esa-sceva/satcom-chunk-collection huggingface dataset:
# Nonlinear Maximum Power Point Tracking Control Method for Wind Turbines Considering Dynamics
## 4 Deficiencies of the Conventional MPPT Method from Other Perspectives
### Neglecting the Variations of Kinetic Energy Stored in the Rotor and Generator  
Apart from the mechanical transmission loss and the electromagnetic loss, rotating parts will absorb or release kinetic energy while converting wind energy into electric energy. The power flow of the wind energy generation systems is:  
\[P_{\text{m}}=P_{\text{L}}+P_{\text{e}}+\Big{(}I_{\text{r}}+n^{2}J_{\text{g}} \Big{)}\omega_{\text{r}}\dot{\omega}_{\text{r}} \tag{31}\]  
where, \(P_{\text{L}}\) represents the mechanical transmission power loss and the electromagnetic power loss; \(P_{\text{e}}\) represents the electric power; \(\Big{(}I_{\text{r}}+n^{2}J_{\text{g}}\Big{)}\omega_{\text{r}}\dot{\omega}_{ \text{r}}\) represents the derivative of kinetic energy stored in rotor and generator.  
Figure 3 describes the power flow of the wind energy generation system. The rotating parts (rotor, generator, gearbox, and so forth) in VSWTs serve as energy storage devices that extract energy from the wind while accelerating and release kinetic energy to the grid while decelerating. As the growing moment of inertia of rotating parts, the speed for rotating parts to extract and release energy will slow down, which means slower dynamic response to wind variations. Actually, the goal of MPPT control is to regulate the instantaneous aerodynamic power instead of the instantaneous electric power to the  
Figure 2: The inertial response time \(\tau\) versus the generator speed \(\omega_{\text{g}}\) using the analytical and the numerical method.  
optimal value. Conventional OT and PSF method set instantaneous electric power to optimal value and neglect the variations of kinetic energy stored in rotating parts assuming the VSWTs' response to wind variations is fast enough. However, response time is needed for the dynamic process of instantaneous aerodynamic power (or torque) to reach the setting instantaneous electric power (or torque). There exists significant power loss in that process. It is valuable to find a novel wind turbine MPPT method to shorten the dynamic process for instantaneous aerodynamic power (or torque) to reach the set value.
# Precise Positioning of Autonomous Vehicles Combining UWB Ranging Estimations with On-Board Sensors
## 4 Design of the Outdoor Positioning System
### Proposed Algorithm for Post-Processing the UWB Ranging Estimates
Then, the travelled distance, \(\triangle_{k-n\to k}\), by the vehicle between \(k-n\) and \(k\) is calculated from the odometry data. Finally, a maximum and a minimum limit can be obtained in order to classify the UWB ranging estimate. \[max\_distance_{k}=\rho_{k-n}+\triangle_{k-n\to k}. \tag{7}\]  
\[min\_distance_{k}=\rho_{k-n}-\triangle_{k-n\to k} \tag{8}\]  
The evaluated UWB ranging estimate should be between both limits. However, knowing that the RC car position has a certain amount of error and that the ranging estimates usually present an uncertainty with regard to the real distance, these limits are increased by a constant value \(C\). \[min\_distance_{k}+C\leq\hat{\rho}_{k}\leq max\_distance_{k}+C \tag{9}\]  
If the UWB ranging estimate is not situated between these limits, it is classified as an NLOS UWB ranging estimate and discarded, not applying the correction phase of the EKF.
## 3 Experimental Results and Analysis
### Experimental Analysis
#### 3.3.5. Experimental Analysis and Comparison
TfNet (named only in this article) involves multi-view triangulation, satellite localization network, landmark regression network, and pose solver, which are relatively complex. It can be seen from Table 8 that six groups of experiments were completed, and the results fluctuate within a certain range, which proves the stability and generalization ability of the model. The orientation accuracy of the proposed method is much better than that of LSPnet, while the translation accuracy of the proposed method is almost the same as that of LSPnet, which proves the superiority of the proposed method under the same processing flow. The orientation accuracy of the proposed method is better than that of SPN, and the translation accuracy of the proposed method is worse than that of SPN. However, the proposed method is simpler than that of SPN in processing flow. Compared with TfNet, the method is poor in pose estimation accuracy and far superior to TfNet in inference speed, which satisfies the requirements of real-time detection.
## 1 Introduction  
Obesity is a serious disease with an increasing prevalence of epidemics in the Western world, including the United States [1]. Obesity-related diseases have been known through numerous reports so far, and the resulting complications have a significant negative impact on the quality of life of modern people [2, 3, 4]. Moreover, adipose tissue is an important regulator of whole-body metabolism and energy homeostasis [5].  
Adipogenesis is the process of generating mature adipocytes from preadipocytes and was based on studies using murine preadipocytes, 3T3-L1 cells, to accelerate lipid accumulation [6]. When differentiation of preadipocytes begins, specific transcription factors are combined to induce the expression of differentiation initiating factors [7, 8]. Excessive action of carbohydrate absorption and insulin signaling in the body accelerates lipogenesis in adipocytes. Acetyl coenzyme A (acetyl-CoA), which plays an important role in the tricarboxylic acid (TCA) cycle during lipogenesis, moves from the intracellular mitochondrial membrane to the cytoplasm. Acetyl-CoA is also involved in the production of fatty acid (FA) and is converted to malonyl-CoA under the influence of the multifunctional enzyme acetyl-CoA carboxylase (ACC) [9]. In the body, not only the accumulation of fat but also the breakdown of fat is regulated by several hormones and various transcription factors [10, 11]. In particular, in the case of the lipolysis process in which TG is degraded, several pathways exist, but the cAMP-PKA pathway leads to the activation of hormone-sensitive lipase (HSL),and the reduction in phosphodiesterase 3B (PDE3B) stands out [12]. Phosphorylated HSL acts on perilipin and leads to the glycerol release of TG [13].  
_Trapa japonica_ Flexov (_T. japonica_) has long been used for food and medicinal purposes. TJ is an annual aquatic plant found in lakes and waters around the world, including Korea, China, India, and North America. _T. japonica_ is also called water chestnut, and it has many varieties such as _Trapa natans_, _T. japonica_, and _Trapa bicornis_. It contains 80% starch, 5% protein as well as a significant amount of vitamins and is reported to have a variety of polyphenols [14]. Based on this, the inhibitory effect of adipogenic transcription factors of _T. japonica_ was recently reported, but only some factors in the mechanism of adipogenesis are dealt with [15]. In addition, _T. japonica_ has been reported to have antioxidant, antidiabetic, and antitumor effects [16; 17; 18]. However, there are limited studies on the regulatory activity of Chinese _T. japonica_ among various metabolic mechanisms related to anti-obesity. In particular, studies on the lipolytic effect in fully mature adipocytes should be explored. Therefore, in this study, we investigated whether a 20% ethyl alcohol extract of Chinese _T. japonica_ had a modulating effect on the mechanisms of adipogenesis, lipogenesis, and lipolysis in differentiated 3T3-L1 cells.
## 2 Materials and Methods
### Data Processing Method  
In this paper, 18 GNSS observation stations in Hong Kong were selected for real-time PPP data processing to explore the positioning performance of real-time PPP and the accuracy of water vapor inversion. IGS ZTD and radiosonde station PWV were used as references to evaluate the accuracy of real-time PPP ZTD and real-time PPP PWV. The average values of bias, standard deviation (STDEV), and root mean square (RMS) were used as precision evaluation indexes.
# Low Temperature Resistance Increase for Bitumen by Compounding with Tar
## 4 Conclusions  
The results of investigations performed in the paper have shown practical possibility for obtaining bitumen of less viscous consistency (P\({}_{25}\) = 170 0.1 mm) by compounding bitumen with penetration grade 100-130 (P\({}_{25}\) = 116 0.1 mm) with tar (conditional viscosity at the temperature of 80 \({}^{\circ}\)C \(v_{\rm c}\) = 82 s) in the amount of 20% by weight. Meanwhile, the following is the case:  
1. The effect of compounding is greater with the decrease in temperature. The tar content equal to 20% by weight is considered as an optimal one when compounding the road bitumen with penetration grade 100-130.
2. At all the tested temperatures (\(-24\)\({}^{\circ}\)C, \(-30\)\({}^{\circ}\)C and \(-36\)\({}^{\circ}\)C), the stiffness of the compounded bitumen is significantly (from 18% to 34%) lower than that of the virgin bitumen, i.e., the compounded bitumen has the increased low temperature stability.
3. The optimal compounding (20% of the tar by weight) increased bitumen penetration by 54 decimillimeters, which changed its original grade 100-130 to 130-200; softening point and viscosity have decreased by 5 \({}^{\circ}\)C and 65%, respectively; Fraas point remained practically unchanged; and ductilityincreased by 10.4%.
4. It has been found by adsorption chromatography that the optimal compounding significantly changes the group chemical composition of bitumen: asphaltenes and resins decreased by 23% and 8.8%, respectively, and oils increased by 11.1%.
5. Reduction in compounded bitumen of solid (asphaltenes) and high-viscosity (resins) components, increase in low-viscosity components (oils), as well as the decrease in the content of methyl groups in them (35.1%), and the increase in the content of quaternary aliphatic carbon atoms (13.4%) increase the mobility of molecules and supramolecular structures, which increases the low-temperature stability of the compounded bitumen.
6. To increase high temperature resistance of the obtained compounded bitumen, it is recommended to modify it with a polymer.  
**Author Contributions:** Conceptualization, B.T.; experiment, B.T., T.S., Y.A. and S.B.; writing--original draft preparation, B.T., T.S., C.O.R. and Y.A. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan, grant No. IRN AP 08857446.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The study did not report any data.  
**Acknowledgments:** The work was performed under grant IRN AP 08857446 from the Committee of Science of the Ministry of Education and Science of the Republic of Kazakhstan. Agreement No. 230 dated 12 November 2020.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Positioning by Multicell Fingerprinting in Urban NB-IoT Networks +
## 5 Performance Evaluation
### Results for the Oslo Dataset
#### 5.2.3 Comparison between Operators  
A direct comparison of the accuracy of the proposed strategies on different networks can be carried out by using the data for the two operators detected in Oslo, i.e., Operator 1 (considered so far) and Operator 2. Since the data of the two operators were collected at the same locations, any difference in performance can be interpreted as operator-specific. The analysis carried out in [3] indicated that Operator 2 has overall roughly 30% less NB-IoT eNBs than does Operator 1 (146 for Operator 1 vs. 107 for Operator 2). This difference is also reflected in the dataset used in this work: 160 unique NPCIs were detected for Operator 1 vs. 139 for Operator 2, and the percentage of valid data points, defined as points where at least one NPCI was detected, is 92.1% for Operator 1 vs. 86.9% for Operator 2. Conversely, the average number of NPCIs detected in locations where at least one NPCI was detected is slightly larger for Operator 2 (6.6) vs. Operator 1 (6.1). The full data are reported in Table 4.  
The analysis for Operator 2 was carried out using the RSRQ parameter and led to the best accuracy for Operator 1, as shown in Table 3. The results are presented in Table 5 and show that the _Enhanced Net_, _Coverage_, and _Weighted Coverage_ provide a similar accuracy for the two networks. Results for the _Net_ and _Single Cell_ strategies show, however, a markedly worse performance when considering Operator 2; since they are the strategies using less information (no RF information for _Net_, only one NPCI for _Single Cell_),  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Operator 1** & **Operator 2** \\ \hline Unique NPCIs & 160 & 139 \\ \hline Valid data points & 4848 & 4577 \\ \hline Valid data points (\%) & 92.1 & 86.9 \\ \hline Average number of NPCIs per valid data point & 6.1 & 6.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Comparison between data used for the Operator 1 vs. Operator 2 networks in the Oslo dataset; a valid data point is defined as a data point where at least one unique NPCI was detected for the considered operator.  
Figure 12: Minimum average positioning error as a function of \(N_{NPCI}\) for the proposed strategies using SINR in all strategies but _Net_; the _Single Cell_ was not analyzed since, by definition, it operates with \(N_{NPCI}=1\).  
that strategies that use more information are not only more accurate but also more robust to information loss.
# XCT and DLW: Synergies of Two Techniques at Sub-Micrometer Resolution
## 4 Conclusions  
Measurements of DLW structures with XCT/XRM have been a less studied field although both methods can clearly enrich each other. In this study, we have shown two similar sample geometries, including one where the XCT was used to analyse for hidden faults, which stem from the DLW fabrication process. It was demonstrated that XCT can identify sub-micron DLW-fabricated structures sufficiently, and thereby, can act as a feedback tool. Internal, hidden structures (fabrication flaws) could be observed, which are not detectable by other techniques such as SEM because of the 3D nature of the complex printed object. At sample 2, we could determine the time at which the structural fault occured. Additionally, sample 2 was used to determine the XCTs resolution along the fabricated infill lines. Thus, we could gather additional information by XCT that helped to verify the hypothesis on the origin of certain imperfections, and act accordingly, adjusting the DLW printing parameters. By using infills and Cura software, it was possible to reduce the total production time of a solid pyramid by 81%. XCT was essential to fine-tune the fabrication parameters. However, an adjustment of the DLW sample preparation route was needed for XCT imaging, in particular, by picking a PET-polymer substrate and a modified DLW process. The shown fabrication route on a PET substrate resulted in a stable process with a high contrast in the XCT compared to the previously used glass substrates. Therefore, XCT is a valuable tool in the quality assurance of DLW structures. Future imaging applications (XCT) for DLW may include studies on the residue of photoresist in microchannels or an internal analysis of microrobotic structures. Finally, we have reflected the usage of the shown structure for XCT phantoms. However, additional studies are needed for a robust and reproducable manufacturing of said phantoms.  
Conceptualization, S.F. and A.F.; methodology, S.F.; software, S.F. and A.F.; validation, S.F., A.F., L.P. and G.-R.J.; resources, S.F.; data curation, S.F.; writing--original draft preparation, S.F.; writing--review and editing, S.F. and A.F. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors declare no conflict of interest.
# Unsteady State Lightweight Iris Certification Based on Multi-Algorithm Parallel Integration
## 4 Experiments and Analysis  
**Data acquisition:** The JLU iris library of Jilin University, China [36] and CASIA iris library of Chinese Academy of Sciences, China [37] are used in all experiments in this paper. The JLU iris library is collected by the Biometrics and Information Security Technology Laboratory of Jilin University and generated by video screenshots. As of 2019, there are more than 80 categories of irises in the original iris library, and each category has more than 1000 images of various states. The number of images of unsteady irises is still expanding. The CASIA Iris Library is a commonly used iris library in the world of iris recognition and has been released for four generations.  
**Experimental external environment:** In the experiments, the CPU frequency is dual-core 2.5 GHz, the memory is 8 GB, and the operating system is Windows.  
**Evaluation metrics:** The evaluation indexes are the ROC curve [38] (a curve indicating the relationship between the False Reject Rate (FRR) and the False Accept Rate (FAR)), the Equal Error Rate (EER) (the value where FRR is equal to the FAR), and Correct Recognition Rate (CRR) [39].  
**Experimental setup:** The experiments first self-certified the contribution of each layer to the certification and explained the relationship between the algorithm settings of each layer and the actual prerequisites. As set out in Section 4.1, the image processing layer experiment is mainly concerned with the extraction of defocused conditions, and explores the effect of extracted iris texture on iris certification; as set out in Section 4.2, feature recognition layer experiment was mainly designed to conduct tests on iris deflection and explore its impact on iris certification. As explained in Section 4.3, the decision layer experiment aimed mainly to test for the presence or absence of illumination and explore the impact of the statistical decision-making method based on external illumination on iris certification. Finally, a comprehensive experiment is set out in Section 4.4. As set out in Section 4.4.1, the actual effect of the overall model is tested, which can explain how the algorithm structure improves the overall recognition rate in the case where the traditional algorithms are used in each layer. As set out in Section 4.4.2, the performance of the algorithm is analyzed by comparing it to existing algorithms according to the prerequisites of this paper.
# Dynamic Performance of Soil-Tunnel System under Transverse Sinusoidal Excitations
## 2 Test Design
### Refined Lining Ring of Model Tunnel
#### 2.4.2 Stiffness of Model Tunnel  
Following the geometric similitude rule, the diameter of model tunnel is 933 mm, and the thickness of a segment is 40 mm. Segments were poured by cement mortar. To get the targeted transverse stiffness of model lining, steel wires and rubber strips were applied to reproduce circumferential bolts and sealant of longitudinal joints, as Figure 5 displays. According to the principle of tensile stiffness equivalent, circumferential bolts were replaced by 3 steel wires with a diameter of 2.5 mm. The layout of the steel wires imbedded in the segmental linings corresponds with the position of the bolt holes in the prototype tunnel.  
In this paper, the radial stiffness of the segmental lining is obtained by multi-stage loading test along a 45-degree direction of tunnel's cross-section. The vertical displacement at the top of the segmental lining was observed by LVDT Transducer, as shown in Figure 6a [3]. In order to decrease the random errors, the final datum is the mean value of 3 group test data. Seven-stage loading was employed in the test. The weight of a loading block is 0.05 kN in each stage. The test results are shown in Figure 6b. According to the test results, the mean value of 3 group test data gives stiffness of the model tunnel as 23.10 N/mm. A numerical model was established to simulate the loading test. The parameters of joints in the numerical model can be calibrated by this loading test. According to the Figure 4, a horizontal concentrated load is applied to the top of the calibrated model. Finally, the transverse stiffness of the model lining can be obtained.  
Figure 4: Sketch of the numerical simulation model.  
Figure 5: Model ring of segmental lining. (**a**) Steel wire. (**b**) Sealant in an assembled ring.
# FE-Aided Synchronization Analysis of Line-Start Synchronous Reluctance Motors
## 1 Introduction
This is an important advantage because the installation space of an electric motor in a larger device could remain the same even considering the upcoming IE4 efficiency regulations. The European commission has announced that IE4 efficiency regulation will be applied to 0.12 kW-1000 kW rated motors from July 2023 [13]. The author expects that the efficiency regulation in the other regions will be further tightened after 2023. The IE4 motor market growth will encourage motor manufacturers to develop IE4 efficiency motors; therefore, the negative impacts from new efficiency regulation can be minimized. Despite the efficiency advantage of LS-SynRMs, they are subject to issues in the synchronization process just as LSPMs are. Nowadays, the synchronization process can be simulated using circuit-field torque-coupled finite element analysis (FEA) to predict successful start-up of line-start synchronous motors. However, the algebraic formulations described in [14; 15; 16; 17] are still useful to approximate the synchronization process because numerical analysis by the FEA is computationally expensive. A relatively simple criterion for determining the synchronizing ability of LS-SynRMs is reported in [18]. Effort has also been made in [8] using a lumped parameter model to approximate the transient state of a LS-SynRM; however, the model was not accurate when compared to the FEA results. To the best knowledge of the author, aside from the work above, the synchronization process of LS-SynRMs (characterized by multiple flux barriers) has been simulated in the design state using circuit-field-torque coupled FEA [9; 10; 11; 12; 19; 20] without an alternative approach. The reason for this may be that accurate estimation of the rotor parameters of a LS-SynRM is challenging due to the complicated rotor geometries. The saturation and variation of the rotor resistance must be accounted for, as stated in [8]. This paper provides an FE-aided analytical approach to approximate the synchronization process of LS-SynRMs. It explains the vulnerability of LS-SynRMs in the synchronization process when compared to LSPMs. Instead of parametric analysis, a numerical methodology is proposed that combines FEA with an analytical approach to approximate steady state torque as a function of slip. This is applied to predict the synchronization ability of LS-SynRMs. The result obtained using the proposed method is compared with that obtained using FEA.