esa-sceva/satcom-chunk-collection huggingface dataset:
# User Comment-Guided Cross-Modal Attention for Interpretable Multimodal Fake News Detection
###### Abstract
To address these challenges, this work tackles three fundamental research problems: the effective integration of user comments as a primary modality rather than auxiliary information in multimodal fake news detection; the design of cross-modal attention mechanisms capable of capturing fine-grained semantic relationships between news content and social validation signals; and the development of interpretable detection systems that provide transparent decision-making processes for practical deployment scenarios. These problems arise from the limitations of existing methods that treat user comments as supplementary data and lack the ability to capture nuanced cross-modal interactions while providing explainable detection decisions. To bridge these gaps, we propose the UC-CMAF framework, which fundamentally transforms the role of user comments from auxiliary information to a primary modality while introducing novel adaptive cross-modal attention mechanisms for comprehensive fake news detection. Our research objectives are threefold: first, to develop a framework that effectively harnesses collective intelligence and social validation signals embedded in user comments; second, to design sophisticated cross-modal attention mechanisms that capture intricate semantic relationships between textual claims, visual evidence, and user feedback; and third, to ensure interpretable detection outcomes through comprehensive attention visualizations and hierarchical importance scoring, thereby enabling transparency and facilitating practical deployment in real-world fact-checking scenarios. The main contributions of this paper include three aspects. First, we propose UC-CMAF, an innovative multimodal fusion framework that successfully integrates three different information modalities--news text, images, and user comments--for fake news detection. Second, UC-CMAF integrates an adaptive co-attention fusion mechanism that can dynamically adjust weights between different modalities, achieving efficient cross-modal information fusion. Finally, we conducted extensive experimental validation on multiple datasets, demonstrating the excellent performance of the UC-CMAF model in fake news detection tasks, and further validated the importance of each component in the model through ablation studies. While effectively identifying fake news, improving the interpretability of detection decisions is of great significance for building public trust and supporting human inter vention [19; 20]. With the rapid development of Explainable Artificial Intelligence (XAI), incorporating its principles into multimodal misinformation identification tasks can achieve the synergistic goal of \"visual explanation + social context explanation\" [21; 22]. Specifically, fake news detection not only requires high accuracy but also needs the model to answer \"why\" certain information is judged as false, which relies on the joint support of cross-modal semantic consistency and verifiable signals from user comments [23; 24].
# Phase Imbalance Analysis of GF-3 Along-Track InSAR Data for Ocean Current Measurement
## 3 Data Processing and Interpretation  
Since GF-3 ATI mode is an experimental mode, there are only a few sets of data obtained in 2018, 2019, and 2020, respectively. Moreover, since the backscattering coefficient of the land scene is stronger than that of the ocean scene, the SAR echo is likely to be saturated, and then, the amplitude and phase information of the echo cannot reflect the real situation. According to the auxiliary data of these GF-3 ATI data, we can analyze the degree of saturation. In order to avoid the influence of data saturation on the experimental results,  
Figure 5: Phase imbalance calibration flowing diagram.  
only three sets of GF-3 ATI data shown in Table 3 can be selected for GF-3 ATI mode phase imbalance analysis and moving target velocity measurement. The first set of data and the second set of data are all land scenes whose interferometric phase will be zero without any errors, which are very suitable for phase imbalance analysis. In fact, the second set of data was obtained by reorganizing an experiment with the imaging parameters of the first set of data to verify whether the phase imbalances of GF-3 ATI mode are systematic errors or random errors. The third set of data was specifically designed for the GF-3 ATI current measurement experiment.
## 4 Experimental Design and Setup
### Prediction Models
#### 4.2.4 Support Vector Machine  
SVM is considered a category of generalized linear classifiers that convert the original dataset training to a higher dimension using a nonlinear mapping [32]. Then, it creates the linear optimal separating hyperplane to separate the dataset into two classes. Furthermore, there are two lines that create a maximal margin hyperplane, which makes the boundary line, where the instances lie on the margins of the maximum margin hyperplane. We used sequential minimal optimization (SMO) in Weka as the implementation for SVM, and this has several features, such as the ability to handle very large datasets and faster model creation for sparse datasets and linear SVM [46]. Additionally, it has the ability to handle complex nonlinear decision boundaries and is less prone to overfitting than other models. These features help SVM to reduce prediction error and improve overall prediction accuracy [32].
## 1 Introduction
Note that displacement can be obtained through the ratio of two I/Q channel output signals in a quadrature receiver system, which is called by the arctangent demodulation. It is found that the phase variation is linear with respect to displacement due to the Doppler effect. This work considers simulations on scenarios with body-RF signals interaction that give a qualitative insight of the feasibility of this antenna system for near-field sensing of human vital signs. Further work is necessary to validate the Doppler radar for near-field sensing of vital signs, since it will be feasible when the electromagnetic performance as well as the performance of other parameters in RF systems, baseband systems, and the underlying signal processing are fully considered. The remainder of this paper is organized as follows. We first present the design and measurement results of the slot-type Doppler radar antenna. Next, we investigate the performance of the designed Doppler radar antenna close to the human body and conduct a feasibility study of the 24 GHz ISM-band Doppler radar antenna for near-field sensing of human respiration. Finally, concluding remarks are provided.
## 2 Materials and Methods
### Evaluation Metrics  
This manuscript compares the accuracy and stability of different regression models of the VIS-NIR spectrum. Therefore, the evaluation metrics of the coefficient of determination (\(R^{2}\)), root mean square error (RMSE), mean absolute error (MAE), and the ratio of performance of deviation (RPD) have been adopted to evaluate the prediction [7; 8; 9; 10; 11]. These methods have been widely used for regression models of the spectrum.  
The RPD has been used for several years by NIR scientists working on agricultural products and has been widely appropriated by soil science researchers.  
\[\text{RMSE }=\sqrt{\frac{1}{n}\sum\
olimits_{i=1}^{n}(y_{i}-\hat{y}_{i})^{2}} \tag{2}\]  
\[\text{RPD}=\frac{SD}{\text{RMSE }}=\sqrt{\frac{n\sum\
olimits_{i=1}^{n}(y_{i}- \overline{y})^{2}}{(n-1)\sum\
olimits_{i=1}^{n}(y_{i}-\hat{y}_{i})^{2}}} \tag{3}\]  
SD is standard deviation. Table 2 shows the different levels of the model for the different RPD values.  
The RPD value could be an important criterion, but [PERSON] pointed out that soil physical properties and chemical contents both exhibit a biased normal distribution; therefore, the ratio of performance to IQ (RPIQ) value is more objective than RPD [23]. RPIQ is based on quartiles, which better represent the spread of the population. The quartiles are milestones in the population range: Q1 is the value below which we can find 25% of the samples; Q3 is the value below which we find 75% of the samples; and Q2, commonly called the median, is the value under which 50% of samples are found. RPIQ is the ratio of IQ to RMSE, where IQ is the difference between the third quartile Q3 and the first quartile Q1. A larger RPIQ value indicates improved model performance. The formula is shown as follows:  
\begin{table}
\begin{tabular}{c c} \hline
**RPD** & **Level** \\ \hline RPD \(\geq\) 3.0 & A \\ 2.0 \(\leq\) RPD \(<\) 3.0 & B \\ 1.5 \(<\) RPD \(<\) 2.0 & C \\ RPD \(\leq\) 1.5 & D \\ \hline \end{tabular}
\end{table}
Table 2: The ratio of performance of deviation (RPD) level.  
Figure 2: Schematic diagram of adaptive boosting (AdaBoost) regression.  
\[IQ=Q3-Q1 \tag{4}\] \[\text{RPIQ}=\frac{IQ}{RMSE}=\frac{Q3-Q1}{\sqrt{\frac{1}{n}\sum_{i=1}^{n }\left(y_{i}-\hat{y}_{i}\right)^{2}}} \tag{5}\]  
The sum of ranking difference (SRD) is simple to understand the comparison of regression models and provides an easy tool to evaluate the methods [24; 25]. Therefore, this manuscript compared the \(R^{2}\), RMSE, MAE, RPD, RPIQ, and SRD of these regression models.
## 2 Vehicular Networking Wireless Technologies
### ITS-G5
#### 2.2.5g  
The 5G is the fifth-generation cellular system that is based on mm-wave technology and will play a crucial role in vehicular communications; it is the latest cellular standard developed by the 3 rd Generation Partnership Project (3 GPP). The 5G standard is particularly designed to support high data rates (max. 20 Gbps) with a minimum latency for real-time application of 1 ms [7]. The 5G architecture also supports other evolving technologies, including mm-wave, Software-Defined Networks (SDNs), Device-to-Device (D2D) communications, Multiple-Input Multiple-Output (MIMO) systems, Network Function Virtualization (NFV), Heterogeneous Networks (HetNets), and network slicing. In [8], energy-efficient, software-defined vehicular edge networks are proposed to enable eco-routing and thus connected transportation systems. With the assistance of the above-mentioned technologies, 5G would be able to achieve very low end-to-end latency, high capacity, high data-rate, massive connectivity of devices, and reliable Quality of Experience (QoE) delivery.  
Additionally, the network management is also a salient feature of 5G assisted by network slicing [9; 10]. In [11], end-to-end network slicing is introduced to jointly optimize communication functionalities in both radio access and core networks, ensuring optimal data throughput and congestion-free systems. Due to the distinctive SDN's capabilities of managing a large number of heterogeneous devices, operating in diverse network environments, and providing both improved security and flexible networking, 5G has a strong potential for VANETs communications [9].
## 5 Conclusions and Final Considerations
### Implications for Practice  
Increase Service Frequency and Coverage. Reinforce bus schedules and routes in areas and during times of high demand (especially for urban buses) to reduce variability in waiting times. A temporal analysis (Figure 6) shows that from midnight to 05:00, the average waiting time exceeds 17 min, likely due to very low service frequency. Between 06:00 and 10:00, waiting times decrease (reaching a minimum of around 6 min at 08:00), while starting at 18:00, they gradually rise again, reaching about 9.8 min by 23:00. These sub-periods differ from the general correlations (e.g., 11:00-21:00), demonstrating the necessity of adjusting schedules hourly and enhancing fleet capacity during peak or nighttime hours.  
Expand Alternative Modes and Real-Time Information. Promote modes such as Metro Valparaiso and Trolleybuses, which exhibit consistently better performance, and implement real-time information systems [24] to enhance users' perception of service quality.  
Assess Cost-Effectiveness and Operational Impact. While boosting service frequency and enlarging the fleet can shorten waiting times, these measures entail substantial capital and operating expenses and may introduce vehicle interactions that generate internal delays. We therefore recommend preliminary cost-benefit analyses and small-scale pilot tests to ensure both financial and operational viability.  
Despite the temporal constraints noted above, increasing service frequency, improving the spatial distribution of transportation options, and utilizing emerging technologies for data collection and analysis are key strategies for optimizing service and reducing inequalities in Greater Valparaiso's public transport. Supported by additional research and the involvement of local stakeholders, these measures can foster a more equitable and efficient transport system.  
Conceptualization, F.G. and V.A.; Methodology, F.G.; Software, F.G.; Validation, F.G, V.A. and S.S.; Formal analysis, F.G.; Investigation, F.G. and V.A.; Resources, A.P.; Data curation, F.G.; Writing--original draft, F.G.; Writing--review and editing, F.G., V.A., S.S. and A.P.; Visualization, F.G.; Supervision, V.A.; Project administration, V.A.; Funding acquisition, A.P. All authors have read and agreed to the published version of the manuscript.  
This research was funded by Agencia Nacional de Investigacion y Desarrollo (ANID) Chile, grant number Fondecyt 11230050.  
The raw data used in this study are publicly available from the Greater Valparaiso Mobility and Transport Survey conducted by SECTRA. Researchers interested in examining the raw dataset should visit the official SECTRA website and follow the instructions provided there to download the data. The processed datasets derived from the clustering analysis and other procedures were generated by the authors and are available from the corresponding author upon reasonable request.  
The authors declare no conflicts of interest.
# Total Ionizing Dose Effects on a Delay-Based Physical Unclonable Function Implemented in FPGAs
## 4 Experimental Results and Discussion
### FPGA Parameters and Functionality  
The core currents and voltages were continuously measured during the entire experiment. The pre-irradiation operation currents were measured to be 23.9 mA for FPGA1 and 29.09 mA for FPGA2. At the end of the experiment [500 krad(Si)], the currents reached 95.97 mA and 83.35 mA, respectively. These internal core currents are within the limits of the vendor recommendations for this FPGA (typical: 25 mA; maximum: 106 mA). Nevertheless, the first failure was registered at 410 krad(Si) in FPGA1. This failure was related to the RS232 communication protocol and a reprogramming of the FPGA was necessary in order to recover normal functionality. This kind of error was reproduced until the end of the experiment. In FPGA2, no failures were registered. Both DUTs could not be reconfigured any more after the deposited dose reached 440 krad(Si). The faulty behaviour that appeared only in FPGA1 can be explained by the batch difference on the DUT or the lower dose rate (the results typically show marginally higher dose degradation threshold at lower dose rates [14]).  
Figure 6 depicts the core currents of FPGA1 and FPGA2 through the irradiation experiment. It is noteworthy that for both DUTs the core current increased linearly with the dose. This increase of leakage current is fully accounted for in the creation of electron-hole pairs due to the ionization of SiO\({}_{2}\)[15].  
Figure 5: Filter Box with the PCB (and DUT) inside and the connections to the different ports and power supply.
# Energy Efficiency Improvement in Reconfigurable Photovoltaic Systems: An Evaluation of Team Systems
## 1 Introduction
In [8; 9], which are more recent publications, authors present the state of the art on SR determination and [9] provide a novel inverter sizing method. However, in all cases, the optimal value of the SR is considered a constant parameter. Accordingly, this work explores the possible improvement in energy efficiency that can occur in GCPV systems where the SR can be adjusted in real time. GCPV systems with adaptive SR are typically referred to as reconfigurable PV systems. Section two of this paper is devoted to illustrating why the SR of GCPV systems must be modified over time to increase the overall energy efficiency of the system. In this manner, the energy efficiency improvement that reconfigurable systems can provide will be justified. Section three presents the two basic types of reconfigurable GCPV systems that allow the modification of their SR in real time. These systems are analyzed and simulated in this section to estimate the expected improvements in energy efficiency. Figure 1: Elements in a GCPV system based on PO configuration. The description of the experimental setup used to validate the simulation results obtained in the previous section is presented in sections four and five. The experimental results obtained are presented in section six. Finally, the discussion of the obtained results and conclusions is presented in sections seven and eight.
## 2 Materials and Methods
### Desulfurization Experiments
#### 2.3.4 Theoretical Model  
The dynamic adsorption behavior and the adsorption affinity of PC and 13X can be examined through different mathematical models. The Adams-Bohart, Yoon-Nelson, and Thomas models are mathematical models widely used to describe the dynamics of adsorption in a fixed-bed column. These models predict the breakthrough behavior of adsorbates in packed-bed systems and are based on simplifying assumptions. Each model's applicability depends on the specific experimental setup, desired accuracy, and available data. In summary, (i) the Adams-Bohart model is employed for preliminary design and estimation of bed height, (ii) the Yoon-Nelson model enables quick predictions of breakthrough time without needing detailed adsorption data, and (iii) the Thomas model provides capacity and kinetic evaluation under equilibrium conditions.  
Based on our experimental setup, and given the expected fast reactivity of SO2 with Ca(OH)2, the equilibrium-driven assumption seemed the most reasonable; thus, from among the most widely used adsorption models, we chose the [PERSON] model to fit the entire breakthrough curve [23; 24]. Indeed, the [PERSON] model had already been successfully applied to Ca-based adsorbents for SO2 adsorption experiments in fixed-bed columns [25].  
The satisfactory agreement of experimental data from the PC sample, here used as a standard material, and the theoretical model provide evidence that the experimental apparatus is suitable for FGD measurements.  
Moreover, the [PERSON] model was used to calculate the Thomas rate constant, \(k_{TH}\) (mL min\({}^{-1}\) mg\({}^{-1}\)), and the predicted bed capacity at the equilibrium, \(q_{0}\) (mg g\({}^{-1}\)), from its linearized expression [24; 26]:  
\[ln\left(\frac{C_{0}}{C_{t}}-1\right)=\frac{k_{TH}q_{0}m}{Q}-k_{TH}C_{0}t \tag{6}\]  
where \(m\) is the mass of adsorbent in the reactor (g) and \(Q\) is the flow rate (mL min\({}^{-1}\)). As the points at low C/C0 prior to a dead time of 5 min described in Section 2.3.3 were due to the system configuration rather than the adsorbent uptake, those experimental points were removed from the calculation.
###### Abstract  
Graphitic carbon nitride g-C\({}_{3}\)N\({}_{4}\) has been modified using platinum and platinum oxide (0.5-5 wt.%) and studied in photocatalytic H\({}_{2}\) evolution reactions with ethanol aqueous solution under visible light irradiation (\(\lambda\) = 409 nm). An analysis of the by-products of the reaction (CO\({}_{2}\), CH\({}_{4}\), C\({}_{2}\)H\({}_{6}\) etc.) was also carried out. The morphology, particle size distribution, and optical properties of the photocatalysts, and the chemical states of platinum cations were examined using various methods. The photocatalysts were investigated using a wide range of methods to clarify the morphology, particle size distribution, optical properties, and the chemical states of platinum cations. Factors affecting not only the activity, but also the selectivity of the photocatalyst in the target process of hydrogen production, have been established. The highest rate of H\({}_{2}\) evolution achieved over 0.5 wt.% Pt/g-C\({}_{3}\)N\({}_{4}\) photocatalysts is 0.6 mmol h\({}^{-1}\) g\({}^{-1}\) (selectivity 98.9%), which exceeds the activity of pristine g-C\({}_{3}\)N\({}_{4}\) by 250 times. Increasing the Pt or PtO content up to 5 wt.% leads to an increase in the rate of formation of by-products (CH\({}_{4}\), C\({}_{2}\)H\({}_{6}\), and CO\({}_{2}\)) and a decrease in the selectivity of H\({}_{2}\) evolution. The study also delves into the role of platinum and the mechanism of charge transfer in PtO/g-C\({}_{3}\)N\({}_{4}\) and Pt/g-C\({}_{3}\)N\({}_{4}\) photocatalysts due to light irradiation.  
Keywords:photocatalysis; photocatalytic H\({}_{2}\) evolution; g-C\({}_{3}\)N\({}_{4}\); platinum; visible light; ethanol +
Footnote †: journal: Physics Letters B
## 3 Results
### Description of the Selected Soil Improvement Techniques
#### 3.2.2 Physical-Mechanical Stabilization  
Physical-mechanical techniques are fundamentally based on the physical modification or reconfiguration of soil structure. The purpose is to improve its engineering properties without inducing significant permanent chemical changes in the mineralogical composition of the clay, unlike chemical methods [7]. The main objective is to control water absorption, increase density, reduce plasticity, and minimize the potential for soil swelling and shrinkage [2].  
Within this category, sources highlight several key strategies.  
1. Deep Foundations: A common technique for managing expansive soils is using foundations that transfer structural loads to stable soil strata below the unstable active zone, where the most significant volumetric changes occur [3].
2. Compaction: This is a widely used physical-mechanical technique. It involves the application of mechanical energy to expel the air contained in soil voids [7]. This results in an increase in dry density and a reduction in the total void volume [2]. By decreasing the available void space, the amount of water the soil can absorb is limited, restricting its swelling potential [2; 7]. The process seeks to achieve MDD at or near the OMC, determined by tests such as the Standard Proctor [7; 51]. This technique is fundamental in reusing expansive clayey soils in embankments, where rigorous execution and control procedures are applied, including layer compaction [51].
* Soil Reinforcement: Incorporating fibrous or geosynthetic materials (such as geotextiles or geogrids) into the soil mass. These materials can be randomly distributed or specifically placed [7]. Reinforcement creates a three-dimensional network within the soil, improving its mechanical strength, such as shear strength and bearing capacity [2,7]. Although it does not eliminate the intrinsic expansivity of the soil, the presence of reinforcement can reduce the potential for swelling and shrinkage and control differential settlements [2].