) is belt width.  
Equation (1) illustrates the coupling kinematic equations of the flexible beam on an elastic continuous sidewall beam tire model: A. Equation (1a) shows the bending equation of flexible belt beam; B. Equation (1b) implies the bending equation of continuous sidewall beam; C. Equation (1c) illustrates the vibration equation of wheel.  
\[\left\{\begin{array}{ll}\frac{EI}{R^{4}}\frac{\partial^{4}u_{r}}{\partial \theta^{2}}+k_{r1}\cdot(u_{r}-u_{sr})+\rho A\frac{\partial^{2}u_{r}}{\partial t ^{2}}-\frac{Pb}{R}\frac{\partial^{2}u_{r}}{\partial\theta^{2}}=0&(\mathrm{a}) \\ \frac{EI_{s}I_{s}}{R^{4}}\frac{\partial^{2}u_{r}}{\partial\theta^{2}}+m_{s} \frac{\partial^{2}u_{r}}{\partial t^{2}}=k_{r1}\cdot(u_{r}-u_{sr})-k_{r2}(u_{ sr}-u_{mr}\cos\theta)&(\mathrm{b})\\ m_{w}\tilde{u}_{wr}=\int_{0}^{2\cdot\pi}\left[k_{r2}\cdot(u_{sr}-u_{wr}\cos \theta)\cos\theta\right]\mathrm{d}\theta&(\mathrm{c})\end{array}\right. \tag{1}\]  
The radial deformation of the flexible belt and the continuous sidewall is considered in the flexible beam on an elastic continuous sidewall tire model, while the coupling deformation characteristic of the continuum mediums, such as the tire belt and the tire sidewall between the radial and tangential  
Figure 2: Schematic diagram of the flexible beam on elastic continuous beam tire model.  
deformations exists. Thus, the flexible ring on an elastic continuous foundation tire model is proposed and developed with the radial and tangential deformation of flexible belt ring and the continuous sidewall ring.
# Recycling 3D Printed Concrete Waste for Normal Strength Concrete Production
###### Abstract  
As the use of 3D-printed concrete becomes more prevalent, the need for effective recycling methods becomes paramount. This study addresses this concern by exploring the repurposing of 3D-printed concrete waste as an aggregate in normal-strength concrete for C30/37 and C40/50 classes, covering both fine and coarse aggregates in its particle size distribution. The extent of recycled aggregate (RA) replacement was determined through sieve analysis. A two-stage investigation assessed the compressive strength performance of the concrete specimens. The initial stage produced reference specimens with no replacement, representing conventional concrete. In the second stage, variable specimens incorporated 50% and 67% recycled aggregate (RA) from 3D-printed concrete waste. Results revealed that in C40/50, both the 50% and 67% replacements consistently exhibited a higher strength than 0%. In C30/37, the 50% replacement displayed decreased strength compared to the 0% and 67%, while the 67% replacement consistently showed superior strength. Adjusting the water content impacted strength; at 67%, slight variations occurred, while at 50%, extra water led to a significant decrease. An overarching discovery is that the efficacy of the 67% replacement level holds regardless of the concrete strength class.  
recycled 3D-printed concrete aggregate; particle size distribution; mix design; compressive strength; normal strength concrete; interfacial transition zone +
Footnote †: journal: Applied  
1
Footnote 1: [[https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci)]([https://www.mdpi.com/journal/applsci](https://www.mdpi.com/journal/applsci))
## 4 Experimental Results and Discussion
### Influence of Frame Number and Pilot Interval on Estimation Accuracy  
In order to further identify the optimal pilot interval and the convergence of multi-frame averaging, the comparison of estimation accuracy is implemented after electric back-to-back (EBTB) and 1 m tap water channel transmission when the SFO is 600 ppm. The pilot interval is defined as _n-m_ in Equation (7). Figure 4a shows the estimated offset obtained from the average result of 120 frames at different pilot intervals. As shown in Figure 4a, when the pilot interval is 4, the estimated offset is too large and the impact of SFO cannot be well-alleviated. The reason is that the phase difference in Equation (5) is small and the estimated SFO value is more vulnerable to noise. Furthermore, the target accuracy can be successfully achieved as the pilot interval is up to 34. In such a case, the curve of estimated offset tends to be flat, and the further increase in the pilot interval will not improve the estimation accuracy. Moreover, since the signal after EBTB transmission is less affected by noise, the estimation accuracy of EBTB is more accurate and the estimated offset is less than \(\pm 1\) ppm. Figure 4b demonstrates the corresponding estimated offset versus the frame number when the pilot interval is 34. It shows clearly that the SFO estimated offsets can all converge very fast, and the required frame numbers are approximately 40. The fast convergence of SFO estimation can further depress the computational complexity. In the following discussion, the pilot interval is fixed at 34 and the phase-conjugated pilots are inserted on the 22 nd subcarrier in each frame. This is because the phase shift of high subcarriers rises faster as the symbol index increases. The large phase difference can achieve more precise estimation accuracy [27].  
Figure 3: EVM performance versus SFO estimation error.
## 5 Practical Issues
### Proof of Concept  
The prototype has two parts: a fixed-wing drone and a ground base station. We pushed the prototype to its limits using manual fly mode. At the same time, it was disturbed by two  
\begin{table}
\begin{tabular}{l l l} \hline
**Name** & **Description** & **Size** \\ \hline Payload & The data of the packet & Max. 246 bytes \\ \hline Payload CRC & 16 bit cyclic redundancy check for payload & 2 bytes \\ \hline \end{tabular}
\end{table}
Table 6: Packet payload structure.  
\begin{table}
\begin{tabular}{l l l} \hline
**Name** & **Description** & **Size** \\ \hline Source Device Address & The device which transmits the packet. & 1 byte \\ \hline Destination Device Address & The device which receives the packet & 1 byte \\ \hline Number of Packets & The number of packets the total message is made of. & 1 byte \\ \hline Packet Number & The number of the packet, among the packets. & 1 byte \\ \hline Payload Size & The number of bytes the packet’s payload is made of. & 1 byte \\ \hline Header CRC & 16-bit cyclic redundancy check for error-checking purposes. & 2 bytes \\ \hline \end{tabular}
\end{table}
Table 5: Packet header structure.  
other devices using LoRa on the same frequency, which can pose a challenge because the device obtains new instructions from the base station every 30 milliseconds. The ground base station is assembled from an ESP32 development board, LoRa RA-02 module, 2004A LCD alphanumeric LCD screen displaying status, joystic, and 10 k\(\Omega\) potentiometer for controlling the throttle, all packed in a 3D-printed box. The drone platform is a 3D-printed fixed-wing aircraft model bought from Eclipson Airplanes. Its electronics are built of a 30A ESC (Electronic Speed Controller), 1200 kv A2212 brushless DC motor, 3000 mAh 3S LiPo battery, ESP32 development board and six pieces of servo motors. Even with obstacles, the drone still follow the commands, demonstrating that the communication system is reliable. To demonstrate the PUF in ESP-IDF, one small block of memory is closed for access to extract a key, which is based on the hardware attribute, and this key is uploaded to the blockchain, and any base station that participates in the blockchain can register and authenticate the drone. This blockchain can be accessed only by multiple service providers while remaining closed off to undesirable entities. It means that when a drone needs to switch to a new base station, the base stations do not have to synchronize with each other about the change. Instead, the drone can notify the old base station that it wants to disconnect and authenticate itself with the new base station, reducing the network overhead.