esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion  
### Isolation, Screening, and Identification of the LAB  
A total of 40 microorganisms isolated from different sourdoughs were evaluated to determine their antifungal capacity. The diffusion agar assay was performed to determine which strains presented the highest antifungal activity. As shown in Table 1, five strains stand out for their antifungal capacity. Most CFS had fungicidal activity against fungi of the genera _Aspergillus_ and _Penicillium_. However, the fungi _Penicillium digitatum_ shows resistance to the CFS of the isolated strains.  
According to the halo of inhibition of fungal growth, the activity of the strains TN10, TF2, TF8, TE4, and T16 was highlighted. These five strains were selected for the continuation of the study. Therefore, strains were identified using the MALDI-TOF MS method and classified with the MBT 7854 and MBT 7311_ RIO database (Bruker Daltonics, Billerica, Massachusetts, USA). This method verified the identity of the microorganisms at the species level: _Lactiplantiobacillus plantarum_ TN10, _Lactiplantiobacillus plantarum_ TF2, _Pedicococcus pentosaccus_ TF8, _Pedicococcus acidilactic_ TE4, and _Pediococcus pentosaccus_ T16. The identifications of the species with a Log score superior to 2 were considered. Henceforth, the acronyms TE4, TF2, TF8, T16, and TN10 will be applied to refer to their respective strain. Moreover, it is essential to emphasize that LAB are recognized as safe by the EFSA, and their presence in food may be beneficial.  
Against this background, several studies have reported the presence of _Lactiplantiobacillus_ and _Pedicococcus_ in sourdough and their use as biopreservative agents [9]. [PERSON] et al. [11]  
demonstrated that the nera _Lactiplantiobacillus_, _Lactococcus_, _Streptococcus_, _Pediococcus_, and _Enterococcus_ are endophytic microorganisms of sourdough and originated in cereal grain.  
During fermentation, the LAB population of sourdough is responsible for the final product's beneficial properties. This group of microorganisms is relevant as starter cultures in fermented food to preserve them and guarantee their safety. Furthermore, isolated LAB from sourdough are suitable for preserved sourdough because they are adapted to these food conditions [34].  
Studies such as that of [PERSON] et al. [35] proved that compounds generated in LAB fermentation result in an impediment against mold contamination. The study evidenced the opposite activity of _P. pentosacous_ against fungi of the genus _Aspergillus_. Furthermore, the authors discovered that _P. pentosacous_ produced antifungal preservative compounds with novel applications in different areas of interest.  
Other studies, such as that of [PERSON] et al. [36], showed the antifungal capacity of the _L. plantarum_ to inhibit the growth of different fungi, including _A. flavus_, _F. graminearum_, _F. cerevisiae_, and _F. verticillioides_.
## 2 Design Methodology
### Proposed Strategy: Scale Factor Determination  
Most of the cells in the practical implementation are surrounded mostly by air (except the fewer central ones in a 4 \(\times\) 4 array). An important observation is that the 4 \(\times\) 4 resonator with an inter-space of 6 mm has approximately the same response as the simulated result in the convergence point of Figure 8 for the first resonant frequency. Assuming this approximation, the scale factor could be inferred without fabricating a preliminary version to extract the disparity ratio by estimating it within the scope of pure simulation from Figure 8. Once the scale factor is applied to the original design, an equivalent resonator of larger dimensions will be obtained. When this new design is simulated under unit cell conditions, the expected resonant frequency should be lower than the measured one.  
The scale factor \(\alpha\) is defined as the quotient of the resonant frequency of the spaced FSS, which has no mutual coupling influence (\(f\,r_{nmc}\)), divided by the resonant frequency of the unspaced FSS (\(f\,r_{mc}\)) with mutual coupling effect.  
\[\alpha=f\,r_{nmc}/f\,r_{mc} \tag{1}\]  
The unit cell dimensions will be scaled according to the ratio between the frequencies that were previously obtained. Only the internal resonator is left unchanged because its resonant frequency coincides with the band that is required to be attenuated. Comparative studies will be carried out to validate the scaling factor method proposed for the FSS design.  
A summary of the proposed methodology for a low-profile FSS design is presented below:  
1. FSS\({}_{mc}\) design with reduced inter-element spacing for a low-profile design at low frequencies.  
Figure 9: Floquet mode simulation vs. measurement of the spaced FSS design (30 mm inter-element spacing).  
2. \(\text{FSS}_{smmc}\) design = FSS\({}_{mc}\) design spaced until reaching convergence in the low-frequency bands (approximately \(\lambda/2\) at the center of the filtered band).
3. \(\text{FSS}_{scaled}\) design = FSS\({}_{mc}\) design scaled by factor \(\alpha\) leaving the inner resonator unchanged.
4. Fabricate FSS\({}_{scaled}\) design.
5. Measure FSS\({}_{scaled}\) design vs. Simulation FSS\({}_{mc}\) design.
###### Abstract  
Leaf area is a key parameter underpinning ecosystem carbon, water and energy exchanges via photosynthesis, transpiration and absorption of radiation, from local to global scales. Satellite-based Earth Observation (EO) can provide estimates of leaf area index (LAI) with global coverage and high temporal frequency. However, the error and bias contained within these EO products and their variation in time and across spatial resolutions remain poorly understood. Here, we used nearly 8000 in situ measurements of LAI from six forest environments in southern China to evaluate the magnitude, uncertainty, and dynamics of three widely used EO LAI products. The finer spatial resolution GEOV3 PROBA-V 300 m LAI product best estimates the observed LAI from a multi-site dataset (\(R^{2}=0.45\), bias \(=-0.54\) m\({}^{2}\) m\({}^{-2}\), RMSE \(=1.21\) m\({}^{2}\) m\({}^{-2}\)) and importantly captures canopy dynamics well, including the amplitude and phase. The GEOV2 PROBA-V 1 km LAI product performed the next best (\(R^{2}=0.36\), bias \(=-2.04\) m\({}^{2}\) m\({}^{-2}\), RMSE \(=2.32\) m\({}^{2}\) m\({}^{-2}\)) followed by MODIS 500 m LAI (\(R^{2}=0.20\), bias \(=-1.47\) m\({}^{2}\) m\({}^{-2}\), RMSE \(=2.29\) m\({}^{2}\) m\({}^{-2}\)). The MODIS 500 m product did not capture the temporal dynamics observed in situ across southern China. The uncertainties estimated by each of the EO products are substantially smaller (3-5 times) than the observed bias for EO products against in situ measurements. Thus, reported product uncertainties are substantially underestimated and do not fully account for their total uncertainty. Overall, our analysis indicates that both the retrieval algorithm and spatial resolution play an important role in accurately estimating LAI for the dense canopy forests in Southern China. When constraining models of the carbon cycle and other ecosystem processes are run, studies should assume that current EO product LAI uncertainty estimates underestimate their true uncertainty value.  
remotely sensed LAI; field measured LAI; validation; magnitude; uncertainty; temporal dynamics +
Footnote †: journal: Remote Sensing
# Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular
## Abbreviations  
\begin{tabular}{l l}
3 GPP & Third Generation Partnership Project \\
5G & Fifth generation mobile networks \\ AAA & Authentication, authorization and accounting \\ ANDSF & Access network discovery and selection function \\ AP & Access point \\ BBU & Baseband unit \\ BS & Base station \\ CAPEX & Capital expenditure \\ CP & Control plane \\ CPRI & Common public radio interface \\ CN & Core network \\ C-RAN & Centralized-RAN \\ D2D & Device-to-device \\ DC & Dual connectivity \\ eNB & Evolved Node B \\ EPC & Evolved packet core \\ ePDG & Evolved packet data gateway \\ GRE & Generic routing encapsulation \\ HetNet & Heterogeneous network \\ HSS & Home subscriber server \\ IEEE & Institute of Electrical and Electronics Engineers \\ IF & Intermediate frequency \\ IFOM & IP flow mobility \\ IP & Internet Protocol \\ IPsec & IP security \\ ITU-R & International Telecommunications Union-Radiocommunication Sector \\ IMS & IP multimedia subsystem \\ IMT-2020 & International Mobile Telecommunications for 2020 and beyond \\ LAA & Lens array antenna \\ LNA & Low-noise amplifier \\ LTE-(A) & Long-Term Evolution (-Advanced) \\ MAC & Medium access control \\ MCS & Modulation and coding scheme \\ MEC & Mobile edge computing \\ MIMO & Multiple-input multiple-output \\ MME & Mobility management entity \\ MUST & Multi-user superposition transmission \\ NOMA & Non-orthogonal multiple access \\ NSWO & Non-seamless WLAN offload \\ mmWave & Millimeter wave \\ OFDM & Orthogonal frequency division multiplexing \\ OPEX & Operational expenditure \\ ORI & Open radio equipment interface \\ OVS & Open vSwitch \\ PAPR & Peak to average power ratio \\ PA & Power amplifier \\ PAA & Phased antenna array \\ PC & Personal computer \\ PCB & Printed circuit board \\ PDCP & Packet data convergence protocol \\ PDN & Packet data network \\ PDU & Protocol data unit \\ PHY & Physical \\ PoC & Proof-of-concept \\ QAM & Quadrature amplitude modulation \\ \end{tabular}
# Dynamic Node Privacy Feature Decoupling Graph Autoencoder Based on Attention Mechanism
###### Abstract  
Graph autoencoders' inherent capability to capture node feature correlations poses significant privacy risks through attackers inference. Previous feature decoupling approaches predominantly apply uniform privacy protection across nodes, disregarding the varying sensitivity levels inherent in graph structures. To solve the above problems, we propose a novel dual-path graph autoencoder incorporating attention-aware privacy adaptation. Firstly, we design an attention-driven metric learning framework to quantify node-specific privacy importance through attention weights and select important nodes to construct the privacy distribution, so that realizing the dynamically privacy decoupling and reducing utility loss. Then, we introduce Hilbert-Schmidt Independence Criterion (HSIC) to measure the dependence between privacy and non-privacy information, which avoids the deviations that occur when using approximate methods such as variational inference. Finally, we use the method of alternating training to comprehensively evaluate the privacy importance of nodes. Experimental results on three real-world datasets--Yale, Rochester, and Credit Defaulter--demonstrate that our proposed method significantly outperforms existing approaches like PVGAE, GAE-MI, and APGE, where the inference accuracy regarding privacy decreased by 25.5%, but the accuracy rate of link prediction achieved the highest 84.7% compared to other methods.  
graph autoencoder; attention; privacy decouple; privacy-utility trade-off Article
# A New Method of Fuzzy Support Vector Machine Algorithm for Intrusion Detection
## 2 Previous Work
Experiments indicated that the computational complexity was reduced significantly and the accuracy maintained high. However, the implementation of this classification method is complex. In recent years, neural networks have made remarkable achievements in computer vision [36; 37; 38] and natural language processing [39; 40; 41]. Researchers have also tried to use neural networks to process system call sequences [42; 43; 44; 45; 46]. AnRAD [47] performs probabilistic inference by self-structuring confabulation network. Their network continuously refines their knowledge base and is capable of fast incremental learning. [PERSON] et al. [48] implemented intrusion detection in a real environment based on a convolutional neural network. In order to accelerate the training process, multiple GPUs must be deployed on a physical host. The challenge of solutions based on a neural network is pricey and space consuming due to the increasing amount of data. [PERSON] et al. [49] proved that their method contributes more critical features for the least square support vector machine to achieve a better detection rate and lower computation cost. [PERSON] [50] applied a semantic structure to system calls. This approach facilitates the representation of software behavior and obtains excellent results in UNM dataset and KD98 dataset. [PERSON] et al. [51] presented a heterogeneous detector which consisted of sequence time-delay embedding, hidden Markov model [52; 53; 54] and a one-class support machine. In addition to satisfactory results, the heterogeneous detector also exhibits the reliability. [PERSON] et al. [55] detected features of the system in the hypervisor. The experiments demonstrated that their detection accuracy achieves 90% whilst the method has the detecting ability of DoS attacks. The algorithms based on frequency can be realized at a lower computation cost by reducing the dimension of the frequency vectors [56]. SVM is sensitive to noises and outliers [57; 58; 59; 60]. FSVM is based on fuzzy theory to reduce the influence of noises or outliers on the classification hyperplane [61; 62; 63; 64; 65]. [PERSON] et al. [67] proposed a method based on the relation between samples and their cluster center. [PERSON] et al. [68] proposed a new FSVM method after considering the imperfection of a distance-based algorithm. However, the above methods also reduce the effect of SVs on the hyperplane when reducing the influence of noises or outliers on the hyperplane.
# Hybrid Dual-Polarization Synthetic Aperture Radar
## 4 Performance in Earth Applications  
How do classification results from HCP data compare to those from quad-pol data? One credible way to answer this question is to look at the results drawn from a variety of applications for which both QP and HCP data are available. There are now numerous peer-reviewed publications that report such comparisons, a number sufficient to provide an answer.  
Many studies exploit an attractive feature of quad-pol SAR data to establish a nearly ideal comparison framework. Data from a QP radar can be transformed [36] from its conventional linearly-polarized format (H interleaved with V on transmit; H and V on each receive) into a different combination of transmit and receive polarizations (e.g., R on transmit; H and V on each receive). Hence, high-quality HCP data can be emulated (see Appendix C.4) from any given set of QP data. This approach assures that the ensuing comparisons of HCP vs. QP performance are objective and repeatable, since the same observational particulars apply for both scenarios.  
What classification methodology is appropriate for HCP data? After reviewing [37] many dozens of candidate comparison studies that have appeared in journal articles, conference papers, or dissertations, three methodological approaches emerge that deserve comment.
# Low-Complexity Progressive MIMO-OFDM Receiver for Underwater Acoustic Communication
## 1 Introduction
The rest of the paper is organized as: Section 2 gives a UWA MIMO OFDM system model, Section 3 explains ICI unaware iterative receiver in detail, and Section 4 describes ICI aware progressive iterative receiver. Section 5 gives the simulation and experimental results for both the receivers and Section 6 concludes our work.
# Cross-Technology Interference-Aware Rate Adaptation in Time-Triggered Wireless Local Area Networks
## 2 Related Work
### Goals of This Study  
The goal of this study is to minimize communication performance degradation caused by various types of CTI in time-triggered WLANs. Specifically, it explores a framework that identifies CTI and mitigates interference using WLAN-based interference mitigation techniques without requiring direct protocol designs for the wireless technologies causing the CTI. The key research questions (RQs) are as follows:  
* In time-triggered WLANs, how can interference mitigation be performed when WLAN devices experience cross-technology interference from multiple types of wireless devices without direct coordination with those devices?
* To perform interference mitigation based on CTI types, how can the CTI devices in the network be distinguished, and how can interference strength information for those devices be obtained?RQ3 How can CTI in the network be effectively mitigated using interference mitigation methods in WLANs without direct coordination for CTI?
# Intention Recognition for Multiple AUVs in a Collaborative Search Mission
## 4 CBIR Method in the AUV Collaborative Search Mission
### Intent Recognition Model Based on Residual Convolutional Neural Networks
During training, the model uses a cross-entropy loss function with the Adam optimizer and a learning rate scheduler to ensure efficient convergence. The training loop involves forward propagation, loss computation, backpropagation, and model weight updates over 300 epochs. Accuracy is monitored during training by comparing predicted and true labels, and the training loss is recorded to assess convergence. After training, the model is saved and tested using a custom testing function, validating its performance on unseen data. This approach ensures the model's robustness and accuracy in dynamic underwater environments.
###### Abstract  
In order to address the issue of limited excavation footage in the drilling and blasting of a water diversion tunnel with a cross-section of approximately 10 m\({}^{2}\), which is unable to meet the demands of rapid construction, a blasting method combining long and short straight-hole cutting was proposed based on the theories of elastic mechanics, blasting craters, explosive gas and stress waves. A mechanical model was established to elucidate the parameter design method and cavity formation principle of the combined cutting. Numerical simulation and field tests were employed to analyze the rock-breaking process of combined cutting, with a view to comparing the blasting effect differences between the traditional inclined cutting method and the combined cutting method. The research results indicate that during the blasting process with combined long and short straight-hole cutting, the uncharged portion of the deep hole can serve as an empty hole during the subsequent blasting of the shallow hole. The concentration of stress at the wall of the empty hole and the superposition of reflected and incident waves serve to enhance the rock-breaking effect of the shallow hole, with the enhancement being influenced by the diameter of the hole and the distance between it and the empty hole. The preferential detonation of the shallow hole can provide a smaller resistance line and free surface distance for deep hole detonation, creating favorable conditions for rock fragmentation in deep hole blasting, making it easier for the rock in the cutting area to be thrown out and increasing the utilization rate of the blast holes. The shape of the formed cavity is a long strip-shaped cube, with its volume being influenced by the spacing between each group of deep and shallow holes. The rock mass damage is most severe in the vertical direction, while the rock mass damage at the center of the upper and lower edges is relatively weaker. In order to optimize the utilization of blasting energy, it is essential to select an appropriate spacing between each group of blast holes. In comparison to the utilization of traditional inclined cuts, the implementation of combined long and short holes has been observed to result in a greater extent of blasting footage and relatively lower explosive consumption. These research findings provide a reference point for the rapid and efficient construction of small-section tunnel engineering, as well as the design of straight-hole cut blasting with reduced consumption.  
small-section tunnel; trending blasting; long and short straight eye; numerical simulation; field test +
Footnote †: journal: Applied sciences  
[PERSON] and [PERSON]
###### Abstract  
Long COVID-19, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), involves symptoms or effects that persist for more than 4 weeks after the initial SARS-CoV-2 infection. One contributing factor to this condition is the disruption in the expression of the antioxidant enzyme Nuclear Factor Erythroid-2 (Nrf2) induced by the COVID-19 infection. Apigenin and related flavonoids, known for their diverse pharmacological activities, including potent antioxidant properties, have emerged as promising candidates for Long COVID-19 therapy. These compounds, particularly apigenin, are recognized for their ability to modulate oxidative stress and inflammation, making them potential activators of the Nrf2 pathway. This study aims to predict the activity of apigenin and its related flavonoids as Nrf2 activators using molecular modeling and molecular dynamics (MD) techniques, providing insights into their therapeutic potential in managing Long COVID-19. The findings from the molecular modeling analysis indicate that apigenin has a favorable affinity, with a free energy value (AG) of \(-6.40\) kcal/mol. Additionally, MD simulation results demonstrate the strong stability of the Keep1-apigenin complex, with an average Root Mean Square Deviation (RMSD) value below \(0.20\) nm and the lowest average Root Mean Square Fluctuation (RMSF) value of \(0.86\) nm. Using the Molecular Mechanics/Generalized Born Surface Area (MM-GBSA) calculation method, the binding affinity of the Keep1-apigenin complex yields a lower free energy value (\(\Delta\)G) of \(-67.039\) kJ/mol, consistent with the molecular modeling results. Apigenin also exhibits the ability to inhibit the binding of Nrf2 to the hydrophobic surface of Keep1, with a total energy value of \(993.266\) kcal/mol and binding affinity value of \(-1.162\) kJ/mol through peptide\(-\)receptor docking. In conclusion, the comprehensive results suggest that apigenin has the potential to be a lead compound for developing Nrf2 activators specifically designed for Long COVID-19 therapy.  
Long COVID-19; apigenin; Nuclear Factor Erythroid-2 (Nrf2); molecular docking; molecular dynamics (MD) simulation