esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Effects of Storage and Maintenance Modes on Battery Performance
### Summary  
1. Storage mainly affects the charge-discharge power performance of Ni-MH battery modules; thus, factors that affect the power performance should be prioritized. Among all the considered storage conditions in this study, the charge-discharge modes have a significant impact on power performance.
2. The test results show that the storage and maintenance methods considered in this paper, such as charge-discharge mode, maintenance period, rest time, charge rate, and storage SOC, have little effects on the capacity recovery rate of Ni-MH battery modules.
3. The \(DDC\) mode effectively saves the single maintenance time, but it can deactivate the active materials of the Ni-MH battery modules. Thus, it should not be solely employed to maintain the Ni-MH battery modules. The \(FDC\) mode presents the best comprehensive maintenance performance, and it is recommended as the preferable method.
4. The 90-day and 120-day maintenance periods provide similar comprehensive maintenance performances. However, the 120-day maintenance period is beneficial for reducing maintenance time and saving maintenance cost, and this makes it the preferable maintenance period. Note that, if the storage time is shorter than one complete maintenance period, the Ni-MH battery modules need to be maintained once before using.
5. During maintenance, the 5-min rest time is more beneficial for maintaining the charge-discharge power and efficiency of Ni-MH battery modules. A slight increase in rest time is conducive to battery charge retention, but this effect is not obvious.
6. During maintenance, the 2-C charge rate is the best for the charge retention of Ni-MH battery modules. On the other hand, the 1-C charge rate is most favorable for maintaining the charge-discharge power and efficiency of the Ni-MH battery modules.
7. The 30% storage SOC is suitable for maintaining the capacity and power, and its performance in terms of charge-discharge efficiency maintenance is equivalent to that of 50% storage SOC.  
Figure 23: Effects of different storage and maintenance methods on battery change rate of efficiency.
# Evaluation of Garlic Landraces from Foggia Province (Puglia Region; Italy)
## 2 Materials and Methods
### Chemical Measurements
#### 2.3.6 Phenolic Compounds  
The lyophilized sample (0.05 g) was placed in a 2 mL Eppendorf tube and added to 1 mL of 80% methanol in water. The sample was mixed for 1 min, sonicated for 5 min, and then centrifuged (4000 g 4 \({}^{\circ}\)C for 20 min). The clear supernatant was diluted 1:1 with an acetonitrile:water (10:90, vol/vol) solvent mixture containing 0.1% formic, and filtered using re-generated cellulose filters of 0.22 \(\upmu\)m pore diameter. The analysis was performed according to [PERSON] et al. [17] with some modification using the UHPLC Dionex Ultimate 3000 RS system (quaternary pump, auto-sampler, column oven, and PDA), coupled by the HESI-II probe with the LTQ Velos Pro ion trap mass spectrometer (Dionex-ThermoFisher Scientific, Waltham, MA, USA). The separation of compounds was performed on a Hypersil GOLD aQ C18 column, 100 mm in length, 2.1 mm ID, and 1.9 \(\upmu\)m particle size (Waters, Milford, MA, USA) maintained at 30 \({}^{\circ}\)C. A binary mobile phase was used: (A) 0.1% formic acid in water and (B) 0.1% formic acid in acetonitrile, at a constant flow of 0.2 mL/min. The gradient program of solvent B was as follows: 0-30 min from 10% to 70%, 30-33 min isocratic 70%, 33-33.1 min from 70% to 10%. The MS conditions were: Capillary temperature 320 \({}^{\circ}\)C; source heater temperature 280 \({}^{\circ}\)C; nebulizer gas N\({}_{2}\); sheath gas flow 30 arbitrary units; auxiliary gas flow 15 arbitrary units; capillary voltage--2.8 kV, S-Lens RF Level 60%. Data were acquired in a negative ionization mode.  
Phenolic compounds were identified by comparing elution times, molecular ions, MS/MS fragmentation patterns of the experimental spectra with those obtained by the available pure standard compounds or by tentative methods using reported data from the literature. Calibration curves were created to obtain quantification results and were based on the UV signal of each available standard. When no commercial standard was available, a similar compound from the same phenolic group was used as a standard.
# Dynamic Reconfiguration of Active Distribution Network Based on Improved Equilibrium Optimizer
## 4 Optimization Algorithms
### The Proposed Improved Equilibrium Optimizer Algorithm
#### 4.3.3 Stochastic Differential Mutation Strategy
The concentration particle \(Ci\) represents a specific solution generated in a given iteration, and its dimensions match the solution space dimensions of the distribution network reconfiguration. _Cij_ represents one dimension of the solution, which is derived from the adaptive ordered loops feasible solution matrix _JM_, with each dimension corresponding to one of the loops in the matrix (i.e., \(j\) is constantly equal to 1). Each basic loop is set as a variable, and each variable corresponds to a branch encoding representing the switch number in the loop. The variable takes values within the range of the number of switches in the loop, and when encoded, it indicates whether the corresponding branch's switch is turned on. For each independent loop, a variation is applied to the intra-ring number \(i\) of branch _Cij_. If the variant number exceeds the maximum number of branches _kj_ in the loop, the result is divided by _kj_, and the remainder is mapped back to the original loop as the final variant branch, following the property that the first branch is connected to the first branch of the loop. Introducing the stochastic differential variational strategy into the standard EO algorithm not only facilitates a smooth transition between the pre-intermediate exploration and development phases but also increases perturbation near the extremum during the algorithm's iterations. This helps prevent stagnation in local optima, contributing to the diversification of the Pareto frontier and enhancing the algorithm's ability to find optimal solutions, thus avoiding low-quality local optima. The integration of the proposed adaptive ordered loop-based feasible solution judgment model _JR_ with the improved EO algorithm further enhances both the solution efficiency and the optimal solution search capability of the reconfiguration algorithm.
# Reduced Overhead Routing in Short-Range Low-Power and Lossy Wireless Networks +
## 6 Conclusions  
Standard RPL exhibits poor performance in P2P communication due to the required additional control overhead and inefficient P2P forwarding. Moreover, it uses source routing for P2 MP communications, and possibly in P2P communications as well. The source routing results in variable size address headers, higher energy consumption, and possibly lower PDR due to higher control overhead. To address this, we presented ERPL, which is not only an enhanced routing and forwarding mechanism for P2P communication for RPL's storing and non-storing MoPs, but it also presents a probabilistic forwarding mechanism based on BF to reduce source routing overhead for P2 MP and P2P communications. ERPL P2P routing and forwarding algorithms reduce the number of transmissions required to delivery a P2P data packet to the destination node thus reducing delay and supporting delay sensitive Internet of Things and Cyber-Physical System applications over LLNs. Moreover, ERPL P2P routing and forwarding algorithms can coexist with existing RPL implementations. Our results demonstrate that ERPL P2P routing and forwarding algorithms not only outperform the standard RPL protocol in P2P communications, but they also outperform the protocol in MP2P and P2 MP communications. Our results also demonstrate that ERPL's probabilistic forwarding algorithm for P2 MP communications substantially reduces the source routing overhead associated with RPL and hence better suits the requirements of short-range wireless LLNs.  
[PERSON] conceived the idea, implemented it, performed the experiments, and collected results. [PERSON] and [PERSON] analysed the results. [PERSON] wrote the paper, [PERSON] contributed in reviewing and editing it.  
This research was funded by Science Foundation Ireland (SFI) and the European Regional Development Fund under Grant Number 13/RC/2077. The APC was also funded by the same research funding.  
This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) and is co-funded under the European Regional Development Fund under Grant Number 13/RC/2077.  
The authors declare no conflict of interest.
# Free-Space QKD with Modulating Retroreflectors Based on the B92 Protocol
## Appendix C  
The MRR-QKD system is divided into the interrogator and MRR terminal, as shown in Figure A4. The interrogator generates an interrogation signal and sends it to the MRR terminal. This interrogation signal is a classical light pulse with fixed circular polarization state (does not carry any information), especially right-hand circular polarization in RM2018. The MRR terminal receives and modulates the interrogation signal and the output signal is in one of states in decoy state BB84 protocol. The modulated signal is retro-reflected back to the interrogator. The interrogator receives and measures the polarization state of the signal.  
The interrogation signal is prepared by means of the classical optical pulse with vertical polarization passes through a quarter wave plate oriented at 45\({}^{\circ}\). It is necessary to select appropriate signal intensity to ensure that each interrogation pulse contains multiple photons when it reaches the MRR terminal. The interrogation signal is modulated with four pairs of MQWs, which is composed of two stacked MQW. The number of MQWs is eight in total, achieving 15 dB extinction ratio of each pair. Each polarization state in BB84 protocol is generated by a set of MQWs and retroreflector in a path respectively, corresponding to H/V(rectilinear basis) and \(+/-\)(diagonal basis). The signal in rectilinear basis is generated by the signal transmitted through the BS2; the signal in diagonal basis is generated by the signal reflected by the BS2. It is worth emphasizing that the interrogation signal with right-handed circular polarization is converted into left-handed circular polarization after passing through the half wave plate oriented at 22.5\({}^{\circ}\). The modulated signal with H/V polarization is converted into \(+/-\) after passing through the half wave plate.  
The transmission loss of each pair of MQWs is controlled independently to realize different states of MQWs. While the transmission loss of the MQWs modulator is set to the lowest (highest), the MQWs is in the \"on\" (off) state. Polarization modulation is achieved by changing the state of MQWs. For example, if the horizontal polarization(H) is selected, MQWs1 is set in low transmission loss allowing horizontal signal to pass. The other three MQWs are set in high transmission loss which blocks the transmission of signal with unwanted polarization(V\(//-\)). In this condition, only the horizontal polarization signal can transmit back to interrogator. The decoy state is realized by accurately controlling the transmission loss of MQWs1. Finally, interrogator receives retro-reflected signal and measures its polarization. The measurement process is the same as the traditional QKD based on BB84 [6].
## 2 Background Information
### Generation Mechanism of Hydrodynamic Noise
#### 2.1.2 Wake Noise
As the flow velocity increases, both the frequency and intensity of vortex shedding are enhanced, leading to an increase in noise intensity. The term \(U^{3}\) in Equation [4] reflects the cubic relationship between vortex strength, shedding frequency, and flow velocity. The frequency of vortex shedding is inversely proportional to the size of the object, and thus the characteristic size d determines both the frequency and scale of vortex shedding. As a result, larger objects produce vortex noise at lower frequencies. These findings indicate that flow velocity, object size, and fluid properties are pivotal factors in the vortex shedding process. Consequently, the characteristics of wake noise can exhibit substantial variation under diverse flow conditions. To enhance comprehension of the genesis of wake noise, numerous scholars have conducted exhaustive research from diverse vantage points. [PERSON] [33] examined the short-wave instability that develops near the vortices at the tip of a blade and explored its potential as a major source of blade-tailwind interaction noise. [PERSON], [PERSON] [34] proposed a method for analyzing and evaluating dynamic noise (DFN) generated by a worm casing tongue based on the wake flow characteristics of a centrifugal impeller. He evaluated the effect of worm casing tongue clearance on the DFN of a centrifugal fan by comparing predicted and measured noise levels from a hydrodynamic perspective. [PERSON] [35] performed large vortex simulations of a single NACA 6512-63 airfoil at low Mach numbers and predicted broadband self-noise and wake-airfoil interaction noise from the simulation results using [PERSON]'s theory of edge noise. Wake noise holds particular significance in military applications. In an effort to investigate the impact of rounded corners on submarine wake field uniformity and propeller non-stationary bearing capacity, [PERSON] [36] conducted submarine drag and self-propulsion calculations using detached eddy simulation (DES). These calculations demonstrated that rounded corners can effectively enhance the quality of the flow field in the wake and reduce the propeller's non-stationary bearing capacity. This finding suggests that the uniformity of wake flow on a submarine propeller disk is a pivotal factor influencing propeller vibration and noise performance.
## 4 System Design
### Application Structure  
The described technical and functional requirements require a client-server application. The client-server application pattern [27; 28] is the most common way of dividing a task into well-segregated components responsible for very specific tasks [26].  
Client-side applications generally represent web applications (usually created with technologies like HTML, CSS, and JavaScript) [29; 30], mobile applications (created with technologies like Objective-C, Kotlin, Swift, Dart, Flutter, etc.) [31], and desktop applications [32]. This piece of the product aims to deliver a consistent and streamlined experience to the user, handling scenarios like optimum data handling, providing user experience and interactions, animations and transitions, basic client-side security, and low-effort user-interface interactions.  
Server-side applications (commonly known as the backend) [33; 34] represent the main code that handles the actual data and business logic of the application. Those applications run primarily on servers to which the client-side applications send requests for data or actions to be executed.  
The server-side application oversees many other tasks like handling the connections with the data storage solutions, imposing security, and handling architecture and authorization.  
In modern development, there is always a constant need for scaling. Systems aim to deliver the promised functionality to a large number of users. To facilitate this behavior, any application needs a proper infrastructure that provides the flexibility and resources required to address a large number of users. This component is generically called cloud infrastructure.
# Explainable Liver Segmentation and Volume Assessment Using Parallel Cropping
## 4 Application to Liver Segmentation  
This study examines the impact of the cropping on the liver segmentation and the application of semiautomatic cropping to segment the liver. The Chan-Vese implementation by [PERSON] and [PERSON] [16] and the U-Net framework by [PERSON] et al. [14] are discussed in this section for liver segmentation. We crop the original liver slice using the proposed voxel-based parallel cropping approach. The cropped liver slice is provided as an input to both models, i.e., traditional liver segmentation using Chan-Vese and learning-based liver segmentation using U-Net. The study analyzes segmented liver output from both models and the impact of cropping on liver segmentation.  
Liver segmentation using the Chan-Vese and U-Net approaches is shown in Figure 3. We apply parallel cropping on the input liver slice to obtain the cropped liver slice. On the left, the Chan-Vese algorithm is applied, obtaining the final segmentation. Similarly, on the right, liver segmentation using U-Net is computed. The U-Net result presents an unwanted segmentation outside the liver, on the right. This unwanted segmentation outside the liver is removed in the post-processing step, obtaining the image's maximum component and filtering out the other unwanted segmentation. U-Net has been trained using the (LiTS) dataset [20], which is composed of 131 CT liver volumes (58638 CT liver slices). We used 100 volumes for training, 10 for validation, and 21 for testing.  
The U-Net model was trained for liver segmentation using 58,638 axial slices derived from 131 annotated CT volumes in the LiTS dataset. We applied the Adam optimizer with a learning rate of \(10^{-3}\), \(\beta\) values (\(0.9,0.999\)), and a weight decay of \(10^{-5}\) for regularization. Training was performed for 250-300 epochs with early stopping and learning rate scheduling, which allowed fine segmentation convergence without overfitting. To improve generalization, we employed data augmentation including random horizontal and vertical flips as well as random rotations.  
The loss function for binary segmentation combined binary cross-entropy (BCE) and Dice loss in an equal proportion:  
\[\mathcal{L}=0.5\cdot\mathcal{L}_{\text{BCE}}+0.5\cdot\mathcal{L}_{\text{Dice}}, \tag{1}\]  
where \(\mathcal{L}_{\text{BCE}}\) represents binary cross-entropy loss, and \(\mathcal{L}_{\text{Dice}}\) denotes the Dice loss computed between the predicted and ground truth masks. This formulation balances pixel-wise classification accuracy with region-level overlap, which is particularly important for liver boundary precision and accurate volume estimation.  
We assess the quality of liver segmentation on original and cropped images and discuss the results and improvement in segmentation quality in the performance evaluation section. In the next section, the study analyzes liver volume assessment as an application for 3D cropping.
# A Review of Air Pollution Monitoring Technology for Ports
## 2 Detection Methods for Air Pollutants in Ports
### Detection Methods for Gaseous Pollutants
#### 2.2.3 CO Detection Methods  
CO is a major pollutant in the air and is mainly produced by the incomplete combustion of carbonaceous substances in the air. When the human body inhales high concentrations of CO, it can induce symptoms such as memory loss, myocardial infarction, coronary heart disease, and hypoxic asphyxia [35], so the monitoring of CO concentration is also important. The manual analysis methods commonly used today to detect CO concentrations are NDIR (Non-dispersive Infrared) spectrometry method [36], and the automated analysis methods are the gas filter correlation IR absorption and the non-dispersive IR absorption method [37].
## Communication protocol
### Mobile Network Infrastructure
#### 2.5.3 VPN Solution  
Virtual Private Network (VPN) tunneling protocols are used for the secure forwarding of IP-Packets between physically distant networks. Well-known examples of such protocols are OpenVPN and IPsec, both of which are equipped with security features that ensure the confidentiality, integrity and authenticity of the forwarded packets. WireGuard is a modern alternative to OpenVPN and IPsec. Compared to these, WireGuard offers higher performance, better usability and stronger security.
## 6 Numerical Results
### Dynamic Topology Environment  
In the dynamic topology environment, UAVs randomly select a direction and a speed (\(\leq\)5 m/s) for their flight. The initial positions of all UAVs are different. The positions after flying for 1800 s are shown in Figure 11.  
Figure 12 shows the utilities of five UAV nodes versus simulation time. With the proposed DCF-TDMA protocol, UAV nodes can achieve time slots adaptively with a rapid change in topology. For UAV-1, its utility arrives at the first high point, which is 9 at the 80 th s. At the 480 th s, UAV-1 achieves the minimal time slots, because the topology changes significantly such that the coalition formatted before cannot obtain any benefit. Therefore, the protocol automatically operates the join-and-leave mechanism. UAV-1 quickly achieves many correct transmission slots again in a few seconds. UAV-1 achieves 11 transmission slots between the 760 th s and 1120 th s. The maximum number of transmission slots for UAV-1 is 17. From the curve of UAV-1, we can see that the topology changes significantly at the 480 th, 640 th, 1160 th, and 1480 th s. Compared to those of UAV-1 and UAV-80, the transmission slot number of UAV-40 is much smoother.  
Figure 10: Convergence speed vs. network size.  
Figure 11: UAV positions after 1800 s.  
The performance of network throughput in the dynamic topology environment is shown in Figure 13. Compared to traditional TDMA and USAP, the throughput of the proposed DCFG-TDMA protocol improves significantly.
# Detection of Induced Activity in Social Networks: Model and Methodology
## 3 Methodology for Identifying and Diagnosing Induced Support for a Political Project
### Model of Induced Activity in Social Networks  
The set-theoretic model of induced activity in a social network includes such basic elements as:  
* IO--set of information objects;
* IA--set of induced activity;
* Text--a set of textual attributes of the information object;
* Feature--the set of discrete characteristics of the information object;
* Com--the set of links between objects in the social network;
* Feedback--many signs of feedback from the audience;
* Event--event, political project.  
The model can be represented as follows (Figure 1)  
Let the information object in social networks have a number of properties:  
1. Textual features;
2. Discrete features;
3. Connections with another information object.  
Let us suppose the following:  
* It is possible to identify information objects that deviate from the norm, i.e., have anomalous characteristics by textual characteristics, connections, or by discrete features;
* It is possible to identify feedback characteristics for information objects that will differ from the norm;  
Then:  
* Those objects that differ from the norm in terms of the set of discrete features and the level of feedback from the audience belong to the set of guided/induced activity.  
In accordance with the proposed model, we will formulate the concept of induced activity:  
An induced activity is a set of information objects united by textual features, discrete characteristics, and connections with another information objects around one event, activity, or theme, designed to increase the level of feedback from the audience and form a necessary point of view.  
The proposed model of induced activity differs from the existing ones in that it takes into account the level of audience feedback in the social network of the political project, connection between informational objects, as well as their textual and discrete characteristics. At the same time, the model allows to form the requirements for the algorithm of segmentation of the audience of the political project.  
Figure 1: A model of induced activity in social media.