esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Sensory Analysis and Acceptability  
Figure 4 reports the results of the QDA regarding the cheese CTR and ECO.  
Among the identified and considered descriptors, only a few significant statistical differences according to the fed composition were displayed. As regards appearance, ECO resulted in a more \"yellow color\" and in a lower \"presence of lighter colored spots\"; the \"milk odor\" and the \"sour and piquant taste\" intensity were higher in the CTR cheese, and the \"sweet taste\" in the ECO one. The differences in the color and appearance of the ECO samples could be due to the presence of carotenoids in the olive cake since it has been demonstrated to be an important source of these substances; as regards the CTR cheeses, the higher intensity of \"milk odor\" could be related to the amount of 2-ketones in the volatile fraction, while that of piquant and sour taste to the highest amount of SCFFA [55]. Figure 5 shows the results of the consumer's acceptability test.  
The consumers mostly appreciated the ECO cheese, especially for its appearance and taste. A more intense yellow color, together with a sweeter and less sour and piquant taste, is related to the consumer's acceptability.  
Figure 4: QDA spider plot of significant descriptors of Caciocavallo cheese. CTR: milk and cheese made by dairy cows fed concentrate without olive cake supplements. ECO: milk and cheese made by dairy cows fed concentrate with 7% enriched olive cake as 7% of a DM.
## 2 Theoretical Analysis
### Series Model  
As shown in Figure 3, the standard equation of the model is:  
\[\left\{\begin{array}{c}M\ddot{X}+k\left(X-x\right)=F\\ k\left(x-X\right)+c\dot{x}=0\end{array}\right. \tag{5}\]  
Substitute \(F=F_{0}e^{i\omega t}\) and \(X=X_{0}e^{i(\omega t-\varphi)}\) into the equation and apply Euler's Formula, \(e^{i\varphi}=\cos\varphi+i\sin\varphi\), to determine the damping and stiffness:  
\[c=\frac{F_{0}}{\omega X_{0}}\sin\varphi+\frac{F_{0}}{\omega X_{0}}\cot\varphi \cos\varphi+2\omega M\cot\varphi+\frac{\omega^{3}M^{2}X_{0}}{F_{0}\sin\varphi} \tag{6}\]  
\[k=\frac{c}{\frac{1}{\omega}\cot\varphi+\frac{\omega MX_{0}}{F_{0}\sin\varphi}} \tag{7}\]  
Figure 3: Series model.  
The periodical energy consumption of damping is:  
\[q=\int c\dot{x}\mathrm{d}x=\int\limits_{0}^{T}c\dot{x}^{2}\mathrm{d}t=\sum \limits_{i=1}^{i=f_{s}\cdot T}c\dot{x_{i}}^{2}t_{i} \tag{8}\]
# A Distributed Real-Time Monitoring Scheme for Air Pressure Stream Data Based on Kafka
###### Abstract  
Strict air pressure control is paramount in industries such as petroleum, chemicals, transportation, and mining to ensure production safety and to improve operational efficiency. In these fields, accurate real-time air pressure monitoring is critical to optimize operations and ensure facility and personnel safety. Although current Internet of Things air pressure monitoring systems enable users to make decisions based on objective data, existing approaches are limited by long response times, low efficiency, and inadequate preprocessing. Additionally, the exponential increase in data volumes creates the risk of server downtime. To address these challenges, this paper proposes a novel real-time air pressure monitoring scheme that uses Arduino microcontrollers in conjunction with GPRS network communication. It also uses Apache Kafka to construct a multi-server cluster for high-performance message processing. Furthermore, data are backed up by configuring multiple replications, which safeguards against data loss during server failures. The scheme also includes an intuitive and user-friendly visualization interface for data analysis and subsequent decision making. The experimental results demonstrate that this approach offers high throughput and timely responsiveness, providing a more reliable option for real-time gathering, analysis, and storage of massive data.  
IoT; real-time processing; distributed stream processing; Apache Kafka; monitoring Article
## 6 Economic Benefits of Pre-Grouting
### Economic Benefits of Surface Pre-Grouting  
Surface pre-grouting is performed before the TBM passes through shallow, poorly consolidated ground to strengthen the surrounding rock, facilitating the TBM's safe passage without significantly affecting the excavation time. The main tasks of surface pre-grouting include ground clearing, drilling quantity and depth, and cement slurry preparation, with specific investment details provided in Table 7.  
Advancements in drilling equipment, grouting machinery, and materials have reduced the difficulty of surface pre-grouting in tunnel sections intersecting gullies. However, issues like hole collapse and drill loss still occur in fractured zones, making it challenging to implement pre-grouting effectively. From an economic perspective, while deep tunnel grouting involves substantial drilling and grouting volumes, the technology for deep-hole grouting is still underdeveloped, leading to high labor and material costs.
## 5 The Forward Secrecy Extension  
Forward secrecy is an advanced security feature which makes the past session keys still secure even though the long-term key of a system was stolen by attackers. If a scheme is not with forward secrecy, an attacker, who has gotten the long-term key by some means, can compute all past session keys which were derived from the long-term key.  
Our anonymous authentication protocol can be easily extended to own the feature of forward secrecy by adopting Diffie-Hellman key exchange protocol [24]. The extended protocol is given in Figure 16. Let \(p\) be a prime and \(g\) be a generator with order \(q\) in \(\mathbb{Z}_{p}^{*}\) where \(q\) is also prime and \(q|(p-1)\). In the extended authentication protocol, when \(MS\) is preparing \(\theta_{2}\), she/he randomly chooses an integer \(a\in\{1,\ldots,q\}\) and compute \(r_{3}=g^{a}\bmod p\). Then, \(MS\) sets \(\theta_{2}=E_{pk_{V}}(r_{1},r_{2},r_{3})\). \(V\) prepares \(r_{4}=g^{b}\bmod p\) where \(b\) is randomly selected from \(\{1,\ldots,q\}\) and sends \((r_{1},r_{4})\) to \(MS\). Finally, \(MS\) computes the session key \(k_{s}=r_{4}^{a}\bmod p\) and \(V\) computes \(k_{s}=r_{3}^{b}\bmod p\).  
In the extended version, the mobile user has to pay two more exponentiation computations, _i.e._, \(r_{3}=g^{a}\bmod p\) and \(k_{s}=r_{4}^{b}\bmod p\) for completing her/his authentication. The mobile user can pre-compute \(r_{3}=g^{a}\bmod p\) before the communication.
## 3 Results
### Vibrational Spectra
In the iodide IL, the IR band at 3136 cm\({}^{-1}\) is split into a significantly blue-shifted (\(\Delta\)v = +39 cm\({}^{-1}\)) and a moderately  
Figure 4: Infrared (**a**,**c**,**e**) and Raman (**b**,**d**,**f**) spectra in the CH stretching region. The relevant peaks and shoulder bands are marked by arrows; (**a**) and (**b**) show the data of the iodide ILs; (**c**) and (**d**) show the data of the tetrafluoroborate ILs; (**e**) and (**f**) show the data of the hexafluorophosphate ILs. red-shifted (\(\Delta\)v = \(-\)17 cm\({}^{-1}\)) peak. On the other hand, for the [BF\({}_{4}\)\({}^{-}\)] IL, a moderate blue shift (\(\Delta\)v = +11 cm\({}^{-1}\)) and a significant red shift (\(\Delta\)v = \(-\)44 cm\({}^{-1}\)) are observed. The [PF\({}_{6}\)\({}^{-}\)] IL places itself in between: blue shift of \(\Delta\)v = +17 cm\({}^{-1}\) and red shift of \(\Delta\)v = \(-\)14 cm\({}^{-1}\). This observation perfectly correlates with the polarizability of the three anions: 0.00673 for [I\({}^{-}\)] > 0.00418 for [PF\({}_{6}\)\({}^{-}\)] > 0.00280 for [BF\({}_{4}\)\({}^{-}\)] according to [PERSON] et al. [36]. This suggests that the anion's polarizability plays an important role in determining not only the strength of the hydrogen bond, but also the charge distribution across the cation. This charge redistribution upon methylation is also reflected by many other vibrational modes of the aromatic ring, e.g., for all three anions, the N-C(6) stretching modes are blue-shifted by about 10 cm\({}^{-1}\) in the methylated compounds. In summary, the IR and Raman spectra of the C(2) protonated ILs show that the anion interacts with the cation via formation of a strong hydrogen bond at C(2)-H. Upon methylation, the anion moves to the C(4) and C(5) moiety, where it forms a new hydrogen bond with one of the two protons. The spectra do not suggest that other interaction mechanisms, such as those via the \(\pi\)-electron system of the aromatic ring (often referred to as the on-top position [37; 38; 39]), play a major role. Moreover, [PERSON] et al. [26] performed an experimental and computational study on methylated and nonmethylated butylimidazolium ILs with spherical anions. They found that the melting points and freezing points of these ILs increase with methylation at the C(2) position. They also found that the Raman bands of [BMIm]I shift red upon C(2) methylation, whereas the bands of [BMIm]BF\({}_{4}\) and [BMIm]PF\({}_{6}\) shift blue. This finding indicates that the anion's position in [BMIm]I is closer to the proton at the 4 or 5 position than in BF\({}_{4}\)\({}^{-}\) and PF\({}_{6}\)\({}^{-}\) salts. This is in agreement with our results.
# Numerical Analysis via Mixed Inverse Hydrodynamic
## 2 Mathematical Model  
### FEA Model  
The FEA model was assumed to be 2D axially symmetric. Figure 1a shows the FE analysis model of the rod seal. The mesh convergence analysis was conducted to choose the 6966 mesh elements used in the simulations. The materials used for the analysis were carbon steel for the rod and seal housing and hydrogenated nitrile butadiene rubber (HNBR) for the seal, as used by [PERSON] et al. [17]. The carbon steel of the rod and seal housing has an elastic modulus of 210 GPa, whereas the rubber seal has a relatively small elastic modulus of 12.7 MPa; thus, all objects except rubber are assumed to be rigid bodies. For the physical properties of rubber seals, the Mooney-Rivlin model equation was used, as in [PERSON] et al. [17].  
\[W=C_{10}(I_{1}-3)+C_{01}(I_{2}-3)+D_{1}(J-1)^{2} \tag{1}\]  
where \(W\) is a general form of the strain-energy function for incompressible materials; \(I_{1}\) and \(I_{2}\) are the first and second deviatoric strain invariants, respectively; \(J\) is the elastic volume ratio; and \(C_{10}\), \(C_{01}\), and \(D_{1}\) are material coefficients, i.e., \(C_{10}=-0.167\), \(C_{01}=2.85\), and \(D_{1}=7.5\ \times\ 10^{-3}\).  
Figure 1: _Cont._  
Figure 1b shows the von Mises stress after the interference fit simulation analysis and the pressurized process of the rubber seal. It can be seen that stress concentration occurs at the axial end edge in contact with the seal housing. Figure 2 shows the contact pressure in the sealing zone of Figure 1b for sealing pressures of 20 MPa, 25 MPa, 30 MPa, and 35 MPa. The contact force can be calculated by integrating the static contact pressure in Figure 2 and the length of the sealing zone is the length of the section where the contact pressure exists. As the sealing pressure increases, the contact load increases, the seal contracts more, and the length of the sealing zone decreases.
## 3 Theoretical Background  
### Multicarrier Modulations  
Multicarrier modulation (MCM) defines a technique of transporting data over several subchannels of narrow bandwidth instead of conveying the data over the entire bandwidth in single-carrier modulation (SCM) schemes. MCM is known as a technique that uses multiple carrier signals at different frequencies, sending some of the bits on each subchannel. The main advantages of MCM are summarized as follows: its immunity to multipath fading channels (frequency-selective channels in particular), its enhanced immunity to Intersymbol Interference as the symbol period on each subchannel increases, its spectral efficiency, and its resilience to interference. Indeed, each subcarrier represents only a small portion of the total signal. If one subcarrier is lost or corrupted due to interference or noise, the overall signal remains almost intact. This resilience makes multicarrier modulation robust. OFDM is the most popular scheme used in digital video and audio broadcasting as well as Long-Term Evolution (LTE) downlink transmissions. However, UFMC modulation is proposed as an alternative for many communication systems including DVB-T2. This section presents these modulations and compares their features.
## 5 Discussion  
This paper is based on an actual engineering project of a CSG dam with two stages, designed according to some practical requirements, and it introduces a design method for implementing nonlinear calculations in ANSYS. A numerical model for the CSG dam upon overburden is established using an improved Duncan-Chang constitutive model. The effects of geometric dimensions of the dam body and characteristics of the overburden are considered. The grey relational grade between influencing factors and the dam's maximum settlement and maximum compressive stress is discussed. Based on the results of grey correlation degree, a BP neural network model is established, and the maximum settlement and maximum compressive stress of the dam body is predicted with high accuracy. Combined with the trained prediction model, an optimization method is designed to maximize the economic benefits of the dam under the premise of improving the stress deformation state. The results of the analysis of influencing factors show that changes in the upstream and downstream slope coefficients of the dam have a significant impact on the stress and settlement of the dam. With a trained neural network model, in practical engineering, the results of maximum settlement and maximum compressive stress can be quickly obtained by inputting the slope coefficients and overburden properties into the neural network. Due to using the optimization design as the starting point in designing the network model, factors such as the height, the width, and dosage of cementitious materials of the dam are not considered into the neural network. But according to the outlook, this can be promoted. By considering the complete geometric dimensions, the material parameters of the dam body, and complete material parameters of the overburden into the neural network, a relatively more universal prediction model will be obtained, which can be directly used as a reference of site selection, dimension design, overburden treatment, and design optimization of CSG dams for more design organizations.  
The advantages of the optimization method based on BP neural network are shown in detail, such as significant efficiency improvements, but it may also have some limitations. It heavily relies on the accuracy of the prediction model, which is a prerequisite. If encountering situations with poor prediction results, it is difficult, or even impossible, to obtain the optimal result. Therefore, improving the prediction accuracy of nonlinear calculations is also a worthwhile issue to study.  
In future dam design and construction practices, the optimization methods based on neural network can be used to save time on finite element software calculations, and trained models can be saved for future use. More and more trained prediction models like those in this paper may appear, corresponding to various types of dams and geographical conditions. Designers can directly obtain references for site selection and structural design, or combine them with design optimization, which can improve the operational efficiency of the entire industry and greatly save social resources.
## 2 Description of the Forward Model
### The Radiative Transfer Model  
The VLIDORT radiative transfer (RT) model is used to calculate radiances and their Jacobians with respect to atmosphere and surface parameters. VLIDORT is a linearized pseudo-spherical vector radiative transfer code based on the discrete ordinate method for the determination of single and multiple scattering radiation fields with solar-beam and/or thermal emission (Planck function) sources of radiation in a multilayer stratified atmosphere [51].  
VLIDORT computes a four-element diffuse field of Stokes components {I, Q, U, V}, with I being the total intensity, Q and U describing linearly-polarized radiation and V characterizing circularly-polarized radiation. The magnitude of V is very small in the Earth's atmosphere, and therefore, we ignore this component in our calculations. For diffuse radiation, especially with a high aerosol concentration, multiple scattering has an obvious effect on the optical paths. Contributions from both attenuated solar beam single scattering and multiple scattering are included in VLIDORT [52]. For nadir-viewing at large solar zenith angles (SZA), the pseudo-spherical approximation, which treats solar beam attenuation for a curved atmosphere while all scattering events still take place in a plane-parallel medium, is deployed in VLIDORT instead of the pure plane-parallel assumption.  
The optical properties, the layer total optical thickness, total single-scattering albedos and the 4 \(\times\) 4 spherical-function expansion coefficient matrix characterizing the scattering phase function, and their corresponding derivatives with respect to retrieved parameters are required as inputs to VLIDORT. These optical and linearized inputs are from the aerosol model, Rayleigh scattering and gas absorption model introduced in previous sections, through suitable application of the chain rule.
## 2 Materials and Methods
### Quantification of Adipose Tissues  
Computed tomography (CT) is a standard imaging modality for simulation and is used in the RT planning system prior to NACRT. Using anatomy to delineate the region of interest (ROI) and the Hounsfield unit (HU) to measure the radiodensity of structures such as tumor and adipose tissue, data on both context and structure volume could be obtained. Images were obtained using a CT scanner (Big-Bore CT simulator, Philips, Amsterdam, Netherlands) equipped for simulation with the following specifications: scanning with 16 \(\times\) 0.75 mm collimation, rotation time of 420 msec, and tube voltage of 120 kV. The EAT was contoured based on the anatomical boundary between the outer wall of the myocardium and the visceral layer of pericardium from the level of the left main coronary artery to the cardiac base, ranging from \(-\)195 to \(-\)45 HU (Figure 1B) [13; 14; 15]. The left main coronary artery for fat thickness, peri-thoracic adipose tissue (TAT) for peri-thoracic aortic fat volume, and subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) of the thorax for fat areas were delineated according to the methods shown in our previous publications [13; 16; 17; 18]. For example, the TAT tissue was defined as the adipose tissue surrounding the thoracic aorta, extending 67.5 mm caudally from the level of the bifurcation of pulmonary arteries.  
Figure 1: (**A**) The dose distribution was in color wash with IMRT treatment planning; (**B**) the epicardial adipose tissue (_yellow_) was contoured based on the anatomical boundary of heart, ranging from \(-\)195 to \(-\)45 HU. Abbreviations: EAT, epicardial adipose tissue; MPA, main pulmonary artery; AAo, ascending aorta; RPA, right pulmonary artery; CTV, clinical target volume.
# Counter-Terrorism Video Analysis Using Hash-Based Algorithms
## 6 Implementation and Performance Study
### Matching Algorithm  
Our second algorithm is responsible for comparing the frames and deciding whether they originated from the same image or not.  
It calculates the Hamming Distance of two hashes. If it is lower than a certain threshold it will be considered a match.  
Basically, most of the irrelevant information was lost during the previous process but some pieces may go through it all. The threshold is the last barrier to distinguishing edited images.  
When applied to our database which contains 5370 frames, against a 3-min video, it found the matching frames in 2 h 32 min and 42 s. Please note that we are using a 4-core CPU for a program which admits a very high degree of parallelization; the performance could be greatly improved by hardware.
###### Abstract  
Direct communication between vehicles and surrounding objects, called vehicle-to-everything (V2X), is ready for the market and promises to raise the level of safety and comfort while driving. To this aim, specific bands have been reserved in some countries worldwide and different wireless technologies have been developed; however, these are not interoperable. Recently, the issue of co-channel coexistence has been raised, leading the European Telecommunications Standards Institute (ETSI) to propose a number of solutions, called mitigation methods, for the coexistence of the IEEE 802.11p based ITS-G5 and the 3 GPP fourth generation (4G) long term evolution (LTE)-V2X sidelink. In this work, several of the envisioned alternatives are investigated when adapted to the coexistence of the IEEE 802.11p with its enhancement IEEE 802.11 bd and the latest 3 GPP standards, i.e., the fifth generation (5G) new radio (NR)-V2X. The results, obtained through an open-source simulator that is shared with the research community for the evaluation of additional proposals, show that the methods called A and C, which require modifications to the standards, improve the transmission range of one or both systems without affecting the other, at least in low-density scenarios.  
connected vehicle; IEEE 802.11p; IEEE 802.11 bd; 5G-NR V2X; co-channel coexistence; simulation 2023