esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Experimental Results and Analysis
### Effect of Nanomaterials on the Dispersion of Breakdown Voltage in Transformer Oils  
A breakdown experiment was conducted on pure oil and nanoparticle fluids with a water content of 26 ppm.  
The error bars of the breakdown voltage of pure oil at different temperatures were obtained by processing the experimental data, as shown in Figure 12. From the figure, it can be observed that the dispersion of the breakdown voltage was large within the temperature range of \(-30\)\({}^{\circ}\)C to \(-10\)\({}^{\circ}\)C, indicating an unstable breakdown voltage. The dispersion of the breakdown voltage was smaller around \(0\)\({}^{\circ}\)C due to its minimal absolute value. As the temperature continued to increase, the dispersion of the breakdown voltage of pure oil started to increase again, indicating a significant influence of temperature variation on the stability of the breakdown voltage of the oil sample.  
The summary of the breakdown test data for nanofluid is shown in Figure 13. Compared to Figure 12, it can be observed that, within the experimental temperature range, the dispersion of the breakdown voltage for the nanofluid was significantly smaller than that of pure oil. Furthermore, as the temperature increased above \(20\)\({}^{\circ}\)C, the dispersion further decreased. This indicates that, at higher temperatures, the nanomaterials still had a noticeable effect on reducing the dispersion of the breakdown voltage in oil gaps.  
Figure 11: Results of the breakdown experiment of pure oil under different electric fields.  
When the temperature was below 0 \({}^{\circ}\)C, the dispersion of the breakdown voltage for the nanofluid was smaller than that of pure oil. When the temperature was above 0 \({}^{\circ}\)C, the nanomaterials had less impact on the dispersion of the breakdown voltage in transformer oil compared to below 0 \({}^{\circ}\)C, and their effect was not as significant. As both types of oil exhibited the minimum breakdown voltage at 0 \({}^{\circ}\)C, the addition of nanomaterials had no noticeable effect on improving the dispersion of the breakdown voltage. On the basis of the analysis, it can be concluded that, within the temperature range of \(-\)30 \({}^{\circ}\)C to 30 \({}^{\circ}\)C, the breakdown voltage values had a large dispersion, while the addition of nanomaterials to transformer oil resulted in a smaller dispersion of the breakdown voltage. From the perspective of practical applications, nanomaterials significantly improve the dispersion of the breakdown voltage in transformer oil.
# Resilience in the Context of Cyber Security: A Review of the Fundamental Concepts and Relevance
## 3 Cyber Resilience: Fundamental Concepts
### The Relevance of Cyber Resilience in Various Segments
#### 3.2.7 Financial System  
The financial system has also been a frequent target of attacks for various reasons, such as the potential financial gains from a successful attack; obtaining resources to finance terrorist actions; or causing the collapse of national and global financial markets [57]. Data protection has sought to use reliable and user-friendly digital identification systems to provide protection mechanisms that are secure and robust enough to guarantee the resilience of various organizations, including banks [58]. Financial institutions are increasingly dependent on digital technologies and are exposed to cyber-attacks, technical failures, human error and natural disasters, so cyber resilience is becoming an urgent necessity [59].
## 3 Software Receiver Implementation
### Back-End  
The back-end subsystem is composed of the constellation demapper and the SCCC Decoder. The two blocks are responsible for transforming the received symbols in the output bits, reducing the errors due to channel impairments. As seen in the previous section, the front end of the receiver was not highly computationally intensive. On the other hand, the back end has been computed to be the most computationally intensive part of the receiver. For its recursivity and because of the several executed operations, the back end has been demonstrated to be the bottleneck of the receiver. For this reason, the development of the receiver has focused on the implementation of the back-end blocks on GPU, for optimizing their execution and improving the overall performance of the system. It is worth mentioning that both the constellation demapper and the SCCC decoder have been implemented entirely on the GPU with the input data that are moved to GPU memory before entering the back end and are moved back to the CPU (to be processed at the output) only at the end of the chain.  
Specifically, the demapper block aims to transform the constellation symbols, corrected by the demodulator blocks, into soft bits represented as LLRs. Then, the SCCC decoder block eventually corrects transmission bit errors, providing the correct information bits. Figure 5 shows the architecture of the implemented back end, with a focus on the internal architecture of the SCCC decoder.  
A detailed description of the development of the two back-end blocks (i.e., demapper and decoder) is reported in [15]. Here, an overview of the implementation choices is given to introduce the performance evaluation carried out in the next section.  
Figure 4: Implemented Front-End Architecture.
## 5 Implementation and Evaluation
### Results
#### 5.2.4 Interoperability  
Figure 6 shows the ontology alignment distribution across all edge servers. The result indicated that 95% of the data fields were aligned, proving that the proposed ontology is robust enough to handle heterogeneous datasets. Only 3% of the fields are unaligned, while 2% of the fields are partially aligned, which indicates slight differences in schema mapping or metadata errors. These results also demonstrate that the ontology can be integrated seamlessly into the decentralized systems and further support the effectiveness of this approach in reaching semantic consistency. A better standardization of metadata might decrease the percentage of unaligned fields.  
Figure 4: Global accuracy vs. number of edge servers (m).  
Figure 5: Convergence time in relation to server-specific dataset size.  
Table 3 shows a comprehensive analysis of the ontology alignment rate in different application domains. Traffic monitoring has the highest alignment rate, which is 97%, due to its consistent and well-structured data schemas. Parking management and environmental sensing rank the second and third with alignment rates of 93% and 94%, respectively. These marginally lower rates are explained by sporadic problems like inadequate metadata or mismatched units. While there are minor issues, the total alignment rate across all domains is excellent and thus very promising regarding the adaptability and resilience of the proposed ontology. These alignments could be further improved by making data formats more standardized and improving the quality of information.  
The local and global accuracy of the system before and after ontology updates are compared in Table 4. While the range of local accuracy tightens from 81.2 to 87.5% to 80.9-87.2%, the global accuracy decreased slightly from 89.4% to 89.1%. With this minor variation, it simply proves that some new attributes get successfully added inside the ontology in which the systems do not contribute any serious diminishment in performance. It is likely that the new data fields bring in added complexity, leading to a slight deterioration in the performance. On the whole, all these results testify to how good the proposed system is in view of the changed ontologies.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Ontology Version** & **Global Accuracy (\%)** & **Local Accuracy Range (\%)** \\ \hline Base Ontology & 89.4 & 81.2–87.5 \\ Updated Ontology & 89.1 & 80.9–87.2 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Accuracy impact of ontology updates.  
Figure 6: Data alignment to ontology.
###### Abstract  
In this study, the contents and associated soil properties of 6 metal elements (Pb, As, Cu, Zn, Ni, Cr) were measured in 63 topsoil samples in the affected areas of a typical non-ferrous metal slag field in Huili City, Sichuan Province, China. The associated soil properties of the 6 metals include Ammonium Nitrogen (NH\({}_{4}^{+}\)-N), Nitrate (NO\({}_{3}^{-}\)-N), Available Phosphorus (AP), Available Potassium (AK), Electrical Conductivity (EC), Cation Exchange Capacity (CEC), Soil Water Content (SWC), and pH. Multivariate statistics-spatial analysis-soil pollution comprehensive evaluation method was used to quantify the environmental pollution degree of heavy metals in the topsoil and divided (zone) the slag field based on the degree of pollution. Pearson correlation analysis and positive matrix factorization (PMF) were used to identify and quantitatively analyze pollution sources and their contributions. The results show that the average contents of Pb, As, Cu, Zn, Ni, and Cr were 13.27, 19.87, 6.91, 50.55, 25.06, and 77.71 mg\(\cdot\)kg\({}^{-1}\), respectively. Nemerow comprehensive evaluation results showed that the sites with Slight Pollution and Mild Pollution accounted for 26.98% and 3.17% of the total sampling sites, respectively. Approximately 70% of the sampling sites in the study area had no heavy metal pollution in the soil. Sites with No Pollution or Slight Pollution were mainly distributed in the forest areas with vegetation coverage, while sites with Moderate Pollution or Heavy Pollution were mainly distributed in crop planting areas and areas near slag fields. PMF model revealed four pollution sources: natural sources, mixed industrial and transportation sources, agricultural sources, and industrial river water. These results will provide theoretical references for the utilization and treatment of heavy metal-contaminated soil around the slag field in the dry-hot valley.  
dry-hot valley; heavy metals; soil; spatial distribution; source analysis Article
# Laser Inter-Satellite Link Visibility and Topology Optimization for Mega Constellation
###### Abstract
As such, this paper explores the visibility law of the interstellar link layer and proposes connection strategies for characterization and construction of scalable and connected intra-layer topologies for spatial information network topologies utilizing Starlink constellation as an example. The remaining sections of this paper are structured as follows: In Section 2, an overview of Free-space optics is presented along with the Starlink constellation configuration plan. Section 3 describes the universal geometric approach for optimal inter-satellite visibility. Section 4 reveals the simulation results using the proposed strategy and the variation laws. Finally, this work is concluded in Section 5.
## 2 Materials and Methods
### Assessment of Antioxidant Activity  
Antioxidant activity was determined using the 2,2-diphenyl-1-picrylhydrail (DPPH\({}^{\bullet}\)) and 2,2\({}^{\prime}\)-azino-bis 3-ethylbenzothazoline-6-sulfonic acid (ABTS\({}^{\bullet+}\)) methods. Ethanol at 80% was used for sample preparation. The results are expressed as \(\mu\)M of Trolox equivalents (TE)/g dry weight. The DPPH\({}^{\bullet}\) assay was performed in accordance with [PERSON] et al. [20]. Briefly, 0.3 mL of the sample was mixed with 2.7 mL of DPPH\({}^{\bullet}\) (\(6\times 10^{-5}\) M). The mixture was left in the dark for 1 h at 4 \({}^{\circ}\)C; then, the absorbance was determined at 517 nm. The ABTS\({}^{\bullet+}\) assay was performed following the method of [PERSON] et al. [21]. The ABTS\({}^{\bullet+}\) radical was produced by mixing 7 mM ABTS\({}^{\bullet+}\) solution with 10 mL of 2.45 mM potassium persulfate in complete darkness for 16 h with constant agitation. The radical ABTS\({}^{\bullet+}\) was diluted in 80% ethanol, reaching an absorbance value of 0.7 \(\pm\) 0.02 at 734 nm. Later, 3.9 mL of diluted ABTS\({}^{\bullet+}\) radical was taken and mixed with 0.1 mL of the sample, and subsequently left for 6 min in the dark. The absorbance of the mixture at 734 nm was determined.
###### Abstract  
The identification of tiny objects via single-frame infrared is a significant challenge in computer vision, primarily due to large variances in target dimensions, overcrowded backgrounds, suboptimal signal-to-noise ratios, the propensity of bounding box regression to vary with target size, and potential partial occlusion scenarios. Addressing these challenges, we propose a study network for enhancing features in the infrared detection of small targets utilizing multi-scale attention. In particular, the introduction of the Iterative Attentional Feature Fusion (iAFF) module at the detection network's neck aims to tackle the issue of minor target features being overshadowed in the process of cross-scale feature fusion. Additionally, we present the Occlusion-Aware Attention Module (OAAM), which demonstrates greater tolerance for target localization errors in regions where local features are missing due to partial occlusion. By combining the scale and spatial attention mechanisms of the Dynamic Head, our approach adaptively learns the relative importance of different semantic layers. Furthermore, the integration of Normalized Wasserstein-Gaussian Distance (NWD) aims to tackle the convergence issues associated with the increased sensitivity of bounding box regression in identifying minor infrared targets. For assessing our technique's efficiency, we present a novel benchmark dataset, IRMT-UAV, noted for its considerable discrepancies in target size, intricate backdrops, and substantial variations in the signal-to-noise ratio. The outcomes of our experiments using the public IRSTD-1k dataset and the internally developed IRMT-UAV dataset reveal that our technique surpasses cutting-edge (SOTA) methods, with mAP50 enhancements of 1.4% and 4.9%, respectively, thus proving our method's efficiency and sturdiness.  
Keywords:infrared small target detection; feature fusion; bounding box regression; attention mechanism
## 3 Methods  
The structure of the methodology is as follows:  
* SCADA data from the target damaged wind turbine (Tar) and from a reference healthy wind turbine (Ref) were pre-processed as indicated in Section 2.
* Based on the Pearson correlation coefficient between the possible input variables and the output (power, currents, and voltages), features were selected.
* The features matrix was orthogonalized and reduced in dimension through PCA transformation.
* The reduced features matrix was fed as input to a support vector regression with Gaussian kernel.
* The fault incipience was individuated through the analysis of how the mismatch between model estimates and measurements changed.  
The structure of the method is summarized in Figure 2.  
In Sections 3.1 and 3.2, the principles of principal component analysis and support vector regression are briefly summarized; the expert reader can skip these subsections. In Section 3.3, the use of the models for fault diagnosis is described.
# Erythrocytes and Nanoparticles: New Therapeutic Systems
## 3 NPs and RBC
### RBC and Polymeric NPs  
Similarly, polymeric NPs have been increasingly exploited for active delivery of therapeutic molecules [63; 64; 65].  
Correspondingly, the use of polymeric NPs covered with RBCs has shown different advantages. In a recent study [66], RBC-camouflaged poly(caprolactone) NPs loaded with paclitaxel (PTX) and co-administered with tripeptide Arg-Gly-Asp (iRGD, a tumor penetrating peptide) have shown good results in metastatic breast cancer treatment (Figure 3). The antineoplastic agent PTX was able to guarantee a strong regression of metastases, acting for a longer time thanks to the increase in blood circulation time. In addition, to ensure an effective drug delivery [55], the possibility of modifying the polymeric core with thermosensitive lipid dipalmitoylphosphatidylcholine (DPPC) was also investigated.  
Figure 3: Scheme of preparation of polymeric NPs coated with RBC membrane. Reproduced with permission from [66] (Copyright John Wiley & Sons, 2016).  
Figure 2: Preparation of gold NPs coated with RBC membrane. Reproduced with permission from [62] (Copyright John Wiley & Sons, 2013).  
Poly (lactide acid) (PLA) represents another biocompatible and biodegradable polymer used in the field of drug delivery [26; 67]. Recently, RBC membrane-coated PLA NPs loaded with doxorubicin for the treatment of acute myeloid leukemia have been explored [55]. These structures showed a sustained release of the drug compared with uncoated PEG-PLA NPs (with a release of 20% for RBC membrane-coated PLA NPs versus 40% for PEG-PLA NPs within 72 h).  
Another polymer widely used to perform NPs is the poly(D,L-lactide-co-glycolide), PLGA, which fulfils several requirements for drug or gene delivery. In a recent study, RBC membrane-coated PLGA NPs loaded with perfluorocarbons (PFC) [68] showed a decrease in tumor hypoxia thanks to the high solubility of PFC. Similarly, good properties of PLGA have found application in colorectal cancer treatment.  
In another work [69], cell proliferation of the gastrointestinal tract was inhibited after treatment with gambogic acid-loaded PLGA NPs, which were covered with RBC membrane. Mice treated with these NPs showed an increased survival time.  
Although polymeric NPs covered with RBCs offer interesting opportunities in nanomedicine, a recurrent drawback is related to the lack of targeting of solid tumors, due to the outside shell represented by RBC membranes. Thus, surface modifications of RBC membranes--or thermosensitive lipid DPPC insertion in the inner core of polymeric NPs--could represent appropriate strategies for enhancing the efficacy of drug targeting and release. This could be thanks to a more rapid destruction of the core and a better release of the therapeutic agent [70].
## 2 Results
### The Volatile Compositions of Freeze-Dried Teas from Different Cultivars  
Table S4 shows the volatile compositions of freeze-dried tea samples of different tea cultivars. A total of 66 volatiles were annotated and quantified in these freeze-dried tea samples, including 21 alcohols, 16 aldehydes, 6 ketones, 9 esters, 1 acid, and 13 miscellaneous. Similarly, alcohols were the major volatile compounds in freeze-dried tea samples (48.6%-63.6% of total volatiles). 'Chunyuz' contained the highest content of total alcohols, followed by 'Longjing43', 'Zhenong117', and 'Jinguanyin', whereas 'Chunyu1' contained the lowest content of total alcohols. The highest levels of total aldehydes and total esters were found in the freeze-dried samples of 'Longjing43', while the lowest contents of total aldehydes and total esters were respectively found in the freeze-dried samples of 'Jinguanyin' and 'Chunyu1'. Based on the clustering results (Figure S1), the freeze-dried samples of 'Longjing43' were discriminated from the other four cultivars, and the freeze-dried samples of 'Jinguanyin' and 'Chunyuz' had high similarity in the volatile profiles. Figure S2 shows the PCA result of freeze-dried samples of different tea cultivars based on the volatile compositions. The samples of the same cultivars were clustered well and discriminated from each other. The freeze-dried samples of 'Chunyuz' were characterized by high levels of alcohols, including 3,7-dimethylocta-1,6-dien-3-ol, heptan-2-ol, 2-[(1S)-4-methylcyclohex-3-en-1-yl]propan-2-ol, and (5E)-3,7-dimethylocta-1,5,7-trien-3-ol, while the freeze-dried samples of 'Jinguanyin' were characterized with (6E)-3,7,11-trimethyldodeca-1,6,10-trien-3-ol, (15,4R)-1,6-dimethyl-4-propan-2-yl-3,4,4a,7,8,8a-hexahhydro-2H-naphthalene-1-ol, and phenylmethanol.  
Figure 5: The PCA result of black tea samples from different tea cultivars based on the volatile compositions. (**A**) score plot; (**B**) loading plot. The number of replicates is equal to 3.
# Satellite Climate Data Records: Development, Applications, and Societal Benefits
###### Abstract  
This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs) in the context of transitioning research to operation (R2O). Requirements and critical procedures of producing various CDRs, including Fundamental CDRs (FCDRs), Thematic CDRs (TCDRs), Interim CDRs (ICDRs), and climate information records (CIRs) are discussed in detail, including radiance/reflectance and the essential climate variables (ECVs) of land, ocean, and atmosphere. Major international CDR initiatives, programs, and projects are summarized. Societal benefits of CDRs in various user sectors, including Agriculture, Forestry, Fisheries, Energy, Heath, Water, Transportation, and Tourism are also briefly discussed. The challenges and opportunities for CDR development, production and service are also addressed. It is essential to maintain credible CDR products by allowing free access to products and keeping the production process transparent by making source code and documentation available with the dataset.  
climate data record; satellite; remote sensing 20168333103390/rs80403310390/rs
## 5 Overview of 5G-Enabling Technologies
### Integration of Non-Terrestrial Networks (NTNs) with 5G
#### 5.5.3 NTN Architectures  
The adoption of NTN technology would significantly enhance 5G communication services when combined with the current terrestrial communication architecture. In a typical terrestrial cellular radio access network (RAN), standard communication components, such as the BS, UE, core network, and data network, are crucial for successful service delivery [149]. While the core network is charged with the responsibilities such as mobility management and session management, the data network focuses more on ensuring successful data transfer from one network access point to the other. These various network components play a complementary role in the total communication process. Thus, failure of a particular component may render the entire communication process useless. For typical NTN networks, the network architecture has been designed to provide enough redundancy to avoid network failures. Therefore, the integration of NTN components with the existing terrestrial infrastructures will play a crucial role in transforming communication processes. NTN integration can adopt either the physical (PHY) or network (NET) layer integration approach. While the former adopts existing terrestrial components for the NTN integration, the latter employs new radio access technologies (RATs). The NTN architecture may be any of the underlisted, depending on the non-terrestrial (NT) positioning [148; 149].  
* NT platform as a user: This architecture uses terrestrial infrastructure from an existing network to provide service for the NTN platform. Moreover, it might designate other satellites at higher altitudes to service satellites as users. Since the space satellites are served by the ground station (GS), this design enables communication to occur independently of ground stations, lowering the potential roundtrip delay.
* NT platform as a relay: Here, there may be two possibilities. The NTN platform can be used to provide backhauling services by acting as the link between the BS and the core network, which is typically secured by fiber optics. The NTN platform can alternatively serve as a relay in the connection between users on the ground and BS, thus providing direct access connectivity.
* NT platform as a BS: The BS functionalities can be incorporated into the flying component in this approach. This method is applicable only to scenarios where the NTN platform is equipped with a regenerative payload with enough processing capabilities.
* In addition to the three architecture models mentioned above, mixed architectures may combine several NT platforms to serve various functions [142]. A diagram showing the general architecture of NTN is presented in Figure 13.  
Figure 13: General Architecture of NTN.