esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Adsorption Isotherms of MIPs
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**Sample**} & \multirow{2}{*}{\begin{tabular}{c} \(Q_{\mathrm{e,exp}}\) \\ **(mg g\({}^{-1}\))** \\ \end{tabular} } & \multicolumn{3}{c}{**[PERSON]**} & \multicolumn{3}{c}{**[PERSON]**} \\ \cline{3-8}  & & \begin{tabular}{c} \(Q_{\mathrm{m}}\) \\ **(mg g\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} \(K_{\mathrm{L}}\) \\ **(mg g\({}^{-1}\))** \\ \end{tabular} & \begin{tabular}{c} \(K_{\mathrm{F}}\) \\ **(L mg\({}^{-1}\))** \\ \end{tabular} & \
\begin{tabular}{c} \(K_{\mathrm{F}}\) \\ **(mg g\({}^{-1}\))** \\ \end{tabular} &
\begin{tabular}{c} \(n\) \\ \end{tabular} & \(R^{2}\) \\ \hline MIP1 & 564 & 606.9 & 0.00869 & 0.9527 & 27.54 & 2.751 & 0.9926 \\ NIP1 & 506.5 & 635.3 & 0.00384 & 0.9979 & 49.78 & 2.155 & 0.9838 \\ MIP2 & 120 & 110.6 & 0.02401 & 0.9287 & 27.54 & 4.842 & 0.9984 \\ NIP2 & 42 & 47.37 & 0.00725 & 0.9891 & 6.915 & 3.853 & 0.9357 \\ MIP3 & 61.8 & 69.02 & 0.01661 & 0.9959 & 13.53 & 4.000 & 0.9923 \\ NIP3 & 50.8 & 57.50 & 0.01543 & 0.9943 & 11.15 & 4.013 & 0.9958 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Model fitting parameters from binding isotherm of MIPs and NIPs for gossypol. \(Q_{\rm e}\) (mg g\({}^{-1}\)) and \(C_{\rm e}\) (mg L\({}^{-1}\)) are the equilibrium adsorption capacity and the equilibrium concentration of gossypol, \(Q_{\rm m}\) (mg g\({}^{-1}\)) is the maximum adsorption capacity of the MIP, and KD (mg L\({}^{-1}\)) is the equilibrium dissociation constant. The binding isotherm was used to differentiate recognition sites in terms of their binding ability using the Scatchard model (Figure 5). The Scatchard plot for MIP1 and MIP2 were two lines with different slopes, indicating binding site heterogeneity in MIPs. However, the Scatchard plot for MIP3 was a single straight line, implying that the binding sites in the MIP3 were almost homogeneous. The Scatchard plots for MIP1 and MIP2 contained two different linear regression lines, suggesting two types of binding sites, e.g., higher-affinity and lower-affinity binding sites. Linear regression parameters of the Scatchard plot are summarized in Table 6. As can be seen, the higher-affinity binding sites dominated at a lower concentration range of 200-500 mg L\({}^{-1}\), while the lower-affinity binding sites prevailed at a higher concentration range of 500-2000 mg L\({}^{-1}\). The Q\({}_{\rm max}\) values at higher concentrations were 654 mg g\({}^{-1}\). The experimental Q\({}_{e}\) values at the highest concentration were 564 mg g\({}^{-1}\). Such high binding capacity also demonstrated that the prepared MIP1 had outstanding binding affinity towards the target template gossypol. Figure 5: (**A**) Scatchard plot of MIPs for gossypol; (**B**) Scatchard plot of MIPs for gossypol.
## 2 Contributions of Our Work  
In this work, we explore and demonstrate the potential of UFMC in combining radar jamming and communication. To the best of the authors' knowledge, this is the first series of studies to combine radar jamming and communication through UFMC. In particular, this will be the first work to present the joint radar jamming and communication using UFMC. To that end, we:  
1. Generated UFMC chirp waveforms for the joint function of radar jamming and communication.  
Analyzed the advantages of UFMC in radar jamming and communication joint systems, discussed the constraints of joint waveforms, provided the auxiliary process of joint waveforms for communication subsystems, and provided a design trade-off analysis of radar jamming and communication.
* 3. Conducted simulation experiments; the results indicate that the joint waveform based on UFMC chirp can effectively enable jamming with radar and exhibit excellent communication error rate performance.
* 4. Implemented the proposed method on software defined radio (SDR) devices and demonstrated its feasibility.  
The remaining sections of the paper are organized as follows: Section 3 introduces the configuration of the application scenarios. Section 4 presents the modulation principles of UFMC, compares UFMC with FBMC and OFDM, introduces the waveform design of UFMC chirp, and outlines the processing flow at the transmitting and receiving ends of the joint signal. Section 5 analyzes the constraints and evaluation metrics for the joint signal. Section 6 presents the simulation experiments, validating the feasibility of the proposed method in terms of communication and jamming functionalities. Section 7 presents the feasibility assessment of the proposed joint system using SDR-based hardware implementation. Finally, the research conclusions are summarized in Section 8.
# Recent Advances in Sample Preparation for Cosmetics and Personal Care Products Analysis
## 2 Sample Preparation Strategies for Cosmetics Analysis
### Solid Phase Extraction (SPE)  
SPE is one of the most popular techniques for the extraction of organic compounds from aqueous matrices. SPE allows the isolation of the target analytes from the sample to a solid phase where they are retained. Afterwards, analytes are recovered by elution in a solvent [78]. However, its application to cosmetics analysis usually requires a previous sample pre-treatment, mainly performed by simple dilution in water [42; 45; 50] or an organic solvent such as MeOH to obtain a liquid phase [43; 46]. Undoubtedly, the sorbent selection is critical to obtain a successful SPE method since it plays an important role in the efficiency and analyte selectivity. In recent years, great efforts have been devoted to the development, characterization and application of advanced sorbents to improve analyte selectivity and specificity, with a high sorptive capacity, simultaneously enhancing their physicochemical stability [79; 80].  
Nowadays, a wide range of existing commercial SPE sorbents are based on classical normal phases (silica, alumina), reversed-phases (C18, C8) and ion exchange sorbents [80].  
The commercial reversed-phase water-wettable polymer N-vinylpyrrolidone-DVB sorbent, commonly known as Oasis HLB(r), presents a hydrophilic-lipophilic balance, thus it can be used for acidic, basic and neutral analytes. Oasis HLB(r) has been employed to extract coumarin derivatives from cosmetics [43]. Analysis was performed by LC-MS/MS, obtaining recoveries between 80 and 93% and LODs lower than 20 ng g\({}^{-1}\). Another commercially available mixed-mode cation-exchange reverse phase sorbent, known as Oasis MCX(r), a sulphonic-acid modified cross-linked polystyrene, has been employed for antibiotics determination in cosmetics [42]. The Bond Elut AccuCAT(r) cartridge, consisting of a strong cation exchange (SCX), a strong anion exchange (SAX) and C18 was employed for the isolation of the n-nitrosamine NDELA from cosmetics as well as from triethanolamine (TEA), a commonly used cosmetic raw material frequently contaminated with NDELA. This commercial sorbent showed the highest sensitivity and recovery with the least matrix interferences [44]. The selection of the elution solvent is also a critical parameter. It depends on the analyte properties and on the determination technique. Since several of the target compounds are relatively polar, the use of polar solvents such as water [44] or mixtures of water/methanol [42; 43] has mainly been employed. In most cases, after SPE, evaporation and reconstitution in the mobile phase composition was carried out to concentrate the extracted analytes before LC-MS/MS analysis [42; 43].
# CVE2 ATT&CK: BERT-Based Mapping of CVEs to MITRE ATT&CK Techniques
## 2 Method
### Our Labeled CVE Corpus
#### 2.1.3 Data Augmentation  
The severe data imbalance which characterizes our CVE dataset can potentially degrade the performance of many machine learning models since few techniques have high prevalence, while the others have low or very low frequencies [24].  
One scheme for dealing with class imbalance is oversampling [24]. This data-level approach consists of randomly oversampling duplicate examples from low-frequency classes to rebalance the class distribution. However, this can result in overfitting and we opted to use the TextAttack Framework [25] for generating adversarial examples. TextAttack is a Python framework designed for adversarial attacks, data augmentation, and adversarial training in NLP. The adversarial attack finds a sequence of transformations to perform on an input text such that the perturbations adhere to a set of grammar and semantic constraints and the attack is successful [26]. These transformations performed can be reused to expand the training dataset by producing perturbed versions of the existing samples. As such, TextAttack Framework offers various pre-packaged recipes for data augmentation [27].  
Figure 1: The distribution of CVEs among techniques.  
We chose the EasyDataAugmenter (EDA) for augmenting the CVE dataset, which performs four simple but powerful operations on the input texts: synonym replacement, random insertion, random swap, and random deletion. EDA significantly boosts performance and shows particularly strong results for smaller datasets [28], which makes it the perfect candidate for oversampling our labeled CVE corpus. Moreover, EDA does not perform major alterations of the content and is not as computationally expensive as other recipes, such as CLAREAugmenter, while providing satisfactory results on our CVE corpus.  
Since one CVE can be mapped to multiple techniques at the same time, rare techniques among the dataset are usually found in combination with highly prevalent techniques. Using all CVEs that are mapped to a specific technique for augmentation would only preserve the class imbalance, generating new samples for both low-frequency and high-frequency techniques. To counter this undesired effect, EasyDataAugmenter was fed only with CVEs that were particular to only one technique and were mapped to that technique only, thus producing new samples only for the desired class.  
Figure 3 displays the distribution of CVEs per technique after performing the data augmentation. The initial severe imbalance among techniques was scaled down, but still exists, due to the reduced number of particular CVEs for low-frequency techniques.
# Evaluation of 3D Concrete Printing Extrusion Efficiency
## 2 Materials and Methods
### Printing System  
The tested printing system features a modular design that enhances the ergonomics of printer operation. Its simple assembly facilitates rapid preparation for use and simplifies the cleaning of components after printing is completed.  
The print head consists of the following components:  
1. Tank: With a volume of 20 L, it provides a material buffer for printing, ensuring a consistent supply throughout operations. Made of stainless steel, the tank is designed to resist the corrosive effects of geopolymer additives, ensuring durability and longevity;
2. Drive shaft: This is responsible for transmitting torque from the motor to the extruder screw;
3. Mixer blades: An integrated mixer is essential for preventing the decomposition of the material, ensuring a homogeneous consistency throughout the printing process. The mixer operates in synergy with other components to maintain the mix's quality, providing a consistent and reliable output necessary for the structural integrity of the printed object;
4. Quick clamp: This enables the rapid disassembly of the print head and its effective cleaning;
5. Sleeve with screw: This assembly regulates the correct dosage of material during printing. The sleeve, made of polyamide (PA6), is a replaceable component. The screw, constructed from stainless steel, is integral to the pumping and dosing system of the 3D printer, capable of handling concrete mixes. Designed for easy cleanup and resistance to corrosive substances, the screw features an L/D (length/diameter) ratio of 3.5, which was optimized based on results from previous tests, to ensure efficient dosing of reinforced materials while maintaining compatibility with foamed mixes;
6. Nozzle: Constructed from wear-resistant materials, the nozzle ensures long service life, even under the abrasive conditions associated with concrete and geopolymer mixes. Designed to be cost-effective, it allows for easy replacement, reducing downtime during maintenance. The manufacturing process is streamlined for ease of production, and the nozzle's design facilitates simple cleaning, which is crucial when switching between different mix types, such as foamed concrete and standard concrete;
7. Motor: The motor is the extruder drive element;
8. The diagram of the printing system used in the research, featuring a modular design that enhances the ergonomics of printer operation, is presented in Figure 3. Figure 4 shows the laboratory 3D printer prepared for print-head performance tests, along with a view of the internal components of the print head.  
Figure 4: (**a**) The laboratory 3D printer prepared for print-head performance testing; (**b**) the internal components of the print head.  
Figure 3: Diagram of the printing system used in the research: (1) tank, (2) drive shaft, (3) mixer blades, (4) quick clamp, (5) sleeve with screw, (6) nozzle, (7) motor.
# Experimental Evaluation of Unicast and Multicast CoAP Group Communication
## 2 Group Communication
### Importance of Group Communication in the IoT  
The basic CoAP interaction model is based on one-to-one communication, i.e., a client is exchanging messages with a server. The basic interaction model covers a wide range of interaction patterns that are found in various fields of the IoT. However, in many use cases, a one-to-many communication pattern is convenient or even essential for various reasons. Sometimes, the data collected from sensors might not be sufficient to get the complete information about the monitored object. In other cases, it is desired to get the information from more than one source to increase accuracy or reliability. Sometimes, data from many sources need to be collected and processed before they can be used. Likewise, it is often needed to control more than one actuator at once to make the complete object act as desired. This need to communicate with groups of objects is obvious in many IoT scenarios and is very well recognized in the IETF, as it is part of the charter of the IETF CoRE Working Group [10].  
The relevance of multicast communication for wireless networks for Building Automation Systems (BASs) has been identified in [11]. In this paper, we focus on group communication in BASs, which is in line with the experiments we conduct on the testbeds in Section 5.  
There are many ways to group resources based on the application requirements. Table 1 shows some possible types or motivations for resource grouping in BASs.  
Within this context, we have defined the requirements and goals for CoAP group communication, which are described in detail in [9]. We have motivated their importance in the context of IoT applications, constrained devices and LLNs. For the completeness of this article, we summarize the requirements for group communication in Table 2.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Type** & **Groups Based on** & **Example** \\ \hline Physical & physical structure of building & desk, part of room, room, wing, floor, building, etc. \\ Logical & similarity or functionality & all light intensity sensors \\ Application & application point of view & power consumption of heterogeneous devices \\ Administrative & roles, rights or policies & access keys of security guards \\ \hline \hline \end{tabular}
\end{table}
Table 1: Potentially relevant types of resource grouping in Building Automation Systems (BASs).
## 2 Imaging System Design
### Imaging Control Principle  
The block diagram of the imaging control is shown in Figure 2. The imaging controller first calculates the imaging cycle \(t_{p}\) using Equation (1). The imaging controller adjusts the timing sequence of each imaging cycle to guarantee \(\rho\), which is essential for photogrammetry mapping to be satisfied:  
\[t_{p}=\frac{L_{C}\cdot(1-\rho)\cdot H}{v^{W}\cdot f} \tag{1}\]  
Figure 1: Mechanism of the three-axis inertially stabilized platform.  
where \(\rho\) is the image overlap rate along flight, \(L_{\text{C}}\) is the along-flight length of the sensor, \(f\) is the focal length of the optics, \(v^{W}\) is the velocity of the aircraft, and \(H\) is the relative height of the aircraft.  
During the preparation period of each imaging cycle, the gimbal angle calculation model calculates the azimuth gimbal angle \(\kappa\), pitch gimbal angle \(\omega\), and roll gimbal angle \(\varphi\) based on the attitude of the three-axis platform and the desired imaging attitude (refer to Section 3.2). An adaptive fast terminal sliding mode control strategy subjected to the uncertain disturbances is used for the Servo Control module [20; 21; 22], which estimates the parameters of the lumped uncertain disturbances online and drives each axis tracking the desired gimbal angle. The IMC Calculation module calculates the longest exposure duration \(T_{M}\) according to the image motion compensation residual. Then, the Imaging Controller module sets the exposure duration \(T_{E}\) and other parameters of the area camera for the current imaging cycle (refer to Section 4.2). During the photographing period, the IMC Calculation module computes the angular rate \(\omega_{F}\) (refer to Section 4.1), the Imaging Controller module changes the servo state of the pitch axis to the velocity model, and the Servo Control module makes the pitch axis rotate at angular velocity \(\omega_{F}\). Meanwhile, the Imaging Controller module sends a level signal of exposure pulse to the area camera to trigger exposure.  
The primary function of the velocity control for the Servo Control module is to compensate the image motion angular velocity. The lead-lag compensation algorithm is used for the velocity control, which not only increases the bandwidth of the velocity servo system but also achieves high-precision velocity tracking performance. The velocity in inertial space sensed by the gyro is used for the velocity feedback in the velocity servo system. The uncertain disturbances of the aircraft can be also sensed by the gyro and will be compensated by the closed loop of the velocity control of the servo system.  
Figure 2: Block diagram of the imaging control.
## 3 Simulations  
A 3-D finite element model (FEM) of the stiffened cylindrical shell was built for numerical analysis of the interaction between the AE signal and the stiffener. The corresponding specification is shown in Figure 4.  
The outer diameter for the cylindrical shell in the model was 1000 mm, the wall thickness was 2 mm, and the axial length was 600 mm. The stiffener's axial length was 5 mm, and the outer diameter was (1000 + 2\(h\)) mm. The stiffener was attached to the cylindrical shell and located in the middle of the shell. \(h\) varied from 0 to 40 mm for different demands and practical dimensions. A dynamic displacements was excited along the \(z\)-axis on ES to generate the simulated AE signal with L(0,1) mode as the main mode. The excitation signal was a modulated sinusoidal pulse with three cycles, with its center frequency \(f_{\rm{c}}\) varying from 100 kHz to 170 kHz based on the bandwidth in which fatigue cracks occur and grow. The time domain waveform for the excited signal with \(f_{\rm{c}}\) = 150 kHz is shown in Figure 5. The parameters that meet the waveform separation conditions in Section 2.3 were specifically chosen as \(d_{1}\) = 30 mm, \(d_{2}\) = 50 mm, \(d_{3}\) = 100 mm, \(d_{4}\) = 220 mm, and \(d_{5}\) = 200 mm, which was utilized to determine the placements of EP, R, and T.  
Table 1 summarizes the material properties employed in the simulations. Free boundary conditions are imposed to the FEM in simulations ensuring consistency between simulations and experiments. All FEM models are meshed by tetrahedral grid elements. To ensure proper calculation precision and convergence, for the wave with the highest frequency, more than 20 elements in the wavelength were used, and the time step was set  
Figure 4: The 3-D model for the cylindrical shell with a stiffener used in simulations.  
to at least 1/20 of the highest frequency. Therefore, the maximum cell grid is 0.2 us, and the time step is determined to be 0.7 mm. To reduce the time cost of simulation, the response period obtained from simulations continues for 0.15 ms, which contained the interested scattered signals.
# Hypernetwork Representation Learning with the Set Constraint
## 3 Problem Definition  
This section formally defines our studied problem. The hypernetwork is usually abstracted as the hypergraph \(H=(V,E)\) with the set of nodes belonging to \(T\) types \(V=\{v_{i}\}_{i=1}^{|V|}=\{V_{i}\}_{t=1}^{T}\) and the set of hyperedges which can be associated with no less than two nodes \(E=\{e_{i}=(v_{1},v_{2},\ldots,v_{m})\}_{i=1}^{|E|}\)\((m\geq 2)\). If the number of nodes is two for each hyperedge, the hypernetwork degenerates to a traditional network. If \(T\geq 2\), the hypernetwork is defined as a heterogeneous hypernetwork. Here the problem of hypernetwork representation learning with the set constraint is formally defined as follows.  
**Definition 1**.: _Given a hypernetwork \(H=(V,E)\), the problem of hypernetwork representation learning with the set constraint aims to learn a low-dimensional vector \(r_{n}\in R^{k}\) for each node \(n\) in the hypernetwork, where \(k\) is expected to be much smaller than \(|V|\), making the learned node representation vectors explicitly preserve both the hypernetwork topology structure and the hyperedges._
# Helicopter Takeoff and Landing Point Location in Cities for Emergency Services
###### Abstract  
In low-altitude rescue, civilian helicopters, relying on their speed, efficiency and flexibility, play at center stage. Due to the terrain restrictions of the disaster area, it is difficult for helicopters to carry out safe and efficient rescue in cities. In order to facilitate emergency rescue, fixed helicopter takeoff and landing points for rescue missions must be selected strategically and wisely. However, the traditional method is to analyze the satellite data and conduct field surveys manually, which is rather subjective. A scientific, simple and efficient method of location selection is in urgent need. This paper analyzes the normativeness of the location of the helicopter's take-off and landing point and establishes a model of the slope and undulation of the landing site. It utilizes ArcGIS software to build layers and selects for the terrain element models that meet the specifications. It also studies the rescue radius commonly used in the world and then maximizes the location range of the take-off and landing point based on the greedy algorithm. Considering the construction cost, the final optimized site selection result is obtained. The results show that the use of GIS space technology can effectively select suitable take-off and landing points and gain valuable time for low-altitude rescue.  
GIS spatial analysis; site selection problem; terrain analysis factor; greedy algorithm +
Footnote †: journal: Applied  
1  
[PERSON], [PERSON], S. Helicopter Takeoff and Landing Point Location in Cities for Emergency Services. _Appl. Sci._**2022**, _12_, 9570. [[https://doi.org/10.3390/app1299570](https://doi.org/10.3390/app1299570)]([https://doi.org/10.3390/app1299570](https://doi.org/10.3390/app1299570))  
Academic Editor: [PERSON]  
Received: 21 August 2022  
Accepted: 21 September 2022  
Published: 23 September 2022  
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