esa-sceva/satcom-chunk-collection huggingface dataset:
# Adaptive Rate-Compatible Non-Binary LDPC Coding Scheme for the B5G Mobile System
## 3 Channel Clustering Based on the K-Means++ Algorithm  
Wireless signals are susceptible to the effect of a variety of physical factors during transmission, such as signal source position, obstacles, antenna gain, transmit power, and so on. In order to ensure the validity and reliability of information transmission, it is necessary to change the transmission code rate according to different channel conditions. We usually use channel estimation techniques to judge the quality of channel states. However, the channel estimation algorithm with computational complexity would reduce the effectiveness of the communication system.  
With the rise of machine learning, more simple and effective methods are used to reduce the complexity [6; 31; 32]. The clustering algorithm is an important unsupervised learning algorithm in machine learning. Because of its flexibility, rapid classifications based on different similarities of data are widely used in various technical fields [47; 48].  
The partition-based clustering algorithm is one of the most commonly used algorithms. Usually, the method based on distance division is used to divide the objects with approximate characteristics into the same cluster. The distances of objects in the same cluster are as close as possible. The distance between objects in different clusters is as far as possible. Partition-based clustering algorithms often need to enumerate the possibilities of all categories in order to obtain an optimal solution.
## 3 Results
### Synthesis and Characterization of CaS nanoclusters
#### 3.1.2 Effect of CaS Clusters in Human Carcinoma Cell Density  
We studied the effect of CaS nanoclusters on the growth and survival of carcinoma cancer cell cultures. The effect of a single dose of a dispersion containing CaS clusters on the density of carcinoma cells as a function of time is summarized in Figure 4. The optical absorption spectrum of the CaS dispersion employed is displayed in the insert. The optical absorption spectrum is characterized by bands around 280 nm and a long wavelength tail that extends to 600 nm, consistent with a mixture of monomers and clusters. Carcinoma cells exposed to the CaS dispersion did not exhibit significant growth with time compared to carcinoma cells not exposed to the CaS dispersion. Indeed, there was a monotonic decrease in the density of carcinoma cells exposed to CaS from 90 to less than 80 cells/mm\({}^{2}\) in the first 72 h following the dose. The density of cells decreased at a rate of (0.10 \(\pm\) 0.1) cells per mm\({}^{2}\) per hour. Carcinoma cells not exposed to the CaS dispersion, on the other hand, exhibited a growth from 70 to about 120 cells/mm\({}^{2}\) in the first 72 h. The rate of increase in the cell density was (48 \(\pm\) 2) cells per hour per mm\({}^{2}\). These results led us to conclude that the dose of CaS clusters reduces carcinoma cell proliferation.
# On the Rollout of Network Slicing in Carrier Networks: A Technology Radar
## 3 Impact of Network Slicing
### TN Slicing
#### 3.3.1 On the Mapping of 3 GPP Slice Information into TN Nodes
For example, in Figure 7A, instead of configuring multiple nextHops for one EP_Transport to allow multiple optional \"links\" between the gNB port and the cell site router, the solution adopted is as follows: to configure one nextHop for each EP_Transport, but have more than one EP_Transport for an EP_N3 to achieve similar load balance or resilience goal.
## 3 Results  
The absorption spectrum and reflection spectrum of the absorber when VO\({}_{2}\) patterns are in the metal phase are shown in Figure 2a. The results show that there are two absorption bandwidths of 90% absorptance reach as wide as 2.32 THz from 1.87 to 4.19 THz and 2.03 THz from 8.70 to 10.73 THz under normal incidence. Moreover, there are also four perfect absorption peaks located at 2.3 THz, 3.6 THz, 8.8 THz and 10.4 THz, respectively. Due to the influence of the polarization angle is one of the most important properties of the absorber, we simulated the absorption spectrum under different polarization angles. Figure 2b is the color map under different polarization angles. Obviously, due to the symmetry of the structure, polarization is insensitive.  
Figure 1: (**a**) Three-dimensional schematic of the absorber. (**b**) Top view of the unit cell.  
The conductivity of VO\({}_{2}\) can be controlled by adjusting the temperature. The change of conductivity can change the dielectric constant of VO\({}_{2}\). Therefore, the absorptance of the absorber can be continuously tuned by changing the temperature. When the conductivity of VO\({}_{2}\) changes from 200 S/m to \(2\times 10^{5}\) S/m, we can tune the absorption from 2% to 94% at the corresponding frequency range, and the central position of the peak keeps unchanged, as shown in Figure 3. When the conductivity is \(2\times 10^{5}\) S/m, VO\({}_{2}\) appears as a metallic phase, and the best performance of the absorber is achieved. The absorption peaks that appear in the two absorption bands of VO\({}_{2}\) at low conductivity can be explained by wave interference theory. The two absorption peaks in Figure 3b are at 3.21 THz and 9.63 THz, while the corresponding vacuum wavelengths are 93 \(\upmu\)m and 31 \(\upmu\)m, respectively. The refractive index in the dielectric layer is \(\sqrt{\varepsilon}\), and the corresponding wavelengths in the dielectric layer are 48 \(\upmu\)m and 16 \(\upmu\)m. The thickness of the dielectric layer is d = 12 \(\upmu\)m, and the length is precisely the corresponding 1/4 and 3/4 wavelengths, which meets the destructive interference condition between reflection and incidence. When the structural phase of VO\({}_{2}\) is not a metallic phase, the position of the absorption peak is determined by the thickness of the dielectric layer. The presence of VO\({}_{2}\) is to tune the amplitude of absorption peaks. As the conductivity increases, the dielectric constant of VO\({}_{2}\) changes, and the insulating phase gradually approaches the metal phase, and the absorptance gradually increases.
## 5 Field Tests and Discussion on Results
### Field Tests for NB-PLC-Based Demand Side Management System
#### 5.1.1 NB-PLC Test over LV Power Lines  
The field measurements for the testing of NB-PLC communication for DSM services are carried out on allocated residential, commercial, and industrial sites. The distance between the sending and receiving ends for NB-PLC signal communication is 150 m for each site. The complete experimental setup is depicted in Figure 1 whereas Figure 5 illustrates the elaborated setup for field measurement when communication is performed on a LV NB-PLC network. A signal of 1 V is injected through one energy meter using Laptop A and is received by a different energy meter using Laptop B. It is important to note that the transmission of the signal should be within the same phase for which phase identification is done before investigating the NB-PLC signal characteristics. The USB Emulation/RS232 (SCI-B) port is incorporated in both sending and receiving end transceivers, which make them compatible with the USB port of laptops to display the transmitted and received signal results. External power supplies are given to the transceiver, thus through energy meters the power grid connection port can transmit the signal into the LV network.  
Figure 4: Signal communication in DSM control technique for SACs.  
Figure 6a-c show the SNR profiles for NB-PLC communication on LV channels of residential, commercial, and industrial consumers. It can be observed that SNR gains vary between \(-10\) dB and \(45\) dB and are high in the residential channels as compared to commercial and industrial consumers. A difference of \(10\) to \(20\) dB can be observed in all three channels. A detailed analysis is presented by box plot analysis in Section 5.4 power consumption of conventional and inverter based air conditioners are compared.
## 3 Results and Discussion
### Volatile Compounds of Cold Brew Samples
#### 3.3.6 Furans with Aldehyde Function  
In this study, furfural and 2-Furancarboxaldehyde, 5-methyl were determined.  
Furfurals have been detected in sugar rich foods such as juice and honey as well as coffee. It is an organic compound in the decomposition of xylose and can be produced under thermal conditions. Three pathways were found to coexist for the formation of furfural:  
1. the Maillard reaction induced by saccharides and nitrogenous compounds,
2. the direct cleavage of pentose,
3. indirect conversion from pentosan, which only made a minor contribution [49].  
The analysis of total xylose in a wide selection of green coffee and the assessment of its fate during processing allowed the derivation of a maximum total xylose limit of 0.40% [50].  
2-Furancarboxaldehyde, 5-methyl (HMF) is formed either by acid catalyzed degradation of reducing sugars or via the Maillard reaction. Fructose was found to be twice as reactive as glucose in the formation of HMF and brown pigments. The reaction consists of a structural change of hexoses into an intermediate 1,2-endiolic form (containing a double bond and containing 2 hydroxyl groups), which rapidly eliminates water. The presence of HMF depends on temperature, pH, sugar concentration and the water activity, which plays an important role in the degradation of sugars. HMF formation increases proportionally with the decrease in water activity, pH and higher temperature of the system [51; 52]. In any case, the heating processes and HMF content can affect the quality of such products.  
The effect of brewing methods on furfural levels was investigated by [PERSON] et al. [53]. Furfural concentrations were reduced after hot coffee brewing, with a slight increase after espresso brewing. Hot coffee preparation contributed to a higher loss of furan compounds (about 87%) compared to espresso brewing (about 47%). This can be explained by additional furan formation during brewing due to high pressure (3.5 bar) and temperature. In a similar research to [PERSON] et al. the furfural content averaged 71 \(\mathrm{\SIUnitSymbolMicro g}\)/mLin espresso [54]. Compared to cold brew coffee, an average result reached 86.8 \(\mathrm{\SIUnitSymbolMicro g}\)/g for furfural and 47.4 \(\mathrm{\SIUnitSymbolMicro g}\)/g for 2-Furancarboxaldehyde, 5-methyl. Only in one sample from profile A (24h 15 \(\mathrm{\SIUnitSymbolMicro C}\)) was the concentration higher than average in relation to furfural. This means that lower coffee roasting temperature decreases the content of this compound in cold brew coffee. The aroma of furfural was described as pungent but sweet, similar to bread, caramel and cinnamon [30]. In the context of HMF, no one sample from profile A was higher than average:very close to an average value with a result of 45.8 \(\upmu\)g/g was A 24h 15 \({}^{\circ}\)C.
## 3 Materials and Methods
### EIM Data Processing and Classification
#### 3.3.2 Fusion Methods
Figure 4: Graphical representation of Gaussian pyramid fusion applied to EIM. C. Weighted average fusion is used to combine images by assigning them different weights depending on the contribution in terms of specific features, such as the global or local similarity, of each input image [38]. This method aims to assign greater relevance to the most significant regions within the fusion context, thereby ensuring the optimal integration of information while maintaining the coherence of the resulting image. Weighted average fusion was based on a linear combination of the intensities of the pixels in the input images (Equation (9)), where the fused pixel value \(I_{\text{fused}}(x,y)\) at position \((x,y)\) is derived from the input image intensities \(I_{i}(x,y)\) using normalized weights, \(w_{i}\), to avoid bias. A decreasing weight scheme was applied from the superficial to inner layers as \(w=[0.2381,0.2032,0.1683,0.1333,0.0984,0.0635,0.0286]\). The outer layers were prioritized, assuming that they may have contained relevant information for diagnosis. In this way, the fused image \(I_{fused}\) integrated the superficial and deep features of the tissue, preserving the variations in the density and contrast (Figure 5). \[\Delta=\frac{1.0-0.1}{N-1}=0.15 \tag{5}\]0  
D. Fusion using Wavelet-PCA is a multi-scale approach that enables the integration of multiple images, thereby optimizing the representation after merging the different layers. PCA was applied to obtain an image that summarized the most significant variance in the set. The first seven principal components were considered to generate a fused image containing the global structure represented by a low-frequency sub-band, \(LL_{\text{fus}}\). Afterward, the surface layer \(PC_{\text{Synt}}^{1}\) was selected as a reference to apply a level-1 Wavelet decomposition using the Daubechies-4 (d2b) filter. From this, the high-frequency bands \(LH_{\text{ref}},HL_{\text{ref}}\), and \(HH_{\text{ref}}\), which contained information regarding the edges and textures, were extracted. The final image was reconstructed using the Inverse Wavelet Transform (IWT), integrating the global structure obtained through PCA and the finer details from the reference image (Equation (10)). Figure 6 shows a schematic representation of this method. \[\Delta=\frac{1.0-0.1}{N-1}=0.15 \tag{5}\]1  
\[\Delta=\frac{1.0-0.1}{N-1}=0.15 \tag{5}\]2 Image fusion using weighted average. \[\Delta=\frac{1.0-0.1}{N-1}=0.15 \tag{5}\]3 Wavelet-PCA fusion applied to EIM images.
# V2X Communication over Cellular Networks: Capabilities and Challenges
## 1 Introduction
These cross-border demonstrations are very challenging as all UCs must be supported with minimal service disruption, even when the serving operator has to change in real time [13]. In the research community, several attempts have been made to define UCs for V2X communications. The authors in [14] created an initial V2X UC description using the early inputs from EU projects and from the Next Generation Mobile Networks Alliance (NGMN). In [15], the authors provided an analysis of UCs presented in research projects and identified tele-operated driving, vulnerable road user discovery, traffic efficiency, and cooperative sensing and movement as the key categories of V2X UCs. Then, the authors investigated which of these UCs could be supported by the technologies available at the time (i.e., LTE-V and 802.11p), as well as new technological enablers (i.e., millimeter wave (mmWave) and vehicular Visible Light Communication-VLC). This analysis did not provide full details in terms of specific performance indicators, such as the delay, reliability, throughout, etc. Further V2X survey papers, such as [16] and [17], mainly focused on testing and security issues, respectively. The success of V2X communications depends on both the level of driving automation and the respective level of support by the cellular networks. Although research projects offer innovative ideas and concepts, 5 GAA and 3 GPP are the main organizations driving the evolution of V2X. As there are a plethora of UCs specified by these organizations, one of the key contributions of our paper is to provide further insight for the most advanced UCs (called autonomous driving and advanced driving assistance by 5 GAA) and identify the commonalities and differences set by 5 GAA and 3 GPP. Moreover, we have thoroughly investigated whether delay and capacity requirements can be supported by existing 4G and 5G networks standards. To do this, we have conducted a complete and detailed analysis of the delay factors of both systems for the control and the user planes and through all communication interfaces (e.g., Uu and PC5) and types of communication (e.g., broadcast, multicast, and unicast). As for the capacity analysis, we have considered 3 GPP's urban grid and have evaluated the needs for the most advanced UCs following evaluation assumptions specified by 5 GAA. The paper also provides a discussion of potential solutions and technological trends that tackle existing shortcomings. The rest of the paper is organized as follows: Section 2 analyzes the UC definitions in 5 GAA and 3 GPP and presents the specified performance requirements; Section 3 discusses 3 GPP's 4G and 5G network architecture designed to support V2X communications; Sections 4 and 5 provide a thorough delay and capacity analysis for both 4G and 5G net works and compare the findings against the UCs' requirements; Section 6 discusses open issues and future trends; and Section 7 concludes the paper.
## 4 Experimental Setup
### Baselines and Experimental Settings  
To evaluate the performance of proposed models, the following baseline models are implemented.  
* **ii-CF**[24]: the similarity score between movies is measured using PCCBaseline with the number of neighbors is set at 40.
* **SVD**[6] and **SVD++**[7]: both models are trained using 40 hidden factors with 100 iterations and the step size of 0.002.
* **NMF**: optimization procedure is a regularized SGD based on Euclidean distance error function [41] with regularization strength of 0.02 and 40 hidden factors.
* **kNN-Content**[38]: PCC\({}_{\text{genome}}\) is used as the similarity measure.
* **kNN-ContentAE-SVD** and **kNN-ContentAE-SVD++**[39]: 600-feature vectors for movies are learned from 1044 NLP-preprocessed genome tags using a 3-layer AE.
* **FM\({}_{\text{genome}}\)**[14]: each feature vector is composed of one-hot encoded user and movie ID, movie gennes and genome scores associated with each movie; the model is trained with degree \(d=2\) and 50 iterations.
* **I-AutoRec**[35]: a 3-layer AE is trained using 600 hidden neurons, and the combination of activation functions is \((Identity,Sigmoid)\).  
In our experiments, the optimal hyperparameters for each baseline method above are carefully selected using 5-fold cross validation to guarantee fair comparisons. For ii-CF model, the number of neighbors is chosen from \(\{10,20,30,40,50,100,150\}\), and the similarity measures implemented are Cos, PCC and PCCBaseline. For SVD, SVD++, and NMF models, the number hidden factors is chosen from \(\{20,30,40,50,60,80,100\}\). These traditional models are reimplemented using Numba compiler ([[https://github.com/numba/numba](https://github.com/numba/numba)]([https://github.com/numba/numba](https://github.com/numba/numba)), accessed on 2 November 2021) to optimize their performances [42]. For I-AutoRec model, the size of the hidden layer is set for \(n\in\{200,400,600,800,1000\}\) units; and the choices of activation functions \(f(\cdot),g(\cdot)\) are experimented with \((Identity,Identity)\), \((Identity,Sigmoid)\), \((Sigmoid,Sigmoid)\). Finally, the regularization strength is tuned \(\lambda\in\{0.001,0.002,0.01,0.02,0.1,1,2\}\) for all baselines.  
In this paper, we have two main contributions. In the following, a novel autoencoder named Half Convolutional Autoencoder is first introduced to capture the fundamental characteristics of each movie from its original Tag Genome. The ability to extract essential features of an HCAE is empirically proven to outperform that of the classical AE and its variants via the application in various RSs. Secondly, through the newly generated representation for each movie, a user's interest is vectorized by the movies she rated.  
Both the movie and user vectors are then adopted to initialize the latent vectors in matrix factorization models, which significantly boosts the precision of the systems.
## 1 Introduction
### Electrochemical Measurements  
All electrochemical measurements were performed in a three-electrode setup: A titanium coated with slurry as the working electrode, a platinum foil as the counter electrode, and Hg/Hg\({}_{2}\)SO\({}_{4}\) as the reference electrode. A solution containing 5 M H\({}_{2}\)SO\({}_{4}\) served as the electrolyte at room temperature. Cyclic voltammograms (CV) and galvanostatic charge/discharge (GCD) were measured by an electrochemical workstation (CHI 660D). Working electrodes were prepared with the as-prepared materials, acetylene black, and PVDF (Polyvinylidene Fluoride) in a mass ration of 8:1:1. The resulting slurry was dropped evenly onto the titanium sheet substrate (1 cm \(\times\) 1 cm), and dried at 70 \({}^{\circ}\)C in a vacuum oven overnight. The loading weight was controlled to be around 2 mg cm\({}^{-2}\). Then, the dried finished electrode was immersed in 5 M H\({}_{2}\)SO\({}_{4}\) solution to infiltrate the active compositions completely. Electrochemical impedance spectroscopy (EIS, Nyquist plots) was carried out in the three-electrode system at an open circuit potential over a frequency range from 0.01 Hz to 100 kHz with a 10 mV amplitude.  
The capacitance values are calculated from cyclic voltammetry curves according to the following Equation (1):  
\[C=\frac{\int_{V_{a}}^{V_{c}}I(V)\times dV}{2\times m\times v\times(V_{c}-V_{a})^ {\prime}} \tag{1}\]  
where \(C\) is the gravimetric capacitance (F g\({}^{-1}\)), \(I\) is the current value of the CV curve, \(v\) is the scan rate of the CV curve, \(m\) (g) is the mass loading of active material, and \(V_{c}-V_{a}\) is the potential window.  
The capacitance values were also calculated from galvanostatic charge-discharge curves according to the following Equation (2):  
\[C=\frac{I\times dt}{m\times(V_{c}-V_{a})^{\prime}} \tag{2}\]  
where \(C\) is the specific capacitance (F g\({}^{-1}\)), \(I\) is the current value of the GCD curves, \(dt\) is the time of the galvanostatic discharging, \(m\) (g) is the mass loading of active material, and \(V_{c}-V_{a}\) is the potential window.
## 2 Methodology
### Case Study in Two Cities with Different Solar Radiation
#### 2.2.2 Benchmark Building Specifications  
Through the investigation of urban residential buildings in Xi'an and Yulin, a typical building was selected as the carrier for this study. The building faces the south, with 26 stories and a floor height of 3 m and a standard unit composed of four households, including two household types. The building area of A-type households is 115 m\({}^{2}\), including three bedrooms, a living room, a kitchen, a dining room, and two bathrooms. B-type households, also with an area of 115 m\({}^{2}\), include two bedrooms, a living room, a kitchen, a dining room, and bathrooms. The south window-wall ratio of one unit is 0.4, while the north window-wall ratio is 0.2. Figure 4a shows the floor plan of a standard unit. Details of the building envelope are provided in Table 1. The building energy consumption and  
Figure 3: Monthly total solar radiation of the two cities.  
Figure 2: Monthly average dry-bulb temperature of the two cities.  
indoor thermal comfort index of this building with no insulation layer, sunvisor, or solar energy utilization were taken as the benchmark for comparison. Considering the influence of building orientation and occlusion on the amount of solar radiation received by the building facade, according to the local residential sunshine hours [41] and fire spacing requirements, the north-south spacing of the residential building was set at 72 m, while the east-west spacing was 13 m. A unit of the middle building was selected as the research object, as shown in Figure 4b.