esa-sceva/satcom-chunk-collection huggingface dataset:
# Battery Characterization via Eddy-Current Imaging with Nitrogen-Vacancy Centers in Diamond
## 3 AC Magnetometry  
The PL of a diamond sample displays various cross relaxation features, extensively discussed in the literature [13, 14, 15], as a function of the bias magnetic field, as shown in Figure 2. In this paper, we exploit a cross-relaxation feature between NV and P1 centers occurring at 51.2 mT (area B in Figure 2a). This feature is used in the battery measurement because of its improved sensitivity compared to the broad NV-NV cross-relaxation feature near the zero field (area A), and its reduced dependence on the magnetic field compared to cross relaxation with NV centers not aligned along the magnetic field at 60 mT (area C) and to the ground state level anticrossing (GSLAC) feature at 102.4 mT (area D). Figure 2b shows the corresponding signal amplitude \(R\) detected with the LIA, demodulated at the referenced frequency. To maximize the response to alternating signals, \(R\) has to be maximized. The NV features seen in Figure 2 are expected to display a temperature dependence. For example, the NV-P1 cross-relaxation features are expected to shift by \(-1.34\,\mathrm{\SIUnitSymbolMicro T}/\mathrm{K}\) at room temperature [16], which can lead to drifts and be interpreted as magnetic field noise. As noted in the inset (d), we chose to use the features at 52.5 mT to detect the AC magnetic signals. The noise sensitivity of the sensor for the parameters used in this experiment leads to an estimated sensitivity of \(40\,\mathrm{nT}/\sqrt{\mathrm{Hz}}\) with a bandwidth of 100 kHz. It should be pointed out that the bandwidth of this technique can be expanded up to MHz, depending on pump-power intensity and NV-axis alignment with respect to the external magnetic field [11].  
Figure 2: **(a)** Photoluminescence (PL) of nitrogen-vacancy (NV) centers as a function of the background magnetic field. The four areas A, B, C and D that can be exploited for magnetometry indicate features due to spin mixing, cross relaxation between NV centers and P1 centers, cross relaxation with NV centers that are not aligned along the magnetic field, and ground state level anticrossing, respectively. **(b)** Corresponding amplitude of lock-in amplifier (LIA) referenced at 100 Hz for those features. **(c)** Zoomed-in B area of **(a)**, PL recorded with field-modulation depth of 0.48 mT at 100 Hz. **(d)** Zoomed-in B area of **(b)**, indicating the working point at 52.5 mT.
## 3 Results
### Data Statistical Analysis
Due to the magnitude of the effect size, it is worth highlighting the differences between the baseline case and the +40 V\({}_{\rm T}\) case for the bare headform in the left side impact (0.280 \(\pm\) 0.008 vs. 0.540 \(\pm\) 0.002) and in the right-side impact (0.750 \(\pm\) 0.007 vs. 1.060 \(\pm\) 0.015). \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Front (Y-Rot)** & **Left Side (X-Rot)** & **Right Side (Z-Rot)** \\ \hline Coating & 6.14 \(\times\) 10\({}^{-11}\) & 2.86 \(\times\) 10\({}^{-10}\) & 1.73 \(\times\) 10\({}^{-12}\) \\ \hline Tangential velocity & 2.78 \(\times\) 10\({}^{-10}\) & 1.61 \(\times\) 10\({}^{-14}\) & 6.35 \(\times\) 10\({}^{-14}\) \\ Interaction & 4.60 \(\times\) 10\({}^{-7}\) & 0.00131 & 9.13 \(\times\) 10\({}^{-7}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Two-way ANOVA results (\(p\)-values) for the BrIC. \(p\)-values \(<\) 0.05 portrayed as shaded cells. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Front (Y-Rot)**} & \multicolumn{3}{c}{**Left Side (X-Rot)**} & \multicolumn{3}{c}{**Right Side (Z-Rot)**} \\ \cline{2-10}  & **HIC** & **–40\% V\({}_{\rm T}\)** & **Base Case** & **+40\% V\({}_{\rm T}\)** & **–40\% V\({}_{\rm T}\)** & **Base Case** & **+40\% V\({}_{\rm T}\)** & **Base Case** & **+40\% V\({}_{\rm T}\)** & **Case Case** & **+40\% V\({}_{\rm T}\)** \\ \hline \multirow{4}{*}{**Front (Y-Rot)**} & Average & 1213 & 870 & 857 & 1049 & 1056 & 1145 & 893 & 825 & 781 \\ \cline{2-10}  & SD & 30 & 11 & 15 & 58 & 20 & 68 & 32 & 15 & 16 \\ \cline{2-10}  & CV(\%) & 2.51\% & 1.31\% & 1.73\% & 5.53\% & 1.86\% & 5.98\% &  
Finally, significant differences of the two-way ANOVA for the peak of the resultant angular acceleration (PAA) were found both for the coating factor, the magnitude of the tangential velocity and their interaction in all three impact directions (Table 8). In this case, all post-hoc comparisons for the covered headform resulted in significant differences and the effect size revealed strong differences in most cases. On the contrary, in the case of the bare headform, only one comparison for the tangential velocity with the bare headform resulted in significant differences (Table 9). This comparison was between the base case and the +40% V\({}_{\rm T}\) case in the left side impact (3330 \(\pm\) 233 rad/s\({}^{2}\) vs. 6241 \(\pm\) 277 rad/s\({}^{2}\)). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Front (Y-Rot)**} & \multicolumn{3}{c}{**Left Side (X-Rot)**} & \multicolumn{3}{c}{**Right Side (Z-Rot)**} \\ \cline{3-11}  & **BrIC** & \multicolumn{3}{c}{**–40\% V\({}_{\rm T}\)**} & **Base Case** & **+40\% V\({}_{\rm T}\)** & **–40\% V\({}_{\rm T}\)** & **Base Case** & **+40\% V\({}_{\rm T}\)** & **Base Case** & **+40\% V\({}_{\rm T}\)** & **Base Case** & **+40\% V\({}_{\rm T}\)** \\ \hline \multirow{5}{*}{**Casing**} & Average & 0.210 & 0.310 & 0.400 & 0.170 & 0.280 & 0.540 & 0.620 & 0.750 & 1.060 \\ \cline{2-11}  & SD & 0.004 & 0.007 & 0.001 & 0.020 & 0.00
# Biosorption of Pb(II) Using Coffee Pulp as a Sustainable Alternative for Wastewater Treatment
## 4 Conclusions  
At the level of adsorption parameters, this research concluded that the optimum pH for the removal of Pb(II) with coffee pulp was 2.0 units, and the kinetic adsorption model that adjusted the most was the pseudo-second order model of [PERSON], with a Langmuir isotherm and pHpzc of 3.95 units. The removal of Pb\({}^{2+}\) ions with the coffee pulp was 86.45%, and the capacity of maximum adsorption was 24.10 mg\(\cdot\)g\({}^{-1}\) using a particle size of 180 \(\upmu\)m, and a contact time of 105 min at 100 RPM at room temperature in synthetic wastewater.  
Finally, we expressed that coffee pulp can be used as a sustainable alternative for the removal of lead in synthetic and real wastewater, which would contribute to achieving goal 3.9 of Goal 3 \"Health and Well-being\" and goal 6.9 of Goal 6 \"Clean Water and Sanitation\" of the SDGs of the 2030 agenda. Coffee pulp can also be used to remove other inorganic pollutants that have a high environmental impact on the ecosystem.  
**Author Contributions:** Performed the experimental methodology, systematization, and analytical treatment of the experimental data obtained, [PERSON]; guided the research conducted, [PERSON], [PERSON], and [PERSON]; drafted the manuscript, [PERSON] and [PERSON]; translated the article and reviewed the writing and citation of the bibliographic references, [PERSON], [PERSON], and [PERSON]. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
Figure 6: Stages and inputs involved in the Pb biosorption process in wastewater at the pilot scale.  
**Acknowledgments:** We thank [PERSON] (head of the chemistry department) and [PERSON] (Pontificia Universidad Javeriana) for all the support and encouragement they gave us during the time we spent undertaking this research work.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# A Disturbance Rejection Control Method Based on Deep Reinforcement Learning for a Biped Robot
## 2 Related Work  
### Calculation of the ZMP Position  
In 1972, [PERSON] and [PERSON] defined the ZMP concept at the beginning of their paper on the control of humanoid robots [2]. The ZMP is the point on the ground at which the tipping moment equals zero. According to [PERSON]'s theory, when a person stands upright on the ground, their ZMP coincides with the projection point of the center of gravity. The smallest polygonal area of all contact points between the foot and the ground is called the support polygon. If the center of gravity projection can be kept within the support polygon, then a person maintains balance no matter how they move.  
Humanoid robots are usually equipped with six-axis force/torque sensors on the soles of their feet. One such sensor is installed on each foot at the joint between the sole of the foot and the ankle joint. Equations (1) and (2) are the ZMP formulas for the right foot based on measurements made by one six-axis force/torque sensor:  
\[p_{R_{x}}=\frac{\left(-\tau_{y}-f_{x}d\right)}{f_{2}}, \tag{1}\]  
\[p_{R_{y}}=\frac{\left(\tau_{x}-f_{y}d\right)}{f_{2}}, \tag{2}\]  
where  
\[p_{R}=\left[p_{R_{x}}\ p_{R_{y}}\ p_{R_{z}}\right]^{T}\]  
Here, \(p_{R}\) is the ZMP position of the right foot, and \(d\) is the installation height of the sensor from the ground.  
After calculating the ZMP positions, \(p_{R}\) and \(p_{L}\), of the two feet, the ground forces \(f_{R}\) and \(f_{L}\) are obtained from the force-torque sensor measurements. Using this information, we obtain the ZMP position when the two feet are considered at the same time:  
\[p_{x}=\frac{p_{R_{x}}f_{R_{x}}+p_{L_{x}}f_{L_{z}}}{f_{R_{x}}+f_{L_{z}}}, \tag{3}\]  
\[p_{y}=\frac{p_{R_{y}}f_{R_{x}}+p_{L_{y}}f_{L_{z}}}{f_{R_{x}}+f_{L_{z}}}, \tag{4}\]
## 2 The Current Status and Challenges of Security Resource Management and Scheduling
[PERSON] analyzed the structural features of subway security service processes and used Generalized Stochastic Petri Nets (GSPNs) to model the subway security service processes, constructing an Embedded Markov Chain (EMC) that was isomorphic to the GSPN model in order to perform in-depth analysis of the subway security service process performance, effectively identifying bottlenecks in the process and providing a theoretical basis for the targeted optimization of the security system [14]. Traditional security resource scheduling often fails to account for real-time changes in passenger flows, making it inadequate for the rapidly fluctuating passenger volumes seen at high-speed train stations. Existing technologies have not fully utilized advanced data analysis and prediction models to enable dynamic security resource scheduling, limiting their optimization potential and effectiveness. Moreover, research on security resource scheduling in high-speed train stations remains relatively limited. Currently, the management of security resources in high-speed train stations primarily relies on traditional shift systems. These systems typically allocate security resources based on fixed time intervals and perform personnel rotations according to a predetermined schedule. Shifts are generally divided into fixed periods--such as morning, midday and evening--or organized according to peak and off-peak passenger flows [15], with each shift lasting for a set period (e.g., 8 h) of time to ensure that there are seamless security operations throughout the day. Although the shift system is simple and easy to manage, it lacks the flexibility and efficiency needed to handle fluctuating passenger volumes and emergencies at high-speed train stations. While it can maintain basic security procedures during normal operations, the fixed-shift system struggles to adapt to dynamic demands as passenger volumes can vary significantly during different time periods and under special circumstances. Therefore, the current security resource management approach adopted at high-speed train stations urgently requires more flexible and dynamic scheduling methods to effectively respond to variations in passenger flows across different periods and circumstances.
# A Relative Coordinate-Based Topology Shaping Method for UAV Swarm with Low Computational Complexity
## 6 Conclusions and Future Work  
The topology shaping method is the significant basis of functional topology construction in UAV swarm applications. In this paper, an LAPJV-based topology shaping method is proposed for the UAV swarm system. In this method, the mapping relationship from initial topology to target topology with minimum global energy consumption is fully considered. First, without relying on external localization information, the coordinates of the UAVs corresponding to the initial and target topology shape are derived by the MDS algorithm. Then, based on the linear assignment problem, the optimal mapping relationships with minimum global energy consumption are obtained through the LAPJV algorithm. Simulation results show that the proposed method can achieve optimal mapping with minimum global energy consumption for any target topology.  
Moreover, although the worst-case computational complexities of the LAPJV algorithm are the same as the improved KM algorithm, the proposed LAPJV algorithm reduces computation time by over 94% compared with the improved KM algorithm, the KM algorithm and the Auction algorithm in the case of 1000 UAV nodes. In addition, it does not rely on any external localization information, which is practical for swarming application scenarios in complex environments.  
In our future work, the idea of parallel computing can be applied to the proposed topology shaping method to further reduce the computation time. Moreover, topology  
Figure 11: The number of assignment statistics in the case of 1000 nodes. (**a**) Number of assignment statistics after column reduction; (**b**) Number of assignment statistics after reduction transfer; (**c**) Number of assignment statistics after augmenting reduction; (**d**) Number of assignment statistics after augmenting phase.  
shaping can be achieved much faster by reducing the connectivity between UAVs to form a sparse distance matrix, which is a more practical model.  
Conceptualization, Y.Y., X.Z. and K.Q.; Funding acquisition, X.Z. and K.Q.; Methodology, Y.Y. and J.Z.; Supervision, X.Z., B.L. and K.Q.; Visualization, Y.Y. and J.Z.; Writing--original draft, Y.Y. and J.Z.; Writing--review and editing, Y.Y., X.Z., B.L. and K.Q. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the Central Military Commission grant number 61403120404.  
Not applicable.  
The authors would like to thank the editor and the anonymous reviewers for their careful reading and valuable suggestions that helped to improve the quality of this manuscript.  
There are no conflicts of interest to report.
# The Influence of Track Irregularity in Front of the Turnout on the Dynamic Performance of Vehicles
## 4 Result Analysis
### Influence of Different Irregularities
#### 4.2.2 Time-Frequency Analysis
For the lateral acceleration of the vehicle body, the main frequency range affected by the irregularity is below 5 Hz, and the irregularity at 40 m wavelength affects the lateral acceleration in the whole range of the turnout area. The irregularity of longitudinal level  
The influence of the LL in front of the turnout on variations in the wheel-rail vertical force and vertical acceleration of the vehicle body are shown in Figure 14. The LL of the short wavelengths (3 m and 5 m) in front of the turnout has a significant effect on the wheel-rail vertical forces. When the vehicle passes through the LL of short wavelengths, the wheel-rail vertical force will greatly increase. Afterward, there is an instantaneous detachment and collision between wheel and rail, and the vertical force decrease to 0 kN. When the separated wheels and rails contact again, there will be a great impact force on the wheel and rail. The range of wheel-rail detachment increases as the wavelength decreases. Therefore, some wheel-rail detachments will continue into the turnout area, and it also causes the overrun of the wheel unloading rate. The vertical acceleration of the vehicle body presents a periodic simple harmonic variation, and the maximum value appears at a short wavelength of 3 m. Interestingly, comparing the changes in the waveform of the wheel-rail vertical force and vertical acceleration of the vehicle body, it is discovered that the peak value of the vertical acceleration of the vehicle body presents a certain delay, which is caused by the time difference between the wheel-rail dynamic interaction and vehicle vibration. In addition, the LL in front of the turnout has longer-lasting effects on the vertical accelerations of the vehicle body. The changes in the wheel-rail vertical force barely lasts 20 m away from the switch rail point, while the changes in the vertical acceleration of the vehicle body are throughout the turnout. Figure 13: Time-frequency graphs of dynamic indicators at the AL in front of the turnout: (**a**) Wheelset lateral force; (**b**) Lateral acceleration of the vehicle body. Figure 15 shows the time-frequency diagrams of the wheel-rail vertical force and vertical acceleration of the vehicle body under the LL in front of the turnout at wavelengths of 3 m and 40 m. The LL at the wavelength of 3 m in front of the turnout has a much greater effect on the wheel-rail vertical force and the vertical acceleration of the vehicle body than the irregularity at the wavelength of 40 m. Under the effect of the LL at the wavelength of 3 m, the wheel-rail vertical force presents a high-frequency response at the extremes, while the vertical acceleration of the vehicle body has a large response until 40 m away from the switch rail point, and the frequency effect is concentrated below 20 Hz.
## 5 Conclusions  
The results of this study led to the following conclusions.  
1. The _ilt_-RPCA-back CLR model has two issues. (1) The change in element position severely affects the relationship between geochemical elements. (2) The score and load transformation to clr space disrupts the corresponding relationship between the elements. Therefore, it is important to carefully consider the use of this model for the identification of geochemical element combinations.
2. The proposed method of singular value overlay analysis has clear advantages in identifying porphyry copper deposits. However, it is difficult to distinguish skarm-type copper related to porphyry from porphyry molybdenum. Additionally, the distinction between porphyry skarn-type copper deposits and porphyry gold deposits is not well defined. Nevertheless, this method can reduce the anomaly grade.  
Figure 6: Geochemical anomaly map of typical deposits in western Gangdese. (**a1–a8**) Singular anomalies of copper elements of Zhu nuo, Jianglaang-zong, Balazha, Ri a, She suo, Tuan jie, Sa ka, and Ri na; (**b1–b8**) Singular anomalies of association elements of Zhu nuo, Jianglaangzong, Balazha, Ri a, She suo, Tuan jie, Sa ka, and Ri na; porphyry Cu deposit: Zhu nuo, Jianglaangzong, and Balazha; skarn Cu deposit: Ri a and She suo; porphyry Mo deposit: Tuan jie; porphyry Au deposit: Sa ka and Ri na.  
3. This paper investigates the geochemical laws, geochemical markers, and geochemical models based on geological foundations. It provides objective geological connotations for the identification and evaluation of anomalies using geochemical data. By overcoming the limitations of traditional technical methods and single element analysis, which are influenced by elemental chemical properties, redox environment, weathering erosion, and other factors, these methods offer significant advantages in anomaly screening. They greatly reduce multiple solutions and subjectivity, highlighting the prospecting value of anomalous regularity.  
Writing--original draft, S.Z.; writing--review and editing, X.J. and S.G.; visualization, S.Z.; investigation, S.G.; methodology, X.J. and S.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (No. U22A20572).  
The authors declare no conflict of interest.
## 4 Simulation and Performance Analysis  
The results of the simulations performed assess how well the EGR technique performed in managing sparse vehicular networks in a highway traffic scenario for the high mobility of vehicles. Throughput, end-to-end delay, and one-hop link disconnections were evaluated in the simulation. The EGR algorithm's results are compared with the following contemporary routing approaches: SLD-GEDIR), J-GEDIR, and P-GEDIR [22].
# Effects of Atmospheric Turbulence on Optical Wireless Communication in NEOM Smart City
## 5 Channel Model and BER Analysis  
The probability density functions (PDFs) of log-normal (LN) and gamma-gamma (G-G) distributions are considered to model the turbulence [53; 54]. These two models are discussed in the following sections.
## 4 Experiments  
### Experimental Setup  
#### 4.1.1 Dataset Description and Preprocessing  
We conducted extensive experiments using the AI-Enhanced Cybersecurity Events Dataset [17], which contains 20,000 real-world security incidents. The dataset includes diverse cyber threats with the following key attributes: timestamp, source IP, destination IP, user agent, and attack type. We performed a 70-15-15 split for training, validation, and testing, ensuring temporal consistency by maintaining chronological order. To account for class imbalance, we employ stratified sampling based on attack types.  
The dataset comprises several attack categories: DDoS (28.3%), Malware (23.7%), Phishing (19.5%), Insider Threats (15.2%), and Ransomware (13.3%). The temporal distribution spans from January 2020 to January 2024, providing a comprehensive coverage of evolving attack patterns. Table 1 summarizes the key statistics of our dataset.  
The raw dataset underwent several essential preprocessing steps to ensure data quality and consistency. For the missing values treatment, we interpolated missing timestamps using adjacent event timestamps, which accounted for 0.3% of entries. Missing source and destination IP addresses (1.2%) were labeled as 'unknown', while events with missing attack types (0.8%) were classified based on other available features using a rule-based approach. In terms of outlier processing, we identified and handled response time anomalies exceeding three standard deviations from the mean. These outliers were either corrected through cross-validation with system logs or removed if verified as recording errors. Extreme values in system impact metrics were capped at the 99 th percentile to maintain data distribution integrity while preserving genuine peak events. For data normalization, all of the numerical features were standardized using z-score normalization to ensure a consistent scale across different metrics. Categorical features were appropriately encoded, and temporal features were converted to UNIX timestamps for uniformity. After preprocessing, the final dataset retained 98.5% of the original entries, with removed data verified as invalid or as duplicate records.