esa-sceva/satcom-chunk-collection huggingface dataset:
# A Micro-Segmentation Method Based on VLAN-VxLAN Mapping Technology
## 3 Proposed Method
### Micro-Segmentation  
#### 3.1.1 Micro-Segmentation  
There are currently two popular approaches to micro-segmentation. The first approach involves implementing business-based security controls by installing endpoint security software or plug-ins inside each virtual machine. This approach has several advantages, such as being located close to the endpoint of the traffic and enabling different security control rules to be developed for different services, resulting in a fine-grained and highly flexible micro-segmentation approach. However, this approach also has several drawbacks, such as difficulties in installation and deployment, the fact that each endpoint security software or plug-in can only protect a single virtual machine, and increased deployment difficulties when the scale increases. Moreover, high flexibility brings increased management, operation, and maintenance costs and inconsistent security requirements of the business, which may result in the inability to complete the implementation of security policies in bulk. Since the security software is installed on top of the operating system, there are issues of compatibility with business software, and the consumption of virtual machine resources to consider. When the scale of deployment is larger, performing threat library and patch upgrades may have a greater impact on the performance of the cloud platform, and the cost of this model is higher.  
The second approach is a network-based micro-segmentation approach, which configures virtual machines on the same subnet into segregated VLANs, making it impossible for virtual machines to interoperate at the virtual switch level through network isolation. Virtual machine traffic has to be forwarded to the VxLAN Tunnel Endpoint (VTPE) switch first, and then \"secure service chaining\" is implemented through the SDN controller. The advantages of this approach are that it is easier to implement, less costly, has no software compatibility issues, does not consume computing resources, and is more stable than the business-based micro-segmentation approach. However, this approach has some drawbacks. Firstly, the policy is not as fine-grained as the business-based micro-segmentation approach. Additionally, the SDN controller needs to manage virtual switches to implement network-based micro-segmentation. Otherwise, it cannot ensure that virtual machines will not interoperate at the virtual switch level, and it is easily hijacked by the network manufacturer. Moreover, during the process of changing the network configuration, information such as IP addresses needs to be changed, which can cause business interruptions, making it unacceptable for certain time-sensitive servicesOur research focuses on the improvement of network-based micro-segmentation methods.
# Nationwide Flood Monitoring for Disaster Risk Reduction Using Multiple Satellite Data
## 2 Materials and Methods
### Synchronized Floodwater Index  
#### 2.4.1 Modified Land Surface Water Index (MLSWI)  
MLSWI was used for floodwater detection in Equation (1) [25; 26]. MLSWI can be developed and applied to temporal processing to extract floodwater using annual time-series data such as the cloud-free 46 images in 2015. After adjusting the range of MLSWI according to land classification at training sites in the Sirajganj district (2480 km\({}^{2}\)), the detected floodwater areas were validated to be representative of the seriously flood-damaged district, and had been listed by BWDB as one of the priority areas for the implementation of flood mitigation measures. The time-series MLSWI of floodwater was matched with the time-series water levels observed in 2015. In addition, the behavior of the time-series MLSWI was evaluated and analyzed with in-situ data, ground truth samples.  
\[\text{MLSWI}_{267}=\frac{1-\rho_{NIR}-\rho_{SWIR}}{1-\rho_{NIR}+\rho_{SWIR}} \tag{1}\]  
where \(\rho\) is the atmospherically corrected surface reflectance of MODIS, \(\rho_{\text{NIR}}\) is band 2 (NIR: 841-876 nm), \(\rho_{\text{SWIR}}\) is band 7 (SWIR: 2105-2155 nm).
## 1 Introduction
The findings of the study indicate that the utilization of graphene nanofluids with minimum quantity lubrication (MQL) demonstrates promising potential as an effective alternative for reducing surface roughness, tool flank wear, and cutting temperature. [PERSON] et al. [23] explored the efficacy of nanofluid in terms of its impact on tool life, wear mechanisms, surface roughness, machined surface morphology, and material removal rate during the turning process of 30 CrMnSiA high-strength low-alloy steel. The experimental setup involved the utilization of the minimum quantity lubrication (MQL) technique along with SiO\({}_{2}\)-H\({}_{2}\)O nanofluids (referred to as NF-MQL). The Multi-response optimization analysis unveiled that the NF-MQL cutting condition emerged as the most optimal choice, leading to notable enhancements of 28.34% and 5.09% in surface roughness and material removal rate, respectively. [PERSON] et al. [24] conducted process parameter optimization utilizing sustainable cooling techniques, with the objective of enhancing the surface quality of the finished product while simultaneously reducing energy and resource consumption. The nanofluids were prepared by incorporating silicon carbide (SiC) nanoparticles (NPs) into a soluble oil medium at different weight percentages (0.5 wt%, 1 wt%, and 1.5 wt%). Furthermore, the experimental findings indicate that the SiC-based nanofluids, when employed in MQL mode, exhibit superior turning performance compared to conventional MQL.
## 4 Discussion
### Effect of Stitching Thread Thickness  
In order to analyze the effect of stitching thread thickness on failure and the residual strengths of the stitched composites after impact, the 5 \(\times\) 5 laminates with three stitching thread thickness, namely 500d, 1500d and 3000d (500d, 1500d, and 3000d laminates), were investigated after the impact of 10 J.  
Figure 11: Distributions of different damage modes with different stitched densities after the low-velocity impact damage: (**a**) MTF; (**b**) FCF; (**c**) FTF; and, (**d**) DF.  
Figure 12: The predicted residual strengths with different stitched densities.  
Figure 13 shows the failure of stitching thread in stitched composites with three different stitching thread thicknesses after the impact of 10 J. It is observed that the SBF is only found in the 500d stitched composite, while no SBF occurred in the 1500d and 3000d stitched composites due to the maximum stresses of stitching elements being lower than the strength of the stitch.  
Figure 14 shows the progressive damage processes of stitched composite laminates with different stitching thread thicknesses after impact of 10 J. Due to the SBF occurring in the 500d laminate, its damage modes and damage area are significantly different from the 1500d and 3000d laminates. As shown in Figure 15, the final damage modes and damage areas of the 1500d and 3000d laminates are similar. However, the final damage area of the 500d laminate is far larger than the other two laminates and its final damage mode contains a large number of fiber failures (FTF + FCF), especially given that the FTF is much more serious than the other two. With the increase of the number of layers, the damage area of the MTF decreases firstly and then increases, the FCF occurs in the first three layers and the damage area decreases rapidly, the FTF only occurs in the 6 th-8 th layers and it is rarely found in the stitched (1500d and 3000d) composites, moreover, the damage area of the DF shows a significant increase.  
Figure 14: Progressive damage processes of the laminates after the impact of 10 J.  
Figure 13: SBF of the laminates after the impact of 10 J.  
Figure 16 shows the predicted residual strengths of the laminates with three stitching thread thicknesses. When compared with the 500d laminate, the residual strengths of the 1500d and 3000d laminates are increased by 43.5% and 47.8%, respectively. It indicates that the greater the stitching thread thickness of the stitched composites, the greater the residual strength. This is consistent with the conclusion of literature [30]. However, the gap between the 1500d and 3000d laminates is 3%. It means that if there is no SBF, the stitching thread thickness will have little effect on the residual strength, but if it does, there will be a significant effect, which is not reflected in the literature [30].  
Figure 16: The effect of stitching thread thickness on residual strength under the impact of 10 J.  
Figure 15: Distribution of different damage modes with different stitching thread thicknesses after the low-velocity impact damage: (**a**) MTF; (**b**) FCF; (**c**) FTF; and, (**d**) DF.
## 3 End-to-End Modeling
### Optimal SNR and Related Uncertainties  
The optimal SNR is defined as the minimal one to get a good detection of forest parameters. The SNR at the ground level (GE SNR) is chosen as an indicator for the evaluation. Of course, a better detection can be obtained for a greater SNR, but the lidar characteristics are strongly constrained for air- and space-borne systems by this parameter. Getting a lower SNR, there will be less constraint on the payload (e.g., energy, mass, volume).  
**Optimal SNR for GE detection**. The input signals are simulated from airborne measurements considering a 20 m footprint. By applying the EES, the PDF of the ground echo (GE) detection _vs._ the GE SNR is derived (Figure 9). The result shows that the optimal SNR at the ground level to get a good GE detection is \(\sim\)6.  
**Optimal SNR for forest parameters**. The GE detection is not sufficient to ensure a good assessment of both forest vertical structures and optical parameters. Therefore, the optimal SNR is studied by considering the uncertainties on these parameters. The acceptable uncertainty on the lidar-derived _TTH_ (\(\varepsilon_{TTH}\)) and _QMCH_ (\(\varepsilon_{QMCH}\)) is 1.5 m and 5%, respectively, as described in [PERSON] and [PERSON] [42]. The uncertainty on \(\alpha\) depends on the one on _FOT_. Hence, the _FOT_ at the canopy bottom, which is an integrated value, was preferred for this study instead of \(\alpha\). Figure 10 gives the results of the relative error simulations to retrieve the _TTH_, _QMCH_ and _FOT_ for different GE SNR. We can consider that sufficient accuracy can be obtained for all parameters for a GE SNR larger than 10. In the following, the link budget of the spaceborne lidar was then assessed using the optimal _SNR0_ = 10.  
Figure 8: The probability density functions (PDF) of the good detection of the ground echo (GE) _vs._ footprint diameters.
## 6 Model Interpretation Results
### Global Explanations
The effect of increasing the receiver's altitude (lower left panel in Figure 10) shows a sinus-shaped (but globally increasing) contribution with less than ca 6 dB and 4 dB impacts above and below the zero line, respectively. The effect of clutter height is shown in the lower right panel in Figure 10. Up to 11 m, clutter height has zero influence on the PL behavior of the terrain. From 11 m to 16 m, clutter height has a constant impact of under 2 dB on the PL. (3) Interactive Feature Marginal Contribution  
Figure 11 demonstrates the contribution of the interaction effect (explained by Equation (11)) between the independent features. The value of the color represents the average contribution of the combination of the corresponding feature values in dB units to the model's PL predictions. The interaction effects must be interpreted beyond the net effect of each single independent feature, which has been incorporated in model decisions beforehand. The interaction of distance and the Tx-Rx angle, which is identified as the foremost interactive effect in our model, is represented in the foremost panel in Figure 11. The combination of distance and the Tx-Rx angle can be understood as a proxy feature of site-specific attributes, e.g., a building's density, shape, material, etc., at each receiver's location point. The trained EBM model based on the measurements along the survey routes suggests receiver location-specific effects on PL ranging from \(-\)20 dB up to \(+\)20 dB, depending on the receiver point, with most of the locations in the average range. The result shows distinct spatial zones depending on distance and the Tx-Rx angle ranges. For example, the area with the highest interactive effect on increasing PL is the region comprising the locations with a distance above 600 m from the transmitter location and Tx-Rx degrees ranging from \(-\)120 degrees up to \(-\)175 degrees, while the region with a distance above 600 m from the transmitter location and Tx-Rx degrees ranging from 50 degrees up to 100 degrees are the receiver locations with the highest interactive effect on decreasing PL. Further interpretation of the interactive results requires more detailed spatial information of the area between the transmitter and the receiver, as well as the specific attributes of the receiver location. Figure 11: Interactive contribution of independent features to generate PL prediction.
## 3 Hydrogen Production Technologies
### Background Concepts
#### 3.1.3 Coal Gasification  
Coal is a chemically complex and highly variable substance, which can be converted into a variety of products. The gasification process of coal is one method to produce power, liquid fuels, chemicals, and hydrogen [46].  
Specifically, hydrogen is produced by first reacting coal with oxygen and steam--under high pressures and temperatures--to form synthesis gas (a mixture consisting primarily of carbon monoxide and hydrogen), like is shown in Equation (2).  
\[2\,\mathrm{CH}+\mathrm{O}_{2}+\mathrm{H}_{2}\mathrm{O}\ \xrightarrow{\mathrm{Heat + Pressure}}\ \mathrm{CO}+4\,\mathrm{H}_{2}+\mathrm{CO}_{2} \tag{2}\]  
After removing impurities from the synthesis gas, the carbon monoxide present in the gas mixture reacts again with steam to produce additional hydrogen and carbon dioxide, following the reaction of Equation (3).  
\[\mathrm{CO}+\mathrm{H}_{2}\mathrm{O}\ \xrightarrow{\mathrm{H}_{2}}+\mathrm{ CO}_{2} \tag{3}\]  
Hydrogen is removed in a separation system, and the highly-concentrated carbon dioxide stream is subsequently captured and stored.
## 3 Results  
### The Temporal Characteristic of SIUS  
#### 3.1.1 Total SIUS in 2000-2023  
Figure 2 presents the SIUS valuation results for Henan Province. The findings reveal that total SIUS increased from 53.41 Mt in 2000 to 499.35 Mt by 2023, exhibiting an average annual increase rate of 10%. Among the five downstream sectors, the building sector holds the largest share of SIUS, accounting for 67% of the total in 2023. With rapid urbanization, SIUS in the buildings sector in Henan Province continued to grow, from 37.11 Mt to 332.62 Mt. The second downstream sector is the machinery sector, which experienced significant growth from 9.89 Mt in 2000 to 97.37 Mt in 2023, maintaining an average annual expansion rate of 10%. The remaining three sectors (infrastructure, transportation, and domestic appliances) have smaller proportions of the total SIUS, not exceeding 14% in 2023.  
Figure 2: SIUS from 2000 to 2023 in Henan Province.
# Pas: Privacy-Preserving Authentication Scheme Based on SDN for VANETs
## 2 Relate Works  
### Symmetric Cryptography-Based Authentication Schemes  
In symmetric cryptography, the sender and the receiver share the same secret key. Compared to other cryptography mechanisms, symmetric cryptography has higher efficiency. In [8], vehicles generate a set of pseudonymous which handle depending on the seeds issued by the trusted authority, where RSUs are able to assign short-term pseudonyms for vehicles based on the handles. The proposed scheme alleviates the cost of generating and maintaining the pseudonyms for ambudsman and reduces the delay of changing pseudonyms. However, as only the pseudonym owner and RSU know the key corresponding to the pseudonym, when receiving the message from the sender, the receiver has to communicate with RSU to verify the legality of the message from the sender. Ref. [9] proposed prediction-based authentication (PBA). PBA adds the location prediction result generated by a position-prediction mechanism. In order to improve efficiency and reduce storage pressure, a short signature mechanism is adopted to guarantee the security of the location prediction result. [PERSON] et al. uses an efficient MAC-based message to achieve mutual authentication [10]. In the proposed scheme, all messages transmitted by vehicles do not include any identifying information, which ensures privacy protection. However, the above schemes cannot guarantee non-repudiation. Once the key is disclosed, it is difficult to identify the adversaries from all entities in VANETs.
# Preparation and Modification of Biochar Materials and their Application in Soil Remediation
## 3 Removal Mechanism of Major Pollutants by Biochar
### Precipitation  
Mineral components in biochar, such as CO\({}_{3}\)\({}^{2-}\), PO\({}_{4}\)\({}^{3-}\), SiO\({}_{3}\)\({}^{4-}\), Cl\({}^{-}\), SO\({}_{4}\)\({}^{2-}\), SO\({}_{3}\)\({}^{2-}\), and OH\({}^{-}\), combine with heavy metal ions to form water insoluble substances such as metal oxides, metal phosphates, and metal carbonates, which promote the adsorption and immobilization of heavy metals. [PERSON] et al. [92] believed that the adsorption of Cu, Zn, and Cd by fertilizer biochar was mainly attributed to the precipitation of CO\({}_{3}\)\({}^{2-}\) and PO\({}_{4}\)\({}^{3-}\), while the electron surface complexation via -OH groups or delocalized \(\pi\) was less.
# Shear Lag Effect on Box Steel Beams with Wide Curved Flanges
## 2 Wide-Flange Beam with Curved Flanges  
A special case of a girder cross-section is a wide-flange section with curved flanges, often used in bridge construction not only due to its favorable aerodynamic shape, but also due to its esthetically pleasing appearance (Figure 2). Let us consider a boxed cross-section continuous girder with an ideally linear stress-strain diagram, subjected to uniform transversal load, applied in the plane of the webs. For such a girder (assuming adequate L/H ratio) where the flanges behave in accordance with the hypothesis of plane sections, there is a stress variation across the width of the flange not only due to the flange shear deformability, but also due to the varying distance of the flange fibers from the neutral axis [7] depending on the degree of curvature. In practice, we mostly encounter convex curvatures of the lower flanges of girders, so it is necessary to determine the distribution of longitudinal stresses across the width of the flange, taking into account the parameters of flange curvature, its width, and the girder spans. For low values of the radius of the curvature of the flange, the impact of the reduction in shear lag (increasing the distance from the web-flange joint increases the distance from the neutral axis) is significant, and for high values (approaching the form of a flat flange), the impact of reduction will be negligible. Therefore, the concept of the \"effective angle\" (Figure 3) of the flange is introduced. Effective angle defines the part of the arc curvature that will remain \"active\", but unlike the case of flat flanges, the axial stresses of the effective flange part (normalized to the maximum stress of the flange) must have an equal resulting bending moment (relative to an arbitrary point) as the moment calculated from the stress state obtained by experimental/analytical/numerical analysis.  
Figure 2: Box cross-section with curved flange—Mainland—Ciovo Bridge [8].
# A Hybrid Multi-Agent Reinforcement Learning Approach for Spectrum Sharing in Vehicular Networks
## 4 Hybrid Training
### Centralized Learning (QMIX)  
In the centralized learning phase a central body, the QMIX, facilitates centralized learning by collecting and integrating relevant information from all agents that coordinate the learning process. Agents share their learning with the QMIX, thus fostering collaborative learning. The QMIX combines these decentralized learnings, thus resulting in a joint action value function [28]. This joint action value function guides the actions of all agents to achieve a common goal enhancing collaboration among them. Moreover, the small-scale characteristics of the communication channel are updated, and agents store their experiences. These experiences serve as valuable data for optimizing learning through gradient descent, thus further improving decision making over time.
## 7 Conclusions  
An innovative bionic Morse coding technique mimicking a humpback whale song is presented in this research. The mimicked communication signal can be detected by the eavesdropper but is excluded from the process of recognition as the communication signal characteristics are akin to a humpback whale song. The eavesdropper will assume it as a natural sound due to its signature. The humpback whale song segments are translated to standardized bionic Morse codes. Characters of the English language are compared with traditional Morse coding and found better speed with lower complexity. Less than \(10^{-3}\) BER is achieved at a five km transmission at SNR down to \(-7\) dB. The errors were diminished to zero BER by MP estimation and equalizing errors by VTRM technology. Proposed novel bionic Morse coding technique is feasible for LPR constraint covert communication which can be applied in military and oceanography for perfectly secure and stealthy communications. Future works include to verify the novel concept with the Doppler spread and experiments in lake and sea trails.  
All authors contributed significantly to the work presented in this manuscript. The detail of contribution is: conceptualization, S.L. and M.B.; methodology, M.B.; software, M.B.; validation, S.L., L.W. and G.Q.; formal analysis, S.L., M.B. and Y.T.; investigation, M.B. and L.W.; resources, G.Q.; data curation, S.L. and Y.T.; writing--original draft preparation, M.B.; writing--review and editing, S.L.; visualization, S.L. and M.B.; supervision, G.Q. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Natural Science Foundation of China [Grant Nos. 61771152, 61431004, 61601136 and 61601137], National Key R&D Program of China [Grant Nos. 2018 YFC0308500 and 2017 YFC0305702] and the Natural Science Foundation of Heilongjiang Province of China (Grant No. YQ2019F002).  
The authors declare no conflicts of interest.