esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Water Stability and Permeability Characteristic of Phosphogypsum Sample  
As shown in Figure 3, the residual mass of the samples decreased under continuous shaking in water. The cumulative spalling mass of the samples treated with water E1 was 37.24 g, which was greater than that of those treated with the microbial solution. The microbially treated samples had a similar change tendency: the sample E2 treated by OD\({}_{600}\) = 0.1 had the lowest peeling amount at 19.45 g, while the result of the OD\({}_{600}\) = 0.5 treated sample E4 was slightly larger at 24.78 g. It can be seen from the spalling results that the water stability of the samples treated by microorganisms is improved.  
Figure 4 illustrates that the content of CaCO\({}_{3}\) at various stages of peeling has a decreasing trend, the outermost layer sample has the highest content of CaCO\({}_{3}\), and the internal transition gradually reduces. The linear curve was used to fit the downward trend. The outermost CaCO\({}_{3}\) content of the OD\({}_{600}\) = 0.5 treated sample is the highest. As the bacterial concentration decreased, CaCO\({}_{3}\) content slightly decreased. However, regarding the internal area of the sample, the content of CaCO\({}_{3}\) had the fastest decline in the E4 curve, and the gradient was the largest. This indicates that with the increase in bacterial concentration, the formation of CaCO\({}_{3}\) is more discrete, and the interior of the sample has a greater difference in CaCO\({}_{3}\) content.  
The permeability characteristics of the samples modified with different bacterial concentrations decreased significantly, which is shown in Table 4. The permeability coefficient  
Figure 4: The content of CaCO\({}_{3}\) of the peelings.  
Figure 3: Residual mass of sample.  
of most samples decreases by one order of magnitude compared with that of the untreated sample. Compared with the untreated sample, the average value of the modified samples treated with OD\({}_{600}\) = 0.1, 0.3, and 0.5 decreased by 45.82%, 24.03%, and 34.59%, respectively. The minimum value decreased by 36.16%, 15.71%, and 51.58%, respectively. The OD\({}_{600}\) = 0.5 treated sample had the largest differentiation coefficient, but it has the lowest permeability coefficient among the samples. The calcium carbonate particles generated after microbial mineralization can seal up the pores in the particles and the flow channels of the internal fluid. However, with the increase in the bacteria concentration, the permeability coefficient decreased, but the heterogeneity of the sealing treatment increased.
# Dynamic SDN Controller Load Balancing
###### Abstract  
The software defined networking (SDN) paradigm separates the control plane from the data plane, where an SDN controller receives requests from its connected switches and manages the operation of the switches under its control. Reassignments between switches and their controllers are performed dynamically, in order to balance the load over SDN controllers. In order to perform load balancing, most dynamic assignment solutions use a central element to gather information requests for reassignment of switches. Increasing the number of controllers causes a scalability problem, when one super controller is used for all controllers and gathers information from all switches. In a large network, the distances between the controllers is sometimes a constraint for assigning them switches. In this paper, a new approach is presented to solve the well-known load balancing problem in the SDN control plane. This approach implies less load on the central element and meeting the maximum distance constraint allowed between controllers. An architecture with two levels of load balancing is defined. At the top level, the main component called Super Controller, arranges the controllers in clusters, so that there is a balance between the loads of the clusters. At the bottom level, in each cluster there is a dedicated controller called Master Controller, which performs a reassignment of the switches in order to balance the loads between the controllers. We provide a two-phase algorithm, called Dynamic Controllers Clustering algorithm, for the top level of load balancing operation. The load balancing operation takes place at regular intervals. The length of the cycle in which the operation is performed can be shorter, since the top-level operation can run independently of the bottom level operation. Shortening cycle time allows for more accurate results of load balancing. Theoretical analysis demonstrates that our algorithm provides a near-optimal solution. Simulation results show that our dynamic clustering improves fixed clustering by a multiplicative factor of 5.  
multi controllers; architecture; SDN; load balancing +
Footnote †: journal:  
_Future Internet_**2019**, _11_, 75; doi:10.3390/f11030075
## 2 Security Considerations for Marine Network Protocols
### Non-Repudiation  
The firmware must verify that the receiver has received a message, and that a receiver is sure about the identity of a sender. Non-repudiation has been increasingly becoming important on other domains of security especially as it relates to forensics and legal challenges [16]. Non-repudiation is bound to become more relevant, even in a high risk environment, such as maritime commercial enterprises. For example, how can a port verify that a vessel operator received a set of instructions in an event where said operator says that no instructions have ever been received?
# Security and Privacy in Physical-Digital Environments: Trends and Opportunities
## 3 Security, Privacy, and Confidentiality
### Blockchain Security  
Blockchain technology provides a secure and dependable means of storing user data by employing a combination of consensus mechanisms, smart contracts, and encryption algorithms. Nevertheless, such designs are vulnerable to malicious attacks due to their inherent inadequacies. Therefore, it is imperative for blockchain developers to adopt robust security measures in the design and implementation of blockchain systems to ensure they meet the highest standards of security and reliability.  
The consensus algorithm plays a pivotal role in upholding the safety and efficiency of blockchain technology. It is responsible for ensuring that all nodes in a decentralized network are in agreement with respect to the state of the ledger. Practical Byzantine Fault Tolerance (PBFT), Proof of Work (PoW), Proof of Stake (PoS), and Delegated Proof of Stake (DPoS) [21] are a few examples of consensus mechanisms that help achieve the consistency and accuracy of data across different nodes. However, these algorithms are susceptible to security risks. For instance, the PoW mechanism is vulnerable to the double spend attack, which involves the fraudulent use of a cryptocurrency more than once.  
In MR, blockchain security is crucial for managing and verifying the authenticity of interactions and assets that bridge the digital and physical worlds. Blockchain systems can be used to protect MR assets by creating immutable records of virtual items and experiences, which can be \"anchored\" in real-world locations. However, similar to the Metaverse, MR experiences face risks associated with consensus mechanisms, where double-spending or unauthorized duplication of digital assets could compromise user trust. Furthermore, decentralized ledgers need to efficiently handle real-time data from MR environments without sacrificing security [22].
# Tomographic Diffractive Microscopy: A Review of Methods and Recent Developments
## 5 The Advancements of Tomographic Diffractive Microscopy
The advantages of TDM are remarkable; while microscopes like the digital holographic microscope are able to provide a 3D topography of the samples [23; 87; 88], the ability of quantitative reconstruction of the sample permittivity/refractive index using TDM is unique; moreover, the lateral resolution in TDM has been well improved far beyond the Rayleigh criterion [15]. The studies of TDM have been increasing rapidly in recent years. To our knowledge, the first commercial products of TDM were released by Nanolive in Switzerland in 2015 [89], and Tomocube KAIST in Korea at 2017 [90]. These work with transmission configuration and provide 3D reconstructions of cells with transverse resolutions of 200 nm and axial resolutions of 400 nm [91]. Hence, future developments may focus on the implementation of the reflection configuration and the use of multiple wavelengths of illumination to improve the axial resolution. Moreover, integrating TDM with other super-resolution techniques can provide multiple-modal image methods; for example, a combination of TDM with single molecule fluorescent microscopes is able to perform the structural and functional analysis of a sample simultaneously; a combination of TDM with scanning probe microscopy permits the structural, topographic, and chemical (tip-enhanced Raman spectroscopy, TERS) information of a sample. To the best of our knowledge, TDM has only been applied to investigate the individual structures, such as isolated cells and nano-fabricated structures, but three-dimensional imaging of unmarked raw tissues is also possible using TDM. However, every coin has two sides; it is worth noting here that the main drawbacks of TDM are: (i) TDM under Born/Rytov approximation is only valid for samples with low permittivity contrast \(\Delta\epsilon<0.1\); (ii) TDM under Born approximation has a resolution limit which is twice as good as the Rayleigh criterion resolution; (iii) the non-linear inversion procedures improve the resolution but are time-consuming. Several hours are at least necessary to reconstruct the investigated sample, thus it is difficult to realize real-time analysis for the samples using non-linear inversion methods. (iv) An isotropic resolution still remains a challenge, despite several studies reporting TDM with isotropic resolution [44; 57; 67], and a combination of sample rotation with illumination rotation not only needs accurate correction of the angles, but also greatly increases the amount of data collected [44; 67].
## 5 Statistical Analysis of Residual Displacement Ratios
### Effect of Displacement ductility  
Figure 14 illustrates the mean residual displacement ratios for different levels of displacement ductility. It is obvious that the influence of displacement ductility on residual displacement ratios strongly depends on the post-yield stiffness ratio. For a zero post-yield stiffness ratio, the mean \(C_{\text{r,seq}}\) increases and saturates as \(\mu\) increases. On the contrary, for positive post-yield stiffness ratio (\(r>0\)), the mean \(C_{\text{r,seq}}\) decreases with the increase in \(\mu\).  
This indicates that for elastic-perfectly plastic oscillators, the larger the displacement ductility, the higher the proportion of residual to peak inelastic displacements reaches. However, for hardening oscillators, the larger the displacement ductility, the lower the proportion of residual to peak inelastic displacements reaches.
## 3 Finite Element Analysis  
### Procedure  
The elasto-plastic analysis was performed using the commercial FEA code MARC to better elucidate the crack growth characteristics. A stationary crack was considered because, in this study, a branch angle \(\theta\) from the main crack was predicted. Figure 13 shows the mesh used, with a crack length \(a\) fixed at 5 mm; only the uniformly stressed square working section was considered, represented by a simple square in plain strain assumption with a thickness of 4 mm. Second-order isoparametric quadrilateral and triangular elements, refined to 25 \(\upmu\)m near the crack tip, were used with the singular elements [21] arranged around the tips; for smaller elements, they were greatly distorted due to a large number of loading cycles, resulting in remarkably poor analysis accuracy. The total numbers of elements and nodes were 644 and 1968, respectively. The boundary conditions applied for cruciform specimens under mixed mode I/II loading were also described. At each edge center, a pilot node was connected to the remaining nodes of that edge through a multipoint constraint; all the loads were applied to these pilot nodes as concentrated normal and shear forces (\(F\) and \(S\), respectively). The use of this mesh and loading procedure allowed the confirmation that the MTS occurred at \(\theta=\) -70.5\({}^{\circ}\)due to pure mode II loading in the elastic analysis. The contact between crack faces was taken into account and the friction coefficient was set to 0.3.  
When analyzing the fatigue problems, the choice of the material constitutive model is crucial. In this study, the model combining the nonlinear kinematic hardening rule with the isotropic hardening rule, developed by [PERSON] and [PERSON] [22] (C&L model), was used as  
\[t^{it+\Delta ti}\sigma_{y}={}^{0}\sigma_{y}+Q\Big{[}1-\exp\Big{(}-B^{it+\Delta ti }\bar{e}^{p}\Big{)}\Big{\}} \tag{14}\]  
\[\mathrm{d}\alpha=\frac{2}{3}h\mathrm{d}e^{p}-\zeta\mathrm{d}a\mathrm{d}\bar{e} ^{p} \tag{15}\]  
where \({}^{it+\Delta ti}\sigma_{y}\) is the updated yield stress at time \(t_{i}+\Delta t_{i}\), \({}^{0}\sigma_{y}\) is the initial yield stress, \(Q\), \(B\), \(h\), and \(\zeta\) are material constants,\({}^{it+\Delta ti}\bar{e}^{p}\) is the accumulated effective plastic strain at \(t_{i}+\Delta t_{i}\), \(\alpha\) is the shift of the yield surface center, \(e^{p}\) is the plastic strain, and \(\mathrm{d}\) of \(\mathrm{d}\alpha\) and \(\mathrm{d}\bar{e}^{p}\) implies increment. The material constants for RP and RF, determined via strain controlled uniaxial fatigue experiments, are summarized in Table 4 along with [PERSON]'s modulus \(E\) and Poisson ratio \(\
u\). The FEA was performed on these two rail steels to clarify the material effect on the crack growth rate.  
Figure 11: Branch crack growth rates of mixed mode I/II against \(\Delta K_{\mathrm{I}}\) for RP.
## 5 Second Generation: Optimization of Virtual Inertia Systems
### Second Generation of Virtual Synchronous Generators
Figure 16: Comparison of traditional virtual synchronous generator (VSG) controller with the online learning based controller: (**a**) frequency of the system for step load changes; (**b**) power exchange with the system (Adapted from [91]). Figure 15: Modified virtual synchronous generator (VSG) using adaptive dynamic programming (ADP) (**a**) overall schematic of the controller; (**b**) the action and critic neural network based structure. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Parameter** & **No VI** & **Simple VSG** & **ADP Based VSG** \\ \hline Peak Power for Event A & 0 W & 2184 W & 1979 W \\ Settling time for Event A & 12.6 s & 35.1 s & 31.3 s \\ Peak Power for Event B & 0 W & \(-\)2235 W & \(-\)2029 W \\ Settling time for Event B & 11.1 s & 29.1 s & 26.6 s \\ Energy delivered (Wh) & 0 Wh & 8.2 Wh & 6.2 Wh \\ Net energy exchanged (Wh) & 0 Wh & 1.6 Wh & 0.9 Wh \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Performance comparison of the system without virtual inertia (VI), simple virtual synchronous generator (VSG) based and adaptive dynamic programming (ADP) based VSG (Data from [91]).
## 4 Results and Discussion
### Feature Extraction
#### 4.2.1 Time Domain Feature Extraction
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \multirow{2}{*}{**Particle Diameter**} & \multirow{2}{*}{**Quartile**} & \multicolumn{4}{c}{**Bubbly Flow**} & \multicolumn{4}{c}{**Slug Flow**} & \multicolumn{4}{c}{**Annular Flow**} \\ \cline{3-10}  & & \(m\) & \(S\) & \(R\) & \(m\) & \(S\) & \(R\) & \(m\) & \(S\) & \(R\) \\ \hline \multirow{3}{*}{1.5 mm} & min & & & & 5.74 & 0.28 & 2.08 & 8.02 & 0.33 & 2.35 \\  & median & & & & 6.13 & 0.38 & 2.65 & 10.27 & 0.46 & 3.11 \\  & max & & & & 7.05 & 0.60 & 3.50 & 17.48 & 0.74 & 4.40 \\ \hline \multirow{3}{*}{3 mm} & min & 4.65 & 0.21 & 1.47 & 4.73 & 0.38 & 2.43 & 4.93 & 0.27 & 1.79 \\  & median & 4.85 & 0.30 & 2.18 & 5.05 & 0.54 & 3.64 & 5.27 & 0.29 & 2.26 \\  & max & 5.01 & 0.44 & 3.01 & 5.49 & 0.86 & 5.08 & 5.88 & 0.51 & 3.25 \\ \hline \multirow{3}{*}{6 mm} & min & 4.11 & 0.17 & 1.26 & 3.38 & 0.31 & 1.99 & & & \\  & median & 4.60 & 0.26 & 1.91 & 3.61 & 0.37 & 2.52 & & & \\  & max & 4.76 & 0.40 & 2.71 & 3.97 & 0.50 & 3.51 & & & \\ \hline \multirow{3}{*}{all} & min & 4.11 & 0.17 & 1.26 & 3.38 & 0.28 & 1.99 & 4.93 & 0.27 & 1.79 \\  & median & 4.70 & 0.28 & 1.98 & 4.91 & 0.41 & 2.79 & 9.00 & 0.40 & 2.72 \\  & max & 5.01 & 0.44 & 3.01 & 7.05 & 0.86 & 5.08 & 17.48 & 0.74 & 4.40 \\ \hline \end{tabular}
\end{table} 
Table 2: Distribution of time domain parameters of flow patterns.
## 3 Results  
### Fuel Dynamics Estimated from MODIS NDVI Products  
The shrublands/grasslands from the Owyhee Uplands region showed a high degree of interannual variability in vegetation greenness, as depicted by the NDVI profile (Figure 3). There was a slight but gradual increase in greenness throughout the 2000-2011 time periods. One of the high fire years (2005) had the highest NDVI values, and two of the other three high fire years had higher than average NDVI profiles those from the other years. Plots of NDVI time series in grasslands (not shown) showed the same general patterns, although the NDVI values tended to be higher than in shrublands.  
Decided differences were noted between images depicting spatial patterns in live fuels for low versus high fire years (e.g., 2001 versus 2005; Figure 4). Greenness was highest in the spring, which is when live fuel loads should be the greatest. This is when rainfall is the most plentiful, and vegetation is actively growing throughout the region. Variability in greenness patterns in the imagery tended to be highest in the spring datasets. Meanwhile, the summer data depicted much lower levels of green vegetation throughout the region. Shrubland/grassland areas had lower levels of heterogeneity in greenness patterns in the summer than in the spring (Figure 4). These areas typically \"brown-up\"during the summer months as the rainfall diminishes. Areas with high greenness in the spring, and low greenness in the summer, have the greatest potential for burning.  
Figure 4: Image comparisons showing live fuels for a low fire year (2001) versus a high fire year (2005) for spring (**top**) and summer (**bottom**). The darker tone of the 2005 spring live fuel image indicates higher biomass for that year. Differences between spring and summer images indicate the loss of green biomass as a function of summer heat and seasonal dryness. The red circle indicates an area where fire occurrence was especially frequent from 2000 to 2011, and includes the Murphy Fire.  
Figure 3: Seasonal Normalized Difference Vegetation Index (NDVI) profile for shrullands in the study area (aggregated from 3357 shrubland plots and field data). Arrows denote years that had large burned area relative to other years. The trend line indicates that greenness in these shrullands trended upward over the time frame.  
Comparison between shrubland sites that burned at least once between 1984 and the present, and those that did not, indicated spectral differences between the two groups (Figure 5). Those sites that burned at least once tended to have higher live biomass levels in spring and higher dead biomass levels in summer than those sites that did not burn during the time frame. Figure 5 shows dead biomass for one burned site versus the mean dead biomass for sites that have not recently burned. We noticed that the levels of dead biomass are often, but not always, particularly high during the year that the site burned.
# Rapid Classification of Wheat Grain Varieties Using Hyperspectral Imaging and Chemometrics
## Materials and Methods  
### Sample Preparation of Wheat Seeds  
Five varieties of wheat seeds, including Annong1124, Longpingmai6, Shannong102, Weilong169, and Zhenmai9, were friendly provided by Anhui Longping High-Tech Seed Industry Co., Ltd. in Hefei, Anhui province, China. They were harvested in 2018, packed in kraft bags, and then sent to the laboratory. After removing the shrivelled and damaged individuals, a total of 33,494 wheat seeds were obtained. There were 7388 seeds for Annong1124, 6240 seeds for Longpingmai6, 6394 seeds for Shannon902, 6326 seeds for Weilong169, and 7146 seeds for Zhenmai9, respectively. Wheat varieties were marked by corresponding number of 1, 2, 3, 4, and 5 for convenient recording according to the above-mentioned rank.
###### Abstract  
Internet growth has generated new types of services where the use of sensors and actuators is especially remarkable. These services compose what is known as the Internet of Things (IoT). One of the biggest current challenges is obtaining a safe and easy access control scheme for the data managed in these services. We propose integrating IoT devices in an access control system designed for Web-based services by modelling certain IoT communication elements as resources. This would allow us to obtain a unified access control scheme between heterogeneous devices (IoT devices, Internet-based services, etc.). To achieve this, we have analysed the most relevant communication protocols for these kinds of environments and then we have proposed a methodology which allows the modelling of communication actions as resources. Then, we can protect these resources using access control mechanisms. The validation of our proposal has been carried out by selecting a communication protocol based on message exchange, specifically Message Queuing Telemetry Transport (MQTT). As an access control scheme, we have selected User-Managed Access (UMA), an existing Open Authorization (OAuth) 2.0 profile originally developed for the protection of Internet services. We have performed tests focused on validating the proposed solution in terms of the correctness of the access control system. Finally, we have evaluated the energy consumption overhead when using our proposal.  
access control; Internet of Things; security; MQTT; OAuth Article
## 2 Materials and Methods
### The Reference Measurements and Cumulative Error
The mean distance deviation is estimated by comparing the surfaces of the optically scanned implant and the nominal CAD implant. The magnification error is obtained by rescaling the optically scanned implant in the x-, y-, and z- axis scales to fit the nominal CAD implant. In order to verify the results of the surface comparisons, mesh sensitivity analyses were performed to confirm an optimal mesh size for reference models of both the SD skull and the implant. Finally, the combined standard uncertainty of medical imaging, 3D thresholding, 3D modeling, and AM is evaluated in terms of length-dependent (LD) and non-length-dependent (NLD) components. The worst-case error of the respective process is calculated by multiplying the LD error with the maximum length of the implant and summing the NLD error. Subsequently, the error of each process is summed to evaluate a cumulative error for the end-use implant.