esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Global navigation satellite system (GNSS) radio occultation (RO) receivers onboard the recently-launched COSMIC-2 (C2) satellite constellation provide an unprecedented number of high vertical resolution moisture profiles throughout the tropical and subtropical atmosphere. In this study, the distribution and variability of water vapor was investigated using specific humidity retrievals from C2 observations and compared to collocated ERA5 and MERRA-2 reanalysis profiles within 40\({}^{\circ}\)N to 40\({}^{\circ}\)S from September to December 2019, which is prior to the assimilation of C2 in the reanalyses. Negative C2 moisture biases are evident within the boundary layer, so we focused on levels above the boundary layer in this study. Overall, C2 specific humidity shows excellent agreement with that of ERA5 and has larger differences with that of MERRA-2. In the tropical mid-troposphere, C2 shows positive biases compared to ERA5 (6-12%) and larger negative biases with MERRA-2 (15-30%). Strong correlations are observed between C2 and reanalysis specific humidity in the subtropics (>0.8) whereas correlations are slightly weaker in the deep tropics, especially for MERRA-2. Profile pairs with large moisture differences often occur in areas with sharp moisture gradients, highlighting the importance of measurement resolution. Locations which demonstrated weaker humidity correlations in active convection regions show that ERA5 has a negative specific humidity bias at 3 km in higher moisture environments, whereas MERRA-2 displays a large positive bias at 7 km. However, additional explanations for profile pairs with large moisture differences remain unclear and require further study.  
tropsheric water vapor; radio occultation; COSMIC-2; reanalysis; tropics; subtropics Article  
Evaluation of Tropospheric Moisture Characteristics Among COSMIC-2, ERA5 and MERRA-2 in the Tropics and Subtropics [PERSON] et al. (2021), 13, 880. [[https://doi.org/10.3390/rs13050880](https://doi.org/10.3390/rs13050880)]([https://doi.org/10.3390/rs13050880](https://doi.org/10.3390/rs13050880))  
1
# Teletraffic Analysis of DoS and Malware Cyber Attacks on P2P Networks under Exponential Assumptions
###### Abstract  
Peer-to-peer (P2P) networks are distributed systems with a communication model in which no central authority governs the behavior of individual peers. These networks currently account for a considerable percentage of all bandwidth worldwide. However, this communication model also has a clear disadvantage: it has a multitude of vulnerabilities and security threats. The nature of the P2P philosophy itself means that there is no centralized server responsible for uploading, storing, and verifying the authenticity of the shared files and packets. A direct consequence of this is that P2P networks are a good choice for hackers for the spread of malicious software or malware in general since there is no mechanism to control what content is shared. In this paper, we present a mathematical model for P2P networks to study the effect of two different attacks on these systems, namely, malware and denial of service. To analyze the behavior of the cyber attacks and identify important weaknesses, we develop different Markov chains that reflect the main dynamics of the system and the attacks. Specifically, our model considers the case in which a certain number of nodes are infected with a cyber worm that is spread throughout the network as the file is shared among peers. This allows observation of the final number of infected peers when an initial number (we evaluate the system for from 1 to 14 initial nodes) of malicious nodes infect the system. For the DoS attack, our model considers the portion of peers that are unable to communicate and the average attack duration to study the performance degradation of such an attack. A two-pronged approach was used to study the impact of the attacks on P2P networks; the first focused only on the P2P network, and the second focused on the attacks and the network.  
teletraffic; peer-to-peer networks; cyber attacks +
Footnote †: journal: Applied  
0203
## 3 Feature Extraction and Recognition Based on IPSO-VMD  
### Feature Extraction Based on VMD  
The failure of different components in the system will change the frequency distribution of the signal, further leading to the adjustment of the energy distribution of the signal. In order to avoid the dependence of traditional fault diagnosis methods on abnormal samples, VMD decomposition results under the optimal parameter combination are used to determine the effective components in combination with the correlation coefficient method. Finally, the energy ratio of the first five effective components is used as the feature parameter.  
1. Correlation Coefficient  
Correlation coefficient is a statistical indicator to measure the closeness of correlation between different variables. The correlation coefficient of sample X and sample Y is defined as follows:  
\[\rho_{(X,Y)}=\frac{\text{Cov}(X,Y)}{\sqrt{D(X)}\sqrt{D(Y)}} \tag{11}\]  
where, \(\text{Cov}(X,Y)\) is the covariance of sample \(X\) and sample \(Y\), \(D(X)\) and \(D(Y)\) are the variances of sample \(X\) and \(Y\), respectively. The correlation coefficient \(\rho\in[-1,1]\); the larger the absolute value of the correlation coefficient, the closer is the correlation between the two samples.  
For discrete digital signals, the correlation coefficients of signals \(x(i)\) and \(y(i)\) can be described as follows:  
\[\rho_{(x(i),y(i))}=\sum_{i=0}^{\infty}x(i)y(i)/\left[\sum_{i=0}^{\infty}x^{2} (i)\sum_{i=0}^{\infty}y^{2}(i)\right]^{1/2} \tag{12}\]  
For signals, the correlation coefficient \(\rho\) describes the similarity of two signals if \(\rho=1\) represents that the two signals are completely correlated. On setting the threshold value \(\sigma=0.1\), if the correlation coefficient between the \(i\)-th IMF component and the original signal is \(\rho>\sigma\), the IMF component is considered as an effective component.  
2. IMF Energy Ratio  
First, the original signal is processed by IPSO-VMD to obtain \(K\) IMF components. The energy \(imf\ E_{i}\) of each IMF component is calculated according to Equation (10):  
\[imf\ E_{i}=\int_{0}^{T}imf_{i}^{2}(t)dt,\ i=1,2,\cdots,K \tag{13}\]  
The obtained \(imf\ E_{i}\) is normalized, and the normalized \(imf\ E_{i}\) of the effective components is constructed as the eigenvector \(T\):  
\[T=\left[\frac{imf\ E_{1}}{E},\frac{imf\ E_{2}}{E},\cdots,\frac{imf\ E_{n}}{E}\right] \tag{14}\]  
where, \(E\) is the energy of the original signal, and \(n\) is the number of effective components.
# Production of Photovoltaic Electricity at Different Sites in Algeria
## 2 Materials and Methods
### Photovoltaic System  
The direct conversion of sunshine into electricity without the need for a heat engine is known as photovoltaic conversion [7]. The fundamental benefit of photovoltaic devices is that they can be built as independent systems to provide outputs ranging from microwatts to megawatts. They are robust and simple in design, require very little maintenance, and are available in a variety of sizes. As a result, they are employed in megawatt-scale power plants, reverse osmosis facilities, remote buildings, solar home systems, communications, satellites, and spacecraft. With such a broad range of uses, photovoltaics are in greater demand every year [8].  
Cells, mechanical and electrical connections, supports, and devices for controlling and/or altering the electrical output are only a few of the parts that make up a photovoltaic power-generating system. These systems are rated in kilowatt-peak (kWPp), which represents the maximum amount of electrical power that a system is anticipated to produce on a clear day with the sun directly overhead [9].
# Efficient Transmit Antenna Subset Selection for Multiuser Space-Time Line Code Systems
## 1 Introduction
\(\mathbf{I}_{n}\) and \(0_{n}\) denote the \(n\times n\) identity matrix and the \(n\times n\) matrix with all zero elements, respectively. \(\mathbf{X}(\cdot,k)\) indicates the \(k\)-th column vector of a matrix \(\mathbf{X}\). \(\mathbf{X}(:,[1:(k-1)\ (k+1):end))\) stands for the submatrix remained by deleting the \(k\)-th column vector in a matrix \(\mathbf{X}\). \(blkdiag\{\ \mathbf{Q}_{2},\cdots,\mathbf{Q}_{2}\}\) returns a block diagonal matrix whose diagonal matrices are \(\mathbf{Q}_{2},\cdots,\mathbf{Q}_{2}\).\(\mathcal{CN}(0,\sigma^{2})\) means a complex normal distribution with a zero mean and variance \(\sigma^{2}\).
# Tunable non-Hermiticity in Coupled Photonic Crystal Cavities with Asymmetric Optical Gain
## 1 Introduction  
Rationally designed photonic crystal (PhC) nanostructures have accelerated the development of various optical devices, such as low-loss optical waveguides, wavelength-selective filters, high-speed modulators, and low-threshold ultra-small nano-lasers [1; 2; 3; 4]. In such devices, the PhC nanostructures take advantage of the photonic bandgap, which prohibits the propagation of photons with certain frequencies, thereby serving as excellent light reflectors and mirrors. In particular, wavelength-scale PhC defect nano-cavities, which support resonant optical modes with high-quality factors, efficiently confine photons into an extremely small physical volume. Furthermore, they have enabled the development of chip-scale photon sources. Moreover, they have facilitated studies on intriguing quantum photonic phenomena, such as quantum phase transitions in cavity quantum electrodynamics [5; 6; 7; 8; 9]. In this regard, the application of the quantum mechanical concept of parity-time (PT) symmetry to a coupled optical cavity system has drawn increasing attention; this is because unprecedented lasing operations have been successfully demonstrated using such a system [10; 11; 12; 13; 14; 15; 16]. Particularly, the authors of [15] systematically controlled the spatially asymmetric optical gain in a coupled PhC defect nano-cavity system by introducing absorptive nanomaterials, e.g., graphene, and enabled the realization of non-Hermitian lasing actions in unbroken and broken PT-symmetric phases and the unique non-Hermitian phase transition at exceptional points (EPs). Furthermore, they identified and accurately analyzed lasing modes and the corresponding non-Hermitian behaviors using a PhC defect nano-cavity that exhibits only a few resonant optical modes with a wide free spectral range within a given optical gain frequencyrange. However, despite numerous merits, the potential of PhC nano-cavities for non-Hermiticity control has not been explored sufficiently, suggesting that rational design and cavity engineering can facilitate the development of new non-Hermitian photon sources.  
In this study, we theoretically investigate the controllable non-Hermitian behaviors of the eigenmodes and eigenfrequencies in doubly coupled PhC cavity systems by controlling the intercavity coupling and the level of asymmetricity in the optical gain. We propose three different coupling control schemes by slightly modifying the coupled cavity structures and examine the tunability of the coupling constant. In addition, we introduce the spatially asymmetric optical gain and analyze the non-Hermitian behaviors of complex eigenfrequencies and modal field distributions. Our numerical analysis reveals that the interplay of the asymmetric gain and intercavity coupling plays a key role in determining the state of the non-Hermitian optical system.
# The Vicious Cycle of Obesity and Low Back Pain: A Comprehensive Review
## 4 Spinal Changes Related to Obesity
### Facet Joints  
Obesity exacerbates facet joint osteoarthritis primarily through mechanical overload and systemic inflammation, accelerating cartilage degradation, subchondral bone remodelling, and osteophyte formation, which collectively may contribute to pain and restricted mobility [80]. Inflammatory pathways also play a critical role, as elevated cytokine levels in obesity amplify catabolic activity within joint tissues, promoting ECM degradation and impairing cartilage repair. This imbalance weakens the subchondral bone supporting the facet joints, making it more prone to degeneration and microfractures (Figure 2). Additionally, lipid abnormalities further contribute by enhancing osteoclast activity and inhibiting osteoblast differentiation, resulting in a compromised bone microenvironment [96]. Interestingly, despite similar prevalence rates of facet joint-related LBP in obese and non-obese individuals based on BMI [81], obese patients have been reported to experience less pain relief following radiofrequency ablation treatments [82]. Moreover, another study found an association between increased outer abdominal fat thickness and higher rates of facet joint osteoarthritis, suggesting that fat distribution, rather than BMI alone, may influence facet joint degeneration [80].
# Digital Human Technology in E-Learning: Custom Content Solutions
## 6 Evaluation and Discussion
### Discussion  
Both the generated audio and digital human animations aligned closely with the instructional content. Notably, the casual style achieved the highest ASR score, likely due to its linguistic simplicity, while the formal and key points styles scored slightly lower. The faster tempo of the key points style may have further reduced ASR accuracy. Additionally, the casual style exhibited the greatest short-time energy, suggesting a dynamic intonation that could enhance learner engagement.  
A principal advantage of this system is its capacity to offer varied content delivery styles, enabling educators to tailor instruction to diverse pedagogical requirements. The automated generation process also substantially decreases the effort and time needed to develop e-learning materials.  
Nevertheless, certain constraints persist. The generation speed remains suboptimal for high-resolution animations or complex scripts, which may impede real-time implementation. Moreover, customization is currently confined to predefined styles, and reliance on pre-trained models restricts adaptability to specialized domains or underrepresented languages. For contents, current AI systems have limitations in semantic abstraction and hierarchical structuring, particularly when expressing complex hierarchical relationships in a coherent and logical manner. For example, as shown in Figure 2c, \"influential in physics  
\begin{table}
\begin{tabular}{l c c} \hline \hline
**Style** & **LSE-D** & **LSE-C** \\ \hline Casual & 8.923 & 6.650 \\ Formal & 8.968 & 5.703 \\ Keypoint & 9.059 & 5.865 \\ \hline \hline \end{tabular}
\end{table}
Table 7: LSE-D and LSE-C scores for three video styles.  
\begin{table}
\begin{tabular}{l c} \hline \hline
**Question** & **Average Score** \\ \hline Content Consistency & 6.2 \\ Expression Style & 5.7 \\ Audio Quality & 6.0 \\ Visual Quality & 5.5 \\ Attraction & 5.3 \\ Overall Experience & 5.8 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Evaluation of survey results.  
& mathematics\" is a general statement, while \"contributed to optics & calculus\" represents specific subfields. Although optics is a branch of physics, the hierarchical distinction aims to emphasize the progression from overall impact to specific contributions. Future research should focus on optimizing computational efficiency, incorporating adaptive algorithms, and extending language support to broaden the system's global applicability.
## 4 Conclusions  
This paper studies the temperature profiles within mushroom PCM cells, using a three-dimensional finite element simulation model. On the basis of practical application objectives, the electrical, thermal, phase change, and percolation dynamics during the switching processes were simulated in turn using the finite difference method. The simulation results show that both RESET and SET operations are implemented by the melting and quenching of the GST material close to the GST-BE interface, mainly depending on the cooling rate. A higher efficiency of PCM cells can be achieved by virtue of thermoelectric heating with positive current polarity. In terms of the simulated geometry and materials in this article, the Peltier effect is more powerful and occurs at a more critical location, while its influence on programming current gradually weakens with the cell size scaling, resulting in a decreased contribution of total thermoelectric effects. These results provide physical insights into switching operations and thermoelectric effects in PCM cells, which is necessary for effective cell engineering. The cell geometry and material properties can strongly influence the temperature profiles and the programming currents, and the thermoelectric effects are closely related to the temperature and the temperature gradients. Further researches are needed for the development of PCM cells with a higher thermal efficiency focused on the utilization of thermoelectric effects related to different geometry and materials.  
Conceptualization, C.M. and J.H.; Methodology, C.M.; Formal Analysis, C.M., J.L. and J.Z.; Writing-Original Draft Preparation, C.M.; Writing-Review & Editing, J.H., J.Z. and Z.H.  
This research was funded by National Key Research and Development Plan.  
Figure 10: **(a)** Temperature profiles of the cells at the end of the current pulse (1.5 mA, 150 ns) with and without thermoelectric effects; **(b)** corresponding phase distribution within the GST layer. Blue and red regions represent the amorphous and crystalline phase, respectively.
## 4 Method Validation
### Field Applications in Real Mines
#### 4.2.1 Results of Meter Classification and Reading  
The quadruped robot was placed in the mine power distribution room to collect pictures and recognize the meter data in the real mine scene, and the mine power distribution room scene is shown in Figure 19.  
A total of 100 photographs were collected by the quadruped robot in the power distribution room of the mine, of which 55 were pointer meters and 45 were digital meters. Applying the meter reading technique proposed in this study, the correct readings were 48 for pointer meters and 42 for digital meters, with accuracies of 87.27% and 93.33%, respectively. The results of the readings are shown in Table 10.  
The number of images with pointer meter reading errors between \(\pm\)0.5 were counted in the experiments, resulting in an error distribution graph as shown in Figure 20.  
Figure 21 shows examples of the results of pointer and digital meters and readings identification captured by the quadruped robot at different locations in the mine power distribution room. In summary, the intelligent meter reading inspection robot technology proposed in this paper is able to better recognize the meter readings inside the mine power distribution room.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Meter Type** & **Image Statistics** & **Correct (Errors \(\leq\) 0.5)** & **Accuracy** \\ \hline Pointer & 55 & 48 & 87.27\% \\ Digital & 45 & 42 & 93.33\% \\ \hline \hline \end{tabular}
\end{table}
Table 10: Results of meter classification and reading.  
Figure 19: Mine power distribution room scene.
## 2 Problem Statement and Modeling  
### Research Scenario  
This paper presents a research scenario where a CAV is integrated into a manually driven traffic flow to explore a single-vehicle control strategy. As depicted in Figure 1, all vehicles maintain their lanes without any lateral lane-changing. The traffic flow includes a mix of human-driven vehicles (HVs) and the CAV. The HVs adhere to a traditional driving model, while the CAV employs a specifically designed control algorithm for longitudinal following.  
The traffic system enables data exchange through communication technologies at the intersection. Equipped with onboard sensors, the CAV interacts with nearby vehicles to gather real-time data on the speed and position of the vehicle ahead, adjusting its speed to maintain a safe distance. Moreover, the CAV accesses vital SPaT information by connecting with roadside units. These SPaT data allow the system to calculate the remaining green-light time, aiding the CAV in deciding whether to speed up or slow down.
## 3 Proposed Scheme: RSP-Based Message Authentication for VANET
### Revocation  
At any time, if a malicious vehicle is found using the information of anonymous identity that is claimed by the malicious vehicle, and the registration table is recorded in all RSUs, then the ORG, PRGs and NRGs of the malicious vehicle will be explored and revoked by the TA and all RSUs, so the malicious vehicle will not be able to request any new registration information in the next time slot. Only ORG revocation must always be recorded. Revoked PRGs and NRGs can be withdrawn in the next two time slots. Thus, the overhead of the revocation list is small. To trace the original registration information, all RSUs must keep a record of registration information for one day. The overhead of recording the registration table is also light.  
For example, vehicle \(i\) registers its original registration set in TA with its real identity as the information in Table 5.1. At \(T_{t\text{-}2}\), it registers a new registration set in RSUa, \(\{ID_{Ra},T_{t\text{-}2},IDS^{\prime}_{vi},DS^{\prime}_{vi},PRS^{\prime}_{vi}\}\) with its anonymous identity, \(\{ID_{TA},T_{\text{0}},ID_{vi},DS_{vi}\}\) as the information in Table 5.2. Then, the vehicle obtains a new registration set from RSUb and RSUc at \(T_{t\text{-}I}\) and \(T_{t\text{ as the information in Tables 5.3 and 5.4. When it was found that it use the anonymous identity \(\{ID_{Rc},T_{t},ID^{\prime\prime}_{vi},DS^{\prime\prime}_{vi}\}\) to perform a malicious attack in time slot \(T_{t}\). According to the information in anonymous identity, Table 5.4 will be checked, and be traced back from Tables 5.4, 5.3, and 5.2 to Table 5.1 in TA. TA will revoke the right of vehicle \(i\), and inform the information about the original registration set and the new registration sets in Tables 5.3 and 5.4 to all RSUs to deny the new anonymous request from vehicle \(i\).
# Monitoring of Structures and Infrastructures by Low-Cost GNSS Receivers
## 3 The Experience
### The Structure of the Bridge and Its Problems  
The bridge has an overall length of 66 m and an average elevation of 8 m. It consists of two side-by-side decks, each of which is made up of two simply supported spans with a span of 31.50 m and consisting of prestressed post-tensioned concrete. Each deck has a width of approximately 16 m and is made up of five reinforced concrete beams connected by five crossebeams and a 20 cm thick upper slab. The structure is located in an area subject to hydrogeological risk. Prior to installation of the GNSS monitoring system, the area was already monitored with piezometers and inclinometers to measure ground displacement and the changes in the water-table level, as well as with a system based on strain gauges installed on the bridge to monitor deck movement with respect to elevation. This system is expected to be able to correlate land displacement with any subsequent displacement of the bridge. The layout, initially composed of three antennas, has been successively integrated with three other points located on the central pier. The GNSS monitoring system has also been installed on some other bridges along the network.