esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion
In relation with the number and types of penalty coefficients established in the methodology, the definition of the factors these coefficients represent was based, as mentioned in Section 3, on a rock fall protection database built for some areas of the Swiss territory. This was used as a reference for including an initial set of factors to account for in the methodology, and have therefore a starting point in this sense, based on most common potential flaws and malfunctioning observed directly on site. Nevertheless, the lists of factors considered, especially concerning those specific to each protection (Group N), should not be considered as exhaustive and definitive. On the contrary, the methodology features a flexible character allowing new factors and related penalty coefficients to be in principle added any time, to expand the current list for each protection and keep the methodology up to date with the progresses in technology and design of new rock fall protections. In addition, if required, it is even possible to entirely implement other existing types of protections and associated factors (e.g., canopy of rock fall fences, protection galleries). Further advantages of the methodology linked to its flexibility are also the possibilities to apply it to any rock fall scenario/case study, as well as any rock fall hazard guidelines, if existing [5; 6; 23; 24], or, more simply, rock fall intensity-frequency diagram [25; 26; 27]. In particular, regarding the former point, applications of the methodology are not restricted to natural slopes such as in the examples provided, but can include, in a relatively straightforward manner, contexts involving engineered slopes for which rock fall protections might be needed, such as road cuts or open-pit mining and quarrying [28; 29; 30]. As an example, for open-pit mining, benches could be added among the topographic modifications as a new type of protections (segments of slope connecting an upper and a lower flat \"catch-bench\" area, designed to collect falling blocks); their main design parameter could be defined as their width and, among the most relevant factors to take into account for potential reduction of their performance capacity, the phenomenon of backbreak could be considered--reduction of the width (i.e., capacity to collect blocks) due to rupture at the crest of the slope segment constituting the bench [28].
# Seismic Performance Evaluation of Highway Bridges under Scour and Chloride Ion Corrosion
## 3 Effect of Cl\({}^{-}\) Corrosion on the Seismic Performance of Bridge Column
### Comparison of Quasi-Static Test Results of Columns before and after Cl\({}^{-}\) Corrosion
#### 3.3.6 Finite Element Analysis (FEA)  
The specimens were numerically simulated by finite element software OpenSees, in which the restoring force model for the structure was identified from the physical stress-strain relationship of the material in its fiber section. The material type Concrete02 [53] was adopted to simulate the concrete in fiber model. The restraining effect of transverse hoops was simulated by varying the peak value of stress and strain and the slope of the softening section in the skeleton curve in the compression zone. This still allows the residual strength of the concrete to be taken into account when the concrete is compressed to its maximum strength while the effect of cracking on the fiber cross-section is considered when the concrete is in tension. Steel02 [54] was adopted to simulate reinforcement in the model. The stress-strain relationship for reinforcement after entering plasticity was simplified to a straight line with a small slope, whose hardening coefficient \(\mathrm{b}=0.01\), meaning the elastic modulus of reinforcement \(E_{s}^{\prime}=0.01E_{s}\). The displacement-based beam-column element was utilized to simulate the pier-column element for low-circumference cyclic loading. The comparison of hysteresis curves between FEA and test for specimen LL and LLE is shown in Figures 31 and 32, respectively, and for specimen MH and MHE is shown in Figures 33 and 34, respectively.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Specimen Number** & **LL** & **LLE** & **MM** & **MME** & **MH** & **MHE** \\ \hline Cumulative hysteresis & & & & & & \\ energy consumption & 43,936.51 & 19,178.79 & 255,771.10 & 52,148.20 & 308,940.90 & 76,602.51 \\ (kN\(\cdot\)mm) & & & & & & \\ \hline \hline \end{tabular}
\end{table}
Table 5: Cumulative hysteresis energy consumption of each specimen.  
Figure 30: Comparison of equivalent viscous damping coefficient–displacement curves for specimens.  
It can be seen from Figures 31 and 33 that the curve of FEA hysteresis of un-corroded specimen is in good agreement with the curve of experimental hysteresis. It can be obtained from Figures 32 and 34 that the curve of FEA hysteresis and the curve of test hysteresis of specimen LLE and MHE had a good consistency before the peak load, at which point a certain deviation occurred. The main reason is that reinforcement of the specimens corroded by Cl\({}^{-}\) deteriorated in material properties and the reinforcement constitutive relationship of the fiber model used in FEA cannot simulate this effect.
# Annealing Process-Induced Microstructural Variation in NiV/B4C Multilayers
## 3 Results and Discussion  
### Grazing-Incidence X-Ray Reflectometry Analysis (Different Annealing Temperatures)  
The GIXR curves and fitted curves of all NiV/B4C multilayers before and after annealing are shown in Figures 1a and 1b, respectively. The grazing angles of the Bragg peaks progressively decreased as the annealing temperature increased from 70 \({}^{\circ}\)C to 340 \({}^{\circ}\)C, which suggesting an expansion in the multilayer d-spacing thickness. Notably, the third Bragg peak of the NiV/B4C multilayer disappeared after annealing at 340 \({}^{\circ}\)C, indicating that the thickness ratio was 1/3. As shown in Figure 1, based on the GIXR results, we inferred that the structural changes in the NiV/B4C multilayers were attributed to variations in annealing temperature, as all other deposition and measurement parameters remained constant. The structural parameters of the NiV/B4C multilayer films were quantitatively determined using the film simulation software IMD Version 5.0 [19]. The detailed results are shown in Tables 1 and 2. The changes in period and interface width before and after annealing of NiV/B4C multilayers are shown in Figures 2a and 2b, respectively. The results indicate that the interface width increased with rising annealing temperatures, which was caused by the interface roughness and diffusion. Additionally, the increase in the periodic thickness of NiV/B4C multilayers after annealing may be caused by the expansion of boron carbide [20,21]. Figure 1: The GIXR curves and fitted curves: (**a**) before annealing, (**b**) after annealing.
# Kiwifruit Allergy--Molecular Basis, Diagnostics and Treatment
## 3 Protein Families
### Kiwellin  
Allergens Act c 5 and Act d 5 are classified as kiwellin. These are approximately 28 kDa, cysteine-rich proteins that account for nearly one-third of the total protein content in kiwifruit [54]. Structurally, kiwellin comprises two domains: a small, N-terminal domain known as kissper (residues 1-39), containing six cysteine residues, and a large, C-terminal domain known as KiTH (residues 40-189), with eight cysteine residues [55; 56]. The kissper domain has been shown to have pH- and voltage-dependent pore-forming activity, anion selectivity, and channeling, and anti-inflammatory/antioxidant effects [57; 58]. The kissper domain is highly flexible and NMR experiments demonstrated multiple conformations in solution, even with the presence of the three disulfide bonds [55; 56; 58]. In ripe green kiwifruit, actinidin can proteolytically degrade kiwellin, resulting in a 4 kDa N-terminal kissper and 16 kDa C-terminal KiTH. Such proteolytic degradation of kiwellin also occursin golden kiwifruit, but to a lesser extent due to the lower abundance of actinidin in golden kiwifruit varieties [59].  
Skin prick tests (SPTs) among 29 kiwifruit-allergic subjects showed that 38% were positive to kiwellin [56]. IgE recognition to kiwellin can also occur after proteolytic digestion with actinidin, with some sera reacting solely to KiTH in immunoblot assays [56].
# Efficient Small-Object Detection in Underwater Images Using the Enhanced YOLOv8 Network
## 5 Discussion
### Applicable in Various Underwater Marine Scenarios  
To assess the generalization of our method on the underwater dataset, we tested the performance of the model trained on the UTDAC2020 dataset using an unseen underwater dataset, UODD [63], which includes underwater cultured products such as sea cucumbers, sea urchins, and scallops. We selected cases with occlusion, dense small objects, and complex backgrounds to simulate real underwater scenarios, and the results are shown in Figure 10. The results demonstrate that our model performs well and generalizes effectively in real underwater scenarios.  
However, in underwater environments with poor visibility and a high degree of target overlap, our detector may miss certain targets. We speculate that incorporating an underwater image enhancement network during the preprocessing of model data may improve this phenomenon, albeit at the cost of increased model parameters, FLOPs, and a slower inference speed. It is worth considering whether integrating an underwater image enhancement network into the model would be beneficial.
## 2 Classification of HEVs
### HEV Powertrain Configuration
#### 2.2.1 Series Hybrid Powertrain  
Series HEVs are composed of a generator, engine, rectifier, battery, traction motor, mechanical transmission, etc. In series HEVs, the ICE is connected to a generator, which provides power to either run the electric motor or charge the battery. Typically, the electric motor operates the vehicle independently, drawing the necessary power from both the generator and the battery. This configuration allows the electric motor to receive power directly from the generator or from the battery, facilitating electric all-wheel drive capability when the motor, generator, and battery are appropriately mounted on both the front and rear axles. Figure 2 illustrates the series HEV configuration.  
In this configuration, the electric motor alone provides the traction to drive the vehicle [62]. Because there is no mechanical coupling between the ICE and the drive axle, the ICE can function independently of the vehicle's power demands and near its peak efficiency, thereby significantly reducing fuel consumption. Traction motors offer a broader operating range and greater efficiency compared to ICEs. Consequently, the transmission, essential in conventional vehicles, may not be required in a tandem HEV.  
Figure 2: Configuration of series HEV [44].  
In series HEVs, mechanical energy needs to be converted into electrical energy and then electrical energy into mechanical energy, which can be less efficient overall because of the need for two energy conversions. In order to replace the ICE for traction purposes in series HEVs, a sufficiently powerful drive motor is necessary. Consequently, the battery capacity and the generator size must be substantial enough to support this motor. This requirement leads to increased costs for the battery and its components, ultimately restricting the commercial application of series HEVs primarily to heavy-duty vehicles [63]. [PERSON] et al. (2019) [64] introduced a hybrid powertrain design framework for a heavy-duty multi-purpose vehicle, considering various driving conditions. The gasoline equivalent fuel economy of the series hybrid powertrain was 53% higher than conventional diesel powertrain for the target drive cycle. Few hybrid vehicles on the market utilize the series configuration. Despite the limited adoption, several automobile manufacturers, including Mitsubishi, Volvo, and BMW, have explored this technology. A notable example is the BMW i3, which offers an optional gasoline-powered range-extender auxiliary power unit [44]. Some of the more common series hybrids on the market are the Nissan Kizashi, Swiss auto REX VW Polo, and the Volvo S90.
## 3 Analytical CTG/STG FE Models  
The FE models of the sample CTG and STG foundations were developed with two commercial programs, SAP2000 [9] and GISTRUDL [10]. The two programs provide eight-node solid element equipped with different shape functions, i.e., bending improved and non-bending improved. The CTG foundation (5.49 m wide, 18.29 m long, and 1.52 m thick) supports a set of turbine and generator equipment, which weighs a total of 210.01 t. Both the SAP2000 and GISTRUDL CTG models consist of 624 eight-node solid elements and 972 joints (2916 degrees of freedom). The STG foundation (18.90 m wide, 36.58 m long, and 13.11 m tall) also supports a set of turbine and generator equipment together with a heavy condenser. The weight of the turbine and generator is estimated to be 857.29 t and the condenser is assumed to weigh 578.33 t.  
The STG foundation models consist of 3828 eight-node solid elements and 6335 joints (19,005 degrees of freedom). The SAP2000 models additionally include nine incompatible bending shape functions in the eight-node solid elements so that the bending behaviour of the element can be significantly improved, which is not featured in GISTRUDL models. The eight-node solid elements  
Figure 1: Dynamic soil profiles under CTG/STG Foundations \(\mathrm{V_{s}}\): Shear wave velocity of soil, \(\mathrm{\gamma_{s}}\): Unit weight of soil, \(\mathrm{\gamma_{s}}\): Poisson ratio of soil, \(\mathrm{G_{s}}\): Shear modulus of soil.  
used in GTSTRUDL models adopt the 'IPSL (Isoparametric Solid Linear Displacement)' elements. The dynamic FE models are illustrated in Figures 2 and 3. The material property of both CTG and STG foundations is assumed to be 27.6 MPa cylindrical concrete strength with 24,856 MPa Young's modulus. The unit weight of concrete is of typical 2403 kg/m\({}^{3}\).
## 4 Experimental Results
### Hysteresis Curve  
Under a positive or negative \(d\), the force generated by the MTS hydraulic actuator (\(F\)) is defined as push or pull, respectively. The deformation corresponding to an \(F\) of \(0\) kN is defined as residual deformation (\(d_{\text{H-R}}\)), while the deviation of the horizontal displacement of the specimen from its central axis at a \(d\) of \(0\) mm is defined as cumulative deformation [1].  
The hysteresis curves of the IAP and GIAP specimens are compared in Figure 12. It was observed that the hysteresis curve for each specimen is distributed asymmetrically along the coordinate axes, with a symmetric \(d\) and an asymmetric \(F\) because the soil was filled behind the abutment and there was no soil in front of the abutment. In the first quadrant, a typical spindle shape for the \(F\)-\(d\) curve can be observed, with a large area enclosed by the hysteresis loop due to the soil-structure interaction. In the third quadrant, the \(F\) values are significantly smaller than those in the first quadrant for the same value of \(d\), and the curves appear more pinched, without a distinct spindle shape. When the value of \(d\) returns to \(0\) in the hysteresis curve, \(F\) is not \(0\), indicating residual force accumulation. The residual force accumulation increases with an increase in \(d\) and the number of cycles. When \(F\) was \(0\) during the change in \(d\) from \(-35\) mm to \(+40\) mm, the \(d_{\text{H-R}}\) for the GIAP specimen (\(30.6\) mm) was \(12.6\%\) smaller than that for the IAP specimen (\(35\) mm). When \(d\) was \(0\) during change in \(d\) from \(-35\) mm to \(+40\) mm, the residual force accumulation for the GIAP specimen (\(20.9\) kN) was \(22.6\%\) smaller than that for the IAP specimen (\(27\) kN). Therefore, \(d_{\text{H-R}}\) and the residual force accumulation in the GIAP specimen caused by the soil's nonlinearity are overestimated if the girder is not considered.  
Figure 12: Hysteresis curves: **(a)** IAP (\(d=-40\)\(\sim\)\(+\)\(40\) mm) [36]; **(b)** GIAP (\(d=-130\)\(\sim\)\(+\)\(130\) mm).
# High-Frequency Limits of Graphene Field-Effect Transistors with Velocity Saturation
## 4 Simple Model of GFETs
### Complete Model and Discussion  
Let us now calculate the total resistance of the graphene channel taking into account HPhP scattering, the non-uniform carrier density in the channel and the hot electron effect. We compute the total scattering length \(l_{scatt}(x)^{-1}=l_{imp}(V_{g},x)^{-1}+l_{HPhP}(x)^{-1}\) and neglect the ballistic conductance to obtain the local resistance  
\[r_{ds}(x)dx=\frac{\pi\hbar}{4e^{2}W\sqrt{n(x)\pi}}\frac{dx}{l_{scatt}(x)} \tag{8}\]  
The total channel resistance is then obtained by integrating over the channel length:  
\[R_{ds}=\int_{0}^{L}r_{ds}(x)dx \tag{9}\]  
Finally, in short devices with high-mobility graphene, the contact resistance \(R_{c}\) is not negligible. Most of the contact resistance comes from the junction between contacted graphene and the channel. This issue has been overcome in a previous study with the transistor geometry of sample-A [19]. It allows us to calculate the \(V_{g}\) dependent contact resistance. The total transistor resistance is then \(R(V_{g},V_{ds})=R_{ds}(V_{g},V_{ds})+2R_{c}(V_{g})\). For sample-A, we have \(R_{c}\approx 125\)\(\Omega\upmu\)m on the p-doping side (where there are p-p junctions at the two contact edges) and \(R_{c}\approx 275\)\(\Omega\upmu\)m on the n-doping side (where there are p-n junctions at the two contact edges).  
The relevant quantity for an RF transistor is the small signal resistance \(dV_{ds}/dI_{ds}\) that we calculate from the current through the transistor \(I_{ds}=V_{ds}/R\) and the applied bias voltage \(V_{ds}\) across the device. The simulated \(dV_{ds}/dI_{ds}\) is plotted in Figure 5a where the mobility \(\mu=10^{4}\) cm\({}^{2}\)V\({}^{-1}\)s\({}^{-1}\) and \(R_{c}\) are determined from the zero bias transfer curve and the thermal broadening coefficient \(\alpha\) (from [28]) is in principle universal. The very good agreement between measurement and simulation shows that we are able to accurately predict the behavior of a local gate transistor driven at high bias knowing the graphene mobility, the contact resistance and the substrate phonon energy. It validates our transistor model and confirms the role of the h-BN HPhPs at \(\hbar\Omega=0.1\,\text{eV}\) in velocity saturation. To emphasize the effect of the local gate on the saturation we plot in Figure 5b, a simulation for a substrate thickness of \(t_{BN}=300\) nm where all parameters are conserved (apart from \(V_{g}\) which is adjusted to conserve the zero bias density). There is a significant difference between local and remote gate on the shape of the transfer curve. In Figure 5b, the slight asymmetry between p and n doping comes from the contact resistance difference.
# Automated Control of the Fresh State of Industrial Concrete Behaviour by Rheometer Test Adjustment
## 4 Concrete Mix and Mixing Procedure  
To adjust the parameters of the rheological tests and select the best impeller, a concrete mix was designed, and its fresh behaviour was controlled using the prototype.  
The concrete mix was designed using ordinary Portland cement without CEM I 52.5 R. A modified polycarboxylate ether-based high-range water reducer admixture with a specific gravity of 1.05 g/cm\({}^{3}\) was incorporated to achieve a high concrete fluidity (slump values of approximately 19 cm). Fine limestone sand with a 0-4 mm nominal size and a coarse granitic fraction with a nominal size of 4-11 mm were used as aggregates.  
Table 1 presents the basic properties of these aggregates.  
Figure 5: Parameters of the FCT.  
Figure 6: Bingham model.  
Figure 7: Nomenclature of the rheological tests.  
Considering the mixing protocol, the aggregates (fine and coarse) were first mixed for 30 s for homogeneity. This was followed by adding more water (calculated to compensate for the aggregate absorption capacity of up to 80%) and mixing it with the aggregates for another 30 s. The cement was incorporated and mixed with the aggregates for 60 s. Subsequently, water was added. This cement-water contact time point was considered as the reference age (t = 0) for performing all the fresh concrete tests [25]. After 1 min of mixing, the superplasticiser was introduced, the concrete was mixed for a further two minutes, then let to rest for one minute before being mixed once more for a further minute. Lastly, several buckets were filled with the concrete, and the rheometer container was filled too. After that, the concrete was allowed to rest until it was ready for testing.  
Batches of 60 L were produced with the same mix composition in the same mixer under laboratory conditions (20 \({}^{\circ}\)C). All batches were controlled using rheological and industrial tests at different times, using the time of the cement-water contact as the initiation reference. The tests were conducted using the slump test (Abrams cone-UNE-EN 12350-2:2020 [26]) and flow curve test (FCT), and were performed at each of the following testing ages: 10, 15, 20, and 30 min. In addition, three 100 \(\times\) 100 \(\times\) 100 mm cubes were cast to control the compressive strength at 28 days following UNE-EN 12390-3:2020 [27]. The slump and compressive strength results were used to control the homogeneity of the different batches produced.  
After each testing time, the concrete used for the slump test was reintroduced into the mixer, and the vane of the rheometer was extracted, leaving the material in the rheometer. The mixture was remixed for 15 s in the mixer three minutes before the following testing times (15, 20, and 30 min) to re-homogenise the mixture; the concrete in the rheometer containers was also simultaneously re-homogenised using a shovel for the same duration.
## 3 Experimental Results
### Fixed Infrastructure Density Scenario  
In this subsection, we present the results of the simulation experiments obtained by simulating the fixed infrastructure density scenario involving four cells in the simulated area for each investigated technology and its mode, i.e., device-to-device mode 3 and infrastructural mode, and all the simulated traffic intensities.
## 2 Materials and Methods
### Determination of Antiradical Activity against DPPH Radical  
The ability to capture free radicals from microalgae extracts was evaluated using the (1,1-diphenyl-2-picrylhydrazyl (DPPPH) assay [32]. This method is simple, rapid and convenient, independent of sample polarity for the screening of many samples for radical scavenging activity [33]. Briefly, a series of extract concentrations with different ratios of extracts to methanol, i.e., 1: 0.1, 1:0.01, 1:0.001, 1:0.0001 and 1:0.00001 were prepared. For each 4.9 mL of diluted extract, 0.1 mL of 5 mM DPPH radical in methanol solution was added. Then the mixtures were shaken to ensure that all the solutions were well mixed and placed in dark condition at room temperature for 30 min. After that, the absorbance of each sample of algae extract containing DPPH (A\({}_{1}\)), without DPPH (A\({}_{\text{s}}\)) and only DPPH solution without algae extract (A\({}_{\text{o}}\), called control) were recorded at 517 nm using a spectrophotometer (UV 6305, Genway). Percentage inhibition by DPPH in samples was determined by comparison with the methanol-treated control group and calculated using the following formula:  
\[\text{DPPH radical scavenging activity (}\%\text{)}=\left[\frac{\text{A}_{0}-( \text{A}_{1}-\text{A}_{\text{s}})}{\text{A}_{0}}\right]\times 100 \tag{4}\]where \(\rm A_{o}\) is the absorbance of the control solution (containing only DPPH), \(\rm A_{1}\) is the absorbance of test sample containing DPPH solution and \(\rm A_{s}\) is the absorbance of the test sample without DPPH. Ascorbic acid (Vit C) was used as a standard. The concentration of _C. vulgaris_ extract (mg/mL) required for decreasing the initial concentration of DPPH by 50% (EC\({}_{50}\)) was also calculated and expressed relative to ascorbic acid in terms of ascorbic acid equivalent.