esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Operation Principle for J-DBN-Based Equalization
### Cost Function of DBN-1 and DBN-2 Equalizers  
#### 2.3.1 Cost Function of the Adaptive DBN-1-Based Equalizer  
As we know, CMA is a typical blind equalizer for OOK or QPSK modulation format with a single reference radius. To reduce the large residual error after convergence, CMA blind equalization can be combined with a DBN-1 equalizer. The corresponding filter tap weight \(h_{nn}\) and the cost function of the DBN-1 equalizer based on the CMA algorithm are defined as  
\[h_{nn}\to h_{nn}+\mu e_{n\_CMA}x(n) \tag{5}\]  
\[J_{n\_CMA}=\frac{1}{2}\sum_{n=1}^{Q}(R_{1}-|O(n)|)^{2} \tag{6}\]  
where \(\mu\) is defined as the CMA convergence parameter, \(R_{1}\) is the constant module of signals, \(O(n)\) is the output of the DBN-1 network, and the input sequence \(x(n)\) in the optimization network is the test signal with a size of \(Q\).  
Figure 2: The proposed J-DBN equalizers: (**a**) schematic diagram; (**b**) architecture.  
The adaptive error function can be defined as \(e_{n\_CMA}=R_{1}-|O(n)|\). In practical terms, we can find the optimum \(\mu\) and tap number to obtain better channel equalization. Moreover, the weight value can be further optimized with the aid of adaptive equalization and the BP algorithm, which can be given as  
\[w_{ij}^{k+}=w_{ij}^{k}-\Delta w_{ij}^{k}=w_{ij}^{k}-\eta\frac{\partial f_{n\_CMA }}{\partial w_{ij}^{k}} \tag{7}\]
# A Survey of Preservatives Used in Cosmetic Products
###### Abstract  
The aim of this study was to indicate the type of preservatives used in selected categories of cosmetic products sold in Poland (part of the EU market) and determine the frequency of their use. The tested products consisted of 200 leave-on cosmetics, viz. body lotions (n = 100) and face creams (n = 100) and rinse-off cosmetics (n = 100) and mascaras (n = 25). The product labels of 325 adult cosmetic products from international brands were analyzed for the presence of preservatives based on the INCI compositions. The survey focused on preservatives included in Annex V of the Regulation (EC) No. 1223/2009 of the European Parliament and Council of 30 November 2009 on cosmetic products. The tested products contained 29 different preservatives belonging to eight chemical groups. Most preservatives were alcohols or their derivatives, carboxylic acids or their salts, or parabens. The most common types were phenoxyethanol, present in 198/325 (60.9%) formulations, followed by sodium benzoate, in 137 (42.2%), potassium sorbate, in 116 (35.7%), benzyl alcohol, in 76 (23.4%), and methylparaben in 33 (10.2%). Also, 33 of the 60 preservatives included in Annex V of Regulation (EC) No. 1223/2009 were not used in any of the tested preparations. In each category of products, the most common were combinations of two preservatives per single product (34.8% of all products), followed by single-preservative products (25.5%) and three-preservative products (19.4%).  
preservatives; cosmetic regulations; frequency of use; market trends; safety testing; sensitization +
Footnote †: journal: Applied Sciences
# Responses of Medicinal and Aromatic Plants to Engineered Nanoparticles +
## 5 Effect of Metalloid-Based NPs on Medicinal Plants
### Silicon and Silica NPs
#### 5.1.2 Elicitor Effect  
Pretreatment of _Calendula officinalis_ L. seeds with 200 mg/L SiNPs resulted in maximal increase of quercetin content in plants grown under 50% FC [287]. Treatment of _Tunacteum_ _parteninium_ L. plants with 25 mM SiO\({}_{2}\) NPs increased the expression of TpGAS, COST, and TpCarS genes, which are involved in the biosynthesis pathway of the secondary metabolites, parthenolide, and \(\beta\)-caryophyllene, when the time increased from 6 to 24 h, and a similar effect on the expression of genes exhibited salinity stress [259]. _Mentha piperita_ L. plants treated with 50 and 100 mg/L SiNPs considerably enhanced the density and diameter of the peltate glandular trichomes, Chl content, net photosynthetic rate, TPC, and EO content, as well as content of secondary metabolites at 150 days after plantation [152].  
_Dracocephalum kotschvi_ HRs elicited by 100 mg/L SiO\({}_{2}\) NPs after 48 h exposure time showed considerable increase in biomass compared to the control and pronounced enhancement of the expression of _pal_ and _ras_ genes, as well as a strong increase in several secondary metabolites was observed as well [163]. SiO\({}_{2}\) NPs and TiO\({}_{2}\) promoted the expression of GPPS, a key gene involved in thymoquinone biosynthesis pathway in _Nigella sativa_ L. plants, TiO\({}_{2}\) NPs being more effective, and a dose of 100 mg/L raised the gene expression more than that of 50 mg/L. The tested NPs acting as elicitors increased the biosynthesis of thymoquinone in plants via upregulation of related metabolic pathway genes [257]. Continuous production of metabolites from plant cultures using nanoharvesting, in which NPs are designed to bind and carry biomolecules out of living cells, was described by [PERSON] et al. [288] who treated _Solidago nemorials_ HR cultures in MS medium with mesoporous SiO\({}_{2}\)NPs (165 nm diameter) functionalized with both TiO\({}_{2}\) (425 mg/g particles) for coordination binding sites, and NH\({}_{2}\) (145 mg/g particles) to stimulate cellular internalization in order to obtain increased production of polyphenic flavonoids. Moreover, observed post-nanoharvesting growth indicating the viability of the roots after nanoharvesting, and thus their ability to synthesize henceforward the flavonoids, suggested that application of NPs can facilitate continuous isolation of many biologically active compounds from living and functioning plant cultures.
# Implementation of a Breast Phantom with Acoustic Properties for Ultrasonic Thermometry
## 3 Methodology
### System Setup and Ultrasonic Signal Acquisition
#### 3.2.3 Signal Acquisition Protocol  
For the ultrasonic inspection, the connection diagram illustrated in Figure 4 was utilized. Initially, the phantom to be inspected was immersed in a water bath (Thermo Scientific, GP05) with a resolution of 0.1 \({}^{\circ}\)C and stability of 0.2 \({}^{\circ}\)C, using distilled water as the coupling medium for the individual phantom configuration. In contrast, for the configurations involving healthy and tumoral cases, the fatty layer serves directly as the coupling medium, facilitating the transmission of ultrasonic waves in both scenarios. The phantom was kept submerged for 24 h at room temperature to stabilize its temperature. The temperature of the phantom was monitored with a resolution of 0.1 \({}^{\circ}\)C.  
Afterward, the water bath's heating system was activated and set to a temperature 1 \({}^{\circ}\)C higher than the initial measurement, gradually raising the temperature until it reached 32 \({}^{\circ}\)C. The ultrasonic transducer, operating at 1 MHz (Olympus, V303, Houston, TX, USA), has a central frequency of 0.92 MHz, a bandwidth at \(-\)6 dB of 58.27%, and a peak frequency of 0.91 MHz. The transducer was placed perpendicularly to the sample and was connected to an ultrasonic pulser (Olympus, 507 PR), operating in pulse-echo mode, with a pulsed input of 100 V and a pulse-repetition frequency of 500 Hz.  
The echo signals were captured using an oscilloscope (Tektronix, DPO2012B, Beaverton, OR, USA) with a sampling rate of 1 GS/s. This procedure was repeated for each temperature of interest between 32 \({}^{\circ}\)C and 36 \({}^{\circ}\)C in 0.5 \({}^{\circ}\)C increments. Temperature stabilization requires an average time of 25 min for every 0.5 \({}^{\circ}\)C increase.  
Figure 4: Connection diagram of the US inspection setup.  
Figure 3: Experimental setup diagram for both cases: (**a**) fat–gland propagation medium (healthy case); (**b**) fat–gland–tumor propagation medium (tumoral case).  
Figure 5 presents examples of raw signals acquired from different phantoms: a single-layer phantom, a bilayer phantom, and a three-layer phantom. The figure highlights the interfaces for each case study along with the corresponding echoes observed during raw signal acquisition. In the one-layer individual phantom, there are two interfaces: (a) Phantom/First Step and (b) Phantom/Second Step. Similarly, the Two-layer Healthy Case also features two interfaces: (a) Fat/Gland and (b) Gland/Hard Wall. In the Three-Layer Tumoral Case, three interfaces are present: (a) Fat/Gland, (b) Gland/Tumor, and (c) Tumor/Hard Wall.
# Multi-Physics Analysis of a Magnetorheological Valve Train with Experimental Validation
## 5 Results and Discussion
### Variable Valve Timing  
VVT is an important control scheme that increases the combustion efficiency of an engine at various speeds, thereby reducing air pollution and fuel consumption. Because of design restrictions, with the proposed valve, only the angle at which the valve opens can be controlled; the valve closing time cannot be controlled. Therefore, the valve closing time was fixed by considering the cam profile. Figure 18 shows the experimental results for opening angles of 145\({}^{\circ}\), 175\({}^{\circ}\), and 200\({}^{\circ}\).  
The experimental results indicated that variable timing could be achieved with favorable control when the opening angle was small. For instance, as shown in Figure 18a, at 145\({}^{\circ}\), the amount of lift was almost 6 mm, similar to the simulation result. This is good for early valve-opening timing control. However, for valve angles of 175\({}^{\circ}\) (late valve-opening timing) and higher, the experimental results indicated that the lifts were 1 mm smaller than those recorded in the simulations, possibly because of the hysteresis characteristics of the MR fluid. Moreover, spring strength, mechanical inertia, and friction cause a lag in the maximum lift. Nonetheless, with the proposed device, the aim was to achieve variable valve profiles; the accuracy of these profiles was not a focus. Figure 19 depicts the different valve timing profiles achieved using the MR valve during the experiments. Even though the accuracy of these profiles was not as expected, the timing flexibility of the MR valve was found to be reliable nonetheless.  
Figure 17: Experimental results with variable valve lift.  
Figure 18: Comparison of variable timing results for opening angles of (**a**) 145\({}^{\circ}\), (**b**) 175\({}^{\circ}\), and (**c**) 200\({}^{\circ}\).
## 4 Discussion
### Extraction of SCO  
Methanol and chloroform are the most common solvents used for SCO extraction, but, due to their high costs and their toxicity, they are not well suited for the scale-up of an SCO extraction process. Therefore, hexane was chosen as the solvent for all the extraction trials. The literature, however, suggests that pretreatment of the biomass is necessary, if hexane is used for SCO extraction [46]. The results of the present work confirm this assessment. The lipid recovery, calculated from the extracted lipid amount and the lipid content of the used biomass according to analysis, was only 37% without pretreatment before extraction. While mechanical disruption increased the recovery, the effect was not satisfactory. When combining mechanical disruption with induced autolysis, the recovery could be increased to 79%. This indicates that induced autolysis is a very effective method for the pretreatment of biomass for lipid extraction, which is in line with the literature [47].  
Since autolysis proved to be so effective, and bead milling is both energy-intensive and difficult to implement in larger scale [32], the extraction in miniPilot scale was performed without prior bead milling. The drop in lipid recovery from 78% in laboratory scale to 52% in pilot scale is mainly attributed to the difference in extraction conditions used in laboratory and pilot scales. For accelerated solvent extraction, high pressure and temperature were used to facilitate lipid extraction. In comparison, extraction in pilot scale was performed at ambient pressure and moderate temperatures.
# Influence of Water Addition on the Latent Heat Degradation of Sodium Acetate Trihydrate
## 2 Materials and Methods  
### Preparation of Macro-Encapsulated Sodium Acetate Trihydrate Samples  
The material characterized in this study was SAT (Sigma Aldrich, BioXtra, 99% purity). Two different samples have been prepared:  
* A reference sample (SAT60%) with a raw fraction of 60.3 wt.% of CH\({}_{3}\)COONa for a comparison with the data from the literature.
* A second sample (SAT58%) where water was added. In addition to a limitation of aging, this concentration was expected to bring stability regarding the supercooling phenomenon [11].  
The samples were prepared from about 330 g of the raw material. For the second sample, the material was heated at a temperature of 70 \({}^{\circ}\)C for melting. This would allow for a better homogenization of the added deionized water (35 g). The sample was vigorously shaken to homogenize the repartition of water in the volume. The second sample was then solidified for transportation.  
As they were solid, the real concentrations of both samples were measured. To do so, a thermogravimetric analysis device ([PERSON], Pegasus 449 F1) was used. About 50 mg of material was taken from preparation and heated until 200 \({}^{\circ}\)C that was above the evaporation temperature of the water and allows for the analysis of a fully dry sample. For the SAT60% sample, the experiment was repeated three times for reliability, and the residual mass \(w_{SA}\) was included between 59.6 wt.% and 61.5 wt.% (in comparison with a theoretical concentration of 60.3 wt.%). In the second sample, the experiments were repeated two times for reliability, and the residual mass of sodium acetate was found to be between 57.2 and 58.3 wt.%, for an average value of 57.7 wt.%. Such differences are assumed to be due to uncertainties.  
After transportation, the samples were again melted for pouring by a syringe into 250 cm\({}^{3}\) bricks (210 \(\times\) 140 \(\times\) 18 mm\({}^{3}\), 4 mm of thickness) that can contain 350 g of SAT. They were made of polymethyl methacrylate (PMMA) that was found to have good chemical compatibility with SAT [17]. The bricks were sealed in order to limit the evaporation of water. The quantity of material was higher than the value used in the usual devices such as DSC (up to 40 \(\mu\)L) or calorimeter (about 10 mL). Its behavior is assumed to be more representative of that of a real system, having usually more than 1 L of PCM [18; 19]. Once the material was solid, the brick was put into the experimental bench, and the analysis was launched.
## 2 Numerical Model
### Model Setup
#### 2.2.3 Model of the Heat-Transfer Channel  
Whereas the porous domain is represented in 2D to depict the spatial temperature profile, we reduce the flow in the HTF channel to 1D on the basis of the flow profile of a plate flow. Due to the small height of the HTF channel (1 mm) and a moderate mass flux, the Reynolds-numbers (Re) range between 900-1000. This indicates that the flow is laminar and far away from the transition to turbulent flow at Re \(\approx\) 2200 [37]. According to Reference [38], compressiblity effects are only relevant for large velocities (i.e., for Mach number larger than 0.3) and are thus neglected. Thus, the Hagen-Poiseuille law describes the momentum balance of the channel flow. The combined mass and momentum balance equation results to:  
\[\frac{\partial\varrho_{g}}{\partial t}-\
abla\cdot\left(\varrho_{g}\frac{K}{ \mu_{g}}\text{grad }p\right)=0, \tag{10}\]  
with the permeability \(K\) for plate flow and the channel thickness \(d\), \(K=\frac{1}{12}d^{2}\) according to the Hagen-Poiseuille law. The energy balance of the HTF channel contains the same terms as Equation (5) reduced by the contributions of the solid phases:  
\[\frac{\partial}{\partial t}\left(\varrho_{g}u_{g}\right)+\
abla\cdot\left( \varrho_{g}\left(\frac{K}{\mu_{g}}\text{grad }p\right)h_{g}\right)-\
abla\cdot\left(\lambda_{g}\
abla T\right)=2\cdot q_{e}. \tag{11}\]The heat exchange between reactive bulk and HTF channel is included by the source term \(q_{e}\), here multiplied with 2 since only half the reaction bulk domain but the complete HTF channel are resolved. The coupling term \(q_{e}\) is addressed in the following section.
## 5 Further Discussion on the Tracking Control Algorithm
### Advantages and Benefits of the Control Approach  
The advantages and benefits of the proposed velocity transformation based control scheme can be summarized as follows:  
* It is suitable for the control of asymmetric vehicles, which makes the dynamics model more realistic than the model with a diagonal inertia matrix;
* In comparison with other algorithms, after the velocity transformation from the modified controller, additional information hidden in the inertia matrix can be obtained;
* It gives ability to estimate the effect of couplings on vehicle behavior in motion (this effect can be studied for various trajectories and vehicles, e.g., to change them);
* It can be used for both diagonal and non-diagonal inertia matrix models to decide whether the simplified model is sufficient.
## 2 State of the Art
### Additional Features of Industry 5.0
#### 2.6.1 Smart Additive Manufacturing (SAM)  
Sustainable manufacturing is the most popular cost-effective approach for current manufacturing industries, as it helps producers execute development plans, reduce pollution, and maximize resource utilization throughout the development lifecycle [57]. AM, also known as 3D printing, is one of the most prominent features of Industry 5.0, and it is used to make manufacturing products more sustainable. In Industry 4.0, AM prioritized customer satisfaction by incorporating benefits into products and other services. Transparency, interoperability, automation, and actionable insights are also facilitated [58]. SAM has the ability to conserve energy while also assisting in the reduction in material and resource consumption, resulting in pollution-free environmental production. To reap the full benefits of Industry 5.0, SAM is combined with integrated automation capabilities to streamline supply chain management processes and shorten product delivery times.
## 2 Materials and Methods
### Dataset
#### 2.1.2 Spectral Bands and Indices
The methodology for flood inundation mapping often relies on spectral indices, which are mathematical formulations combining pixel values from two or more spectral bands, designed to extract specific characteristics of the Earth's surface based on reflectance values from diverse spectral bands, showing the relative abundance or lack of a specific land-cover type, for example, the Normalized Difference Water Index (NDWI), which extracts information about the presence of water bodies and the Normalized Difference Vegetation Index (NDVI), which extracts information about vegetation cover. The NDWI is a fundamental index used in flood inundation mapping, due to its design for water detection, relying on the contrast in the reflectance between the green and NIR bands. The use of this index can be limited by noise emanating from built-up areas, vegetation, and soil, reducing the accuracy of resulting flood inundation maps. To address this challenge, the modified NDWI (MNDWI), shown in Equation (1), incorporates the SWIR band, which enhances the open water features, while diminishing the features of built-up areas, which are often correlated with open water when the NIR band is used. The NDVI, shown in Equation (2), finds utility in both vegetation detection and flood assessment, facilitated by its ability to distinguish between vegetation and water. \[MNDWI=\frac{Green-SWIR1}{Green+SWIR1} \tag{1}\]  
\[NDVI=\frac{NIR-Red}{NIR+Red} \tag{2}\]  
Considering the diverse strengths and limitations inherent to each satellite sensor, this study will assess the images from each satellite, alongside several distinct band-fusion configurations involving data from both satellites. The configurations that will be evaluated are as follows:  
1. Sentinel-1 (VV + VH)
2. Sentinel-2 (All bands)
3. VV + VH + Sentinel-2 (All bands)
4. VV + VH + NIR
5. VV + VH + SWIR
6. VV + VH + NIR + SWIR
7. VV + VH + RGB
8. VV + VH + RGB + NIR
9. VV + VH + RGB + SWIR
10. VV + VH + RGB + NIR + SWIR
11. VV + VH + NDVI
12. VV + VH + MNDWI
## 2 Digital Twins for Next-Generation Networks
### Digital Twins for Access Networks
#### 2.1.3 Vehicular Networks  
In ([PERSON] et al., 2018), [PERSON] et al. propose an architecture to solve (generic) Federated learning (FL) tasks in heterogeneous vehicular networks (HetVNets). In their simulation scenario, road-side units (RSUs) (i.e., cellular BSs or aerial vehicles) act as FL endpoints with FL capabilities/training resources, while vehicles hold data that can be used in training processes. In their approach, DTs of vehicles and RSUs are deployed, and the FL multi-tasks are considered as a matching game between learning task requests and available data within the RSUs range, which must be optimized in terms of training cost and model accuracy.  
Similarly, [PERSON] et al. (2018) deal with optimizing software-defined vehicular networks where the DT acts as a centralized controller of the network, enabling more computation resources than what is available at the edge. In this centralized configuration, the DT controller provides optimal per-flow routing computation adapted to the demands of vehicles. The authors implement a simulation where the vehicular network state is considered as a temporal graph, constructed as a Hidden Markov Model, and the routing scheme optimization is a temporal graph routing task. The centralized DT can run different routing scheme simulations by prioritizing different parameters, e.g., historical routing or vehicle density, and then apply the best routing scheme found to improve routing efficiency, maintenance, traffic flow, and security in the physical network.
## 1 Introduction
### Eigenvalue-based Sensing Schemes  
Moreover, we investigate the performance of four eigenvalue-based sensing schemes under impulsive noise (IN) circumstances using the conventional MIMO channel model and the implementation-oriented model. Specifically, we assess the performance of the eigenvalue-based generalized likelihood ratio test (GLRT); the maximum-minimum eigenvalue detection (MMED), also known as the eigenvalue ratio detection (ERD); the maximum eigenvalue detection (MED), also known as Roy's largest root test (RLRT); and the energy detection (ED) [6] under several IN conditions and system parameters. Although ED is not an exclusively eigenvalue-based detection technique, it can be implemented using eigenvalue information. It has been included in the analysis in this paper for the sake of completeness, also giving support to a broader pool of comparisons.