esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
As the global concern over greenhouse gas emissions grows, CO\({}_{2}\) storage in deep saline aquifers and depleted reservoirs has become crucial for climate change mitigation. This study evaluates the feasibility of Lithuanian deep saline aquifers, specifically, Syderai and Vaskai, for effective CO\({}_{2}\) storage. Unlike previous theoretical analyses, it provides experimental data on static and dynamic reservoir parameters that impact CO\({}_{2}\) injection and retention. Using micro X-ray computed tomography (MXCT) and multi-resolution scanning at 8 \(\upmu\)m and 22 \(\upmu\)m, digital rock volumes (DRVs) from core samples were created to determine porosity and permeability. The method, validated against analogous samples, identified a representative element volume (REV) within subvolumes, showing a homogeneous distribution of petrophysical properties in the Lithuanian samples. The results show that DRVs can accurately reflect pore-scale properties, achieving 90-95% agreement with lab measurements, and offer a rapid, efficient means for analyzing storage potentials. These insights confirm that Lithuanian aquifers are promising for CO\({}_{2}\) sequestration, with recommendations for further long-term monitoring and applications of this technique across the region.  
CO\({}_{2}\) storage; Lithuanian saline aquifers; digital rock volume (DRV); machine learning; lattice Boltzmann method (LBM) +
Footnote †: journal: Applied sciences  
0000-0002-2200-7820][PERSON]  
1 Department of Mathematical Modelling, Kaunas University of Technology, 44249 Kaunas, Lithuania; [EMAIL_ADDRESS] (S.M.): [EMAIL_ADDRESS] (P.M.)
# A Low-Profile Ferrite Dipole VHF Antenna for Integrated Mast Applications
## 1 Introduction  
Modern naval warships carry out various operations at sea, including responding to multiple threats, such as anti-ship, anti-aircraft, anti-submarine, and land threats; securing maritime control; and securing maritime transportation routes. A multitude of antennas for communication, navigation, electronic warfare, and radar are separately mounted on warships to ensure their smooth operation. An increase in the number of antennas reduces the survivability of warships due to the high radar cross section (RCS) and degrades the performance capabilities of the systems due to electromagnetic interference (EMI). Recently, the concept of an integrated mast was introduced to overcome the RCS and EMI problems [1; 2; 3; 4]. An integrated mast can reduce RCS and EMI structurally through the use of a radome with a frequency selective surface [5; 6]. However, traditional monopole antennas of the types widely used on warships have several disadvantages when mounted on the face of an integrated mast, such as their high-profile and weight issues [7; 8; 9; 10]. Various antennas have been developed to realize low-profile [11; 12; 13; 14; 15; 16; 17; 18; 19; 20]. For low-profile, the antenna is designed as a loop-type structure or with high permittivity and/or permeability materials. For example, four half loops with a bent diamond structure placed on the ground were designed with a height of \(0.116\lambda_{L}\) at the lowest operating frequency [16]. In another study [17], a monopole shaped bow-tie antenna with two tophats, two shorting pins, and a ring slot cut into the ground plane was designed with a height of 0.085\(\lambda_{L}\). Several ferrite structures effectively applied to the inside of a loop radiator were introduced to realize low-profile design with a height of 0.00508\(\lambda_{L}\)[18]. In other work [19], a conformal ferrite dipole antenna with an electrically separated four-loop feeding structure was suggested, showing a very low-profile with a height of 0.00381\(\lambda_{L}\).  
In this paper, an extremely low-profile ferrite dipole VHF antenna with a height of only 0.0008\(\lambda_{L}\) is proposed for application to an integrated mast. To ensure the minimal size and weight of the antenna, 44 plate-type ferrite cells with a total weight of approximately 1.45 kg are used with the ferrite dipole antenna. The antenna is fed by an electric loop feeding structure. By applying a loop feeding structure with five loops, the magnetic distribution is changed from a triangular distribution to a quasi-uniform distribution. As a result, the gain of the antenna in the high frequency band is significantly improved. In the following sections, details of the design and performance of the proposed antenna are presented and discussed. The proposed antenna when mounted on the integrated mast of the offshore patrol vessel (OPV) is also examined.
## 3 The Proposed Protocol  
### System Model  
The system model considered in this paper consists of multiple UAVs, the GCS, and the certificate authority (CA), as shown in Figure 1. First, both the GCS and the UAV should register with the CA to obtain the certificate. Secondly, the UAVs perform authentication and key agreement to establish a secure communication session. Finally, one of the multi-UAVs is selected as the key node, through which the UAVs can achieve mutual secure communication.
# A Payload Based Malicious HTTP Traffic Detection Method Using Transfer Semi-Supervised Learning
###### Abstract  
Malicious HTTP traffic detection plays an important role in web application security. Most existing work applies machine learning and deep learning techniques to build the malicious HTTP traffic detection model. However, they still suffer from the problems of huge training data collection cost and low cross-dataset generalization ability. Aiming at these problems, this paper proposes DeepPSTD, a deep learning method for payload based malicious HTTP traffic detection. First, it treats the malicious HTTP traffic detection as a text classification problem and trains the initial detection model using TextCNN on a public dataset, and then adapts the initial detection model to the target dataset based on a transfer learning algorithm. Second, in the transfer learning procedure, it uses a semi-supervised learning algorithm to accomplish the model adaptation task. The semi-supervised learning algorithm enhances the target dataset based on a HTTP payload data augmentation mechanism to exploit both the labeled and unlabeled data. We evaluate DeepPTSD on two real HTTP traffic datasets. The results show that DeepPTSD has competitive performance under the small data condition.  
malicious traffic detection; HTTP payload; Data augmentation; Transfer learning; semi-supervised learning
# A Robust Method Based on Deep Learning for Compressive Spectrum Sensing
## 4 Datasets and Performance Metrics
### Performance Metrics  
The evaluation metrics for the proposed networks are introduced. For BEISTA-Net, the r-MSE is used as the evaluation metric. A lower r-MSE indicates that the reconstructed signal more closely resembles the original signal. For BSWSS-Net, detection probability (\(P_{\text{d}}\)) and false alarm probability (\(P_{\text{f}}\)) are employed as the evaluation metric. Generally, a higher \(P_{\text{d}}\) and a lower \(P_{\text{f}}\) are desirable.  
The r-MSE is defined as  
\[\text{r-MSE}=\frac{\|\mathbf{X}_{r}-\mathbf{X}\|_{2}^{2}}{\|\mathbf{X}\|_{2}^ {2}}, \tag{22}\]  
where \(\mathbf{X}\) is the original signal and \(\mathbf{X}_{r}\) is the reconstructed signal.  
The detection probability is defined as the ratio of correctly detected samples (true positives) to the total number of actual positive samples, which can be expressed as  
\[P_{\text{d}}=\frac{\text{True Positives}}{\text{True Positives }+\text{False Negatives}}, \tag{23}\]  
where the True Positives is the number of correctly detected positive samples, and False Negatives is the number of positive samples that were incorrectly classified as negative.  
The false alarm probability is defined as the ratio of incorrectly detected negative samples (false positives) to the total number of actual negative samples, which can be expressed as  
\[P_{\text{f}}=\frac{\text{False Positives}}{\text{True Negatives }+\text{False Positives}}, \tag{24}\]  
where False Positives is the number of negative samples incorrectly classified as positive, and True Negatives is the number of correctly classified negative samples.  
In cognitive radio, it is generally required that \(P_{\text{d}}>0.9\) and \(P_{\text{f}}<0.1\).
## 4 Numerical Examples
### Example 5--Reliability-Based Topology Optimization Considering Self-Weight  
The bridge shown in Figure 6a was analyzed by coupling the structure's own weight in the optimization procedure with the aim of analyzing the influence of the self-weight on the optimal configuration. It is worth mentioning that the optimal configurations obtained by the RBTO-BESO_3D and RBTO-SESO_3D methods are different in terms of structural design. However, when examining the optimal configurations, considering the self-weight, as seen in Figure 10, we observed that the two models produced similar configurations with just a denser arc in the shape of a catenary. These changes in topology are attributable to the influence of gravitational force and have important implications for engineers. This is due to the fact that optimizing the structure while taking into account its self-weight can result in more efficient and safe solutions.
###### Abstract  
In complex urban electromagnetic environments, wireless positioning signals are subject to various types of interference, including narrowband, chirp, and pulse jamming. Traditional generic suppression methods struggle to achieve global optimization tailored to specific interference mechanisms. This paper proposes a classification-driven differentiated jamming suppression (CDDJ) method, which adaptively selects the optimal mitigation strategy by pre-identifying interference types and integrating classification confidence levels. First, the theoretical bounds of the output carrier-to-noise ratio (\(C/N_{0_{max}}\)) under typical interference scenarios are derived, characterizing the performance distribution of anti-jamming efficiency (\(\Gamma\)). Then, a mapping relationship between interference categories and their corresponding suppression strategies is established, along with decision criteria for strategy switching based on signal quality evaluation metrics. Finally, an OpenMax-Lite rejection layer is designed to handle low-confidence inputs, identify unknown jamming using the Weibull distribution, and implement a broadband conservative suppression policy. Simulation results demonstrate that the proposed method exhibits significant advantages across different interference types. Under high JSR conditions, the signal recovery rate improves by over 10% and 8% compared to that of the WPT and KLT methods, respectively. In terms of SINR performance, the proposed approach outperforms the AFF, TDPB, and FDPB methods by 1.5 dB, 1.1 dB, and 5.3 dB, respectively, thereby enhancing the reliability of wireless positioning in complex environments.  
GNSS receiver; jamming suppression; classification decision; signal quality evaluation; conservative suppression strategy +
Footnote †: journal: Applied sciences  
_Article_
## 4 Results and Discussion
### Time History Analysis  
#### 4.2.1 General Aspects  
The process of time history analysis is initiated with static analysis. The variations between the models for dynamic and static analyses lie in utilizing energy-absorbing boundaries and \(\alpha\)- and \(\beta\)-coefficients to account for Riley damping and differences in material properties. In this research, dynamic time history analysis was employed. It was essential to adjust the data set to compare the results of equivalent dynamic time history analysis during scaling. The acceleration of the Tabas earthquake was selected as the reference acceleration curve. Specifically, the initial 20 s of the Tabas earthquake, which harbored the highest energy of the earthquake, were chosen for analysis. To scale the peak acceleration of the Tabas earthquake to 0.35 g, dynamic analyses were conducted with a 1.23 history of the acceleration of this earthquake. Since the studies focus on soil properties, the soil resistance parameters in the dynamic analysis in Table 5 are listed. Soil properties can affect the seismic performance of the tank.
# Diamonds for Life: Developments in Sensors for Biomolecules
## 6 Discussion and Future Outlook
The supramolecular recognition occurring between these two biomolecules, the covalently bonded one at the RL and the target analyte, creates a high degree of selectivity, which cannot be matched by electrodes. An additional advantage of biosensors is that they can operate with very small amounts of sample: a droplet of the solution can be simply placed on the receptor layer of the diamond-based biosensor. Furthermore, carbon-made biosensors with electrochemical detection have already been used to detect highly proliferative cells, such as human breast adenocarcinoma (MDA-MB-231), breast cancer isolated cell line (MCF-7), and hepatocellular carcinoma isolated cell line (HepG2), as portrayed and summarized by [PERSON] et al. [62], showinga great potential of carbon-based materials not only to detect biomolecules, but also the ability to provide a label-free, non-invasive, and non-destructive method for detecting early-stage cancer. This could be an interesting approach for boron-doped diamond in the future. In conclusion, when weighing diamond-based electrodes against biosensors in the detection of biomolecules, there are, in one hand, the practical advantages of the easy-to-produce and easy-to use diamond-based electrodes and, on the other hand, the outstanding ability of biosensors to detect biological molecules of high molecular weight with a lower amount of analyte and very high selectivity. The manufacturing of biosensors requires, however, a sequence of chemical functionalisation steps, which may pose as a disadvantage because of the increased time, cost, and complexity of fabrication. For these reasons, the choice between a diamond-based electrode and a biosensor depends on several issues: the size, charge, and solution mobility of the target molecule; the amount of analyte; the intended type of detection; the intended selectivity and the time and money for fabrication. This review was written through the equal contribution of all authors. We acknowledge University of Aveiro and FCT/MCTES (Fundacao para a Ciencia e a Tecnologia, Ministerio da Ciencia, da Tecnologia e do Ensino Superior) for financial support to LAQV-REQUIMTE (Ref. UIDB/50006/2020), and to CIECO--Aveiro Institute of Materials (Refs. UIDB/50011/2020, UIDP/50011/2020 & LA/P/0006/2020) through national founds (PID-DAC) and, where applicable, co-financed by the European Regional Development Fund (FEDER), within the PT2020 Partnership Agreement. The work of Instituto de Telecomunicacoes is funded by FCT/MCTES through national funds and when applicable co-funded EU funds under the project UIDB/50008/2020-UIDP/50008/2020. The research contract of FF (REF-168-89-ARH/2018) is funded by national funds (OE), through FCT, in the scope of the framework contract foreseen in Nos. 4, 5 and 6 of article 23 of the Decree-Law 57/2016, of 29 August, changed by Law 57/2017, of 19 July. The authors declare no conflict of interest.
## 3 Materials and Methodology  
### Construction of the Physical Analog Model  
The backfill working face belongs to the coal seam 5 th and has a strike length of 652 m. A physical analog model was built according to the geological and mining conditions of the backfill working face, with dimensions of 2.5 m \(\times\) 0.3 m \(\times\) 1.5 m (length \(\times\) width \(\times\) height). The monitoring system's layout and its multiple mechanical parameters are shown in Figure 3. The backfill working face contains a total of 23 strata. The floor stratum is 13 m thick; the coal seam is 2.5 m thick; and the overburden strata are 134.5 m thick. The thickness of each layer in the model was determined based on rock sample tests and simple measurements of the corresponding actual geological layers. The model's geometric similarity ratio (Cl) was adjusted to 100:1, the movement similarity ratio to 10:1, the stress similarity ratio to 166.7:1, the volumetric weight similarity ratio (Cr) to 1.667:1, and the mass similarity ratio to 1.667 \(\times\) 106:1. The model's stress compression was calculated to be 0.10 MPa based on the stress-to-overlying strata height similarity ratio under simulation. In the physical analog model, stress compression refers to the use of a pneumatic cylinder to apply a stress similarity ratio to the top of the model to compress for insufficient stress when the strata model is below ground level. The mechanical properties and the proportions of the materials used for the physical similarity model are shown in Tables 3 and 4. On site, the daily advancement of mining is 5 m, with two shifts of 8 h for coal mining and 8 h for maintenance. Since the similarity ratio of movement in the physical analog model was determined to be 10:1 and the advanced distance of the working face in the model was 190 cm, the excavation step of the working face in the model was 5 cm every 96 min. After taking 38 steps, about 3648 min in total, the model was completely mined.  
Figure 3: Monitoring system’s layout and its multiple mechanical parameters.
## 3 Structure and Function of Alternative \(\bullet\) Factors
### Group 3 \(\bullet\) Factors  
Members of this group are structurally and functionally diverse, but usually contain \(\sigma_{2}\), \(\sigma_{3}\) and \(\sigma_{4}\) domains. The \(-\)10 and \(-\)35 elements are varied among members and distinct from those recognised by Groups 1 and 2, although the presence of \(\sigma_{3}\) correlates with the recognition of extended \(-\)10 elements in some cases [40,41]. They fall into at least four phylogenetically-distinct subgroups that partially correlate with function: flagellum biosynthesis, heat shock response, general stress, and sporulation [11,42]. (1) The expression of \"late\" genes involved in flagellum biosynthesis is controlled by \(\bullet\) factors closely related to _E. coli_\(\circ^{28}\) (FliA) in all motile Gram-negative and Gram-positive bacteria, making this the most widely distributed alternative \(\bullet\) factor. Indeed, the _B. subtilis_ orthologue \(\sigma^{\rm D}\) can complement an _E. coli filA_ mutant, highlighting conservation in promoter recognition as well as function [43]. Closely related paralogues are also found in non-motile bacteria including _Streptomyces_ (\(\sigma^{\mathrm{WhiG}}\)) where it is required for sporulation [44] and the obligate intracellular parasite _Chlamydia trachomatis_ where it is developmentally regulated [45]. (2) In \(\alpha\)- and \(\gamma\)-proteobacteria, the response to the accumulation of unfolded proteins in the cytoplasm caused by heat shock and other stresses is controlled by \(\sigma\) factors related to _E. coli_\(\sigma^{32}\). (3) In Gram-positive bacteria, the general stress response is controlled by \(\sigma\) factors related to _B. subtilis_\(\sigma^{\mathrm{B}}\). In _B. subtilis_, \(\sigma^{\mathrm{B}}\) controls almost 200 genes in response to a wide range of challenges including environmental stressors such as ethanol, osmotic stress, and nitric oxide, as well as energy-related stresses such as ATP depletion [46, 47]. Although most organisms have a single \(\sigma^{\mathrm{B}}\)-like protein, up to 9 paralogues are present in _Streptomyces_ that are involved in both stress responses and development [48, 49, 50]. (4) Endospore formation in _B. subtilis_ is driven by four related compartment-specific Group 3 \(\sigma\) factors (\(\sigma^{\mathrm{F}}\), \(\sigma^{\mathrm{E}}\), \(\sigma^{\mathrm{G}}\), \(\sigma^{\mathrm{K}}\)). At an early stage of sporulation, asymmetric cell division forms a pre-spore compartment that is ultimately engulfed by the \"mother cell\". The activation of \(\sigma^{\mathrm{F}}\) in the pre-spore triggers a criss-cross signalling cascade that results in the sequential activation of \(\sigma^{\mathrm{E}}\) (mother cell), \(\sigma^{\mathrm{G}}\) (pre-spore), and \(\sigma^{\mathrm{K}}\) (mother cell) [51].
# A Dynamic Framework for Community-Facility Siting with Inter-Community Competition
## 3 Model Development
### Mathematical Model
#### 3.2.2 Objective 2: Maximize Service Efficiency  
In this study, we employed the service supply rate (SSR) to evaluate service efficiency. The SSR represents the ratio of the total service supply provided by all community facilities located to the total service demand within  
We adopted the Gaussian function to calculate the distance attenuation factor \(w_{ij}\), as it can reflect the distance attenuation effect more accurately and has been widely used in the literature to capture the impact of distance on demand [68; 69]. The Gaussian function is expressed as follows:  
\[w_{ij}=\left\{\begin{array}{cc}(e^{-(\frac{1}{2})\times\left(\frac{d_{ij}}{d_{0 }}\right)^{2}}-e^{-(\frac{1}{2})})\Big{/}(1-e^{-(\frac{1}{2})})&\left(d_{ij} \leq d_{0}\right)\\ 0&\left(d_{ij}>d_{0}\right)\end{array}\right. \tag{3}\]  
It should be considered that, in practice, community facilities should be accessible to all residents nearby. This means that within the service threshold distance, the demand point \(i\) receives a service that may come from multiple facility points. Thus, in period \(t\), the amount of service received for a single demand point \(S_{i}^{t}\) is as follows:  
\[S_{i}^{t}=\sum_{j\in J}D_{i}w_{ij}x_{ij}^{t} \tag{4}\]  
Then, the objective of maximizing service efficiency in period \(t\) can be expressed as follows:  
\[\max f_{2}=\sum_{i\in I}\sum_{j\in J}D_{i}w_{ij}x_{ij}^{t}\Big{/}\sum_{i\in I}D _{i} \tag{5}\]  
Constraints:  
\[\sum_{j\in J}y_{j\in}^{t}=p^{t}\forall c\in C,t\in T, \tag{6}\]  
\[\sum_{c\in C}y_{j\in}^{t}\leq 1,iff^{t}<q\forall j\in j,t\in T, \tag{7}\]  
\[\sum_{c\in C}y_{j\in}^{t}=1,iff^{t}=q\forall j\in j,t\in T,\