esa-sceva/satcom-chunk-collection huggingface dataset:
# Substitution of Pork Fat with Beeswax-Structured Oleogels in Semi-Smoked Sausages
###### Abstract  
The expansion of the assortment of low-saturated-fat sausages is a trend in healthy eating, and the use of alternative ways to reduce their saturated fat content is required. This study aimed to partially substitute pork fat with 7% and 10% oleogel, obtained by structuring sunflower oil with a two-component mixture of monoglycer and beeswax, in the recipe for semi-smoked sausage. The physicochemical characteristics of the sausages were evaluated, and the fatty acid profile and sensory properties were analyzed. In the samples where pork fat was partially replaced with oleogel at 7% and 10%, there was a decrease in the content of saturated fatty acids (SFA) by 35% and 38%, respectively. The addition of oleogel to sausages significantly reduced the content of stearic and palmitic acid, increased the content of linoleic acid, and improved the fatty acid profile. The microstructure of the sausages showed a more homogeneous structure with a lower content of large lipid granules as the amount of oleogel added increased. The sensory analysis showed that the addition of 7% oleogel did not deteriorate the organoleptic properties. Therefore, the partial substitution of pork fat with 7% oleogel can be recommended to produce healthy sausages with improved fatty acid profile and sensory properties.  
oleogels; saturated fatty acids; monoglycerides; beeswax; semi-smoked sausages
## 5 Conclusions  
Previous methods to evaluate the rubber membrane penetration effect involve the use of brass rods or the assumption of isotropic specimen, which do not conform to real experimental practices. To this end, a simple experimental procedure is developed for measuring the membrane penetration in this paper. A multiscale triaxial apparatus was designed, and a series of isotropic consolidation drainage triaxial tests were carried out on specimens with different diameters. The following preliminary conclusions are obtained:  
1. The penetration effect of the rubber membrane should not be ignored. The ratio of the membrane penetration to the total volume change for rockfill materials ranged from 13.0% to 39.4%, while the penetration proportion of sandy gravel reached 69.4%. Compared with the small-sized triaxial test, the large-scale triaxial consolidation drainage test can reduce the penetration proportion of the membrane and should be recommended and promoted.
2. There is a great difference in the experimental results of the membrane penetration of rockfill materials and sandy gravel calculated by the former formula, and the former formula is not applicable to all materials. Therefore, the membrane penetration should be corrected by comprehensively considering the particle size and lithology of materials.  
The method proposed in this paper and the developed apparatus has obvious advantages over previous methods in operability and practicability. The unit membrane penetration is deduced from theoretical analysis, and the method is applied to the triaxial tests of rockfill materials and sandy gravel. The equation verified in this paper can be used to calculate the membrane penetration and to further investigate the law of change under different confining pressures.  
**Author Contributions:** [PERSON] wrote the manuscript; [PERSON] edited and revised the manuscript; [PERSON] and C.C. collected the data, drew the Figures and analyzed the data. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was supported by NHRI (Grant Number Y320008 and Y322001).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Orifice versus Converging-Nozzle Grid Turbulence: A Wavelet Perspective
## 4 Results
### Turbulence Intensity  
The root-mean-squared (rms) velocity can be normalised by the cross-sectional-area-averaged velocity (\(U_{mean}\)) to give the relative turbulence intensity. Figure 4 depicts the turbulence intensity (\(Tu\)) contours at 10D downstream of the perforated plate for the OPP and CNPP. It is evident from the plots that \(Tu\) has higher magnitudes for the OPP than that of the CNPP. The turbulence intensity results are summarised in Table 1. At the lower studied wind speed with \(U_{mean}\) of 7.4 m/s, the cross-sectional-area-averaged turbulence intensity (\(Tu_{mean}\)) for the OPP case is 0.115, with the largest deviation of about 6%, whereas the \(Tu_{mean}\) value for the CNPP is 0.108 with a maximum variation of 9%; see Figure 4a,c. At the higher wind speed \(U_{mean}\) of 11 m/s, the \(Tu_{mean}\) value of the OPP is 0.116, 8% higher than that associated with the CNPP; see Table 1 and Figure 4. It is thus clear that the OPP, with zero thickness as far as the freestream wind is concerned, generates cleaner, more homogeneous, and isotropic turbulence. The physics behind this can be associated with the enhanced three-dimensionality of the flow structure in the developing region immediately downstream of the OPP [32] which increases the mixing rate and reduces the grid-shadow effect. Additionally, this is an indication of turbulence decay as the mean flow is essentially uniform and the turbulence has no significant source of sustained energy input. When turbulence is homogeneous and isotropic in nature, the flow is statistically invariant under translational or rotational changes, and it is convenient to work in Fourier or frequency space. Henceforth, we investigate the power spectrum of this fluctuating streamwise velocity using Fourier transform to understand the energy distribution over the frequency domain.  
Figure 4: Turbulence intensity (\(Tu\)) at X/D = 10 downstream for OPP at (**a**) \(U_{mean}\) = 7.4 m/s and (**b**) \(11.1\) m/s, and for CNPP at (**c**) \(U_{mean}\) = 7.4 m/s and (**d**) \(11.2\) m/s.
# A Chaotic Compressive Sensing Based Data Transmission Method for Sensors within BBNs
## 2 Related Work
For data senders, the proposed method can flexibly control the proportion and the quantity of sections to be concealed which may contain critical information, according to different scenarios and application requirements. For example, the transmitted information can be concealed completely by senders without affecting the data recovery quality. In addition, senders could select independently only one or more sections to be concealed. For the data receivers, the information they could obtained varied according to their authorization levels. For instance, the receivers with the restricted authorization could only achieve the very part of data without critical information, while the receivers with the full authorization could recovery nearly intact original information.
# Basins of Convergence in a Multi-Perturbed CR3 BP +
## 4 Application to the Sun-Mars System: Adding the Effects of Phobos and Deimos
### Radiation Effects  
Now, the effects of the Sun's radiation forces are studied. In order to simplify the calculations, the satellites are not included in the simulation since their effect has been proven to be negligible. Since the radiation factor depends not only on the emitting body but also on the characteristics of the infinitesimal mass, we chose to use an arbitrary  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Libration Points** & **Obtained Coordinates** \\  & \(\left(\mathbf{x_{L}},\mathbf{y_{L}}\right)\left[-\right]\) \\ \hline \(L_{1}\) & (0.99525, 0) \\ \(L_{2}\) & (1.00476, 0) \\ \(L_{3}\) & (d1.00000, 0) \\ \(L_{4}\) & (0.50000, 0.86603) \\ \(L_{5}\) & (0.50000, \(-0.86603\)) \\ \hline \hline \end{tabular}
\end{table}
Table 11: Coordinates of the Sun–Mars libration points considering triaxiality effects.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Phobos**[33] & **Deimos**[34] \\ \hline Mass [kg] & \(1.06590\times 10^{16}\) & \(1.47620\times 10^{15}\) \\ Major axis of the orbit [km] & \(9.37600\times 10^{3}\) & \(2.34580\times 10^{4}\) \\ Orbital period [H] & \(7.65\) & \(30.00\) \\ Average movement (approximate) [1/s] & \(3.63108\times 10^{-5}\) & \(9.25925\times 10^{-6}\) \\ \hline \hline \end{tabular}
\end{table}
Table 12: Mars satellite data: Phobos and Deimos.  
value for the radiation factor \(q_{1}=0.4\left[-\right]\) of the Sun and a null radiation factor for Mars (\(q_{2}=0\left[-\right]\)).  
The results are shown in Figures 14-16 and Table 13. Clearly, it can be seen that radiation does have an important effect on the BCs and the libration points.  
In this particular case, one of the collinear Lagrange points (that corresponding to \(x>1-\mu\)) does not appear. So, the system has only four libration points, which are renumbered. That is why the numbering of the points in this case differs from that used before now. In addition, the region converging to \(L_{1}\), the Lagrange point located between the Sun and Mars, enlarges with respect to the areas converging to the other libration points, especially in the broad domain. In the reduced domain, more cells of space converge towards the other Lagrange points. The regions of convergence towards the triangular points remain symmetric with respect to the abscissa axis. Finally, it is also convenient to highlight that the triangular points have moved closer to the Sun, so they are no longer at the midpoint between the Sun and Mars, and the collinear points are located almost symmetrically with respect to the Sun.
# Enhanced Location Prediction for Wargaming with Graph Neural Networks and Transformers
## 4 Experimental Results
### Baseline Methods for Comparison  
To validate the effectiveness and practicality of ELP-Net, we conducted a comparative experiment between the following methods. All models were trained using a dataset split with a ratio of 8:2 for the training and test sets:  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Module** & **Parameters** & **Value** \\ \hline \multirow{2}{*}{Transformer} & Number of heads \(H\) & 8 \\  & Dropout & 0.1 \\ \hline \multirow{2}{*}{GNN} & Depth \(L\) of mix-hop & 3 \\  & Retain ratio \(\alpha\) of mix-hop & 0.05 \\ \hline \multirow{4}{*}{Others} & Learning rate \(\gamma\) & 0.001 \\  & Learning decay rate & 0.7 \\ \cline{1-1}  & Time steps \(T\) & 10 \\ \cline{1-1}  & Weight decay & 0.0001 \\ \cline{1-1}  & Mini-batch size \(b\) & 32 \\ \cline{1-1}  & Epochs & 15 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameter settings.  
* CNN-GRU: The model proposed by [PERSON] et al. [19], combining convolutional neural networks (CNNs) and gated recurrent units (GRUs).
* CNN-MSA-GRU: An enhanced version of the CNN-GRU model with the addition of a multi-head self-attention (MSA) module.
* ELP-Net: Our proposed model, integrating a graph learning layer, graph convolution, temporal convolution modules, and transformer architecture for improved feature representation and prediction accuracy.
# ZSM Framework for Autonomous Security Service Level Agreement Life-Cycle Management in B5G Networks
## 2 Related Work
### Orchestration  
The orchestration layer offers great potential to seamlessly manage diverse domains and, due to the wide range of possibilities it provides, it has attracted the attention of the scientific community. In [PERSON] et al. (2019), an orchestration model is proposed, focusing on providing high availability for service function chains, where multiple VNFs that perform the same function but with different roles (Master or Slaves) are instantiated on distinct servers, generating multiple paths for delivering the same service.  
Recently, lightweight forms of orchestration have gained significant attention due to their shorter deployment time and ease of portability and scalability. In [PERSON] et al. (2019), a survey on container orchestration is presented, where among the identified gaps are container monitoring capabilities, tools, and autonomous features in orchestration frameworks that enable self-healing and self-optimization. In the study by [PERSON] et al. [PERSON] et al. (2019), an open-source Core Network (CN) was orchestrated using Docker Swarm as the manager. Their approach involved deploying multiple nodes with a load balancer and a floating IP to establish a highly available 5G core (5 GC). However, this work primarily leveraged Docker's existing capabilities to demonstrate their applicability in the context of 5G. The orchestration lacked dynamism, and the security measures implemented were rudimentary.  
Nevertheless, these efforts in cloud-based VNF orchestration are critical, as they lay the foundation for NFV orchestration within 5G and B5G cellular networks. Many of these works tend to focus on specific, isolated aspects, often overlooking the involvement of multiple actors across different domains within the overarching management of 5G networks. In contrast, our approach bridges these gaps by introducing autonomous, policy-intent-based orchestration. This enables us to enforce security measures and countermeasures seamlessly, whether applied to standalone VNFs or to E2E network slices covering the entire 5G system.
## 3 Results
### Guided Wave Techniques Results  
#### 3.2.1 Simulation for Guided Waves  
The simulation was performed to understand the constructive and destructive interference of the guided waves in the bonding region and to visualize the spatial distributions in the debonded region in order to understand what to expect in the experimental investigation. The snapshots of the normal distribution along the plane of symmetry at different time frames are shown in Figure 15 where propagation of only A0 mode is evident. In Figure 16a,b, the spatial distributions of the normal displacement for two cases are shown in the left and the middle at 75 us where visually the two cases are almost indistinguishable. Thus, the differential image (Figure 16c) was obtained by taking a difference between the reference case without defect and the case with the defect at 75 us. The differential image plot shows the area, which is most suitable to record the signals to obtain maximum information about the defect. The experimental parameters are selected based on these results. The A-scan results from the case with debonding and case with the perfect bond are shown in Figure 17. The results show that the guided waves in the debonded joint show a higher amplitude than the perfect bond. The results are likely to be caused by the splitting of guided waves in the debonded region, causing constructive interference after the waves have crossed the debonded region.  
Figure 14: Results of the air-coupled through-transmission: (**a**) A-scan; (**b**) C-scan; (**c**) slice at Y = 14 mm.  
Figure 16: Snapshots from simulation (bottom view) of the mirrored model, which shows the normal distributions at the time instant 75 \(\upmu\)s: (**a**) the case with no defect; (**b**) the case with the defect; (**c**) the differential image.  
Figure 15: Snapshots of the normal displacements from COMSOL simulation (side view) of the no defect model at time instants 20 \(\upmu\)s, 55 \(\upmu\)s, and 75 \(\upmu\)s showing propagation of A0 mode.
# Fuzzy Tracking and Control Algorithm for an SSVEP-Based BCI System
## 2 Methods  
A block diagram of the proposed system is shown in Figure 1. First, the subject sits on a chair in front of an LCD screen and focuses on the flickering boxes that appear on the screen. Second, the EEG signals are acquired using electrodes placed on the occipital region of the subject's head. Third, the preprocessing step of the EEG signal removes noise from the signal. Fourth, the features of the EEG signal are extracted by using FFT to derive the energy of each stimulus frequency. Finally, a fuzzy tracking and control algorithm is applied to recognize the appropriate response, which is used to control the air swimmer drone vehicle. A detailed description is provided in the following subsections.
# Energy Efficient Access Point Placement for Distributed Massive MIMO
## 4 Simulation Results
### Analysis with Perfect Environment Information
#### 4.3.2 Value of Radiation Pattern Information  
In most of the current literature on optimizing the AP placement, the radiation pattern of the arrays is assumed to be isotropic, which is, however, unrealistic. This section analyses how power savings are impacted by taking the radiation pattern into consideration. We consider a D-mMIMO system with four 32-element APs. All antenna elements are patch antennas. Two sets of AP placements are generated for each of the five maps. The solutions in set 1 are generated without considering the radiation pattern, while set 2 takes into account the patch antennas. The solutions in set 2 and set 1 are compared in Figure 12, demonstrating an average power saving ranging from 15 dB to 24 dB. This confirms the significance of taking into account the radiation pattern of the antennas, consistent with [5].  
As mentioned in Section 1 considering environment information regarding the potential AP locations is a preposition of considering the radiation pattern. Therefore, the results also imply that it is essential to consider environment information for the AP placement optimization problem.
# Acceleration of Service Life Testing by Using Weibull Distribution on Fiber Optical Connectors
## 2 Theoretical Background  
### Fiber Optical Connector Measurements  
When testing fiber optic functionality, performance is divided into multimode and single-mode fiber [16], and since in practice the single mode fiber is widely employed, this investigation focused on single mode fiber. The main fiber optic measurement test applied to evaluate fiber optics is called attenuation [5], which is caused mainly by bending that can be micro bending or macro bending. The attenuation provokes an exponential loss of the optical power of the fiber, denoted by  
\[P(x)=P_{o}\text{exp}(-\propto z) \tag{1}\]  
In practice, it is applied by using the unit dB (decibel) and Equation (1), rewritten as,  
\[P(z)=P_{o}\times 10^{-\infty/10\text{ dB}} \tag{2}\]  
where \(P(z)\) is the optical power at distance z from the input. \(P_{o}\) is the optical power at the fiber input and \(\propto\) is the attenuation coefficient [dB/km]. On the other hand, in fiber optic single-mode connectors, the insertion loss is among the most critical parameters [10] and it is defined as  
\[IL=10\text{log}\bigg{(}P_{in}\Big{/}P_{out}\bigg{)} \tag{3}\]  
Insertion loss (IL) is measured in dB; \(P_{in}\) is the power input and \(P_{out}\) is the power output.  
Thus, in this investigation the diagnosed failures obtained during the service life and ALT experiments are denotated by their IL measurements requirements. According to the international telecommunication association (UIT) [17], the maximum IL value in a graded index fiber optical connection after environmental or mechanical stress is about \(\leq\)0.4 dB, and for monitoring during stress applied it is about \(\leq\)0.5 dB. The graded index fiber optical connectors are usually measured at the wavelength of 1310 and 1550 nanometers (nm) for IL [3], because for communications applications these are the wavelengths at which single-mode fibers transmit optical power. Here, it is noted that for an optimized fiber connection/coupling that is not submitted to any stress, the IL requirement is about 0.35 dB [18].  
Now, we proceed to review the proportional hazard models that can incorporate the effect of the stress induced in a fiber optical connector while it is performing its function of communication.
# AI-Enabled Intelligent Visible Light Communications: Challenges, Progress, and Future
## 3 Machine Learning in Physical Layer of IVLC
### Optimal Coding
#### 3.5.1 VLC-Based Autoencoder  
End-to-end learning of the transmitter and receiver for communications over a visible light channel was first proposed in [82]. The transmitter and receiver are mapped to the encoder part and decoder part of the autoencoder structure. Symbol-level precoding at the encoder input transfers the original symbols to one-hot vectors. To accurately reconstruct the input from the received signal, the decoder works as a classifier. The transmission channel is built with two fixed weighted layers considering the color crosstalk of optical antennas and additive noise. Then, the categorical cross-entropy function is used to evaluate the loss between the input and the output probability vector of the transmitted symbols. Gradients of symbol errors direct the updating of the encoder and decoder layers through the backward-propagation process. The average symbol error rate performance reflects the superiority of the proposed closed-loop optimized transceiver to a minimum distance maximizing modulation scheme [83]. Apart from the photodiodes-based autoencoder [82; 84], in [85] a convolutional autoencoder structure is proposed for image sensor communication systems. The system utilizes spatially separated LED arrays to convey an OOK-modulated signal and an optical image sensor as the receiver. Convolutional layers are implemented to overcome irradiance spread and lens blur induced by the sensor. The 2D convolution operations of the proposed autoencoder bring performance gain for image-decoding strategies in the simulated ISC systems. Besides the above works on decreasing error rates, the method in [86] takes flicker and illumination levels into account and tries to address real-life application constraints. However, all these works stay with numerical validations. As discussed in Section 2.1, it should be noticed that the channel estimation work is still in a naive stage. Experimental validation of the aforementioned end-to-end communication schemes will suffer performance degeneration due to the unconsidered dynamic nonlinear impairments of devices. To the best of our knowledge, there is still no experimental demonstration of an autoencoder-based VLC system.
# A Simple AMC Antenna for Liquid Monitoring in an Infusion Bag
## 6 Conclusions  
In this paper, an antenna sensor based on an AMC structure is proposed to detect the liquid status in an infusion bag. The sensing system consists of a dipole antenna coupled with an AMC structure, each mounted on opposite sides of the bag. In the without-liquid state, the TM\({}_{20}\) mode of the proposed antenna is excited, achieving a peak gain of 6.45 dBi and an efficiency of 98%, with the antenna operating at 2.4 GHz. Conversely, in the with-liquid state, the presence of a high permittivity liquid shifts the antenna's operational mode to TM\({}_{40}\). At this time, the antenna operates at 2.0 GHz and has a gain of 4.5 dBi. This difference in working statuses realizes the liquid sensing function. To evaluate the effectiveness of the AMC, comparative analyses were conducted on the \(1S_{11}1\) and radiation patterns for three antenna configurations: a dipole antenna, a dipole antenna with a standing pole, and a dipole antenna equipped with an AMC and a standing pole. The \(1\times 4\) square loop AMC surface significantly reduces the interference from the standing pole on the dipole antenna. Consequently, the proposed antenna and the scheme could be used as biomedical wireless sensors for sensing the state of infusion bags.  
Conceptualization, B.Z. and Z.C.; methodology, B.Z. and Z.C.; software, B.Z.; validation, B.Z. and Z.C.; formal analysis, B.Z. and Z.C.; investigation, B.Z. and Z.C.; resources, B.Z. and Z.C.; data curation, B.Z.; writing--original draft preparation, B.Z.; writing--review and editing, B.Z. and Z.C.; visualization, B.Z.; supervision, Z.C.; project administration, B.Z. and Z.C.; funding acquisition, B.Z. and Z.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported in part by National Natural Science Foundation of China under Grant 62271067, and in part by Beijing Key Laboratory of Work Safety Intelligent Monitoring (Beijing University of Posts and Telecommunications).  
Not applicable.