esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Experiments
### Components Evaluation  
#### 5.5.1 Importance of DropAPI  
The DropAPI is necessary for two reasons. First, it addresses the issue of high computational costs associated with incorporating too many APIs [46]. To illustrate, we randomly selected a sample set comprising 200 applications, with an equal split between benign and malicious ones. Constructing a heterogeneous graph (HG) containing all API calls from these APKs, we analyzed them using Androguard. The resulting Neo4j database contained 284,464 nodes for API nodes and 102 nodes for the other four types combined, indicating that 99.89% of the nodes were API nodes. Additionally, when we increased the number of applications to 500 for training our baselines and HertDroid, we encountered memory overflow problems in all models. This underscores that the absence of the DropAPI module would substantially increase computational costs.  
Second, including this module is imperative due to the problem of low performance associated with incorporating too many weakly correlated APIs [47]. We fed the HG with 200 applications into the GAT and GCN models, two models with the fewest parameters among the baselines. Both GAT and GCN models yielded F1 values of less than 0.7. In summary, the DropAPI module adopted in this paper not only reduces the consumption of computing resources but also improves the detection ability of the entire model.
# Simulation Study of Microwave Ablation of Porous Lung Tissue
## 3 Results
### Effect of Tumor Diameter  
The temperature distribution of the lung tissue with tumor diameters of 1.4 cm, 2.0 cm, and 2.6 cm, porosity of lung tissue (\(\phi_{t}\)) is 0.7, porosity of tumor tissue (\(\phi_{t}\)) is 0.6, at P = 10 W and t = 360 s is shown in Figure 3a-c, respectively. It can be seen that the ablation areas of the tissues are all nearly oval, and the temperature of the tissues at the slot of the microwave antenna is the highest. The highest temperatures reached by the ablated lung tissue were 89.4 \({}^{\circ}\)C, 87.3 \({}^{\circ}\)C, and 86.1 \({}^{\circ}\)C for tumor diameters of 1.4, 2.0, and 2.6 cm, respectively. The lung tissue temperatures obtained in the numerical simulation are closer to the temperature distribution in the study by [PERSON] et al. [21]. Observing Figure 3a, we found that the ablation area completely covered the tumor, whereas, in Figure 3b,c, the ablation area sizes are much smaller than the tumors. Therefore, we believe that P = 10 W, t = 360 s is sufficient to completely ablate a tumor with a diameter of 1.4 cm, whereas tumors with the diameters of 2.0 cm and 2.6 cm would require increased ablation power or ablation time in order to be completely ablated.  
We used \(\Omega=1\) as the ablation zone boundary, and the tissue ablation volume can be obtained by surface integration of the two-dimensional region [26]. Table 5 shows the maximum temperature reached, the transverse and longitudinal diameter of the ablation zone, and the ablation volume of tumors with different diameters. As the tumor diameter increased from 1.4 cm to 2.6 cm, the maximum temperature reached by the tissue decreased from 89.4 \({}^{\circ}\)C to 86.1 \({}^{\circ}\)C, the transverse diameter of the ablation zone decreased from 1.30 cm to 0.76 cm, the longitudinal diameter increased from 1.82 cm to 2.19 cm, and the ablation volume increased from 2.34 cm\({}^{3}\) to 2.52 cm\({}^{3}\), which indicates the influence of tumor size on the ablation. The effect of tumor size on ablation was mainly reflected in the transverse diameter of the ablation area, and the increase of tumor diameter would limit the heat transmission in the transverse direction but had little effect on the ablation volume.  
Figure 3: Temperature distribution of porous lung tissue at different tumor diameters (P = 10 W, t = 300 s, \(\phi_{t}\) = 0.7\(\phi_{t}\) = 0.6): (a) d = 1.4 cm, (b) d = 2.0 cm. (c) d = 2.6 cm.
## 3 Key Technology
### Interactive Multiple Models Algorithm Based on Factor Graph Optimization
#### 3.1.2 Smoothing and Fusion of Models  
The factor graph optimization method is employed as the sub-systems information fusion filters, and according to Equation (15), the general function of the IMMFGO in the IMU/GNSS/LiDAR integrated navigation system can be defined as follows:  
\[\begin{split}\mathbf{\hat{X}}_{k}^{*}=\underset{\mathbf{x}}{ \operatorname{argmin}}\Bigg{\{}\|\mathbf{r}_{p}-h_{p}(\mathbf{X}_{k})\|_{ \sum_{p}}^{2}+\sum\limits_{m\in[k-N,k]}\|\mathbf{  
When the number of sub-models is one, the update probability is optimized as follows:  
\[\mu_{k}^{j}=\Lambda_{k}^{j} \tag{26}\]  
Compared to AFGO, the proposed IMMFGO algorithm constructs the sub-models based on the precision of sensors and is adaptive to different environments.
## 2 Materials and Methods
### Clustering Analysis  
Traditional methods, such as NBR with NDVI, cannot identify the regenerated vegetation areas' exact boundary. The NBR has a 20 m resolution, and the NDVI has a 10 m resolution. The aggregation of two analyses may give a distorted view in understanding the regenerated vegetation areas. This study uses clustering analysis to detect the regenerated areas accurately.  
A non-hierarchical clustering method randomly forms a cluster of data and uses it as an appropriate cluster according to the change in the cluster's median value. The number of clusters is initially determined by user input. During the analysis phase, a set number of clusters is repeatedly generated to determine the appropriate number of clusters; the algorithm proceeds to another cluster if the first is deemed inappropriate [35]. This process is repeated until n clusters are created.
## 8 Common Uses of Styrene and Its Derivatives  
Styrene is a versatile and widely used monomer in industrial chemistry, playing a critical role in the production of fiberglass-reinforced plastics [95], construction materials like EPS and XPS insulation [96; 97], lightweight foam products for packaging and disposable items [98], durable adhesives and coatings [99; 100; 101], high-performance paints and inks [102; 103], and medical devices such as lab equipment and drug delivery systems [104; 105; 106]. It is also essential in electronics for its insulating and shock-absorbing properties [107; 108]. Despite its widespread use, it is toxic in nature. However, styrene is used in fuel cell membranes through advanced engineering and material science to ensure safety and performance. It is typically incorporated into copolymers, such as sulfonated styrene-based polymers, which provide excellent proton conductivity and thermal stability--key properties for proton exchange membranes (PEMs). Styrene is chemically stabilized, crosslinked, or encapsulated within a robust polymer matrix to prevent leaching and minimize exposure risks. Manufacturing processes are tightly controlled, adhering to strict safety and environmental regulations, while the sealed operating environment of fuel cells further reduces potential hazards. Although styrene offers cost effectiveness, durability, and high performance in fuel cell applications, ongoing research focuses on developing safer alternatives to further mitigate risks.  
This review article covers the whole aspect of styrene and its derivatives for the application of different types of fuel cells as a material for membrane manufacturing. Firstly, the introduction of different types of fuel cells is explained along with their working principle. Membranes are critically studied, including their types, materials, and ion conductivity mechanisms. In addition to their functions, different types of membranes, such as PEM and AEM, are discussed in detail for PEMFCs, DMFCs, and AEMFCs. Furthermore, different types of uses of styrene and its copolymer are discussed in detail along with their application in the future. The recently published research on styrene use in membrane material is explained in the end with the conclusion and future advancement on styrene-related membranes.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Characteristics**} & \multirow{2}{*}{**Physical State**} & **Density** & **Boiling Point** & **Melting Point** & \multirow{2}{*}{**Solubility**} \\  & & **(\(\rho\))** & **(\({}^{\circ}\)C)** & & **(\({}^{\circ}\)C)** & \\ \hline \multirow{2}{*}{Values} & Colorless/light yellow & \multirow{2}{*}{0.91} & \multirow{2}{*}{145} & \multirow{2}{*}{\(-30\)\({}^{\circ}\)C} & Water: 0\% \\  & & & & & Organic solvents (alcohol, \\ \multicolumn{5}{c}{} & & & & ether, etc.): 100\% \\ \hline \hline \end{tabular}
\end{table}
Table 1: General characteristics of styrene.
# Polycrystalline Formamidinium Lead Bromide X-ray Detectors
## 1 Introduction
[PERSON] et al. introduced a post-annealing process to passivate the ionic migration in pressed wafers of the 'double perovskite' Cs\({}_{2}\)AgBiBr\({}_{6}\), which exhibited an X-ray sensitivity of 250 uC Gy\({}^{-1}\) cm\({}^{-2}\)[17]. The same group have also reported the development of X-ray detectors using hot pressing of CsPbBr\({}_{3}\) to form a quasi-monocrystalline film at temperatures of up to 870 \({}^{\circ}\)K [18]. However, the fabrication of X-ray detectors using pressed polycrystalline FAPbBr\({}_{3}\) has not been reported so far. We have grown micro-crystals of FAPbBr\({}_{3}\) by solution growth, using the inverse temperature crystallisation method (ITC) [19]. The perovskite micro-crystals were used to fabricate a polycrystalline pellet for use as a X-ray detector. A hydraulic press provided  
Figure 1: (**a**) Mass attenuation coefficient calculated using NIST XCOM for FAPbBr\({}_{3}\), CdTe and Se, (**b**) Calculated relative X-ray absorption, expressed as the fraction of incident X-ray photons absorbed by a 1 mm thick detector, for FAPbBr\({}_{3}\), CdTe and Se. pressures ranging from 12 to 124 MPa, and was used to synthesize the FAPbBr\({}_{3}\) microcrystals into pellets of 10 mm in diameter, and with thicknesses between 1 mm and 2.5 mm. The pellets were annealed after pressing at 145 \({}^{\circ}\)C for 15 min in air in order to optimise their conductivity and charge transport properties. Electrical contacts were deposited onto the top and bottom surfaces of each pellet using thermally-evaporated gold. A mechanical mask was used during the contact evaporation to produce circular gold contacts with a diameter of 4 mm. The optical properties of the pellets were studied using photoluminescence spectroscopy, and the morphology of the pellet structure was examined using scanning electron microscopy (SEM) and X-ray diffraction (XRD). The electrical properties and X-ray sensitivity of the devices were systematically studied using a 40 kV X-ray beam, and the effect of different pressures and annealing processes was examined.
# Ripening of Hard Cheese Produced from Milk Concentrated by Reverse Osmosis
## 3 Results and Discussion
### Volatile Compounds  
A total of 42 volatile compounds were identified in RO-cheese: nine alcohols, six ketones, seven acids, seven esters, six aldehydes, four aromatic compounds, and three of other groups. Table 2 shows the volatile compounds grouped by classes and the changes in content throughout the ripening process. Volatile acids and alcohols were the main volatiles identified in RO-cheese (1.5\(-\)46.3 and 0.0\(-\)10.4%TIC, respectively). Esters and ketones comprised the smaller share (0.0\(-\)6.7 and 0.0\(-\)2.9%TIC, respectively, except for the ketones at the initial point of ripening), while aldehydes and aromatic compounds were among the minor ones (0.0\(-\)0.3 and 0.0\(-\)0.4%TIC, respectively). The identified volatile compounds showed a dynamic behavior during cheese maturation; however, the total amounts within most detected chemical groups (except for the ketones and aromatic compounds) increased by the end of ripening (Figure 5). Figure 4: Radar diagram showing the relative content of individual free amino acids (FAA) during six months of RO-cheese ripening (mol%). Results presented are the means of two measurements. Amino acids: GABA, \(\gamma\)-aminobutyric acid; Ala, alanine; Thr, threonine; Glu, glutamate; Asp, aspartate; Gly, glycine; Arg, arginine; Gln, glutamine; Ser, serine; Asn, asparagine; His, histidine; Trp, tryptophan; Phe, phenylalanine; Leu, leucine; Ile, isoleucine; Val, valine; Met, methionine; Tyr, tyrosine; Lys, lysine; Cys, cysteine; Orn, ornithine; and Pro, proline. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Compound** & **RT** & **RI, Exp** & **RL, Theor 1** & **Odor Description 2** & \multicolumn{6}{c}{**Ripening Time, Months**} \\ \cline{6-11}  & & & & & & & & & & & \\ \cline{6-11}
**Alcohols** & & & & & & & & & & & \\ Isopropyl Alcohol & 2.15 & 510 & 515 & Woody, musty & – & 1 & – & – & – & 1 & 0.10 \\
2-Butanol, 3-methyl & 7.92 & 715 & 700 & Musty, vegetable, chesey & 1.34 & – & – & – & – & – \\
3-Butanol-1, 3-methyl- & 8.33 & 725 & 720 & Fruity & – & 0.04 & – & – & – & – \\
3-Butanol, 2-methyl- & 8.34 & 726 & 740 & Fruity, whiskey & – & – & – & – & 0.04 \\
1-Butanol, 3-methyl- & 8.80 & 738 & 750 & Fruity, banana, cognac & – & – & – & – & 0.09 & 0.18 \\
2-3-Butanol
# Development of a Metalens for Radio Wave Ground- Penetrating Radars
## 1 Introduction
The use of a metamaterial with a real part of the refractive index equal to 0.5 makes it possible to improve the characteristics of the antenna, namely: to reduce the level of side lobes, reduce the width of the main lobe directional pattern, and increase the radiation maximum. At the beginning of 2022, several interesting papers on the use of metamaterials in antenna technology were published. Thus, in [30], the effect of a gyro-bianisotropic metamaterial on the input impedance of a dipole antenna was considered. The article [31] is devoted to modeling the SRR structure and demonstrated the presence of magnetic resonance at a frequency f = 23.69 GHz, which is of interest for antennas supporting wireless microwave point-to-point communication systems (for example, in satellite systems). The original metamaterial structure for a dual-band subwavelength resonator antenna with a high gain for frequencies of 3.75 GHz and 5.66 GHz was presented in [32]. Metamaterials are also used in the design of antennas for 5G communication systems; for example, article [33] describes an antenna operating at frequencies ranging from 28.5 GHz to 30.5 GHz and having overall dimensions of 2.58 \(\lambda\). From the analysis of the literature, we can conclude that the worldwide scientific community is paying great attention to the creation and application of metamaterials in antenna technology; many works on the creation of metamaterials with various configurations and geometries have been presented. The authors of the article are looking for new ways and approaches to improve the quality of georadograms [34], so the results of the created antenna array based on the developed \"PlastRam\" antenna element [35] have already been presented. These results show a high accuracy in determining the thickness of the pavement layer. However, there are problems associated with the definition of the boundaries of the layers of the roadway of automobile and pedestrian roads. There are also difficulties in sounding the embankment of railways. To improve the created TerraZond geosounding system, it was proposed to improve the characteristics of the georadar by focusing the electromagnetic waves. For this, a metamaterial based on composite elements in the form of rings was used. A material with the same structure, but made of metallic elements, had a negative refractive index [36].
# Distributed Energy Sharing for PVT-HP Prosumers in Community Energy Internet: A Consensus Approach
## 2 Structure and Function of CEI  
The system architecture of the CEI is shown in Figure 1. There are three entities: PVT-HP prosumer, CHP operator and utility grid. Each prosumer is equipped with PVT, heat pump and user energy management system (UEMS) [13]. UEMS is in charge of communicating with other entities, adjusting local load demand and determine the output of heat pump. The heat pump uses the water from the tank of PVT system as the low temperature heat resource to produce high temperature hot water for end users. Excess electric and thermal energy can be shared among prosumers and the electricity can be sold to utility grid as well. CHP operator guarantees thermal supply through recovering the waste heat of micro-gas turbine when the heat pump cannot meet the users' thermal demand and conducts trading with utility grid and prosumers inside the community. Its energy management system is CHP operator energy management system (CO-EMS). After using the self-produce and CHP power, if the CEI is still in lack of electricity, the insufficient can be balanced by the utility grid.
## 5 Results and Discussion
### Intermodal Scheduling Case Study
#### 5.2.3 Carbon Tax Rate Impact Analysis  
Both academic research and international practices acknowledge that, alongside mandatory carbon emission regulations, carbon taxation plays a crucial role in incentivizing enterprises to manage their carbon emissions effectively. Based on the previously described network structure, Table 8 presents the input data for arithmetic examples of varying sizes, which serve as the basis for subsequent analysis. The influence of carbon tax fluctuations, gradually increasing from zero, on transport mode selection and carbon emissions is analyzed. The results are visualized in a line graph, with Figure 16 illustrating the impact of carbon tax on transport modes and associated costs.  
The introduction of a carbon tax has significantly contributed to reducing CO2 emissions. As the tax rate increases from 0.05 CNY/kg to 1 CNY/kg, emissions decrease substantially. However, beyond a tax rate of 0.8 CNY/kg, emissions stabilize, indicating that the relationship between the carbon tax and emissions is not strictly linear. While higher carbon taxes tend to increase total costs, the reduction in emissions at elevated tax levels partially offsets these costs, leading to a decline in total costs after reaching a peak.  
Figure 16: Impact of a carbon tax on transport modes and costs. (**a**) Changes in total costs and carbon emissions; (**b**) changes in the frequency of modes of transport.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Task** & **Origin–Destination** & **Quantity Demanded (TEU)** \\ \hline
1 & O-10 & (20, 30) \\
2 & O-15 & (20, 40) \\
3 & O-20 & (25, 50) \\
4 & O-25 & (30, 60) \\
5 & O-30 & (30, 70) \\ \hline \hline \end{tabular}
\end{table}
Table 8: Information on different orders.  
In terms of transport modes, higher carbon taxes encourage a shift from road transport to rail and waterway alternatives, promoting a transition to more sustainable logistics. When the tax is below 0.15 CNY/kg, road transport remains dominant and contributes the most to pollution. At the EU's base rate of 0.35 CNY/kg, stricter carbon tax policies result in a greater adoption of low-carbon transport modes. A well-calibrated carbon tax can optimize transport structures and mitigate emissions, but excessively high rates may impose economic burdens. Thus, achieving a balance between environmental sustainability and cost efficiency is essential.
## 2 Materials and Methods
### Data Sources and Processing  
This study utilized monthly vegetation index (NDVI) data derived from SPOT/VEGF-TATION NDVI satellite remote sensing data provided by the Resource and Environment Science Data Center of the Chinese Academy of Sciences. The dataset, generated using the Maximum Value Composite (MVC) method from 10-day composite data, offers 1 km resolution monthly NDVI data from 1998 to 2020 [24]. Additionally, annual NDVI raster data from 2000 to 2018, also at 1 km resolution, were obtained by calculating the mean of monthly NDVI values, representing the overall NDVI situation for the entire year. In order to avoid noise, particularly in arid or urbanized regions that have low NDVI values, an NDVI \(\geq\) 0.1 mask was applied to filter out non-vegetation surfaces before analyses. To isolate true vegetation trends, land cover classification data were obtained from the Resource and Environment Science and Data Center of the Chinese Academy of Sciences ([[http://www.resdc.cn/](http://www.resdc.cn/)]([http://www.resdc.cn/](http://www.resdc.cn/)), accessed on 18 May 2025) with a spatial resolution of 30 m. They were used to mask areas with significant underlying surface changes, which were then removed from the NDVI data. The land-use data were obtained from the 30 m resolution grid dataset publicly released by the Resource and Environment Science and Data Center (RESDC), Chinese Academy of Sciences ([[http://www.resdc.cn/](http://www.resdc.cn/)]([http://www.resdc.cn/](http://www.resdc.cn/)), accessed on 18 May 2025).  
SPEI data were obtained from the Figsshare platform ([[https://doi.org/10.6084/m9.figshare.c.5823533](https://doi.org/10.6084/m9.figshare.c.5823533)]([https://doi.org/10.6084/m9.figshare.c.5823533](https://doi.org/10.6084/m9.figshare.c.5823533)), accessed on 18 May 2025), providing a high spatial resolution (0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\)) SPI dataset for China from 1979 to 2018. To align with the NDVI data  
Figure 1: Study area with land-use distribution in 2020.  
resolution, the SPEI data were resampled to 1 km resolution using ArcGIS10.8 software and classified into five types (Table 1). The data were processed as follows [25]: (1) the original geographic coordinate system WGS84 was projected into UTM zone to eliminate longitudinal distance distortion; (2) the value of each interpolated pixel was computed using a bilinear weighting scheme based on its four nearest neighboring pixels; and (3) the resampling factor was defined as the ratio of the original pixel size to the target pixel size. County-level administrative boundaries and river system data for the West Liao River Basin were sourced from the Resource and Environment Science Data Center, while DEM data were obtained from the Geospatial Data Cloud platform. These datasets provided essential geospatial information for the study.