esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Numerical Analysis
### Benchmarking Numerical Predictions with Test Results  
Detailed comparisons of numerical results with experimental results for the maximum permanent local denting damages (\(d\)) are presented in Table 4 and Figure 3. It should be noted that the permanent local denting (\(d\)) value was non-dimensionalized with the radius of each model. In both table and figure, the bias \(X_{m}\) (modelling uncertainty factor) is also provided, which is the ratio of numerical results over the test results. Generally, the \(X_{m}\) values for all models are close to unity. The mean of the modelling uncertainty factor (\(X_{m}\)) is 1.038 and a quite small coefficient of variation (COV) with 2.98%. These values are shown to exhibit reasonable accuracy of the collision analysis method. Furthermore, the predicted deformed shapes of non-linear finite element analysis and test results are compared for models SS-C-1 and RS-C-1 as indicated in Figure 4. A good agreement of deformed shape is obtained between the numerical results and the test results. Additionally, the numerically predicted longitudinal damage shapes are compared with the measured values in Figure 5. The damage spreads in the longitudinal direction when the flattened part is tilted with a small degree of rotation outward.  
Figure 2: True stress-strain curve applied in FE analysis for RS-C-3 model.  
Figure 4: Comparisons of the test results with numerical predictions: (**a**) model SS-C-1; (**b**) model RS-C-1.  
Figure 5: Comparison of the longitudinal damage profiles obtained from experimental and numerical prediction: (**a**) model RS-C-1; (**b**) model RS-C-2.
## 4 Validation by Numerical Simulation and Results  
### Modeling of the Net Protection System  
The effects of the developed brake frame on the net protection system were numerically validated through ABAQUS Explicit using a specific case in which a spherical impact block of 400 kg mass and 1 m diameter was rolled down a slope at an angle of 54.34\({}^{\circ}\), as shown in Figure 10. The slope and the impact block were modelled as rigid bodies. The height and width of slope were modelled as 20 m and 14.35 m, respectively. The impact energy was assessed to be 30 kJ based on the potential energy related to the height of 7.65 m. The distance between the base of the slope and the net protection system was set as 0.25 m. Factors like height and velocity of the impact block while rolling are shown in Figure 11. The coefficient of friction of the slope was 0.60 and the speed of impact block just before the impact was measured as 10 m/s. The net protection system was assembled using horizontal and vertical wire ropes crossing over each other. A total of seven wire ropes were installed horizontally and twelve wire ropes were installed vertically, both at a distance of 0.5 m between each other. The wire rope was modelled as a two-noded linear 3-D truss element (T3D2), and the spacing between the individual elements was set as 25 mm. The number of elements constituting the wire rope without and with a brake frame were 3176 and 3260, respectively. The physical properties and the sectional area for the modeling of wire rope were used the same as in Section 3.1. There were no specific boundary conditions applied to the twelve vertical wire ropes and their only role was to prevent the horizontal wire ropes from breaking away due to the impact. The seven horizontal wire ropes were designed to withstand the impact due to the hinged boundary conditions at both ends of horizontal wire ropes. Further, the assembly was then analyzed by attaching brake frames to the seven horizontal wire ropes and a comparison was made between the results obtained by modeling the horizontal wire ropes with and without installing brake frames. In the numerical simulation, the brake frames were applied at the center of the horizontal wire ropes only, as shown in Figure 10b, and the proposed equivalent model explained in Section 3.3 was applied afterwards. In order to facilitate the contact condition of impact block with the equivalent model, the 0.3 m length of brake frame installed in each of the horizontal wire rope was divided in two parts which were connected to each other through a series of spring connections. The impact force was observed to be following the force-displacement relationship in Table 2, causing half of the displacement because the brake frame was divided in two parts.  
Figure 10: Numerical models with and without using brake frames, (**a**) without brake frame; and (**b**) with brake frame.
# Accurate Collaborative Globally-Referenced Digital Mapping with Standard GNSS
## 4 Globally-Referenced Electro-Optical SLAM (GEOSLAM)
### GNSS Aiding  
Conventional visual SLAM algorithms are known to drift from the true platform trajectory as a function of the distance traveled by the platform. Furthermore, the map of the structure is created in the arbitrary \(\mathcal{S}\) frame. Such a map cannot be intelligibly shared with another mapping agent having a different \(\mathcal{S}\) frame. Meanwhile, GNSS position estimates are obtained in the global \(\mathcal{G}\) frame and do not exhibit any distance-dependent drift. Accordingly, GEOSLAM ingests standard GNSS position estimates from a software-defined GNSS receiver, called GRID/pprx [6; 61], in a tightly-coupled architecture to create a globally-referenced map, enable cooperative multi-session mapping, and constrain the drift of visual SLAM. Since the stereo camera setup is triggered by the same clock that drives digitization of the GNSS samples (see Figure 7), it is possible to produce GNSS measurements synchronized with the camera image epochs. This section details the various coordinate frames in GNSS-aided visual SLAM, the updated BA cost function, and an initialization routine required to enable GNSS aiding in SLAM.
## 3 Results and Discussion
### Vegetation Indices
#### 3.3.3 Accuracy of VIs Models  
The most accurate results are shown by the NDAF VI model, while all other models show significantly lower accuracy (Figure 14).  
The NDAF VI models are often used in many studies involving canopies extraction of different types of vegetation. In [70], the NDAF VI model is used for predicting grain yield in rice, while in [71] it is used for detecting spatial and temporal variations in soybean  
Figure 14: ROC curves and AUC values for VIs models.  
Figure 13: VIs classified models: (**a**) NDVI; (**b**) NDAF; (**c**) GNDVI; (**d**) MCARI2; (**e**) RDVI2.  
crops. Many authors such as [13; 40; 72] used NDRE as the main VIs model in their studies related to the olive-growing sector. On the other hand, the most used VI for the purpose, the NDVI model [73; 74; 75], is showing the least accurate results in this study.
## 8 Accuracy and Error Measures for Predictive Models  
### Relationship between Observed, Predicted, and True Values  
Predictive accuracy is about the differences between observed and predicted values that are derived based on validation methods [18]. However, it is often questioned what the differences between the predicted values and true values are. Since the true values are mostly unknown, the observed values are used to validate predictive models. For an observed value, it may be again different from its corresponding true value. The difference between the true value and observed value is the error associated with the observed value. Let us refer to this error as an observational error that is the sum of random error associated with observed variable, sampling error, and measuring error. The sampling and measuring errors are the sum of errors resulting from various factors that may affect the accuracy of observation (i.e., measurement) and change with the variable observed. Let us take seabed sediment as an example; the factors may include sampling design, the position accuracy of survey vessel, equipment used for sample collection, field operation, sample storage, sample processing procedure and analysis in laboratory, data entry, etc. However, how much error can be attributed to each of these factors is unknown in most cases. Hence, we have to use observed and predicted values to assess the predictive accuracy in practice.
## 3 Results
### Thermogravimetric Analysis (TGA)  
Thermogravimetric analysis was used to investigate the thermal degradation through the weight loss of the films over a temperature range. The maximum degradation temperatures of the films were analyzed. The onset temperature, T\({}_{10\%}\) (the temperature at 10% mass loss), second derivative peak temperature, T\({}_{\text{max}}\) (maximum decomposition temperature), and the residual mass at 550 \({}^{\circ}\)C for all the samples are reported in Table 2.  
The trend was identical in both cases, and Figure 9 illustrates the three stages of thermal decomposition. The evaporation of moisture in the samples caused the first thermal event, which was a weight loss of up to 1.79-2.34% at a temperature of 86.38-91.61 \({}^{\circ}\)C. The second thermal event, which is connected to the degradation of the glycerol and pectin included in the films, took place at a temperature of 175.42-237.66 \({}^{\circ}\)C, and the weight reduction was 19.75-26.28% [23]. At a temperature of 303.64-348.31 \({}^{\circ}\)C, the third thermal event was noticed. The degradation of the films revealed a further weight reduction of 16.83-25.91%, which can be attributed to the breakdown of the cellulose and starch [24]. The remaining 20.74-27.35 wt% of the biofilms were found as the residual ash at 550 \({}^{\circ}\)C.  
Figure 9: TGA analysis of OW and GW biofilms.
# Narrowband Internet of Things (NB-IoT):
## 5 Open Research Questions and Discussion
### Cell Search and Initial Synchronization  
NPSS and NSSS are two signals based on frequency domain Zadoff-Chu sequence that are used for NB-IoT time and frequency synchronization to the base station. According to NB-IoT standard, NPSS and NSSS may not be transmitted on the same antenna port hence NB-IoT initial synchronization may rely on NPSS only. The challenge is that the imperfect channel conditions may severely affect the cell camping procedure as a small CFO may result in a phase shift to a received frequency domain sequence which as a consequence may degrade the cell search and synchronization performance. To improve this, frequency diversity techniques should also be used for NPSS and NSSS reception improvement.
## 3 Line-Scan Hyperspectral Imaging Instruments
### Major System Components
#### 3.1.3 Image Sensors  
For line-scan hyperspectral systems based on dispersive imaging spectrographs, an image sensor is generally used with one dimension parallel to the wavelength dispersion direction for spectral information collection and the other parallel to the spectrograph entrance slit for spatial information collection. Charge-coupled devices (CCDs) are currently the mainstream image sensors. Spectral responses of the CCDs are mainly governed by the sensor substrate materials. Silicon CCDs have adequate quantum efficiency (QE) in visible and short-wavelength near-infrared (NIR) regions (e.g., 400-1000 nm). Deep depletion CCDs can improve the spectral response toward the red end of the visible region. Indium gallium arsenide (InGaAs) CCDs are the major image sensors used in the NIR region. Standard InGaAs CCDs have fairly flat and high QE in the region of 900-1700 nm. However, by altering the percentages of InAs and GaAs in the sensors, InGaAs CCDs can also be used effectively in SWIR range (i.e., 1000-2500 nm). Detectors working in the MWIR region (i.e., 3000-5000 nm) are also available, such as lead selenide (PbSe), indium antimonide (InSb), and mercury cadmium telluride (MCT). Low-light hyperspectral imaging applications usually need high-performance CCDs, such as electron-multiplying CCDs (EMCCDs) and intensified CCDs (ICCDs). Aside from CCDs, CMOS (complementary metal-oxide-semiconductor) cameras have emerged as alternative image sensors. A CMOS sensor includes both a photodetector and an active readout amplifier in each pixel (called active pixel), making it much faster for signal transfer than the vertical and horizontal registers used by CCDs to shift the electric charges. Hence the CMOS cameras are particularly suitable for high speed hyperspectral imaging applications, such as real-time inspection of food safety and quality on processing lines.
# Signature-Based Security Analysis and Detection of IoT Threats in Advanced Message Queuing Protocol
## 5 Attack Description and Explanation
### Explanation of AMQP Brute Force Attack  
Brute force attacks are a type of cyberattack where unauthorized users attempt to infiltrate a system by repeatedly guessing username and password combinations or uncovering protected information through exhaustive attempts. Attackers often employ various techniques to improve the accuracy of their guesses. Within the AMQP protocol, queue message handling is a vulnerable process that attackers can exploit to gain unauthorized access. By leveraging brute force methods, attackers can obtain the credentials needed to access the system [5].  
**Brutemq**: is a tool designed to brute force RabbitMQ server (AMQP) queue messaging services. The tool works by connecting to a given host on the AMQP port (5672/TCP) and attempting to guess passwords from a predefined list [24].  
**Command for Brutemq Attack**:  
brutemq amqp -d passwords.txt -u admin -e 192.168.10.10:5672 -t 500  
**Explanation of the Command**:  
* -d: Specifies the password list file.
* -u: Indicates the username (e.g., admin).
* -e: Specifies the target host and port.
* -t: Sets the timeout for the attack.
## 2 Data
### OpenStreetMaps and ESA/WorldCover  
Water bodies and built-up areas, which may produce a similar SAR backscatter response to barren land, were masked to limit class confusion using the ESA WorldCover resource [25] and OpenStreetMaps (OSM) data [24]. ESA WorldCover provided insufficient detail on small permanent water bodies, specifically small distributaries, hence 'waterways' from OpenStreetMaps were extracted through the QGIS QuickOSM plugin [26] and re-projected to Sentinel-1 resolution to append finer detail to the mask. For built-up areas, a thresholded December 2023 Sentinel-2 composite with the Normalised Difference Built-up Index (NDBI) was applied to capture recent urban expansion [27]. Utilising a more recent built-up mask in this way reduces the impact of urban sprawl on the results, ensuring that the majority of urban expansion is not misinterpreted as pollution-induced deforestation.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Data** & **Resolution** & **Revisit Time** & **Date Range** & **Source** \\ \hline Sentinel-1 Synthetic Aperture Radar Ground Range Detected & 10 m & 6 days & 2016–2024 & [23] \\ Sentinel-2 MSI: MultiSpectral Instrument, Level-2A & 10 m & 5 days & 2018–2023 & [23] \\ ESA WorldCover 10 m v200 & 10 m & - & 2021–2022 & [23] \\ FAO GAUL: Global Unit Layers, Second-Level & - & - & 2015 & [23] \\ Administrative Units & - & - & - & [24] \\ OpenStreetMaps Vector Data & - & - & 2006–2024 & [14] \\ NOSDRA Oil Spill Incident Data & - & - & 2006–2024 & [14] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Datasets used in this work, including (as appropriate) the spatial resolution of the mapped products, their associated temporal baselines, and the source in each case.  
Figure 1: ESA land-use and land-cover map of the region of interest on panel one, with Bille, Bonny Island, and Port Harcourt labelled and pipeline infrastructure overlaid for reference. In the second panel is the FAO GAUL global administrative sub-state boundaries map of Nigeria, where the region of interest is outlined in red.  
Additional vector data, including the pipeline infrastructure, oil refineries and terminals, and industrial zones, were obtained from OSM to support our analysis (Table 1).
## 8 Discussion
### Technology Readiness Assessment  
Interestingly, we have identified a distinct increase in academic research of CLC within C-ITSs (see Figure 4), but the TRL is still below onsite proof-of-concept implementations. Simultaneously, there is a need for understanding the cryptography part of CLC in the industry, combined with--as elaborated by interviewee [PERSON] and [PERSON]--a desire to have clear proofs as to why such technology would be more beneficial than traditional PKI. Since standardization bodies are inclined to default to PKI, that seems to be a strong barrier for the industry to be convinced and spend resources to evaluate new security controls. To conclude: the current level of TRL for CLC in the domain of C-ITSs is low, where our qualitative study indicates a knowledge gap (specifically cryptography) in the industry and the literature analysis indicates a lack of proof-of-concept implementations that can be used for better buy-in of the industry. The identified gaps for CLC in C-ITSs is, then, hindering the field to be mature enough for adoption in the current state of industry and academia.
## 4 Proposal
### Image Transmission Function  
The _image transmission function_ sends the captured images to the _SEMAR_ server in _base64_ format [45]. The proposed approach utilizes the _sign image_ captured from the surrounding environment during navigation to reset the user's location when encountering loss of direction errors. The image is captured through the phone's camera when the user presses the rescan button. The image size is defined at \(480\times 480\) pixels to ensure a small size while retaining image quality. The image is then encoded into base64 format and sent to the _SEMAR_ server through the _Utility Web Request_. It handles all external communication between _INSUS_ and the _SEMAR_ server via HTTP through a REST API service using a POST request. Since this communication only allows text-based data transmission, the base64 format encodes the binary data of the image into text, ensuring the efficient transmission of image data.
# Proximate Composition and Antioxidant Activity of Selected Morphological Parts of Herbs
###### Abstract  
The aim of the study was to provide an analytical evaluation of the proximate composition, the total content of polyphenolic compounds and the antioxidant activity, of 27 selected plant materials collected in Poland (West Pomeranian). The basic chemical composition was determined in the ground samples according to the Association of Official Analytical Chemists methods. Antioxidant activity was tested using free radical methods ABTS**, DPPH** and the FRAP method. The lowest concentration of dry matter (DM) was measured in black chokeberry (88.82 g/100 g) and the highest was found in milk thistle (94.65 g/100 g) as well as black cumin (95.09 g/100 g). The content of total polyphenols, assessed using the Folin-Cicocalteu method, ranged from 291.832-7565.426 mg of chlorogenic acid equivalent (CGA)/100 g of DM. Antioxidant activity measured sequentially against the radical ABTS**, DPPH** and using the FRAP method was 26.334-1912.016 uM Trolox/g DM, 9.475-1061.068 uM Trolox/g DM and 26.252-1679.766 uM Trolox/g DM, respectively. The methanolic extract from milk thistle fruit in most assays was characterized by the lowest antioxidant activity and the lowest total content of polyphenolic compounds. Methanol extracts prepared from garlic, stinging nettle and cleaves showed the highest content of total polyphenols and antioxidant activity among the tested plant materials. The parts of plants with the highest antioxidant potential can be a source of new bioactive compounds, but further research is required to describe the profile of compounds harmful to human health.  
antioxidant activity; botanicals; herbs; polyphenols; principal component analysis (PCA); proximate composition +
Footnote †: journal: Medical Physics
## 4 Materials and Method
### Interpretation of the Aeromagnetic and Airborne Gravity  
The airborne gravity and aeromagnetic data are interpreted in this study with the aim to delineate the structural trends (fault/lineaments) at different depths range (Figure 4). The interpretation for both airborne gravity and aeromagnetic data are calibrated with the seismic profiles and wells that intercept the area (Figure 1C). All selected datasets (Table 1) were filtered with continuity and apparent susceptibility filters. Anomalies maps are then smoothed through kriging technique to reduce the irregularities and craggy look on the maps. These were performed in Geosoft Oasis Montaj Software.  
The interpretation begins with detecting the magnetic anomalies and marking the structural trends on magnetic anomalies maps, which include the TMI_RTE, TMI_RTE_1 vd, and RTE_AS_20 res/50 res/20 reg/50 reg. The geometry of the magnetic bodies was observed and recorded. Potential changes in the magnetic anomalies in the maps were marked with straight to curvy lines, following the shapes of the magnetic bodies. Similar procedures were performed on the gravity data which include the Tz, Tzz, Txz, Tyz and CLP data (CLP_short/intermediate/long wavelengths). The interpreted structural lines (lineaments) on all magnetic and gravity maps were then compared through overlay and side-to-side comparison to get the general trends from the data.  
All measured strikes directions were recorded and plotted in separate rose diagrams (GeoRose by [50] to illustrate the structural trends from each anomaly map. Strikers measured on aeromagnetic data and Z-tensors were compared with the existing structural maps available for Central Luconia by [51,52].
## 2 Results and Discussion  
### Hydrogel Preparation and Characterization  
Hydrogels were obtained in a three-step method through the reaction of isocyanate-terminated polyurethane (PU) prepolymer and CHT (CHT-HDI-DEG-PTHF-CL-PEG-DEG)(Figure 1). Similar biomaterials were obtained as described in our previous work but using different substrates [11].  
In the first step, CL-PEG copolymers were synthesized via the enzyme ring-opening polymerization process (e-ROP) (Table 1). As is commonly known, the ROP of cyclic esters is generally carried out in the presence of metal-containing catalysts. This may pose some toxicological risks and thus reduce the biosafety of using the obtained biomaterial. Therefore, we decided to use the enzyme as a biocatalyst of the ROP process. The obtained  
Figure 1: Scheme of the hydrogel CHT-HDI-DEG-PTHF-CL-PEG-DEG synthesis.  
polyesters did not require additional purification before being used to synthesize prepolymers and hydrogels. Moreover, the hydrolytic purification process leads to a reduction in the average molar mass of the obtained polyesters. Our goal was to obtain oligomers with a number average molar mass (\(M_{n}\)) in the range of 3000-3500 g/mol. Based on the preliminary research, it was found that this is the optimal molar mass for oligomers used for the synthesis of CHT-PU hydrogels. The molar ratio of CL to PEG was 30:1, 40:1, 50:1, or 60:1. The enzyme ring-opening polymerization e-ROP of CL and PEG was carried out in the presence of immobilized lipase B from _Candida antarctica_ (CA). The synthesized copolymers were characterized by \(M_{n}\) = 2400-3600 g/mol. The reaction yields ranged from 71.0 to 92.0%.  
After that, the CL-PEG C copolymer was used as a raw material for the hydrogel synthesis because it was characterized by the optimal molar mass and the lowest \(D\) value.  
The prepolymers of HDI, CL-PEG copolymer, PTHF, and DEG were obtained in the second step. In the final step, CHT-HDI-DEG-PTHF-CL-PEG-DEG hydrogels were prepared. The prepolymers were obtained in the polyaddition process of HDI, CL-PEG copolymer, PTHF, and DEG in a molar ratio of 2.1:0.7:0.2:0.1. Finally, the hydrogel was reacted with CHT in an NCO (prepolymer)/OH (or NH\({}_{2}\)) (CHT) ratio of 1.65:1 at 80.0 \({}^{\circ}\)C for 4 h under an argon atmosphere. Dibutyltin dilaurate (DBDLSn) was used as a polydtition catalyst.  
The obtained hydrogels had the form of white or gray, flexible solids. Their structure was stable at room temperature. The swelling capacity of the obtained CHT-HDI-DEG-PTHF-CL-PEG-DEG hydrogel was determined. The value of the coefficient of the mass swelling ratio (MSR) was 384.0, 445.0, 492.0, and 509.0% after 2 h, 4 h, 8 h, and 24 h, respectively.