esa-sceva/satcom-chunk-collection huggingface dataset:
# State-of-the-Art Review of Structural Vibration Control: Overview and Research Gaps
## 2 Overview of Structural Control Systems
### Active Control System  
Active control systems are more sophisticated and require a significant power source for operation. These control systems use sensors to measure structural responses. Based on feedback from the sensors, the control forces are computed according to a prescribed controller and are then applied to the structure through actuators. These systems have the advantage over passive systems in adapting to varying load conditions [8]. However, it can also destabilize the structure if the control forces are not applied in the proper position and at the appropriate time. Some control devices are active mass dampers, active tuned mass dampers, and active tendon systems. [PERSON] et al. [2] presented a review of active and semi-active devices for structures since 1997 and identified that research in recent years has moved toward semi-active and hybrid control systems. [PERSON] [28] provided a report on the application of active and semi-active devices in Japan, which discusses the practical application of active control devices in structures.
# DLSTM-Based Successive Cancellation Flipping Decoder for Short Polar Codes
## 5 Conclusions  
To improve the performance of short block length, this paper proposes a DLSTM-based SC flipping algorithm for short polar codes. The DLSTM is used to predict the first error bit and construct a flipping set for the one-bit flipping, clipping all frozen bits to enhance the accuracy of prediction. For the sequences that fail CRC detector, the flipping set is resorted according to channel reliability, and the most unreliable bits are selected for multi-bit flipping. The simulation results show that the proposed algorithm has better error-correction performance compared with the ML-MSCF decoder and the DSCF decoder. In addition, when \(E_{b}/N_{0}=1.0\) dB, the decoding performance is close to CA-SCL (\(L=8\)) for \(N=32\), and the decoding latency is reduced by 49.03%. Furthermore, to make the algorithm robust, we propose a mechanism to make it compatible with different block lengths. For future work, we will focus on multi-task neural networks to predict multiple error bits of polar codes simultaneously.  
Conceptualization, J.C., W.K. and X.Z.; methodology, W.K. and X.Z.; software, W.K. and X.Z.; validation, J.C., W.K. and X.Z.; formal analysis, W.K. and X.Z.; investigation, J.C. and X.Z.; resources, J.C. and W.K.; data curation, W.K. and X.Z.; writing--original draft preparation, J.C., W.K. and X.Z.; writing--review and editing, D.C. and Q.Z.; visualization, X.Z.; supervision, Q.Z.; and project administration, J.C. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Joint Fund for Smart Computing of Natural Science Foundation of Shandong Province (No. ZR2019 LZH001) and the Shandong University Youth Innovation Supporting Program (Nos. 2019 KJN020 and 2019 KJN024).  
Not applicable.  
Figure 19: BLER comparison of the proposed algorithm and optimized algorithm with robustness mechanism with \(T_{\text{max}}=6\).
## 2 Materials and Methods
### Instrumental Analysis  
Prepared extracts of the samples were analysed using an Agilent Technologies 7890B GC System 7000C GC-MS Triple Quad chromatography-mass spectrometer with an HT-8, SCE Analytical Science capillary column (30 m \(\times\) 0.25 mm \(\times\) 0.25 \(\upmu\)m). PCB peaks were recorded using the MRM mode and identified by relative retention times. PCB congeners were quantitated by the method of internal standards using a Marker-7 PCB Mixture \({}^{13}\)C (Cambridge Isotope Laboratories, Inc., Shirley, NY, USA) as a surrogate internal standard (Tables S3 and S4). The limits of determination (LOD) of PCB congeners in the water and fish were 0.01-0.02 ng/L and 0.10-15 ng/g (www), respectively. The LOD method was assessed based on the peak-to-peak signal-to-noise response of each of the PCB peaks (N/S) and at the lowest standard concentration. Values for S/N > 10 were employed to determine the limit of quantitation (LOQ) for each target compound. Relative standard deviation (RSD\({}_{\text{RI}}\)) for the determination procedure was 35% for individual indicator congeners in the water: 28, 52, 101, 118, 138, 153, and 180; 25% for individual indicator congeners and dl-PCBs in the fish: 28, 52, 101, 105, 114, 118, 123, 126, 138, and 153; and 45% for congener 180.
## 3 Results and Discussion
### Principal Component Analysis Applied to Identify the Main Sources of Variability in the Dataset  
PCA shows that the first two components explained nearly 70% of the total variance (Figure 6). The first component (Dim 1) has a positive and significant correlation with Na\({}^{+}\), Cl\({}^{-}\), Ca\({}^{2+}\), SO\({}_{4}\)\({}^{2-}\), Mg\({}^{2+}\) and K\({}^{+}\), while the second component (Dim 2) positively and strongly relates with HCO\({}_{3}\)\({}^{-}\) and SO\({}_{4}\)\({}^{2-}\), and in a weak and negative way with Na\({}^{+}\), Cl\({}^{-}\) and K\({}^{+}\). Both associations could be reflecting the occurrence of two processes, saline intrusion or the weathering processes of the carbonate lithology. Another explanation for the presence of ions such as Na\({}^{+}\), Cl\({}^{-}\) and K\({}^{+}\) could be the dissolution of evaporitic rocks (gypsum, halite, sylvie). However, according to [14], the presence of halite and sylvie is restricted to two points outside the study area. Thus, the results from the PCA provide further support to the interpretations made in the previous section, of the predominance of rainfall and infiltration as a recharge source for the studied SSWB.  
Although K\({}^{+}\) and Mg\({}^{2+}\) show a relatively small contribution to the overall variance of the dataset, based on their importance to further explain the hydrogeochemical processes taking place in the area, both ions were still used for the rest of the multivariate analyses.
## 6 Conclusions and Applications  
### Conclusions  
This work presents a new re-entrant honeycomb metamaterial, and the proposed metamaterial is purposefully optimized by means of assembling metal pins and particle damping. The static and vibration-isolation properties of the metamaterial are investigated by simulations and experiments. Conclusions are as follows:  
1. Compared with the DHM, the load-carrying performance of the CDCHM is improved by approximately 800%, and the mass is only increased by about 16.6%;
2. Increasing the size of the ring structure in the CDCHM can effectively enhance its static performance and vibration-isolation performance at the same time;
3. Adding metal pins to the CDCHM can realize the adjustment of the bandgaps, the larger the size or density of the metal pin and the lower the inferior limited frequency  
Figure 12: Experimental VTL results of different metamaterials: (**a**) DHM; (**b**) CDCHM; (**c**) CDCHM with the copper pins; (**d**) comparison of the filtering results of the CDCHM with the metal pins and the CDCHM with particle damping.  
of the first bandgap; the inferior limited frequency of the first bandgap achieved in this paper is 1709 Hz, and will probably be even lower if the pins are made of a higher-density material;
4. The introduction of particle damping into the CDCHM can further improve the vibration-suppression ability of the metamaterial, and the frequency of the bandgap can be adjusted by the dosage of the particle damping.  
The bandgaps of the proposed CDCHM could be designed by changing the assembly material, which provides a reference for the future metamaterial optimization design. In addition, since the focus of this work is the improvement of the carrying capacity and vibration-isolation performance, and the main application targets of the metamaterials proposed in this work are vehicles, ships and other fields that are not sensitive to mass, so equal mass is not taken as a constraint and a lightweight design is not taken into consideration. In future studies, we will improve the research on this point and further improve the design ideas and methods of metamaterial improvement.
# Compact N-Band Tree-Shaped Multiplexer-Based Antenna Structures for 5G/IoT Mobile Devices
## 2 Related Work
Although the correspondence between simulations and measurements is quite satisfactory, neither the antenna's scalability is a priority nor the operating frequency is suitable for the future generation of mobile communications. Above all, the concept proposed in [17] requires the usage of two feeding ports, which differs from the goal of this work which lies on having a single antenna, fed in a single point, capable of interacting with multiple RF frontends, isolating each frequency. All of these suggested frequency selective networks are associated with higher complexity in the structure's design and fabrication. They demand for additional components and the antennas were designed for lower frequencies than what is expected within the 5G context. The work presented here defends an innovative concept where neither the manufacturing is compromised nor the feeding network imposes the usage of any additional components. In this sense a new concept to design a structure for a multi-band antenna operating in the K/Ka bands is proposed. The design idea lies on sectioning a n-band antenna into \(n\) parts, having each section properly isolated (in frequency) in order to maximize the efficiency, and that is achieved by applying the adequate impedance matching as it will be explained later. This frequency multiplexing concept represents the main difference between the state-of-the-art studied and the structures proposed in this report. With this alternative it is possible to several antennas in a single structure with a single feeding point. Two prototypes were built and tested representing the cases of a dual and a tri-band antenna, ensuring the scalability to other resonances.
# Experimental Validation of a GNSS Receiver Antenna Absolute Field Calibration System
## 2 Materials and Methods
### Validation Methodology
#### 2.3.1 Validation by Comparison with Geo++ GmbH  
Experimental validation and accuracy analysis of the LMMT receiver antenna individual absolute calibration results were performed by comparing them with independent individual calibration results provided by Geo++ GmbH in Germany. Considering the  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Antenna** & **S/N** & **IGS Antenna** & **I/L** & **Calibration Date/** \\  & **Code** & **Campaign No.** \\ \hline Trimble Zephyr 2 Geodetic & 30739001 & TRM57971.00 NONE & Z1 & 26 May 2023/1 \\  & & & 16 June 2023/2 \\  & & & 19 June 2023/3 \\ Trimble Zephyr 2 Geodetic & 30734472 & TRM57971.00 NONE & Z2 & 19 June 2023/3 \\ Trimble Zephyr 2 Geodetic & 30738967 & TRM57971.00 NONE & Z3 & 19 June 2023/3 \\ Trimble Zephyr 2 Geodetic & 30278601 & TRM55971.00 NONE & Z4 & 16 June 2023/2 \\ Leica Geosystems AX1202 GG & 08190116 & LEIAX1202 GG NONE & LG & 16 June 2023/2 \\ Topcon PG-A1 & 308-1874 & TPSPG\_A1 NONE & TP & 20 June 2023/4 \\  & & & 20 June 2023/4 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Overview of individually calibrated GNSS receiver antennas at the LMMT calibration facility; S/N—antenna manufacturer’s serial number; I/L—LMMT internal antenna label added for simpler referencing.  
Figure 5: GNSS receiver antennas utilized in experimental validation of the developed LMMT calibration system; **(a)** Trimble Zephyr 2 Geodetic (TRM57971.00 NONE and TRM55971.00 NONE); **(b)** Leica Geosystems AX1202 GG (LEIAX1202 GG NONE); **(c)** Topcon PG\_A1 (TPSPG\_A1 NONE).  
importance of the Geo++ GmbH calibration system, its contribution to IGS, the fact that it is globally regarded as a leading authority in the field, and that this is basically the best in terms of calibration that one can do, it is completely justified to take Geo++ GmbH calibration results as reference values in the analysis.  
Validation and accuracy analysis was conducted at the PCC pattern level for the antenna Trimble Zephyr 2 Geodetic (S/N: 30739001), which was individually calibrated by Geo++ GmbH on 5 August 2022. The GPS L1 (frequency code G01 consistent with ANTEX) and GPS L2 (frequency code G02 consistent with ANTEX) calibration results (PCO and PCV) for the TRM57971.00 NONE (S/N:30739001) antenna obtained by Geo++ GmbH are given in Figure 6.  
The comparison of the two individual antenna calibration results (Geo++ and LMMT), along with the quantification of the corresponding scalar measures, was performed according to the PCC comparison methodology elaborated in detail by [PERSON] et al. [17] and [PERSON] [32]. The primary objective of the test is to assess the compatibility of LMMT calibration results with those obtained by Geo++ GmbH and to evaluate the practical significance of the developed LMMT system.
## 2 Materials and Methods
### Feasibility Pilot Study
#### 2.2.2 Clinical Evaluation and Instrumental Assessment  
Patients in both the RG and CG were evaluated twice, at baseline (T0) and at the end of the rehabilitation program (T1). The clinical evaluations included scales for the upper limb function (the Fugl-Meyer [11] and the Motricity Index [12]), spasticity (the Modified Ashworth Scale for shoulder, elbow and wrist [13]), lower limb performance (the Deambulation Index [14]), and activities of daily living (the modified Barthel Index [15]). The instrumental evaluations included the evaluation of the muscle strength (handgripr dynamometer) and the finger pinch (pinch gauge). In addition, the Visual Analogue Scale (VAS) for Satisfaction (a self-assessment scale from a 10-cm horizontal axis where 0 means \"no satisfaction\" and 10 \"extreme satisfaction\") was used by patients to rate their satisfaction by making a vertical mark on the 10-cm line [16]. The measurement in centimeters was converted to a number ranging from 0 to 10. The exact question was, \"Are you satisfied with the robotic rehabilitation?\"
# PVPBC: Privacy and Verifiability Preserving E-Voting Based on Permissioned Blockchain
## 8 Performance Analysis
### Voting-Phase Performance Evaluation  
We deployed our voting-phase implementation, which is described in Section 5.2, on the Quorum private blockchain platform in order to mimic its operation on a real-world, production network. We recruited different numbers of candidates to contest the election, in order to evaluate implementation. The number of candidates was increased from 1 to 7. In this experiment, the blockchain was used as a ballot box during the election phase to store the signed encrypted ballots as well as the tracker commitment (Beta). The goal of these experiments was to verify how the cost for casting a ballot varied with different numbers of candidates. Figures 10 and 11 show the average gas-consumption cost (resp. cost in GBP) for casting an encrypted ballot and tracker commitment based on different numbers of candidates. In this experiment, the cost was calculated in GBP. Based on the data points in Figure 11, it is reasonable to suggest that the costs in GBP increases approximately linearly as the number of candidates increases from 1 to 7. When there are 7 candidates, the cost is GBP 0.6. The cost for 2 candidates is approximately GBP 0.22. The linear relationship described here to characterise the cost in GBP for casting and storing an encrypted ballot alongside tracker commitment as a function of the number of candidates is an appealing property of PVPBC.  
Figure 11: Cost in GBP for casting and storing an encrypted ballot alongside tracker commitment.  
Figure 10: Gas cost for casting and storing an encrypted ballot alongside tracker commitment.
# Enabling Biodiversity-Informed Architecture Through Ontology-Driven Data Integration
## 4 Ontology Design and Development
### Defining the Ontology Requirements  
We organised a collaborative workshop with experts from the ECOOPES consortium, comprising architects and ecologists, to define the ontology and knowledge graph requirements. Given that most participants were not ICT specialists or knowledge engineers, identifying and conceptualising ontology requirements posed a significant challenge. To facilitate this process, we structured the workshop around ontology construction best practices, ensuring that domain experts could systematically contribute their knowledge in a way that aligns with semantic modelling principles.  
The participants were divided into four interdisciplinary teams, each consisting of six people, to encourage the \"cross-pollination\" of ideas, leveraging diverse expertise to bridge conceptual gaps. Each team was tasked with defining a comprehensive set of competency questions (CQs) spanning both domains, a fundamental step in ontology engineering that helps capture the intended scope and use cases. These CQs were written on post-it notes to foster discussion and iterative refinement, allowing experts to progressively articulate their knowledge in a structured manner.  
In parallel, the participants identified key concepts and relationships relevant to answering the CQs, mapping out the foundational elements of the ontology. However, the abstraction required for formal ontological representation proved difficult for non-ontology experts. To mitigate this, they were guided to propose synonyms, group related concepts into broader categories, and outline hierarchical relationships, effectively shaping the initial class taxonomy. Recognising that defining structured properties and attributes requires a technical perspective, we encouraged participants to describe informal connections between concepts, which were later formalised by knowledge engineers. When gaps remained in structuring the ontology, participants suggested relevant datasets or external sources that could support answering the identified CQs, ensuring that the ontology remained grounded in real-world data and met FAIR principles for interoperability and reusability.  
This bottom-up, expert-driven approach resulted in a draft skeleton ontology comprising initial classes, properties, and attributes.  
Requirements were captured through CQs, with some listed here to name a few:  
* Which species do we want/do not want to attract close to our building?
* Which species are in PFG _herbs_3_?
* Which species that colonise the building are protected?
* Which species are invasive in this location?
* Which species can reach or live on sloped surfaces?
* What is the soil depth required for PFG _herbs_3_?
## 4 Results
### Structural Equation Modeling Results  
After successfully validating and achieving adequate model fit for the measurement model of the latent constructs by using CFA, we evaluated the structural model. The hypothesized structural model is illustrated in Figure 3. The structural model regression estimates are shown in Table 8. Goodness of fit of the model was also evaluated, and the revised structural model satisfied all model fit criteria. The model fit results are shown in Table 9.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Constructs** & **VSE** & **TMS** & **OC** & **SES** & **SEPP** \\ \hline VSE & 0.733 & & & & \\ TMS & \(-\)0.048 & 0.934 & & & \\ OC & 0.282 & 0.262 & 0.857 & & \\ SES & 0.126 & 0.548 & 0.540 & 0.890 & \\ SEPP & 0.401 & 0.345 & 0.507 & 0.577 & 0.868 \\ \hline \hline \end{tabular} Factor correlations. Square root of AVE on the diagonal. VSE = value of systems engineering, TMS = top management support, OC = organizational commitment, SES = systems engineering support, SEPP = systems engineering process performance.  
\end{table}
Table 7: Discriminant Validity.  
\begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **Std. Estimate (\(\beta\))** & **S.E.** & **C.R.** & \(p\) \\ \hline OC \(\leftarrow\) Number of Projects & 0.164 & 0.026 & 2.557 & 0.011 \\ VSE \(\leftarrow\) Career Level & 0.189 & 0.029 & 2.872 & 0.004 \\ SES \(\leftarrow\) OC & 0.457 & 0.042 & 9.209 & *** \\ SES \(\leftarrow\) TMS & 0.466 & 0.030 & 9.374 & *** \\ SEPP \(\leftarrow\) OC & 0.162 & 0.063 & 2.572 & 0.010 \\ SEPP \(\leftarrow\) VSE & 0.334 & 0.051 & 6.403 & *** \\ SEPP \(\leftarrow\) SES & 0.459 & 0.071 & 7.682 & *** \\ \hline \hline \end{tabular}
\end{table}
Table 8: Structural Model Regression Estimates.  
\begin{table}
\begin{tabular}{l l l l} \hline \hline
**Model Fit Index** & **Criteria** & **Final Revised Model** \\ \hline Chi \(-\) square (\(\chi^{2}\)) & low & 11.279 \\ Degrees of freedom (df) & \(>\)0 & 11 \\ Probability value (\(p\)) & \(>\)0.05 & 0.420 \\ \(\frac{\chi^{2}}{df}\) & \(<\)5 & 1.025 \\ Goodness-of-fit index (gfi) & \(>\)0.90 & 0.985 \\ Tucker-Lewis index (TLI) & \(>\)0.90 & 0.999 \\ Comparative fit index (CFI) & \(>\)0.90 & 0.999 \\ Root mean square error approximation (RMSEA) & \(<\)0.08 & 0.011 \\
90\% Confidence interval (lo90—hi90) & \(<\)0.05–0.08 & 0.00–0.075 \\ Probability of closeness of fit (P\({}_{\text{close}}\)) & \(>\)0.5 & 0.775 \\ \hline \hline \end{tabular}
\end{table}
Table 9: Revised Structural Model Goodness of Fit.
# Design of a Fixed IF Down-Conversion Double-Balanced Mixer for UHF Band Applications
## 3 Proposed Down-Conversion Mixer Design
Under ideal switching conditions, the optimal conversion gain can be achieved. The switching pairs are not ideal in practice. During the switching time period \(t_{switch}\), both switches are on, transforming the switching pairs into differential amplifiers. When \(\mid\)\(V_{LO}\)\(\mid\) is less than 4\(V_{t}\), the conversion gain that considers this non-ideality [12] is expressed as follows:  
\[GC\cong\frac{2}{\pi}\frac{\mathrm{sin}(\pi f_{LO}t_{switch})}{\pi f_{LO}t_{ switch}}g_{m}R_{L} \tag{7}\]  
According to Formula (7), switching time can be reduced by increasing the LO voltage or lowering the switching voltage in order to increase conversion gain. Higher LO drive may lead to saturation in transconductance stages and cause the RF signal to swing beyond the pre-described linear range, which results in lower transconductance \(g_{m}\) and consequently, lowers linearity and gain. Switching does not require high voltage. Hence, it reduces switching time while keeping a lower power level for LO, which is highly beneficial in low power applications [12; 13; 14; 15].
# An Overview of Position Sensorless Techniques for Switched Reluctance Machine Systems
## 3 An Overview of Recent Development in Position Estimation Methods of SRM
### Hybrid Detection Position Sensorless Method
#### 3.3.1 Strategies Based on a Mix of Multiple Sensorless Approaches for Full Speed Range  
Hybrid control algorithms are very common in control because they can comprehensively utilize the advantages of multiple parties [150; 151; 152; 153]. Active fault-tolerant techniques are proposed to deal with position sensor failures. The method of pulse injection is applied [155]. This method is the most widely used, and the pulse injection method is cited as the starting method in many approaches [94; 148]. Four-phase operation is of great significance for SRM to meet more applications. In [123], a state observer and a pulse injection-based inductance detection method are combined to enable the motor to perform well in the starting and full speed range. Position sensorless methods based on fewer current sensors were proposed [149; 153; 160]. The main contribution of these methods is to reduce the current sensor, and the position scheme will be based on the characteristics of inductance and current. There are position sensorless control methods for diagnostic fault tolerance after position sensor failure [94; 95; 101; 155].  
This type of hybrid rotor position estimation method demonstrates a relatively outstanding performance in the local speed range, but in-depth research on other mature methods directly cited has not been performed. However, how to smoothly connect different methods needs to be paid attention to, especially in the case of sudden load or variable speed conditions.