esa-sceva/satcom-chunk-collection huggingface dataset:
# Formation Kinetics and Morphology Characteristics of Natural Gas Hydrates in Sandstone Fractures
## 3 Results and Discussion
### Hydrate Formation
#### 3.1.1 Effect of Fracture Width
Capillary action draws water molecules toward the fissure surfaces, where hydrates preferentially nucleate. Notably, various morphological characteristics of the hydrate were observed under varying fracture widths, as shown in Figure 8. Furthermore, in fractures with a 3 mm width, the hydrate predominantly adopts a dense, strip-like morphology (Figure 8(A1,A2)). This is due to the narrow fracture space, which limits the development of the hydrate's morphology, causing it to grow primarily along the fracture sidewalls, thereby forming a dense, strip-like structure. In fissures with a width of 6 mm, the increased fissure space promotes additional reactions and expansion of hydrates at the gas-liquid interface, with the morphology transitioning from a strip-like to a plate-like structure (Figure 8(A3,A4)). This transformation can be attributed to changes in the flow conditions within the fissure, which increase the contact surface between the gas and liquid. The expansion of the hydrates within the  
Figure 6: CH\({}_{4}\) gas consumption curves during the hydrate formation process under different fracture widths. fissure is influenced by fluid dynamics, thereby facilitating the formation of plate-like hydrates. An additional increase in fissure width (10 mm) encourages a looser morphology of the hydrates, leading to the formation of a flocculent structure (Figure 8(A5,A6)). This is because, in larger fissure spaces, the diffusion of gas and water molecules becomes freer, and the formation of hydrates is no longer constrained by narrow spaces, thereby forming a more loosely structured, flocculent morphology.
# Re-Keying Scheme Revisited: Security Model and Instantiations
## 7 Discussion
### Construction of \(g\)  
If \(g\) is resistant to the SCAs, our schemes are theoretically resistant to the SCAs. Therefore, our aim is to construct \(g\), which consists of operations with less side channel leakage and/or easily-added countermeasures against the SCAs.  
Generally speaking, the non-linear operations, such as SubByte in AES [13], tend to leak the side channel information. The implementations of these operations tend to be complicated circuits, which require much power consumption, including the meaningful information. Moreover, from the implementability, the inputs and outputs of these operations are restricted by a small bit length. This enables adversaries to guess the inputs and outputs to succeed in the statistics of the SCAs. Therefore, it is better to construct the re-keying function with the simple (linear) operations, rather than the non-linear one, to mix the master secret key and the randomness.  
Note that Theorem 1 requires that \(g\) is a (strong) pseudo-random permutation; namely, it is a one-to-one pseudo-random function if one of \(mk\) and \(r\) is fixed. An example of such \(g\) is a composition of an SCA-free function \(g_{\mathsf{MIX}}\) and a pseudo-random permutation \(g_{\mathsf{PRP}}\). The SCA-free function is, for example, \(g_{\mathsf{MIX}}(mk,r)=mk\cdot T\oplus r\), where \(T\) is a regular \(128\times 128\) matrix consisting of zero or one, and \(mk\cdot T\) is a multiplication of a \(128\times 1\) vector \(mk\) and \(T\). Other examples can be obtained by dividing the above \(T\) into \(64\times 64\) or \(32\times 32\) matrices. In addition, the masking countermeasures are easily applicable to linear functions including such \(g_{\mathsf{MIX}}\).
## 4 Experimental Analysis
### TCReC's Reconstruction Ability to Common Network Traffic  
We implement our novel model TCReC and compare it with existing models: mean padding algorithm, k-Nearest Neighbors (KNN), Recurrent Neural Network (RNN), and Transformer. The raw data of ISCX-VPN-2016 dataset are used to simulate the complete network flows and the flows with lost packets. In order to verify the reconstruction ability of different models for Internet application communication data, we adopt a relatively serious packet loss ratio of 70% using CNN as the classifier, and RAI is used as the metric. The experimental results are shown in Figure 7.  
The results show that TCReC also has a strong ability to reconstruct the network data flow characteristics of common Internet applications, and this ability is better than that of other models. However, we found that the reconstruction ability of TCReC is weaker than that of Transformer in this experiment. Considering that the classifier is CNN in this experiment, we did another comparative experiment. When using LSTM as the classifier, the RAI of TCReC is 94.02%, higher than the 91.68% of Transformer, while other models are still lower than TCReC. This phenomenon, compared with what we observed in the experiment in Section 4.5, is due to the difference in the ability of the detection classification model to recognize features, not the lack of reconstruction ability of TCReC.
# Research on Quantization Parameter Decision Scheme for High Efficiency Video Coding
## 5 Discussion  
In this work, we proposed a quantization parameter decision algorithm by using differential evolution in HEVC, and the algorithm can achieve a bitrate saving. To the best of our knowledge, the proposed algorithm is the first attempt to use differential evolution algorithm to decide the quantization parameter of 360-degree panoramic video. However, due to the rich variety of video data, videos of various resolutions and different complex scenes emerge rapidly and the work of this article also needs further improvement. In the differential evolution algorithm, there are too many CTUs in the video sequence to be encoded, and the problem dimension in the differential evolution algorithm is also larger, resulting in a larger time complexity of the algorithm. With the variety of video, such as 4K, 8K, and various immersive videos with 6 degrees of freedom, this complexity problem will become more and more serious. This high-complexity problem can be solved by improving the differential evolution algorithm. As mentioned in Section 1, the differential evolution algorithm has become a stable and efficient algorithm after years of research, so in the future, attempts can be made to adapt different variant forms of differential evolution algorithms to different video formats. Moreover, the algorithm requires many parameters; changing the parameters in the algorithm, such as mutation factor or crossover rate, to try different parameter combinations is also an optimization scheme. Quantization parameter is an important parameter in the process of video coding; lower quantization parameter can improve the quality of reconstructed video, and the bitrate will be increased accordingly. Therefore, it is very important to choose the quantization parameters effectively and reduce the bitrate to save network bandwidth while keeping good video quality. However, in previous studies, there have been few schemes for optimizing quantization parameters in 360-degree panoramic video. This paper makes full use of the data characteristics of 360-degree panoramic video and allocates quantization parameter values for each CTU row of each frame, which can achieve the effect of saving bitrate, thus saving transmission resources.
## 5 CNN-SSAE Neural Network
### Convolutional Neural Network  
The network structure of the CNN is shown in Figure 7 and the parameters of it are presented in Table 1. The CNN can transform the two-dimensional spectrogram into one-dimensional deep features to capture the emotional information of the speech. The characteristics of the CNN proposed in this paper are as follows: (1) After adding the batch normalization (BN) layer to the convolutional layers Con1, Con2, Con3 and Con4, the structure of the whole network is regularized to prevent overfitting, allow a higher learning rate, greatly improve the training efficiency, and solve the vanishing gradient problem. (2) The Global Average Pooling (GAP) layer is used instead of the fully connected layer. In the fully connected layer, a sub-region of each feature subgraph is set for averaging, the sub-regions are slid, and finally, all the average values are connected in series. In contrast, using GAP, each feature subgraph obtains an average value; this increases the emotional information somewhat, reduces the number of parameters, realizes model compression, and improves efficiency.  
The deep features of the spectrogram obtained by the CNN may be redundant. Therefore, an SSAE is adopted to further optimize the deep features, reduce the number of dimensions, and improve the recognition rate.
# Anomaly Detection in Elderly Health Monitoring via IoT for Timely Interventions
## 2 Materials and Methods  
In the 21 st century, European countries are experiencing population aging, which is exacerbated by the crisis in their health systems. Most countries face a lack of personnel and a decrease in birth rates. The long-term effects of these two problems have led to a shortage of personnel to provide palliative care for the elderly. This paper proposes a comprehensive solution that integrates embedded technology with modern systems for analyzing and providing real-time alerts on the health status of elderly individuals who do not have serious health issues. The bracelet device uses a heart rate sensor mounted on an M5 Stack (produced by M5 Stack Technology Co., Ltd., Shenzhen, China) to capture the average heart rate. The system also integrates a preventive component that monitors other parameters whose values could indicate precursor events of an imminent incident. For this identification, the prototype bracelet monitors average heart rate (AR), minimum heart rate (mR), maximum heart rate (MR), number of steps taken (S), deep sleep time (DST), and superficial sleep time (SST). The integrated system uses Azure cloud infrastructure for automatic alert generation and critical event management. In this way, medical staff can intervene to save the lives of those in need.  
This section provides an overview of the proposed system's technical specifications before detailing individual components to ensure a clear and structured approach.  
The proposed system comprises a wearable bracelet equipped with a MAX30100 heart rate sensor (manufactured by Analog Devices Holdings Co., Ltd., Shanghai, China) and an MPU-6050 accelerometer (produced by TDK InvenSense, Shenzhen, China) for tracking steps and sleep. Data is continuously transmitted to an Azure-based cloud platform via secure Wi-Fi communication. The cloud infrastructure preprocesses the data, applies anomaly detection algorithms, and triggers alerts when necessary.  
HADA is designed to analyze six key physiological parameters: AR, mR, MR, S, DST, and SST. The algorithm utilizes PCA to identify deviations from expected trends, enabling personalized health assessments based on individual baseline data. The system periodically retrains HADA to account for changes in patient conditions, ensuring adaptive and accurate monitoring.  
Once processed, data is securely stored in an Azure SQL Database. Alerts are generated and transmitted via Azure Communication Services, including SMS notifications to caregivers if an anomaly is detected. This ensures rapid medical intervention in critical situations.
## 2 Applications of HREM
### HREM in Embryo Research
#### 2.1.2 Chick Embryos  
Chick embryos of very early to late developmental stages were already examined, as shown in Figure 2. Embryos of the blastoderm stage [90; 91] were used for researching the effect that the storage of eggs has on embryonic development and viability. Embryos of late developmental stages have been successfully used for analysing the effect of hemodynamic alterations on the topology and remodelling of the cardiac outflow [72], and for producing metric definition of the dimensions of the great intrathoracic arteries to serve as reference data for such studies [73]. In addition, HREM analysis of an embryo with cephalothoracopagus malformation was successfully conducted, which permitted the formulation of a novel concept explaining the genesis of this abnormality [92].
## 3 Results and Discussion
### Oxidative Stability Assessment
#### 3.3.3 Total Oxidation Value (TOTOX)  
In the assessment of oxidative stability, to obtain the most accurate and comprehensive information, it is necessary to examine the samples in terms of primary (PV) and secondary (\(p\)-AV) oxidation. Combining the two types of tests (PV and \(p\)-AV), it is possible to calculate the total oxidation of the analyzed samples (TOTOX). This index is calculated as two PV units and one \(p\)-AV [56].  
Figure 5 shows the effect of supplementing sausage samples with the DYBPB and DRBPB on TOTOX values compared to control samples and sausage samples with added sodium nitrite. Significantly higher values were recorded for the control samples (SC, SDC, and SSC), i.e., between 5.286-14.442 compared to the sodium nitrite added samples (1.120-7.333) and those supplemented with DYBPB (0.769-11.771) and DRBPB (0.597-10.788) respectively throughout the 20 days of storage.  
Comparing the data presented in Figure 5, similar to the values obtained in the case of PV and \(p\)-AV and in the case of TOTOX, the dose of DYBPB and DRBPB and the type of heat treatment influenced the results obtained.  
As the dose of DYBPB and DRBPB increased, TOTOX values decreased, with lower TOTOX values recorded for the DRBPB-added sausage samples (0.597-10.788) compared to the DYBPB-supplemented sausage samples (0.769-11.771). The heat treatments applied to the sausage samples also influenced the results with lower TOTOX values for smoked and cooked samples (SSDYBPB and SSDRBPB) (0.597-10.788) compared to smoked and dried sausage samples (DSDYBPB and DSDRBPB) (0.756-11.771).  
Comparing the TOTOX values recorded for control sausage samples with added sodium nitrite (DCN and SCN) and sausage samples supplemented with the DYBPB and DRBPB, it can be stated that the incorporation of the DRBPB into sausage formulations in doses that ensure a level of polyphenic compounds of at least 180 mg GAE/kg of pre-processed meat can replace sodium nitrite for both smoked and dried sausages and smoked and dry sausages. Concerning the supplementation of sausage formulations with the DYBPB, it has been observed that this by-product of processing yellow bell peppers can replace sodium nitrite when used at a dose that provides a polyphenic compound content of 270 mg GAE/kg processed meat.  
A similar trend was also reported in the previous study on the evaluation of tomato by-product supplementation of sausages, where the TOTOX value decreased with increasing dose of by-product used, and in terms of the heat treatment used, smoked and scaled samples showed lower values compared to smoked and dried samples [12]. Similar values were also reported by [PERSON] et al. [57], who evaluated the development of oxidation degree over 3 months in sausages to which rosemary extract and tocopherol were added. After 30 days, the values recorded for TOTOX were 5.78-8.61, compared to the control sample, for which 12.07 was recorded.  
Figure 5: Effect of supplementing sausage formulas with dried bell pepper processing by-products on TOTOX value during storage.
## 3 Results and Discussion
### Wall Shear Stress (WSS)
In addition, no matter which model, the WSS at point 2 was the largest among the four points, which was caused by the impingement and shunting of blood here. At the front-end side branch of LAD, namely point 3, the WSS fluctuation was significantly stronger than in the other models, but the WSS value at this point was the smallest among the four feature points. Here, the low and oscillatory WSS was due to the combination of plaque, eddy currents, and shunts that the blood experienced before entering the site. At the shoulder of the DB bifurcation, that is, point 4, the WSS trend of each model was similar, and there was only a slight fluctuation in the time period of 2.1 s to 2.2 s. It is not difficult to observe the changes in the WSS at the four characteristic points. In the early stage of the cardiac cycle, the difference in the WSS value in the different models was small; however, in the late stage of the cardiac cycle (2.0 s \(\sim\) 2.4 s), the difference in the WSS value was significant. This phenomenon was the result of the combined effect of the blood flow velocity and outlet pressure. The WSS increased with the increasing flow rate and decreased with the increasing outlet pressure. In the early part of the cardiac cycle, the blood flow velocity was lower and the pressure was higher, while the latter part was the opposite. To further analyze the distribution of the WSS in the cardiac cycle, the time-averaged wall shear stress (TAWSS) was obtained after postprocessing, as shown in Figure 12.  
Figure 10: Cloud map of the WSS distribution during the peak systolic period. Figure 11: Line chart of the WSS changes at different positions in the cardiac cycle. Figure 12: The TAWSS contours for the different models. The TAWSS can reflect the changes in the WSS during the whole cardiac cycle and is widely used in hemodynamic analysis [16; 19]. The TAWSS distribution was similar to the WSS distribution during the peak systole. Regardless of the model, the regions with higher TAWSS values occurred upstream of the plaque and at the bifurcation of the circumflex, which was associated with higher flow velocity at these locations. A low TAWSS occurred behind the plaque and on the LAD side of the bifurcated shoulder. Since the TAWSS < 0.4 Pa region is considered to be the region that induces the development of atherosclerosis [19], the circular region in the figure enlarges the plaque location, and only the TAWSS < 0.4 Pa part is retained. It is not difficult to see that the circumferential distribution of plaques can lead to changes in the location of atherosclerotic regrowth areas. In Model 1 to Model 4, the areas of the TAWSS < 0.4 Pa were 22.58 mm\({}^{2}\), 18.64 mm\({}^{2}\), 23.52 mm\({}^{2}\), and 25.65 mm\({}^{2}\), respectively. Assessed by this parameter, the order of plaque further development risk from high to low is: when the plaque is located on the side away from the LCA; when the plaque is located on the side away from the heart; when the plaque is located on the side close to the heart; and when the plaque is located on the side close to the LCX.
## 1 Introduction
Figure 1: Illustrations of power efficiency in RF PA transmitters: (**a**) power losses in a conventional linear-mode RF PA and (**b**) power loss representation in a polar-mode RF PA architecture. To perform the simulations and tests of this work, a set of modulated signals that model the nature of the multicarrier signals of real systems were used. These signals are composed of several analog or digitally modulated channels within the VHF airband. In the case of analog channels, 10 kHz sine wave amplitude modulated (AM) signals with 80% modulation depth were selected. For the digital channels, a signal emulating the dynamic behavior of VHF data link (VDL) signals such as those used in this type of system was generated. This digital modulation is a differential 8-phase shift keying (D8 PSK), at an \(R_{S}=10\) kBd symbol rate and using a raised cosine shaping filter with an \(\alpha=0.6\) roll-off factor. In the following sections, these analog and digital modulations for the tests that were performed are referred to as AM-T and VDL-T, respectively. The transmitted signal can be composed of one (1C-CH), two (2C-CH), three (3C-CH), or four (4C-CH) concurrent channels. To provide some perspective, in Figure 2 the MATLAB-generated power spectral density (PSD) of the main signals (120 MHz, 123 MHz, 128 MHz, and 130 MHz concurrent VDL-T channels) in a polar-mode transmitter shows the demanding power bandwidth requirements of a multicarrier signal, where the large fractional bandwidth required, together with a power spectral density (PSD) of the signal envelope that exhibits high energy content at high frequencies (which increases the dynamic demands of the envelope path), is a concern that leads to a careful choice of the RF amplifier drain supply (\(v_{E}\)) network. Taking this into consideration, this work shows a way of overcoming the problems associated with wide fractional bandwidth VHF polar-mode PAs that allow for good linearity figures to be achieved for the application described. This work is mainly divided into three sections. In the first one, a GaN push-pull class-D PA topology is analyzed, proposed, and implemented to mitigate the distortions of the polar systems originating from the RF PA. In the second section, to verify that the implemented RF PA behaves as expected under high-level amplitude modulations (polar-mode architecture), a wideband high-performance GaN-based EA is designed and implemented with a dynamic performance that is sufficient to amplify the signals used for the tests. The third part shows the results obtained from the polar-mode PA, which consists of the integration of the RF PA and the EA implemented in the previous parts.
# Borehole Trajectory Optimization Design Based on the SAC Algorithm with a Self-Attention Mechanism
## 3 Reinforcement Learning Environment Modeling and Design
### Action Spaces  
In the reinforcement learning-driven trajectory control while drilling, the action space defines the behavior that the agent (i.e., \"virtual drill\") can adopt in each step of decision-making and is the core hub of strategy learning and trajectory adjustment. The action space of the agent reflects the trajectory control commands that can be applied at each time step. In the drilling process, the incremental adjustment of the deviation angle and azimuth angle is the main means to realize the trajectory steering and obstacle avoidance control. The action space is defined as a two-dimensional continuous space:  
\[a_{t}=[\Delta\theta_{t},\Delta\phi_{t}] \tag{13}\]  
The agent can adjust the deviation angle and azimuth angle, respectively, within the radian range and can be designed according to the specific situation according to whether there are obstacles. This range setting combines the actual adjustment ability that can be achieved by the conventional rotary steering tool (RSS) in the wellbore structure to ensure that the trajectory planning results have good constructability.