esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results
### Re Partitioning and Chamber-Based Validation  
We used Re and its components derived from satellite-based VPMM, MODM and ECM to simulate the ratios of Ra and Re (\(1-\beta\)*\(\gamma\)) (satellite-based Ra/Re), respectively. Meanwhile, chamber-based Re, Rs and Rm measurements directly showed Rm/Rs (\(\beta\)) and Rs/Re (\(\gamma\)), which can also be used to calculate Ra/Re (\(1-\beta\)*\(\gamma\)) (chamber-based Ra/Re) from 2010 to 2011 (Figure 7). Both satellite-based Ra/Re and chamber-based Ra/Re were not constant throughout the GS. Specifically, all three satellite-based Ra/Re ranged from 0.21 to 0.76 with an average value of 0.50 (\(\pm\)0.14, SD, \(n=126\)) from 2010 to 2011. Chamber-based Re measurements showed that both Rm/Rs and Rs/Re ranged from 0.40 to 0.80 with two exceptions of Rm/Rs that were around 0.20 (dots in circle in Figure 7a). Thus, chamber-based Ra/Re ranged from 0.39 to 0.87, including two values of 0.82 and 0.87 that derived from two abnormal measurements of Rm/Rs (red dots in Figure 6b). Excluding these two abnormal measurements, which will be further discussed later, chamber-based Ra/Re could be well explained (slope \(\approx\) 1.0 from 0.98 to 1.03, \(R^{2}=0.99\), \(p<\) 0.0001) by all three satellite-based Ra/Re (Figure 7b). In addition, all three satellite-based Ra/Re failed to pose significant differences with chamber-based Ra/Re (paired \(t\)-test, \(\alpha=0.05\), \(p>0.1\)). Therefore, any of Ra/Re from satellite-based models calibrated by corresponding linear relationships with chamber-based Ra/Re can be used to separate the EC-based Re estimations into autotrophic (Ra_EC) and heterotrophic components (Rm_EC).  
In this study, we selected MODM because it was the most convenient method whose data inputs, GPP_MOD and LST, can be directly extracted from MODIS products. In the growing season, the average Ra_EC/Re_EC ratios were 0.27 (0.10-0.48, seasonal variation), 0.43 (0.22-0.59) and 0.56 (0.30-0.76) from 2009 to 2011, respectively.  
Figure 7: Chamber-based estimations for the ratios of ecosystem respiration (Re) components from 2010 to 2011 (**a**); and comparison with the corresponding ratios based on the satellite-based Re partitions (**b**). Rm, Rs and Ra are heterotrophic respiration, autotrophic respiration and soil respiration, respectively. Error bars in (**a**) are standard deviations of the mean values from sample plots (\(n=4\) for \(\beta\) and 7 for \(\gamma\)). Dots in red circles in (**a**,**b**) are the abnormal measurements due to the high moisture condition. \(k\) values and dashed line in (**b**) are the linear slope between modeled Ra/Re and chamber-based Ra/Re, and the reference line of 1:1, respectively. All linear regressions are extremely significant (\(p<\) 0.0001). Different Re estimations based on the diverse GPP estimation models are identical to the Figure 1.
# A Heuristic Algorithm for Locating Line-to-Line Faults in Photovoltaic Systems
###### Abstract  
Photovoltaic (PV) systems have experienced rapid global deployment. However, line-to-line short-circuit faults pose serious safety risks and can lead to significant power losses or fire hazards. While existing fault detection methods can identify fault types, they cannot precisely locate fault positions, resulting in time-consuming and costly maintenance. This paper proposes a heuristic algorithm for accurately locating such faults in PV arrays based on module group voltage measurements. The algorithm employs a two-phase approach: fault candidate marking and fault location determination, capable of handling both intra-string and cross-string faults. Simulation tests on a 21 \(\times\) 2 PV array configuration demonstrate a 97.56% fault location success rate, reducing the troubleshooting scope to within a single-module group. The proposed method offers a simple, fast, and cost-effective solution for PV system maintenance, potentially saving significant labor costs and reducing system downtime.  
fault location; photovoltaic systems; line-to-line fault; heuristic algorithms Article
## 3 Lateral Control Strategy  
IMU, GNSS and camera-based systems are commonly used to estimate the vehicle's states accurately. These systems provide various information, such as velocity, acceleration, sideslip angle and attitude, which are critical inputs for lateral control strategy prediction modeling. This article is based on the following references.  
Reference [32] proposed a method for using IMU and GNSS data to evaluate the skid angle and posture of a car. The related work [33] proposed a method to evaluate the car's sideslip angle, considering the characteristics of the measurement signals. The method uses a combination of multiple sensors, including IMU and GNSS, and a neural network.  
The lateral motion control of the unmanned fully line-controlled distributed drive electric vehicle includes lateral displacement control and front wheel angle control. According to its own sensing sensors, it collects information about the difference between its own status and the status of the reference path at the moment. It communicates the wheel turning angle to the steering system using MPC control algorithms to follow the intended path. The lateral control tactics are displayed in Figure 8.  
As displayed in Figure 8, the fore and after tires turning angles of the wheels are solved according to MPC theory for prediction and optimization on the basis of an accurate model. The wheel angles calculated by the two controllers are fed to the vehicle's linear actuators to assure the vehicle follows the required trail precisely and stably. A joint simulation model is set up in the MATLAB/Simulink and CarSim 2019 software. Typical operating conditions are set up, and the simulation is validated on a high velocity and high adhesion coefficient and medium velocity and low adhesion coefficient road surface.
## 2 Results
### Principal Component Analysis
#### 2.2.1 DVB/CAR/PDMS Fiber  
The biplot constructed by the first two principal components that are showing the distribution of investigated _S. romana_ and _S. montana_ populations and VOCs identified with DVB/CAR/PDMS fiber is presented in Figure 3. Principal component 1 (PC1) accounted for 49.37% and principal component 2 (PC2) for 30.62% of total variance in the data. Clear separation between _S. romana_ and _S. montana_ was obtained. For all populations of _S. romana_, except for _S. romana_ M, distinctive components for discrimination observed by using DVB/CAR/PDMS fiber were bicyclogermacrene (C29), alloarmodendrene (C21), _trans_-\(\beta\)-farnesene (C23), isocaryophyllene (C24), selina-5,11-diene (C22), \(\alpha\)-gurjunene (C17) and spathulenol (C36), while _S. romana_ M, was characterized by benzyl alcohol (C11), viridiflorol (C37), ledene (C28), \(p\)-cymene (C9), acetic acid (C1), benzaldehyde (C4) and \(\beta\)-myrcene (C6). Distinctive components for discrimination of _S. montana_ populations were germacrene D (C26), \(\delta\)-cadinene (C32), \(\gamma\)-cadinene (C31), \(\alpha\)-amorphene (C25), \(\alpha\)-muurolene (C30), \(\alpha\)-copaene (C16), \(\alpha\)-cadinene (C34), cadina-1,4-diene (C33) and \(\alpha\)-calacorene (C35).  
Figure 3: Biplot obtained by principal component analysis of VOCs composition of investigated populations of _S. romana_ and _S. montana_, based on major components with average percentages \(\geq\) 1% in at least one of the samples, detected with DVB/CAR/PDMS fiber.
## 3 Results and Discussions  
### Ablation Threshold of CNT Film  
The ablation of the laser caused damage to the CNTs due to the interaction between the femtosecond laser and the CNT film. The ablation threshold is the minimum energy required to remove a single layer of material with irreversibly destroyed, and it is an essential parameter for CNT film. CNT film is composed of a large number of CNTs with different diameters and lengths. With an increase of laser pulse energy, different sizes of micro holes are produced on the surface of CNT film. The diameter can be directly measured, so a \(D^{2}\) method based on the energy conservation for measuring the threshold of material was used.  
According to the Gaussian beam profile and the theoretical threshold behavior of the material, the relationship between the diameter of the modified area and the laser pulse energy can be expressed as [24]:  
\[\mathrm{D}^{2}=2\omega_{0}^{2}\ln(\varphi_{0}/\varphi_{\mathrm{th}}), \tag{1}\]  
where \(D\) represents the diameter of the modified area (\(\upmu\)m), \(\omega_{0}\) is the waist radius of laser beam (\(\upmu\)m), \(\phi_{\mathrm{th}}\) is the threshold fluence of the material (J/cm\({}^{2}\)), and \(\phi_{0}\) is the energy density of the beam at the focal plane (J/cm\({}^{2}\)).  
After applying the value of laser pulse energy \(E\) into the equation,  
\[\mathrm{D}^{2}=2\omega_{0}^{2}\ln(2\mathrm{E}/\pi\omega_{0}^{2}\varphi_{ \mathrm{th}}) \tag{2}\]  
After rearranging the equation by plotting \(\mathrm{D}^{2}\) versus lnE on the scale, a linear relationship can be obtained,  
\[\mathrm{D}^{2}=2\omega_{0}^{2}\ln 2+2\omega_{0}^{2}\ln\mathrm{E}-2\omega_{0}^{2 }\ln\pi\omega_{0}^{2}\varphi_{\mathrm{th}} \tag{3}\]  
By fitting Equation (3) to the experimental data, the beam waist radius \(\omega_{0}\) can be obtained by the slope of the fitting line, and \(\phi_{\mathrm{th}}\) is given by the interception of the regression curve. The x-coordinate and the laser energy density can be converted through \(\varphi_{0}=2\mathrm{E}/\pi\omega_{0}^{2}\).  
After experiments, the diameter of the holes can be measured by SEM. The SEM image of the ablated areas on the CNT film for different pulse energies and the fitting relationship between the logarithm of the incident laser energy and the square of the ablation diameter are shown in Figure 2. A beam waist radius of 5.99 \(\upmu\)m and ablation threshold of 25 mJ/cm\({}^{2}\) were obtained by linear regression.  
Figure 2: (**a**) SEM image of carbon nanotube (CNT) film ablated by different laser pulse energies and number of pulses and (**b**) plot of the diameter square of the produced craters changing with the logarithm of pulse energy.
## 2 Preliminaries
### Paillier Encryption  
The Paillier encryption algorithm [32] is a public key encryption algorithm based on the composite residual difficulty problem, which satisfies the additive homomorphic operation. It contains the following steps:  
1. Key _generation_: 1. Obtain two large prime numbers \(p_{1}\) and \(p_{2}\) that satisfy \(gcd(p_{1}p_{2},\)\((p_{1}-1)(p_{2}-1))=1\). This ensures that the prime numbers \(p_{1}\) and \(p_{2}\) have equal lengths. 2. The following values are computed: \(n=p_{1}p_{2}\), \(\lambda=lcm((p_{1}-1),(p_{2}-1)))\). 3. Define \(\mathbb{L}(x)=(x-1)/n\). 4. Randomly select a positive integer \(g\) less than \(n^{2}\), and there exists \(\mu=(\mathbb{L}(g^{\lambda}\mod n^{2}))^{-1}\ mod\ n\). 5. System public key \(pk=(n,g)\), and system secret key \(sk=(\lambda,\mu)\).
2. Encryption: Given the plaintext \(\mathbb{M}\), randomly select \(\gamma\in\mathbb{Z}_{n^{2}}^{*}\) and calculate \(\mathbb{C}=g^{\mathbb{M}}\gamma^{n}\ mod\ n^{2}\). 3. Decryption: \(\mathbb{M}=\mathbb{L}(\mathbb{C}^{\lambda}\ mod\ n^{2})\times\mu\ mod\ n\).
## 6 Nanopharmaceutics
### Enhanced Skin Penetration of Cannabidiol Using Nano-Lipidic Particles  
[PERSON], [PERSON] and [PERSON]  
Dermazone Solutions Inc., Saint Petersburg, FL 33713, USA  
The utilization of lipid nanoparticles for improved skin uptake in topical formulations has gained interest for the treatment of skin conditions. Cannabidiol (CBD), the non-psychoactive phytocannabinoid found in Cannabis plants, has emerged as a potential therapeutic agent for numerous skin conditions, e.g., inflammation, pain, itch, etc. [1]. However, given its highly lipophilic nature, it is necessary to evaluate encapsulation technologies for a more efficient delivery through the skin layers [2]. This study intends to encapsulate CBD using a proprietary and patented nano-lipidic particle (NLP) technology and demonstrate that the encapsulation results in increased penetration of CBD into the skin. Particle sizes of the NLP with CBD were evaluated using dynamic light scattering (DLS). The average particle size was about 200 nm. Skin penetration of a 2% (w/w) CBD lotion with and without NLP was evaluated and visualized by confocal Raman Spectroscopy using an ex-vivo human skin model (frozen excised human skin). It was found that the NLP delivery system significantly improved the skin penetration of CBD, reaching a depth up to 25 \(\upmu\)m after 20 h, whereas in the skin treated with CBD lotion without the NLP, CBD only remained at the surface. According to these findings, encapsulated CBD can penetrate through the stratum corneum and even reach the epidermis. This greater penetration of CBD appeared to be independent of skin donor.
# An Intelligent Approach for Contact Pressure Optimization of PEM Fuel Cell Gas Diffusion Layers
## 5 Conclusions  
This work presents an intelligence-based approach of clamping optimization for proper contact pressure on the GDL of a PEMFC. Opt LHD, RBFNN, and GA are employed to conduct the proposed intelligent workflow on the basis of a validated full-size physical model of the fuel cell. Conclusions can be drawn as follows:  
The data-driven RBFNN-based agent model is capable of representing the inner physical phenomenon of a fuel cell, i.e., the contact pressure between BP and the GDL under various clamping conditions. It provides a possibility of getting higher computational efficiency in the mechanical prediction of fuel cells.  
A uniform distribution of the contact pressure on the GDL with a properly designed equivalent value can be obtained through adjusting the clamping manner, even for a traditional bolt packing case.  
The RBFNN-GA-based optimization framework is available for multi-objective optimization of the complex structure with much lower computing cost, which has great potential for clamping designs for fuel cell stacks.  
Conceptualization, Y.Q., K.J., and J.L. ([PERSON]); data curation, Y.Q. and P.W.; methodology, Y.Q.; project administration, J.L. ([PERSON]) and T.L.; resources, J.L. ([PERSON]) and J.Z.; supervision, [PERSON] ([PERSON]); validation, T.M. and J.L. ([PERSON]); writing--original draft, Y.Q.; writing--review and editing, [PERSON] ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
The authors gratefully acknowledge the National Key R&D Program of China (Fuel Cell Engine Integration and Control for Heavy Duty Trucks--Vehicle Integration of Fuel Cell Heavy Duty Trucks) and the Natural Science Foundation of Tianjin (China) (18 JCYBJC20000).  
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.  
Figure 14: Comparison of contact pressure distributions of (**a**) original and (**b**) optimized designs.
# Performance Comparison of Selected Filters in Fast Denoising of Oil Palm Hyperspectral Data
## 4 Conclusions  
In this study, Kalman, Wiener, Savitzky-Golay, wavelet, and cosine filters were utilized in fast denoising of oil palm hyperspectral data. Their performances were tested and compared in terms of execution time, SNR gained, and visual quality. All filters managed to improve the SNR of the noisy channels, but the [PERSON] filter slightly outperformed the  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Metric**Bands** & **1** & **2** & **3** & **4** & **297** & **298** & **299** & **300** \\ \hline Raw & 24.0 & 22.86 & 22.91 & 20.36 & 20.4 & 19.7 & 19.7 & 20.1 \\ \hline Kalman & 10.5 & 10.6 & 10.4 & 10.7 & 9.4 & 9.6 & 9.8 & 10.0 \\ \hline Wiener & 10.2 & 10.3 & 10.2 & 9.8 & 9.3 & 9.1 & 9.2 & 9.9 \\ \hline SGolay & 10.2 & 10.2 & 10.2 & 9.9 & 9.1 & 9.1 & 9.2 & 9.6 \\ \hline Wavelet & 10.5 & 10.4 & 10.5 & 10.4 & 9.2 & 9.3 & 9.2 & 9.8 \\ \hline Cosine & 10.0 & 10.1 & 10.1 & 10.0 & 9.3 & 9.4 & 9.7 & 9.9 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The NIQE metrics of the first 4 and the last 4 channels before (raw) and after Kalman, Wiener, Savitzky–Golay, wavelet, and cosine filtering, row-wise from top to bottom.  
others. To the best of our knowledge, this is the first attempt to filter speckle noise from real oil palm hyperspectral data using the Kalman filter. The proposed method was run on a MATLAB R2023b platform powered by an Intel i7 processor. The average time taken by most filters to process each channel was less than 1 s. Once the noise is removed, the field and airborne hyperspectral data should exhibit a stronger correlation. This is important for ground truth verification and further analysis.  
This research received no external funding.  
The data are not publicly available due to a non disclose agreement with the data provider.  
The authors declare no conflict of interest.
# Reservation-Based 3D Intersection Traffic Control System for Autonomous Unmanned Aerial Vehicles
## 6 Scheduling Scheme
### Tasks of the Intersection Manager  
In summary, the tasks of the intersection manager at every scheduling epoch are to schedule the UAVs, to send the responses to the UAVs, and to update the times of the saved reservations for the next scheduling epoch. A response to a UAV includes its scheduled time to enter the intersection and the path in the intersection that it must follow.  
The scheduling scheme implements a genetic algorithm to find the best scheduling sequence. After choosing the best sequence, the intersection manager finalizes the reservations for the best sequence by saving the reservations to the respective cubes' red-black trees. Then, the intersection manager sends responses to the UAVs. The stored reservation times are relative to the current scheduling epoch, thus to prepare for the next scheduling epoch, we update the stored reservation times by decreasing their values by \(k\Delta t\). Also, a UAV's reservation to a cube will be deleted if the reserved departure time of the UAV is less than or equal to zero, which means the UAV has already passed through that cube. The summary of the scheduling done at every \(k\Delta t\) is shown in Figure 8.
# Highly Compact Through-Wire Microstrip to Empty Substrate Integrated Coaxial Line Transition
###### Abstract  
Empty substrate integrated coaxial line (ESICL) technology preserves the many advantages of the substrate integrated technology waveguides, such as low cost, low profile, or integration in a printed circuit board (PCB); in addition, ESICL is non-dispersive and has low radiation. To date, only two transitions have been proposed in the literature that connect the ESICL to classical planar lines such as grounded coplanar and microstrip. In both transitions, the feeding planar lines and the ESICL are built in the same substrate layer and they are based on transformed structures in the planar line, which must be in the central layer of the ESICL. These transitions also combine a lot of metallized and non-metallized parts, which increases the complexity of the manufacturing process. In this work, a new through-wire microstrip-to-ESICL transition is proposed. The feeding lines and the ESICL are implemented in different layers, so that the height of the ESICL can be independently chosen. In addition, it is a highly compact transition that does not require a transformer and can be freely rotated in its plane. This simplicity provides a high degree of versatility in the design phase, where there are only four variables that control the performance of the transition.  
through-wire transition; empty substrate integrated coaxial line (ESICL); empty substrate integrated waveguide (ESIV); substrate integrated waveguide (SIW); microwave subsystems; millimeter-wave subsystems; coaxial conductors +
Footnote †: journal: Applied Sciences
## 5 Overview of Machine Learning Methods
### Machine Learning Classifiers
#### 5.1.1 K-Nearest Neighbor Classifiers  
K-Nearest Neighbor (KNN) is a non-parametric supervised learning algorithm. As depicted in Figure 21, the classification of an individual or new data point is determined by the proximity to a specified number of neighbors. Common distance functions used in KNN include Euclidean distance or negative cosine similarity.  
Figure 20: Comparison of signal distribution before and after Linear Discriminant Analysis (LDA) for 2 classes.
# A Field Investigation on Vortex-Induced Vibrations of Stay Cables in a Cable-Stayed Bridge
## 2 Full-Scale Health-Monitoring System  
The present study on the VIVs of stay cables was performed based on the field data obtained through a long-term full-scale measurement system on a cable-stayed bridge, which is located in the East China Sea, as shown in Figure 1. With a main-span of 620 m, the investigated bridge is a single steel-box-girder-section cable-stayed bridge. The deck has a 30.1 m width and a 3.0 m height, and it is supported by a total of 168 stay cables that are arranged in two inclined planes.  
The full-scale measurement system on the cable-stayed bridge was installed and began to collect data when the bridge was finished in December 2009. The measurement data included the vibration response of stayed cables and the ambient wind conditions. Twenty stay cables were selected and were named CAC1 to CAC20, as shown in Figure 2. At the same location, CAC1/CAC2 means that one cable is the upstream cable in the upstream cable plane and that the other cable is the downstream cable in the upstream cable plane. Only in-plane vibration responses of the selected cables were measured by single axial accelerometers (hrbcaomu, model GTR1) installed at a cable location with an elevation of 6 m above the bridge-deck's surface. The accelerometer measurement range is \(\pm\)5 g, with a high accuracy of 1%, a sensitivity of 1000 mV/g, a frequency band of 0 to 400 Hz, and a sampling frequency of 100 Hz. Two three-dimensional ultrasonic anemometers (DELTA OHM HD2003) were installed on the upstream and downstream lighting columns at the mid-span section of the deck, and each anemometer is located at 6.0 m above the deck's surface. This type of anemometer has good resolution (wind speed: 0.01 m/s, wind direction: 0.1\({}^{\circ}\)) and high accuracy (wind speed: \(\pm\)1%, wind direction: \(\pm\)1\({}^{\circ}\)). The anemometer has a threshold of 0.1 m/s and can record the wind speeds up to 60 m/s. At the top of the east or west tower, the speed and direction of wind were measured and recorded by a propeller-vane anemometer (Young Instruments Model 05103) installed on a steel guardrail that extended 2.1 m above the tower top. The propeller-vane anemometer can cover the wind speed range of 0 to 80 m/s. The resolution of wind speed measurement is 0.3 m/s, while the direction measurement is \(\pm\)3\({}^{\circ}\). The sampling frequencies of the anemometers were set as 32 Hz. A damper was installed on each cable to mitigate the vibration amplitude, and spiral wires were also implemented to prevent the rain-wind-induced cable vibrations.  
Figure 1: Location of the investigated bridge.  
Figure 2: _Cont._
# Predictive Maintenance for Remanufacturing Based on Hybrid-Driven Remaining Useful Life Prediction
## 2 Proposed Methodology
### Prognostic Approach: Hybrid-Driven Remaining Useful Life Prediction  
The prognostic module is designed to estimate the future state based on current state and historical data. This is calculated through predicting the remaining useful lifetime using both the knowledge-based degradation model and the data-driven optimization approach. Such a hybrid-driven approach enables predicting the RUL without the need for a large amount of data.