esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Results
### One-Stage vs. Two-Stage  
In this experiment, we compared the performance of the proposed one-stage EfficientViT model with conventional two-stage approaches. The two-stage architecture involves sequential execution of a segmentation network followed by a classification network, where the classification is performed on the segmentation output image. We experimented with 18 combinations formed by pairing 6 segmentation models (U-Net, Attention U-Net, SegNet, DeepLabV3+, EfficientPS, MobileNetV2) with 3 classifiers (ResNeXt-50, DenseNet-121, VGG-16).  
In contrast, the one-stage approach omits segmentation entirely and performs classification using the original input images. This setting includes EfficientViT and three CNN models (ResNeXt-50, DenseNet-121, VGG-16), all trained and tested under the same conditions.  
All models were trained and evaluated using the same dataset, preprocessing pipeline, input resolution (512 x 512), and hardware environment. Inference speed was measured as the average per-image latency (ms) using a batch size of 1. The results are summarized in Table 3.  
Among the two-stage models, the MobileNetV2 + ResNeXt-50 combination achieved the best performance with an accuracy of 98.42% and an F1 score of 0.9860. However, its inference speed and model size were significantly higher than those of the one-stage ResNeXt-50 model, which achieved comparable accuracy (98.30%) at only 3.26 ms and 91.96 MB. Likewise, the one-stage DenseNet-121 (Accuracy: 98.12%; F1 score: 0.9828, Speed: 5.86 ms, Size: 28.87 MB) and VGG-16 (Accuracy: 97.99%; F1 score: 0.9825) models also outperformed their two-stage counterparts across all metrics.  
The proposed EfficientViT model achieved the highest overall performance among all models, with 98.46% accuracy and a 0.9867 F1 score. It also demonstrated fast inference (3.92 ms) and compact model size (36.41 MB), making it a highly efficient choice for real-time applications.
# TMCrack-Net: A U-Shaped Network with a Feature Pyramid and Transformer for Mural Crack Segmentation
###### Abstract  
The detection of crack information is very important in mural conservation. In practice, the number of ancient murals is scarce, and the difficulty of collecting digital information about murals leads to minimal data being collected. Crack information appears in pictures of paintings, which resembles painting traces and is easy to misidentify. However, the current mainstream semantic segmentation networks directly use the features of the backbone network for prediction, which do not fully use the features at different scales and ignore the differences between the decoder and encoder features. This paper proposes a new U-shaped convolutional neural network with feature pyramids and a transformer called TMCrack-net. Instead of U-Net's jump-join, an AG-BiFPN network is used, which consists of two modules: a channel cross-fusion (CCT) module with a transformer and a bidirectional feature pyramid network. While fully using the information in different network dimensions, the channel cross-fusion module optimizes the final features of each layer to reduce the confounding effect caused by the fusion of features. For the fusion of multi-scale channel information with decoder features, we designed a fusion module based on a channel attention (called FCA) to guide the fusion of enhanced encoder features with decoder features and reduce the ambiguity between the two feature sets. To demonstrate the effectiveness and generalization of the model, TMCrack-Net was evaluated on the Tang Dynasty tomb chamber mural dataset and Crack500. Mlou values of 0.7731 and 0.7944 were achieved, respectively, which are better than those of other advanced crack detection methods. The method yields accurate segmentation performance and is advantageous for mural painting crack segmentation tasks.  
murals; crack segmentation; U-Net; BiFPN; FCA
# A Lifetime Maximization Relay Selection Scheme in Wireless Body Area Networks
###### Abstract  
Network Lifetime is one of the most important metrics in Wireless Body Area Networks (WBANs). In this paper, a relay selection scheme is proposed under the topology constrains specified in the IEEE 802.15.6 standard to maximize the lifetime of WBANs through formulating and solving an optimization problem where relay selection of each node acts as optimization variable. Considering the diversity of the sensor nodes in WBANs, the optimization problem takes not only energy consumption rate but also energy difference among sensor nodes into account to improve the network lifetime performance. Since it is Non-deterministic Polynomial-hard (NP-hard) and intractable, a heuristic solution is then designed to rapidly address the optimization. The simulation results indicate that the proposed relay selection scheme has better performance in network lifetime compared with existing algorithms and that the heuristic solution has low time complexity with only a negligible performance degradation gap from optimal value. Furthermore, we also conduct simulations based on a general WBAN model to comprehensively illustrate the advantages of the proposed algorithm. At the end of the evaluation, we validate the feasibility of our proposed scheme via an implementation discussion.  
WBANs; lifetime; energy consumption; residual energy; relay selection; optimization; heuristic solution; IEEE 802.15.6
## 5 Leukocyte-Endothelial Cell-Platelet Interaction  
In the leukocyte-platelet aggregates which characterize atherosclerosis, platelets recruit and activate leukocytes. For their part, leukocytes act on the hemostatic system by activating platelets through immuno-thrombosis, contributing to either pro-inflammatory (cytokine and chemokine release, reactive oxygen production, and lymphocyte development) or anti-inflammatory effects (inhibited monocyte recruitment and cytokine or chemokine production via platelet receptor glycoprotein Ib\(\alpha\) and sCD40L). Platelets are involved in plaque rupture and atherothrombosis in an attempt to preserve blood vessel integrity. By recruiting immune cells, platelets accelerate the atherosclerotic process [45,46]. Moreover, the interactions with the vascular wall are also suspected to impair leukocyte recruitment by platelets, as platelets may interact directly with endothelial cells in atherosclerosis, under the influence of cytokines [47]. In healthy non-obese individuals, ghrelin was shown to exert no effects on either platelets or endothelial cells [48]. Later studies have shown that ghrelin can inhibit platelet aggregation. Its antithrombotic effects were shown by the protective effects of ghrelin pre-treatment on liver coagulation disturbances in rats and by ghrelin involvement in the inhibition of MCP-1 expression, with indirect decreasing effects on platelet aggregation and adhesion [43,49].  
In excessive adipose tissue, chronic inflammation leads to increased platelet volume. Platelets become highly activated and aggregated. In obese adipose tissues of mice, the  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Determining** & **Action** & **References** \\
**Factors** & & \\ \hline \multirow{4}{*}{ Adipose tissue} & Increases the production of adiponectin, & \\  & decreases the production of leptin and resistin. & [PERSON] et al., 2003 [19] \\  & Stimulates adipogenesis by reducing fat & [PERSON] et al., 2003 [21] \\  & oxidation, increases food intake, and & \\  & stimulates preadipocyte differentiation & \\ \hline Adipose tissue & & \\ inflammatory & Inhibits leptin-induced cytokine expression. & [PERSON] et al., 2004 [37] \\ cells & & [PERSON] et al., 2021 [38] \\ \hline \multirow{4}{*}{ Endothelium} & Promotes endothelial cell proliferation, inhibits & \\  & endothelial cell apoptosis and increases the & \\  & expression of eNOS in arterial endothelial cells. & [PERSON] et al., 2020 [8] \\ \hline \multirow{4}{*}{ Atherosclerosis} & Inhibits overproduction of inflammatory & [PERSON] et al., 2003 [39] \\  & cytokines (IL-1, IL-6, IL-8, and TNF-\(\alpha\)), & [PERSON] et al., 2013 [43] \\ \cline{1-1}  & suppresses MCP-1 and the NF-\(\kappa\)B pathway & [PERSON] et al., 2017 [25] \\ \cline{1-1}  & and decreases the expression of Cox-2 in & [PERSON] et al., 2020 [26] \\ \cline{1-1}  & endothelial cells. & [PERSON] et al., 2016 [44] \\ \hline \hline \end{tabular}
\end{table}
Table 1: Actions of ghrelin related to adipose tissues, endothelium, and atherosclerosis.  
interactions between leukocytes and endothelial cells are higher than in lean mice and the platelets are hyperactivated [50].
# New Trends in Separation Techniques of Lithium Isotopes: A Review of Chemical Separation Methods
## 1 Introduction
### Challenges in Development of Separation Methods for Lithium Isotopes Using Electrochemical
#### 2.3.2 Ion-Exchange Methods Using Resin
The distribution coefficient values (K\({}_{\text{d}}\)) of Li ion in an aqueous solution were assessed and it was found that the K\({}_{\text{d}}\) values of sulfonated Pyr-Styr-DVB/SiO\({}_{2}\) resin were lower than those recorded for sulfonated Styr-DVB resin, and from this it can be concluded that pyridine moieties from the sulfonated Pyr-Styr-DVB/SiO\({}_{2}\) have a small adsorption capacity for Li ions [38], possibly due to the lower aromatic character of pyridine which may decrease the \(\pi-\pi\) interactions/stackings [39; 40]. The isotope separation coefficients (\(\varepsilon\)) per unit mass (\(\varepsilon/\Delta\)Mass) value of the sulfonated Pyr-Styr-DVB/SiO\({}_{2}\) resin was calculated to 8.1 \(\times\) 10\({}^{-4}\) values, which is smaller than the \(\varepsilon/\Delta\)Mass values of many Styr-DVB resins (with cross-linkage degree of 50%) reported in the literature for lithium isotope separation studies [41]. [PERSON] et al. conclude that the hydrophobicity of resins can improve the \(\varepsilon/\Delta\)Mass values, while those values are not proportional to the crosslink degree of the resins [38]. Figure 3: Synthesis of sulfonated pyridine-styrene-divinyl-benzene resin embedded into silica (Pyr-Styr-DVB/SiO\({}_{2}\)) for lithium isotope separation. Adapted from [38].
## 5 Conclusions  
When field measurements of SIF are conducted continuously over an extended period, large and unpredictable fluctuations in illumination may result in estimation errors. To address this issue, we proposed in this study to make use of high-frequency PAR data to assess illumination stability, and then used these data to assess the quality of SIF data. The experimental results of a healthy maize canopy indicated that, by using the proposed method to eliminate low-quality data, the qualities of the SIF retrieved by the 3 FLD, SFM, and SVD algorithms were improved. Under cloudy and rapidly changing illumination conditions, the correlations between PAR and SIF retrieved by 3 FLD and SFM were significantly improved after low-quality data were excluded. Therefore, using the data quality assessment method proposed in this paper, reliable SIF data can be selected from the observation results under various illumination conditions, which is crucial to correctly interpret SIF dynamics, detect stresses, establish mechanistic relationships between SIF and GPP, and validate satellite SIF products.  
Conceptualization, S.H. and Z.L.; methodology, S.H.; software, S.H.; formal analysis, S.H.; investigation, S.H. and Z.L.; resources, S.H., Z.C., H.J., S.X., H.Z. and S.R.; writing--original draft preparation, S.H.; writing--review and editing, Z.L.; visualization, S.H.; supervision, Z.L.; project administration, Z.L.; funding acquisition, Z.L. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China (grant number 42071402) and the Water Resources Science and Technology Project of Jiangxi Province, China (202023 ZDKT10, KT201706).  
**Acknowledgments:** We thank the Natural Science Foundation of China for their support.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# A Novel Geo-Localization Method for UAV and Satellite Images Using Cross-View Consistent Attention
## 3 Proposed Method  
### System Overview  
Geo-localization of UAV and satellite images can be regarded as a bidirectional image retrieval problem [9]. Given a satellite image, the most similar UAV image should be queried to obtain the current longitude and latitude and realize drone navigation. On the contrary, the satellite image for drone-view target localization is queried when a UAV image is given.  
As shown in Figure 2, the proposed method consists of four main parts: color transfer, a Transformer-based module for image retrieving, a piecewise soft-margin triplet loss function, and a similarity calculation module of the test images. In Section 3.3, this method uses the property of orthogonal color space and takes the color distribution of the satellite images as a reference to transfer the color of UAV images. The advantage of color transfer is to overcome the information inconsistency between UAV images and satellite images due to the changing external circumstance, such as seasons, weather, and illumination conditions. In Section 3.2, UAV and satellite images are inputted to two separate Transformer encoders as query and reference and obtain embedded feature vectors, respectively. These embedded feature vectors are used to calculate the similarity of images in different views afterward. In Section 3.4, different similarity calculation methods are compared to calculate the similarity between the cross-view images. A novel piecewise soft-margin triplet loss function is developed in Section 3.5 to overcome the difficulties in network convergence caused by the unmatched numbers of UAV and satellite images. A data augmentation technique for satellite images is proposed in Section 3.6, which benefits the image training stage.
## 4 Loss Reduction Optimization Design  
### Proposed Innovative Design Improvements  
Several innovative design improvements have been developed to minimize electromagnetic losses and enhance thermal performance in high-speed magnetic field-modulated motors for flywheel energy storage systems. (1) Advanced composite rotor structures incorporating carbon fiber reinforcement with embedded copper shielding layers effectively reduce rotor eddy current losses by up to 67% while maintaining mechanical integrity at extreme rotational speeds. The layered configuration creates destructive interference patterns for induced eddy currents while preserving structural strength characteristics essential for high-speed operation. (2) Optimized modulator geometry utilizing non-uniform pole distribution with sinusoidal profile variation along the axial direction substantially mitigates spatial harmonic components responsible for eddy current losses. This configuration redistributes the magnetic flux more uniformly, reducing peak loss density by 42% compared to conventional uniform modulators. (3) Dual-material permanent magnet configuration combining high-remanence NdFeB segments with high-resistivity SmCo segments strategically positioned at regions of maximum harmonic concentration achieves a 38% reduction in magnet losses compared to homogeneous magnet arrangements. The tailored material distribution effectively addresses location-specific loss generation mechanisms. (4) Integrated thermal management solutions featuring direct-contact liquid cooling channels embedded within modulator structures substantially improve heat dissipation from critical loss hotspots. The microchannel configuration enables precision cooling with minimal impact on electromagnetic performance by maintaining optimal operating temperatures throughout the entire speed range. (5) Adaptively controlled field weakening strategies utilizing real-time loss estimation models dynamically optimize excitation patterns based on instantaneous operating conditions. This approach enables proactive loss management across diverse speed and load profiles, substantially improving system efficiency during transient operations. Implementation of these improvements collectively yields a 29% reduction in total electromagnetic losses while enhancing thermal stability by maintaining temperature gradients below 25 \({}^{\circ}\)C across all active components.
## 4 Experimental Results and Discussion
### Discussion  
In this section, we discuss how to improve the efficiency of the proposed AGBCPT method, how to make the derived trading strategy more profitable and stable, and the applications of AGBCPT.  
For the first issue, the main differences between AGBCPT, the proposed approach, and GBCPT, the compared approach, are the encoding schema and the fitness function. In AGBCPT, six parameters are encoded into a chromosome, and the return and risk are jointly considered to evaluate the fitness value of a chromosome. In GBCPT, three parameters are used, and every chromosome is evaluated only by return. Hence, execution times for AGBCPT are slightly longer than those for GBCPT. Taking AGBCPT as an example, the execution time is 43,741 s with a population size of 60 and 40 stocks, which is time-consuming. The efficiency of AGBCPT can be improved via soft computing techniques or hardware devices. For example, chromosomes could be clustered into groups. For every group, the fitness value of a selected representative chromosome could be calculated and used as the fitness value of the other chromosomes in the same group. By thus using \(k\)-means clustering, only \(k\) chromosomes are selected to calculate fitness values, resulting in reduced time costs. Alternatively, the graphics processing unit (GPU) could be utilized to speed up data calculations.  
For the second issue, in the proposed approach, the correlation coefficient of stocks and Bollinger Bands are used to identify trading pairs and signals. However, other factors could be considered to increase profitability and reduce risk. For instance, company fundamentals, e.g., earnings per share, or the P/E ratio, could be used as a filter to avoid high risk stocks. In addition, industrial information could be considered by using the correlation coefficient of industries to identify relationships between industries, yielding more profitable and stable trading pairs.  
As to the applications of AGBCPT, along with the popularity of program trading in recent years, AGBCPT could be enclosed as a module for providing programmers to design trading procedure which can generate trading signals automatically for trading. Besides, for securities company, from customer relationship management point of view, AGBCPT  
Figure 17: AGBCPT and GBCPT profits in different testing periods.  
can be embed in their trading system as a function for providing more information to users, which may increase customer loyalty.
# Integration of Directional Antennas in an RSS Fingerprinting-Based Indoor Localization System
## 5 Experimental Tests
### Test and Results  
More than 200 SR configurations have been set for different combinations of directional and omnidirectional antennas chosen from the initial deployed set with 17 SRs. In order to evaluate the system performance for each configuration, a pathway was established to be followed by the users throughout the whole scenario, as observed in Figure 12. The pathway has been designed to go over all of the target rooms. As in the site survey process, different people carried the tag fixed to their chest to perform the tests with the tag transmitting beacons periodically as the person moves all over the defined areas. Therefore, the reliability of the system is tested in quite hard realistic conditions, taking into account that people movement and body orientation are increasing the RSS temporal fluctuation even more [30].  
The pathways were followed in both directions, and the tests were repeated daily at different time frames during one week. During the tests, the system was operating in its online stage, and the tag was configured to transmit \(N=10\) beacons periodically with a shorter refresh time of \(T=250\) ms (higher \(N\) and lower \(T\) values would overload the system). The tag power transmission was \(P_{TX}=0\) dBm (as previously established during the site-survey process, to ensure connectivity between the tag and all of the SRs along the whole scenario most of the time). Hence, about 500 positions were inferred for each pathway (four per second during 2 min of walking). Finally, a total of 27 tests were performed.  
The probability matrix _PM_ presented in Equation (4) was calculated from the test results for every SR configuration. The \(P_{Sij}\) per each room was easily obtained from the main diagonal of the _PM_. The overall \(P_{S}\) was also obtained applying Equation (3), dividing the total number of successful estimations over the total number of estimations carried out during the test.  
Table 2 presents the results for the most outstanding SR configurations in terms of location success probability (\(P_{S}\)). The table represents the minimum performance (per room and global) obtained for 90% of the 27 tests performed per each configuration. Furthermore, in order to give a deeper comprehension of the results presented in Table 2, Figure 13 shows a box-and-whisker plot with further information about the overall \(P_{S}\) resulting from the 27 tests performed for each SR configuration analyzed in Table 2. This analysis has been conducted using MATLAB function \"boxplot\", given the calculated \(P_{S}\) resulting from each test. In each plot, the central mark is the  
Figure 12: Pathway followed (in blue) by the users during experimental tests.  
median \(P_{S}\) obtained for each configuration, the edges of the box are the 25 th and 75 th percentiles; the whiskers extend to the most extreme resulting \(P_{S}\) values (not considered as outliers); and the considered outliers are plotted individually as red crosses.
## 2 Methods: Three-Dimensional Wear Model and Numerical Method
### Numerical Calculation Method
#### 2.2.3 Hydraulic Performance Test  
To verify the correctness of the numerical model, we conducted hydraulic performance tests on the mining pump. In numerical calculations, different inlet velocities can be given to reflect the inlet boundary conditions of mining pumps under different flow conditions in order to obtain performance output curves under different flow conditions, as shown in Figure 4.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Mesh Scheme** & **Impeller** & **Guide Vane** & **Inlet/Outlet Section** & **Total** & **Head (m)** \\
**Number** & **(Ten Thousand)** & **(Ten Thousand)** & **(Ten Thousand)** & **(Ten Thousand)** & **(Ten Thousand)** & **Head (m)** \\ \hline
1 & 9.1 & 24.9 & 13.2 & 94 & 31.71 \\
2 & 15.2 & 42.0 & 22.8 & 160 & 30.84 \\
3 & 20.0 & 55.1 & 29.9 & 210 & 31.22 \\
4 & 29.1 & 80.2 & 42.9 & 300 & 30.35 \\
5 & 51.5 & 142 & 76.0 & 530 & 30.36 \\
6 & 66.0 & 184 & 101 & 700 & 30.31 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Mesh independence verification.  
By comparing the performance curve obtained from the experiment, it can be found that the numerical simulation results are consistent with the experimental results, indicating the effectiveness of the numerical calculation method.
## 2 Materials and Methods
### The Fundamentals
#### 2.1.2 Sensing, Data Acquisition, and Wireless Communication
We employ a BLE sniffer from \"Bluefruit LE Sniffer (BLE 4.0)\" (provided by Adafruit Industries(r), New York, NY, USA), interfaced with a PC and a well-known open source software tool, \"Wireshark 4.0\" to read the data packets. Our approach involves utilizing a wireless sensor node as a BLE-based non-connectable beacon device operating exclusively in broadcasting mode. To ensure security and data protection, this beacon device does not interfere with other devices; instead, it solely transmits internally stored data. This approach involves intermittent data transmission, with the device returning to a low-power sleep mode in between transmissions. By eliminating receiving capabilities and minimizing transmission time, we aim to achieve the lowest possible power consumption and maximize efficiency.