esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results and Discussions
### Validation Using Research Reactor  
In this experiment, we validated linearity using the UTR-KINKI Research Reactor designed and produced by the American Standard Corporation (Mountain View, CA, USA) [19] at Kindai University, with the FC as a neutron detector. The configuration of the experiment is shown in Figure 10. The reference signal for a true count rate to be compared with FPGA outputs was measured using the Amptek (Bedford, MA, USA) Digital Multichannel Analyzer MCA-8000D.  
Figure 8: FPGA output for emulator output.  
Figure 9: Response characteristics of the developed algorithm.  
The result of linearity is shown in Figure 11. FPGA outputs are within \(\pm\)2% of the span. The result satisfies the requirement mentioned in Section 3.1, indicating that the proposed algorithm demonstrates good linearity performance. However, for a reactor power of 0.01 W, there is a difference between the FPGA output and MCA output. We suspect that this is due to the limited number of time constants available in the count-rate converter because the number of time constants in \(10^{3}\) from \(10^{6}\) cps is lower than the rest of the range. To investigate this hypothesis, we created a simulation model using MATLAB (R2023a) Simulink and added one additional time constant in the range of \(10^{4}\) to \(10^{5}\) cps. We then conducted verification using this simulation model. Figure 11 shows the results of comparing the original algorithm with the improved algorithm using the simulation model created in MATLAB Simulink. The results of the original algorithm align well with the verification results using the research reactor, confirming the validity of the simulation model. Furthermore, the results of the improved algorithm align well with the values obtained from the MCA-8000D at 0.01 W, demonstrating that the addition of time constants can improve linearity.  
Figure 10: Experimental configuration with UTR-KINKI Research Reactor.
# Resistance to Cybersecurity Attacks in a Novel Network for Autonomous Vehicles
## 2 Related Work
### Security in Opportunistic Networks  
Where technology is used, security is always a key consideration. When safety is dependent upon the technology, security is of the utmost importance. Given that in the use of VANETs the network will have an impact upon many vehicles (each made from tonnes of metal) there is an opportunity for a vast amount of damage to be caused to other individuals and bystanders. Due to the open-access nature of a VANET, they are vulnerable to multiple forms of attack that must be defended against [15].  
A proven low-cost hardware (Raspberry Pi) method for dealing with faulty nodes is to use a multi-layered approach that allows all devices in a complex network to be self-organised and provide self-adaptive routing algorithms [16]. This could be used to improve resiliency to cybersecurity attacks as an attacking node is equivalent to a node with a deliberate fault.  
One method of increasing the security of a MANET is using a reputation-based mechanism [17]. In such a network, every node collects reputation information from neighbouring nodes and gathers indirect reputations from other nodes. These get updated with each interaction so that a given node's reputation is as up-to-date as possible [18].  
In order to provide resilience to Black Hole Attacks another proposed method is isolating the nodes from the network entirely. This can be done by holding a master routing table with trusted routes stored [19]. One problem with this is that once it is isolated it would never receive a message again, even if the malfunctioning node began to function again.  
Blockchain technologies have recently become popular methods to decentralise and provide smart contracts for greater security in novel networks [20]. A number of key elements make up the technologies: Decentralisation, Transparency, Open Source, Autonomy Immutability and Anonymity [21]. All these factors combined provide a network without fixed infrastructure with a method of remaining secure [22]. It has been proved that such technologies can be used within opportunistic networks [23]. In the proposed method however, two nodes meeting causes their chains to be merged creating a theoretically infinitely long chain.
# A Systematic Literature Review of Various Control Techniques for Active Seat Suspension Systems
## 8 Control Methods Used in the Active Seating Suspension System
### PID Controller  
PID controller is a simple and reliable controller, which is commonly used in many industrial applications due to its flexibility [97]. The standard form of PID control can be represented as  
\[u=k_{p}\;e(t)+k_{I}\;\int_{0}^{t}e(\tau)\;d(\tau)+k_{d}\frac{de(t)}{d(t)}, \tag{8}\]  
where \(u\) is the actuating control force, \(e\) is the error difference between the output and input defined as \(e(t)=y(t)-x(t)\). \(k_{p}\), \(k_{I}\) and \(k_{d}\) are proportional, integral and derivative control parameters of the controller.  
PID controller was used to reduce the vertical and pitch accelerations for active seat suspension associated with the state variable feedback controller for precise displacement and velocity control through the actuator [51]. The state feedback was proposed to eliminate the overshot caused by the actuator with a PID controller. Generally, PID is integrated with various control methods either to reduce the overshot of the plant or to speed up the control system.
## 2 Channel Propagation Characteristics  
Wireless communication systems heavily rely on understanding channel propagation characteristics for efficient signal transmission and reception. This section focuses on exploring the characteristics of the mid-band and high-band frequency spectrum, as these frequency ranges have gained significant importance in meeting the ever-growing demand for higher data rates and expanded network coverage. This understanding will aid in developing effective strategies for channel modeling, system design, and performance optimization [13].
# LLM-Based Cyberattack Detection Using Network Flow Statistics
###### Abstract  
Cybersecurity is a growing area of research due to the constantly emerging new types of cyberthreats. Tools and techniques exist to keep systems secure against certain known types of cyberattacks, but are insufficient for others that have recently appeared. Therefore, research is needed to design new strategies to deal with new types of cyberattacks as they arise. Existing tools that harness artificial intelligence techniques mainly use artificial neural networks designed from scratch. In this paper, we present a novel approach for cyberattack detection using an encoder-decoder pre-trained Large Language Model (T5), fine-tuned to adapt its classification scheme for the detection of cyberattacks. Our system is anomaly-based and takes statistics of already finished network flows as input. This work makes significant contributions by introducing a novel methodology for adapting its original task from natural language processing to cybersecurity, achieved by transforming numerical network flow features into a unique abstract artificial language for the model input. We validated the robustness of our detection system across three datasets using undersampling. Our model achieved consistently high performance across all evaluated datasets. Specifically, for the CIC-IDS-2017 dataset, we obtained an accuracy, precision, recall, and F-score of more than 99.94%. For CSE-CIC-IDS-2018, these metrics exceeded 99.84%, and for BCCC-CIC-IDS-2017, they were all above 99.90%. These results collectively demonstrate superior performance for cyberattack detection, while maintaining highly competitive false-positive rates and false-negative rates. This efficacy is achieved by relying exclusively on real-world network flow statistics, without the need for synthetic data generation.  
large language model; machine learning; fine-tuning; deep learning; cybersecurity; network security; cyberthreat; attack detection; multiclass classification; attack classification +
Footnote †: journal: Applied sciences  
Article
## 3 Discussion
### Electron Microscopy Analysis  
#### 3.4.1 SEM-EDS Observations of Geogrids  
SEM analyses were performed with an attached EDS probe to detect the presence of different elements in the top coating of the aged geogrids. EDS spectra were taken from selected (rectangular) areas of the samples.  
Figure 10 reveals the presence of mainly SiO\({}_{2}\) (sand) and Al\({}_{2}\)O\({}_{3}\) (bauxite) and a minor contribution of other elements, such as iron, potassium, magnesium, sodium, calcium, and barium. These elements occur in the form of oxides, chlorides and sulfates. Table 4 presents the composition of elements in the coating layer of aged geogrids (% \(w/w\)).  
Figure 10: _Cont._  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Sample** & \(\Delta H\)**(J/g)** & \(T_{\text{m}}\)**(\({}^{\circ}\)C)** & \(\Delta H_{\text{o}}\)**(J/g)** & \(W_{\text{k}}\)**(\%)** \\ \hline HDPEV\({}_{1}\) & 153.3 & 131.15 & 293 & 52 \\ HDPEV\({}_{2}\) & 154.1 & 130.13 & 293 & 52 \\ HDPER\({}_{1}\) & 178.8 & 129.77 & 293 & 60 \\ HDPER\({}_{2}\) & 184.1 & 130.22 & 293 & 62 \\ HDPER\({}_{3}\) & 174.7 & 129.70 & 293 & 59 \\ HDPER\({}_{4}\) & 185.0 & 129.60 & 293 & 62 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Differential scanning calorimetry (DSC) results for new (virgin-V) geogrid samples and aged (Radiowo-R) geogrid samples. \(\Delta H\): melting enthalpy; \(T_{\text{m}}\): melting point; \(W_{\text{k}}\): degree of crystallinity.  
Figure 10: Scanning electron microscopy (SEM) and energy dispersive spectrometer (EDS) analysis for the coatings in the geogrid samples 1 (**a**), 2 (**b**), 3 (**c**).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Characteristic** & **Elemental** & **Elemental** & **Elemental** \\
**Elements** & **Percentage (\%) (a)** & **Percentage (\%) (b)** & **Percentage (\%) (c)** \\ \hline Ba & - & 50.31 & \\ O & 3.69 & 28.01 & 44.37 \\ Na & 38.10 & 1.27 & 1.92 \\ Mg & 0.32 & 1.08 & 5.12 \\ Al & 1.31 & 1.57 & 8.77 \\ Si & 3.13 & 2.97 & 18.40 \\ P & - & 0.07 & 0.29 \\ S & 0.31 & 11.68 & 2.44 \\ Cl & 51.55 & 0.41 & 2.80 \\ K & 0.46 & 0.43 & 2.91 \\ Ca & 0.27 & 0.64 & 2.17 \\ Ti & - & - & 1.04 \\ Mn & - & - & 0.27 \\ Fe & 0.86 & 1.49 & 6.60 \\ Cu & - & - & 1.11 \\ Zn & - & - & 1.78 \\ Cd & - & 0.06 & - \\ TOTAL & 100 & 100 & 100 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Percentage of elements in the coating layer of the geogrids.
# Evaluation of Survivability of the Automatically Obfuscated Android Malware
## 3 Results  
### Findings: Obfuscation Strategies  
Table 7 shows how different types of obfuscation have a varying impact on the malware detection ratio. The original dataset was obfuscated using Obfuscapk with varying levels  
of obfuscation methods as described in Table 5 in the previous section. The outcome of the experiments indicated that the detection rate of VirusTotal for the original set of malicious applications was 91%. This detection rate dropped to 71% on altered apps where the Medium obfuscation strategy was used. It dropped further to 66% on obfuscated apps when the Encryption strategy was used, and to 65% when the High obfuscation strategy was used. It was also observed that the Low obfuscation strategy had less of an impact on malware detection.  
Another noticeable outcome derived in this work was that the impact of trivial and non-trivial obfuscation techniques had almost similar detection rates. A counterintuitive conclusion that can be derived by considering an Android APK is that an archive with a large number of files and a malicious component can be found almost anywhere, and it is not possible to determine which of the above-mentioned techniques should be used if automated obfuscation is applied.
# Open-Bite Correction Using a Mid-Palatal TAD with an Intrusion TPA: Anteroposterior Position of TAD
## 4 Discussion  
### Advantages of a Mid-Palatal TAD for the Maximilary Molar Intrusion  
The mid-palatal TAD has several advantages over buccal interradicular ones [11; 12].  
The failure rate of a mid-palatal TAD is very low because the mid-palatal bone is a dense cortical bone, and its thickness is enough to provide stable anchorage throughout the intrusion procedure [14; 15; 16].  
Clinicians can place a TAD in the mid-palatal area without the root trauma. The buccal interradicular spaces between the maxillary first and second molars are frequently too narrow to place a TAD safely. In the authors' experience, even though buccal TADs were placed well in the buccal interradicular septal bone, they frequently failed as the molars were intruded, with the TADs becoming closer to the alveolar crest and periodontal ligament [15; 17; 18]. The stability of buccal interradicular TADs is compromised when the implants are close to the alveolar crest and into the periodontal ligament [19; 20].  
The buccal TADs should be placed in an attached gingva because, if the TADs are placed in the nonkeratinized movable gingva, irritation, ulcer, or granulation tissue will happen around it. The TAD position should be high enough to get an intruding force with a long range of action. However, in many cases, the buccal attached gingva in the maxillary first and second molar area is not wide enough to place TADs high. Conclusively, it is hard to find a good indication for the buccal TADs between the first and second molars.  
When it is impossible to use the buccal area between the maxillary first and second molar roots, clinicians usually select the location between the maxillary second premolar and first molar as an alternative site. However, in open-bite cases which need a posterior intrusion, the efficiency is decreased, as the lever arm becomes shorter. In this situation, the mid-palatal TAD is a better choice to get a long lever arm by placing it posteriorly.  
A mid-palatal TAD requires only one TAD. Hence, it is more economical.
## 3 Results
### Principal Component Analysis  
Principal Component Analysis (PCA) of the volatile profile of Lemon catnip (Figure 3) revealed that principal components PC1 and PC2 effectively described the chemical variability, with distinct compound loadings. The high positive loading of _cis_-linalool oxide (furanoid) (+4.98% of the total variable, based on correlations) on PC1 indicates its strong association with this axis, suggesting its prominence in samples characterized by oxygenated monoterpenes. Similarly, geraniol (+4.34%) and \(\alpha\)-terpineol (+4.23%) contributed significantly to the PC1 calculation. Negative PC1 loadings, such as nervl acetate and geranyl acetate (both \(-\)6.28% of the total variable, based on correlations), emphasize the influence of esterified compounds with lower polarity, suggesting that these compounds dominate samples with negative PC1 scores. The strong negative contributions of 1,8-cineole (\(-\)4.75%) and caryophyllene oxide (\(-\)5.20%) reinforce this interpretation, placing them in chemically distinct clusters.  
PC2's largest negative loading from borneol (\(-9.69\%\)), followed by linalool (\(-9.60\%\)) and nerol (\(-9.33\%\)), indicates that samples with negative PC2 scores are enriched in monoterpene alcohols with potential floral and herbal notes. In contrast, aldehydes such as geranial (+7.71\(\%\)) and neral (+6.30\(\%\)) dominated the positive PC2 space, suggesting a lemma-like aromatic character. The moderate positive loadings for \(\beta\)-pinene oxide, lavandulol, and 2,6,6-trimethyl-2-cyclohexene-1-methanol (each +2.43\(\%\)) reflect contributions from oxygenated terpen with potential antimicrobial and fragrant properties. This separation along PC2 indicates a distinction between fresh, citrus-dominant, and earthy, alcohol-rich aroma profiles.  
According to the results of the PCA analysis, the multivariate relationships between compounds demonstrate that ester and aldehyde content primarily define inter-sample variation. These results provide a statistically grounded chemical fingerprinting approach for differentiating essential oil chemotypes in Lemon catnip.
## 1 Introduction
More specifically, the SAP particles used were spherical in the submicron range based on poly (methacrylic acid) crosslinked with ethylene glycol dimethacrylate which were synthesized via radical polymerization and later encapsulated with CaO-SiO\({}_{2}\) inorganic shell via the sol-gel method [25; 39]. The incorporation of SAPs in mortars was conducted in two different dosages, 1% and 2% by weight of cement (bwc). The results obtained in this work revealed that the flexural strength improved by 3%, while the compressive strength remained practically intact for the mortar/SAP composite materials compared to the control specimens. Moreover, the total and closed porosity of the mortar/SAPs specimens were reduced by about 0.5% and 2.5% for mortar-SAPs-1 and mortar-SAPs-2, respectively, while self-healing behavior was enhanced for both SAPs concentrations (in the case of mortar-SAPs-1 by 60% and in the case of mortar-SAPs-2 by 10% compared with mortar-reference specimens). The added value of this work resides in the optimization of the SAPs functionality in cementitious-based materials and the improvement of the cementitious materials self-healing properties due to tailored SAPs structure, which are easy to fabricate via the combination of the sol-gel process, radical polymerization and the coprecipitation method. Finally, a new approach for the quantitative evaluation of mortars self-healing behavior was proposed.
# A Novel Liquid-Solid Fluidized Bed of Large-Scale Phase-Changing Sphere for Thermal Energy Storage
## 3 Measurement Instruments and Data Reduction  
### Measurement Instruments and Uncertainty  
The turbine flowmeter has a nominal diameter (DN) of 32 mm and can measure liquid flow between 5 and 45 L/min. The weight method was used for calibration before mounting on the experimental loop, and the uncertainty was determined to be less than 5%. The differential pressure transducer with a capacitive sensor has a measurement range of 0-5 KPa and an uncertainty of less than 2%FS according to the manufacturer. The signal is firstly converted to a current of 4-20 mA and then transmitted to the data recorder. The four T-type thermocouples were calibrated using thermostatic water bath and the error is less than 0.2 K. Both the pressure and temperature signals are recorded with a frequency of 1 Hz.  
During the pre-test, it was found that the temperature difference between the inlet and outlet of the fluidized bed is almost undetectable. This is because the heat-releasing or -absorbing rate during the PCM phase changing is much less than the capacity of the fluid which motivates and fluidizes the spheres. In the following sections, it will be shown that the magnitude of the duration required for a sphere to finish phase changing is around 20 min. The average heat-exchanging rate between the spheres and fluid is thus estimated on the order of 100 W, which only causes a temperature rise less than 0.05 K for the flow rate between 20 and 40 L/min. Therefore, the fluidized bed in the present study is actually a thermostatic water bath with controllable flow stream.  
As a consequence, the heat-storage progression and the PCM status in the spheres cannot be judged through the temperature signals. A new measurement technique based on image processing was proposed as described in the following subsection.
## 4 Fatigue Life Estimation of PC Composite Box Girder Bridge with Corrugated Steel Webs
### Fatigue Life Estimation
#### 4.2.3 Fatigue Calculation Analysis  
When using MIDAS/FEA NX 2022 to establish the finite element model, the main analysis steps are three parts: establishing three-dimensional model, linear static analysis and stress fatigue calculation analysis. Generally, the stress of the model in MIDAS/FEA NX 2022 refers to the Von Mises stress of the analytical model, which can be regarded as a combination of normal stress and shear stress and can also be used to describe the joint action of complex stress states. Usually, we call this stress Van Mises stress. When the material changes, the fourth strength theory, which is the shape change energy theory in material mechanics, is more in line with reality.  
As shown in Figure 31, the maximum Von.Mises stress in the concrete section is 24.22 MPa. As shown in Figure 32, the maximum Von.Mises stress in the web portion of the corrugated steel is 135.74 MPa. The maximum stresses all occur near block 0#.  
Figure 31: Von.Mises stress diagram for concrete section.  
Figure 30: Schematic diagram of loading curve of finite element simulation.  
The fatigue calculation results in the post-processing of MIDAS/FEA NX 2022 finite element analysis mainly include None life, Goodman life and Gerber life. Tables 6 and 7 are the fatigue calculation results of the maximum Von.Mises stress point of the concrete part and the corrugated steel web part, respectively.  
From Tables 6 and 7, it can be concluded that the fatigue life of the maximum Von.Mises stress position of concrete can be regarded as the fatigue life of the PC composite box girder bridge with corrugated steel webs is 705,882 times, and the damage degree is \(1.41\times 10^{-4}\%\).  
The simulation results show that the fatigue life of concrete is much smaller than that of corrugated steel webs, and the maximum stress of corrugated steel webs is much smaller than its design strength, and fatigue failure will not occur. And the maximum stress received by each part is smaller than the allowable stress.
###### Abstract  
The interaction between CO\({}_{2}\) and rock during the process of CO\({}_{2}\) capture and storage was investigated via reactions of CO\({}_{2}\), formation water, and synthetic sandstone cores in a stainless-steel reactor under high pressure and temperature. Numerical modelling was also undertaken, with results consistent with experimental outcomes. Both methods indicate that carbonates such as calcite and dolomite readily dissolve, whereas silicates such as quartz, K-feldspar, and albite do not. Core porosity did not change significantly after CO\({}_{2}\) injection. No new minerals associated with CO\({}_{2}\) injection were observed experimentally, although some quartz and kaolinite precipitated in the numerical modelling. Mineral dissolution is the dominant reaction at the beginning of CO\({}_{2}\) injection. Results of experiments have verified the numerical outcomes, with experimentally derived kinetic parameters making the numerical modelling more reliable. The combination of experimental simulations and numerical modelling provides new insights into CO\({}_{2}\) dissolution mechanisms in high-pressure/temperature reservoirs and improves understanding of geochemical reactions in CO\({}_{2}\)-brine-rock systems, with particular relevance to CO\({}_{2}\) entry of the reservoir.  
Keywords:CO\({}_{2}\) sequestration; physical simulation; Numerical modelling; dissolution; precipitation +
Footnote †: journal: Applied Sciences