esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Scientific Background
### Polycyclic Aromatic Hydrocarbons  
Polycyclic aromatic hydrocarbons (PAHs) are characterised by organic compounds with multiple aromatic rings with possibly functional groups attached to these rings. PAHs co-emitted with BC during incomplete combustion are believed to be trapped in micro porous structure of BC, due to the high affinity of PAHs for flat aromatic surface [124]. PAHs are colourless, white, or pale to yellow organic compounds. There are several routes through which PAHs enter the environment and they are often found as a mixture. PAHs are a group of several hundreds of chemically related compounds with different structures and toxicity. These compounds are comprised of numerous individual compounds having at least two condensed rings. PAHs are divided into two categories based upon their molecular weight--those with less than four rings are termed as low-molecular-weight compounds, while those with four or more rings are high-molecular-weight compounds. According [PERSON] et al. [125], the effect of PAHs on human health is primarily based on the duration and route of exposure and the relative toxicity of PAHs. Elevated systolic blood pressure and pulse pressure are substantially correlated with PAHs.  
Understanding the association between BC and PAHs is critical in order to determine their negative effects, transport and fate throughout the environment. BC is considered to be ubiquitous in the atmosphere and have a strong sorbtive power for organic pollutants such as POPs and PAHs. It has been revealed that the distribution of PAHs in different environmental sections is dependent upon BC distribution due to the strong sorption ability of BC for PAHs [126].  
PAHs are fully involved in the formation of soot particles (Figure 7) although the early stages of soot formation, namely inception and growth, are highly debated and central to many ongoing studies in combustion research [127; 128; 129]. The combustion process of fuel starts with the decomposition reactions of the fuel molecules, i.e., pyrolysis and oxidation, and subsequent recombination and cyclisation reactions lead to the formation of PAHs. Recent results [130] contribute to the understanding of soot formation.  
Four PAHs are particularly targeted in the legislation: benzo(a)pyrene, benzo(b)fluoranthene, benzo(k)fluoranthene and indeno(1,2,3-cd)pyrene (Aarhus Protocol on POPS). Benzo(a)pyrene and naphthalene contributed the most to the PAH carcinogenic potency of biomass-burning emissions according to [131].  
Figure 7: Soot formation pathways from fuel combustion adapted from several sources in the literature [127; 128; 129].
## 5 Conclusions  
All of the four different spent mushroom substrates (_P. eryngii_, _L. edodes_, _P. ostreatus_, and _A. bisporus_) evaluated in this work showed significantly higher removal of TPHs than the non-inoculated soil demonstrating the usefulness of these wastes in the remediation of contaminated soils with petroleum hydrocarbon. _A. bisporus_ and _P. eryngii_ clearly colonize the contaminated soil. However, the mere colonization of the soil did not assure high removal of TPHs since the inherent microbiota of the SMS and its interaction with the autochthonous soil microbiota are also important factors. The SMS of _A. bisporus_ was the most effective SMS for the bioremediation of contaminated soils with petroleum hydrocarbon. _L. edodes_ SMS reached high degradation of the heaviest aliphatic chains (>C\({}_{35}\)) and the aromatic chains >EC\({}_{12}\)-EC\({}_{16}\). SMS of _P. ostreatus_ was the most effective SMS for the degradation of the aliphatic chains >C10-C12 and aromatic chains EC\({}_{10}\)-EC\({}_{12}\). Finally, _P. eryngii_ SMS was only useful for the biodegradation of the light aliphatic chains >C\({}_{10}\)-C\({}_{12}\).  
This work demonstrates the feasibility of the bioremediation of contaminated soils with petroleum hydrocarbons using abundant agricultural waste such as SMS of different fungi. The re-use of SMS for this purpose promotes the circular economy and the Green Deal of the European Union reducing the environmental and climate footprint of the food system.  
Conceptualization, R.A.-H., C.G.-D. and E.E.; methodology, B.M. and N.B.; validation and formal analysis, R.A.-H., B.M. and N.B.; investigation, R.A.-H., N.B., C.G.-D. and E.E.; data curation, R.A.-H. and N.B.; writing--original draft preparation, R.A.-H. and C.G.-D.; writing--review and editing, R.A.-H., C.G.-D., B.M., L.D.-M. and E.E.; supervision, C.G.-D. and E.E.; project administration, E.E.; funding acquisition, E.E. and C.G.-D. All authors have read and agreed to the published version of the manuscript.  
This article is result of the European Union's LIFE Program under the grant contract number LIFE20 ENV/ES/000416.  
Not applicable.  
Data Availability Statement: The data presented in this study are available on request from the corresponding author.  
We thank the Technological Center for Mushroom Research in La Rioja (CTICH, La Rioja, Spain) to provide the spent mushroom substrates and the Centro de Investigaciones Energeticas, Medioambientales y Tecnologicas (CIEMAT, Madrid, Spain) for the analysis of the TPHs.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data and in the writing of the manuscript.
## 4 Study Case
### GSMS Data Collection Phase
#### 4.1.2 Label P2: Search Performance Phase  
**The search performance phase** collected initial sources from scientific article libraries' databases, including ISI Web of Science, IEEE, Scopus, and ACM. A rigorous and systematic procedure was employed [21], which started with a search string established based on the requirements of this paper. The aim was to determine if this search string was appropriate for achieving the desired outcome. To this end, a series of tests were conducted.  
This work applied different chains using the ISI Web of Science database to define the search string. The first attempt was to use long and complex chains, such as **((\"software development\" OR \"requirements engineering\" OR \"information systems\" OR \"computer systems\") & \"Grounded Theory\")**, which could lead to errors or exclude relevant topics [21]. The second attempt was to use short terms, such as **\"software,\" \"software development,\"** and **\"Grounded Theory.\"** This approach yielded more articles, as shown in Table 2. The first rows are related to terms associated with software; the following rows are about GT and the combination of the two terms.  
The combination was addressed by combining the two search strings **\"Grounded Theory\" & \"Software Development\"**, while excluding terms such as **\"requirement,\" \"design,\"** or **\"development.\"** This search yielded 197 articles, as shown in Table 2.
## 3 Results
### Pairwise Comparison Effects  
For the results of the pairwise comparisons in the post-examination, significant differences were also found at the hip, knee, and ankle joints, as shown in Figures 3 and 4. When considering the neutral shoes' impact on the hip joint, significant differences in extension angle during the final stance phase were observed at 83-100% (\(p\) = 0.006) in V1, 70-100% (\(p\) = 0.002) in V2, and 78-100% (\(p\) = 0.004) in V3. However, no significant differences were noted with the bionic shoes. Hip angle velocity showed significant differences in the neutral shoes at V1, V2, and V3, while significant differences for the bionic shoes were only observed at V3 compared to V1 and V2. The hip moment also exhibited significant differences, along with smaller values, during the final stance phase around 60-100% (\(p\) < 0.001) when comparing the bionic shoes to the neutral shoes at V1 and V2. Hip power showed significant differences in both the neutral shoes and bionic shoes at V1, V2, and V3. In terms of the knee joint, significant joint angle differences were displayed during the initial stance phase both in the neutral shoes and bionic shoes at V1, V2, and V3. Knee angle extension showed significant increases in the bionic shoes compared with the neutral shoes in the final stance phase around 65-100% (\(p\) < 0.001). The knee angle extension velocities were significantly different, showing faster velocities in the neutral shoes compared to the bionic shoes at 20-75% (\(p\) < 0.001) in V1 and 25-75% (\(p\) < 0.001) in V2. Both knee moment and knee power displayed noteworthy disparities in the context of shoe results around the 40% (\(p\) < 0.001) stance phase. Notably, the bionic shoes exhibited larger values compared to the neutral shoes. In terms of the ankle joint, ankle angle velocity showed significant differences in the final stance phase around 80-100% (\(p\) < 0.001) at all velocities except for V2 versus V3 in the bionic shoes. Significant distinctions were observed in both ankle moment and ankle power across all velocities. Notably, the data from the bionic shoesrevealed a greater number of differences, particularly during the middle and final stance phases around 50-80% (\(p<0.001\)). In the final stance phase around 60-100% (\(p<0.001\)), ankle moment and ankle power showed a larger value in the bionic shoes compared with the neutral shoes.  
Figure 3: Lower limb joint angle and angle velocity waveforms of mean and standard deviation over the stance phase for neutral shoes and bionic shoes. The shaded red rectangles represent the main effects of the velocities (\(p<0.05\)). The shaded blue rectangles represent the main effects of the shoes (\(p<0.05\)). At the bottom of the figure, the gray horizontal bars represent interaction effects (\(p<0.05\)), the red horizontal bars represent pairwise comparison effects in terms of the velocities (\(p<0.05\)), and the blue horizontal bars represent pairwise comparison effects in terms of the shoes (\(p<0.05\)).
# A Study of the Thermodynamic Properties of Nd-C and Ce-C TRISO Fission Product Binary Systems
## 2 Materials and Methods  
### Sample Preparation  
Neodymium carbide and cerium carbide samples were fabricated at the University of Texas at San Antonio (UTSA) (San Antonio, TX, USA) with a customized Tri-Arc Melt Furnace, Model 5 TA, from Centorr Vacuum Industries. Nd and Ce foil with 99.9% purity (sourced from Alfa Aesar, Haverhill, MA, USA) were refined through a melt-clean-remelt process to remove impurities. These were reacted with graphite under an inert, ultra-high purity argon environment to produce four Nd-C and two Ce-C samples of various molar compositions, which were shipped to Ontario Tech University (OTU) and then stored in an argon environment to prevent potential oxidation. A more thorough description of the fabrication process is described by [PERSON] et al. (2014). The planned crucibles for the DSC experiments had a measured inner diameter of 5.95 mm and inner height of 3.20 mm. However, the fabricated samples were too large to fit into the volume, having a diameter of approximately 8 mm and height of 4 mm. The samples were resized at OTU within an argon-filled glovebox to fit within the measurement crucibles.
# A Tiered Control Plane Model for Service Function Chaining Isolation
## 4 Services in the Architecture
### Service Components on the Orchestration Plane  
The end-user orders a set of services (VNFs) from the ISP in a web portal, and while being unaware of the data-center location of each service, he wants to ensure that integrity and confidentiality are preserved in the SFC between the VNFs. The end-user requires both checking if the infrastructure is capable of delivering the services and also placing an order of service provisioning. This implies that the end-user can do four new types of service requests provided by the orchestration layer with respect to isolation and encryption: 1--Request of encryption capabilities per VL, 2--Request of isolation capabilities per SFC, 3--Request of provisioning an SFC with encrypted links and 4--Request of provisioning transitive encryption services to enable VNF bypass in the SFC (Figure 9).  
These simplified end-user services are utilized in an application such as a webshop in the Operation Support System (OSS) domain (Figure 9). The practical result of such service requests ends up in a list of VNFs connected to an SFC, which also includes an inner SFC specification. These are called Network Service Descriptors (NSD) [19] and are stored in a repository. This architecture focuses on hierarchical SFCs and encryption services, assuming minimal modifications of the ETSI model in the form of NSD extensions. However, modifications of the NSDs are required in order to support a description of encryption services (encrypting VNFs). Additionally, an extension of the NSD describing the VNF Forwarding Graph Descriptor (VNFFGD) is needed, in order to support hierarchical SFC descriptors. A type extension of the Virtual Link Descriptor (VLD) is also needed to describe inner Encryption Links for Tier 3. The orchestration application provisions the VNFs towards all relevant Service Providers, as well as provisioning backup VNFs for redundancy, while it distributes the relevant identifiers during the VNF instantiation. Furthermore, the control plane is responsible for selecting what VNF instances will participate in the SFC. The necessary NSD extensions are described in the Protocol and Interface section (Section 5). In summary, the orchestrator maintains the following functionality:  
* Interpret end-user requests of VNFs and SFC in order to create the NSDs,
* Calculate where it is most efficient to run the VNFs,
* Consider any VNF constraints,
* Verify that it exists a Transport Link between every Service Provider that participates in the SFC,
* Ensures that the encrypting VNFs are co-located with normal VNF during provisioning,
* Provision VNFs at all Service Providers,
* Generate a pass-phrase (PSK) per VNF instance to enable authorization of the VNFs. When the VNF is provisioned, this key is submitted as a VNF application parameter.
# Developing a Building Fire Information Management System Based on 3D Object Visualization
## 5 Prototype Development and Scenario Analysis  
### Prototype Implementation of the BFIMS  
The BFIMS consists of four modules: (1) \"Management\" module for setting by type; (2) \"object\" module for object data input; (3) \"information\" module; and (4) \"report\" module for object data output (see Figure 4a). The BFIMS uses graphical elements to convey information to end users instantly (see Figure 4b). In the object module, a particular type is set as a metadata for grouping and visualizing individual object information. The type is underlined with the values used in JSON (lines 34-49 in Figure 5) by designating the name and describing the type and the colors for visual representation of the grouped objects (lines 7-23 in Figure 5). It is grouped by the type list in the checkbox format. The type consists of fire risk elements and resource elements as depicted in Figure 4.  
Figure 4: Examples of the BFIMS screenshot. (**a**) Graphic User Interface (GUI) module icons in BFIMS (1: Management; 2: Object; 3: Information; 4: Report); (**b**) GUI screenshots in BFIMS (left: type input; center: type selection; right: data input); (**c**) Fire facilities data derived from BFIMSFigure 5: System code: data input.  
Typically, the object model created in Sketchup can be stored such that each component has its own location and physical information, but there are limits to the storage of user-recognizable location data and maintenance information. In the \"object\" module, the user creates a particular object as a Sketchup component, and then sets the category to which each object belongs by selecting the type defined in the \"management\" module as well as the relevant attribute data, such as location and maintenance history data (lines 16-20 in Figure 6). Objects with the selected type can be visualized in the color designated by selecting the check box in the type list, and are classified by type (Figure 7a). In addition, objects that are distinguished by color can be visualized in a 3D environment, which can show instant spatial relationships and their locations.  
Figure 6: System code: Object data input.  
The \"information\" module is used to display the defined object information in a tabular form in a single unit (Figure 7b). Moreover, a method exists to display multiple grouped object information by outputting the attribute data pertaining to the objects dependent on the selected types using the list  
Figure 7: BFIMS implementation: (**a**) Object visualization; (**b**) single object data output; and (**c**) multiple grouped objects data output.  
dialog in the \"management\" module (Figure 7c). In the \"report\" module, attribute data of all objects stored in the \"object\" module can be generated in a spreadsheet format. They can be exported to an ExcelTM file and saved for additional analysis in the future.
## 8 Challenges and Future Directions
### Future Directions
#### 8.2.6 Privacy Policies and Security  
It is important to implement detailed privacy policies such as a strong user consent mechanism, data anonymisation where possible, and a clear data usage and storage policy. Users should be clearly informed about what data will be collected, how they will be used, and how they will be stored. This will ensure the protection of user data. There should also be room for users to opt out of data collection for specific applications. Robust security measures must be in place to protect the user data collected and ensure there is no data breach.
## 3 Results
### Performance Testing and Analysis of Soil Electrical Conductivity Prototype
#### 3.2.4 Comparative Performance Tests  
To assess the potential of the prototype as a replacement for commercially available foreign products, comparative performance tests were conducted. Six soil samples with varying conductivity gradients were prepared. The widely recognized 2265 FS portable soil electrical conductivity meter, produced by Spectrum, was selected as the benchmark instrument. This meter features the following three measurement ranges: 0.0-200.0 \(\upmu\)S/cm, 200-2000 \(\upmu\)S/cm, and 2.00-200.00 mS/cm, with corresponding resolutions of 0.1 \(\upmu\)S/cm, 1 \(\upmu\)S/cm, and 0.01 mS/cm. Its measurement accuracy is 1.0% of the full\(-\)scale range for the selected gear. The conductivity of the six soil samples was measured using both the prototype and the Spectrum 2265 FS meter at 25 \({}^{\circ}\)C. The comparative test results are presented in Figure 12.  
Figure 11: Experiment results of the radial sensitivity range of the soil electrical conductivity prototype.  
Figure 10: Dynamic response curve of soil electrical conductivity prototype.  
The specific data, error ranges and prices of the comparison tests are shown in Tables 4 and 5.  
As illustrated in Figure 12, the linear fitting curve for the measurements obtained from both the prototype and the 2265 FS sensor is (y = 1.10176x \(-\) 16.808), with a coefficient of determination (R\({}^{2}\)) of 0.9995. The absolute error ranges from \(-\)61.40 uS/cm to 23.90 uS/cm, while the relative error ranges from \(-\)1.94% to 1.86%. These results demonstrate that the accuracy of the prototype is comparable to that of the 2265 FS sensor, indicating that its performance is effectively on par with the commercial standard.
# Deployment Protection for Interference of 5G Base Stations with Aeronautical Radio Altimeters
## 4 Results and Discussion
### Summary  
To present the results more clearly, we compare the radius of all prohibited zones in Tables 4 and 5.  
The radius of the horizontal prohibited zone increases with altitude AGL. Without considering the antenna's vertical scan angle and aircraft attitude, for omnidirectional antennas, \(R_{\rm 6 dB}\) increases from 0.4 km to 3.2 km. For beamforming antennas, \(R_{\rm 6 dB}\) increases from 1.4 km to 3.4 km. A 10\({}^{\circ}\), the vertical scan angle can increase the protection radius by 0.1 km  
Figure 24: Relationship between angle shutoff and \(d\).  
Figure 25: Relationship between angle shutoff and \(\varphi_{v}\). (**a**) \(d=1\) km. (**b**) \(d=3\) km. (**c**) \(d=5\) km.  
to 2.5 km. A 30\({}^{\circ}\) aircraft pitch\(\backslash\)roll angle can further increase the radius by 1.3 km to 3.7 km. Additionally, the ICAO 6 dB also increases the prohibited zone radius by 0.2 km to 2 km.  
The radius of the vertical prohibited zone also increases with altitude AGL. In addition to providing the radius on the ground, the radius in the air is also provided. For omnidirectional antennas, the \(R_{\text{6 dB}}\) on the ground ranges from 0.2 km to 3.2 km. The \(R_{\text{6 dB}}\) in the air ranges from 0.2 km to 2.6 km. For beamforming antennas, the \(R_{\text{6 dB}}\) on the ground ranges from 0.8 km to 3.4 km, while the \(R_{\text{6 dB}}\) in the air ranges from 0.2 km to 6.1 km. A 10\({}^{\circ}\) vertical scan angle can increase the radius by 0.1 km to 2.7 km. A 30\({}^{\circ}\) aircraft pitch\(\backslash\)roll angle can further increase the radius by 1.3 km to 3.7 km. Additionally, the ICAO 6 dB also increases the prohibited zone radius by 0 km to 2 km.  
Regarding the power control method, for omnidirectional antennas, a 1 dB decrease in Tx power within the horizontal prohibited zone increases the deployable base station positions by 10.8%. For beamforming antennas (\(\theta=10^{\circ}\), \(\alpha\backslash\beta=30^{\circ}\)), a 1 dB decrease in Tx power increases the deployable base station positions by 7.5%. In the vertical prohibited zone, the results are 5.8% and 3.1%. As the Tx power continues to decrease, the incremental increase gradually diminishes.  
Regarding the angle shuffoff method, under the given distance and angle, most base stations only need to shut off some angles to avoid interference. As the distance increases, the required angle shutoff decreases. At 1 km, it is 140\({}^{\circ}\), reducing to 50\({}^{\circ}\) at 3 km and merely 25\({}^{\circ}\) at 5 km. However, with an increase in base station height (the increase in \(\varphi_{\varphi}\)), the required angle shutoff increases at a given distance. It is 145\({}^{\circ}\) at 1 km, 93\({}^{\circ}\) at 3 km, and 45\({}^{\circ}\) at 5 km.
## 3 Results
### Changes of Curvature  
The average curvature angle as per [PERSON]'s classification in own modification before mechanical preparation did not significantly differ from 45\({}^{\circ}\). The biggest average change in canals curvature was observed in WO group (7.0+/\(-\)2.87), the lowest in K group (1.30+/\(-\)1.49) (Table 3).  
The data analysis proved that the average curvature angle before canal preparation is different from after it was instrumented in each group. Highly statistically significant differences were observed in WO, MT, and PM groups (\(p\) < 0.0001) while in K group statistically significant (\(p\) < 0.05) (Table 3). The NIR test showed a statistically significant difference in  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Endodontic Instrument Type**} & \multicolumn{5}{c}{**Working Length Changes (mm)**} \\ \cline{2-6}  & **Min** & **Max** & **Me** & **Q1** & **Q3** \\ \hline K & 0.0000 & 0.2500 & 0.0000 & 0.0000 & 0.2500 \\ PN & 0.0000 & 0.5000 & 0.0000 & 0.0000 & 0.2500 \\ MT & 0.0000 & 0.5000 & 0.0000 & 0.0000 & 0.2500 \\ WO & 0.0000 & 0.5000 & 0.0000 & 0.0000 & 0.0000 \\ \hline \hline \end{tabular} \(p\) = 0.9035.  
\end{table}
Table 2: Comparison of working length changes.  
Figure 6: Amount of resin removed in particular measurement points in groups: (**a**) K, (**b**) MT, (**c**) PN, (**d**) WO.  
changes of curvature angle only between WaveOne and Mtwo instruments. Comparison of rest of the examined instruments showed no statistically significant differences (Table 3)  
In each group, the average length of the canals' curvature before the mechanical preparation is different from the one after the preparation. That difference is highly statistically significant (\(p<0.05\)) (Table 4). Comparative analysis of the instruments showed statistically significant differences in curvature length changes only while comparing WO and MT groups.