esa-sceva/satcom-chunk-collection huggingface dataset:
# Novel Design of Expandable Spinal Cage for Efficient Lumbar Spine Fusion Operation
## 2 Design of an Expandable Cage
### Link Mechanism for Height Extension  
The height expansion of the spinal cage using a link mechanism is achieved through linkage mechanism, as shown in Figure 1. This mechanism consists of a total of five joints and connecting links. Height adjustment is accomplished by horizontally shifting the position of Joint 1, while joints 2 and 3 remain fixed throughout process. Horizontal displacement of Joint 1 results in a corresponding change in height of Joint 4, which can be mathematically expressed. The defining position of Joint 1 as relative horizontal distance from fixed Joint 2 as depicted in Figure 1, height H of Joint 4 can be represented by the following equation.  
\[H=L_{2}\text{sin}\;(cos^{-1}\frac{X_{1}^{2}+L_{2}^{2}-L_{1}^{2}}{2x_{1}L_{2}}) \tag{1}\]  
Equation (1) can be used to determine maximum and minimum height range of Joint 4 according to the displacement range of Joint 1. This height range, depending on displacement, provides crucial information for optimizing design to ensure sufficient height expansion.  
In addition to the height variation of Joint 4, changes in position of Joint 1 also affect height of Joint 5. Typically, the height variation of Joint 5 is expressed by a highly complex equation; however, it can be simplified under certain conditions. Specifically, as illustrated in Figure 1, when linkage lengths satisfy the condition that lengths \(L_{2}\) and \(L_{3}\) are equal and lengths \(L_{4}\) and \(X_{2}\) form a parallelogram structure, the height of Joint 5 always equals the height of Joint 4. A significant advantage of this parallelogram linkage structure is that the angle between the upper and lower surfaces remains unchanged during height adjustment, effectively achieving independent control of height and angle, one of the primary goals established in this study.  
Figure 1: Link mechanism for height extension.
# New Space Engineering Design: Characterization of Key Drivers
## 3 Results and Discussion
### Toward Practical Application in Early Design  
The results of this study provide a structured knowledge base that aligns with the latest trends and directions of the New Space sector. By identifying key design drivers, associated enablers, and a clear categorization logic, this research translates the complexity of this landscape into a critically assessed reference, supporting conceptual clarity and system-level thinking, particularly during the early stages of development.  
This foundation is solid yet accessible to organizations of different sizes and capabilities. In practice, it can support the creation of early-stage design frameworks that aim to foster innovation in New Space systems. Within the typical engineering design process, it informs the phase of product planning, which precedes conceptual design [45].  
Such frameworks may include checklists, roadmaps, prioritization schemes, benchmarking criteria, or workflows for identifying requirements. These can help guide early design iterations and assist companies still building their internal processes. Both established companies aiming to stay aligned with sector evolution and small enterprises or startups typically operating with limited resources can benefit from using this structure to maintain competitiveness in a rapidly evolving market.  
Systems and design engineers may use the results to identify key focus areas, align decisions with market and technological directions, and evaluate tradeoffs under context-specific constraints. The interdisciplinary nature of these findings also allows for the incorporation of broader considerations (e.g., cost and sustainability) and for updating existing requirement sets to meet new external constraints. Depending on the strategic goals and use cases, users may be guided toward appropriate development approaches, such as Design for Additive Manufacturing or Design for Environment.  
Overall, these results can support the identification of innovation pathways and enable sustainable, forward-looking design strategies, particularly during the early stages of product planning.
## 5 Optimization Results and Discussion
[47] to increase TRP production in their bench-scale FBR. They performed genetic modifications of the TRP-producing \"wild\" strain S028. Basically, \"they removed the PTS import-system of GLC, by replacing it with a more effective one based on the galactose permease/glucokinase (GalP/Glk) uptake system, by modulating the gene expression of GalP/Glk. The resulting T5 strain showed an increase in the specific TRP production rate in a non-optimal FBR by 52.93% compared to the initial strain\" [47], and by ca. 70% if the FBR used was operated optimally (this paper analysis). * Due to its complex modular structure, the results obtained with the HSMDM of this paper reveal the close link between the cell key metabolites and the FBR operating
conditions. Thus, this hybrid model is complex enough to adequately represent the dynamics of the FBR state variables (i.e., the biomass growth, the GLC depletion, and the excreted TRP and PYR in the bulk phase), as well as the dynamics of the cell key species involved in the concerned reaction pathway modules, i.e., (a) glycolysis, (b) ATP recovery system, and (c) TRP-operon expression. * The paper proves that the HSMDM is also suitable to be used in solving multi-objective engineering problems, for instance by using the Pareto-optimal front technique.
## 2 Material and Methods
### Data Processing and Statistical Analysis  
In this study, data are presented as the mean \(\pm\) standard deviation, derived from triplicate analyses, to ensure reliability of results. To investigate the relationships and variations within plant organs, were applied different statistical methods to our dataset. The results from GC-MS were treated as operational taxonomic units (OTUs) and transformed using the arcsine square root method. These data were then converted into a matrix using percentage area (%), excluding unidentified substances or those with less than 1% content [34]. Subsequently, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) was applied to examine similarities among OTUs, based on the class and distribution of chemical compounds in different organs and phases. For dendrogram generation, we used Euclidean distances with the Unweighted Pair Group Method with Arithmetic Mean (UPGMA) [34]. Additionally, the following analyses were conducted: I--variations between the chemical compositions of organs; II--chemical diversity among different compartments; III--variations in micromolecular evaluation indices and diversity. To compare the obtained means, analysis of variance (ANOVA) was employed using Statistica software, version 13 (StartSoft Inc., Tulsa, OK, USA). Means were subjected to [PERSON]'s test at a significance level of 5% probability [35].
# A Controlled-Environment Quality Assessment of Android GNSS Raw Measurements
## 2 GNSS Positioning and Basic Performance of Android Smartphones
### Positioning and Navigation with Android Smartphones  
Following the release of raw GNSS measurements in Android smartphones, it became possible to directly compute pseudoranges and, in turn, to solve the trilateration problem employing advanced and customized techniques [6]. Raw GNSS data can be obtained from any supported phone through the GNSSLogger App released by Google, or similar available apps. Subsequently, raw data can be postprocessed by implementing custom software or through the official Google tool. In this work, the GNSSLogger App and the Google 'gps-measurement-tools-master' MATLAB(r) open source Toolbox, both available from the Android Developers website [15] have been used. The postprocessing tool was forked and upgraded to account for ionospheric and tropospheric delay corrections and to compute carrier-smoothed solutions.
# Thermal Characteristics Study of the Bump Foil Thrust Gas Bearing
## 2 Numerical Simulation Research  
The aerodynamic bump foil thrust bearing mainly consists of three parts: the top foil is used to provide lubricating surface; the bump foil plays the role of elastic support; the bearing housing is applied to fix the top foil and the bump foil. The structure of bump foil thrust gas bearing is shown in Figure 1.  
As shown in Figure 2, the entire structural system is divided into six areas along the gas film thickness direction to describe the heat flow. From area A to area G, heat is generated inside the gas film (area C), and one part of the heat is transferred to the ambient or cooling air (area A) through the thrust disc (area B). Another part is transferred to the top foil (area D), and then to the bearing housing (area F) by heat conduction or heat convection (area E) and finally transferred to the open air (area G). When there is cooling air passing through the bump foil channel, only a small part of the heat is transferred to the surrounding air through the bump foil and bearing sleeve.  
Figure 1: Structure of thrust bump foil gas bearing.  
Figure 2: Heat flow transfer model.
# Linear Algorithms for Radioelectric Spectrum Forecast
## 2 Theory and Background
### Generalized Autoregressive Conditional Heteroskedastic Algorithm  
An important number of models, most of which have the property that conditional variance depends on past, have been proposed for capturing special data characteristics. Algorithms commonly used are those with autoregressive conditional heteroskedasticity (ARCH) introduced in [27] and generalized ARCH (GARCH) given by [28]. Modeling ARCH-GARCH considers conditional error variance as a compression function of the past of the series.  
ARCH modeling usually requires a great number of lags (\(q\)), and therefore a great number of parameters. This might yield a model with a great number of parameters, which is in opposition to the parsimony principle. This fact drives many times to difficulties when using the model to describe data in an adequate way. On the contrary, a GARCH model uses an inferior quantity of parameters, which makes it preferable to an ARCH model [29; 30; 31]. In this paper, the GARCH algorithm with order \(p\geq 0\) and \(q\geq 0\) for the discrete-time stochastic process \(r_{t}\) is expressed in Equations (4) and (5)  
\[r_{t}=\mu+c,\ \varepsilon_{t}\sim N\left(0,1\right) \tag{4}\]  
\[\sigma_{t}^{2}=\alpha_{0}+\sum_{i=1}^{q}\alpha_{i}r_{t-i}^{2}+\sum_{j=1}^{p} \beta_{j}\sigma_{t-j}^{2} \tag{5}\]  
where \(\varepsilon_{t}\) is an independent and identically distributed process with a zero mean and one standard deviation, \(\mu\) is the mean constant offset, \(\sigma_{t}^{2}\) is variance, and \(\alpha_{0}\) is the constant in the conditional variance. Unknown parameters for model are \(\alpha_{0}\), \(\alpha_{i}\) and \(\beta_{j}\) for some positive integer \(p\), \(q\).  
Just as in an ARIMA model, ACF and PACF are useful for \(p\) and \(q\) order identification in a GARCH(\(p\),\(q\)) process [30].
# Solvothermal Synthesis of Size-Controlled Monodispersed Superparamagnetic Iron Oxide Nanoparticles
###### Abstract  
Superparamagnetic iron oxide nanoparticles are of great interest in magnetic targeted drug delivery due to their unique properties. In this paper, size-controlled superparamagnetic iron oxide nanoparticles were synthesized in an ethylene glycol/diethylene glycol (EG/DEG) binary solvent system via a facile solvothermal method. X-ray diffraction (XRD), a scanning electron microscope (SEM), and a vibrating sample magnetometer (VSM) were used to confirm that the prepared samples were superparamagnetic Fe\({}_{3}\)O\({}_{4}\) nanospheres. When the \(V_{\rm EG}\)/\(V_{\rm DEG}\) was varied from 100/0 to 80/20, 60/40, and 40/60, the average diameters of the resulting Fe\({}_{3}\)O\({}_{4}\) nanospheres were approximately 700, 500, 300, and 100 nm, respectively. In addition, the saturation magnetization (\(M_{\rm s}\)) of Fe\({}_{3}\)O\({}_{4}\) nanoparticles with a size of 100, 300, 500, and 700 nm was 72.14, 75.94, 80.28, and 85.41 emu/g, and the corresponding remanent magnetization (\(M_{\rm r}\)) was 3.34, 3.97, 3.26, and 4.28 emu/g, respectively. The relevant formation mechanisms of Fe\({}_{3}\)O\({}_{4}\) nanoparticles are proposed at the end. These superparamagnetic Fe\({}_{3}\)O\({}_{4}\) nanoparticles with high saturation magnetization may have use as targeted drug carriers.  
targeted drug delivery; superparamagnetic; size-controlled; solvothermal method +
Footnote †: journal: Applied Physics Letters
## 3 Results  
### Characteristics of Included Studies  
The initial literature search yielded a total of 468 articles. After removing duplicate records, 347 articles were included for title and abstract screening. Subsequently 148 studies were identified for further full-text evaluation. Finally, seven qualified studies were deemed suitable for this meta-analysis (Figure 1).  
Characteristics of eligible studies are summarized in Table 1. Of those, four were prospective and three were retrospective. Studies were conducted in Italy (\(n=3\)), UK (\(n=2\)), Netherlands (\(n=1\)), and Brazil (\(n=1\)) and published between 2003 and 2016.  
Figure 1: Study flow chart.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  
A total of 430 patients were analyzed in this meta-analysis. The mean patient age ranged from 55 to 67 years. Mean tumor size was reported only in two studies, ranging from 1 to 7 cm. The most common histopathological type was squamous cell carcinoma (SCC), as reported in six of the eligible studies and ranging from 88.9% to 100% of patients.  
Overall, six out of seven studies reported the type of magnetic field used, ranging from 1 to 3 Tesla. Moreover, three studies relied on two radiologist readers, three had a single reader, and one study did not provide any information. Finally, PGE1 injection was used in five out of seven studies.
# Synthesizing Explainability Across Multiple ML Models for Structured Data
## 3 Proposed Method: Weighted Importance Score and Frequency Count (WISFC)  
We introduce WISFC, a method that combines feature-importance outputs from multiple explainable models by integrating two metrics: Weighted Importance Score (WIS) and Frequency Count (FC). WIS measures a feature's average importance across models, while FC captures how often it appears among each model's top-k. WISFC balances importance,magnitude, and stability, directly addressing our research questions by enabling reliable, reproducible aggregation of diverse explainers.
## 2 Results  
### Carotenoid Composition and Content  
A total of 23 carotenoids were detected by liquid chromatography-mass spectrometry of the albedo tissue and juice sacs of R-HJH and HJH. As shown in Table 1, the quantity of total carotenoids in the albedo tissue of R-HJH was 15.553 \(\pm\) 0.100 \(\upmu\)g/g (dry weight), which was 4.03-fold greater than that in HJH. Lycopene in the albedo of R-HJH and wild-type HJH reached levels of 10.407 \(\pm\) 0.315 \(\upmu\)g/g and 0.2974 \(\pm\) 0.189 \(\upmu\)g/g, respectively, which accounted for 66.91% and 7.60% of the total carotenoids, respectively. \(\upbeta\)-carotene accumulated to 1.347 \(\pm\) 0.096 \(\upmu\)g/g in the albedo of R-HJH and was the second highest carotenoid, while it was 0.235 \(\pm\) 0.035 \(\upmu\)g/g in the albedo of HJH. The change trend of carotenoids in the juice sacs between R-HJH and wild-type HJH was consistent with that in the albedo. The total carotenoid content in the juice sacs of R-HJH was 2.89-fold greater than that in wild-type HJH (19.432 \(\pm\) 1.104 \(\upmu\)g/g vs. 6.720 \(\pm\) 0.153 \(\upmu\)g/g, \(p<\) 0.01). The quantity of lycopene in the juice sacs of wild-type HJH was 3.207 \(\pm\) 0.061 \(\upmu\)g/g, which accounted for 19.54% of the total carotenoids. However, the content of lycopene in the juice sacs of R-HJH was 11.333 \(\pm\) 1.104 \(\upmu\)g/g, which was 2.53-fold greater than that in HJH. The proportion of lycopene in the juice sacs of R-HJH reached 58.32%. The \(\upbeta\)-carotene level was significantly higher in the juice sacs of R-HJH than those of wild-type HJH (1.890 \(\pm\) 0.191 \(\upmu\)g/g vs. 0.200 \(\pm\) 0.007 \(\upmu\)g/g, \(p<\) 0.01). In addition, the phytoene contents in the albedo and juice sacs of R-HJH reached levels of 1.166 \(\pm\) 0.259 \(\upmu\)g/g and 3.017 \(\pm\) 0.158 \(\upmu\)g/g, respectively. However, phytoene was undetected in the albedo or the juice sacs of HJH.  
Figure 1: Internal appearance of red-fleshed pummelo (**left**) and wild-type HJH pumpelo (**right**) fruit.
## 8 Performance Comparison
### Communication Cost  
Table 3 provides a comparative analysis of communication costs, contrasting our proposed scheme with referenced alternatives. This assessment specifically evaluates the communication costs incurred during the authentication phase of our scheme. For  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scheme** & \(\mathbf{V_{i}}\) & \(\mathbf{RSU_{k}}\) & **Total Performed Operation** \\ \hline
[14] & \(2T_{m}+9T_{h}+1T_{se}\) & \(4T_{m}+3T_{h}+4T_{se}\) & \(6T_{m}+12T_{h}+5T_{se}\approx 20.508\) ms \\
[19] & \(6T_{h}\) & \(4T_{m}+10T_{h}\) & \(4T_{m}+16T_{h}\approx 12.12\) ms \\
[28] & \(2T_{m}+4T_{h}\) & \(4T_{m}+4T_{h}\) & \(6T_{m}+8T_{h}\approx 17.284\) ms \\
[29] & \(6T_{h}+2T_{m}\) & \(5T_{h}+1T_{m}\) & \(11T_{h}+3T_{m}\approx 9.034\) ms \\ Proposed & \(6T_{h}\) & \(10T_{h}\) & \(16T_{h}\approx 0.896\) ms \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of computation cost.  
Figure 10: Comparison of computation cost [14; 19; 28; 29].  
this analysis, we assume the following sizes: the timestamps, identities, and random numbers are set to 32 bits, 160 bits, and 160 bits, respectively; the encryption/decryption processes utilize 256 bits; and the hash function output is set at 256 bits. The size of the elliptic curve point, represented as \(P=(Px,Py)\), is established at 320 bits. In our scheme, the communication overhead required in the first authentication is 2240 bits. The communication overhead required in the handover authentication process is 1600 bits. Hence, the total communication of our scheme is 3840 bits.  
For comparison, the communication costs of the schemes presented in [14; 19; 28] and [29] are 7264 bits, 3618 bits, 4416 bits, and 1440 bits, respectively. Figure 11 visually demonstrates that the communication overhead of the proposed protocol is much smaller than [14; 28]. This juxtaposition highlights that our proposed scheme achieves competitive communication costs in relation to the other referenced schemes. Our protocol balances security and efficiency through optimized cryptographic design. Introducing 159 bits of additional computation addresses four high-risk vulnerabilities while ensuring robust anonymity and forward secrecy.
## 3 Results  
To process and analyze the measured data, see Table A1 in Appendix A, it was decided to compare all measured pair data sets. According to the fact that skewness and kurtosis of the measured data sets was out of normal values, not only comparison of means, but also comparison of medians were chosen to be processed. To determine the statistically significant differences between data sets, hypothesis tests were used. Reasons for disruption of data distribution normality was also discussed and probable reason was found in the properties of the measuring device. All commercially available UHF RFID readers that offer the possibility to measure RSSI values offer the measurement resolution of 1 or 0.5 dBm, which is possibly not detailed enough.  
The matrix, see Figure 3, was derived based on measured RSSI for individual items that are located 2 m from each other.  
Figure 2: Radiation patterns of Confidex Survivor RFID Tag according to the datasheet [24].  
Figure 3 illustrates the average value of measured RSSI (rounded to an integer) of an RFID tag located in the center of the cell, with the RFID antenna above the center of that matrix. From the picture, it can be read that in the case of a distance of 2 m the difference of RSSI is minimal, as well as in the case of a reading distance of 8 m, where it is slowly beginning to merge. The biggest difference in RSSI values is around 4 and 6 m, where the position of individual tags on a given matrix can be easily determined based on RSSI.  
RF tags are further limited by the need, in passive systems, to power up their radio frequency integrated circuits through rectification of the incoming signal. There is a powerful analogy between the optical-polarizer experiment and the backscatter link of an RF tag system as described in [25]. The performed measurements were based on a real situation where a drone flies over an item in a warehouse. Because in real conditions it is not always possible to guarantee from which side the drone will fly over the RFID tag, we also chose RFID antenna as well as RFID tags with circular polarization.
## 3 Results and Discussions
### Loading of CO\({}_{2}\) at the Final Stage  
The loading of CO\({}_{2}\) (\(\alpha\)) can be determined using TOC analysis (Teledyne Tekmer, Phoenix 8000, Mason, OH, USA), and the results are shown in the last column of Table 4. The obtained values are in the range of 0.1081-0.6061 mol-CO\({}_{2}\)/mol-amine, depending on the operating conditions. It can be found that the value is related to the pH, \(T\), and flow rate ratio (\(\gamma\)). The results show that the lower the pH, the higher the \(\alpha\) value; however, it was also found that the higher the \(\gamma\), the higher the \(\alpha\). However, the relationship between them is hard to quantitatively determine. Therefore, a linear  
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multirow{2}{*}{**No**} & **Optimum** & \(E\) & \(R_{A}\times 10^{4}\) & \(K_{G}a\) & \(\gamma\) & \(\varphi\) & \(\alpha\) \\ \cline{2-7}  & **Conditions** & **(\%)** & **(mol s\({}^{-1}\) L\({}^{-1}\))** & **(s\({}^{-1}\))** & **(\(\star\))** & **(mol mol\({}^{-1}\) L\({}^{-1}\))** & **(mol mol\({}^{-1}\))** \\ \hline
17 & A4B1C2D1 & 87.01 & 3.53 & 0.132 & 1.00 & 0.1512 & 0.1425 \\
18 & A4B4C2D1 & 66.03 & 9.89 & 0.242 & 1.18 & 0.1377 & 0.1500 \\
19 & A4B4C4D1 & 73.42 & 11.0 & 0.305 & 0.82 & 0.1077 & 0.1093 \\
20 & A1B4C1D4 & 19.23 & 3.21 & 0.041 & 11.37 & 0.3864 & 0.5350 \\
21 & A4B1C4D1 & 90.26 & 3.64 & 0.152 & 0.74 & 0.1162 & 0.1115 \\
22 & A1B3C1D4 & 29.75 & 3.58 & 0.053 & 8.73 & 0.4648 & 0.5205 \\ \hline \hline \end{tabular}
\end{table}
Table 8: Data obtained in the verification test of the optimum conditions.  
Figure 6: Elapsed times for pH and T for the controlled and uncontrolled experiments.  
regression including the Taguchi experimentation is required. A total of sixteen data sets, as listed in Table 4, are adopted, and the results are shown as follows:  
\[\alpha(\text{mol/mol})=0.3847\exp(\frac{459.444}{T(\text{K})}-0.2376\text{pH}) \gamma^{0.5978} \tag{19}\]  
Figure 7 shows the confidence of regression, where it is found that the measured values are close to that of the calculated values, indicating that they are reliable in regression. Therefore, the equation can be used to calculate the values obtained in the optimum conditions and uncontrolled experiments. The results are also presented in Figure 7, where a slight deviation shows that Equation (19) is predicable. In addition, the parameter importance analysis shows \(\gamma>\text{pH}>T\), indicating that the liquid gas contact is significant for CO\({}_{2}\) loading. For the sake of comparison, two solvents, MEA [35] and aqueous ammonia [36], were used in the bubble-column scrubbers for CO\({}_{2}\) capture, and they are also exhibited Figure 7. It was found that most of the data falls in between the error range. In addition, the loading of the aqueous ammonia was close to that obtained in this work.
## 4 Discussion
### Analysis of the Evaluated Metrics for Each Method
#### 4.1.6 Variance Reduction (%)  
Variance reduction is highest with the V2 GGlide method, achieving values exceeding 20% at high SoC levels. This result shows the effectiveness of V2 GGlide in smoothing power oscillations under favorable charge conditions, making it particularly suitable for scenarios with ample storage capacity.