esa-sceva/satcom-chunk-collection huggingface dataset:
# Two Design Options for Compact Linear Accelerators for High Flux Neutron Source
## 2 Proton RFQ Accelerator Design
### Beam Dynamics Simulations  
In the beam dynamics designs, the proton RFQs are optimized with the utilization of the ParmteqM code [41]. The main design parameters of the proton RFQs (162.5 MHz vs. 325 MHz) with constant inter-vane voltages of 65 kV and 85 kV are shown in the Figure 4.  
Both RFQs hold a Kilpatrick limit lower than 1.85 and a high energy gain per unit length. The cavity lengths are 5.18 m and 3.66 m, with synchronous phases of \(-90.0^{\circ}\)\(-\)\(-\)27.7\({}^{\circ}\) and \(-90.0^{\circ}\)\(-\)\(-30.0^{\circ}\), respectively. For 162.5 MHz RFQ design, the minimum aperture radius is 3.37 mm and the maximum modulation factor m is 2.17. Correspondingly, they are 2.16 mm and a factor of 2.16 in the 325 MHz RFQ design.  
The multi-particle tracking simulations are carried out by using the ParmteqM code with an input distribution of 100,000 macro-particles. The transverse phase spaces (x-x\({}^{\prime}\)) and (y-y\({}^{\prime}\)) are 4D waterbag, while the longitudinal one (\(\varphi\)-W) is uniform. The transmission efficiency and transverse RMS envelopes as a function of the longitudinal position of the RFQ accelerators are given in Figure 5a-d. Besides, the transverse particle distributions (x-x\({}^{\prime}\)) at RFQ inputs of both designs (162.5 MHz vs. 325 MHz) are shown in Figure 5e.f. Both RFQs have a high transmission efficiency over 95%. The beam losses mainly concentrate on the sections of the shaper and gentle buncher in the RFQ accelerators. The averaged RMS beam size at the 162.5 MHz RFQ exit is 0.84 mm, while the 325 MHz RFQ has a smaller one of 0.61 mm at the output.  
Figure 4: Evolutions of the synchronous phase (Phase in degree), aperture radius (a in mm) and modulation factor (dimensionless m) along RFQs: (a) 162.5 MHz design, (b) 325 MHz design.
## 4 Data and Examples
### Analysis of Multivariate Traffic Parameter Characteristics
#### 4.2.4 Multivariate Traffic Parameter Phase Space Reconstruction  
An analysis of the time series characteristics of multivariate traffic parameters reveals that they exhibit relatively complex variation patterns. To quantify their complex features, we selected three typical sections from Figure 4 and conducted a multivariate phase space reconstruction using the time series data of vehicle speeds, headways in Section 1, first section travel times, and total travel times. Based on 500 time series records collected from the sections, the MATLAB ChaosToolbox lzb3.0 toolbox was used to calculate the embedding dimension and time delay results of the multivariate parameters [46; 47]. The results indicate that each element variable in the multivariate phase space exhibits chaotic characteristics. These results are shown in Table 4.  
In addition, based on the embedding dimension and time delay calculation results of each traffic parameter in Table 5, for example, a 500 \(\times\) 6 matrix can be reconstructed as a 457 \(\times\) 123 phase space.
# The Effect of Processing Methods on Phytochemical Composition in Bergamot Juice
## 3 Results
### Phytochemical Content in Bergamot Juices Obtained with Different Juice Extraction Systems
\begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Ep-1** & **Ep-2** & **Ep-3** & **dBJ** \\ \hline _flavanone glycosides_ & & & & \\ neoeriocitrin (mg/L) & 114 \(\pm\) 20 \({}^{\text{a}}\) & 219 \(\pm\) 64 \({}^{\text{b}}\) & 402 \(\pm\) 122 \({}^{\text{c}}\) & 7 \(\pm\) 2 \({}^{\text{d}}\) \\ narirutin (mg/L) & 18 \(\pm\) 3.0 \({}^{\text{a}}\) & 18 \(\pm\) 3.5 \({}^{\text{a}}\) & 37 \(\pm\) 3.9 \({}^{\text{b}}\) & \(<\)0.1 \\ naringin (mg/L) & 97 \(\pm\) 13 \({}^{\text{a}}\) & 175 \(\pm\) 58 \({}^{\text{b}}\) & 394 \(\pm\) 83 \({}^{\text{c}}\) & 5 \(\pm\) 1 \({}^{\text{d}}\) \\ neohesperidin (mg/L) & 66 \(\pm\) 15 \({}^{\text{a}}\) & 124 \(\pm\) 69 \({}^{\text{b}}\) & 279 \(\pm\) 78 \({}^{\text{c}}\) & 4 \(\pm\) 2 \({}^{\text{d}}\) \\ _Quaternary ammonium compounds_ & & & & \\ _N,N_-dimethyl-\(L\)-proline (mg/L) & 436 \(\pm\) 49 \({}^{\text{a}}\) & 569 \(\pm\) 126 \({}^{\text{a}}\) & 667 \(\pm\) 147\({}^{\text{a}}\) & 395 \(\pm\) 38 \({}^{\text{a}}\) \\ _limonoid aglycones_ & & & & \\ Limonin (mg/L) & 20 \(\pm\) 4 \({}^{\text{a}}\) & 37 \(\pm\) 13 \({}^{\text{a}}\) & 65 \(\pm\) 14 \({}^{\text{b}}\) & 5 \(\pm\) 1 \({}^{\text{c}}\) \\ Nomilin (mg/L) & 17 \(\pm\) 4 \({}^{\text{a}}\) & 42 \(\pm\) 11 \({}^{\text{b}}\) & 67 \(\pm\) 12 \({}^{\text{b}}\) & 3 \(\pm\) 1 \({}^{\text{d}}\) \\ \hline \hline \end{tabular} Means in a row without a common superscript letter differ (\(p<0.05\)) as analyzed by two-way ANOVA and the TUKEY test.  
\end{table} 
Table 2: Concentration (mean \(\pm\) standard deviation, \(n=3\)) of flavanone glycosides, quaternary ammonium compounds, and limonoid aglycones in bergamot juice obtained using 3 different juice extraction methods: hand squeezing (Ep-1); FMC (Ep-2); screw press of peeled fruits (Ep-3), and in debittered bergamot juice (dBJ). Figure 2: Comparison of RP-HPLC-DAD chromatograms at 284 nm of flavanone glycosides in bergamot juice (BJ) obtained using 3 processing methods: (**a**) Standard mixture of eriocitrin (1), neoeriocitrin (2), narirutin (3), naringin (4), hesperidin (5), neohesperidin (6). (**b**) Hand squeezed BJ (Ep-1); (**c**) FMC–BJ (Ep-2); (**d**) BJ obtained by screw press of peeled fruits (Ep-3); (**e**) debittered bergamot juice (dBJ). affect L-ascorbic acid and \(N\),\(N\)-dimethyl-\(L\)-proline, which did not significatively differ (\(p<0\). 5) from fresh hand squeezed BJ (Table 2).
# Ultrasound-Based Smart Corrosion Monitoring System for Offshore Wind Turbines
## 6 Results and Discussion
### Test Samples Measurements
#### 6.1.2 Measurements Precision of Exposed Test Coated Samples  
Different sets of numbered coated samples have been exposed to a controlled corrosive environment under the cyclic aging test after 1 month, 3 months (see Figure 6 (bottom)), and 6 months exposure. After the completion of the exposure time, each sample has been tested using the UT. The ultrasound thickness measures have been performed in both on scribe and no-scribe locations of the coated samples, as discussed in Section 5.1.  
The precision of measures obtained for the test coated samples exposed under cyclic aging test for different time durations with respect to the signal level has been plotted in Figure 10. Here, also, the SL refers to the Root Mean Square (RMS) value of the first detected echo measured after the amplifier, and precision refers to the standard deviation of 25 measures performed in the same location (\(\sigma_{\text{ToF}}\)). Comparing the precision of ToF measures between on scribe and no-scribe areas, it can be seen that, in order to obtain similar precisions in Scribe and Non-Scribe areas, we must increase the SL by \(\sim\)75 mV (see the \(B\) parameter of fitting curve) when measuring Scribe areas.  
Furthermore, in the case of the on scribe area, it can be observed that the most lower signal level data points belong to the samples with higher exposition time. This may be caused due to the non-uniformity of the corrosion layer developed on the scribe area. In general, we are obtaining a good precision for both bare and coated samples. The ToF precision computed here is the standard deviation of ToF values of 25 measures at the same sensor position (as discussed in Section 5.2). If we place the sensor on different locations of the same sample and calculate the standard deviation of ToF measures, the obtained precision is lower than the given values here. This is because the thickness at different locations of the same sample varies, even for the non-exposed bare steel samples. These small thickness variations (at \(\upmu\)m level) are due to the common existing imperfections during the sample production. Therefore, in order to have a good precision of ToF measures, the positioning of the sensor on the same location is very important. As discussed in Section 3, from the two modes of operation (fixed and mobile), the positioning accuracy can be a constraint for the mobile solution, which we have to address in future work.
## 2 Constellation Design
### Constellation Technical Characteristics  
As a low-latitude satellite constellation with the design concept of coverage priority, HSC features multispectral, hyperspectral, and SAR sensors, as well as AIS for integrated ocean observations. Onboard image processing technology is integrated for ship detection. Details of these characteristics are provided below.
## 4 Results and Discussion  
A number of studies have carried out thermohydrodynamic lubrication studies on tilting pad bearings [27; 28; 29]. However, the isothermal method, which considers the thermal effect by average viscosity (corresponding to mean temperature) of the oil film estimated from the overall heat balance [25], is still widely used for design purposes [30; 31; 32]. Such is  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \multirow{2}{*}{\(\epsilon^{\prime}\)} & \multicolumn{5}{c}{**Constant \(\mu\) and without \(k_{x}\), \(k_{z}\)**} & \multicolumn{5}{c}{**Relative Deviation**} \\ \cline{2-9}  & \(K_{xx}\) & \(K_{yy}\) & \(C_{xx}\) & \(C_{yy}\) & \(K_{xx}\) & \(K_{yy}\) & \(C_{xx}\) & \(C_{yy}\) \\ \hline
0.1 & 14.3 & 13.7 & 18.8 & 18.4 & 0.69\% & 1.44\% & 1.05\% & 1.08\% \\
0.2 & 8.18 & 6.82 & 9.88 & 8.98 & 1.68\% & 0.44\% & 1.20\% & 1.43\% \\
0.3 & 6.74 & 4.46 & 7.13 & 5.68 & 1.17\% & 2.19\% & 1.66\% & 1.73\% \\
0.4 & 6.62 & 3.18 & 5.95 & 3.90 & 0.60\% & 2.15\% & 1.65\% & 1.76\% \\
0.5 & 7.25 & 2.31 & 5.40 & 2.71 & 0.14\% & 1.70\% & 0.92\% & 1.81\% \\
0.6 & 8.63 & 1.62 & 5.23 & 1.82 & 0.12\% & 2.41\% & 0.76\% & 2.15\% \\
0.7 & 11.1 & 1.06 & 5.48 & 1.14 & 0.28\% & 1.85\% & 3.52\% & 2.56\% \\
0.8 & 15.8 & 0.593 & 6.46 & 0.608 & 0.63\% & 2.79\% & 0.78\% & 3.18\% \\
0.85 & 20.3 & 0.399 & 7.11 & 0.400 & 2.87\% & 2.44\% & 3.49\% & 2.91\% \\ \hline \end{tabular}
\end{table}
Table 1: The validation of the dynamic characteristics program for the tilting pad bearings.  
introduced to advanced rotor dynamics software such as Ref. [33]. In this paper, we focus on the influence of dynamical variation of turbulence coefficients and viscosity on stiffness and damping coefficients. Thus, the lubricating film is considered isothermal. For the same reason, the impact of inertia of the pad is not considered. So the cross-coupling equivalent stiffness and damping coefficients of tilting pad bearing are close to zero.  
The structure and operating parameters of the tilting pad bearing are shown in Table 2 unless otherwise stated, and the assembled radius clearance \(C_{b}\) has values of 109.5 and 143.5 \(\upmu\)m which were taken from a rotor system of a certain modeled gas turbine test rig.
# Causal Inference-Based Self-Supervised Cross-Domain Fundus Image Segmentation
## 4 Experiments
### Discussion on Causal Inference-Based Pseudo-Label Fusion Module
#### 4.3.1 Effectiveness of Pseudo-Label Fusion  
To demonstrate the effectiveness of the causal inference-based pseudo-label fusion, we compared the segmentation results of three schemes: one that does not employ pseudo-labels for self-supervision, one that generates pseudo-labels using a single-path approach solely based on target domain images, and the final method that incorporates causal inference. The corresponding results are presented in Table 3. The experimental findings indicate that the use of the pseudo-label module enables the model to exploit the information from target domain images, thereby significantly enhancing segmentation performance and validating the effectiveness of self-supervised learning. Moreover, incorporating the causal inference strategy further optimizes pseudo-label generation by effectively mitigating the interference caused by mixed domain styles, resulting in more accurate and reliable pseudo-labels for supervising the model. This strategy not only enhances the generalization ability of the model but also provides a robust theoretical foundation for cross-domain adaptation.
# Unveiling the Role of Minerals and Trace Elements of Thermal Waters in Skin Health
## 2 Minerals, Trace Elements, and Other Compounds of TSW in Skin Health
### Anions
#### 2.1.3. Bicarbonate
Additionally, a controlled, randomized, double-blind clinical study was performed to compare Comano TSW with tap water, showing a reduction in PASI scores and hydration improvement in the studied group. Histologic reports showed a significant reduction in hyperkeratosis, acanthosis, and papillatosis; no undesired side effects were described [37]. An observational study was conducted on children with mild-to-severe atopic dermatitis who underwent balneotherapy at the Comano thermal spring water center. The results showed a statistically significant improvement in AD severity after the Comano TSW balneotherapy, and the therapy was well tolerated. Furthermore, no relevant adverse effects were reported during the treatment course [38]. Nitrodi thermal spring water (Nitrodi TSW) is medium-mineral water classified as bicarbonate and rich in silica. Several studies have shown its potential anti-inflammatory activity [69; 70]. Recently, [PERSON] et al. [39] conducted a study with the aim of studying the biological effects of Nitrodi TSW on human dermal fibroblasts to determine whether the water exerts in vitro effects that could be relevant to skin wound healing. The results showed that Nitrodi TSW exerts strong promotional effects on dermal fibroblast viability and a significant stimulatory activity on cell migration; in short, Nitrodi TSW induces alpha-SMA expression in dermal fibroblasts, thus promoting their transition to myofibblast-protein ECM deposition. Furthermore, Nitrodi thermal spring water reduces intracellular reactive oxygen species (ROS), which play an important role in human skin aging and dermal damage. Additionally, a significant stimulatory effect on the cell proliferation of epidermal keratinocytes was observed, as well as an enhancement of their response to the oxidative stress caused by external stimuli. Other studies have suggested that bathing in hot springs may affect the gut microbiota in healthy individuals, showing that the relative abundance of _Bifidobacterium bifidum_ was increased significantly after seven consecutive days of bathing in a bicarbonate spring, and significant increases in other gut microbiota were also observed after bathing in simple, bicarbonate, and sulfur springs [71].
# Towards Efficient Sink Mobility in Underwater Wireless Sensor Networks
## 4 Proposed Scheme  
In UWSNs, the efficient use of mobile sinks results in high throughput with minimum energy utilization [14; 15]. In the proposed scheme, the main focus is on the movement of mobile sinks. This attention brought about good results, which can be seen in the following sections.
# Towards a Glass New World: The Role of Ion-Exchange in Modern Technology
## 2 Glass Strengthening: The Ion-Exchange Contribution
### Ion-Exchanged Noble Metal Nanoparticles in Glasses for Sers Applications
#### 3.2.1 Glasses for SERS Substrate by Ion-Exchange Technique  
Soda-lime and float glasses with their large commercial availability, high transparency, good chemical durability, high sodium content, and ion inter-diffusion coefficients are the most popular material for the realisation of SERS substrates by ion-exchange process. The presence in trace of some impurities, such as iron or arsenic, within these glasses promotes the reduction of the exchanged noble metal ions into metallic clusters during the subsequent sample treatment [100; 155; 156; 157; 158].  
Not to be forgotten are the commercial borosilicate glasses (e.g., Schott BK7 or Corning 0211 glasses) which, with their higher purity, are the most common substrates for the realisation of integrated optical devices by ion-exchange process. Although the almost total absence of impurities does not make them suitable for the formation of metal nanoparticles by chemical reduction processes, recent studies have shown the possibility of obtaining efficient SERS substrates also by using these highly pure glasses [159].  
Finally, it should also be mentioned that, together with these widely used glass systems, phosphate or fluorophosphate glasses are recently gaining ever-increasing interest due to their lower processing temperature, higher diffusion coefficient for noble metal ions, and better reducing properties thanks to the large concentration of non-bridging oxygens generated during the glass synthesis [99; 160].  
Having incorporated the metal ions in the glass matrix by the ion-exchange process, one can promote their precipitation into metal nanoparticles by adopting different strategies, as described below.
# Challenges, Threats, Security Issues and New Trends of Underwater Wireless Sensor Networks
## 2 Particularities and Constraints
### Unreliable Communication Channel
#### 2.2.2 Limited Bandwidth and Low Data Rates  
The available bandwidth of underwater acoustic channels is limited and dramatically depends on both transmission range and depth.  
As shown in Table 1, for long range communication in deep water, the available bandwidth ranges from 500 Hz to 10 kHz; for medium range communication in shallow water, the available bandwidth ranges from 10 to 100 kHz; and for short range communication in deep water, the available bandwidth ranges from 100 to 500 kHz. The available bandwidth becomes much wider with the decrease of communication range, especially at ranges less than 100 m.  
As shown in Table 1, the data rate is also relevant with communication range. For long range communication, the maximum data rate is approximately 10 kb/s. For medium range communication, the maximum data rate is approximately 50 kb/s. For short range communication, the maximum data rate can reach more than 100 kb/s. There is a tradeoff between data rate and channel bandwidth.  
Because underwater acoustic communication is possible only over limited bandwidths, the data rate of the underwater acoustic channel is much slower than radio channel in the air. In many UWSN applications including AUV control, a larger communication range is more important than a higher transfer rate.
# Communication Architecture in Mixed-Reality Simulations of Unmanned Systems
## 5 The Proposed Architecture Design
### Addressing  
Each entity needs to have two parts of its address to send messages between two different networks. The first part specifies the HW network address, i.e., the address of the physical RF modem at which it can be reached, and the second (SW) part specifies the entity's address within the simulation and has to be unique for each entity. Information about these addresses needs to be propagated to all entities in both networks. A service similar to the IPv6 Neighbor Discovery protocol, as described in [41] can be used for that (alternatively, if the available bandwidth is an issue and multiple channels are available, a method similar to the cluster-based beaconing process [44] can be utilized). The router advertisement service has been adopted in the proposed architecture. This service has been modified to help with maintaining the reachability information of other active neighbors and the discovery of new entities in the environment. The entities periodically broadcast packets (_advertisements_) containing their ID and both their HW and SW address parts. After reception of such an advertisement, the entities update the list of their neighbors.  
The message broadcast is the dissemination of a message to all reachable neighbors, both HWEs and SWEs. In the MR system, this means the usage of a standard broadcast method at the sender's network (UDP broadcast in the SW network and RF transmission broadcast in the HW network) followed by a re-broadcast by the message relay node to the other networks upon message reception at the level of the GCS.  
Figure 3 shows the principle of dual addressing on an example of two HW UAVs and two virtual ones modeled within the GCS. Here, all the communication participants have a unique SW address, and the SWEs share the HW address of the GCS.
# Smart Mobility and Aspects of Vehicle-to-Infrastructure: A Data Viewpoint
## 4 Data Categorization
### Data Categorization by Method of Collection  
Another way we can categorize data for V2I communication is according to the way the data are collected. The most amount of data are collected through sensors in intelligent infrastructure, such as camera systems, temperature sensors, barometric pressure meters, traffic censuses and others. These sensors are not movable, so data from them are always evaluated against the same location [13].  
Camera systems, radar, vehicle speed sensor and lidar are just some of the sensors that are equipped with intelligent cars. Unlike sensors in the infrastructure, the vehicle dynamically changes its position and changes the location with which the data is correlated.  
Figure 6: Categorization of data collected within V2I.  
This location is detected through GNSS/GPS sensors. Vehicle location data are often also obtained from online navigation systems or mobile applications, such as Google Maps or Waze. By obtaining the position data of several vehicles, it is possible to predict traffic jams. However, it should be taken into account that the number of mobile devices does not have to be the same as the number of vehicles, for example, in the case of a bus with a larger number of passengers [13].  
Relevant information may also be obtained from information systems. For example, we can obtain information on mobile signal road coverage through the GIS. Monitoring systems can provide data on, for example, the number of available parking spaces. A different perspective may be on obtaining useful information provided by people, such as reports from emergency services (police, health service and firefighters) or citizen reports [13].
# Automated Multiple Concrete Damage Detection Using Instance Segmentation Deep Learning Model
###### Abstract  
In many developed countries with a long history of urbanization, there is an increasing need for automated computer vision (CV)-based inspection to replace conventional labor-intensive visual inspection. This paper proposes a technique for the automated detection of multiple concrete damage based on a state-of-the-art deep learning framework, Mask R-CNN, developed for instance segmentation. The structure of Mask R-CNN, which consists of three stages (region proposal, classification, and segmentation) is optimized for multiple concrete damage detection. The optimized Mask R-CNN is trained with 765 concrete images including cracks, efflorescence, rebar exposure, and spalling. The performance of the trained Mask R-CNN is evaluated with 25 actual test images containing damage as well as environmental objects. Two types of metrics are proposed to measure localization and segmentation performance. On average, 90.41% precision and 90.81% recall are achieved for localization and 87.24% precision and 87.58% recall for segmentation, which indicates the excellent field applicability of the trained Mask R-CNN. This paper also qualitatively discusses the test results by explaining that the architecture of Mask R-CNN that is optimized for general object detection purposes, can be modified to detect long and slender shapes of cracks, rebar exposure, and efflorescence in further research.  
multiple damage; deep learning; mask r-cnn; concrete crack; efflorescence; rebar exposure; spalling 10.390/app10228008