esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Fundamentals of Frequency-Selective Surfaces
### Telecommunication Services Frequencies: Basic Design Constraints
As the frequency decreases, the size of the unit cell increases, making techniques for reducing unit cell size particularly important for low-frequency applications. As demonstrated in the literature, meandered designs are often employed for this purpose, as they reduce the area of the unit cell while maintaining effective performance at longer wavelengths.
# A Hierarchical Multi-Label Classification Algorithm for Gene Function Prediction
## The Proposed Algorithm  
### Notation and Basic Definitions  
Let \(X\) be a set of \(n\) gene instances, \(x_{i}\) be any gene instance with \(m\) attributes written as \(x_{i}=(a_{1},a_{2},...,a_{m})\), where \(x_{i}\in X\) (\(1\leq i\leq n\)). Let \(C\) be a set of all the GO classes, \(C=\{c_{1},c_{2},...,c_{|C|}\}\). The GO hierarchy is a DAG denoted by \(G=<V,E>\). \(V=\{1,2,...,|V|\}\) is the set of vertices and the edges set is \(E\), where \(e=(k,l)\in E,k,l\in V\) means an edge. Each node in \(V\) represents a class, so \(V=C\) and the class \(c_{k}\) is represented simply by the node \(k\) if there is no ambiguity. Each node represents one gene function, and a direct edge \(e=(k,l)\in E\) describes the hierarchical relationship that \(k\) is the parent node of \(l\). We further denote the set of children nodes of a node \(k\) as \(child(k)\), the set of its parent nodes as \(par(k)\), the set of its ancestor nodes as \(anc(k)\), the set of its descendant nodes as \(desc(k)\) and the set of its siblings as \(sib(k)\).  
Given an instance \(x_{i}\in X\), if \(x_{i}\) has the function the node \(k\) presents, the real label at the node \(k\) is \(1\), and this is also called that this instance \(x_{i}\) belongs to the node \(k\). If there is no ambiguity, it is said that its node \(k\) is \(1\) for short. The result of a binary classifier \(f_{k}\) for the class \(c_{k}\) is denoted as \(d^{*}_{ik}\), where \(1\leq k\leq|C|\), and it is used to predict the label of \(x_{i}\) at node \(k\). \(d^{*}_{ik}\) represents the probability of the instance \(x_{i}\) belonging to the node \(k\) given by this classifier \(f_{k}\), which is also written as \(P^{*}_{i}(k=1)\).  
The set of \(|C|\) binary classifiers provides a multi-label score \(d^{*}_{i}=(d^{*}_{i1},d^{*}_{i2},...,d^{*}_{i|C|})\), which is called the preliminary results. The preliminary predicted label for an instance \(x_{i}\in X\) with all the classes is denoted as a vector \(y^{*}_{i}=(y^{*}_{i1},y^{*}_{i2},...,y^{*}_{i|C|})\) for \(1\leq k\leq|C|\). It is obtained by selecting a threshold \(\theta\) for \(d^{*}_{i}\). If \(d^{*}_{ik}\geq\theta\), set \(y^{*}_{ik}=1\), the representing \(x_{i}\) belongs to class \(c_{k}\); otherwise, set \(y^{*}_{ik}=0\) for \(1\leq k\leq|C|\). We say that this result for an instance \(x_{i}\) is consistent with the hierarchy constraint if and only if \(d^{*}_{ik}\geq d^{*}_{il}\), where \(k\) is the parent class of \(l\). The final predicted score at the node \(k\) is written as \(d_{ik}\), which is the posterior probability \(P_{i}(k=1)\). If we get the consistent preliminary result, then \(d_{i}=d^{*}_{i}\); otherwise, we need to use other methods to get the final consistent score \(d_{i}\). Similarly, the final prediction vector \(y_{i}=(y_{i1},y_{i2},...,y_{i|C|})\) can be obtained by selecting a threshold \(\theta\) for \(d_{i}\).
# A Framework for Constructing a Secure Domain of Sensor Nodes
## 5 Results and Discussion
### Analysis of Wireless Bandwidth Consumption  
When designing solutions for the IoT, the small resources of IoT nodes are a challenge. In particular, the problem relates to the limited energy resources of the power sources that can be used. The analysis of the efficiency of energy consumption and its saving is complicated and very dependent on the specific conditions of the operation of the IoT network nodes. Undoubtedly, elements such as the type of wireless interface used, the expected reach of a single node and the entire network, the method of data exchange between nodes, the volume of data necessary for transmission between nodes, among others, have significant influences on energy consumption. The framework of this study did not allow for a detailed analysis of the problems related to energy consumption. To illustrate the expected costs when using the proposed solution to protect the functioning of the domain of the sensor nodes, the following sections present an analysis of the bandwidth consumption for the most critical procedures of the phase of creating a secure domain of sensor nodes.
# Reinforcement Learning for Semi-Active Vertical Dynamics Control with Real-World Tests
## 4 Training the Controller
### The Reinforcement Learning Setting  
The basic setting of RL is depicted in Figure 7. An RL agent learns a desired behavior out of interaction with an environment. The agent can manipulate the environment by applying an action \(a\) and, in return, obtains an observation vector \(o\) and a scalar reward \(r\). The goal of RL algorithms is to adapt a policy \(\pi\) such that the expected discounted return is maximized.  
As opposed to the standard setting in control theory, in the basic RL setting, the agent does not need any prior knowledge about the environment and a deterministic behavior of the environment is not required. The non-deterministic approach of RL makes these algorithms especially appealing for vertical dynamics control, where the road excitation is assumed to be stochastic.  
Since the RL algorithm adapts the policy solely through interaction and no additional information about the environment is necessary, such algorithms are very generic and can solve a wide range of sequential decision-making problems. However, the theory on RL assumes that the environment behaves as a Markov Decision Process (MDP) [27]. Even though the time delay in the input-to-force dynamics described in Section 3.2 violates this assumption, the algorithms applied in this work are robust enough to train a performant policy.  
In deep RL, artificial neural networks are used to approximate several functions, e.g., the so-called _action-value function_, _state-value function_, and the policy. In the last decade, several powerful deep RL algorithms were proposed, such as the deep Q-network (DQN) [28], proximal policy optimization (PPO) [29], deep deterministic policy gradient (DDPG) [30], and soft actor-critic (SAC) [31]. Over the years, different well-maintained open source implementations of these algorithms have been created and benchmarked. The most widely used libraries include the RLLib [32] and stable-baselines3 [33].
## 6 Conclusions  
This paper proposes a network routing protocol, AODV-EM, which optimizes node energy consumption and mobility to address the need for real-time, accurate transmission of position and status information in unmanned cluster cooperative positioning networks, particularly under conditions of high mobility and heavy load. The NS-3 simulation platform is used to compare AODV-EM protocol with the traditional AODV, OLSR, and DSDV protocols in terms of packet delivery rate, network throughput, average end-to-end delay, average jitter, and standard deviation of node residual energy. The experimental results show that the AODV-EM protocol has better performance for unmanned cluster networks under conditions of dense node distribution and high node mobility, which not only improves the efficiency of data transmission, but also ensures the reliability and stability of data transmission. However, when several key nodes in the unmanned cluster network fail, the network link will be broken, and the network performance cannot be fundamentally improved by optimizing the routing protocol alone. Therefore, future research will focus on the design and implementation of network topology reconstruction algorithms. These algorithms will be combined with routing protocols after node failure to dynamically adjust network topology, restore connections and optimize data transmission paths, so as to effectively mitigate the negative impact of node failure on network performance.
# Non-Contact High Voltage Measurement in the Online Partial Discharge Monitoring System
## 1 Introduction
This article describes the assumptions of the non-contact high voltage measurement method using a capacitive probe and the construction of a measuring module specially designed for a portable PD monitoring system. The diagnostic reliability of the system has been increased thanks to the possibility of correlating the number of recorded pulses by PD detectors with the voltage value on the monitored transformer. Additionally, when using  
Figure 2: Daily distribution of average voltage values and average AE pulse rate obtained from 30 days of monitoring of a 330 MVA power transformer. electromagnetic PD sensors (UHF antennas or high-frequency current transformers (HFCT) sensors), it is possible to create phase-resolved partial discharge (PRPD) patterns that can be used to recognize the type of defect or identify the sources of interference. Equipping the portable PD monitoring system with a voltage measurement module based on a capacitive probe allows it to be fully independent of the substation systems and devices, and at the same time, ensures a high flexibility and ease of installation on the transformer. It is worth noting that the proposed solution is the first of its kind in the world.
## 2 Antenna Design Stages  
The proposed dual-band microstrip antenna was developed systematically to ensure optimal performance at 28 GHz and 38 GHz for mmWave applications. The design methodology integrates precise dielectric material selection, rigorous analytical modeling, and parametric optimization, all of which are critical for achieving high gain, low return loss, and enhanced radiation efficiency in next-generation communication systems.
## 3 Results and Discussion
### Extractions Experiments and Chemical Equilibrium Calcualitons
The former presents a composition consistent with the LiCoO\({}_{2}\) (s) stoichiometry, while the latter presents no Li at the surface of the particles, indicating only the presence of cobalt oxides. These results are consistent with a dissolution mechanism that would take place with the existence of an external passive layer. \begin{table}
\begin{tabular}{l c c} \hline \hline \multicolumn{1}{c}{\(E_{0}\) **(V)**} & \multicolumn{1}{c}{**log\(K_{eq}\) (–)**} & **Equation** \\ \hline \multicolumn{3}{l}{**Heterogeneous reactions**} \\ \hline LiCoO\({}_{2}+4H^{+}+e^{-}\rightleftarrows\pm\) Li\({}^{+}+\) Co\({}^{2+}+2\)H\({}_{2}\)O & 52.307 & (1) \\ Li\({}_{2}\)O + 2H\({}^{+}\rightleftarrows\pm\) Li\({}^{+}+\) H\({}_{2}\)O & 35.293 & (2) \\ CoO + 2H\({}^{+}\rightleftarrows\) Co\({}^{2+}+\) H\({}_{2}\)O & 5.265 & (3) \\ CoO\({}_{2}\)O\({}_{3}+6H^{+}+2e^{-}\rightleftarrows\pm\) 2 Co\({}^{2+}+3\)H\({}_{2}\)O & 46.378 & (4) \\ Co\({}_{3}\)O\({}_{4}+8H^{+}+2e^{-}\rightleftarrows\pm\) 3 Co\({}^{2+}+4\)H\({}_{2}\)O & 30.724 & (5) \\ Co(OH)\({}_{2}+2H^{+}\rightleftarrows\pm\) Co\({}^{2+}+2\)H\({}_{2}\)O & 12.2 & (6) \\ \hline \multicolumn{3}{l}{**Redox half reactions**} \\ \hline Co\({}^{3+}+e^{-}\rightleftarrows\) Co\({}^{2+}\) & 1.920 & (7) \\ Co\({}^{2+}+2e^{-}\rightleftarrows\) Co\({}^{0}\) & \(-\)0.28 & (8) \\ Cl\({}_{2}(aq)+2e^{-}\rightleftarrows\) 2 Cl\({}^{-}\) & 1.358 & (9) \\ HClO + H\({}^{+}+2e^{-}\rightleftarrows\) CL\({}^{-}+\) H\({}_{2}\)O & 1.482 & (10) \\ O\({}_{2}(aq)+4H^{+}+4e^{-}\rightleftarrows\pm\) 2H\({}_{2}\)O & 1.229 & (11) \\ O\({}_{2}(aq)+2H^{+}+2e^{-}\rightleftarrows\) H\({}_{2}\)O\({}_{2}\) & 0.695 & (12) \\ \hline \multicolumn{3}{l}{**Homogeneous aqueous-phase reactions**} \\ \hline ClO\({}^{-}+2H^{+}+\) CL\({}^{-}\rightleftarrows\) Cl\({}_{2}(aq)+\) H\({}_{2}\)O & 10.6 & (13) \\ LiCl(\(aq)) \(\rightleftarrows\) Li\({}^{+}+\) CL\({}^{-}\) & 1.512 & (14) \\ HCl(\(aq)) \(\rightleftarrows\) H\({}^{+}+\) CL\({}^{-}\) & 0.710 & (15) \\ CoCl\({}^{+}\rightleftarrows\) Co\({}^{2+}+\) CL\({}^{-}\) & \(-\)0.570 & (16) \\ CoCl\({}_{2}(aq)\rightleftarrows\) Co\({}^{2+}+2\)CL\({}^{-}\) & \(-\)0.020 & (17) \\ CoCl\({}_{3}^{+}\rightleftarrows\) Co\({}^{2+}+3\)CL\({}^{-}\) & 1.710 & (18) \\ CoCl\({}_{4}^{+}\rightleftarrows\) Co\({}^{2+}+4\)CL\({}^{-}\) & 2.090 & (19) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Chemical system. Figure 3: XPS results for the solid sample before and after extraction. (**a**) Co 2p core level spectra; (**b**) Co 3p core level spectra; (**c**) Li 1s and O 1s core level spectra. The solid line: Initial LiCoO\({}_{2}\) particles. The dashed line: Solid particles after extraction.
# A Fast Point Clouds Registration Algorithm for Laser Scanners
###### Abstract  
Point clouds registration is an important step for laser scanner data processing, and there have been numerous methods. However, the existing methods often suffer from low accuracy and low speed when registering large point clouds. To meet this challenge, an improved iterative closest point (ICP) algorithm combining random sample consensus (RANSAC) algorithm, intrinsic shape signatures (ISS), and 3D shape context (3 DSC) is proposed. The proposed method firstly uses voxel grid filter for down-sampling. Next, the feature points are extracted by the ISS algorithm and described by the 3 DSC. Afterwards, the ISS-3 DSC features are used for rough registration with the RANSAC algorithm. Finally, the ICP algorithm is used for accurate registration. The experimental results show that the proposed algorithm has faster registration speed than the compared algorithms, while maintaining high registration accuracy.  
point clouds registration; iterative closest point (ICP); intrinsic shape signatures (ISS); 3D shape context (3 DSC); random sample consensus (RANSAC); effective root mean square error (ERMSE) +
Footnote †: journal: Applied Sciences
# Distortion of Thomson Parabolic-Like Proton Patterns Due to Electromagnetic Interference
## 4 Correlation between Measured EMP and Captured Parabolic Track of Protons  
In order to compare the extracted curve (blue) with the modulated one (red) in the time domain, we plotted both the extracted and the modulated parabolas as a function of TOF, as Figure 6 shows. In addition, the undistorted parabolic track is shown.  
This curve corresponded to the ideal parabolic track that would be plotted in the image plane if the electric field were constant. Moreover, both curves in the frequency domain could be compared. Therefore, the parabolic dependence (1) was subtracted from all curves. Figure 6 shows both curves plotted as a function of TOF. Obviously, the undistorted parabola became a constant function without any variations due to the EMP. The modulation periods of both parabolas presented similarities. In order to quantify the similarity of the two curves in Figure 6, their frequency spectra were calculated and compared to each other. As it can be observed in Figure 7, the frequency ranges are almost identical. Additionally, we found the five highest peaks occurring at the same frequencies in both spectra. The result of this procedure is shown in the inset where the frequencies at which the peaks occur are listed. Since we are interested mainly in the values of frequencies on the x axis, the y axis of both plots were normalized. Consequently, both spectra in Figure 7 were integrated using the trapezoidal rule for approximating the definite integral and the ratio of integrals was calculated to be 1.2.  
Similar correlation was observed by also analyzing several additional TP snapshots and the corresponding antenna signals. The ratios between the integrals of the extracted and modulated curves were estimated to vary between 0.7 and 1.3.  
Figure 6: (**a**) Extracted (blue), modulated (red), and undistorted (black) parabolic track corresponding to protons. (**b**) Obtained curves from parabolas by subtracting parabolic dependence (1). X axis was the same in both figures. The direction of the y axis in (**a**) is the opposite with respect to Figure 2. Y axis in (**b**) shows the modulation amplitude in pixels.
# Method for Volume of Irregular Shape Pellets Estimation Using 2D Imaging Measurement
###### Abstract  
Growing population and decreasing amount of cultivated land conditions the increase of fertilizer demand. With the advancements of computerized equipment, more complex methods can be used for solving complex mathematical problems. In the fertilizer industry, the granulometric composition of products matters as much as the quality of production of chemical composition products. The shape and size of pellets determines their distribution over cultivated land areas. The effective distance of field spreading is directly related to the size and shape parameters of a pellet. Therefore, the monitoring of production in production lines is essential. The standard direct methods of the monitoring and control of granulometric composition requires too much time and human resources. These factors can be eliminated by using imaging measuring methods that have a variety of benefits, but require additional research in order to assure and determine the compliance of real-time results with results of the control equipment. One of the fastest, most flexible and largest amount of data providing methods is the processing and analysis of digital images. However, then we face the issue of the suitability of 2D images to be used for the evaluation of granulometric compositions, where processing of digital images provides only two dimensions of a pellet: length and width. This study proposes a method of evaluating an irregular pellet. After experimental research we determined \(<2\%\) of discrepancy when compared to the real volume of a pellet.  
image processing; fertilizers; distribution; monitoring Article
## 3 Results and Discussion
### Effect of Carbonization Pressure on Composition and Microstructure of CGBS
#### 3.2.2 BET  
Figure 11 shows the BET results of CGBS at different carbonization pressures. The specific surface area of CGBS1 is 45.86 m\({}^{2}\)/g, and the pore volume is 0.0745 cm\({}^{3}\)/g, while the specific surface area and pore volume of CGBS2 are 20.65 m\({}^{2}\)/g and 0.0605 cm\({}^{3}\)/g, respectively. The results show that with the increase in carbonization pressure, the specific surface area and pore volume of CGBS gradually decrease. On the one hand, the calcium carbonate produced by carbon fixation makes the slurry system structure more compact [33]. On the other hand, it may be due to the increase in carbonization pressure, the increase in hydration reaction rate, and the increase in hydration products, which leads to the decrease in pores in the slurry and the decrease in specific surface area [34].  
Figure 11: BET diagram of CGBS at different carbonization pressures.  
Figure 10: XRD patterns of CGBS at different carbonization pressures.
# Telecommunication Systems for Small Satellites Operating at High Frequencies: A Review
## 3 MarCO
### Telecommunication Requirements and Design  
In order to perform its primary mission, the MarCO spacecraft needed to be compatible with the Deep Space Network antennas and with the signal transmitted from the Insight spacecraft. Hence, it was required to use X-Band frequency for the Direct to Earth (DTE) link, and UHF frequency for the relay link from InSight. In terms of data rate, given that InSight was transmitting UHF data at 8 kbps, the relay system on the MarCO spacecraft was also required to function at the same data rate on the DTE link. The data rate requirement significantly drove the design of the hardware, especially for the high gain antenna. Additionally, the spacecraft were both supposed to navigate to Mars with their own trajectory, which implied that the radio had to be equipped with navigation functionalities to allow for ranging and Doppler estimation.  
Given these requirements, the system was designed with a unique radio, the Iris transponder that included a UHF receiver, all the X-Band functionalities, and the navigation features. The Iris radio is connected on the X-Band receiving path to a low noise amplifier (LNA) which is connected to one low gain patch antenna and one medium gain patch antenna array for X-Band uplink functions to the DSN. On the transmitting side, the Iris radio is connected to the solid state power amplifier (SSPA) which has three antenna ports and it is connected to a low gain patch antenna, a medium gain patch antenna array and an high gain antenna reflectarray, respectively. For the UHF, a loop antenna is connected to the Iris UHF receiver. A blog diagram is shown in Figure 4. Both the reflectarray and the loop antenna are deployable antennas.  
Figure 4: MarCO block diagram.  
The X-Band data rates mode used are 62.5 bps and 1000 bps for uplink, while for downlink the mission used a variety of data rates from 62.5 bps up to 8000 bps. At UHF, the data rate used was 8000 bps and the system was functioning in receiving mode only without any transmitting capabilities.
## 2 Materials and Methods
### Sampling and Analysis
#### 2.3.2 Biochemical Analysis  
At the end of the experiment, blood was sampled from the anaest fish (\(n=10\) fish/group). The blood (about 3 mL) was collected from the caudal vessel using a heparinized syringe (50 IU \(\mu\)L\({}^{-1}\)). Fresh whole blood samples (2 mL), with EDTA (ethylenediaminetetraacetic acid) added as an anticoagulant for blood plasma preparation, were used for biochemical assays in the same way as described by [PERSON] et al. [35]. The plasma samples were analyzed for the following biochemical parameters--total protein (TP, g\(\cdot\)L\({}^{-1}\)), alanine aminotransferase (ALT, \(\mu\)kat\(\cdot\)L\({}^{-1}\)), aspartate aminotransferase (AST, \(\mu\)kat\(\cdot\)L\({}^{-1}\)), lactate dehydrogenase (LDH, \(\mu\)kat\(\cdot\)L\({}^{-1}\)). cholesterol (CHOL, mmol\(\cdot\)L\({}^{-1}\)), triglyceride (TAG, mmol\(\cdot\)L\({}^{-1}\)), cortisol (COR, nmol\(\cdot\)L\({}^{-1}\)), and glucose (GLC, mmol\(\cdot\)L\({}^{-1}\)) levels. For the glucose analysis, a part of the whole blood sample was pipetted separately into plastic tubes (Vacuette) with sodium fluoride (NaF), as an inhibitor of glycolysis. All analyses were performed in a third-party lab (Stafila Laboratory, Czech Republic).  
2.3.3. Glutathioneione Antioxidant Status (GSH/GSSG Ratio)  
Immediately after blood collection, 100 uL of each whole blood sample was pipetted into plastic microtubes (Eppendorf, Hamburg, Germany) and used for oxidized (GSSG) glutathione analysis, while 50 uL of each whole blood sample was used for reduced (GSH) glutathione analysis in the same way as described by [PERSON] et al. [35]. The results are presented as the glutathione ratio (GSH/GSSG).