esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Method
### LEO Satellite Clock Broadcasting for Real-Time Applications  
The GNSS satellite clocks are typically broadcast as low-order polynomial coefficients to users either in navigation messages with a low frequency via satellite links, or in real  
Figure 4: Sentinel-3B satellite clocks estimated using the CNES real-time clocks on DOY 227, 2018 without and with alignment to the satellite clocks of G05.  
time streams with high frequency via Internet links [12]. Like the clocks of GNSS satellites, predicted LEO satellite clocks (see Section 2.2) can be fitted with low-order polynomials and provided to users. Due to the bad LEO satellite clock prediction behaviors over the mid- to long-term [38; 39], broadcasting clock coefficients over low-frequency navigation messages like GNSS is not a good option for LEO satellites. It is suggested to either significantly increase the update rate of the broadcast clock messages, or transfer the clocks via real-time streams with the Internet. An update interval of a few seconds can be considered.
## 4 Discussion  
The present study sought to investigate the protective effect of the AGTR1 antagonist losartan on human NP cell inflammation and degeneration induced by TNF-\(\alpha\). Outcomes revealed that TNF-\(\alpha\) induced the expression of pathologic tRAS molecules and led to pro-inflammatory and catabolic effects in human NP cells. Inhibition of AGTR1 with losartan could partly inhibit the inflammatory and catabolic reaction. Therefore, present results suggest that TNF-\(\alpha\)-induced disc degeneration may partially be mediated through AGTR1 signaling. Treatment with AGTR1 antagonist losartan could inhibit the TNF-\(\alpha\)-induced degenerative state and maintain the NP cell phenotype depending on the administration or drug delivery method and the resulting achievable local tissue concentrations.  
In accordance with previous studies, we found that losartan interacted with the PPARy pathway [38]. Inhibition with the PPARy inhibitor T0070907 partly abolished the effects of losartan on nucleus pulposus cells. This implies that the PPARy pathway contributes to losartan's anti-inflammatory effects, as also suggested by [PERSON] et al. [20]. Our results also indicate that losartan has an impact on the gene expression of extracellular matrix-related components. Losartan has been reported to affect TGF-beta expression and reduce collagen I production in human fibroblasts [39]. Additionally, the interaction of losartan with TGF-beta signaling was confirmed by other research groups [40].  
Targeting the tissue renin-angiotensin system may have significant therapeutic potential in modulating the metabolism of the degenerative IVD, which may potentially translate into a reduction of discogenic pain.
## 1 Introduction
### Research Contributions  
Therefore, in this paper we present a new AB-ResUNet+ architecture. Our intention is to construct a network that can achieve high segmentation accuracy with a small dataset and use it for segmentation of complex cardiovascular structures.  
In summary, the contributions of the paper are as follows:  
* We present a new AB-ResUNet+ architecture that uses residual learning, squeeze and excitation operations, Atrous Spatial Pyramid Pooling (ASPP), and the attention mechanism.  
* The channel attention block is inserted into the skip connection to optimize the coding ability of each layer.
* The proposed architecture works well with small datasets.
* Our proposed architecture significantly improves the segmentation of challenging cardiovascular structures.  
We evaluated our model on eleven datasets with different cardiovascular structures. Our experimental evaluations show that the proposed AB-ResUNet+ architecture outperforms the UNet, ResUNet, and ResUNet++ architectures by achieving higher values in terms of Dice coefficient and mean intersection over union (mIoU).
## 3 Potential Security Implications of IoT in 6G Environment
### 6G Usage Scenario-Related Vulnerabilities
#### 3.2.4 Ubiquitous Connectivity  
Ubiquitous connectivity in 6G aims to bridge the digital divide by extending access to underserved regions, yet this introduces unique security concerns [45]. The expansion of connectivity to rural, remote, and sparsely populated areas frequently necessitates interoperability with various systems and networks, which can inadvertently give rise to security vulnerabilities. IoT devices in these regions are often more susceptible to attacks due to weaker infrastructure, limited security resources, and inconsistent network reliability. Additionally, ensuring secure and seamless communication across different environments with varying network conditions exacerbates the risk of data breaches, unauthorized access, and operational disruptions [47].
## Dispersive Fourier Transformation for Versatile Microwave Photonics Applications  
**[PERSON]**  
School of Engineering and Digital Arts, University of Kent, Canterbury, Kent, CT2 7 NT, UK;  
E-Mail: [PERSON]_ADDRESS]; Tel.: +44-1227-827-621; Fax: +44-1227-456-084  
_Received: 15 November 2014; in revised form: 12 December 2014 / Accepted: 12 December 2014 / Published: 18 December 2014_  
**Abstract:** Dispersive Fourier transformation (DFT) maps the broadband spectrum of an ultrashort optical pulse into a time stretched waveform with its intensity profile mirroring the spectrum using chromatic dispersion. Owing to its capability of continuous pulse-by-pulse spectroscopic measurement and manipulation, DFT has become an emerging technique for ultrafast signal generation and processing, and high-throughput real-time measurements, where the speed of traditional optical instruments falls short. In this paper, the principle and implementation methods of DFT are first introduced and the recent development in employing DFT technique for widespread microwave photonics applications are presented, with emphasis on real-time spectroscopy, microwave arbitrary waveform generation, and microwave spectrum sensing. Finally, possible future research directions for DFT-based microwave photonics techniques are discussed as well.  
**Keywords:** dispersive Fourier transformation; microwave photonics; femtosecond lasers; dispersion; time stretch
# Current Progress in Femtosecond Laser Ablation/Ionisation Time-of-Flight Mass Spectrometry
## 4 Performance of fs-LIMS Instruments in the Element and Isotope Analysis
### Depth Profiling, Chemical Imaging, and 3D Chemical Analysis
This can be achieved by tuning the second pulse delay (-73 ps) and pulse energy (-72 nJ/pulse). The DP setup allowed for about 15- and 5-fold signal increase for Ni and Cr signals, respectively, compared to SP. All individual Cr and Ni layers could be resolved, and a mean depth resolutions of \(\sim\)30 nm for Ni and \(\sim\)37 nm for Cr could be achieved (Figure 10B) [88]. These studies show that fs-LIMS can readily compete with state-of-the-art LA-ICP-MS instruments [175]. Current x, y, z translational stages can position sample surface against the laser focal spot with desired precision and accuracies down to tens of nm. fs-laser ablation typically produces low surface contamination in near ablated crater area. With well-defined crater shapes, the next ablation spot can be placed near the beforehand produced crater without affecting quantification. Based on this observation, a 2D multi-position binning mode was proposed to sequentially probe the entire sample area of interest layer-by-layer [176]. Arrays of electrode-posited micrometre-sized Sn/Ag solder bumps served as a test bed for the method development. The presented studies show that the layer-by-layer approach outperforms the single crater analysis protocol when inhomogeneity is non-uniformly distributed along with the sample, and the probing ion source size has a similar dimension to the chemical components of interest. Increase of the lateral measurement spot statistics led to increased sensitivity with a signal enhancement of about ten times. With a repetition rate of fs-laser systems and fast data acquisition systems, a rectangular area of 1x1 mm\({}^{2}\) size can be analysed within several hours with crater sizes of about 10 \(\upmu\)m. Typically, the time for moving the stage from one to other position limits is comparable with the measurement time at the one position [165]. The capability of fs-LIMS for chemical imaging which did not show considerable heat effects on the sample (e.g., affecting zones and ablation rims) has been demonstrated in several studies [165; 177]. Recent studies conducted on silica chert with fs-ablation applying IR (775 nm), near-UV (378 nm), and UV (258 nm) clearly demonstrated that UV fs-ablation is preferable for this material [160; 178]. Figure 11 shows ablation spots resulting from these three different laser wavelengths observed by optical microscopy. The crater quality for UV fs-laser ablation is best and the measurement results in well-defined craters. Furthermore, an improved sensitivity of the deep UV fs laser ablation mass spectrometric measurements was demonstrated in these studies. Current fs-LIMS can conduct 3D chemical analysis by combining chemical imaging and depth profiling measurements [134; 159]. High-resolution 3D chemical analysis down to the sub-micrometre level in all spatial dimensions seems to be possible, as well as taking into account the performance of the current fs-LIMS [24].
# Spatial Distribution of Forest Fire Emissions: A Case Study in Three Mexican Exoregions
## 2 Materials and Methods
### Variables for Estimating Emissions
#### 2.2.1 Biomass  
The goal was to establish a base map of the biomass and to update it for each year of interest. The distribution of the aboveground carbon stocks of woody vegetation in Mexico was selected as the base map ([PERSON], 1980; [PERSON] and [PERSON], 1980), because it (1) uses field and remote sensing data with similar dates, (2) has been validated, and (3) covers the whole of Mexico with a 30 m spatial resolution. The biomass was estimated by applying conversion factors for the vegetation type, as proposed in ([PERSON] and [PERSON], 1980), and it was resampled to 500 m.  
Annual updating was performed using Net Primary Production (NPP), which is defined as the generation of organic material that plants accumulate in their tissue, as a result of photosynthesis by unit area ([PERSON] and [PERSON], 1980; [PERSON] and [PERSON], 1980). NPP was extracted from MOD17A3 data ([PERSON], 1980) for the Gross/Net Primary Production  
Figure 1: Study area: three selected ecoregions.  
(GPP)/(NPP). To estimate the biomass based on NPP, a conversion factor of 0.48 [28] was used. We applied the same conversion factor for the whole study area, because NPP is an annual product and has a coarse spatial resolution (1 km\({}^{2}\)), while the biomass map was made for a specific period and has a higher spatial resolution. Both products, the base map and the annual biomass from NPP, were combined for an estimate of the biomass for a specific year.
# Research on Performance Prediction Model of Impeller-Type Breather
## 2 Numerical Method
### Wall Liquid Film Model  
When droplets hit a solid surface, the droplets may splash, spread, stick, or rebound, depending on the impact energy and surface temperature. Scholars from all over the world have done a lot of experimental research and proposed some evaluation criterion. In this paper, the interaction model between oil droplets and the wall surface was based on the research of [PERSON] [18], as shown in Figure 1.  
To determine the result of droplet-wall collision, splashing parameter \(K\) and the Weber number \(We_{d}\) have been used and the result is presented as follows:  
\[K^{2}=\frac{\rho_{p}{u_{r}}^{2}d_{p}}{\sigma_{p}}\frac{1}{\min\Big{(}h_{0}/d_{ p},1\Big{)}+\delta_{bl}/d_{p}}, \tag{4}\]  
\[We_{d}=\frac{\rho_{p}{u_{p}}^{2}d_{p}}{\sigma_{p}}, \tag{5}\]  
where \(u_{r}\) is the velocity of the oil droplets relative to the wall; \(d_{p}\) is the diameter of the droplet; \(\sigma_{p}\) is the surface tension of the droplet; \(h_{0}\) is the initial thickness of the oil film; \(\delta_{bl}\) is the thickness of the boundary layer; \(u_{p,n}\) is the normal component of the oil drop velocity.  
When the splashing parameter K is greater than the critical value 57.7, the oil droplets will splash and produce new oil droplets in a smaller size. The parameters such as the diameter of the oil droplet will be determined by the cumulative probability distribution function fitted by the experiment. When the splashing parameter K is less than the critical value 57.7, oil droplets do not break and remain their original size. After collision with the wall, there are three main kinds of phenomenon, which include spread, stick, and rebound. When the Weber number is less than 5 and greater than 10, stick and spread of the oil droplets will happen, respectively. These two phenomena are considered as completely collected by the wall surface. However, when the Weber number is between 5 and 10, the  
Figure 1: Interaction of droplets and the wall.  
oil droplets will rebound, that is, the oil droplets return to the flow inside the breather and are not collected by the wall surface.
## 3 Data Collection, Preprocessing and Methodology
### Area of Interest  
This study is focused on two small areas during the winter term. The first one is situated close to the village of Neratov (next to the city of Lazne Belohrad and near Pardubice) in the Pardubicky region, the Czech Republic. The north-western part of the pond Skrin was monitored (see Figure 3). The total area of the pond is 269,000 m\({}^{2}\), and the pond is used for fish farming. Pond Baroch was chosen as the second area of interest (see Figure 4). Pond Baroch is part of a nature reserve with evidence number 1926. The pond is situated south to southwest of the village of Hrobice, near Pardubice. The Regional Office of the Pardubice Region manages the area. The size of the nature reservation is around 30,000 m\({}^{2}\). The reason to protect this nature reserve is its grounded pond, adjacent needs, forest and meadow communities, and ornithological locality.  
Figure 3: Pond Skrin, data source: [42]. The red box bounds the area of interest.
# An Automatic Geometric Registration Method for Multi Temporal 3D Models
## 2 Study Area and Data
### Data Acquisition  
The flight platform was a six-rotor UAV, as shown in Figure 2c, equipped with a full-frame Sony ILCE-7 RM4 camera. The detailed parameters of the flight platform and camera system are shown in Table 1. According to the technical requirement that the  
Figure 1: An illustration of the location and topography of the study site. (**a**) The location of the study site. (**b**) The digital ortho model of the study site. (**c**) The digital elevation model and contour of the study site.  
ground sampling distance (GSD) of the UAV image is 2 cm, the designed flight routes are shown in Figure 2a, where the relative flight altitude was 130 m, and the overlap of heading and side direction were 80% and 60%, respectively. During the experiment period, the same flight routes were used twice to collect UAV data. The first acquisition was on 22 June 2021, and a total of 182 images were acquired. The second collection time was 15 July 2021, and a total of 184 images were obtained.  
In order to evaluate the difference between the two cycle models, we selected stones of different sizes within the study site to be painted red, and measured their spatial positions using GNSS-RTK, as shown in Figure 2b.
## 4 HSC with More Active Layers
In the case of HSCs with the configuration of ITO/PEDOT-PSS/polymer: PbS/PbS/LiF/Al, a maximum PCE was obtained when using PDBT as the donor materials in the blend mixture [62]. Although various strategies for HSCs have been studied to improve the PCE by exploiting the merits of conjugated polymer and semiconductor materials, the PCE of these HSCs is still far below 10%; the value is remarkably lower than pure PbS NCs or OSCs. This is mainly attributed to the poor charge transfer and carrier extraction efficiencies in the hybrid blend film. Most recently, [PERSON] et al. [63] developed a new HSC with the device structure of ITO/ZnO/PbS NC/PBDTTT-E-T: 2,2'-((2Z,2'Z)-((5,5'-(4,4,9,9-tetrakis(4-hexylphenyl)-4,9-dihydro-indaceno[1,2-b:5,6-b']dithiophene-2, 7-diyl)bis(4-((2-ethylhexyl)-oxy)thiophene-5,2-diyl))bis(methanyylylidene))bis(3-oxo-2,3-dihydro-1H-indene-2,1-diylidene))dimalononitrile (IEICO)/MoO\({}_{3}\)/Ag. There are two active layers in this device configuration, viz. PbS NCs and polymer/SM blend film. The usage of small-molecule acceptors instead of NCs increases the efficiency reported for all solution-processed organic/inorganic NC HSCs.
## 4 Control Scenarios
### Main Service Scenario  
Figure 6 shows the outline of four significant scenarios. The description below gives a rough description of the service scenarios:  
* **Detection of the Fire Occurrence Place**: Real-time ignition detection service package by smart sensors detect fire point and provides real-time AR-based fire occurrence monitoring service to users, administrators, and rescuers;
* **Context Awareness and Actuator Control-Based Fire Detection**: This is an actuator control service package through detection of fire occurrence. When a fire is detected, it shuts down gas and electricity which can further enlarge the fire;
* **AR-Based Fire Escape Guideline Service**: Provides safe evacuation and rescue guidelines to rescuers and fire fighters through fire status information detected by human detection sensors and smart sensors;
* **Connection of Integrated Control Center and Safety Center**: Provides services for rapid reporting and real-time monitoring to fire stations and control centers after a fire occurs.  
Figure 5: The fire extinguish and fire escape guidance algorithm.
# Frequency-Dependent Acoustic Reflection for Soil Classification in a Controlled Aquatic Environment
## 5 Conclusions  
### Summary of Findings  
This study provides compelling evidence that acoustic reflectance spectrum analysis can effectively distinguish between different soil types in an aquatic environment. The precise and repeatable spectral differences observed between missing graded sand (SP) and missing graded gravel (GP) suggest that grading characteristics and grain size play a significant role in shaping acoustic wave interactions. These findings reinforce the viability of using frequency-dependent acoustic responses for sediment classification, offering an alternative to traditional intensity-based acoustic approaches.
## 3 Fluorophore Coupled to a Resonant Cavity in the Strong-Coupling Regime
### Emission Spectrum in the Strong-Coupling Regime  
There exists an alternative way to describe the coupling of a dipole to a lossy cavity, which is conceptually quite different from the ones presented in the previous sections. This model ([18], Chapter 1, Complement 1A) treats the spontaneous emission of an atom coupled to a bounded continuum of electromagnetic modes, with a bandwidth \(\gamma_{c}\). As previously, the atom is modeled as a two-level system with transition frequency \(\omega_{0}\), and the continuum is assumed to have a \"Lorentzian\" density of states (modes) centered on a frequency \(\omega_{c}\) and with a bandwidth expressed through the Full Width Half Maximum (FWHM) and from now on taken to be equal to \(\gamma_{c}\). In particular, while conceptually very different, this model predicts the same temporal behavior as the previous ones. Its interest is that it predicts the distribution in energy of the emitted photons in the continuum which is an observable that one can measure in practice: the so-called vacuum Rabi splitting.  
This model is developed in appendix (Supplementary Material), where we show that, in the highly strong-coupling regime, the probability of emitting a photon in mode j, denoted \(P_{\mathrm{emitj}}(t\rightarrow+\infty)\equiv|\beta_{\mathrm{j}}(t \rightarrow+\infty)|^{2}\) obeys  
\[P_{\mathrm{emitj}}(t\rightarrow+\infty)=\frac{1}{4}\frac{|g_{\mathrm{j}}|^{2} }{\left[(\omega_{\mathrm{j}}-\omega_{0})+g\right]^{2}+\left(\frac{\gamma_{c}} {4}\right)^{2}}+\frac{1}{4}\frac{|g_{\mathrm{j}}|^{2}}{\left[(\omega_{\mathrm{ j}}-\omega_{0})-g\right]^{2}+\left(\frac{\gamma_{c}}{4}\right)^{2}}+\mathrm{C.T.} \tag{21}\]where the cross-term C.T. is given by:  
\[\text{C.T.}=\frac{|g|^{2}}{2}\frac{(\omega_{j}-\omega_{0})^{2}-g^{2}+\left(\frac {\gamma_{c}}{4}\right)^{2}}{\left[(\omega_{j}-\omega_{0})^{2}-g^{2}+\left(\frac {\gamma_{c}}{4}\right)^{2}\right]^{2}+4\left(\frac{\gamma_{c}}{4}\right)^{2}g^{ 2}} \tag{22}\]  
As seen from Equation (21), in the strong-coupling regime \(g>\gamma_{c}\), the distribution of emitted photons features two peaks separated by \(2g\), and of FWHM\(=2\times\gamma_{c}/4=\gamma_{c}/2\). Therefore, an \"order of magnitude\" condition to be able to distinguish the two peaks is:  
\[2g>\frac{\gamma_{c}}{2}\quad\Rightarrow\quad\boxed{g>\frac{\gamma_{c}}{4}} \tag{23}\]  
When this condition is fulfilled, strong-coupling is achieved and the emission spectrum consists of two non-overlapping Lorentzian distributions respectively centered around \(\omega_{0}-g\) and \(\omega_{0}+g\), which is the Rabi splitting previously described in Equations (5) and (6).
## 3 Elastographic Methods
### Transient Elastography (TE)
#### 3.1.2 TE in Non-Alcoholic Fatty Liver Disease (NAFLD)  
In children with NAFLD (age range from 5.5 to 11.3 years), the combination of pediatric NAFLD fibrosis index (PNFI) and TE were used to assess the presence of clinically significant liver fibrosis. Both PNFI and TE values were significantly higher in children with significant fibrosis [53]. The combined use of PNFI and TE predicted the presence or absence of clinically significant fibrosis in 98% of children with NAFLD. This could help to identify children who should undergo liver biopsy because the confirmation of advanced fibrosis would lead to closer follow up and screening for cirrhosis-related complications.  
In a series of 52 biopsy-proven pediatric non-alcoholic steatohepatitisitis (NASH), the following cutoffs for staging liver fibrosis were found: 5-7 kPa for F1 (area under the receiver-operating characteristic (AUROC) curve, 97.7%), 7-9 kPa for F2 (AUROC, 99.2%), >9 kPa for F3 (AUROC, 100%) [42].
## 4 Analysis of Influencing Factors
### Influence of the Excavation Depth of the Foundation Pit
#### 4.1.1 Tunnel Horizontal Displacement  
Figure 9(a) illustrates the tunnel's maximum horizontal displacement resulting from the completion of excavation in the adjacent foundation pit to varying depths. The tunnel horizontal displacement increases by 21.26%, 33.33%, 50.57%, 61.49% and 76.44% as the excavation depth increases from 14 m to 24 m. The tunnel's maximum horizontal displacement gradually increases with excavation depth, demonstrating a linear relationship. Referring to the tunnel deformation control standard outlined in the existing specifications, it is observed that when the excavation depth exceeds 20 m, the tunnel's horizontal displacement surpasses the control value.  
Figure 9: Comparison between the measured and simulated tunnel displacement results.