esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Importance of Surface Modification of SnO\({}_{2}\) ETL
### Thickness
The relative thicknesses of the films at various SnO\({}_{2}\) concentrations were 33 nm (10%), 47 nm (15%), 65 nm (20%), and 98 nm (30%) (as shown in Figure 5a-d). Furthermore, the films exhibit poor continuity when the SnO\({}_{2}\) concentration is 10%, and several groups of islands form, as illustrated in Figure 5e. These surface flaws add to the resistance value. When the content is increased to 20%, as shown in Figure 5f,g,i,k, the electrical conductance increases and the films remain clearly uniform. When the concentration reaches 30%, the reunion scenario manifests, which increases the resistance (Figure 5h,l). Additionally, the thickness of the changed layer affected how well the active materials used light by affecting the light transmittance of the film. The progressive increase in thickness was caused by an increase in the SnO\({}_{2}\) concentration. Furthermore, the concentration, crystallinity, and electrical properties of the SnO\({}_{2}\) film were expected to vary with the thickness of the film [85]. The high crystallinity of SnO\({}_{2}\) enabled efficient charge transport and extraction from perovskite, improving device performance. However, it required SnO\({}_{2}\) to be processed via a high-temperature annealing process, which easily caused the decomposition of SnO\({}_{2}\) and limited its widespread applications in wearable electronic devices [86; 87]. Currently, the low-temperature processing of SnO\({}_{2}\) ETL has accomplished many achievements by retaining material properties comparable to those of high-temperature annealed SnO\({}_{2}\), contributing to further improvement of PSC performance [88]. However, more research is required to determine the impact of the SnO\({}_{2}\) thickness after 250 \({}^{\circ}\)C annealing. Because the thickness can be adjusted by changing the concentration during the spin coating process, the content of the precursor solution was varied. In terms of PV performance and hysteresis, the precursor concentration and annealing temperature were crucial. An approximately 40 nm-thick SnO\({}_{2}\) film with an amorphous nature was discovered to be ideal for obtaining excellent performance with minimal hysteresis because the film morphology contributed to enhancing electron transport and reducing the defects formed in the perovskite crystal structure, which lowered the carrier recombination [70].
## 5 Experimentation, Results, and Analysis
### Performance Metrics
#### 5.2.2 Standard Metrics  
BLEU  
The Bilingual Evaluation Understudy (BLEU) score measures the similarity between the generated and the reference captions by considering precision of n-grams. Mathematically, it is defined as:  
\[\text{BLEU}=BP\times\exp\left(\sum_{n=1}^{N}w_{n}\log p_{n}\right) \tag{24}\]  
where \(BP\) is the brevity penalty, \(w_{n}\) are the weights for each n-gram, and \(p_{n}\) is the precision for n-grams.  
METEOR  
The Metric for Evaluation of Translation with Explicit ORdering (METEOR) takes into account synonyms, stemming, and paraphrases. It is calculated as:  
\[\text{METEOR}=\text{Precision}\times\text{Recall}\times\frac{(1-\text{Penalty}) }{\text{Precision}+\text{Recall}} \tag{25}\]
## 2 Materials and Methods
### Data Analysis
#### 2.4.1 Signal Preprocessing  
A fourth-order, zero-lag, low-pass Butterworth filter was applied to the COP signals with a cutoff frequency of 6 Hz via Nexus motion capture software v2.8 to eliminate any noise present in the signal that could not be attributed to each participant's postural control mechanism. This cutoff frequency was chosen because numerous studies on the frequency content of postural sway have shown that its signal content exists at or below 5 Hz [38; 39; 40; 41].  
As feet together trials were completed using only one force plate, and feet tandem trials were completed using two, the feet together data resulted in only one COP signal, whereas the feet tandem data resulted in two COP signals. In order to compare the two condition types, the two COP signals for the feet tandem trials were combined into one resultant COP for the entire body as follows [4; 42; 43]:  
\[COP_{net}=COP_{L}\frac{F_{zL}}{F_{zL}+F_{zR}}+COP_{R}\frac{F_{zR}}{F_{zL}+F_{zR}} \tag{1}\]  
where \(COP_{L}\) and \(COP_{R}\) are the values of the COP signal from the left and right foot, respectively, and \(F_{zL}\) and \(F_{zR}\) are the vertical forces exerted on the force plates under the left and right foot, respectively.
# Effect of Citrus Fiber on the Rheological Properties of Dough and Quality of the Gluten-Free Bread
## 4 Conclusions  
This study demonstrates the possibility of using citrus fiber as a component of gluten-free formulations based on the mixture of corn and potato starches, in order to improve the nutritional value of bread, modify its structure and slow down staling. The results indicate that the presence of citrus fiber modifies the rheological properties of the dough, increasing the values of storage and loss moduli and zero shear viscosity, and decreasing the compliance and tangent of the phase shift angle. A partial replacement of starch with citrus fiber resulted in a significant drop in apparent viscosity under flow in comparison to control dough. The presence of a highly water-absorbent substance caused structure strengthening in the range of small deformations, while at large deformations allowed easier flow. Thus, the rheological properties of the dough were improved, allowing it to be more susceptible to technological processing, including mixing, transport, and molding. The presence of citrus fiber caused a reduction in bread volume, accompanied by changes in crumb structure, such as a smaller number of pores per area, but greater porosity and increased pore size. The application of citrus fiber resulted in a decrease in hardness, springiness and chewiness of the crumb in comparison to control, and the change was proportional to the applied level of addition. A significant decrease in hardness and chewiness of crumb, caused by the presence of fiber with a high water binding capacity and the elevated water level in the bread formulation, indicates that such an addition could be effective not only for nutritional reasons but also for staling retardation. On the other hand, a decrease in the concentration of structure-forming gums caused by additional water has some negative effects, such as a decrease in bread volume, and an increase in size of pores.  
Conceptualization, J.K. and L.J.; methodology, J.K., L.J., M.W., R.Z.; formal analysis, L.J.; investigation, J.K., L.J., M.W., R.Z.; data curation, J.K., L.J., M.W., R.Z.; writing--original draft preparation, L.J.; writing--review and editing, J.K., L.J., M.W., R.Z.; supervision, J.K. All authors have read and agreed to the published version of the manuscript. This research received no external funding.
# Enhanced Efficient EMT-Type Model of the MMCs Based on Arm Equivalence
## 4 Modelling Process of the Proposed AEM
### Thevenin Equivalent Circuit for Full States  
The full-state Thevenin equivalent circuit is detailed in Figure 8a, where the IGBT \(T_{3}\) is inserted in parallel with \(D_{2}\) to switch the de-blocked or blocked modes. The \(T_{3}\) is ON for de-blocked mode, or OFF for blocked mode. In Figure 8b-d, the paths that current flows through under different states are highlighted in red, respectively. The parameters of the equivalent circuit are listed in Table 1. Here, in blocked mode, \(R_{\text{EQ1}}\) is assigned with \(NR_{\text{on}}\) to account for the conductive resistances of all diodes on the arm.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**State** & **Current Direction** & \(T_{3}\) & **D1** & **D2** & \(V_{\text{EQ1}}\) & \(R_{\text{EQ1}}\) & \(V_{\text{EQ2}}\) & \(R_{\text{EQ2}}\) \\ \hline \multirow{2}{*}{De-blocked} & Positive & ON & OFF & OFF & Equation (32) & Equation (31) & 0 & 0 \\  & Negative & ON & OFF & ON & Equation (32) & Equation (31) & 0 & 0 \\ \multirow{2}{*}{Blocked} & Positive & OFF & ON & OFF & 0 & \(NR_{\text{on}}\) & Equation (39) & Equation (38) \\  & Negative & OFF & OFF & ON & 0 & \(NR_{\text{on}}\) & 0 & 0 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The parameters of the equivalent circuit.  
Figure 8: The The Thevenin equivalent circuit for full states: (**a**) Thévenin equivalent circuit, (**b**) Steady state; (**c**) Positive current at blocked state; (**d**) Negative current at blocked state.  
Figure 7: The Thevenin equivalent process in the blocked state: (**a**) The positive direction of the current; (**b**) The negative direction of the current; (**c**) Thévenin equivalent circuit of the arm in the blocked state.
## 5 Cutter Spacing Optimization and Bit Rock Breaking Simulation
### Analysis of Optimization Results  
Drawing from the correlation between the gleaned design variables and the target quantity and with an objective to optimize the minimum mean cutting force, an optimized mean cutting force of 11.68 kN is achieved when the resultant longitudinal distance 1  
Figure 16: Contour map.  
Figure 15: The picture of Pareto.  
measures 10 mm, longitudinal distance 2 records 10.06 mm, and transverse distances 1 and 2 both equal 7 mm. A numerical simulation of the rock-breaking cutter based on the established parameters and its comparison to the cutting force from the pre-optimized scheme are shown in Figure 17. The data reveal that the peak and fluctuation in cutting force exerted by the optimized cutter during the rock fracturing process are considerably smaller than those experienced prior to optimization. This suggests that the optimized cutter design encounters less resistance, thereby demonstrating enhanced effectiveness in the rock-breaking process. The average cutting force exerted by the optimized cutter is computed to be 10.96 kN, which signifies a reduction of approximately 13.7% in comparison to the 12.7 kN experienced before optimization. Furthermore, the deviation between the optimized forecasted value and the simulated value is merely 6.2%, thereby affirming that the derived mathematical model is significantly reliable.  
To further substantiate the beneficial role of the optimized cutter arrangement scheme in enhancing the drill bit's efficiency, finite element models of rock breaking using pre- and post-optimized cutter arrangement schemes were established in the ABAQUS software. In these models, the mesh size at the contact point between the drill bit and rock is 4 mm, while 12 mm is used elsewhere, as shown in Figure 18a. A WOB of 80 kN and a rotational speed of 210 r/min are applied to the drill bit, with the rock surfaces, except the superior one, remaining fixed. The footage of the PDC drill bit using pre- and post-optimized cutter arrangement schemes is depicted in Figure 18b. The drill bit using the post-optimization cutter arrangement scheme demonstrates superior penetration capacity, attributable to the reduced cutting force from cutter layout optimization, which consequently decreases the resistance encountered during rock breaking and improves the footage of the drill bit. Based on numerical calculations, the footage of a drill bit using a post-optimized cutter layout can reach 263.6 mm, compared to 239.8 mm pre-optimization, indicating a 9.9% improvement in footage. The data imply that a drill bit optimized with the cutter arrangement scheme does not manifest high efficiency in the initial stage of rock breaking but rather in the middle and later stages. As the depth of rock broken by the drill bit increases, the post-optimized cutter arrangement scheme gradually displays higher efficiency than the pre-optimized scheme, suggesting its greater suitability for deep and hard stratum drilling.  
Figure 17: Comparison of cutting forces before and after optimization.
# Wireless Communication Technologies for Smart Grid Distribution Networks +
## 2 Available Wireless Technologies for Smart Grid Communications
### Digital Subscriber Lines (DSLs)  
DSL offers an already-built infrastructure with high-speed data transmission that has previously been exploited in smart grid projects. Its disadvantages are reliability, potential downtime, and the expense of installing and constantly maintaining communication cables.  
In general, wired technologies, such as DSL, PLC, and even optical fiber, are costly for wide-area development, but they offer the most robust communication capabilities. On the other hand, wireless technologies reduce installation costs but have constraints in terms of bandwidth and security options.
## Data and Methods
### Validation Samples for Accuracy Assessment of PALSAR/Landsat Forest Maps  
The result validation is vital to land cover classification studies. Accurate surface coverage samples are fundamental for ensuring the reliability of the result and effectiveness of classification algorithm. The validation data used in this study was from the high resolution satellite images taken in 2010 from Google Earth which has been widely used in validation of land cover products because of its high spatial accuracy [42; 43].  
In this study, we used the stratified random sampling method to acquire the validation samples. According to the FAO forest definition above [44], we attained validation samples from the very high resolution (VHR) remote sensing images of Google Earth circa 2010 to guarantee equal probabilities of obtaining the validation samples. To collect samples, we performed the following steps. First, the sampling was stratified by class (forest layer and non-forest layer) based on the previous PALSAR-based [45], and then the random points were generated by using the ArcGIS software (Figure 5a). Second, according to these random points, we established circles with a radius of 25 m as Regions of Interest (ROIs) which can guarantee the homogeneity of landscape and the accuracy of validation result [46; 47]. If the size of ROI is too small, the location error inherent in satellite images will affect the verification results and create more uncertainty in landscape heterogeneity. At the same time, we abandoned the ambiguous ROIs to ensure the quality of ROI. Finally, the ROIs were put into the Google Earth and interpreted according to the very high resolution images from around 2010 (Figure 5b). Furthermore, we used the Collect Earth (Figure 5c), which is a tool integrating very high resolution imagery from multiple sources (e.g., Google Earth, Being Maps) and also customized imagery in Google Earth Engine. In total, we acquired 2898 ROIs which include 683 forest ROIs and 2215 non-forest ROIs to validate the forest products in this study.  
Figure 4: The PALSAR-based forest map (**a**) and the Landsat-based vegetation/non-vegetation map (**b**) in the Loess Plateau in 2010.
## 3 Results and Mechanism Analysis  
### Uniformity Analysis of Remolded Specimens  
#### 3.1.1 Influence of the Sample Height on Uniformity  
Figure 4 exhibits the variations in the layered dry densities of samples with overall heights from 8 to 16 cm under different designed dry densities. When the designed dry density and moisture content were fixed, the stratified dry density of the sample was found to decrease with the increase in the stratified thickness. The smaller the delamination thickness, the closer it is to the top of the sample; when the layer thickness is small, the dry density of the sample is larger than the designed dry density. With the increase in the overall height of the sample, the layered dry density curve tended to be flat and close to the designed dry density. At this time, the overall change in the remolded sample was represented by the upper part being denser than the lower part. The reason may be that with a higher sample height under the same dry density, the arrangement of soil particle aggregates yields during compaction, and there are greater the number of particles in the same volume of soil, resulting in a reduction in the number of pores. At the same time, the space where water can exist is reduced, and the channels through which water and air can move become smaller [32]. A small number of through-pores are gradually blocked with the increase in the delamination height of the sample, resulting in the gradual stabilization of the dry density and better uniformity.  
Figure 4: The variation in the dry density of the loess samples.
## 6 Simulation Results and Discussion
### Throughput Comparisons
#### 6.1.2 Throughput Comparisons for the Linear Topology  
As explained in the first set of experiments, when the application's topology is linear, less buffering is required, and this has a positive effect on the throughput performance. One can easily see an increase in the numbers of streams being processed, while the curves appear to have an increasing (positive) slope over time, which is not the case for the random topology. Between the two scenarios, again, the first one seems to achieve better performance by an average of 20%, as the second scenario necessarily requires more data streams to be buffered; thus, it adds overheads. Again, in both cases, our strategy outperforms its competitors. Figures 6 and 7 show the throughput performance for the random topology under the first and second scenarios, respectively.  
Figure 4: Throughput comparisons with a random topology for the first scenario: \((u>v>w)\).  
Figure 5: Throughput comparisons with a random topology for the second scenario: \((v>u>w)\).
# A Novel Magnetic Coupling for Miniaturized Bandpass Filters in Embedded Coaxial SIW
## 1 Introduction
To do that, a novel magnetic coupling structure is proposed and studied in detail to demonstrate the feasibility of implementing such wideband filtering responses, while keeping a high miniaturization degree and a fully packaged solution. Thus, the use of the LTCC technology enables a multi-layer implementation of the filter couplings, as well as the deployment of bigger embedded loading capacitances, achieving improved performance if compared to conventional magnetic irises.
# A Physical Layer Security Enhancement Scheme under the Ambient Backscatter System
## 3 IANT Scheme Design
### Design of Reader Side Scheme
#### 3.1.2 The Second Sub-Slot  
In the second sub-slot, we select the tag to generate artificial noise and the other tag to transmit confidential information. The tags with the best and worst channel quality among all tags are selected respectively. The channel quality between tags and reader is determined by the following criteria:  
\[i=\underset{i\in K}{\mathrm{argmax}}|h_{k}d_{k}\eta_{k}|,j=\underset{i\in K \backslash\{i\}}{\mathrm{argmax}}|h_{k}d_{k}\eta_{k}| \tag{8}\]  
After the tag selection is completed, the reader first broadcasts a message notifying all tags of the result of the data tag selection. The message consists of \(K\) bits, all of which are '0' except the \(i\)-th bit. Next, the selected data tag responds to U bits, where U represents a binary representation of the index of the selected tag, and the other tags do not send any information. After the reader receives the response, the above process will be repeated, the artificial noise generation tags in response to U bits of the reader broadcast message.
###### Abstract  
This study presents a comprehensive kinetic analysis of sulfamethoxazole (SMX) degradation by the photo-Fenton process, highlighting its potential for removing emerging micropollutants in water treatment. The degradation of SMX followed pseudo-first-order kinetics, with increasing Fe(II) concentrations significantly accelerating the oxidation rate. A kinetic model was developed to describe SMX removal, aromaticity loss, and color changes during treatment. Although SMX was rapidly eliminated, intermediate aromatic and chromophoric compounds persisted, requiring extended reaction times for complete mineralization. The kinetic modeling of aromaticity and color revealed distinct degradation pathways and rate constants, showing a strong dependence on iron dosage. The formation of nitrate and sulfate was used to monitor nitrogen and sulfur mineralization, respectively. Optimal nitrate formation was achieved at 22 mol SMX: 1 mol Fe(II), beyond which excessive iron promoted radical scavenging and the formation of stable Fe-aminophenol complexes, inhibiting complete nitrogen oxidation and aromatic degradation. Moreover, excessive Fe(II) led to increased water coloration due to complexation with partially oxidized aromatic byproducts. These findings emphasize the need for optimized catalyst dosing to balance degradation efficiency and minimize secondary effects. The proposed kinetic models offer a predictive tool for improving photo-Fenton-based treatments and integrating them with biological processes to enhance micropollutant bioremediation.  
stiffamethoxazole; photo-Fenton process; kinetic modeling; aromaticity degradation; color removal; nitrate and sulfate formation; iron complex Article
# Application of Natural Antioxidants from Fruits Waste for Improving Egg Quality Characteristics
## 4 Fruit Waste Bioactive Compounds and Antioxidant Potential
Berries' waste and pomaces (blueberry, raspberry, chokeberry, elderberry, and strawberry) contain high levels of phenolic compounds, especially anthocyanins that can help neutralize free radicals and protect against oxidative damage in both poultry and eggs [64; 65]. Other fruit wastes mentioned in the European Commission and FAO reports [40; 42; 47] are papaya peels and seeds, from major producers like India and Brazil, which represent about 25-30% of the fruit's weight [66]. Kiwi skin and core make up about 20-25% of the fruit's total mass. New Zealand, Italy, and Chile are the top kiwi-producing countries and contributors to this waste. Watermelon rind comprises about 30-35% of the fruit, contributing significantly to waste in countries like China, which leads global production [67]. The United States, Turkey, and Iran are major cherry producers, from which the pits and stems contribute to around 10-15% of the waste during processing. Also, countries like China, Romania, and the United States generate considerable amounts of plum waste from pits and skins (about 20-25% of the total weight of the fruit). Lastly, the pear and peach contribute to approximately 20-25% of fruits' waste, produced by China, Italy, Argentina, and Spain (Table 1). \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Fruit Name, Latin Name** & **Plant** & **Fruit Waste** & **Antioxidant Compounds** & **Reported Concentrations** & **Reference** \\ \hline Citrus & & & total polyphenols & 8.04 to 12.16 mg/g GAE & [44; 45] \\ (_Ctrus sinensis x Citrus paradis_) & _Rustace_ & peel & lutein, zeaxanthin & 36.46 to 81.52 mg/kg & [44; 45] \\ \hline Grapes & & & total phenolic acids & 604.7-1160.5 mg/kg & \\ (_Vitis vinifera_) & _Vitacone_ & pomace & total flavonoids & 20.8-84.10 mg/kg & [46] \\  & & & total sulphenes & 9.1–69.5 mg/kg & \\ \hline Apple & & & total polyphenols & 1.1–289.1 mg/g gallic acid & \\ (_Malus domestic_) & _Rustace_ & pomace & total flavonoids & 45–119 mg/100 g fruit & [48; 49] \\  & & & antioxidant activity & 0.034–0.1 mM Trolox & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Antioxidant compounds present in fruits’ waste.