esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Landsat 9 and Data Processing  
This study mainly used Landsat 9 optical remote sensing data, which can be processed and calculated through the Google Earth Engine (GEE) website platform ([[http://developers.google.cn](http://developers.google.cn)]([http://developers.google.cn](http://developers.google.cn)), accessed on 7 May 2023). In this study, the GEE cloud removal algorithm was used to remove the cloud, and the image values corresponding to each pixel were obtained, followed by the extraction of the spectral band, vegetation indices, and other image feature parameters.  
Landsat 9 was launched by USGS and NASA on 5 November 2021. After about 100 days of debugging, the data collected by Landsat 9 will be freely available to the world in early 2022 [29]. Landsat 9 is a near-polar sun-synchronous orbit satellite with an orbital height of 705 km, an orbital inclination of 98.2, a regression period of 16 days, a single scene width of 185 km, and a design life of five years. Landsat 9 is equipped with OLI-2 and TIRS-2 instruments, of which OLI-2 contains 9 bands with a spectrum spanning visible, near and mid-infrared, enabling monitoring of vegetation, coastal zone, aerosol, water vapor and, cloud [30]. Additionally, TIRS-2 contains two thermal infrared bands; it can satisfy the needs of thermal infrared radiation or thermal environment monitoring on the surface of the earth. The spatial resolution of bands 1 to 7 and 9 are 30 m, band 8 is 15 m, and bands 10 to 11 are 100 m. The Landsat 9 image includes Level-1 Precision Terrain (L1 TP)-processed data and Level-2 data [31]. This research discusses the Landsat 9 Level 1T data in Shangri-La from March to May 2022 through GEE.
# Repair Performance of Self-Healing Microcapsule/Epoxy Resin Insulating Composite to Physical Damage
## Materials and Methods
### Methods
#### 2.2.1 Mechanical Damage Test  
The scratch damage was used to simulate the mechanical damage in epoxy resin insulating material to verify the repair behavior to physical damage. The scratches were carried out with China Tianchuang QHZ scratch tester. The morphology of scratches was observed by China Guanggu SGO-PH80 optical microscope (OM). According to the optimum polymerization temperature (about 45 \({}^{\circ}\)C) of repairing agent (DCPD), the curing temperature (above 60 \({}^{\circ}\)C) of reaction product (PDCPD) and the normal operating temperature (less than 155 \({}^{\circ}\)C) of epoxy resin insulating material, the temperatures of 60 \({}^{\circ}\)C were selected in this paper. The heating time was 30 min and 60 min, respectively.  
Moreover, the alternating current (AC) breakdown strength of samples was carried out to verify the self-healing effect to mechanical damage in electrical insulation performance. The breakdown strength was tested on the platform constructed by Ningxia High Voltage Electronic Instrument Company JNC801 transformer. The cylinder-plate electrodes manufactured according to GB/T 1048-2006 standard were used as the electrodes, which are made of brass. In addition, the electrodes and samples were immersed in 25# mineral insulating oil to prevent the surface discharge. The breakdown test for each type of samples was repeated 20 times.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Basic Performances of** & \multicolumn{4}{c}{**Concentrations of Microcapsule in Composite**} \\ \cline{2-6}
**Composite** & **0 wt. \%** & **0.5 wt. \%** & **1 wt. \%** & **5 wt. \%** & **10 wt. \%** \\ \hline Repair efficiency to scratch & 0 & \(\geq\)50 & \(\geq\)70 & \(\geq\)73 & \(\geq\)76 \\ about 25 \(\mu\)m wide (\%) & & & & & \\ Thermal decomposition & & & & & \\ temperature (\({}^{\circ}\)C) & 396.8 \(\pm\) 1.5 & 399.1 \(\pm\) 1.9 & 402.7 \(\pm\) 2.3 & 400.3 \(\pm\) 2.1 & 391.0 \(\pm\) 3.9 \\ Young’s modulus (GPa) & 2.67 \(\pm\) 0.03 & 2.63 \(\pm\) 0.13 & 2.50 \(\pm\) 0.21 & 2.34 \(\pm\) 0.17 & 2.11 \(\pm\) 0.33 \\ Tensile strength (MPa) & 51.6 \(\pm\) 2.7 & 50.0 \(\pm\) 1.9 & 46.1 \(\pm\) 3.1 & 40.3 \(\pm\) 2.9 & 32.6 \(\pm\) 3.7 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Basic performances of composite with different concentrations of microcapsule.  
Furthermore, the cross-section test was carried out to further observe the reaction process of repairing agent. And the Czech Tescan MIRA3 scanning electron microscope (SEM) was used to make an intuitive comparison between the pure sample and composite.
## 3 Materials and Methods
### Evaluation Strategy  
For the quantitative evaluation of the proposed ArCAR system with each fold test, weighted objective metrics, including recall or sensitivity (SE), specificity (SP), overall accuracy (Az), F1-score, Matthews correlation coefficient (MCC), precision or positive predictive value (PPV), and negative predictive value (NPV), are used. To prevent having test sets that are unbalanced with regard to all classes, the weighted-class strategy is used. The criteria for all of these metrics are defined as follows:  
\[\text{Recall/Sensitivity (SE)}=\frac{\text{TP}}{\text{TP}+\text{FN}}\;, \tag{1}\]  
\[\text{Specificity (SP)}=\frac{\text{TN}}{\text{TN}+\text{FP}}\;, \tag{2}\]  
\[\text{F1}-\text{score (DICE)}=\frac{2\cdot\text{TP}}{2\cdot\text{TP}+\text{FP}+ \text{FN}}\;, \tag{3}\]  
\[\text{Overall accuracy (Az)}=\frac{\text{TP}+\text{TN}}{\text{TP}+\text{ FN}+\text{TN}+\text{FP}}\;, \tag{4}\]  
\[\text{MMC}=\frac{\text{TP}\cdot\text{TN}-\text{FP}\cdot\text{FN}}{\sqrt{ \left(\text{TP}+\text{FP}\right)\left(\text{TP}+\text{FN}\right)\left(\text {TN}+\text{FP}\right)\left(\text{TN}+\text{FN}\right)}}, \tag{5}\]  
\[\text{Precision/PPV =\frac{\text{TP}}{\text{TP}+\text{FP}}}\;, \tag{6}\]  
\[\text{NPV}=\frac{\text{TN}}{\text{TN}+\text{FN}}\;, \tag{7}\]  
where TP, TN, FP, and FN are defined to represent the number of true positive, true negative, false positive, and false negative detections, respectively. To derive all of these parameters, a multidimensional confusion matrix is used. Finally, to avoid having test sets  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \# & **Layer Type** & **Filter Size, Maps** & **Pooling** \\ \hline
1 & Input data: 70 \(\times\) 1014 (2D) & - & - \\
2 & CONV. 1 & 7 \(\times\) 7, 64 & 2 \\
3 & CONV. 2 & 5 \(\times\) 5, 128 & 2 \\
5 & CONV. 4 & 3 \(\times\) 3, 256 & NA \\
6 & CONV. 5 & 3 \(\times\) 3, 256 & 2 \\
7 & CONV. 6 & 3 \(\times\) 3, 256 & 2 \\
8 & Dense 1 & 1024 & - \\
9 & Dense 2 & 1024 & - \\
10 & Softmax (Output) & Based on the number of classes & - \\ \hline \hline \end{tabular}
\end{table}
Table 6: Detail Structure of the Proposed ArCAD System.  
that are unbalanced with regard to all classes, we used the weighted-class strategy with each dataset to calculate the evaluation indices [27].
# Motion Correction for Brain MRI Using Deep Learning and a Novel Hybrid Loss Function
###### Abstract  
Purpose: Motion-induced magnetic resonance imaging (MRI) artifacts can deteriorate image quality and reduce diagnostic accuracy, but motion by human subjects is inevitable and can even be caused by involuntary physiological movements. Deep-learning-based motion correction methods might provide a solution. However, most studies have been based on directly applying existing models, and the trained models are rarely accessible. Therefore, we aim to develop and evaluate a deep-learning-based method (Motion Correction-Net, or MC-Net) for suppressing motion artifacts in brain MRI scans. Methods: A total of 57 subjects, providing 20,889 slices in four datasets, were used. Furthermore, 3T 3D sagittal magnetization-prepared rapid gradient-echo (MP-RAGE) and 2D axial fluid-attenuated inversion-recovery (FLAIR) sequences were acquired. The MC-Net was derived from a UNet combined with a two-stage multi-loss function. T1-weighted axial brain images contaminated with synthetic motions were used to train the network to remove motion artifacts. Evaluation used simulated T1- and T2-weighted axial, coronal, and sagittal images unseen during training, as well as T1-weighted images with motion artifacts from real scans. The performance indices included the peak-signal-to-noise ratio (PSNR), the structural similarity index measure (SSIM), and visual reading scores from three blinded clinical readers. A one-sided Wilcoxon signed-rank test was used to compare reader scores, with \(p<0.05\) considered significant. Intraclass correlation coefficients (ICCs) were calculated for inter-rater evaluations. Results: The MC-Net outperformed other methods in terms of PSNR and SSIM for the T1 axial test set. The MC-Net significantly improved the quality of all T1-weighted images for all directions (i.e., the mean SSIM of axial, sagittal, and coronal slices improved from 0.77, 0.64, and 0.71 to 0.92, 0.75, and 0.84; the mean PSNR improved from 26.35, 24.03, and 24.55 to 29.72, 24.40, and 25.37, respectively) and for simulated as well as real motion artifacts, both using quantitative measures and visual scores. However, MC-Net performed poorly for images with untrained T2-weighted contrast because the T2 contrast was unseen during training and is different from T1 contrast. Conclusion: The proposed two-stage multi-loss MC-Net can effectively suppress motion artifacts in brain MRI without compromising image quality. Given the efficiency of MC-Net (with a single-image processing time of \(\sim\)40 ms), it can potentially be used in clinical settings.  
MRI; motion correction; deep learning; brain +
Footnote †: journal:
## 4 Numerical Analysis
In the case of TAS with silencing, the highest reliability that can be achieved with \(k_{min}=9\) number of RRHs is of three nines, which can be useful in the case of serving the UE with moderate reliability. However, the only reliability level that is achieved from the silencing scheme with \(k_{min}=6\) RRHs is one nine. We present the result of throughput reliability trade-off in Figure 10. We generate the fading channel coefficient as Rayleigh fading with unit mean. Each RRH and UE is equipped with a single antenna, and the path loss exponent is 3.5 and \(\theta=0\) [dB]. The desired distance to the UE is 20 m, while each interfering node is 40 m. Next, we choose any reference used as a stringent URLLC user and compute the corresponding reliability and average system sum throughput as output in C-RAN networks with a different number of cooperating RRHs for each scheme. As shown, there is a clear trade-off between average system sum throughput and reliability. MRT outperforms silencing and TAS with silencing schemes because cooperating RRHs simultaneously transmit to the reference user. This diversifies the path through multi-point multi-connectivity and has larger diversity gain, improving performance. Meanwhile, the average system sum throughput of the MRT scheme reduces as the number of cooperation increases. This is because cooperating RRHs cannot transmit to their own UE, consequently reducing average system sum throughput. Average system sum throughput of silencing and TAS with silencing shows a similar performance. For example, with \(k=1\), the average system throughput rises slightly. This  
Figure 8: Illustration of EE for silencing, TAS with silencing and MRT with the \(N=10\) and \(\epsilon_{th}=10^{-5}\) as function of \(k\). is because silent RRH benefits other active users in the system with reduced interference. Meanwhile, as \(k\) increases, we see the reduced average system throughput for fewer users being served as the RRH remains silent or cooperates to transmit. Note that the MRT average system sum throughput is small compared to TAS and silencing because other remaining active users experienced full interference, and consequently a degradation of overall average system sum throughput. For, target reliability maintaining the average system throughput, TAS seems to be a better option as compared with silencing and MRT. Note that with the \(k=0\), i.e., full interference: all the schemes have the same average system sum throughput and reliability, which means all the RRH are actively serving their user in the network. Figure 10: Trade-off analysis between reliability and average system sum throughput for silencing, TAS with silencing and MRT schemes as a function of \(k\). We set \(\theta=0\) [dB]. Figure 2:0 Overview of reliability levels achievable with different number of cooperating RRHs \(k\) for silencing, TAS with silencing and MRT schemes with the \(N=10\).
## 5 Conclusions  
In this paper, the vortex-induced force of the deep-water jacket pipe was studied based on the CFD method. The vibration dampers commonly used for vibration reduction of power lines were used on the jacket pipes. The models of the pipe with the vibration dampers were established, and the stability of the model was verified. The wind speed range causing the wind-induced VIV of the pipe was preliminarily estimated. The influence of installing the vibration dampers on the lift and drag coefficients of the pipe was analyzed, and we explained the reason from the perspective of the flow field. The main conclusions are as follows:  
1. The installation of vibration dampers can effectively reduce the vortex-induced force. The lift coefficient of the pipe is reduced by about 65%, the drag coefficient of the pipe is slightly reduced.
2. The influence of the vibration dampers on the vortex-induced force is stable under different wind speeds. The error of the influence of the vibration dampers on the vortex-induced force under different wind speeds is about 2%.
3. The influence of the vibration dampers on the vortex-induced force is related to the arrangement. Compared with the arrangement in one row, when the vibration dampers are arranged in two rows, the vortex shedding frequency is reduced by 16%.
4. The influence of installing the vibration dampers on the flow field of the pipe was analyzed. The high-velocity areas on the upper and lower sides of the pipe are destroyed after the vibration dampers are installed. The vortex shedding is destroyed, and the overall vortex shedding moves backward, thereby reducing the wind-induced vortex force.  
The jacket will have many pipes affected by vortex-induced vibration. This paper only considered one pipe that will vibrate during the construction stage and did not consider different pipe diameters. In addition, fluid-structure interaction was not considered, which requires future study.  
Conceptualization, C.L. and L.L.; methodology, C.L. and L.L.; software, Z.W., J.C. and Y.Y.; validation, L.L., C.L. and Z.W.; formal analysis, C.L.; investigation, Z.W.; resources, C.L.; data curation, J.C. and Y.Y.; writing--original draft preparation, C.L., Z.W. and J.C.; writing--review and editing, L.L. and Y.Y.; supervision, C.L. and J.C.; project administration, C.L. and L.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.
# Optimising Amber Processing Using 3D Scanning: New Perspectives in Cultural Heritage
## 1 Introduction
### Amber Significance and Characteristics  
Research on amber, also called \"the gold of the north\", is conducted by various companies and research institutions specialising in geology, gemmology, archaeology and chemistry. One renowned institution engaged in research on amber is the Institute of Geological Sciences, Polish Academy of Sciences (PAN). This institute performs detailed geological, mineralogical and chemical analyses aimed at understanding the processes of amber formation and its properties. Additionally, research on amber is carried out by private gemmological laboratories that specialise in mineral and gemstone analyses. These laboratories often provide services related to identifying the origin of amber, assessing its authenticity and analysing inclusions inside it, which can provide information about its history. Because amber is also a significant subject of archaeological research, institutions such as archaeological museums and universities conducting archaeological studies often engage in amber analyses, especially if it is found in an archaeological context. It is worth noting that research on amber encompasses diverse scientific fields and requires collaboration among experts from various disciplines to obtain a fuller picture of its origin, properties and history [11].  
Sometimes, inclusions (remnants of plants or insects from the Cretaceous and Cenozoic periods) can be found inside the solidified resin, making such specimens the most valuable, Figure 2 [20].
## 4 Discussion
### Effect of Sediment Porosity on Sound Speed and Density  
[PERSON] [13] analyzed data obtained from 8287 samples from 456 2-to-12 m-long sediment cores, which were obtained from various regions of the Pacific and Atlantic Oceans and the Norwegian, Mediterranean and Black Seas, and derived empirical formulas for calculating the density and the sound speed at the bottom. He also showed that the sound speed has a non-linear dependence on porosity \(P\), noting that at some levels of \(P\), the sound speed can be even less than that in water. Let us calculate the bottom sound speed and density using [PERSON]'s empirical formulas. We assume that the bottom sediment is a two-component medium, and it consists of water and rigid particles only. The density \(\rho_{b}\) and the compressional sound speed \(c_{b}\) of such a media is  
\[\rho_{b}=\rho_{w}(2.604-0.01606P), \tag{11}\]  
\[c_{b}=c_{w}\Big{(}1.631-0.0178P+0.00012P^{2}\Big{)}, \tag{12}\]  
where \(\rho_{w}\) and \(c_{w}\) are the density and the sound speed of the water near the seafloor, respectively, and \(P\) is the porosity of the sediment in terms of percent. \(P\) is limited in this model between 25% to 90%.  
Figure 14 shows the dependence of \(c_{b}\) and \(\rho_{b}\) on the porosity \(P\) (i.e., volume fraction of water), which is calculated here for water-saturated sediment with \(P\) varying from 0.3 to 1 for a 1000 m bottom depth and a sound speed of water near the bottom of 1527 m s\({}^{-1}\)[54]. A comparison with our results implies that the water content in the seafloor sediments of the study area is generally in the range of 50 to 60%.  
Figure 13: A cross plot of the sound speed (blue circles), constrained by depth migration of seismic line ISEM-2073 for the sediment overburden layers between the top salt and the seafloor across the study area vs. the mid-layer depth below the seafloor (Figures S1 and S2 in supplementary information). A first-degree linear trend fit of these values (black line) yields \(c_{0}=1539\) m s\({}^{-1}\), and \(K=0.84\) s\({}^{-1}\), with a correlation factor \(r^{2}=0.93\).
# Influence of Concrete Strength Class on the Long-Term Static and Dynamic Elastic Moduli of Concrete
## 2 Materials and Methods  
### Materials  
The three chosen concrete strength classes were C16/20, C20/25, and C25/30, as classified by Eurocode 2 [11]. A CEM II A-LL 42.5R rapid hardening cement, complying to standard specification [12] and readily available on the market, was selected. This was a composite cement consisting of 65-79% cement clinker and 21-35% a mixture of ground-granulated blast furnace slag (GGBS) and lime.  
River aggregates with rounded edges were purchased from a local supplier. The particle size distribution of all types of aggregates is presented in [10]. A constant wa ter/cement ratio of 0.5 was considered for all three mix proportions shown in Table 1. The super-plasticizer represented 0.5% of the cement mass for each mix proportion, and was decided upon after successive laboratory trials. The fresh properties of each concrete mix presented in Table 1 were previously reported in [10].  
Mix 1 refers to the C16/20 concrete strength class, whereas Mix 2 and Mix 3 refer to the C20/25 and C25/30 concrete strength classes, respectively.
## 2 Spitz Tumors
### MAP3K8-Mutated Spitz Tumors  
The mitogen-activated protein kinase kinase kinase 8 (_MAP3K8_) gene is located on chromosome 10p. It encodes a serine/threonine and tyrosine kinase that is primarily expressed by the immune system and is activated by TNF-alpha, ILIR, and toll-like receptors to promote signaling through activation of the RAF-MEK1/2-ERK1/2 pathway [71, 72, 73]. Several _MAP3K8_ oncogenic fusions and truncations have been described in Spitz tumors [9, 19, 20, 21, 22, 23], which commonly result in the loss of the C-terminal inhibitory/regulatory domain of the protein and subsequent unopposed activation of the N-terminal kinase domain leading to increased MEK1/2-ERK1/2 signaling [74, 75].  
Clinically, _MAP3K8_-fused Spitz neoplasms usually present as pigmented exophytic lesions on the lower extremities of patients of all ages, with a slight female prediction [20, 22]. Morphologically, most of these lesions are nodular or dome-shaped, asymmetric with overlying epidermal hyperplasia, and show a compound melanocytic proliferation with a predominantly nested junctional component [7, 9, 19, 20, 21, 22, 23]. Melanocytes are invariably epithelial with large, uniform nuclei, prominent nucleoli and an abundant eosinophilcytoplasm [7; 20; 23]. Moderate to severe cytologic atypia, deep mitotic figures, absent maturation, scattered multinucleated giant melanocytes, epidermal ulceration, and high-level Pagetoid scatter of melanocytes in the epidermis are frequently reported [7; 20; 23]. Interestingly, _MAP3K8_-fused Spitz neoplasms frequently harbor additional genomic alterations with prognostic implications, namely biallelic inactivation or deletion of _CDKN2A/B_[7; 9; 10; 11; 21]. _MAP3K8_ fusions can be detected using RNA or DNA-based NGS and/or FISH analysis [3].
# A New LoRa-like Transceiver Suited for LEO Satellite Communications +
## 4 Results and Discussion
### DCCSS Performance Evaluation and Comparison with CSS
Figure 5: Robustness of DCSS against a Doppler rate with a different complexity order (\(SF=12\), \(B=B_{ref}\) and \(N_{pay}=51\) bytes). maximum payload size for the slowest data rates, \(SF\in\{10,11,12\}\) on 125 kHz is 51 bytes), for different DR values, in an AWGN channel model. To ensure the fairness between the latter waveforms, the DR is not compensated for both cases and we assume that \(\Delta f\) and \(\Delta tau\) are equal to zero. The results confirm the fact that DCSS is much more robust to DR than CSS. For instance, it can be easily seen that, for CSS signals, the PER is greater than 0.5 for all SNR values, if the DR is equal or greater than 12 Hz/s. Whereas, for DCSS signals, a PER equal to \(10^{-3}\) (respectively, \(10^{-2}\)) is achieved at SNR\(=-18\) dB for DR\(=200\) Hz/s (respectively, DR\(=240\) Hz/s). After evaluating the performance of DCSS, we dedicate the next paragraph to assessing the robustness of our proposed receiver when communication with LEO satellites is considered.