esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Field Modal Testing for PV Support Structure  
### PV Support Structure  
The flexible PV support structure consisted of concrete foundations, support columns, diagonal cables, support cables, and PV modules fixed to the support cables through metal clamp fixing, as shown in Figure 3(a). The structure tested in this study is shown in Figure 3(b). Each PV module measures 2172 mm \(\times\) 1303 mm \(\times\) 35 mm with 26 mm inter-module spacing at a tilt angle of 15\({}^{\circ}\). The span between the columns is 21.9 m. Two support cables, each with a diameter of 16 mm and an initial tension of 60 kN, connected the ends of the span. The 60 kN load was selected based on the tension applied during the construction stage, as specified by the company responsible for the photovoltaic project. Sixteen PV modules were mounted on the support cable secured by metal clamp fixings. A typical PV module comprises multiple solar cells encapsulated with protective EVA layers, sandwiched between a high-transparency tempered glass cover and a polymer backsheet, and is supported by an aluminum alloy frame with an integrated junction box and bypass diodes for electrical protection. The support columns, made of Q345 steel, stood 3.5 m high, and were fixed to concrete foundations. The diagonal cables were anchored to the concrete foundations and connected to the top of the support columns. This configuration balanced the initial tension of the support cables and ensured the columns remained stable.  
Figure 4: _Cont._  
The FE model was established using ANSYS APDL 2022R1 software as shown in Figure 5. The material properties and element types for the FE model were selected with reference to previous research [28; 50; 51]. The cable was modeled using LINK180 with an initial tension of 60 kN applied. The cable had a Young's modulus of 1.95 \(\times\) 10\({}^{11}\) Pa, a density of 7850 kg/m\({}^{3}\), and a Poisson's ratio of 0.3. The PV module was modeled using SHELL181, with a Young's modulus of 7.2 \(\times\) 10\({}^{9}\) Pa, a density of 304.25 kg/m\({}^{3}\), and a Poisson's ratio of 0.33. The steel support columns were modeled by the BEAM188 element. The bottoms of the columns were constrained in all degrees of freedom in the FE model. The columns had a Young's modulus of 2.06 \(\times\) 10\({}^{11}\) Pa, a density of 7850 kg/m\({}^{3}\), and a Poisson's ratio of 0.3.  
Figure 6 presents the first four mode shapes obtained from the FE model. The first-order mode is the half-wave vertical bending mode with the maximum displacement occurring at the mid-span  
ment occurring at the quarter-span PV panels. The fourth-order mode is the second-order torsional mode with maximum displacements occurring at the front and rear ends of the quarter-span PV panels. And the first four orders of modal frequencies derived from FE analysis are 1.69 Hz, 2.20 Hz, 3.08 Hz, and 4.24 Hz, respectively.
## 1 Introduction
During operation, we observed frequency drift in the oscillating longitudinal mode, accompanied by fluctuations in output power. We qualitatively analyzed these phenomena and attributed them to changes in the optical path length. This hypothesis was verified by detecting the centroid position of the output laser spot. To address the issue, we replaced the K9-glass etalons with an FP etalon made of LT crystal. This modification successfully corrected the frequency drift and suppressed multiple-longitudinal mode (MLM) operation. Our findings provide valuable insights into the use of EO crystals for stabilizing SLM lasers, offering a promising approach for improving laser performance in precision applications.
###### Abstract  
This paper proposes a semiconductor optical amplifier (SOA)-based multilevel polarization shift on-off keying (MPS-OOK) transmission for free-space optical (FSO) communication. At the transmitter end, the MPS-OOK signal is modulated with a constant linear state of polarization (SOP) at the high-intensity level and various SOPs at the low-intensity level in order to improve the spectral efficiency (EE) with the transmitted power efficiency. At the receiver end, first, a polarization-independent SOA was introduced to optically suppress the turbulence-induced scintillation effect and equalize the intensities of the various SOPs in the deep gain saturation state without polarization distortion. Then, a linear polarizer (LP) with a high extinction ratio (ER) was deployed to convert the equalized SOPs into a known intensity. Finally, the converted MPS-OOK signal was detected using a single photodiode (PD) and distinguished using a multilevel fixed-threshold decision (M-FTD). The proposed technique was evaluated using experiments. A Mach-Zehnder modulator (MZM)-based fading simulator was introduced to emulate the turbulence-induced scintillation effect. The experimental results demonstrated that the scintillation effect was effectively mitigated and the SE was improved by up to 2 bit/s/Hz using the proposed four-level polarization shift on-off keying (4 PS-OOK) transmission.  
multilevel polarization shift on-off keying; semiconductor optical amplifier; scintillation effect; spectral efficiency; free-space optical communications +
Footnote †: journal: _photonics_
# Enhanced Efficient EMT-Type Model of the MMCs Based on Arm Equivalence
## 2 General Structure, Control Scheme, and Previous Models of the MMC
### Previous Models
#### 2.3.2 Type B: Average Value Models (AVMs)  
The AVMs neglect the impact of SM capacitor ripple voltage by using a single equivalent capacitance, and further improve the simulation efficiency. The AVMs have less accurate simulations compared to the DEMs [15].  
A brief overview of the AVM is expressed here, and a further description is given in [13]. As shown in Figure 4, the IGBTs are not explicitly represented and the behaviour of the MMC is modelled with the controlled voltage sources (\(v_{\text{vj}}\)) and controlled current source (\(I_{\text{con}}\)), where  
\[v_{\text{vj}}=v_{\text{ref, vj}}\frac{V_{\text{dc}}}{2} \tag{6}\]  
\[I_{\text{con}}=\frac{1}{2}\sum_{j}v_{\text{ref, vj}}i_{j} \tag{7}\]  
Figure 3: The detailed equivalent models (DEM) topology: (**a**) The HBSM; (**b**) The submodule (SM) equivalent circuit, with companion model; (**c**) The SM Thévenin equivalent circuit; (**d**) The arm Thévenin equivalent circuit.  
\[C_{\text{eq,AVM}}=\frac{6C_{0}}{N} \tag{8}\]  
where, \(v_{\text{ref,vj}}\) is the \(j\) phase voltage reference generated by the control system, which is a per-unit value; \(C_{\text{eq, AVM}}\) represents the DC-side equivalent capacitance; \(L_{\text{Arm}}\) (= \(L_{0}\)) and \(R_{\text{Arm}}\) (= \(NR_{\text{ON}}\)) denotes the arm equivalent inductance and resistance, respectively. Under de-blocked mode, the switch (\(S_{1}\)) is open, and \(S_{2}\) is closed; under blocked mode, \(S_{1}\) is closed to emulate the MMC blocking while switch \(S_{2}\) is open. The dynamics under blocked mode are relatively inaccurate [15].
## Materials and Methods
### Experiment Setup  
A commercial blood pressure meter with a cuff (OMRON M1) was used as the gold standard in this work to measure SBP on the left brachial artery. The PPG signal was collected using the CMS50 FW Pulse Oximeter without automatic gain control (AGC) function. The PPG signal sampling rate was 60 Hz and the quantization resolution was 8 bits. The optical sensor with both red (wavelength 660 nm) and infrared (wavelength 880 nm) light sources were used. The collected signal was sent via Bluetooth to a PC, where SBP estimations were performed.  
This study was performed at the Clinical Department of Geriatrics of the Lithuanian University of Health Sciences. Nineteen subjects took part in the research (12 women and 7 men), including 6 persons aged 70-77, 11 persons aged 82-85, and 2 persons aged 88 years old with body mass index BMI = 22.4 \(\pm\) 1.3. All subjects, but two, used blood pressure-regulating drugs. Five subjects had ischemic heart disease.  
SBP measurements and PPG records were done for each subject 5 days in a row (one per day), at any convenient time for the subject. The subjects sat with their left hand placed on a support and a PPG sensor placed on their left-hand finger, as shown in Figure 14a. The PPG signal recording was always done first using the pulse oximeter. This procedure took 5 min. The SBP measurements were done immediately after that, using the blood pressure meter, as shown in Figure 14b. Standard cuff type for an arm circumference ranging from 220 to 320 mm was used. Since measurements were performed in a calm state, the records are without movement artefacts.  
The experimental protocol of the study was approved by the Kaunas Regional Biomedical Research Ethics Committee (permission No. BE-2-53), allowing the use of a pulse oximeter CMS50 FW at the Clinical Department of Geriatrics. According to the Association for the Advancement of Medical Instrumentation (AAMI) protocol [49], the blood pressure values were measured by experienced medical staff.  
All subjects were informed about the performed research and their written consent was obtained.  
Figure 14: (a) PPG signal recording posture; (b) SBP measurements posture.  
Figure 13: Estimated \(SBP_{e}\) blood pressure value (dot line) and \(SBP_{mfl}\) in BPEW (stepwise line).
# Path Tracking Control Strategy Based on Adaptive MPC for Intelligent Vehicles
## 8 Future Work and Limitations
### Limitations  
1. Computational Complexity: The real-time implementation of the adaptive MPC controller, especially under complex dynamic environments, requires substantial computational resources. Although the current system meets real-time requirements (average latency of 5.2 ms per control cycle), further optimization is needed for scenarios with higher-frequency state updates or more stringent real-time constraints.
2. Curvature Estimation Dependency: The controller's performance heavily relies on accurate real-time curvature estimation. In scenarios where curvature data are noisy or delayed (e.g., due to sensor limitations or communication latency), the tracking performance may degrade. Future work could explore robust curvature prediction methods to mitigate this issue.
3. Validation Scope: The current study validates the controller under predefined variable curvature conditions and low/high-adhesion road surfaces. However, real-world driving scenarios may involve more complex dynamics, such as sudden obstacles, dynamic traffic participants or extreme weather conditions. Extending the validation to these scenarios would further demonstrate the controller's robustness.
# Low-Cost COTS GNSS Interference Monitoring, Detection, and Classification System +
## 5 Algorithmic Design
### Post-Processing
The equation effectively quantifies the disagreement between the individual predictions and the mean prediction, providing a measure of how confident the model is in the prediction.
## 4 Application Scenarios for Different Network Topologies
Since one can calibrate the optical spectrum of the Tx signal and estimate the electrical spectrum of the Rx signal based on the raw data from the ADC, one can derive the degradation due to multiple cascading ROADMs. This information can be then fed back to the Tx directly in the bi-directional case or through the in-band signal/network management layer in the other case. Then, one can adjust the Tx FIR filter in one step based on a certain pre-calibrated table. Next, the Rx FIR filter can be adaptively adjusted to compensate any dynamic bandwidth narrowing effect. The adaptive nature of the demonstrated method is well suited for real deployment. In the case with cascaded ROADMs, the spectral response of multiple filters will vary inadvertently. By estimating the spectrum of the received signal from the raw data of the ADC samples, one can dynamically adjust the simple FIR filter, which is implemented after the ADC, to compensate the bandwidth narrowing effect. This leads to an improved performance for the long-haul optical communications system.
# Matched-Filter Thermography
## 3 Matched Filtering
### Pulse Compression  
Range/depth resolution can be enhanced in MF by incorporation of pulse compression techniques. That is, the pre-known signal can be coded with different types of phase or frequency compression techniques (e.g., linear frequency modulation/chirping or binary phase coding) in order to make the MF output waveform narrow. Panels (g)-(i) show a scenario in which linear frequency modulation has been implemented (chirp frequency range 1 Hz to 20 Hz; duration 1s) to enhance the range resolution; note the narrow output of MF in panel (i). By doing so, MFs gain the ability to simultaneously enhance both SNR and range resolution. This enhancement can be readily observed through comparison of the MF outputs of panels (c) and (i) and those from two delayed replicas of the filter (\(\tau_{1}~{}=~{}2\) s and \(\tau_{2}~{}=~{}2.5\) s), panels (l) and (f).  
Figure 1: Simulated filter, noisy response, and matched-filter output for: (**a**–**c**) single-frequency response of a single reflector; (**d**–**f**) single-frequency response of two reflectors; (**g**–**i**) Linear frequency modulation (LFM) response of single reflector; LFM response of two reflectors.
## 4 Discussion and Conclusions
### Conclusions  
(1) From the perspective of the space-time evolution process of deformation and fracture of surrounding rock, the surrounding rock under the excavation of step method resisted rockburst in the form of \"fracture zone\" or \"logarithmic spiral\" in the process of deformation and fracture. The range of rockburst area was effectively reduced, and the risk level and intensity of rockburst were effectively reduced, which realized the gradual release of rockburst energy and the treatment and improvement of tunnel rockburst.  
(2) From the perspective of characteristics of acoustic emission energy, although the buried depth continued to increase by using the excavation of step method, the absolute energy and cumulative energy of acoustic emission of each key point of the two specimens maintained a small value, which realized the gradual release of rockburst energy.  
(3) From the perspective of characteristics of two-dimensional spectrum, after the excavation optimization design, the frequency band range was relatively fixed, which showed that the high frequency and ultrahigh frequency values of the acoustic emission waveform signal fluctuated greatly, while the low frequency and ultralow frequency values changed little, indicating that during the experiment, the formation of small-scale and smaller-scale cracks in the interior had random characteristics, while large-scale and larger-scale fractures had certain commonalities, which were characterized by zonal fracture.  
Conceptualization, X.S.; methodology, D.L.; software, C.R. and J.Y.; validation, X.S.; formal analysis, C.R.; investigation, D.L.; data curation, C.R.; writing--original draft preparation, C.R.; writing--review and editing, J.Y.; project administration, X.S.; funding acquisition, X.S. and D.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China, grant number (5217042575, 52074299); Key Scientific Research Project of Gansu Provincial Department of Transportation, grant number (u150154); Fundamental Research Funds for the Central Universities, grant number (2023)CCXSB02).  
Not applicable.  
All data included in this study are available upon request by contact with the corresponding author.  
Author [PERSON] was employed by the company Shanxi Transportation Research Institute Group Co., Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 5 Discussion
### Summary of Research Results  
Recently, global logistics companies have been significantly impacted by global supply chain crises arising from the U.S.\(-\)China trade dispute, the COVID-19 pandemic, the Russia\(-\)Ukraine conflict, and global climate change. Amid the growing importance of global supply chain management, various studies have been conducted using the GSCPI. However, research on the relationship between the GSCPI and global logistics companies remains scarce. Therefore, this study aimed to explore the impact of global supply chain pressure on global logistics companies using the VARM approach, which led to the following findings.  
First, the impact of the GSCPI on air cargo, integrated logistics, and pipeline companies showed both positive (+) and negative (-) relationships depending on the lag. However, the t-statistics were below the threshold of 1.291, corresponding to a 90% confidence level, which indicates that these results were not statistically significant.  
Second, the effect of the GSCPI on shipping companies exhibited a positive (+) relationship and was found to be statistically significant. The t-statistics for COSCO Shipping and Maersk Group were 1.83058 and 3.08136, respectively, showing significance at the 95% confidence level. For Hapag-Lloyd, the t-statistic was 1.61508, indicating significance at the 90% confidence level.
## 4 Results
### Multiple Electric Vehicle Connection and Disconnection  
In this second test, various EVs are connected and disconnected at different periods and nodes of the microgrid to simulate the increase and decrease of active and reactive power of loads defined in Figure 3 (L1-L6). Figure 10 shows the events at different periods to identify the controller response under multiple EVs connections and disconnections. The following are the six events considered in the connection and disconnection test of multiple EVs.  
Figure 8: Power behavior of distributed generators (DGs) with the six events (Events 1–6): (**a**) Active power and (**b**) reactive power.  
* Event 1: at the beginning of the first period (from \(t_{0}\) to \(t_{1}\)), L1 increases the active power consumption after connecting five EVs to Node 1, changing the power by nine times the fixed load of \(25+j0.001\)\(\Omega\); at the end of the period, this load is disconnected.
* Event 2: at the beginning of the second period (from \(t_{1}\) to \(t_{2}\)), the active power increases in L2 when one EV is connected to Node 2, and the power increases by four times its normal value of 10 + j0.03 \(\Omega\); at the end of the period, this load is disconnected.
* Event 3: at the beginning of the third period (from \(t_{2}\) to \(t_{3}\)), the greatest change of active power is presented in Node 3 (L3) with the connection of 10 EVs, and the consumption in that node is almost 13 times the fixed load of \(20+j0.01\)\(\Omega\); at the end of the period, this load is disconnected.
* Event 4: at the beginning of the fourth period (from \(t_{3}\) to \(t_{4}\)), three EVs are connected to Node 4 (L4), which provides a power consumption of almost five times the average consumption of \(15+j0.02\)\(\Omega\); at the end of the period, this load is disconnected.
* Event 5: at the beginning of the fifth period (from \(t_{4}\) to \(t_{5}\)), the connection of two EVs is presented at Node 5 (L5), resulting in an increase in the load of 22 times the normal active power consumption with respect to the fixed load of \(25+j0.09\)\(\Omega\); at the end of the period, this load is disconnected.
* Event 6: at the beginning of the sixth period (from \(t_{5}\) to \(t_{6}\)), two EVs are connected to Node 6 (L6), which generates an additional power consumption at the node of almost eight times the normal consumption of \(18+j0.05\)\(\Omega\); at the end of the period, this load is disconnected.
## 3 Results and Discussion
The results shown in Appendix A indicate that the influence of CO and HC in the _AI_ is not too important due to the low variation of these emissions with the pre-injection rate, duration and starting instant. On the other hand, SFC and NOx emissions are more sensitive. A representative quantity of pre-injection is necessary, specifically 20%, due to the important reduction on NOx emissions. Nevertheless, if this pre-injection rate is increased, it leads to important increments in SFC and, to a lesser extent, CO and HC emissions. Regarding the pre-injection instant, early pre-injections are appropriate to reduce NOx but the increase increment in SFC is considerable; for this reason, a -19\({}^{\circ}\) CA ATDC was obtained. Finally, the injection duration mainly affects to NOx and short injections lead to considerable NOx reductions. The goal of NOx reduction using pre-injections is to control the combustion temperature. It is well known that high combustion temperatures promote NOx formation [56]. In order to control the combustion temperature, it is necessary to rigorously inject the fuel at the optimum instant. It is worth mentioning that in practical applications it is not possible to reduce the injection duration at the desirable level. For instance, the present engine is a four-stroke medium-speed model which runs at 500 rpm, which corresponds to 0.00033 s to reach \(1^{\circ}\) CA. Some current piezo-injectors are able to switch on and off in tens of microseconds but solenoid or electromagnetic injectors have longer response times. For this reason, pre-injections shorter than \(1^{\circ}\) CA were not analyzed in the present work. Using \(1^{\circ}\) CA pre-injection duration, the _AI_ is represented in Figure 4. As can be seen, the minimum value of _AI_, \(-0.0122\) is reached using 20% pre-injection rate and \(-19^{\circ}\) CA ATDC pre-injection starting instant, as indicated above. The consumption against the pre-injection rate and starting instant is shown in Figure 5. This figure refers to \(1^{\circ}\) CA pre-injection duration. As can be seen, early pre-injections promote considerable increase increments in SFC, as indicated above. On the other hand, the pre-injection rate also promotes increase incr  
Figure 4: _AI_ against \(R\) and \(S\). Pre-injection duration \(1^{\circ}\) CA.