esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Discussion and Conclusions
The dependability obtained by two different methods using the model are 59% and 57%, and based on historical data for a period of 6 years, the average value of dependability is 52.6%. This consistency underscores the model's effectiveness in capturing the real-world performance and dependability of the CCS systems. Moreover, the historical data's alignment with the model's output validates the use of fuzzy logic in predicting and improving dependability. This approach not only facilitates proactive maintenance and risk management but also supports strategic decision-making by providing a sophisticated understanding of system vulnerabilities. The adaptability of the model to different mining contexts and its reliance on expert knowledge further enhance its practicality and robustness. Ultimately, this model serves as a valuable tool for mining companies aiming to achieve greater sustainability, efficiency, and cost-effectiveness in their operations. Future research could explore the further refinement of this model by integrating it with advanced data analytics and machine learning techniques to enhance predictive accuracy and adaptability. Additionally, expanding the application of this model to other industries beyond mining could reveal broader insights and benefits, establishing it as a versatile tool for dependability assessment across various sectors. The continued evolution and validation of this model will ensure its relevance and efficacy in the ever-changing landscape of technical system management. Conceptualization, N.S. and M.G. ; methodology N.S., M.G. and P.M.; Writing--review and editing N.S., P.M., D.K., A.D. and M.G., supervision S.S., N.S. and M.G. All authors have read and agreed to the published version of the manuscript. This work was financially supported by the Ministry of Science, Technological Development and Innovation of the Republic of Serbia, Contract on realization and financing the scientific research work of the Mining and Metallurgy Institute Bor in 2024, Contract No. : 451-03-66/2024-03/200052. Not applicable. The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. Gratitude to Ministry of Science, Technological Development and Innovation of the Republic of Serbia; Mining and Metallurgy Institute Bor, Zeleni bulevar 35, Bor; Gacko Mine and Thermal Power Plant. The authors declare no conflict of interest. \begin{tabular}{c c c c c c c c c c c c c c} \hline \hline  
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# Geometrical Degrees of Freedom for Cellular Structures Generation: A New Classification Paradigm
## 2 Design and Geometrical Consideration
### RVE Variation Factors  
#### 2.4.1 RVE Variation Based Boundary Information  
Sometimes, the CS unit cells can vary based on the boundary of the design space; this is the case for conformal CSs. For conformal CSs, [PERSON] et al.'s approach consists of using conformal CSs to create a lightweight structure [30]. There are different advantages in using conformal CSs, most importantly, the non-uniformity can potentially increase the strength of the CS.  
Figure 10 shows the difference between a uniform and a conformal strut arrangement for a lattice structure. Other authors such as [PERSON] et al. [31] have written about conformal CSs; they suggested a novel method of generating conformal CSs by offsetting the surfaces of the design space and dividing the result into tetrahedra. The same method had been used by [PERSON] et al. [96]. Another interesting application of conformal CSs structures was showcased by [PERSON] et al. [97]. The team used CSs for body protection and investigated their ability to absorb energy from the impact. The conclusion was that foams are suitable for energy absorption use. They defined four types of what they call conformal methods. In their framework, only the swept and the meshed structures correspond to the definition of conformal CSs. This framework is also used in this paper. As the name \"conformal\" implies, in the trimmed method the struts are cut at the boundaries. The \"swept method\" requires two surfaces, often parallel, in which unit cells are swept in the normal direction between the two surfaces. The mesh method is more robust as it does not require any specific surface configuration, nor does it require them to be parallel. The main disadvantage of the trimmed method is that unit cells near the boundary are weakened. To remedy that, the same authors have suggested wrapping a skin around the design space. Furthermore, [PERSON] [98] discussed a conformal CS technique in his PhD thesis; the technique consists of slicing design spaces (in STL format), taking some of the resulting intersection points and then generating conformal structures by offsetting the original design space [98]. An accurate example is given by [PERSON] et al. [28]. Another example of the volume fraction varied between two boundaries is in the work by [PERSON] and [PERSON] [29]; a custom example of that case was made in Figure 11.  
Figure 9: RVE transformation of a syroid structure with scaled unit cells.
## 2 Test Matrix and Material Properties  
### Test Matrix  
A total of 180 specimens were designed and tested. Twenty-seven FCHC cylinders (which have a diameter of 100 mm and height of 200 mm) and three unconfined specimens of the same size were prepared for the quasi-static axial compression tests. Three types of FRPs, namely, the CFRP, GFRP, and AFRP, were adopted in the present study to investigate the effects of the FRP types and confinement stiffnesses. The FCHC specimens were applied with a 150-mm overlapping zone to prevent debonding failure and a one-layer CFRP strip, 20-mm high, was added at both ends to avoid end failure occurring there. Each test matrix had three nominal identical specimens, ensuring better reliability of the test results. A total of 150 FCHC cylinders (which have a diameter of 100 mm and height of 50 mm) of the same size were prepared to test the axial dynamic compressive behavior using SHPB equipment. All the specimens were made from the same batch of high-strength concrete with a design strength grade of 70 MPa. The mixing ratio of the concrete is reported in Table 1.
## 1 Introduction
Previous studies on the interaction of SWCNTs with albumin showed that laser irradiation of water-albumin dispersion leads to the chemical reaction between negatively charged amino acid residues Asp and Glu and nanotubes and, accordingly, to the formation of covalent bonds between them [16]. The structure of the nanocomposite, represented by alternating layers of CNTs with albumin and collagen, was selected based on the simulation results. Such a structure is energetically favorable. It is characterized by high stability and is achieved in a short period of time [17]. The results of the interaction of the nanocomposite components with each other are shown, as well as the analysis of the internal micro- and nanostructure of nanocomposites. Effects of the SWCNT type and concentration on the electrical conductivity of nanocomposites and the proliferation of heart cells in their structure are presented. The investigated properties of nanocomposites indicate the potential of their application as electrically conductive interfaces.
## 4 Results and Discussion
### Publication Years and Source Types  
According to our results in Figure 4, we obtained 193 studies after applying the inclusion and exclusion criteria, indicating that FL gained more interest after its introduction in 2016. Numerous publications have been dedicated to addressing issues related to FL. Figure 5 shows the distribution of the studies over the years. As shown in the figure, the selected studies that offer solutions to the non-IID data problem or provide communication efficiency started in 2019 and increased over the years. The studies aim to solve both challenges that started in 2020 and increased in recent years.  
Figure 4: Flow diagram of the selection results.  
Another research aspect of this work focuses on the selected studies' source types and publication venues. The selected studies have been published in four sources: conferences, journals, workshops, and symposiums, as shown in Figure 6. Most of the studies that addressed the non-IID data challenge were published at conferences (55% of the 93 selected studies). The studies that aim to provide efficient communication in federated learning and the studies that address both challenges were mainly published in journals (49% of the 74 selected studies and 54% of the 26 selected studies, respectively).  
Table 4 shows the most common publication venues that published more than one work of the selected studies that aimed to overcome the non-IID data problem. The table includes the types of publications, the number of studies, and the ratio of published studies to the total number of selected studies. In general, the selected studies were published in 77 publication venues. The leading conference is CVPR while the leading journal is IEEE Transactions on Parallel and Distributed Systems.  
Table 5 shows the most common publication venues that published more than one work of the selected studies that aimed to provide communication efficiency in FL. The table includes the types of publications, the number of studies, and the ratio of published studies to the total number of selected studies. In general, the selected studies were published in 60 publication venues. The leading journal is IEEE Internet of Things Journal, with seven publications. We omitted the table for the publication venues for the studies that address both challenges since all venues had only one study published, except for one journal (Journal of Systems Architecture) that published two works.  
Figure 5: Percentage of selected studies published over the years.  
Figure 6: Percentage of selected studies based on source types.
## 5 Results and Discussion
### Computational Complexity  
The elapsed signal processing time \(t_{S}\), representing the total time consumed by both the signal generation and the demodulation, is adopted as a metric to measure the computational complexity performance. In this study, 100, 150, and 200 DMT symbols each are performed in the transmissions. The value of \(t_{S}\) for various schemes are measured and then shown in Figure 11. The figure illustrates that the PTS and GCS schemes require the longest signal processing times, and the corresponding values of \(t_{S}\) increase dramatically with an increase in the number of DMT symbols used. In addition, many times of IFFT computations are required in the PTS scheme to find its optimum combination of phase factors. GCS also has more difficulty in seeking the optimum generated matrix and phase rotation vectors as greater numbers of subcarriers are used. In addition to these overhead loads, many more complex adder and multiplier have to be performed in both the PTS and the GCS, which consumes more hardware resources and requires more time. However, the \(t_{S}\) of the proposed scheme is shorter and changes very little as the number of symbols used increases, meaning that a lower computational complexity is obtained. The additional operations performed in the proposed  
Figure 10: Comparisons of BER performance.  
scheme consist entirely of \(\mathbf{H}_{M}\) spreading and \(\mathbf{H}_{M}^{-1}\) dispreading, which are both easily employed and convenient for hardware implementation.  
In summary, the proposed scheme is beneficial to the high-speed data transmission from the carefully performance investigation of the PAPR, the BER, the transmission rate, the PSD and the computational complexity.
### Problems and Challenges
#### 1.2.3 Location Awareness to Trigger a Real-Time Incident Response  
In order to implement a prompt and real-time incident response, the use GPS/GNSS and Geographical Information Systems (GIS) tools were required to locate the nearest healthcare service provider. One such tool is the Quantum GIS (QGIS), which is an open source software that can align and map geographical maps to GPS coordinates. In the Methods section it was used to create layers of information covering a geographical area; e.g., an area with contours for plains at same altitude, or areas in a map that have the same demographic information about healthcare centers in vicinity. This information was modelled as layers, and it was overlaid over the GPS coordinates. The tool can be used to load road and rail route information into the environment, and it can be used to identify the shortest path between two points in a network based on either distance or time [37].  
Various filtering mechanisms have been used to overcome the problems related to noise using stationary wavelet transforms, a Chebyshev second-order filter, and a Savitzky-Golay filter for signal conditioning. The algorithms were implemented in MATLAB, and could be ported to the embedded hardware. Comprehensive trauma scoring could be performed in real time, and the scores could be uploaded to the FHIR servers if required. The location awareness built into the kit using GPS modules could be used to locate the nearest healthcare center, and a shortest path could be calculated to reach the destination.
## 3 Experimental Verification
### Monitoring Performance Analysis  
#### 3.2.1 Monitoring Performance During the Climbing Scaffold Stationary Phase  
Monitoring data for 20 h on 29 June, when the climbing frame was station-ary, was selected for analysis. As shown in Figure 6b, at any given time, at least 15 Bei-Dou satellites were continuously tracked. Nevertheless, the number of visible satellites varied significantly over time, indicating fluctuations in satellite availability during the monitoring process.  
The corresponding outliers are removed, and the preprocessed data after correction can be used for filtering and smoothing. As shown in Figure 7, a comparison is made between the preprocessed data and the corresponding filtered data.  
Figure 5: Data before and after gross error elimination: (**a**) original monitoring data; and (**b**) after gross error elimination data.  
Figure 6: Original data quality status: (**a**) BeiDou satellite sky distribution map; and (**b**) number of satellites.  
As shown in Figure 7, the raw monitoring data exhibit significant high-frequency noise across all three directions, with noticeable gross errors at certain time points. These fluctuations lead to considerable data instability, affecting the real-time monitoring accuracy of the climbing scaffold system. Among them, the U direction (Figure 7c) demonstrates the lowest monitoring precision, with a fluctuation range of approximately [\(-\)0.08 m, 0.08 m], where high-frequency noise is particularly prominent. In contrast, the N direction (Figure 7b) shows the smallest fluctuation range, approximately [\(-\)0.02 m, 0.02 m], indicating the highest precision with relatively less noise. After applying filtering and data optimization techniques, high-frequency noise in all three directions was significantly suppressed, leading to a noticeable improvement in data smoothness. In the U direction, the fluctuation range effectively converged to [\(-\)0.04 m, 0.04 m], successfully eliminating abnormal spike noise. The optimized data not only preserve the original displacement trend but also mitigate high-frequency noise interference, resulting in a more stable dataset. The removal of spike anomalies through filtering ensures that the processed data better reflect the actual structural displacement patterns.  
To quantify the accuracy assessment, the mean value of a long-duration static dataset, during which the scaffold did not ascend, was taken as the ground truth. The root mean square errors (RMSEs) in the E, N, and U directions were then calculated. After applying filtering and other data optimization processes, the RMSEs in the E, N, and U directions were reduced by 51.4%, 45.5%, and 49.6%, respectively, compared to the original displacement sequence. Specific values are shown in Table 1:  
Figure 7: Comparison of monitoring data before and after processing on 29 June: (**a**) E direction; (**b**) N direction; and (**c**) U direction.
## 4 Results and Discussion
### Prediction of Optimal Planting Zones for Se-Rich Wheat, Rice, Rapeseed, and Tea
The superior prediction performance for rice and rapeseed may be attributed to the correlation analysis results: the selected indicators for these two crops had higher correlation coefficients (\(|r|>0.5\)) and were more distinct from other indicators, whereas the correlation coefficients for wheat were relatively low (\(|r|<0.4\)). The Se-rich planting zones delineated for rice, rapeseed, and tea using the BP-NN model provide planting recommendations for these crops in Xiaoyan Town, Nanzhang County. Se-rich rapeseed optimized planting zones were associated with soils containing high levels of Mo, Se, Mn, and Cu. Se-rich rice and tea-optimized planting zones were primarily distributed in areas underlain by Silurian strata, characterized by acidic soils. According to [PERSON] et al. (2024), Se-rich tea thrives in acidic soils because tea plants have a higher affinity for selenite. Se-rich rice, on the other hand, is suited to slightly acidic soils, likely due to the concentration of paddy fields in these regions [5]. Additionally, the mobility of Se species differs by soil type: selenate in alkaline soils is prone to leaching due to its high mobility, whereas selenite in acidic soils tends to accumulate due to its lower mobility [57]. Based on these findings, rapeseed is best planted in soils with high Mo, Se, and Mn content, while rice and tea are better suited for acidic soils. Appropriate fertilization strategies should also be implemented to reduce heavy metal content in crops and improve the yield and quality of Se-rich products.
# Check for special characters and punctuation
## 5 Discussion
### Practical Implications  
The demonstrated improvements in security and statistical preservation, combined with efficient processing, represent a significant advancement in practical steganographic applications. Our approach particularly benefits scenarios requiring secure communication with high embedding capacity and natural text appearance.
## 3 System Model
### IAB System Specifics  
In this study, we considered an IAB system operating in the in-band half-duplex mode. The former implies that the bandwidth \(B\) is utilized at both the access and backhaul links. Relying on the results of [10], we assume that the IAB-node and IAB-donor can simultaneously either transmit or receive on all their physical antennas. However, simultaneous transmission and reception are not feasible due to excessive interference. Semi-centralized coordination of resources was assumed, where the CU makes a decision on long-term resource allocation according to TDM operation to avoid violating half-duplex constraints.  
We assumed mmWave operation of the IAB system. The capacity of the access and backhaul links can be abstracted by utilizing [PERSON]'s law:  
\[C=B\log_{2}\left(1+\frac{P_{\text{T}}G_{\text{T}}G_{\text{R}}}{\text{PL}(d)N_ {0}B_{\text{PRB}}M_{\text{SF}}L}\right), \tag{1}\]  
where \(P_{\text{T}}\) is the emitted power, \(G_{\text{T}}\) and \(G_{\text{R}}\) are, respectively, the transmitter's and the receiver's antenna gains, \(N_{0}\) is the thermal noise power spectral density, \(B_{\text{PRB}}\) is the size of the physical resource block (PRB), \(M_{\text{SF}_{\text{[AB]}}}\backsim Norm(0,\sigma_{\text{SF}_{\text{L}}\text{ OS}/\text{SF}_{\text{L}}\text{OS}})\) is the slow fading, and \(L\) represents aggregated losses given, in decibels, by  
\[L_{\text{[AB]}}=M_{\text{I}}+F_{\text{N}}+L_{\text{C}} \tag{2}\]  
with \(M_{\text{I}}\) being the interference margin, \(F_{\text{N}}\) the noise figure, and \(L_{\text{C}}\) the cable losses.
## 2 Infrastructure, Instrumentation and Calibration Methods
### Calibration and Validation Methods
#### 2.2.5 Tandem Phase Cal/Val  
The ideal scenario to characterize the relative bias between two altimeters is to make them observe the same location of the Earth at the same time or a few seconds apart [21]. This is accomplished during a tandem phase, which many new satellite missions incorporate into their regular operations. During this phase, the newly launched satellite is placed on the same orbital track as a reference orbit. The two satellites fly in unison on the same orbit but separated only some seconds apart. For example, Sentinel-3B flew in tandem [22] with Sentinel-3A for four months (6-June-2018 to 16-October-2018) before being placed on its nominal orbit. Similarly, Jason-3 was flying in tandem with Jason-2 with a temporal distance of 80 s for six months (12-February-2016 to 2-October-2016). In [12], the PFAC-derived calibration results of the Jason-2/Jason-3 tandem phase have been presented. The present plan for the future Sentinel-6 will implement a 12-month tandem phase with Jason-3, where the two satellites will fly 30 s apart [23].  
This work (see Section 4) presents the relative calibration results from the Sentinel-3 A/B tandem phase. The following Section presents the PFAC's in-situ measurements, the models employed, and the processing strategies followed for the implementation of the aforementioned calibration methodologies for Sentinel-3A, Sentinel-3B and Jason-3 altimeters for absolute and relative calibration.
## 3 Results and Discussion
### Biological Characterization of the Scaffolds  
#### 3.7.1 Viability of Pre-Osteoblastic Cells within Scaffolds  
The viability and proliferation of the MC3T3-E1 pre-osteoblastic cells on the five scaffold compositions were quantitatively determined using the colorimetric PrestoBlue(r) viability assay during 2 and 7 days in cell culture according to the ISO 10993-5 (2009) standards (Figure 7). Cell viability values on each scaffold composition were statistically evaluated and compared with the Alg/MC/TMC control scaffold at each experimental time point. On day 2, the number of viable cells was comparable for all four modified scaffolds and the Alg/MC/TMC control, and no significant differences were observed. After 7 days of culture, all four modified scaffolds presented a similar effect on cell proliferation, proportional to the Alg/MC/TMC control (Figure 7). These results indicate that the incorporation of alginate-based bioinks with conventional glasses (100% SiO\({}_{2}\)) or bioactive glasses (70%Si-30%CaO) does not negatively impact the viability and proliferation of pre-osteoblastic cells, while an increase in the concentration appears to be associated with a significant increase in cell proliferation (\(p<0.01\)). A similarly strong cell adhesion and a high viability and proliferation increase from day 2 up to day 21 were observed in crosslinked alginate/chitosan scaffolds seeded with human nucleus pulposus cells and dental pulp stem cells, rendering alginate and chitosan suitable biomaterials for the fabrication of 3D porous scaffolds for bone and cartilage tissue engineering [42].  
Figure 6: SEM images of samples before (**a-e**) and after (**f–o**) immersion in 2 xSBF solution for 2 weeks.