esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Proposed HE-DEPSO Algorithm
### Adaptive Hybrid Mutation Operator
#### 4.1.2 Selection of Mutation Strategy for Adaptive Hybrid Mutation Operator  
The adaptive hybrid mutation operator implemented in the HE-DEPSO algorithm uses two mutation strategies that aim to improve the exploration and exploitation abilities of the HE-DEPSO algorithm at different stages of the evolutionary process. Concretely, for each individual \(X_{i,t}\) in the population, this operator generates a mutated vector \(V_{i,t}\) as follows:  
\[V_{i,t}=\begin{cases}X_{i,t}+F_{i}\cdot(X_{E_{r},t}-X_{i,t})+F_{i}\cdot(X_{P_ {r},t}-X_{HL_{r},t})&\text{if }rand[0,1]<\alpha_{t}\\ \omega\cdot X_{i,t}+c_{1}\cdot r_{1}\cdot(X_{gbest,t}-X_{i,t})&\\ +c_{2}\cdot r_{2}\cdot(X_{gbest,t}-X_{i,t})&\text{otherwise}\end{cases} \tag{39}\]where \(rand[0,1]\) is a random number selected uniformly within the interval \([0,1]\) and \(\alpha_{t}\) represents the probability of selecting between the \"DE/current-to-EHE/1\" mutation strategy and the adopted mutation strategy of the PSO algorithm (Equation (18)).  
The probability of selection \(\alpha_{t}\) is updated at each iteration according to Equation (33), taking a value of \(\tau=1.8\). Figure 2 shows the mutation strategy selection curve followed by the adaptive hybrid mutation operator of the HE-DEPSO algorithm. The probability selection curve described by Equation (33) with a value of \(\tau=1.8\), for a maximum number of iterations \(t_{max}\), is illustrated in red in Figure 2. On the other hand, Figure 2 shows, as an example, a possible distribution of occurrences among which is selected the mutation strategy \"DE/current-to-EHE/1\" (squares in blue color) or the adopted strategy of the PSO algorithm (circles in magenta color). According to these graphs, it can be observed that, within the first stages of evolution of the HE-DEPSO algorithm, the probability of selection \(\alpha_{t}\) tends towards values close to 1, which increases the probability that the mutation strategy \"DE/current-to-EHE/1\" is selected, and the balance between exploration and exploitation provided by this strategy is taken advantage of. On the other hand, towards the advanced stages of the algorithm evolution, the mutation strategy adopted from the PSO algorithm is selected more frequently; this implies that, during the advanced stages, there is a higher probability that the HE-DEPSO algorithm increases its exploitation ability due to more frequent use of the information of the best positions of each individual, as well as the information of the position of the best individual in the population.
## 5 Discussion
### Critical Issues in the Preprocessing Phase: Dark Pixels  
The preprocessing phase of S2 data highlighted critical issues, in particular those related to the presence of extremely dark pixels, also highlighted in previous research studies [2; 25; 26; 59], that can be misclassified as burned areas while the procedure generates commission errors. In the present work, data preprocessing accounted for all those issues in order to reduce the generation of false positives as much as possible. Specifically, a raster mask was generated for each satellite observation in order to mask out pixels corresponding to several other land cover types that are also relatively dark in this spectral domain, such as bare soil in arable land or dark areas that are due to water spectrum absorption or that are affected by topographic shadow (Table S2). In addition, the use of multitemporal series of optical satellite data requires spectral reflectances normalized for the BRDF effect to avoid the temporal spectral variability originating from the varying sun zenith angle throughout the solar year. To deal with all the above-mentioned requirements, the S2A L2A MUSCATE product has been selected as a data source in consideration of its major improvements when compared to the standard S2 L1C and L2A products. Thanks to a multitemporal cloud identification approach [46], these products provide more precise information about cloud and cloud shadow pixels. Moreover, products are terrain-corrected for areas affected by topographical shadow, including topographic mask and low sun mask, the latter considering pixel aspect, slope, and sun zenith angle. During the preprocessing phase, a proper masking of extremely dark pixels not representing burned areas plays a key role in decreasing the generation of false positives, besides reducing the computational effort.  
The S2 weak geolocation spatial accuracy, determined in a recent study to be around 12 m [55], currently requires an additional preprocessing step in order to improve the consistency of multitemporal pixel profiles. The new S2 archive release from the forthcoming S2 reprocessing campaign, foreseeing a geometric refinement making use of a large set of global ground control points obtained via automatic matching, should overcome this limitation and allow for improved geolocation spatial accuracy.
# Research on Tracking Control of Urban Rail Trains Based on Improved Disturbance Observer
###### Abstract
The strict condition that the rate of change of disturbance is equal to zero is also removed, which aligns better with the actual scenario of URTs operation. The rest of this paper is organized as follows. Section 2 analyzes the coupling force and running resistance to which the URTs is subjected and establishes a multiple point-mass model. In Section 3, an improved disturbance observer is designed, and proof of stability under the IDOBC method is given. Section 4 gives the simulation validation and statistical analysis. Some conclusions are provided in Section 5. The naming of the symbols is summarized in Table 1. \begin{table}
\begin{tabular}{c c} \hline
**Symbol** & **Description** \\ \hline \(x_{i}(t)\),\(v_{i}(t)\), and \(\hat{v}_{i}(t)\) & Position, speed, and acceleration of carriage \\ \(u_{i}(t)\) & The control input of carriage \\ \(f_{in_{(i+1)}}(t)\) & Coupling forces between \(i\)th and \((i+1)\)th carriage \\ \(\Delta\theta_{i(i+1)}(t)\) & Coupler deformation length \\ \(\kappa\) & The elastic coupling coefficient \\ \(S\) & The sum of the original length of the carriage and coupler \\ \(m_{i}\) & The mass of \(i\)th carriage \\ \(a_{i}\),\(b_{i}\), and \(c_{i}\) & The Davis coefficients \\ \(l_{r}\),\(\kappa\) & The length and center angle of the curve \\ \(\theta\) & The slope angle \\ \(l_{s}\) & The tunnel Length \\ \(f_{i}(t)\) & The running resistance of \(i\)th carriage \\ \(f_{ai}(t)\) & The additional resistance of \(i\)th carriage \\ \(\mathcal{O}_{i}(\cdot)\) & The unknown external disturbance of \(i\)th carriage \\ \(d_{Li}(t)\) & The lumped disturbance of \(i\)th carriage \\ \(x_{r}(t)\),\(v_{r}\) & The target position and speed \\ \(\tilde{x}_{i}(t)\),\(\tilde{v}_{i}(t)\), and \(\tilde{u}_{i}(t)\) & The position, speed, and control input error of \(i\)th carriage \\ \(L\) & The observer gain matrix \\ \(K\) & The controller gain matrix \\ \hline \end{tabular}
\end{table} 
Table 1: Nomenclature.
## 4 Conclusions  
In conclusion, this study came to fill a gap regarding the characterisation of the profile of volatile compounds of olive oils from the Douro region. It was possible to identify the volatile compounds characteristic of extra virgin olive oils from this region. In sensory terms, most of the extra virgin olive oils (approximately 64%) were classified as ripe fruity. Among the olfactory and gustatory sensations, the attributes of dried fruits, tomato, apple, tomato leaves, banana, and lavender stood out. Regarding volatile compounds, the following compounds were detected in all samples: (_E_)-2-hexenal, (_Z_)-3-hexen-1-ol, (_E_)-2-hexen-1-ol, (_Z_)-3-hexen-1-ol acetate, 1-hexanol, and 2-methyl-4-pentanal. The study of the sensory profile demonstrated the potential of this region in the production of differentiated oils with unusual sensory attributes. Considering the results obtained in the sensory analysis, it was impossible to separate the olive oils by municipalities or sub-regions. Thus, the volatile fraction study of the olive oils from the Douro region and their relationship with the sensory attributes are essential to guarantee their genuineness and identity regarding their future appreciation. It is necessary to characterise the genetic material present in the Douro region in future work.  
Figure 3: Dendrograms obtained from olfactory and gustatory sensations (**a**) and volatile profile (**b**) evaluated in olive oils from the Douro region.  
**Author Contributions:** Conceptualisation, N.R. and J.A.P.; methodology, K.S., N.R. and E.R.; validation, N.R., J.A.P. and E.R.; investigation, N.R., J.A.P. and E.R.; resources, J.A.P.; data curation, K.S.; writing--original draft preparation, K.S.; writing--review and editing, N.R., J.A.P. and E.R.; supervision, J.A.P.; project administration, N.R., J.A.P. and E.R.; funding acquisition, N.R., J.A.P. and E.R. All authors have read and agreed to the published version of the manuscript.  
**Funding:** The authors are grateful to the Foundation for Science and Technology (FCT, Portugal), which gave financial support through national funds FCT/MCTES (PIDDAC) to CIMO (UIDB/00690/2020 and UIDP/00690/2020) and SusTEC (LA/P/0007/2021). The authors are also grateful to the Project OILVECOA--Centenarian olive trees of Coa Valley region: rediscovering the past to valorize the future, ref. COA/BRB/0035/2019 and the GreenHealth Project (NORTE-01-0145-FEDER-000042) co-financed by European Regional Development Fund (ERDF) through the NORTE 2020 (Program Operational Regional do Norte 2014/2020). [PERSON] thanks to National funding by FCT--Foundation for Science and Technology, P.I., through the institutional scientific employment program contract.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
## 5 Field Vehicle Test Measurements
For example, for SV 22 in Trajectory 1, the uncertainty reaches 34 Hz in 40 s. This means that at the end of the tunnel the code phase offset of SV 22 is roughly 0.46 chips due to the disabling of the feedback component and the use of only the feed-forward component for tracking. This phase offset is still tolerable by the DLL discriminator, and as can be seen in Figure 31, the TCAPLL re-tracks the signal without re-acquisition. Compared to the stand-alone GPS, for which the receiver has to re-acquire the signal, the TCAPLL is roughly 0.6 s faster in finding the satellites. Finally, Figure 32 shows the PLI output of SV 19 when accelerations of 5 m/s\({}^{2}\) occur on the y-axis in Trajectory 1. The PLL bandwidth in the TCAPLL is set to 2 Hz and in the stand-alone GPS to 7 Hz. In the TCAPLL, the PLL maintains tracking all the time. However, for the GPS, this is not the case. The PLL loses track as soon as there is acceleration and is unable to track again, and the energy starts to shift between the in-phase and quadrature phase components. This shows the advantage of having a feed-forward component that helps the GPS receiver to cope better with dynamics even when using a 2 nd order PLL filter with a bandwidth as low as 2 Hz. The results obtained are comparable to a more sophisticated GPS that would use a higher order loop filter and larger bandwidth. In summary, the measurements obtained from the vehicle test drive validate the simulation results obtained in the previous section. It has been shown that with the same MEMS inertial sensors, the TCAPLL outperforms the MTi-G Xsens. Also, it provides a performance similar to the Javad Alpha receiver, which is a carrier differential GPS receiver, with the advantage of computing a navigation solution when there are fewer than four visible satellites. In addition, with the TCAPLL, after losing a satellite there is no need for re-acquisition for a certain period of time defined by the uncertainty of the feed-forward component. Moreover, if the satellite reappears after this period, the re-acquisition search \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Error [deg]** & **Roll** & & & **Pitch** & & **Heading** \\ \hline Trajectory & 1 & 2 & 1 & 2 & 1 & 2 \\ \(\sigma\) & 0.159 & 0.143 & 0.164 & 0.157 & 0.547 & 1.305 \\ mean & 0.096 & 0.058 & 0.196 & 0.185 & 0.413 & 1.191 \\ \hline \end{tabular}
\end{table} 
Table 7: Standard deviation and mean of the TCAPLL attitude error during Trajectory 1 and Trajectory 2. Figure 30: Feed-forward frequency uncertainty during Trajectory 1 (**left**) and Trajectory 2 (**right**). span is reduced due to _a priori_ information from the aiding frequency component. The analysis provided in this paper proves that with proper initialization and error modeling, the MEMS inertial sensors bring several advantages to the GPS receiver which can be crucial in challenging environments where bad GPS conditions exist.
## 3 Results and Discussion
### Effect of Vegetation  
The effect of plants on pollutant removal was tested by comparing the removal efficiency of three units with the same porous media (fine gravel): one unplanted (W2 FG-U), one planted with common reed (W3 FG-R), and one planted with cattail (W4 FG-C) (Table 2). The unit with cattail achieved the best performance in removing all pollutants, while the unplanted unit had the worst. The one-way between-groups ANOVA and [PERSON]'s HSD test (Table 5) showed a statistically significant difference in the average OM removal between units W2 FG-U and W3 FG-R and between W2 FG-U and W4 FG-C. In addition, there is a statistically significant difference in the average removal of nitrogen forms (TN and NH\({}_{4}\)-N) between units W2 FG-U and W4 FG-C (Table 5). Therefore, we conclude that the presence of plants creates favorable conditions in the CW, enhancing its effectiveness in removing these pollutants. As mentioned previously, plants transport oxygen to the rhizosphere, which is necessary for the growth of microorganisms, the decomposition of organic compounds, and nitrification. They also serve as a support medium by providing a surface for biofilm growth on the stems and roots [35; 50]. A crucial stage in the removal of nitrogen is the conversion of ammonium to nitrate, which is made easier by the oxygen expelled from plant roots. Furthermore, organic substances expelled by plant roots provide heterotrophic bacteria with carbon sources, facilitating denitrification and the breakdown of organic compounds. By stabilizing substrate particles, vegetation also improves adsorption and sedimentation processes, increasing the overall effectiveness of pollutant removal [36; 51].  
The broad root and rhizome systems of both species offer a large surface area for pollutant absorption, sediment stabilization, and microbial colonization. The thick root systems of _Typha latifolia_ and _Phragmites australis_ improve sedimentation and filtration by physically trapping suspended particles [35]. _Typha latifolia_ creates favorable circumstances for denitrification in deeper, anoxic zones, and while it provides enough aeration to support nitriifying bacteria, it is somewhat less effective at transferring oxygen [52]. The dynamics of microbial communities are greatly influenced by the presence of _Typha latifolia_ and _Phragmites australis_ in CW. Numerous microbial consortia, such as nitrifiers (i.e., _Nitrosomonas_ and _Nitrobacter_) and denitrifiers (i.e., _Pseudomonas_ and _Paracoccus_), which are essential for the nitrogen cycle, are found in root-associated biofilms [41]. Furthermore, aerobic heterotrophic bacteria, which decompose organic matter and improve COD and BOD removal, are supported by plant-mediated oxygenation. Studies have shown that, compared to unplanted systems, planted CWs support greater microbial diversity and enzymatic activity, which improves pollutant degradation [50].
# Security Hardening and Compliance Assessment of Kubernetes Control Plane and Workloads
## 5 Kubernetes Vulnerabilities and Kubernetes Penetration Testing
### Penetration Testing Tools, Demonstration, and Security Compliance Assessment
It assists security professionals and system administrators in evaluating the security posture of their Kubernetes environments through comprehensive automated security scans. By simulating potential attack vectors, Kube-hunter identifies misconfigurations, obsolete components, and other vulnerabilities that attackers could exploit. It can be crucial in securing Kubernetes infrastructure but must be incorporated into a comprehensive security framework for optimal defense against contemporary threats. Compliance assessment can be performed by using kube-bench. Kube-bench is an open-source utility that evaluates a Kubernetes cluster's configuration following the CIS (Center for Internet Security) Kubernetes Benchmark, a compilation of best practices designed to enhance the security of Kubernetes deployments. Figure 17: Kube-hunter deployment process. Figure 18: Kube-hunter scanning options. It automates the auditing of Kubernetes clusters, evaluating compliance with the CIS Kubernetes Benchmark and generating a comprehensive report on security configurations. The benchmark encompasses multiple Kubernetes components, such as the API server, Kubelet, controller manager, and scheduler, guaranteeing secure configuration for each element. The outcomes of the Kube-bench assessment can be categorized into the following segments: Master Node Security Configuration (including Master Node Configuration Files, API Server, Controller Manager, Scheduler), Etcd Node Configuration, among others. Kube-bench starts with assessing master node security compliance, as shown in Figure 19:  
The tool additionally offers solutions to address test results categorized as \"Warning\" and \"Failed\". Several recommended solutions have been previously articulated and elucidated in the prior section, thereby substantiating and validating the fundamental issue this paper seeks to address: The newly implemented Kubernetes clusters lack default security measures. Therefore, implementing robust measures is crucial to attain confidentiality, integrity, and availability and to strengthen the cluster's security posture. Figure 21 below illustrates remediation proposals for the master node:  
Figure 19: Kube-bench master node scanning. Figure 20: Kube-bench full scan results. * API server accepting anonymous requests (-anonymous-auth=true);
* Unsecured etcd communication channels;
* Kubelet authorization set to AlwaysAllow. * The remedial procedures recommended by kube-bench were implemented as follows:
* -anonymous-auth=false added to the API server manifest;
* Mutual TLS was enforced for etcd using custom CA-signed certificates;
* Kubelet authentication mode changed to webhook, and unauthorized cache TTLs tightened. A subsequent scan indicated substantial progress, with all critical problems rectified and outstanding warnings about documentation and manual file permission checks.
# Development of a Staggered PCD End Mill for Carbon Fiber Reinforced Plastic
## 2 Design of Staggered PCD End Mill  
### Structural Design  
Helix edge is often used in the side edge of cemented carbide or coated end mills [27]. These kinds of end mill have good cutting performance, but the wear resistance is poor. Straight edge is often used in PCD cutter and it has high machining accuracy. However, the straight-edge structure will generate large cutting force in machining. To reduce machining defects, improve machined surface quality and increase the cutter's life, this work combines the advantages of helix-edge and straight-edge structures in the design of staggered PCD end mill. The magnitude and direction of cutting force is decreased and changed by side-edge re-configuration of the staggered PCD end mill. Figure 1 shows the structure of the staggered PCD end mill.  
Traditional PCD end mill has co-rotating cutting-edge inclination [28], while in the staggered PCD end mill, the directions of cutting-edge inclination of two adjacent side edges are opposite. The staggered PCD end mill is composed of a cemented carbide body and four PCD inserts with different inclination directions. Two adjacent inserts have the same inclination magnitudes and different directions, and they form a pair of cutting units. The staggered PCD end mill can be used in flank milling and end milling.
# Unlicensed Spectrum Allocation for LTE and Wi-Fi Coexistence with HAP
## 2 Related Technology and Works  
The concept of unlicensed LTE was first introduced in the 3 rd Generation Partnership Project (3 GPP) Release 10. Years of advancement led to three main variants, namely LTE-U, Licensed Assisted Access (AAC), and MulteFire [2; 3; 4].
## 3 Results
### Circularity Assessment Frameworks
#### 3.2.4 MFA- and LCA-Based Tools  
1. Material Flow Analysis Tools (MFA). MFA is an analytical method that captures the state and changes of materials' stocks and flows in a particular system by calculating the mass balances over time within a defined space [65]. MFA-based tools focus on specific aspects of material circularity, namely the amount of materials used by calculating their mass. However, they fail to address other aspects such as material quality and resource scarcity. The main challenges inherent to MFA analysis are data uncertainty and information availability. Still, it can be applied at every analysis level due to its flexibility and simplicity [65]. An example is STAN (subSTance flow ANalysis) tool [66] which is free software that helps to perform material flow analysis according to the Austrian standard ONorm S 2096 (Material flow analysis--Application in waste management) under consideration of data uncertainties.  
2. Lifecycle-Based Tools. LCA is a tool to assess the environmental impacts of a product, process, or service along the entire life cycle. LCA is one of the tools mainly applied to quantify and evaluate the benefits/impacts of CE strategies and/or to choose between different circular strategies. Case studies in the built environment literature can be found on waste management systems and materials such as concrete and steel. Lately, LCA has been used to assess the environmental impacts of different end-of-life (EoL) alternatives for products and services [65]. However, conducting a transparent, effective LCA requires a longtime experience and holistic methodology on EoL assessments.  
Similarly, LCC-based tools are used to address the economic aspect of circularity in buildings, investigate the feasibility of circular solutions, and conduct financial impact analysis of circular business models.  
Integrating the lifecycle-based tools within other schemes such as sustainability certification systems helps to complement those and deliver more inclusive circularity assessments.