esa-sceva/satcom-chunk-collection huggingface dataset:
# Evaluating CHIRPS and ERA5 for Long-Term Runoff Modelling with SWAT in Alpine Headwaters
## 3 Results  
### Performance Evaluation Using Gauge Observations  
The observed precipitation and runoff regime in the period 1991-2018 was plotted using vertical averaging, for a comparison between catchments, and horizontal averaging, for a comparison between elevation bands (Figure 5). Annual precipitation \(P_{annual}\) is slightly lower in catchment b2 Drava (966 mm) than in catchments b1 Sill and b3 Isel (1050 mm and 1048 mm). The warm season is much wetter \(P_{warm}\) = 674 mm than the cold season \(P_{cold}\) = 348 mm. The inter-annual variations in \(P\) (Figure 5a) show that most precipitation falls in summer (June, July, August) and late autumn (October, November), with July being the wettest (140 mm), while the winter months are much drier (36 mm in February). The distribution of \(P_{annual}\) in elevation bands shows a precipitation increase with elevation, from 807 mm to 1266 mm, giving a vertical \(P\) lapsing rate at 420 mm km\({}^{-1}\) (Figure 5b). The precipitation amounts from the CHIRPS and ERA5 products were compared to observations for the annual, seasonal and monthly time steps in the period 1991-2018 (see Table 10). A general positive \(P\) bias is present for both products, but it is significantly lower for CHIRPS than for the ERA5 product (\(PB\_P\) = 15% CHIRPS, 37% ERA5). The CHIRPS also shows a lower seasonal \(P\) bias (warm and cold seasons) at all elevation bands. The performance of both products is lower in the cold than in the warm season. A relatively small bias at higher elevations (>1500 m a.s.l.) (\(PB\_P\) = 1% CHIRPS, 21% ERA5) increases significantly (\(PB\_P\) = 50% CHIRPS, 68% ERA5) at lower elevations (<1000 m a.s.l.). This is then reflected in the vertical \(P\) lapsing, which is present in both products, but the rate of observed lapsing is not matched by the GPPs (Figure 5b). Both products show an unbalanced performance between catchments (vertical averaging), Figure 6. For the CHIRPS product, a small error in catchments b1 Sill (\(PB\_P\) = \(-\)3%; \(MAE\) = 197 mm) and b2 Drava (\(PB\_P\) = 2%; \(MAE\) = 101 mm) is significantly increased in catchment b3 Isel (\(PB\_P\) = 45%; \(MAE\) = 477 mm). The ERA5 product shows a small error in catchment b2  
Figure 5: Average monthly precipitation and flow duration for characteristic durations (10, 25, 50, 75 and 90%) in the b3 Isel catchment (**a**) and annual precipitation in vertical bands with linear interpolation from observations and GPPs (**b**) in period 1991–2018. Drava (_PB_P_ = 27%; _MAE_ = 258 mm) but a larger error in catchments b1 Sill (_PB_P_ = 40%; _MAE_ = 421 mm) and b3 Isel (_PB_P_ = 43%; _MAE_ = 449 mm). For the monthly time step, the ERA5 shows a stronger linear correlation to the observations (_R\({}^{2}\_\)P_ = 0.83 CHIRPS, 0.91 ERA5), but the CHIRPS shows a lower bias (_PB_P_ = 15% CHIRPS, 37% ERA5) and lower _MAE_ (_MAE_P_ = 34 mm CHIRPS, 37 mm ERA5), Figure 7. The CHIRPS shows a smaller bias in monthly precipitation for all months except May.
# Effect of the Anti-Yaw Damper on Carbody Vertical Vibration and Ride Comfort of Railway Vehicle
## 2 Mechanical Model of Railway Vehicle  
To study the effect of the anti-yaw damper upon the vertical vibrations of the railway vehicles carbody during running on a track with irregularities, a model of the rigid-flexible coupled type vehicle is being considered.The model is featured in Figure 1. As for the track model, the rigid track hypothesis is adopted, an approach justified by the fact that the eigenfrequencies of the vertical vibrations of the vehicle carbody, relevant from the ride comfort viewpoint, are much smaller than the frequencies in the wheelset-track system.  
The vehicle carbody is represented through a free-free equivalent beam, with a constant section and uniformly distributed mass, Euler-Bernoulli type. This model allows considering the vertical vibration modes of the carbody, relevant for the ride comfort, i.e., the vibration rigid modes-bounce \(z_{c}\), pitch \(\theta_{c}\), and the first vertical bending mode. The vertical displacement of the carbody medium fiber \(w_{c}(x,t)\) is the result of the overlapping of the three vibration modes,  
\[w_{c}(x,t)=z_{c}(t)+\Big{(}x-\frac{L_{c}}{2}\Big{)}\theta_{c}(t)+X_{c}(x)T_{c}( t), \tag{1}\]  
where \(L_{c}\) represents the carbody length, \(T_{c}(t)\) is the coordinate of the carbody bending and \(X_{c}(x)\) represents the natural function of this vibration mode, described in the equation  
\[X_{c}(x)=\sin\beta x+\sinh\beta x-\frac{(\sin\beta L_{c}-\sinh\ \beta L_{c})(\cos\beta x+\cosh\beta x)}{\cos\beta L_{c}-\cosh\beta L_{c}}, \tag{2}\]  
\[\text{with}\ \beta=\sqrt[4]{\frac{\omega_{c}^{2}\theta_{c}}{EI}}\text{ and}\ \cos\beta L_{c}\cosh\beta L_{c}=1, \tag{3}\]  
Figure 1: The mechanical model of the railway vehicle.  
where \(\omega_{c}\) is the natural angular frequency of the carbody bending, and \(\rho_{c}=m_{c}/L_{c}\) where \(m_{c}\) is carbody mass and \(L_{c}\) is length of carbody.  
Due to the fact that bogies and wheelsets feature reduced elastic deformations, they are represented with rigid bodies. The vibration modes of the two bogies in the vertical plane are the bounce \(z_{b1,2}\) and pitch \(\theta_{b1,2}\). The vertical displacements of the wheelsets \(z_{w1...4}\) are equal to the vertical track irregularities against each wheelset.  
Each wheelset is connected to the bogie chassis through a Kelvin-Voigt system that models the primary suspension, with the elastic constant \(2k_{zb}\) and damping constant \(2 cz_{2b}\). The bogie is connected to the carbody through a secondary suspension, modelled via a Kelvin-Voigt system, with the elastic constant \(2k_{zc}\) and damping constant \(2 cz_{zc}\). The anti-yaw damper is represented through a Maxwell model, where the anti-yaw damper stiffness is rendered via an elastic element of stiffness \(k\), whereas the anti-yaw damping is modelled through a damping element \(c\).The angle \(\alpha\) stands for the mounting angle of the anti-yaw damper.
## 3 Analysis of Test Results
### Characteristics of AE  
According to the number of AE events, the damage process can be divided into four stages: the initial stage (I), the active stage (II), the calm stage (III), and the failure stage (IV) (as shown in Figure 6). The initial stage of AE is present during the closure stage of fracture and the linear elastic stage. In this stage, the AE events are sporadically distributed, and there are hardly any new cracks generated; the AE mainly originates from the compaction of the original cracks, and the amplitude fluctuations during this stage are not significant. The active stage of AE starts from approximately 40% of the peak stress and ends when the stress reaches 98% of the peak stress; in this stage, a large number of cracks are generated, extended, and connected, which is the main stage of crack initiation and propagation; the amplitude exhibits obvious fluctuations, but the change in the center of fluctuations is not significant. During the calm stage, the number of newly generated acoustic emissions decreases sharply, which is mainly due to the fact that a significant number of cracks have already formed within the rock mass, and the stress is redistributed at crack tips. In this stage, internal fractures undergo a process of large crack extension to the initiation and propagation of small cracks; the amplitude fluctuations during this stage decrease, and in some specimens, the fluctuations disappear. In the failure stage, stress concentration occurs on the fracture surface, and the cracks further extend until they become interconnected; also, the number of AE events rapidly increases, and the amplitude shows a significant increase with fluctuations.
# Multispectral Target Detection Based on Deep Feature Fusion of Visible and Infrared Modalities
## 3 Proposed Methodology
### C3-PSA Optimization
Each scale generates a feature map \(F_{i}\in\mathbb{R}^{C^{\prime}\times H\times W}\), which is concatenated to obtain a fused multiscale feature representation defined as follows:  
\[F=\text{Cat}([F_{0},F_{1},\dots,F_{S-1}]) \tag{18}\]  
To further enhance channel-wise feature differentiation and suppress irrelevant information, the SEWeight module is employed to extract an attention weight vector:  
\[Z_{i}=\text{SEWeight}(F_{i}) \tag{19}\]  
These vectors are recalibrated using the softmax function:  
\[\text{att}_{i}=\text{Softmax}(Z_{i})=\frac{\exp(Z_{i})}{\sum_{j=0}^{S-1}\exp( Z_{j})} \tag{20}\]  
where \(\text{att}_{i}\in\mathbb{R}^{C^{\prime}\times 1\times 1}\) represents the normalized channel weights. Subsequently, each branch's feature map is element-wise multiplied by its respective attention vector to generate the optimized feature representation:  
\[Y_{i}=F_{i}\cdot\text{att}_{i},\quad i=0,1,\dots,S-1 \tag{21}\]  
The final output is concatenated as  
\[\text{Out}=\text{Cat}([Y_{0},Y_{1},\dots,Y_{S-1}]) \tag{22}\]  
Thereby yielding a multiscale attention-enhanced output feature representation. Since the original C3 module contains residual structures, replacing it with the C3-PSA module at the corresponding network positions significantly enhances feature extraction capabilities without altering the overall network topology. Extensive experiments demonstrate that incorporating the C3-PSA module into the YOLOv5 backbone effectively improves the ability to capture and refine multiscale information. This results in notable gains in both detection accuracy and recall rates. Compared to the conventional YOLOv5, the C3-PSA-enhanced version achieves superior target identification and localization, particularly in high-density or large-scale variation scenarios. Furthermore, it maintains robust detection performance across complex scenes. The effectiveness and applicability of this module will be further validated through detailed experimental comparisons and analyses.
# Flexible Antennas: A Review
## 3 Fabrication Techniques for Flexible Antennas
### Screen Printing  
Screen printing is a simple, fast, cost-effective, and viable solution for fabricating flexible electronics, which has been widely adopted to implement RFID antennas by printing conductive inks or pastes onto low-cost, flexible substrates such as PET, paper, and textile substrates [100]. It is a woven screen-based technique having different thicknesses and thread densities. A squeeze blade is driven down, forcing the screen into contact with the substrate to produce a printed pattern. Thus, the desired pattern is formed by the ink ejecting through the exposed areas of the screen on the affixed substrate [101]. It is also an additive process like inkjet printing as opposed to the subtractive process of chemical etching, which makes it more cost-effective and environmentally friendly. A screen-printed dual-polarization 2.45 GHz antenna and rectenna on polycotton for RF power transfer and harvesting were demonstrated in a prior article [102]. The rectenna was tested and compared with a similar FR4 rectenna, and the performance was found a third of standard FR4.  
A high-frequency RFID reader antenna system was fabricated by screen printing silver (Ag) particle inks onto a flexible paper substrate operating at 13.56 MHz [103]. This screen printed antenna's performance (Q factor) was significantly lower compared to a Cu made loop antenna element with the same geometry. For improving this, antenna DC resistance needs to be reduced by adding more silver printing layers, which eventually increases the manufacturing cost. As screen printing is cost-effective, a partially reflective surface with a parasitic patch array to create a simple beam-switching, low-profile, and flexible wearable detection system was designed on a flexible substrate from PremixGroup [104]. The antenna array was printed using Aurel Automation 900 screen printer, and the antenna was optimized for the 77 GHz band and had a high gain of 11.2 dB, which can detect objects within a range of 10 m. The fabrication process has been given in Figure 6. A DEK Horizon 03i (ASM Assembly Systems Weymouth Limited, Weymouth, UK) semiautomatic screen printer was used to fabricate a graphene-flakes-based wideband elliptical dipole antenna on a polyimide substrate operating from 2 to 5 GHz for low-cost wireless communications applications [105]. Screen printing is cost-effective compared to other fabrication technologies of flexible antennas. However, it has some limitations like resolution dependence on the surface quality of the substrates, the limited layer control, and lack of thickness control for the conductive layer. Figure 6 shows the fabrication of a flexible antenna using the screen printing process and a sample prototype.
## 4 Conclusions  
The prediction of the total soluble solid (TSS) content in tomatoes has important implications for various stakeholders in the agricultural and food industries. Tomato producers can benefit from optimising harvest time, improving quality control, and predicting yield in advance. The food processing industry can enhance product development, quality assurance, and process optimisation. Consumers can make informed choices based on accurate product information. Researchers can deepen their understanding of tomato ripening, develop new varieties, and improve predictive models. This study's results provide a rapid and precise method for estimating TSS, contributing to increased efficiency, sustainability, and consumer satisfaction within the tomato industry.  
In this study, we estimate the amount of brix (soluble solids) in beef tomato fruit by ANN and MLR methods. To evaluate the models R\({}^{2}\), MAE, MAPE, and RMSE metrics were used. The regression equation is written according to the coefficients obtained as a result of MLR analysis. According to the MLR model, while TKM, acidity, Vitamin C, L, a, b, C, h, K, Mg, Na, and P are significant, ash, pH, hardness, fructose, glucose, Ca, Mn, and lycopene are insignificant. All variables are significant at the 0.05 error level, except Vitamin C (significant at the 0.10 error level). Based on the metric outcomes that were acquired, the ANN model was more successful in both the training and testing partitions. Line plots created for training and testing splits also support the metric results. Furthermore, graphs have been used to visually represent and compare the actual and predicted values of the models in each of the two partitions. According to the training data set results of the MLR model established to estimate the amount of brix in tomato fruit, the results were calculated as MAE: 0.2349, RMSE: 0.3048, R\({}^{2}\): 0.8441 and MAPE: 5.5368, while, according to the ANN model, they were calculated as MAE: 0.0250, RMSE: 0.031, R\({}^{2}\): 0.9982 and MAPE: 0.5814. Since the training and testing results of both ANN and MLR models are close to each other, it can be said that the models are consistent and there is no overlearning problem in the models.  
Conceptualisation, A.K. and U.E.; methodology, A.K. and U.E.; software, U.E.; validation, O.K., G.M. and A.K.; formal analysis, A.K.; investigation, U.E.; resources, A.K.; data curation, A.K. and G.M.; writing--original draft preparation, A.K.; writing--review and editing, A.K., G.M., U.E. and O.K.; visualisation, O.K.; funding acquisition, G.M. All authors have read and agreed to the published version of the manuscript. The APC was funded by the National University of Science and Technology Politechnica Bucharest through the program PubArt. Not applicable. Not applicable. Not applicable. Data Availability Statement: The raw data supporting the conclusions of this article will be made available by the authors on request. The authors declare no conflict of interest.
# An Enhanced Mechanism for Fault Tolerance in Agricultural Wireless Sensor Networks
## 3 WSN Topology
### WSN Routing and Data Transmission  
In our scheme, the sensor nodes are associated with the nearest CHs, where the CHs announce their coverage with their identification to all members of the cluster. After that, each CH sends a scheduling TDMA to all cluster members; in this way, it allows all sensor nodes to allocate a _time slot_ for the transfer of their data. In this part, the routing mechanisms between the WSN devices are explored.
# Advancing C-V2X for Level 5 Autonomous Driving from the Perspective of 3 GPP Standards
## 4 4G and NSA-Based 5G V2X Services
### System Support
#### 4.1.5 Media Handling and Interaction Support  
For 4G V2X services, the 3 GPP supported and focused on simple message delivery for collision avoidance. Apart from many important 4G & 5G V2X use cases, media handling i.e., video sharing and composition scenarios (described in (_TR 22.886 Rel-15_)) is one of the crucial use cases for advanced driving of eV2X services. This dictates the importance of 5G technology fusion with 4G technology to realize and address important and critical V2X use case scenarios. There is no doubt that the architectural and other enhancements (discussed above) are effective in addressing the potential requirements for aV2X services and applications. In the near future, other essential and effective advancements will be produced for future V2X (5G V2X) services. Hence, the research community is encouraged to start focusing on 5G V2X services and use case scenarios.  
At the current stage, the support of 4G & 5G communication technologies for V2X services considers advanced use cases and functionalities such as media transmission, video sharing, and visual information utilization. The media handling and interaction reported in the document (_TR 26.985_) provides details (less in _Rel-15_ and more in _Rel-16_) for advanced media transmission capabilities using networked visual information. In addition, the _Rel-16_ document reports the investigation of procedures for capture, compression, and transmission. For example, the use of a camera and LiDAR for capturing high-resolution perception data and transmitting the compressed version to other UEs. Some of the other important media-based V2X use cases are support for remote driving, information sharing for high/full automated driving, video data sharing for assisted and improved automated driving, teleoperated support, and video composition. Though it is a matter of choice between Uu and PC5 interfaces when realizing media-based V2X use cases, the Uu interface favors QoS and high-bitrate media transmissions. Interestingly, the technical document (_TR 26.985 Rel-16_) describes how to leverage the 5G QoS framework for supporting different traffic and service flows e.g., media streams, maneuver instructions, conversational service, uplink video, and audio flows when realizing remote driving use case. However, the media format i.e., resolution, framerate, bitrate/quality, etc., and adaptation is an open challenge in handling media and interactions. Given the huge importance of media in vehicular operations and services, this could be a useful avenue for researchers to contribute to the development of aV2X services.
## 4 Discussion
### Outcomes Analysis
The real-world data collected using sensors and experiments in this paper was verified by multiple transportation construction experts and engineers. Compared with the studies of [17; 18], the data and the findings help establish baselines, find benchmarks, and set performance goals for concrete construction. Furthermore, the observations on the results of Tables 5 and 7 reveal that for the early strength development of concrete, the slopes of the correlation regression equations for both Method #C1 (y = 1.0497x) and Method #C2 (y = 1.0361x) are greater than 1, which implies that the 6 in. cylinders overestimate the compressive strengths of in-place concrete compared with the 4 in. cylinders. One reason is that more heat is generated from 6 in. cylinders than 4 in. cylinders during cement hydration reaction. One practical implication of the findings for construction professionals is that they should be aware that the specimen size difference can lead to the risk of loading stress on a concrete structure before it matures. This research used the test data for the curing durations of 1-7 days, which indicate concrete early strengths. When using 6 in. cylinders for concrete strength testing, construction professionals can reduce the test results of compressive strengths by 9% when using an ambient air curing method and 14% when using an insulated box curing method for concrete early strengths of 1 to 7 days. The analysis shows that the quality control of concrete construction projects relies on the data-driven decision-making of curing method selection. For example, this research used 3500 psi as the target compressive strength of the concrete mixture design. The compressive strength can be 7000 psi for precast and prestressed concrete and 15,000 psi for load-bearing columns. Hence, the decisions on curing methods and cylinder types have increased influences on the accuracy of the strength estimation of high- and ultra-high-strength concrete. Particularly, these decisions need to be made before the start of construction. In this case, construction professionals and engineers should be cautious when using 6 in. testing cylinders for high-early strength concrete or precast and prestressed concrete. Moreover, this recommended practice can help the concrete industry reduce the potential risks of applying loads to premature concrete structures. Possible consequences of over-estimating in-place concrete strength in construction projects include structure failure, reduced durability, and possible concrete cracking. Usually, the practical application of avoiding over-estimation is to multiply a safety factor or empirical value. This research improved the accuracy and reliability of concrete compressive strength estimates, which can help concrete quality control and resource allocation.
## 3 Results and Discussion
### Modulus and Phase Angle Are Affected by Temperature  
The dynamic shear modulus and phase angle of asphalt mastics were investigated in this work under frequencies of 10 rad/s and various temperatures. Figure 9 depicts the correlation between temperature and the dynamic shear modulus of asphalt mastics. The graph shows that the modulus keeps decreasing when the testing temperature rises. This implies that regular asphalt mastics and fiber asphalt mastics are temperature-sensitive materials.  
The phase angle of asphalt mastics is affected by temperature, as seen in Figure 9. The phase angle increases rapidly with increasing experimental temperature before stabilizing as the temperature increases further. This suggests that natural asphalt mastics and mastics treated with fibers are temperature sensitive. Moreover, adding fibers to asphalt mastics can dramatically raise the dynamic shear modulus, improving compressive strength and creating a reinforcement effect. The phase angle of various asphalt mastics grows progressively as the testing temperature rises. Plain asphalt mastics have a more noticeable phase angle than fiber asphalt mastics. With increasing temperature, the viscous component of asphalt mastics becomes more prominent, making them susceptible to high-temperature permanent deformation. As the trial temperature rises, the properties of various asphalt mastics transition from elastic to viscous behavior, with conventional asphalt mastics exhibiting the most pronounced viscous condition and being highly susceptible to high-temperature permanent deformation. However, the addition of fibers can significantly enhance the resistance of asphalt mastics to deformation at high temperatures. Figure 9 illustrates that all the samples' phase angles fall within the range of 60 to 80\({}^{\circ}\), indicating significant viscoelastic characteristics for the chosen matrix asphalt and the basalt and bamboo fiber asphalt mastic materials used in the experiment.  
Figure 8: Illustration of asphalt mastic sample.  
Figure 9: Temperature’s effect on fiber-modified asphalt mastics’ modulus and phase angle: (**a**) basalt fiber; (**b**) bamboo fiber.