esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Results and Discussion
### Non-Wovens in Brownfield Remediation  
To date, oil-binding non-wovens have been extensively used for spill containment, but not yet for brownfield remediation. The idea of using a non-woven material to continuously or intermittently bind hydrocarbons, be pressed out and be reused, has the potential to save adsorbent material and costs. The principle is simple (see Figure 9).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Date**} & \multirow{2}{*}{**Time**} & **Amount of Water Pumped Up, Cleaned and Re-introduced in the Ground (1.9 L/s)** & **Cleaning by Classic Oil Separator (OS)** & **Cleaning by Non-Wovens in the Ihe Inclined Bed Filter (IBF)** \\ \hline
21 September 2021 & 10:35–16:40 & 41,610 & x & - \\ \hline
21 September 2021 & 11:00–16:40 & 38,760 & - & x \\ \hline
22 September 2021 & 09:15–16:00 & 46,170 & - & x \\ \hline
23 September 2021 & 10:20–16:15 & 40,470 & - & x \\ \hline
28 September 2021 & 09:35–16:00 & 37,050 & x & - \\ \hline
28 September 2021 & 10:00–16:00 & 41,040 & - & x \\ \hline
29 September 2021 & 12:15–17:10 & 33,630 & x & - \\ \hline
29 September 2021 & 12:30–17:10 & 31,920 & - & x \\ \hline
30 September 2021 & 09:30–18:20 & 60,420 & x & - \\ \hline
30 September 2021 & 10:30–18:20 & 53,580 & - & x \\ \hline Total [L] & & 511,290 & 259,350 & 251,940 \\ \hline \hline \end{tabular}
\end{table}
Table 9: The 511.3 m\({}^{3}\) groundwater cleanup took place from 21–30 September 2021.  
The non-wovens in these experiments retained 18 times their own weight in mineral hydrocarbons (and still 17 times their weight after 15 cycles of pressing out and reusing), and were able to retain 8.6 times their weight of rapeseed oil when fresh and 7.8 times their weight of rapeseed oil after 15 loading cycles. The oil-laden non-wovens can be recycled in the processes by pressing them out. A configuration with endless tape could be used. When fully loaded or mechanically overstressed, the oil-laden non-wovens can be incinerated.
## 2 Configuration and Structure
### Graphene Film  
Graphene is an emerging material with single layer carbon atoms in the form of hexagons. This unique structure offers graphene optical properties of controllable light absorption, considerable carrier mobility, uniform light absorption rate of 2.3% in a broadband, etc. [10; 22; 23; 24; 25; 26; 27; 28; 29; 30]. These favorable properties imply the graphene has good potential in the application of high-speed, low-footprint and low-power consumption devices.  
As shown in Figure 2b, a plate capacitor is formed by applying bias voltage to graphene layers. Light absorption is then controlled by the applied external electric field via the electrostatic doping effect. Since the interband transition in graphene is affected by Fermi level with no consideration of sign, both graphene layers can simultaneously be \"transparent\" at the high driving voltage, which refers to the \"ON\" state. An efficient numerical calculation method is important [31]. As has been reported [32], the graphene layer can be modeled as a 3D bulk material with a constant thickness or a 2D surface structure. To obtain accurate results, a smaller grid size is required in 3D simulations, which implies longer calculation time and larger memories requirement. On the basis of accuracy, it is desirable to model graphene as a 2D layer for higher efficiency. In this work, the graphene layer is considered a surface conductivity dielectric with a thickness of zero. Benefit from the reduced number of meshes, the calculation time reduces with accuracy guaranteed. The surface conductivity \(\sigma_{\text{g}}\) of the graphene may be adjusted by its chemical potential \(\mu_{\text{c}}\). This process can be well described by the Kubo formula [33], in which \(\tau\) corresponds to the relaxation time, the intraband transition \(\tau_{1}\) is 1.2 ps and the interband transition \(\tau_{2}\) is 15 fs. Graphene layers exhibit special physical properties at the epsilon-near-zero (ENZ) point, \(\mu_{\text{c}}(\text{ENZ})\approx 0.5\) eV [34]. When \(\mu_{\text{c}}\) is larger than \(\mu_{\text{c}}(\text{ENZ})\), graphene shows the characteristics of the dielectric medium. Conversely, graphene behaves like a metallic layer and strong light absorption happens when \(\mu_{\text{c}}\) is smaller than \(\mu_{\text{c}}(\text{ENZ})\). Equation (4) illustrates the relationship between chemical potential and bias voltage [30]:  
\[\mu_{\text{c}}=\hbar v_{\text{F}}\sqrt{\pi\eta\left|V_{\text{g}}-V_{0}\right|} \tag{4}\]  
where \(v_{\text{F}}\) is the Fermi velocity of graphene (\(v_{\text{F}}=2.5\times 10^{6}\) m/s) [35] and \(\eta=\epsilon_{\text{F}}\epsilon_{0}/de\) is derived from the parallel capacitor model (\(\epsilon_{\text{F}}\) and \(d\) are the permittivity and thickness of SiO\({}_{2}\) isolation layer, respectively). As shown in Figure 4, \(\mu_{\text{c}}\) can shift from 0.2 to 0.6 eV as the applied voltage changes from 0.608 to 5.442 V.
# A Comprehensive Review of Developments in Electric Vehicles Fast Charging Technology
## 2 Fast Charging Techniques for Electric Vehicles
### Bidirectional Charging Integration  
Bidirectional charging, also known as vehicle-to-grid integration, is a promising concept in the electric vehicle ecosystem. It allows electric vehicles not only to draw energy from the grid for charging but also to discharge stored energy back into the grid [77], as shown in Figure 3. This bidirectional energy flow turns EVs into mobile energy storage resources, offering flexibility and support to the power grid [78]. Advanced bidirectional charging systems use communication protocols and control strategies to manage power flow, ensuring grid stability and optimizing energy usage. By participating in grid services, EVs with V2G capabilities can stabilize the grid, manage loads, and integrate renewable energy sources. This integration enhances grid stability, enables load management, and supports renewable energy integration, optimizing the use of renewable resources and improving grid efficiency [25; 74; 78; 79]. However, successful V2G integration depends on a compatible infrastructure, communication systems, and regulatory support, which may vary by region and market dynamics [22; 80].  
Bidirectional charging offers convenience and demands additional setup and planning compared to standard charging methods. Although generally safe, its added complexity requires meticulous management. These chargers exhibit moderate weatherproofing, ensuring functionality in various conditions. However, integration with infrastructure relies on the availability of compatible charging stations and home setups, which are not yet widely accessible. Compatibility extends to some electric vehicles (EVs) with additional hardware, but it is not universally compatible across all models. The discharger cycles inherent to bidirectional charging may lead to slightly accelerated battery degradation over time. Nonetheless, there is potential for a broader adoption and future upgrades to enhance system capabilities, emphasizing its scalability and upgradability. Despite its advantages,  
Figure 3: Bidirectional EV charging V2G.  
bidirectional charging tends to have lower efficiency compared to other faster charging methods, primarily due to additional conversion steps being involved in the process.
## 2 Materials and Methods  
### Raw Materials  
#### 2.1.1 Shield Muck  
The shield muck used in this study was sourced from a shield tunnel section of Changsha Metro Line 7 in Hunan Province, China. According to ISO 11465:1993 [44] (gravimetric method for soil moisture determination), the initial moisture content of the raw shield muck measured 23.71 \(\pm\) 1.2%. Given the high and variable moisture content significantly affecting test results, the collected shield muck underwent pretreatment: dried to constant weight in a 105 \({}^{\circ}\)C forced-air drying oven (China Shanghai Yiheng Scientific Instrument Co., Ltd., Shanghai, China), mechanically crushed using a jaw crusher (China Henan Red Star Mining Machinery Co., Ltd., Zhengzhou, China), sieved through a 2 mm square-aperture sieve, and then sealed for storage. Phase analysis of the shield muck was conducted using a MiniFlex 600 X-ray diffractometer (Cu target, 40 kV), as shown in Figure 1a, with the operational parameters set to a scanning range of 15-80\({}^{\circ}\) and a scanning speed of 4\({}^{\circ}\)/min. The chemical composition of dried shield muck was analyzed by X-ray fluorescence spectroscopy (Table 1), revealing dominant components of SiO\({}_{2}\) (44.62%), Al\({}_{2}\)O\({}_{3}\) (18.37%), and CaO (13.13%), collectively accounting for 76.12% of total content. The major mineral phases included calcite, quartz, muscovite, and kaolinite, consistent with component characteristics reported in previous shield muck studies [3].  
Figure 1: XRD patterns of (**a**) shield muck and (**b**) GGBPS powder.
## 2 Materials and Methods
### Sample Treatment and Analysis  
The wet and dry samples were collected and transferred to the laboratory within 72 h. They were filtered through a 0.45 um quartz fiber membrane, which was pre-measured and recorded. The filtrates (wet deposition) were acidified with 1:1 HNO\({}_{3}\) in a 30 mL aliquot and ready for analysis. Both the membrane and its precipitate were dried below 65 \({}^{\circ}\)C until the mass difference between the two measurements was under 0.5 mg. The dried precipitates (dry deposition) could then be used for analysis.  
Samples were analyzed for Pb, Cr, Cd, Ni, Cu, and Mo. About 50 mg of each sample was digested in a mixture of HCl, HNO\({}_{3}\), HF, and HClO\({}_{4}\)[12], and analyzed using Inductively Coupled Plasma Mass Spectrometry (ICP-MS, NexION 300Q, PerkinElmer, Waltham, MA, USA) and Atomic Fluorescence Spectrometry (AFS, AFS-8330, Titan Instruments, Beijing, China) for As concentration.  
Quality assurance and control involved standard reference substances (soil, CSS21-GSS26) from the National Institute of Metrology, China. Table 1 shows the detection limits of the wet and dry depositions. The sample recoveries ranged from 90% to 110%, and the analyses were performed in triplicate, ensuring levels of accuracy and precision that meet the quality requirements [25].  
The Mineral Liberation Analyzer (MLA) is a process mineralogy automatic analysis and testing equipment developed by the University of Queensland, Australia. Equipped with an energy spectrometer, we can achieve automatic scanning and energy spectrum analysis, accurately identify mineral types, and determine content. Regolith sample observations were made with the aid of an MLA in the Institute of Resource Utilization and Rare Earth Development, Guangdong Academy of Sciences in China. The MLA 650 system consisted of an FEI Quanta 650 scanning electron microscope, Bruker Quanta 200 dual probe electric refrigeration energy spectrometer, and MLA software version 3.1. The working conditions were an acceleration voltage of 20 kV, a working distance of 10 mm, and high vacuum mode.
# Cattle Weight Estimation Using Fully and Weakly Supervised Segmentation from 2D Images
## 4 Conclusions  
Artificial intelligence techniques can enable analyses that were not previously possible, and can be applied to the livestock field for great benefits. In the livestock industry, the weight of cattle is directly related to the competitiveness of the farm.  
In this study, an image-based cattle weight estimation system was proposed. To estimate the body weight, a segmentation mask was obtained from the top-view images of 43 cattle, 12 kinds of features were extracted from the segmentation, and regression analysis was performed. The MAPE of the proposed system was 5.06% for FSS and 9.8% for WSS. The results of the FSS method demonstrated that it can be effectively used in livestock farms. Fully supervised segmentation is generally a method that can achieve high accuracy compared to weakly supervised methods. However, preparing a sufficient dataset for the deep learning model to train requires a significant investment of human resources and time. On the other hand, this study has demonstrated that weakly supervised segmentation can achieve a similar performance while dramatically reducing the required human resources and time. In addition, the performance of the deep learning model improves as the amount of training data increases; therefore, if enough data are available, the performance of the WSS method can be improved. In future studies, we plan to find more effective features in the WSS mask and improve the performance of the WSS method by collecting more research data.  
Conceptualization, H.-c.C.; methodology, C.-b.L., H.-s.L. and H.-c.C.; software, C.-b.L.; validation, C.-b.L. and H.-s.L.; formal analysis, C.-b.L.; investigation, C.-b.L.; resources, H.-s.L.; data curation, C.-b.L. and H.-s.L.; writing--original draft preparation, C.-b.L.; writing--review and editing, H.-c.C.; visualization, C.-b.L. and H.-s.L.; supervision, H.-c.C.; project administration, H.-c.C.; funding acquisition, H.-c.C. All authors have read and agreed to the published version of the manuscript.  
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2022R11 IA3053872) and was supported by \"Regional Innovation Strategy (RIS)\" through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (MOE) (2022 RIS-005).  
The animal study was approved by the Gangwon-do Live-stock Research Institute in Republic of Korea.  
Not applicable.  
The data used in this study are available upon request from the corresponding author.  
The authors declare no conflict of interest.
## 1 Introduction  
In gearbox optimization design, determining optimum gear ratios has been a greatly important task. It can be explained by the fact that the size, the mass, and therefore, the cost of a gearbox is significantly affected by the gear ratios. To illustrate, Figure 1 shows the relation between the gear mass and the gear ratio of the second stage \(u_{2}\)[1]. It can be seen from the figure that with the optimum value of \(u_{2}\) (\(u_{2}=2\)), the mass of gears is merely about 178 (kg) whereas it reaches about 275 (kg) when \(u_{2}=6\). Therefore, there has been various research work dealing with optimizing gear ratios so far [1; 2; 3; 4; 5; 6; 7; 8; 9; 10; 11]. The methodology of gear ratio optimization can basically be divided into three groups, e.g., graph method, practical method, and model method. The oldest method is the graph method [2; 12], whereby the gear ratios are found based on the graph of the relationship between the component ratios and the total gearbox ratio. Figure 2 is an example of this method in which the gear ratios of the first and the second stages \(u_{1}\) and \(u_{2}\) of a three-stage helical gearbox are determined graphically. The practical method is introduced in [13], in which the optimum gears are determined based on the actual data from gearbox companies. For example, the mass of a two-stage helical gearbox is minimum when the ratio of the center distances of the second to the first stage is 1.4-1.6 [13]. From that comment, the optimum gear ratios are given. The most common method is the model method [3; 4; 14; 15; 16]. In this method, models for calculating optimum gear ratios are determined by solving optimum problems with different target functions such as minimal gearbox length [3; 4; 15], minimal mass of gears [4] or minimal gearbox cross section [4; 14; 16].  
In literature these studies have investigated various levels of gear stages such as two-stage gearboxes [17; 18], three-stage gearbox [4; 14], and four-stage gearboxes [19]. Also, the determination of optimum gear ratios of bevel gearbox was carried in [20; 21; 22; 23]. Recently, the optimum partial gear ratios have been found for mechanical driven systems using a gearbox and a chain drive [5; 9; 23] or a V-belt drive [22; 24; 25].  
As previously mentioned, the optimal gear ratios directly impact the cost of the gearbox. However, up to now, there has been no research on calculating the optimal gear ratios with cost objective function. For this reason, this article presents a study on cost optimization in terms of finding the optimum gear ratio of three-stage Helical gearboxes. The objective functions selected were the optimum gear ratios for second and third stage gears. Eleven input parameters were taken to investigate each parameter's influence and their interaction on the objective functions. A simulation experiment was planned using computer program to carry out the above issue.
# Exposure to NO\({}_{2}\) and PM\({}_{2.5}\) While Commuting: Utility of Low-Cost Sensor
## 4 Discussion  
The study provided valuable insights into the variability of exposure to air pollutants across different modes of transport during both the heating and non-heating seasons. The analysis of travel patterns, environmental conditions, and pollutant concentrations revealed significant seasonal differences and transport-mode-specific exposure trends to PM\({}_{2.5}\) and NO\({}_{2}\). Data from fixed air quality monitoring stations indicated that concentrations of both PM\({}_{2.5}\) and NO\({}_{2}\) were higher during the heating season compared to the non-heating season. This finding aligns with previous research and is attributed to increased emissions from residential heating and unfavorable meteorological conditions that limit pollutant dispersion. In contrast, personal exposure measurements using low-cost sensors, which accounted for transport mode and season, exhibited inverse seasonal trends. This may be explained by the dynamic nature of personal exposure during commuting, where local emission sources and variable traffic conditions play a crucial role. This highlights the necessity of supplementing fixed monitoring data with mobile measurements to achieve a comprehensive assessment of air pollution exposure. Comparing our findings to studies in other regions (Table 2) revealed considerable variations in pollutant exposure.
## 3 Characterization of Asphalt Binder
### Multiple Shear Crep Recovery  
The DSR with G*/sin \(\delta\) (AASHTO M320) is the typical parameter for rutting prediction of asphalt pavement. However, this method has been revised to provide a better prediction on the rutting performance of modified asphalt binder by MSCR. This method measures the permanent strain accumulated in the binder after designated cycles of shear loading and unloading. In which, lower permanent shear strain indicates higher rutting resistance of the pavement.  
Figure 6: Modified Asphalt Binder Viscosity at Low Modifier Percentage.  
Figure 7: Modified asphalt binder viscosity at high modifier percentage.  
Subsequently, the rutting resistance of asphalt binder is characterized using non-recoverable compliance (Jnr) which is considered as the best approach to replace the current Superpave testing method, \(G^{*}/\sin\delta\) (\(\omega\) = 10 rad/s) [43; 48]. Additionally, the percent recovery (R) is also determined in order to understand the high temperature viscoelastic deformation properties [43], where higher R value indicates a better resistance to rutting. Meanwhile, a lower Jnr value shows a better resistance to permanent deformation (rutting).  
The mean recovery percentage (\(n\) = 3) of the tested asphalt binders are presented in Figures 8 and 9. Based on the non-recoverable compliance criteria, the results show that the modified binders have lower rutting potential as compared to the control binder, PG 58-28. Additions of newly manufactured pellets have significantly increased the resistance to permanent deformation by at least 27% greater than PG 58-28 binder. Asphalt binder modified using 5% PECC-ICA has shown the best performance, in terms of non-recoverable compliance criteria and percent recovery after continuously multiple loading action on the sample. Referring to the specimens prepared using 3% PECC-1 CA and 3% PECC-2 CA, application of 1% coupling agent in the PECC material represents better elastic response compared to 2% coupling agent, which is consistent to the Jnr analysis. Samples tested using lower stress levels have resulted in smaller non-recoverable compliance and superior in terms of percent recovery. This is clearly simulated the condition in the field, where heavy vehicles (e.g., lorries and trucks) cause more severe permanent deformation compared to other vehicles, as we can see the rut depths in the slow lane are typically more severe than the fast lane of a highway.  
Overall, without the presence of coupling agent, asphalt binder modified using 3% PECC has shown a better recovery percentage compared to 5% PECC sample. With the addition of coupling agent, a higher percentage could be adopted in the modification process of asphalt binder. However, the amount of coupling agent should be limited to 1% to avoid adverse effects on its resistance to rutting.
## 2 Materials and Methods
### Antibacterial Activity
To the best of our knowledge, the inhibitory effect of _P. pinea_ L. bark polar extract against _E. coli_ is revealed here for the first time. Some studies have highlighted the antibacterial action of _P. pinaster_ Ait. and _P. pinea_ L. bark phenolic-rich extracts against _S. aureus_ and _E. coli_. Recently, [PERSON] et al. [10] have demonstrated the inhibitory action of 50 mg mL\({}^{-1}\) aqueous and ethanolic extracts derived from _P. pinaster_ Ait. bark against _S. aureus_ (ATCC\({}^{\otimes}\) 6538), under the 24 h treatment, but they have not prevented _E. coli_ (ATCC\({}^{\otimes}\) 9337) growth, whilst [PERSON] et al. [13] have also proved the suppressing capacity of Pycnogenol\({}^{\otimes}\) against methicillin-resistant _S. aureus_ viability. Conversely, [PERSON] et al. [20] evidenced bacteriostatic activity of 20 mg mL\({}^{-1}\) Pycnogenol\({}^{\otimes}\) for _S. aureus_ (ATCC\({}^{\otimes}\) 6538) and _E. coli_ (ATCC\({}^{\otimes}\) 9337) but not bactericidal effect. All these research groups have suggested that phenolic compounds may be involved in the antibacterial action of pine bark polar extracts, with particular attention to catechin and proanthocyanidiths [68; 69]. Additionally, the hypothesis of complexation between phenolic compounds and bacterial proteins, through hydrogen bond and hydrophobic connections [20] and/or synergic effects between phenolic compounds and other extract components, should be posed. Furthermore, quinic acid present in the studied pine bark polar extracts may also have an important role in their antibacterial effect; [PERSON] et al. [70] have recently demonstrated the antibacterial effect of quinic acid against ten foodborne pathogens, including _S. aureus_ ATCC 6538 (minimum inhibitory concentration of 2.5 mg mL\({}^{-1}\)), with an ability to damage the normal function of the _S. aureus_ cell membrane. This compound has also shown an inhibitory effect against _E. coli_ ATCC\({}^{\otimes}\) 11229 growth (minimum inhibitory concentration of 5 mg mL\({}^{-1}\)) [70]. Considering the promising data revealed in the present study, polar fractions from Portuguese _P. pinaster_ and _P. pinea_ barks exhibit interesting antioxidant and antibacterial actions, which may be ascribed to quinic acid and phenolic compounds. Therefore, these forest by-products can be regarded as renewable raw materials of polar added-value bioactive compounds for food and nutraceutical and biomedical applications, such as skin care, in addition to the current energy generation, in accordance with the biorefinery concept.
# 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  
The V2X services continue to receive 4G and 5G-based system support from 3 GPP standardization. In this regard, various enhancements are produced for enhancing V2X (eV2X) and advancing V2X (aV2X) services support. These enhancements have been addressing architectures, application layers, security aspects, media handling, etc.