esa-sceva/satcom-chunk-collection huggingface dataset:
# A Novel Hybrid Model for Cantonese Rumor Detection on Twitter
## 5 Conclusions and Future Work  
In this paper, we have proposed a novel hybrid model called XGA for detecting Cantonese rumors, which takes advantage of XLNet, BiGRU, and the attention mechanism. To be specific, we extracted both semantic and sentiment features for the detection. The XLNet, which was pre-trained and fine-tuned on Cantonese data, was used to produce text-based and sentiment-based embeddings. In addition, we combined the character embeddings extracted by XLNet with Cantonese word embeddings to learn the words' external contexts and internal structures. Furthermore, we made use of BiGRU and the attention mechanism to obtain the important semantic features, which were then concatenated with sentiment features to get the final classification results. We performed two experiments to evaluate the effectiveness of our model and came to the following conclusions: the XLNet performed better than other word embedding models, and the XGA model we designed achieved the F-score of 0.9267 in Cantonese rumor detection and outperformed other widely used detection models in all metrics.  
In the future, we plan to conduct further research on Cantonese word segmentation to improve the performance of word embeddings. In addition, we will try to discover more effective features for the Cantonese rumor detection and make use of them in our model.  
Conceptualization, H.W., X.C., L.K., H.S. and Z.L.; methodology, H.W., X.C., and L.K.; validation, X.C. and L.K.; formal analysis, X.C. and L.K.; investigation, X.C. and L.K.; data curation, X.C., L.K., Z.L. and H.S.; writing--original draft preparation, X.C. and L.K.; writing--review and editing, X.C., L.K., H.W., Z.L. and H.S.; supervision, H.W.; project administration, X.C. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding. This work was completed under the guidance of [PERSON] of Sichuan University, China.  
The authors declare no conflicts of interest.
# An Intelligent Parking Management System for Urban Areas
## 3 Description of the System  
To monitor the number of available spaces in the parking zones a low-cost, low-energy WSN will be employed. This means that a complex roll-out or new cabling infrastructure will not be required in the zone where the proposed system is deployed. The sensors will detect the passage of vehicles on the roads into and out of the parking areas located on public roads in real-time. The authorities and drivers will, therefore, know the occupancy levels of the parking zones at all times. The real-time response is essential because the system would not be practicable if there was a considerable delay in updating these data. Relaying pseudo real-time information to drivers avoids them having to spend more time on the road searching for a parking space, which hinders the circulation of other vehicles and increases fuel consumption, emissions, and noise pollution. Therefore, the proposed system will enable transport regulators to manage public parking zones sustainably. In addition, to facilitate a scalable and flexible roll-out in large urban areas, the system can make use of virtualisation and computing paradigms to obtain the processing and storage resources required by the system architecture. This will enable comprehensive, centralised handling of the data provided by the sensor network in a control centre.  
Figure 1 shows the system being deployed on a public road and in a controlled parking area. The scheme represents the sensors and their direction on the access points and their communication with the gateway that relays the signal to the data centre. This gateway system may also provide in situ information on the occupancy level of both areas through an LED system.
# Anthropometric Characteristics and Somatotype of Young Slovenian Tennis Players
## 5 Conclusions  
This study investigated somatotype development alongside detailed anthropometric and body composition changes in young Slovenian tennis players aged U12 to U18. Our findings revealed significant age- and sex-related differences not only in somatotype profiles but also in body height, mass, BMI, skinfold thicknesses, girths, limb lengths, and bone breadths. The detailed anthropometric characteristics provide valuable normative data for longitudinal monitoring, athlete profiling, and optimisation of talent development strategies in tennis. Specifically, age-related increases were observed in body size and muscularity indicators, while fat distribution showed site-specific variation across adolescence. Sex differences became more pronounced with age, particularly for body composition variables such as skinfold thickness, reflecting differing growth and maturation trajectories between boys and girls. These comprehensive results expand upon previous somatotype-focused studies by providing robust evidence of concurrent anthropometric and body composition development patterns. For practitioners, the findings emphasise the importance of integrating somatotype assessments with anthropometric monitoring to design age- and sex-specific training programs. Such individualised approaches can optimise physical conditioning, support healthy growth, and reduce injury risk during critical developmental windows in youth tennis players. Future research should continue to explore how these morphological changes relate to functional performance and injury prevention, further informing evidence-based training guidelines.  
**Author Contributions:** Conceptualisation, A.G. and A.F.; methodology, A.G.; software, A.G.; validation, A.G., T.F. and A.F.; formal analysis, A.G.; investigation, A.F.; resources, T.F.; data curation, A.F.; writing--original draft preparation, A.F.; writing--review and editing, A.G. and T.F.; visualisation, A.G.; supervision, T.F.; project administration, T.F.; funding acquisition, A.F. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Slovenian Research Agency (grant number P5-0147).  
**Institutional Review Board Statement:** This study was conducted in accordance with the Declaration of Helsinki and approved by the Commission for Ethical Issues in Sport, Exercise and Physical Activity in the Faculty of sport, University of Ljubljana (14 June 2025, no. 033-5/2025-16).  
**Informed Consent Statement:** Informed consent was obtained from all subjects involved in this study.  
**Data Availability Statement:** The raw dataset supporting the conclusions of this article will be made available by the authors on request.  
**Acknowledgments:** The authors thank all the athletes for their participation in this study.  
**Conflicts of Interest:** The authors declare no conflicts of interest.
# Legal Judgment Prediction via Heterogeneous Graphs and Knowledge of Law Articles
## 3 Our Method
### Graph Construction Based on Legal Text
#### 3.2.2 Point-Wise Mutual Information Graph  
PMI is a way to calculate word association, the value of which represents the closeness of the relation between two words. The basic idea of PMI is to count the probability of two words appearing together in the text. If the probability is higher, its relevance is closer and the association is higher. PMI is calculated as follows:  
\[E_{i,j}=PMI(i,j) = log\frac{p(i,j)}{p(i)p(j)}\] \[p(i,j) = \frac{\#NW(i,j)}{\#NW} \tag{2}\] \[p(i) = \frac{\#NW(i)}{\#NW}\]  
where \(\#NW\) is the number of sliding windows defined in the whole dataset, \(\#NW(i,j)\) is the number of windows containing word \(i\) and word \(j\) and \(\#NW(i)\) is the number of sliding windows containing word \(i\). When PMI is positive, the larger its value is, the greater the semantic relevance between two words it represents. When PMI is negative, there are basically no relationships between the two words. Only the edges with positive PMI values are retained in our method and the edges with negative weights are directly discarded.
# Weed Detection in Rice Fields Using Remote Sensing Technique: A Review
## 5 Weed Detection Using Remote Sensing Technique
### Image Data Collection  
There are multiple platforms available for data gathering for weed detection in crops, such as digital cameras [37], hand-held spectroradiometers [38], polarization spectroscopy [39], and satellites [40]. However, unmanned aerial vehicles (UAV) are the most popular platforms researchers use to identify weeds in crops, due to their availability, high-quality data delivery, and ease of handling [41]. Nevertheless, the data collection differs in the types of sensors attached to UAVs: RGB, multispectral, or hyperspectral.
# Enhanced Multistream Fast TCP: Rapid Bandwidth Utilization after Fast-Recovery Phase
## 4 Simulation Setup
### Experimental Setup and Network Topology
#### 4.1.2 Evaluation Method  
The simulation experiments were performed to analyze the behavior of EMFast TCP after the fast-recovery phase and the results were compared with Fast TCP, MFast TCP, TCP New Reno, and SCTP. We desired to calculate the convergence time of the transport protocols after the fast-recovery phase to see its impact on goodput and throughput in comparison with the proposed algorithm. An error-model was used to introduce packet loss. The packet was completely removed from the system; so, the receiving node could not receive the specific packet. This created a gap in the sequence number on the receiver's side and the data was received out of order. This phenomenon triggers the fast-retransmit phase following the fast-recovery phase. After the fast-recovery phase, the protocols increased their congestion window as per their algorithm to consume the available bandwidth of the network link.  
Each simulation experiment was repeated five times to collect the data, and average values were used to compare the performance of EMFast TCP with other protocols. In the first experiment, independent traffic for EMFast TCP, Fast TCP, MFast TCP, TCP Reno, and SCTP was generated without any other traffic/flow. This scenario was created to study the behavior of the protocols in isolation. In this experiment, Fast TCP, MFast TCP, TCP New Reno, and SCTP were using their default algorithm to manage their congestion window after the fast recovery. In second experiment, four additional flows of TCP New Reno were generated along with the traffic of protocols that are under study. In these experiments, we investigated the convergence time, fairness index, end-to-end goodput, and throughput.
# DK-SLAM: Monocular Visual SLAM with Deep Keypoint Learning, Tracking, and Loop Closing
## 3 Deep Keypoint-Based Monocular SLAM
### Deep Keypoint Meta-Learning
#### 3.1.4. The Distribution Strategy of Deep Keypoints  
To ensure a balanced dispersion of learned keypoints across all scales and corners within an image, we incorporate a keypoint distribution strategy during the feature extraction stage. We uniformly distribute the entire set of keypoints across a multi-scale image pyramid. Within each layer of the image pyramid, a predefined number of keypoints is distributed evenly within the grid of different regions on the image. Thus, this strategy can prevent the concentration of learned keypoints in specific areas.  
```
0: Feature training dataset \(D_{f}\), inner loop learning rate \(\alpha_{1}\), outer loop learning rate \(\alpha_{2}\).
1: Copy the initial network parameters as \(\theta_{a}\) and \(\theta_{b}\).
2:while not done do
3: Sample a batch of support set \(D_{s}\) and query set \(D_{q}\) from \(D_{f}\), whose batch size is the same
4: Sample a minibatch \(D_{s}^{i}\) from \(D_{s}\). Sample a minibatch \(D_{q}^{i}\) from \(D_{q}\). Where \(i=0...n-1\). \(n\) is the number of batch size.
5:for\(D_{s}^{i}\) and \(D_{q}^{i}\) in \(D_{s}\), \(D_{q}\)do
6: Calculate the gradient on \(\theta_{a}\) using \(D_{s}^{i}\) and Equation (4). The gradient is \(\bigtriangledown_{\theta_{a}}L_{all}\).
7: Update \(\theta_{a}\) with \(\bigtriangledown_{\theta_{a}}L_{all}\). \(\theta_{a}^{\prime}=\theta_{a}-\alpha_{1}\bigtriangledown_{\theta_{a}}L_{all}\)
8: Repeat steps 6 and 7 for m iterations. Received updated m times \(\theta_{a}^{m}\). In our implementation, we set m as 4. We call these iterations as inner loop.
9: Calculate the gradient on \(\theta_{a}^{m}\) using \(D_{q}^{i}\) and Equation (4). The gradient is \(\bigtriangledown_{\theta_{a}^{m}}L_{all}\).
10: Update \(\theta_{b}\) with \(\bigtriangledown_{\theta_{a}^{m}}L_{all}\). \(\theta_{b}^{\prime}=\theta_{b}-\alpha_{2}\bigtriangledown_{\theta_{a}^{m}}L _{all}\) We call the updating for \(\theta_{b}\) as outer loop.
11:endfor
12:endwhile
```  
**Algorithm 1** The Procedure of Deep Keypoint Meta-Learning in DK-SLAM.
## 2 The Adopted Technology  
The proposed design is based on the commercial 0.15 \(\upmu\)m GaAs p-HEMT process from WIN Semiconductor Corp, whose cross-section on a GaAs substrate with a thickness of 100 \(\upmu\)m and a dielectric constant of 12.9 is illustrated in Figure 2. It consists of air and SiN layers (with a dielectric constant of 6.9) with thicknesses of 0.15 \(\upmu\)m and 2.3 \(\upmu\)m, respectively. Two metal layers, from the top to the bottom, Metal-2, and Metal-1, have thicknesses of 4 \(\upmu\)m and 1.33 \(\upmu\)m, respectively. The technology provides thin-film resistors (TFRs) with a square resistance of 50 ohms and is available in a variety of transistor models, including coplanar waveguide (CPW) transistors, switching transistors, and E/D mode transistors (for level shifting circuits). The Metal-Insulator-Metal (MIM) capacitor can be realized by using via holes (via\({}_{2}\)) and double-metal layers. In addition, the high resistivity substrate, low loss tangent and high conductivity metal layer can effectively reduce the dielectric loss and conduction loss of all the above circuits. Consequently, the process is ideally suited for MMIC designs with low noise amplifiers, mixers, attenuators and phase shifters.
## 3 Results and Discussion
### Antimicrobial Properties and Biocompatibility of the Hydrogel  
As a biomaterial, the biocompatibility and antibacterial properties of a hydrogel are crucial, wherein a cytocompatibility >70% is preferable [46]. Thus, we tested the cytotoxicity of the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel using the CKK-8 reagent, and the cell viability was determined to be 89.16%, as shown in Figure 7a. In addition, the cell morphology can be seen in Figure 7b, wherein it is apparent that the majority of L929 cells were still alive (green fluorescence), and only a small number of dead cells were observed (red color) [44; 45]. The cells were spindle-shaped, indicating that the growth conditions were favorable and that the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel exhibited a low cytotoxicity along with a high biocompatibility, thereby rendering it a suitable candidate material for use in wearable devices.  
Figure 6: SEM images of (**a**) the PAM hydrogel and (**b**) the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel. **(c**) The hydrogel adheres to the extended human elbow joint. (**d**) The hydrogel deforms as the human elbow bends. (**e**) Change in resistance with an increase in the stress–strain. (**f**) Change in the resistance upon arm movement.  
Additionally, we evaluated the antibacterial activity of the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel against _E. coli_ and _S. aureus_. In Figure 7c, the two Petri dishes on the left-hand side of the figure represent the control group, while the right-hand images represent the _E. coli_ and _S. aureus_ colonies on the agar plate after contact with the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel on the agar plate. Compared with the blank group, the colony counts of the two bacteria were greatly reduced in the hydrogel-treated group. As a result, the antibacterial activities of the hydrogel against _E. coli_ and _S. aureus_ were determined to be 10.92 and 65.92%, respectively, and this was attributed to the coordination complexation between Zn\({}^{2+}\) and the BHMP carboxyl groups enhancing the antibacterial properties of the hydrogel. This also led to a bactericidal effect, indicating that the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel exhibited good bactericidal properties against both bacteria [40]. Therefore, the P(BHMP-AM)-Zn\({}^{2+}\) hydrogel exhibited excellent antibacterial properties against _E. coli_.
## 4 Discussion  
The present study systematically compared the physiological demands and performance outcomes between cycling and running sprint tests among professional soccer players. The main results underscore the distinctive energy demands and system contributions specific to each modality, which bear significant implications for athletic training  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline  & \multicolumn{2}{c}{**Running Test**} & \multicolumn{2}{c}{**Cycling Test**} \\ \cline{2-5}  & \(\mathbf{R^{2}}\) & \(\boldsymbol{p}\)**-Values** & \(\mathbf{R^{2}}\) & \(\boldsymbol{p}\)**-Values** \\ \hline Peak Power (W) & & & & \\ ATP-PCr (kJ) & 0.58 & 0.001 & 0.46 & 0.005 \\ Glycolytic (kJ) & 0.41 & 0.019 & 0.36 & 0.026 \\ Oxidative (kJ) & 0.31 & 0.078 & 0.29 & 0.081 \\ Mean Power (W) & & & & \\ ATP-PCr (kJ) & 0.35 & 0.030 & 0.31 & 0.037 \\ Glycolytic (kJ) & 0.38 & 0.011 & 0.34 & 0.015 \\ Oxidative (kJ) & 0.33 & 0.051 & 0.28 & 0.053 \\ Fatigue index (\%) & & & & \\ ATP-PCr (kJ) & & & & \\ Glycolytic (kJ) & & & & \\ Oxidative (kJ) & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: Coefficient of determination (R\({}^{2}\)) of the relationship between energy system contribution and performance variables for the repeated sprint modalities.  
Figure 4: Correlation heatmap of performance metrics.  
and performance optimisation. The core objective of this investigation is to bridge a gap in knowledge by comparing the physiological demands and performance outcomes of cycling versus running sprints, thereby offering insights into the most appropriate testing modality for soccer players. The primary outcomes highlighted significant statistical differences in performance and physiological reactions between the cycling and running assessments, excluding lactate changes and the peak heart rate (HRpeak). Importantly, it was observed that the running tests elicited a greater total energy expenditure (TEE) and energy demand from the participants. Contrary to previous assumptions, the performance correlations between the test protocols (running and cycling) were less robust than anticipated. This finding suggests that cycling might not be the optimal modality for testing repeated sprint ability (RSA) in running based sports as soccer.
# A Domain-Based, Adaptive, Multi-Scale, Inter-Subject Sleep Stage Classification Network
## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & \multicolumn{2}{c}{**Only L\({}_{\text{Jy}}\) (CB)**} & \multicolumn{2}{c}{**Only L\({}_{\text{Jy}}\) (MF)**} & \multicolumn{2}{c}{**L\({}_{\text{Jy}}\)(MF)**} + \(\sigma\)L\({}_{\text{Jy}}\) \\ \cline{3-8}  & & **Acc** & **CK** & **Acc** & **CK** & **Acc** & **CK** \\ \hline SHHS2 & Before DA & 0.584 \(\pm\) 0.038 & 0.358 \(\pm\) 0.043 & 0.588 \(\pm\) 0.006 & 0.396 \(\pm\) 0.054 & 0.522 \(\pm\) 0.042 & 0.277 \(\pm\) 0.068 \\  & After DA & 0.592 \(\pm\) 0.035 & 0.415 \(\pm\) 0.026 & 0.834 \(\pm\) 0.014 & 0.788 \(\pm\) 0.019 & 0.849 \(\pm\) 0.027 & 0.837 \(\pm\) 0.039 \\ \hline SHHS1 & Before DA & 0.556 \(\pm\) 0.037 & 0.285 \(\pm\) 0.018 & 0.522 \(\pm\) 0.024 & 0.284 \(\pm\) 0.025 & 0.499 \(\pm\) 0.037 & 0.267 \(\pm\) 0.039 \\  & After DA & 0.561 \(\pm\) 0.049 & 0.304 \(\pm\) 0.061 & 0.787 \(\pm\) 0.047 & 0.722 \(\pm\) 0.076 & 0.827 \(\pm\) 0.031 & 0.790 \(\pm\) 0.048 \\ \hline MESA & Before DA & 0.578 \(\pm\) 0.041 & 0.348 \(\pm\) 0.080 & 0.575 \(\pm\) 0.078 & 0.340 \(\pm\) 0.035 & 0.623 \(\pm\) 0.029 & 0.390 \(\pm\) 0.043 \\  & After DA & 0.604 \(\pm\) 0.031 & 0.392 \(\pm\) 0.073 & 0.638 \(\pm\) 0.014 & 0.350 \(\pm\) 0.025 & 0.868 \(\pm\) 0.030 & 0.840 \(\pm\) 0.047 \\ \hline SHHS1\(\rightarrow\)MESA & Before DA & 0.602 \(\pm\) 0.031 & 0.295 \(\pm\) 0.044 & 0.528 \(\pm\) 0.041 & 0.363 \(\pm\) 0.036 & 0.524 \(\pm\) 0.042 & 0.325 \(\pm\) 0.038 \\  & After DA & 0.558 \(\pm\) 0.039 & 0.292 \(\pm\) 0.055 & 0.702 \(\pm\) 0.053 & 0.622 \(\pm\) 0.092 & 0.851 \(\pm\) 0.032 & 0.803 \(\pm\) 0.054 \\ \hline SHHS2\(\rightarrow\)MESA & Before DA & 0.557 \(\pm\) 0.048 & 0.224 \(\pm\) 0.112 & 0.560 \(\pm\) 0.038 & 0.316 \(\pm\) 0.064 & 0.541 \(\pm\) 0.054 & 0.297 \(\pm\) 0.043 \\  & After DA & 0.528 \(\pm\) 0.066 & 0.299 \(\pm\) 0.037 & 0.790 \(\pm\) 0.032 & 0.693 \(\pm\) 0.065 & 0.857 \(\pm\) 0.034 & 0.809 \(\pm\) 0.042 \\ \hline SHHS2\(\rightarrow\)SLPDB & Before DA & 0.376 \(\pm\) 0.041 & 0.055 \(\pm\) 0.030 & 0.404 \(\pm\) 0.062 & 0.023 \(\pm\) 0.067 & 0.423 \(\pm\) 0.098 & 0.105 \(\pm\) 0.042 \\  & After DA & 0.408 \(\pm\) 0.035 & 0.022 \(\pm\) 0.042 & 0.771 \(\pm\) 0.025 & 0.648 \(\pm\) 0.044 & 0.822 \(\pm\) 0.025 & 0.747 \(\pm\) 0.055 \\ \hline SHHS2\(\rightarrow\)SHHS1 & Before DA & 0.423 \(\pm\) 0.023 & 0.314 \(\pm\) 0.040 & 0.450 \(\pm\) 0.034 & 0.265 \(\pm\) 0.092 & 0.436 \(\pm\) 0.052 & 0.235 \(\pm\) 0.046 \\  & After DA & 0.446 \(\pm\) 0.038 & 0.318 \(\pm\) 0.024 & 0.752 \(\pm\) 0.040 & 0.701 \(\pm\) 0.058 & 0.798 \(\pm\) 0.039 & 0.747 \(\pm\) 0.057 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: The comparison results of different loss computation. Figure 8: Confusion matrix of the subject-specific sleep stage classification under the cross-dataset test when the training set comes from SHHS2, and the test set comes from SLPDB.
# Cooperative SWIPT MIMO-NOMA for Reliable THz 6G Communications
## 7 Conclusions  
This paper thoroughly studied the application of the EH technique to a cooperative MIMO-NOMA system for THz communications. The EH coefficient was derived to verify the intended SINR, data rates, and spectral efficiency for MIMO-NOMA served users. The maximal possible comparable EH-based energy efficiency was examined in accordance with a 1 Gbps reference point to the far user and 3 Gbps to the near user. The system outperformed comparable studies (e.g., similar cooperative MIMO-NOMA THz communication system) in terms of gain with a simpler design. Furthermore, it outperformed our previous work using a similar simplified system with an SISO scheme, providing better  
Figure 8: Sum rates vs. transmit power.  
Figure 7: OP vs. transmit power.  
overall performance (in terms of reliability, OP, SE, and EE) by more than 50% (with a doubled individual user gain), considering the simplicity and reliability tradeoff. Overall, the findings demonstrated how the defined strategies successfully preserved continued communication between the BS and the potentially obstructed FU, as well as how the overall system performance was greatly enhanced. Additionally, this work provided a dynamic path-selection mechanism for further reliability. Moreover, it is worth noticing that the scalability of the system presents a flexible adaptation for system planners as the examined parameters are adjustable according to the deployment situations. To the best of the authors' knowledge, SWIPT has never been adopted with such a system of cooperative THz MIMO-NOMA systems achieving such results. The SE, EE, and reliability have not previously been improved, especially using the dynamic mechanism we adopted.  
Conceptualization, H.W.O.; methodology, H.W.O.; software, H.W.O.; validation, H.W.O.; formal analysis, H.W.O.; investigation, H.W.O.; resources, H.W.O.; data curation, H.W.O.; writing--original draft preparation, H.W.O.; writing--review and editing, N.S.; visualization, N.S.; supervision, H.A.-R.; project administration, H.A.-R.; funding acquisition, N.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The authors declare no conflict of interest.