esa-sceva/satcom-chunk-collection huggingface dataset:
# Composite Kernel Method for PolSAR Image Classification Based on Polarimetric-Spatial Information
## 4 Experiment
### Data Description
#### 4.1.1 Flevoland Data Set  
The first data set is comprised of a C-band RadarSat-2 PolSAR image collected in the fine quad-pol mode. To facilitate visual interpretation and evaluation, a nine-look multi-looking processing was performed before used for classification. A subset with a size of 700 \(\times\) 780 pixels was used in our experiment. Figure 2(a) is a color image obtained by Pauli decomposition, and Figure 2(b) is the corresponding reference map. A total of four classes are identified: building area, woodland, farmland,and water area. Note that the reference map is not exhaustive, and pixels that are not assigned to any class are shown in gray. To use the data set for performance evaluation, labeled pixels are randomly split into two sets that are used as the training set and the testing set. To ensure the stability and reliability of the performance evaluation results while keeping the computational burden within a controllable range, 1% of the labeled pixels are selected as training samples and the rest of the labeled pixels are taken as testing samples. Detailed information about the training and testing set is listed in Table 3.
## 3 Applications  
### Statement of Problem  
The City of Regina is the capital city of the Canadian province of Saskatchewan, located at 50\({}^{\circ}\)27\({}^{\prime}\)17\({}^{\prime}\) N and 104\({}^{\circ}\)36\({}^{\prime}\)24\({}^{\prime}\) W. It is the second largest city in the province, having a population of about 215,000. The City of Regina can be reached by several highways, including the Trans-Canada Highway from both the west and east sides and four provincial highways from other directions. The city is served by the Ring Road, a high speed connection between Regina's east and northwest that loops around the city's east side (the west side of the loop is formed by Lewvan Drive) with future plans to construct another perimeter highway to encircle the city farther out [31]. This type of highway with no traffic lights is one of the important sources of traffic noise, and typical to most Canadian cities.  
To evaluate the performance of traffic noise modelling in different road aging conditions, three locations, namely A, B and C as shown in Figure 2, are selected as the measuring sites. As can be seen from Figure 2, these sites are distributed along the Trans-Canada Highway on which the speed limit is 100 km/h. More significantly, the sites are very close to each other with similar traffic and road construction conditions. Site A is a special site locate along Assiniboine Ave to Wascana Pkwy in the City. Before 4 October 2013, this way was an old pavement before it was repaved with a new pavement. Site B, from Wascana Pkwy to Assiniboine Ave, is paved with new pavement materials and selected for measuring the noise data and comparing to that of the old pavement under very similar conditions. Further, site C, from Albert St to Wascana Pkwy, was formerly old pavement before being paved in the summer of 2012, and experiments were conducted to find the noise effects of the old pavement. As shown in Figure 2, the surrounding environment and road construction conditions of these three sites are similar. There are no barriers or trees which will influence the sound propagation and thus affect the sound measurement, between the road and sound analyzer (as indicated in Figure 3).  
Figure 2: Selection of the measuring sites.  
The sound pressure levels for each selected site are measured by utilizing the B&K Modular Precision Sound Analyzer 2260 produced by Br\(\ddot{\text{u}}\)el & Kjaer in Denmark, as shown in Figure 3a. Sound Analyzer 2260 supports one-channel measurements of environmental noise and noise at work, have a resolution/accuracy from 6.3 Hz to 20 kHz in 1/3-octaves of the frequency range. The setup of the experiments also refers to [PERSON]\(\ddot{\text{e}}\)[PERSON]'s research which considered the impact of traffic flow management on overall noise pressure levels [32]. The layout of the microphone adopted in the experiment is shown in Figure 3b, in which the microphone is placed 1.5 m above the ground and 7.5 m away from the center line of the highway.
# Trace CH\({}_{4}\) Gas Detection Based on an Integrated Spherical Photoacoustic Cell
## 1 Introduction
In this paper, an integrated SPAC is designed and manufactured, and the sensitivity and frequency response of the SPAC are simulated in detail using COMSOL. The first-order radial resonance frequency and the second-order angular resonance frequency of the SPAC are determined. The SPAC is applied in an all-fiber PAS system based on the white-light interferometry (WLI) demodulation algorithm. Even though the PAS system operated at a non-resonant mode, the reduction in sensitivity is fully compensated by the high sensitivity of the acoustic sensor working at the resonant frequency, and a high-sensitivity detection of CH\({}_{4}\) gas is realized. Compared with the other SPACs presented so far, the proposed integrated SPAC has the characteristic of a small volume, and can be used for remote and long-distance measurement of trace gas detection.
## 7 Simulation and Results
### Increasing Number of Hops  
Following results are compared with the number of hops between the source and the sink. The results shown in Figure 18 and Figure 19 are the cumulative results of the simulations with regard to the number of hops between the source and the sink.  
Please note that the number of hops for hotline assisted routing are different than that of all wireless routing. For example three hops of all wireless routing contain all wireless hops whereas three hops of hotline assisted routing contain at least one wired hop (gateway to gateway). This gateway to gateway wired hop can cover more than one hops of all wireless routing.
# Notch Fatigue Life Research Based on Critical Distance Theory
## 1 Introduction
ABAQUS software was used for finite element simulation to analyze the fatigue performance of arc notches of different radii. The fatigue life prediction model at the notch was established by using the critical distance theory, and the influence of the radius on the fatigue life of the arc notch was investigated. A simplified method for the fatigue life analysis of steel box girder diaphragm arc notches is obtained, with a view to providing a reference for fatigue design and the evaluation of steel bridge panel arc notches.
# Volatile, Microbial, and Sensory Profiles and Consumer Acceptance of Coffee Cascara Kombuchas
In Europe, coffee cascara was considered a novel food from 2005 until recently, when it received authorization by the European Food Safety Authority (EFSA) to be used as a food in the European market [6]. Since then, it has been incorporated in bread production as flour [7], added to food matrices like yogurts [8], or used for infusion preparation [2,9]. In the USA, it has been marketed as natural cascara tea. Fermented foods are defined as foods made via desired microbial growth and enzymatic conversions of food components. Microorganisms determine the course and outcome of fermentation processes and contribute to the development of the characteristic properties of the final fermented food [10]. Kombucha is a fermented beverage traditionally consumed in Asia for centuries, and, as trade routes expanded, it reached Europe [11] and other Western countries. It is mainly made of sweetened green and/or black _Camellia sinensis_ tea and a symbiotic culture (SCOBY), which comprises mainly acetic acid bacteria and yeasts, in addition to minor microorganisms [12]. Several potential benefits of traditional kombucha have been reported in vitro and in animal studies, such as antibacterial activity [13,14]; anticarcinogenic activity for colon breast, lung, and prostate cancers [13, 14, 15, 16]; and a hypogricamient effect and weight loss in diabetic rats [17]. Most of these effects are related to the relevant antioxidant [18, 19, 20] and anti-inflammatory activities [15,20] inherent to _C. sinensis_. But kombucha brings about the benefits of being a cold beverage that can be consumed at any time in warm weather, replacing cold drinks. It also increases bioactive compounds' bio-accessibility [21]. In recent years, kombucha's popularity has exploded globally along with the healthier foods trend. The global kombucha market size was valued at USD 2.64 billion in 2021 and is expected to expand at an annual growth rate (CAGR) of 15.6% from 2022 to 2030 [22]. Recently, new raw materials have been added to or have even replaced _C. sinensis_ in the production of kombucha and kombucha-like products. This includes food industry by-products, as sustainable and healthy alternatives [23]. So far, there are no reports on coffee cascara kombucha, other than our recent publication on its potential bioactivity [20]. Considering the potential health-promoting qualities of coffee cascara and the prospect of sustainability in coffee production, this study aimed to elaborate kombuchas from coffee fruit cascara infusions with different fermentation intensities and characterize the SCOBY microbial profiles and changes in the beverages' volatile profile during fermentation, associating these changes with their sensory attributes. We also evaluated the acceptance of the beverages by consumers in Rio de Janeiro.
## 3 Results and Discussion
### Differentiation and Identification of Viable LAB
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Characters**} & \multicolumn{1}{c}{\multirow{2}{*}{**1**}} & \multicolumn{1}{c}{\multirow{2}{*}{**2**}} & \multirow{2}{*}{**3**} & \multirow{2}{*}{**4**} & \multirow{2}{*}{**5**} & \multirow{2}{*}{**6**} & \multirow{2}{*}{**7**} & \multirow{2}{*}{**8**} & \multirow{2}{*}{**9**} & \multirow{2}{*}{**10**} & \multirow{2}{*}{**11**} \\  & **(n = 10)** & & & & & & & & & & \\ \hline Morphology \({}^{1}\) & R & R & R & C & C & C & C & C & C & C \\ Cell arrangement \({}^{2}\) & sc & sc & sc & sc & sc & sc & sc & sc & t & t & lc \\ \(15\)’C & - & + & + & + & + & + & + & + & + & + & - \\ \(45\)’C & + & + & + & - & - & + & - & + & + & + & + \\ pH \(9.2\) & n.d. & n.d. & n.d. & n.d. & - & - & + & + & + & + & - \\ \(6.5\)’NaCl & n.d. & n.d. & n.d. & n.d. & + & + & - & + & + & + & - \\ Resistance to \(60\)’C & + & + & + & - & - & + & + & + & + & + \\ Hydrolysis of: & & & & & & & & & & \\ arginine & - & - & + & - & - & + & + & + & - & + & + \\ asculin & + & + & + & + & - & + & + & + & - & + & - \\ Acid production from: & & & & & & & & & & & \\ arabinose & - & + & + & + & + & + & - & + & + & + & + \\ ribose & - & + & + & + & + & + & + & + & + & + \\ xylose & - & + & + & + & + & + & - & + & + & + & + \\ fructose & + & + & + & + & + & + & + & + & + & + \\ galactose & + & + & + & + & + & + & + & + & + & + & + \\ lactose & + & + & + & + & + & + & + & + & + & + & + \\ sucrose & + & + & + & + & + & + & + & + & + & + \\ glycerol & + & + & + & + & + & + & + & + & + & + & + \\ CO\({}_{2}\) from glucose & - & - & - & - & + & + & - & - & - & - & - \\ \hline \hline \end{tabular} \({}^{1}\) R, rod; C, coccus. \({}^{2}\) sc, short chain; t, tetrads; lc, long chain. Abbreviation: n.d., not determined.  
\end{table} 
Table 3: Phenotypic grouping of the LAB forming biofilms on the wooden table surfaces.
# Multi-Mode Lithium-Ion Battery Balancing Circuit Based on Forward Converter with Resonant Reset
## 5 Experiments and Analysis
### Experimental Results  
According to the conclusion in Section 3, \(\mathrm{T_{S}}=50\) us is chosen as the switching period of the MOSFETs in the experiment since different switching periods of MOSFETs have a small effect on the balancing efficiency, but a large effect on the balancing speed.  
The balancing experiment of an eight-cell lithium-ion battery pack under charging with 1A is performed. Initial voltages are \(\mathrm{U_{B1}}=2.951\) V, \(\mathrm{U_{B2}}=2.898\) V, \(\mathrm{U_{B3}}=2.841\) V, \(\mathrm{U_{B4}}=2.865\) V, \(\mathrm{U_{B5}}=2.921\) V, \(\mathrm{U_{B6}}=3.678\) V, \(\mathrm{U_{B7}}=3.663\) V, and \(\mathrm{U_{B8}}=3.435\) V, and the  
Figure 12: Experiment prototype and experiment platform: (**a**) prototype front side, (**b**) prototype back side, (**c**) experiment platform.  
balancing result is shown in Figure 14. The comparison of the balancing result with the balancing circuit in [35] is shown in Table 4.  
Figure 14: Experimental result of battery balancing under charging with 1A.  
As shown in Figure 14 and Table 4, the balancing time to reach the maximum voltage difference of 0.05 V in the balancing circuit of [35] is about 7250 s. In contrast, only 1260 s is taken to reach the maximum voltage difference of 0.042 V, and the balancing time is increased by 82.5%. Finally, in the proposed balancing circuit, all voltages of the cells converge to 3.151-3.193 V and the maximum efficiency of the proposed balancing circuit is about 83.31%. Therefore, a good balancing effect is demonstrated by the proposed balancing circuit.
# Design of an Active and Passive Control System of Hand Exoskeleton for Rehabilitation
## 2 Exoskeleton Mechanism Description
### Joint Design  
The key problem of the hand exoskeleton design is the design of the joints. The exoskeleton adopts the SPRM with the parallel mechanism as the joint module, which includes the metacarpophalangeal (MCP) joint, the proximal interphalangeal (PIP) joint, and the distal interphalangeal (DIP) joint, as shown in Figure 1b,c. The mechanism has the advantages of the SPRM and the parallel mechanism, which can realize the telecentric motion around the joint center and adapt to fingers of different thicknesses. Meanwhile, by adjusting the lengths between the exoskeleton joints, the exoskeleton can also adapt to fingers of different lengths. In addition, the force exerted by the exoskeleton is perpendicular to the finger bones, which avoids secondary damage [30].
# Evaluation of Adjustment Effects of Highway Guide Signs Based on the TOPSIS Method
## 1 Introduction
In research on the effectiveness evaluation of traffic signs, scholars have approached the topic from multiple perspectives, employing a variety of methods for analysis and assessment [27; 28; 29]. [PERSON] [30] developed an evaluation system for traffic safety facilities by examining their impact on drivers and vehicles, incorporating indicators such as speed and driving trajectories into the framework. [PERSON] et al. [31] developed the guide sign evaluation method to assess the effectiveness of traffic signs through simulation experiments and applied it to the evaluation of traffic signs at intersections. [PERSON] et al. [32] evaluated and classified interchange diagrammatic guide sign complexity, proposing a theoretical framework for quantitative assessment that offers valuable insights for traffic sign design and application. In summary, existing research has made significant progress in areas such as the layout design of traffic signs, information load control, driver characteristics, and evaluation methods. Studies have shown that design elements (e.g., color, font size, contrast, and layout) significantly impact drivers' visibility and comprehension speed, while reasonable control of information load helps prevent information overload and reduces drivers' cognitive burden. Moreover, research indicates that drivers' personal characteristics (e.g., age, experience, and educational background) strongly affect their ability to recognize and understand sign information, suggesting that sign design should accommodate the needs of diverse groups. However, with the continuous expansion of the highway network and increasing complexity of road structures, traditional sign design and evaluation methods face new challenges: (1) Delayed information updates: New or expanded highways often alter travel routes, but signage on certain sections may not be updated promptly, leading to misjudgments by drivers. (2) Increasingly complex information hierarchies: In dense road networks, signs must provide multi-level route guidance to ensure drivers can accurately select directions at complex interchanges. (3) Lack of standardization and consistency: Inconsistencies in information delivery, layout specifications, and continuity among regional signage systems undermine the navigation experience for drivers. (4) Insufficient comprehensive evaluation systems: Existing studies tend to focus on individual design elements or specific case analyses, lacking systematic evaluation models for complex networks. Given these challenges, this study proposes a comprehensive evaluation framework synthesizing insights from driver behavioral analytics, cognitive science principles, and traffic engineering methodologies. By integrating subjective and objective assessment methods, it contributes to the academic discourse on optimizing traffic signage systems for safety, efficiency, and user experience in complex highway networks.
# LoRaWAN Networking in Mobile Scenarios Using a WiFi Mesh of UAV Gateways
## 5 Simulation Results
### Frequency and Duration of Disconnections
In this regard, the DF VSF algorithm seems to experience less disconnections than the LoRaUAV VSF algorithm. This can be explained by the reduced coverage offered by the DF algorithm and the consequent presence of fewer but longer disconnection periods. In fact, a more in depth analysis of the disconnection periods larger than 500 s of the DF VSF algorithm reveals that several GNs remain isolated for more than 2500 s, while, with the LoRaUAV VSF, isolation periods are no longer than 2000 s, meaning that the mesh is able to cover the GNs for a longer time before loosing them definitely. Nonetheless, both VSF algorithms show low performances and a high chance of almost permanent isolation of GNs. This claim is supported by the low AE-PRR results obtained by the VSF algorithms in all the previous sections of this chapter. The CRM algorithm improves the situation. One first observation is that the algorithm is fairer towards teams. In fact, disconnection periods of the same duration are approximately uniformly distributed among teams. This is caused by a better average distribution of the UAV mesh. The second observation is that disconnections are more frequent if compared with the LoRaUAV VSF algorithm operating alone. However, disconnections are shorter and the number of disconnection periods above 500 s is reduced by \(\approx\)1000 units overall, with team 0 and team 1 experiencing the most marked improvements. This means that, albeit partitions are still possible, they either happen much later in the simulation or they are recovered sooner by the system. The introduction of the MP algorithm on top of the CRM algorithm gives some interesting results. First, the frequency of shorter disconnection periods increases in comparison with the results obtained with just the CRM algorithm, especially in the interval \([0,30]\) seconds. This increase can be explained by the numerous connection recovery attempts, some of them successful, others only partially successful because the connection is lost again after some time. The disconnection periods above 500 s remains approximately the same obtained with the CRM algorithm, but with a huge disproportion towards team 2 members for the reasons already explained before in this section. \begin{table}
\begin{tabular}{l c} \hline \hline
**Algorithm** & **Total Average Disconnection Time (s)** \\ \hline DF VSF & 23,199 \(\pm\) 3350 \\ LoRaUAV VSF & 21,826 \(\pm\) 2976 \\ LoRaUAV VSF + CRM & 12,365 \(\pm\) 2258 \\ LoRaUAV VSF + CRM + MP & 11,876 \(\pm\) 1600 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Total average disconnection time and relative confidence interval obtained with different algorithm combinations.
## 3 Results and Discussion
### Adsorption Isotherms
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Langmuir Model**} & \multicolumn{4}{c}{**Freundlich Model**} & \multicolumn{4}{c}{**Sips Model**} \\ \cline{2-11}
**Ionic** & \(q_{m}\) & \(K_{L}\) & \(R^{2}\) & \(K_{F}\) & \(1/n\) & \(R^{2}\) & \(q_{m}\) & \(K_{S}\) & \(1/p\) & \(R^{2}\) \\  & **(mg/g)** & **(mL/mg)** & **(mL/mg)** & **(m)** & **(m)** & **(m)** & **(m)** & **(m)** & **(m)** \\ \hline
[Bmim][BF\({}_{4}\)] & 1577.7 & 4.24 & 0.105 & 0.96 & 144.3 & 0.300 & 0.98 & 2524.1 & 2.67 & 0.512 & 0.99 \\
[Emim][BF\({}_{4}\)] & 1365.8 & 2.31 & 0.178 & 0.98 & 81.5 & 0.341 & 0.98 & 2100.9 & 1.47 & 0.569 & 0.99 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Fitting parameters of isotherms (Langmuir, Freundlich, and Sips models) for adsorption of ionic liquids ([Bmim][BF\({}_{4}\)] and [Emim][BF\({}_{4}\)]) onto ion-exchange resin (Amberlite IR 120 Na). Figure 5: Langmuir, Freundlich, and Sips isotherms for adsorption of ionic liquids ([Bmim][BF\({}_{4}\)] and [Emim][BF\({}_{4}\)]) onto ion-exchange resin (Amberlite IR 120 Na). The value of \(1/n\) is indicative of the type of adsorbate-adsorbent system as follows: irreversible (\(1/n=0\)), favorable (\(0<1/n<1\)), or unfavorable (\(1/n>1\)). For [Bmim][BF4] and [Emim][BF4], the values of \(1/n\) were 0.300 and 0.341, respectively, further proving that two ILs are adsorbed favorably by the ion-exchange resin during this study. The Sips model is a composite of the Langmuir and Freundlich models with three parameters [39]. It can be employed to predict the heterogeneous adsorption systems and circumvent the limitation of the rising adsorbate concentration associated with the Freundlich isotherm [35]. For a homogeneous surface, \(1/p\) is equal to 1, while when \(1/n\) is between 0 and 1, this suggests the surface of adsorbent is heterogeneous [40]. It can be seen from Table 4 that the Sips model (with R\({}^{2}\) reaching 0.99) reproduced the adsorption experimental data better than the [PERSON] and Freundlich models, which could also be demonstrated graphically in Figure 5. Accordingly, results suggested that the adsorption of [Bmim][BF4] and [Emim][BF4] onto the resins is probably controlled by a heterogeneous process [41].
## 4 Dynamic Model Updating Examples
### Supplementary Example: Dynamic Model Updating of the F-Shaped Structure  
As described in Ref. [23], a 25-frame-FE model of the F-shaped structure was updated by the MUUM and CMPES methods based on the simulated \"experimental\" data generated by introducing certain flexibility at the three joints and the density of the material. The updating parameters and correlated and uncorrelated mode pairings for the MUUM method were the same as Ref. [23]. According to the same optimized parameters listed in Table 4, the updated results by both methods were listed in Table 10.  
Similar to Section 4.1.1, although both the updating methods work well, the \(RMSE_{FRE}\) obtained by the CMPES method is still smaller than the MUUM method.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Group Name** & **Correlated Mode Pairs** & **Uncorrelated Mode Pairs** \\ \hline MUUM & (A1, E1) (A1, E2) (A3, E3) (A4, E4) (A5, E5) & \\  & (A6, E6) (A7, E7) (A8, E8) (A9, E9) (A10, E10) & (A7, E6) (A6, E7) \\ \hline MUUM-I & (A1, E1) (A1, E2) (A3, E3) (A4, E4) (A5, E5) & (A7, E6) (A8, E6) (A6, E7) (A8, E7) \\  & (A6, E6) (A7, E7) (A8, E8) (A9, E9) (A11, E10) & (A6, E8) (A7, E8) \\ \hline MUUM-II & (A1, E1) (A1, E2) (A3, E3) (A4, E4) (A5, E5) & (A7, E6) (A8, E6) (A6, E7) (A8, E7) \\  & (A6, E6) (A7, E7) (A8, E8) (A9, E9) & (A6, E8) (A7, E8) \\ \hline \hline \end{tabular}
\end{table}
Table 8: Groups of correlated and uncorrelated mode pairs for the MUUM method based on the impact modal test data.  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Group Name** & \(RMSE_{FRE}\) **(\%)** & \(RMSE_{MAC}\) & \(CV\) & **Group Name** & \(RMSE_{FRE}\) **(\%)** & \(RMSE_{MAC}\) & \(CV\) \\ \hline MUUM & 2.55 & 0.2082 & 0.1784 & CMPES & 2.55 & 0.1902 & 0.1552 \\ MUUM-I & 6.36 & 0.2147 & 0.1852 & CMPES-I & 2.55 & 0.1902 & 0.1552 \\ MUUM-II & 7.46 & 0.2161 & 0.1870 & CMPES-II & 2.54 & 0.1903 & 0.1552 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Robustness comparison of the MUUM and CMPES methods based on the impact modal test data.