esa-sceva/satcom-chunk-collection huggingface dataset:
# Modeling a Dual-Mode Controller Design
## 1 Introduction  
To improve the efficiency of an adapter operated under light load conditions, the adapter should be operated under discontinuous conduction mode (DCM), primarily due to the low current, zero-voltage-switching characteristic of the main power switch, and the zero-current switching characteristic of the output diode [1; 2; 3; 4; 5]. This can improve the efficiency of the power stage circuit and the power density characteristics [6; 7; 8; 9]. An analysis of the active-clamp fly-back converter was proposed in [10]. In this research, a symmetrical control was used to drive the power switche, and the efficiency improved by 4% compared to the traditional RCD configuration. A fly-back converter with variable frequency control not only provides valley-switching but also reduces electromagnetic interference. Quasi-resonant fly-back (QR) converters operated under low and medium electrical loads are considered satisfactory due to their small size, low cost, and high efficiency. A QRF converter with a discontinuous conduction switching action should be operated in continuous conduction mode (CCM). A QRF converter has a high peak current and high switching loss, which reduces the efficiency of the converter when the main switch is turned off under a heavy load condition [11; 12; 13; 14; 15]. This study used an adaptive valley-switching circuit under a light load condition, and one strategy circuit using a constant limit switch to turn off the timing when the heavy load caused the input current in the fly-back converter to enter the CCM. Moreover, the conduction loss in a fly-back converter is reduced when a heavy load is applied [16; 17; 18; 19; 20; 21]. In recent years, a strategy for mitigating transients of balanced and unbalanced system has been proposed, as presented in [22]. The supplemental strategyof Set point automatic adjustment with correction enabled (SPAACE) has been used to enhance its performance and extend its application to more generic electrical systems. The proposed algorithm had the following characteristics:  
1. A quadratic prediction strategy for SPAACE to increase prediction accuracy.
2. A dead-zone band supplemental strategy for SPAACE to improve set point tracking.
3. An approach to implement SPAACE in unbalanced systems.  
In this paper, a dual-mode fly-back converter is proposed. This converter has the advantages of high efficiency when a light load is applied, and low current stress due to the power switch when a heavy load is applied for low-power applications. In continuous and discontinuous conduction modes, both fixed-off time control and valley-switching control were applied to the converter [23]. This control scheme circuit will be vital for future QRF converters. However, the control method and stability of the converter can be explained using a control design unit. Therefore, this paper describes the operation of a dual-mode control QRF converter and analyzes its stability under dual-mode control.
## 3 Results and Discussion
### Synergistic and Antibacterial Mechanisms of PVA/BC/C-Ag Composite Membranes  
The PVA gel had a 3D network structure that combines with BC, which also had a dense network structure, to form a denser structure (Figure 9). This structure constituted the substrate throughout which silver-loaded biochar was uniformly dispersed to form a PVA/BC/C-Ag composite membrane for bacteriostatic treatment of drinking water. Corn stalks were used as a source of biochar because of  
Figure 8: PVA/BC/C-Ag composite membrane antibacterial curve for _E. coli_ (**a**), SEM of PVA/BC/C-Ag membrane after treatment of contaminated water (**b**), and comparison of the retention rate and antibacterial ability of _E. coli_ after filtration of bacterial suspension with commercial filter paper (50 mm in diameter and 0.22 \(\upmu\)m in pore size) and several membranes (**c**).  
their low cost, environmental friendliness, and sustainability. Because carbonized straw has a large specific surface area, the silver-loaded biochar was prepared for water treatment after loading silver. The main antibacterial effect of the PVA/BC/C-Ag composite membranes derived from the silver, which is widely used due to its broad-spectrum and long-lasting bactericidal properties. The zeta potential analysis showed that the surface of the PVA/BC/C-Ag composite had a positive potential in deionized water (Supplementary Figure S1). The positive charge released by nanosilver destroys bacteria through electrostatic interactions with negative surface charges on cell membranes, causing the cells to rupture. It also interferes with nutrients in the cell, further inhibiting bacterial growth and causing sterilization. A representative ruptured _E. coli_ bacterium can be seen in Figure 8b.
# Comparison of Machine Learning Models for Sentiment Analysis of Big Turkish Web-Based Data +
## 3 Materials and Methods
### Sentiment Tagging  
The sentiment tagging stage was performed to analyze the sentiment of the preprocessed data. Based on the fact that the study consists of Turkish texts, sentiment expressions vary according to the context, and product reviews in the cosmetics industry are created in a specific context. The sentiment tagging process was performed manually and created a sentiment dictionary. In addition, although sentiment analysis has been carried out in various contexts in Turkish texts, no study has been found in the context of Turkish product reviews in the cosmetics industry.  
Sentiment labeling was conducted according to word level and phrase level. Positive words/phrases were given a score of +1, negative words/phrases were given a score of \(-1\), and words/phrases that did not contain any emotion were given a score of 0. In addition, the net score was determined according to the sum of the positive or negative sentiments in a sentence.
## 3 Results and Discussion  
### Protein Concentrates Characterization and Tachno-Functional Properties  
The content of protein (dry basis) found in SPC was 66.1 \(\pm\) 1.5%, this concentration was slightly lower to others reports on _A. platensis_ protein concentrates (69-75%) [19; 31]. The difference in protein concentration may be due to the biomass growth conditions or the protein extraction process, in this regard, the use of pretreatments (sonication or high pressures) for cell disruption as used in [19; 32] and [33] could increase the protein concentration up to 73-85% in the concentrates.  
The WHC and OHC properties of SPC were 0.49 \(\pm\) 0.029 g/g and 3.25 \(\pm\) 0.218 g/g, respectively. The WHC observed for the SPC was very lower than previous reports (3-5 g/g) [17; 20] but similar than the values found by [PERSON] and [PERSON] [32]. In the case of the OHC, it was slightly higher than the reported by [PERSON] et al. (2.5 g/g) [17] but lower than the OHC of the SPC in [20; 32], these studies demonstrated around 6-8 g/g,this enhanced OHC could be attributed to a partial unfolding of the protein structure due to the sonication pretreatment for the protein extraction.  
For soy protein (control) the WHC (18.77 \(\pm\) 1.091 g/g) and OHC (1.48 \(\pm\) 0.126 g/g) were significantly higher and lower (\(p\)! 0.05), respectively, compared to the results of SPC. In related works [34; 35; 36], the OHC of soy protein (1.0-5.5 g/g) agrees with the results of this study. In contrast, the WHC determined herein was higher than previous studies (3.5-6.9 g/g) [35; 36; 37]. The difference in WHC may be due to the processing of the protein or drying methods.
# Lightning-Ignited Wildfires beyond the Polar Circle
## 5 Conclusions  
Within the Arctic, the majority (>75%) of wildfires occurred in Russia. The fire occurrences in Northern America and Scandinavia were ca. 24% and <1%, respectively. Within Russia, the fires mainly (>85%) occurred in Eastern Siberia. Wildfire occurrence increased doubled in the Arctic and tripled in Eastern Siberia in the second decade of the 21 st century. These fires were caused by a warming-driven increase in lightning together with elevated air temperature, which led to a decrease in soil moisture content and, consequently, fuel flammability. The influence of warming-driven lightning on fires was mostly observed in Eastern Siberia (>40% of explained variance). Similar values at a continental scale (Eurasia) and in the entire Arctic are caused by Eastern Siberia's input. Driven by increased lightning occurrence and warming, the fires' occurrence boundary is shifting northward and has already reached the Arctic Ocean coast in Eastern Siberia. Extreme shifts in boundaries synchronize with air temperature extremes (heat waves). Together with the lightning increases, negative trends of moisture parameters may cause a synergy impact on the burning rate in the Arctic. However, rapid GPP recovery, in combination with countervailing positive GPP trends throughout the Arctic, suggests that the circumpolar Arctic continues to serve as a sink for atmospheric carbon. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/atmos14060957/s1](https://www.mdpi.com/article/10.3390/atmos14060957/s1)]([https://www.mdpi.com/article/10.3390/atmos14060957/s1](https://www.mdpi.com/article/10.3390/atmos14060957/s1)), Figure S1: Dynamics of summer (JJA) (**a**) air temperature, (**b**) precipitation, (**c**) soil moisture, (**d**) terrestrial water content, and (**e**) SPEI drought index. Trends are significant at \(p<0.05\) except for (**a**) EastSib, (**b**) FarEast, and (**c**) WestSib (\(p<0.1\)). **Author Contributions:** Conceptualization, V.I.K. ; methodology, V.I.K. and S.T.I; validation, V.I.K., S.T.I. and M.L.D. ; formal analysis, S.T.I., M.L.D., A.S.G. and A.V.S. ; investigation, V.I.K. ; S.T.I. and M.L.D. ; resources, S.T.I., M.L.D., A.S.G. and A.V.S. ; data curation, S.T.I., M.L.D., A.S.G. and A.V.S. ; writing--original draft preparation, V.I.K. ; writing--review and editing, V.I.K. ; visualization, S.T.I., M.L.D., A.S.G. and A.V.S. ; supervision, V.I.K. ; project administration, V.I.K. ; funding acquisition, V.I.K. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the Tomsk State University Development Program (*Priority-2030*). **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** Publicly available datasets were analyzed in this study.
## 3 Results  
### Transmission Characteristics and Impedance between the Transmitter Electrode  
Table 1 gives the transmission characteristics of the one- and two-electrode transmitters. The transmission characteristics were evaluated by the ratio between the received signal amplitude and the amplitude of the transmitter output. The transmission characteristic of the two-electrode transmitter was 26 dB greater than that of the one-electrode transmitter.  
Sensitivity of the electric properties in this simulation was evaluated by changing the values by \(\pm 12\%\). The relative permittivity \(\varepsilon_{\mathrm{r}}\) was changed from 170 to 150 and 190, and the electrical conductivity \(\sigma\) was changed from \(0.62\) S/m to \(0.55\) S/m and \(0.69\) S/m. The transmission characteristics ranged from \(-50.5\) dB to \(-50.0\) dB for the one-electrode transmitter and \(-24.3\) dB to \(-24.0\) dB for the two-electrode transmitter. From these results, it was concluded that the sensitivity was sufficiently low for the present simulation.  
The impedance \(Z_{\mathrm{in}}\) between the transmitter electrode and the ground electrode of the transmitter was calculated. In the case of the one-electrode transmitter, the circuit board was used as the ground electrode. The impedance \(Z_{\mathrm{in}}\) is the total impedance of all external factors viewed from the output terminals of the signal source not including the resistance inside the transmitter. Table 1 gives the calculated values of \(Z_{\mathrm{in}}\). The imaginary part of \(Z_{\mathrm{in}}\) for the one-electrode transmitter was approximately 200 times larger than the real part. This is because the ground is floating in the one-electrode transmitter and the signal path contains capacitive couplings.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Structure of Transmitter** & **One-Electrode** & **Two-Electrode** \\ \hline Transmission characteristics (dB) & \(-50.4\) & \(-24.1\) \\ Impedance between transmitter electrodes \(Z_{\mathrm{in}}\) (\(\Omega\)) & \(33.3-j69.7\times 10^{2}\) & \(79.9-j10.8\) \\ \hline \hline \end{tabular}
\end{table}
Table 1: Transmission characteristics and input impedance.  
Figure 3: Transmitter models: (**a**) One-electrode transmitter; (**b**) Two-electrode transmitter.  
In contrast, the imaginary part of the \(Z_{\text{in}}\) for the two-electrode transmitter was much smaller. This is because there is a direct signal path between the signal and ground electrodes that passes through the human body without capacitive coupling in the air. This result suggests that the electric passing through the human body contributes more to the signal transmission in the two-electrode transmitter than in the one-electrode transmitter. It should be noted, however, that the signal that reaches the receiver is only a small part of the total current that flows out of the transmitter electrode. Therefore, the electric field distribution around the transmitter and the receiver must be investigated to assess the total current.
## 5 Comparison between New and Predeveloped CLSMs  
In this section, the performance of the CLSM developed in this study (i.e., CLSM-10 in Figure 4) was compared with that of predeveloped CLSMs by conducting additional laboratory tests in order to measure their flowability and compressive strength. The predeveloped CLSMs were based on sandy and clayey soils and bottom ash. Based on the unified soil classification system (USCS), each soil was classified into silty sand (SM) and inorganic silt with low-to-medium compressibility (ML). They were collected at a construction site in Boryeng-si, South Korea. The detailed geotechnical characteristics and particle size distribution of this soil are shown in Figure S3 and Table S1, respectively. The bottom ash was collected at a power plant in Pohang-si, South Korea. The chemical properties of the bottom ash are listed in Table S2.  
In order to investigate and compare the flowability and compressive strength of the predeveloped CLSMs with those of the new CLSM, the specimens were manufactured based on previous studies by [PERSON] [17] and [PERSON] [52] on soils and [PERSON] [53] on bottom ash (Figure 6).  
The CLSM developed in this study showed the highest flowability (Figure 6a). This indicated that injecting the developed CLSM into desired locations near underground pipes or culverts could considerably reduce costs. As shown in Figure 6b, the 28-day compressive strength of the CLSM developed in this study was within the standard limit (i.e., from 0.3 to 2.1 MPa). Overall, the developed CLSM possessed a high flowability, which could facilitate placement and re-excavation, as well as provide sufficient compressive strength to support embedded structures, such as pipes, culverts, paved roads, etc.  
Even though the new CLSM developed in this study showed good performance, future studies are needed to analyze several uncertainties as follows: (a) due to its exceptional flowability (i.e., the flowability was 700 mm), the precise endpoint and total quantity and installation timeframe of the CLSM injection in fields should be investigated; (b) in terms of the soundness (i.e., volume stability) of the CLSM specimens, it is less likely that the  
\begin{table}
\begin{tabular}{c c c} \hline \hline \(\mathbf{\phi}\) (\(\mathbf{\lx@math@degree}\)) & **Cu (kPa)** & \(\mathbf{\gamma_{t}}\) **(kN/m3)** \\ \hline
12.4 & 69.3 & 13.8 \\ \hline \hline \end{tabular}
\end{table}
Table 6: The results of triaxial compression test for CLSM developed in this study.  
Figure 6: Comparison of (**a**) flowability and (**b**) unconfined compressive strength between CLSM developed in this study and predeveloped CLSMs [17; 53].  
soundness of the binder would be a major concern, because the microstructure of the CLSM was much looser compared to that of concrete and the proportion of binder was relatively small. However, the soundness of the CLSM should be analyzed based on the acceleration test method proposed by [PERSON] [54] and [PERSON] [55] for field applicability.
## 4 Discussion
### The Diffusion Behavior of Nitrogen Atoms During the Nitriding Process
According to the cross-section, N element concentration changes can be introduced to the thickness of the penetration layer, that is, the larger the deformation variable, the wider the N element distribution area, the thicker the penetration layer, in line with the results observed under the metallurgical microscope. This indicates that deformation can enhance the diffusion of nitrogen atoms, increase the nitriding speed, and promote the growth of the thickness of the infiltration layer. This phenomenon occurs because, during the deformation process, 316L austenitic stainless steel undergoes a martensitic transformation. Martensite possesses a BCC (body-centered cubic) or BCT (body-centered tetragonal) lattice structure, which is less densely packed compared to the FCC (face-centered cubic) lattice of austenite [24]. As a result, nitrogen atoms exhibit a lower diffusion activation energy in martensite, facilitating their movement within the stainless steel matrix. Furthermore, martensite tends to nucleate at defects such as dislocations, and its internal structure contains numerous structural imperfections [25]. Nitrogen atoms also diffuse along dislocations, which are relatively open structures. Consequently, the frequency of atomic jumps along these defects is higher than that of diffusion within the lattice. Thus, dislocations serve as channels for atomic diffusion, further reducing the diffusion activation energy of nitrogen atoms in martensite. In summary, the presence of structural defects, such as dislocations, along with the formation of martensite, both contribute to lowering the diffusion activation energy of nitrogen atoms in the material, thereby accelerating their diffusion rate.
# Ad-BBR: Enhancing Round-Trip Time Fairness and Transmission Stability in TCP-BBR
## 5 Experiment and Evaluation
### RTT Fairness
#### 5.3.1 Static Network Experiments
and BBRv3 algorithms demonstrated better fairness, with the 10 ms stream throughput approaching half of the overall throughput, while the Cubic and Reno algorithms favored short streams, achieving a throughput ratio close to 0.6. Although these trends vary slightly with increased buffer sizes, the overall competitive fairness remains largely unchanged. Under the Ad-BBR algorithm, the throughputs of 10 ms and 50 ms streams are relatively balanced, and the fairness indices are significantly improved, resulting in an approximate 11% enhancement in competitive fairness compared to BBRv1 and about 2% better than BBRv3, an improved version that focuses on RTT fairness.
## 1 Introduction
In this work, we describe the initial step of the InTarsis project, which is the characterization of the deformation field as the baseline for the monitoring of the Riotinto mining, Spain. This paper is structured in two main parts. We begin with a historical review of field deformation in the area using all available data from the ESA radar catalog. Next, we conduct a comprehensive analysis focusing on the unstable zones using ascending and descending Sentinel-1 images. We combine them in a new post-processing method in which we exploit the information provided by each velocity measurement to take advantage of the outstanding resolution capacity of Sentinel-1. Sentinel-1 constellation offers a 6-day revisit time for its pre-defined acquisition mode for land and coastal zones (Interferometric Wide swath IW) with a 5 \(\times\) 20 m ground resolution [9]. Combined with the free and almost instant availability of the data, as its part of the Copernicus observation program, makes Sentinel-1 a good option for monitoring applications [10; 11; 12] and especially in mining environments [13; 14; 15; 16; 17; 18; 19]. The InTarsis project is part of the RawMatCop program, which aims to develop skills, expertise, demonstrations, and applications of Copernicus data to the raw materials sector. It is co-funded by the European Commission (DG for Internal Market, Industry, Entrepreneurship, and SMEs) and the EIT RawMaterials (RM Academy). The EU aims to facilitate the exchange of best practices among its member states to improve the sustainable and safe supply of raw materials to the EU economy and society [20].
## 4 Results and Discussion  
### Multicollinearity Assessment of the Contributing Indicators  
To minimize multicollinearity among input variables, we conducted Pearson correlation analysis between all pairs of the initial 16 contributing factors. Indicators with an absolute correlation coefficient exceeding 0.5 were considered highly correlated. The Pearson correlation coefficients between each pair of the 16 contributing indicators are shown in Figure 8. As a result, plain curvature, roughness, rainfall, and snowmelt were excluded from the final modeling process. Notably, rainfall and snowmelt are the only triggering factors in our dataset.  
The correlation coefficient between elevation and rainfall reached 0.618, while that between elevation and snowmelt was 0.725, indicating strong linear relationships. These findings are consistent with previous research highlighting the influence of topography on precipitation patterns in mid- and high-latitude mountainous regions [47]. For example, [PERSON] et al. [48] reported a significant linear relationship between precipitation and elevation in Northern Xinjiang. Similarly, [PERSON] et al. [49] identified a positive elevation-precipitation relationship during the warm season in Xinjiang. In our study  
Figure 8: Pearson correlation coefficients between each pair of 16 contributing indicators.  
area, warm-season precipitation contributes substantially to the annual total, which further justifies the strong observed correlation.  
Therefore, despite rainfall and snowmelt being triggering indicators, their high correlation with elevation suggests that excluding them will not significantly reduce the model's ability to capture triggering conditions. This approach also helps avoid redundancy and improves model stability.  
Consequently, the final set of 12 contributing factors included in the model were profile curvature, sediment transport index (STI), topographic wetness index (TWI), elevation, aspect, slope, normalized difference vegetation index (NDVI), land cover, distance to roads, distance to rivers, distance to faults, and lithology.  
Given this evidence and consistent with prior studies, excluding the highly correlated indicators does not compromise the comprehensiveness or robustness of the dataset. Similar correlation-based indicator selection procedures have been widely adopted in landslide susceptibility modeling to ensure model stability and interpretability [20; 50].