esa-sceva/satcom-chunk-collection huggingface dataset:
# Nature-Inspired Optimization Algorithms for the 3D Reconstruction of Porous Media
## 2 Material and Methods  
### 3D Porous Media Reconstruction  
To study the macroscopic behavior of a porous media, the geometry and topology of the pore space need to be determined. However, the acquisition of the porous media microstructure requires the application of specialized and expensive equipment (TEM, GEM, etc.) that can accurately capture the distribution of the pores in a short time. Another, less equipment-demanding way to derive the 3D porous media structure is to apply a 3D reconstruction algorithm, utilizing the material information enclosed in a single 2D thin slice of the material, which can be captured easily using a conventional microscope.  
Mainly, there are two categories of 3D material reconstruction algorithms: (1) statistical/stochastic methods that apply linear and non-linear filters to an uncorrelated Gaussian distribution [5; 7; 8; 35] and (2) optimization-based methods that tackle the reconstruction process as an optimization problem [9; 10]. The former methods are characterized by lower accuracy and higher computation time compared to the latter ones. However, both types of algorithms use the same measures for encoding the porous space and describing the morphological properties of the material, such as multiple-point and auto-correlation functions [36]. These functions are capable of statistically describing the microstructures of the 2D slice of porous media and thus can be used to construct 3D models with the same statistical properties.  
A recent work investigating the role of the correlation function in 3D material reconstruction [37] has shown that among the diverse number of correlation functions, the following two-point auto-correlation function exhibits a high reconstruction performance:  
\[R_{z}=\frac{(Z(\mathbf{x})-\varepsilon)(Z(\mathbf{x}+\mathbf{u})-\varepsilon)}{\left(Z(\bm {x})-\varepsilon\right)^{2}}, \tag{1}\]  
where \(\mathbf{x}\) is the vector of the coordinates of each image pixel, \(\mathbf{u}\) is the distance vector, \(\langle\cdot\rangle\) is the average operator, and \(Z(\mathbf{x})\) is the phase function defined as:  
\[Z(\mathbf{x})=\left\{\begin{array}{l}1,\,\mathbf{x}\in\text{\emph{p}ore\,space}\\ 0,\,\mathbf{x}\in\text{\emph{material}}\end{array}\right.. \tag{2}\]  
Moreover, \(\varepsilon=\langle Z(\mathbf{x})\rangle\) corresponds to the porosity of the material.  
It is worth noting that when calculating the auto-correlation function of the 2D slice image, the method of periodic boundaries is applied for the coordinates lying outside the image's dimensions. The porosity and the auto-correlation function of Equation (1) corresponds to the first two statistical moments of the 2D image, which describe the distribution of the pixel values inside the material image space.  
In this study, the 3D reconstruction of a material using an algorithm belonging to the second abovementioned category was examined. The defined optimization problem was solved by applying several nature-inspired optimization algorithms discussed in the next section.
# Pressure Transient Model of Water-Hydraulic Pipelines with Cavitation
## 2 Mathematical Models  
### Basic Equations without Cavitation  
The simple water-hydraulic pipe is shown in Figure 1. To illustrate the propagation and reflection of the pressure transients, the sequence of events, which is caused by a valve closure in the middle of the pipe connected with the downstream and upstream tanks, will be discussed. Without a loss of generality, the pipe diameter is assumed to be constant, and the released gas is negligible.  
The general model of pressure transients in the pipeline involves the continuity equation and the momentum equation, which are mentioned in [PERSON] et al. [29]. The continuity equation is derived from the mass conservation law as follows:  
\[\frac{1}{c_{0}^{2}}\frac{\partial p}{\partial t}+\frac{\rho}{\pi r_{0}^{2}} \frac{\partial q}{\partial x}=0, \tag{1}\]  
where \(p\) is the pressure in pipeline, \(q\) is the flow rate, \(\rho\) is the density of fluid, \(c_{0}\) is the acoustic velocity in the fluid, \(r_{0}\) is the radius of the pipeline, \(x\) is the spatial variable, and \(t\) is the time variable.  
Meanwhile, the equation of momentum is constructed by [PERSON]'s law of motion as follows:  
\[\frac{\rho}{\pi r_{0}^{2}}\frac{\partial q}{\partial t}+\frac{\partial p}{ \partial x}+F(q)=0. \tag{2}\]  
In Equation (1), \(c_{0}\) can be given by  
\[c_{0}=\sqrt{B_{eff}/\rho}, \tag{3}\]  
where \(B_{eff}\) is the effective bulk modulus.
## 4 Discussion
The frequency of membrane perforation was higher when a single implant was placed (4.8%) than when multiple implants were placed (0%). This result might be related to the fact that the ratio of irregular sinus floor was higher in the single implant group (43%) than in the group with multiple implants (29%). Among single implant placed patients, one case with membrane perforation occurring had an extensive maxillary sinus pneumatic with root protruding of the adjacent teeth. It is recommended to indirectly elevate the Schneiderian membrane in the difficult-to access area by performing an adequate membrane elevation of the adjacent easy-to-access area. For example, when the elevation of the Schneiderian membrane is difficult due to an irregular sinus floor, sufficient membrane detachment of adjacent medial and lateral sinus walls can lead to spontaneous elevation of the Schneiderian membrane on the irregular sinus floor. In the present study, all implants were placed, and most healing abutments were connected simultaneously with minimally invasive lateral approach MSFE. Reducingthe number of total surgeries can reduce patient morbidity, which could be considered for minimally invasive management. For simultaneous implant installation with lateral approach MSFE, a gain of primary stability of placed implant might be crucial. With less than 3 mm of residual bone height, implant primary stability is unpredictable [25]. Our study included patients with a mean residual bone height of 3-4 mm, which might exhibit unpredictable primary stability of the implant. To secure sufficient primary stability, bone drilling protocol was adjusted to under-preparation of the osteotomy site less than 10% of the desired implant diameter [29]. Various methods to increase the primary stability of the implant have been proposed. Although the [PERSON] osteotomy technique improved primary stability with bone compaction, it could lead to unintentional bony fracture or even benign paroxysmal positional vertigo of the patient [30]. Furthermore, high interfacial pressure induced from under-preparation or Summers' osteetome might lead to the microfracture of the trabecular bone, which might compromise the marginal bone level maintenance [31]. Recently, various osseodesification drills have been introduced to increase implant primary stability with plastic deformation of the trabecular bone [32]. This technique can also be considered for minimally invasive treatment of atrophic posterior maxilla with poor bone quality. The limitation of the present study was that there was no preoperative computed tomography evaluation before the minimally invasive lateral approach for MSFE with simultaneous implant placement. Measurement of residual bone height and maxillary sinus width, bone density evaluation from preoperative computed tomography should be needed for deciding the proper surgical approach in the implant rehabilitation of atrophic posterior maxilla [25]. Further evaluation using cone-beam computerized tomography on bony healing of osteotomy site and volumetric changes of graft material is needed.
## 3 Dual-Band Doherty Power Amplifier  
Wireless communications systems have different standards and requirements where each standard can use a certain frequency band. At the same time, mobile communication systems are being developed where the data rate is one of the main targets for each generation; the growth of data rate requires a complex modulation and more bandwidth [11; 12; 13; 14; 15]. However, due to the crowded spectrum, the upcoming generation may use more frequency bands in order to fulfil the targeted requirements (e.g., 5G spectrum consists of three bands are 700 MHz, 3.6 GHz and 26 GHz) [16], in this case, the devices of the new generation should be designed to deal with these frequency bands in addition to the compatibility with the previous mobile generations.  
Figure 4: Voltage and current behavior of Doherty amplifier [10].  
Moreover, a new 3 GPP protocol which is narrowband Internet-of-Things (NB-IoT) specifies the maximum output power to be at least 23 dBm for long-range communications [17]. This protocol supports the two frequency bands 699-915 MHz and 1710-1980 MHz; the demand for integrating power amplifiers that can support high power and high efficiency on a chip is increasing since it can increase the battery life and reduce the running cost [17].  
In order to increase modulation bandwidth efficiency, carrier aggregation technology was introduced, where new wireless communications systems technologies are expected to use multi-band multi-standard applications [18]. To support dual-band simultaneously, two power amplifiers can be used for each band, but this increases the die area and requires more circuitry to combine their outputs. Therefore, dual-band design can provide a reduction in the size and cost of the system, and Doherty can provide good efficiency [19]. The use of dual-band also requires the PA to work in conjunction with software-defined radio (SDR) [20], which can use the same hardware at two different frequencies to perform a similar function.  
The term dual-band can be implemented in two ways; the first is called reconfigurable dual-band amplifier, in this case, the power amplifier is designed to work in two frequency bands, one at a time, where the circuit properties and configuration is changed depending on the target band. On the other hand, the concurrent dual-band implies that the amplifier can work on both frequency bands without any modification or changing of the design; intermodulation distortion should be considered especially if the two bands are close to each other because the effect of device nonlinearity will be significant, in this case, some interference will be introduced to the neighboring channels. The next subsections will deal with dual-band limitations, challenges, and the techniques that were used to make the Doherty power amplifier works in two bands.
## 3 Design of Maritime Data Security Management Platform
### Application Layer  
The application layer provides various special data service systems for shore-based users and ship users and provides convenient and intelligent services according to users' needs. For example, shore-based users can use the Marine environment forecasting system to obtain wind, wave, current and other marine environment data of the desired area, and use the ship steering simulation system to view the three-dimensional Marine environment of a specified port. Using the electronic navigation chart system, ship users can not only view the basic Marine geographic information but also choose to overlay AIS data,  
Figure 1: The architecture of the maritime data security management platform.  
Marine environment forecast data, ship route data, ship pollution emission data, hazardous conditions and other comprehensive navigation data. Through the use of a route planning system, users can analyze navigation data, determine the degree of risk of ship navigation and develop a safe navigation plan. With the development of an intelligent ocean, more maritime applications can be expanded on the platform to facilitate the use of more users.
# Efficient Online Engagement Analytics Algorithm Toolkit That Can Run on Edge
## 1 Introduction
### Concerns  
As online meetings and exams become increasingly reliant on video analytics to understand the behavior and attentiveness of the audience, it is important to consider the concerns that the audience might have about these analytics being applied to their video feed.  
One concern that the audience might have is about privacy [20]. With online meetings and remote work, it is often necessary to share personal information and data, such as one's location, webcam feed, and computer screen. This can raise concerns about data security and the risk of data breaches and the policies to protect privacy. Many people are understandably concerned about their data being collected, shared, or used in ways that they did not consent to. A qualitative study conducted in Japan found that students who participated in online classes were comfortable with showing their faces on camera, but they were hesitant to be recorded due to concerns that the recordings might be shared publicly [21]. To address this concern, it is important for online meeting hosts and employers to provide clear information about how the analytics will be used, and to give the audience control over their data. This might include options for opt-in or opt-out, as well as clear information about what data will be collected and how it will be used.  
There is also a risk that the analytics could be biased and used for nefarious purposes, such as surveillance or control. To address this concern, it is important for online meeting hosts and employers to be transparent about how the analytics will be used and to ensure that they are not being used for purposes that are not in the best interests of the audience.
# CGFL: A Robust Federated Learning Approach for Intrusion Detection Systems Based on Data Generation
## 4 Experiments and Results
### Results and Discussions
#### 4.2.2 Performance of Data Augmentation  
We conducted an analysis of the changes in model performance before and after data augmentation to illustrate the enhancement in our proposed model's capacity to identify minority samples. We refined the trained composite network exclusively using the original data. The CVAE (Conditional Variational Autoencoder) was employed as the feature extractor, and softmax was employed as the classifier. Tables 4-6 illustrate the model's performance on the NSL-KDD, IDS2017, and IDS2018 test sets with and without data augmentation, respectively.  
The F1-score, a critical metric for evaluating models on imbalanced datasets, measures the balance between precision and recall. As shown in Table 4, the F1-scores for all five categories improved. Notably, the score for R2L increased from 0.5333 to 0.6053,  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Clients**} & \multicolumn{4}{c}{**Test Accuracy (\%)**} \\ \cline{2-5}  & **PHEC [48]** & **[49]** & **FATRAF [47]** & **CGFL** \\ \hline K = 100 & 94.75 & 92.44 & 94.88 & **96.81** \\ K = 150 & 84.28 & 81.37 & 82.98 & **88.37** \\ K = 200 & 74.62 & 72.49 & 76.83 & **81.08** \\ \hline \hline \end{tabular}
\end{table}
Table 3: Performance comparison with other methods in ICS/SCADA.  
while U2R showed a dramatic rise from 0.1671 to 0.9843, indicating a significant enhancement in detecting minority class attacks. Additionally, the G-Mean metrics displayed notable improvements.  
On the IDS2017 dataset, as depicted in Table 5, data augmentation led to substantial improvements in F1-scores across categories: infiltration rose from 0.3233 to 0.4532, Bot increased from 0.7842 to 0.8971, and Web attack climbed from 0.6409 to 0.8531. However, a slight decline in the recall rate for benign samples occurred, likely due to misclassifications in the augmented data.  
For the CSE-CIC-IDS2018 dataset, Table 6 highlights significant improvements in recall rates across all categories. Cyber attacks, in particular, improved from 0 to 0.7238. However, an increase in false positives across other categories slightly reduced Bot's accuracy, potentially due to the larger dataset size.  
Overall, all categories benefited from varying degrees of improvement. Data augmentation had a profound positive impact on model training across the three datasets. The CVAE-GAN module, in particular, significantly enhanced overall model performance, despite minor reductions in recall and precision.
## 4 Discussion
### Use of PRI as a Stress Indicator  
Figure 9 shows that the PRI neatly follows the same diurnal behaviour as Y(II), which is, by definition, inversely related to NPQ, making it a biochemical indicator that is complementary to SIF. When using PRI, it is important to consider that PRI bears both structural and biochemical information. Unlike to SIFA, there is no corrective vegetation index to separate the biochemical and structural components of PRI. This makes the interpretation of PRI in physiological terms less straightforward. Still, PRI time series revealed some stressed periods, as PRI did not adhere to its upward trend during this period. Using high-temporal resolution data of PRI, several methods using de-trending techniques exist to remove the structural effect from the PRI measurement [42; 43]. The differences in the stress reaction between PRI and SIFA indicate that both variables are sensitive to different parts of the photosynthetic apparatus. This suggest that they provide complementary information on the plant's photosynthesis. The combination of ecosystem-scale PRI and SIFA has already proven its value for photosynthesis estimations [44].
# A Review of Acoustic Emission Source Localization Techniques in Different Dimensions
## 4 Acoustic Emission Source Localization Techniques for Three-Dimensional (3D) Structures
### Extend the Two-Dimensional Source Localization
[74] proposed a positioning method for a right-angle tetrahedral sensor cluster. Combining the spatial information of the sensor cluster, the acoustic emission source was located by collecting the time difference of arrival of the first wave between different sensors. This method can be applied to anisotropic materials and requires fewer sensors. There are also some two-dimensional methods that can be applied to three-dimensional positioning, for example, establishing the objective equation of the error function [75] for localization methods, using iterative algorithms to locate the acoustic emission source from the information collected by the sensor array [76; 77], three-dimensional beam forming localization methods [78; 79; 80; 81; 82; 83; 84], etc. Beam forming is a commonly used method in two-dimensional positioning. However, especially in the past few years, there has been an increasing trend in exploring the possibility of calculating beam forming results in three-dimensional space, but most of them are focused on locating noise sources in space [85; 86; 87; 88; 89; 90; 91]. These methods provide reference for the application of beam forming technology in three-dimensional acoustic emission source localization.
## 2 Selected Wireless Sensor Networks Standards: State-of-the-art
### 802.15.4e Factory Automation MAC Layer
#### Architecture  
The 802.15.4e Factory Automation MAC layer is based on the IEEE 802.15.4 physical layer and develops particular superframe formats as well as transmission modes to support deterministic TDMA [29]. The gateway supports three main transmission modes: discovery mode, configuration mode and online mode.  
The _discovery mode_ takes place during either network setup or joining procedure. The gateway sends superframes with beacons to indicate the discovery mode. When a device wanting to join the network receives such a beacon, it tries to access the transmission medium to send a _Discover Response_ frame to the gateway with its current configuration parameters. The frame will be retransmitted by the device until the gateway receives it or changes its transmission mode.  
During network setup or reconfiguration, the gateway is in a _configuration mode_ and indicates this status in the superframe beacon. When the device receives the beacon and gets access to the transmission medium, it sends a _Configuration Response_ frame to the gateway with its current configuration until the gateway receives it or changes its mode. As soon as the gateway receives the _Configuration Response_ frame, it sends a _Configuration Request_ frame with the new device configuration parameters and the device sends an acknowledgement in the next superframe.  
In the _online mode_, devices can send data to the gateway in the timeslots allocated during the configuration mode and the gateway acknowledges the received data in the following superframe.  
The superframes are sent to the end devices by the gateway and their structures depend on the current gateway transmission mode. The first slot is designed as the beacon slot (Fig. 11) and is common to all superframe structures. The end devices can detect the start of a new superframe at the reception of this first slot and synchronize themselves with it. Additionally, the beacon specifies the current trans  
Figure 10: 802.15.4e Factory Automation MAC Layer network elements.  
mission mode and also acknowledgements for data transmitted in the previous superframe. In discovery, configuration and optionally online modes, the beacon is followed by up to two management time slots, which manage the bidirectional transmission between gateway and actuators. During online transmission mode, the next time slots are allocated to sensors. These timeslots can be either dedicated to a particular device or shared by a group of devices using CSMA/CA. In the first case, no addressing information is necessary, whereas the second case requires a simple addressing scheme. Then, actuator time slots are reserved in the superframe. The direction of the communication between actuators and gateway is indicated in the beacon, and each time slot can be either dedicated or shared.
# FtsZ Interactions and Biomolecular Condensates as Potential Targets for New Antibiotics
###### Abstract  
FtsZ is an essential and central protein for cell division in most bacteria. Because of its ability to organize into dynamic polymers at the cell membrane and recruit other protein partners to form a \"divisome\", FtsZ is a leading target in the quest for new antibacterial compounds. Strategies to potentially arrest the essential and tightly regulated cell division process include perturbing FtsZ's ability to interact with itself and other divisome proteins. Here, we discuss the available methodologies to screen for and characterize those interactions. In addition to assays that measure protein-ligand interactions in solution, we also discuss the use of minimal membrane systems and cell-like compartments to better approximate the native bacterial cell environment and hence provide a more accurate assessment of a candidate compound's potential in vivo effect. We particularly focus on ways to measure and inhibit under-explored interactions between FtsZ and partner proteins. Finally, we discuss recent evidence that FtsZ forms biomolecular condensates in vitro, and the potential implications of these assemblies in bacterial resistance to antibiotic treatment.  
bacterial cell division; FtsZ association states; protein interactions; biomolecular condensates; macromolecular crowding; phase separation; cytomimetic media; persister states +
Footnote †: journal: _antibiotics_