esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Development of RF WPT-Enabled IoT Application
### Implementation and Experimental Validation
#### 3.4.1 Selection of a Sensor Node
To enable the energy harvesting supply, the node is equipped with a DC-DC converter, which can convert an input voltage from 0.1 V to over 5 V to a stable DC voltage in the range from 2 to 3.6 V. Importantly, having the ten \(\upmu\)A current on its input, the converter demonstrates the efficiency of over 80%. As the energy buffers, the tantalum capacitors storing up to 10 J of energy storage in total are used. A sensor node also has the place for a single CR2032 lithium battery, which can be used as an alternative or a backup power source option. The node is equipped with an instrumental-grade external analog-to-digital converter and with low-consuming environment sensor (i.e., temperature and humidity) and three-axis acceleration sensors. For this node, we have developed the firmware, making the sensor node measure the acceleration, process it (i.e., calculate the Fast Fourier transform (FFT) to estimate the speed of rotation) and the temperature, and send them twice a second in BLE advertisements. The practical energy consumption profile of the node for this specific application, which was measured with an Agilent N6705 power analyzer (Santa Clara, CA, USA) and then visualized in MATLAB, is depicted in Figure 5. The data processing and communication phases, and the key numbers related to the consumption are shown in the picture. One can see that the mean power required for stable operation of the system is 1.36 mW. Figure 3: An integrated sensor node by Solmu Technologies. This consumption is higher than the one we expected and used in our feasibility analysis. The three reasons for it are the higher consumption of the sensors, the extra consumption for preparing the packets for the BLE, and, especially notable, the additional consumption for signal processing. The calculation of the FFT required quite substantial processing, which also brought along with it the  
Figure 4: Structure of the sensor node. Figure 5: Measured power consumption profile of the sensor node. extra consumption. Nonetheless, one can see that, even with this consumption, the application stays feasible for WPT in h1.6, even though the communication range will likely decrease to below 1.5 m.
## 1 Introduction
For the TDPO method, the only need is to calculate the induced electromagnetic current on the surface of the target, and then integrate it. Although it is difficult to deal with the multiple reflections [25; 26; 27; 28], its accuracy is also acceptable if the surface is large enough and located in a far-field region. The TDSBR method combines the advantages of the geometric optics (GO) method and PO method [29; 30; 31; 32], so the accuracy of TDSBR is better than that of TDPO. However, at least 10 ray tubes per wavelength are needed to build a TDSBR instrument. As the frequency increases, the computational complexity and time required for TDSBR increase. Although the time-domain, high-frequency approximation methods can speed up the solution, their accuracy for complex problems such as multi-scale structures is still poor. According to the characteristics of the above methods, the DGTD method has more advantages than FDTD, FETD and FVTD in complex geometry modeling, time domain integration and accuracy, and TDPO is simpler and faster than TDSBR. Consequently, in this paper, a hybrid DGTD/TDPO method is proposed to improve the efficiency of the DGTD method in the calculation of transient electromagnetic scattering from multi-scale composite targets. The DGTDPO hybrid method avoids the step error of the FDTD/PO hybrid method when solving unstructured grid problems. At the same time, compared with the MoM/PO hybrid method, this hybrid method can avoid the low frequency breakdown of MoM. In fact, the DGTDPO hybrid method is not only valuable in the area of electromagnetic scattering, but also a great prospect for the study of electrochemical hydrogen evolution [33], the buckling and flexural vibration analysis of plates with intermediate supports [34] and the nonlinear vibration of fluid flow in single-walled carbon nanotubes [35]. In this work, a discontinuous Galerkin time domain solver (DGTD) is hybridized with the TDPO method for the first time to analyze transient multi-scale and composite objects' scattering problems. The proposed hybrid method possesses the advantages of both DGTD and TDPO. Numerical results demonstrate that the accuracy and efficiency of the proposed method are good enough in various scattering scenarios. The paper is organized as follows. The formulations of DGTDPO hybrid method are reported in Section 2. Numerical results aimed at validating the advantages of proposed hybrid method for multi-scale and multi-targets composite transient electromagnetic scattering are provided in Section 3. Finally, conclusions are drawn in Section 4.
## 3 Results
### Results of the Sensitivity to Environmental Domains  
A total of 146 participants completed the questionnaire on environmental domains. In general, most of the questionnaires were filled out by caregivers, followed by parents, and only to a small extent by people on the autism spectrum (Table 3).  
From the analysis of the questionnaire answers, it emerged that the thermal, visual, and indoor air quality (IAQ) topics showed the same trend. It can be seen that the majority of people on the autism spectrum were not particularly sensitive (\"not at all\") to the variations of these parameters. Conversely, acoustic perception showed a different trend, where more than 80% of the people on the autism spectrum were classified as \"minorly\", \"averagely\", or \"extremely\" sensitive to this environmental factor. The sensitivity of the \"sporadic\" type was about 5% for all 4 comfort domains (Figure 3). In this paper, only general results on the four comfort domains are reported, while a complete analysis of all the questions explored in the sensitivity questionnaire is reported in [36; 37].  
\begin{table}
\begin{tabular}{c c c c c} \hline  & **Participants** & **Local Survey** & **Online Survey** & **Total** \\ \hline \multirow{4}{*}{Respondents} & People on the AS & 3 & 5 & 8 \\  & Caregivers & 41 & 38 & 79 \\  & Parents & 26 & 33 & 59 \\  & Total & 70 & 76 & 146 \\ \hline \multirow{4}{*}{Gender distribution} & Female & 19 & 29 & 48 \\  & Male & 49 & 44 & 93 \\ \cline{1-1}  & Other & 2 & 3 & 5 \\ \cline{1-1}  & Total & 70 & 76 & 146 \\ \hline \multirow{4}{*}{Autism severity distribution} & Low severity & 33 & 23 & 56 \\  & Medium severity & 24 & 21 & 45 \\ \cline{1-1}  & High severity & 13 & 32 & 45 \\ \cline{1-1}  & Total & 70 & 76 & 146 \\ \hline \end{tabular}
\end{table}
Table 3: Overview of participants from the questionnaire on environmental domains.  
Figure 2: User day of a fictive person on the autism spectrum.  
The special sensitivity to environmental stimuli of people on the autism spectrum allowed for the development of requirements and suggestions for the SENSHOME solution. It contributed to understanding which rooms of living environments are most risky for people on the autism spectrum.
## 2 Results
### DksA and (p)ppGpp Inhib Ribosomal Synthesis and Regulate Metabolic Networks  
The main hallmark of the stringent response is the suppression of ribosome production. In \(\Delta\)_dkSA_ and \(\Delta\)_relA\(\Delta\)_spoT_, the expression of 43 and 50 ribosomal DEGs, respectively, was significantly increased (FC \(>\) 2 and \(p\)-adjust \(<\) 0.05). Of these DEGs, 42 were found to be jointly controlled by both DksA and (p)ppGpp (Table S3), implying a shared regulatory mechanism. Notably, the deletion of _dkSA_, _relA_, and _spoT_ led to lower expression levels of 30 DEGs involved in ribosomal synthesis compared to \(\Delta\)_dkSA_ or \(\Delta\)_relA\(\Delta\)_spoT_ alone. These results indicate that the regulatory pattern of ribosome synthesis is realized through site 2 of RNAP, which requires both (p)ppGpp and DksA.  
Previous research had highlighted the essential role of (p)ppGpp or DksA in the growth of _Erwinia amylovora_ and _Salmonella enterica_[28; 29]. In this study, pathway enrichment analysis revealed that the TCA cycle, fatty acid degradation, and carbon fixation pathways of \(\Delta\)_dkSA_, as well as the purine metabolism pathway of \(\Delta\)_relA\(\Delta\)_spoT_ were significantly inhibited (Figures 4 and 5). These pathways are involved in carbon source utilization and likely contribute to the slower growth of mutant strains in LBNS medium (Figure 6A). Our analyses thus suggest that both DksA and (p)ppGpp act to regulate metabolic networks while inhibiting genes involved in ribosome biosynthesis.  
Figure 3: Validation of candidate DEGs by RT-qPCR. (**A**) Gene transcription in \(\Delta\)_dkSA_. (**B**) Gene transcription in \(\Delta\)_relA\(\Delta\)_spoT_. (**C**) Gene transcription in \(\Delta\)_dkSA_relA\(\Delta\)_spoT_. The data are the means and SEM from three independent RT-qPCRs.  
Figure 4: The model for the cellular processes of \(\Delta\)_dksA_. Red, green, and black indicate significant upregulation (FC > 2 and \(p\)-adjust < 0.05), significant downregulation (FC < 0.5 and \(p\)-adjust < 0.05), and no significant regulation (0.5 \(\leq\) FC \(\leq\) 2 or \(p\)-adjust \(\geq\) 0.05), respectively.  
Figure 5: The model for the cellular processes of \(\Delta\)_relAAspoT_. Red, green, and black indicate significant upregulation (FC > 2 and \(p\)-adjust < 0.05), significant downregulation (FC < 0.5 and \(p\)-adjust < 0.05), and no significant regulation (0.5 \(\leq\) FC \(\leq\) 2 or \(p\)-adjust \(\geq\) 0.05), respectively.
# Positioning-Based Uplink Synchronization Method for NB-IoT in LEO Satellite Networks
###### Abstract  
With the growth of Internet of Things (IoT) business demands, NB-IoT integrating low earth orbit (LEO) satellite communication systems is considered a crucial component for achieving global coverage of IoT networks in the future. However, the long propagation delay and significant Doppler frequency shift of the satellite-to-ground link pose substantial challenges to the uplink and downlink synchronization in LEO satellite-based NB-IoT networks. To address this challenge, we first propose a Multiple Segment Auto-correlation (MSA) algorithm to detect the downlink Narrow-band Primary Synchronization Signal (NPSS), specifically tailored for the large Doppler frequency shift of LEO satellites. After detection, downlink synchronization can be realized by determining the arrival time and frequency of the NPSS. Then, to complete the uplink synchronization, we propose a position-based scheme to obtain the Timing Advance (TA) values and pre-compensated Doppler shift value. In this scheme, we formulate a time difference of arrival (TDOA) equation using the arrival times of NPSSs from different satellites or at different times as observations. After solving the TDOA equation using the Chan method, the uplink synchronization is completed by obtaining the TA values and pre-compensated Doppler shift value from the terminal position combined with satellite ephemeris. Finally, the feasibility of the proposed scheme is verified in an Iridium satellite constellation. Compared to conventional GNSS-assisted methods, the approach proposed in this paper reduces terminal power consumption by 15-40%. Moreover, it achieves an uplink synchronization success rate of over 98% under negative SNR conditions.  
NB-IoT; non-terrestrial network; uplink synchronization; timing advance; time difference of arrival +
Footnote †: journal:
# WSN Nodes Placement Optimization Based on a Weighted Centroid Artificial Fish Swarm Algorithm
## WSNs Nodes Optimal Placement Based on WCA-AFSA  
### Example of a Wind Turbine Blade  
For a one megawatt level horizontal axis wind turbine blade, the length is 29 m. The blade material is glass fiber reinforced plastic. The density is 1950 kg/m\({}^{3}\). The modulus of elasticity is 16.5 GPa. The Poisson ratio is 0.305. The first five mode shapes are shown in Figure 7. The first five mode frequencies and their mode shape features are listed in Table 2.  
Figure 6: Results comparison of WCA-AFSA with AFSA.  
The low order modes have major mode shapes contribution and can describe the structure dynamic characteristics. Thus, the first five modes are selected as the target modes. The low order modes are mainly in the form of waving vibration. The sensor placement focuses on the waving vibration. The sensor placement focuses on the waving vibration. The waving vibration is a high-order mode shape. The waving vibration is a high-order mode shape.  
direction (Y direction in Figure 7) which is the main degrees of freedom (DOFs). There are a total of 1073 nodes (DOFs). Considering the difficulty of placing sensors in blade tip, the 36 DOFs in the blade tip are negligible. Therefore, there are a total of 1037 nodes (DOFs) which participate in computation. The first five mode matrix \(\mathbf{\phi}\) is a 1037 \(\times\) 5 matrix.  
Here, we place 10 WSNs nodes sensors. Figure 7(a),b shows the _MAC_ bar graph by AFSA and WCA-AFSA, respectively. Their maximum off-diagonal elements are 0.122655 and 0.008995 respectively. The values of _MAC_ by AFSA and WCA-AFSA are shown in Tables 3 and 4. The above result shows that the improved algorithm has better performance.  
The sensors in this placement scheme distribute dispersedly. The scheme avoids the sensors' local aggregation. Here, sensors are placed in the blade root and other large deformable airfoil locations, which are most in poor conditions. Data from these locations can comprehensively reflect the blade health state.
## 3 Results and Discussion
### Pyrolysis Gas Chromatography Mass Spectrometry (Py-GC/MS)
The increase in the LG/polysaccharides ratio at T1 may correspond to the microbial activity producing a preferential degradation of carbohydrates and less condensed lignin units. On the other hand, the total lignin peaks increase during the first year of composting (T0-T2), and a reduction of LG units is observed at expenses of the LS with a decrease in the LG/LS ratio. These trends corroborate that the celluloses in maize residues are preferentially degraded, leaving a residue enriched in lignin. Non-oxidized alkyl-phenols, defined as Ph-C1, Ph-C2, and Ph-C3, are identified as 4-methylguaiacol, 4-ethylguaiacol, 4-vinylguaiacol, and 4-propylguaiacol. An increase in the sum of the relative abundance of non-oxidized alkyl phenols points to the selective preservation of some constituents of the lignin macromolecule in the compost pile. An increase in the relative abundance of higher oxidation degree G-compounds (vanillin, acetovanillone, and vanillic acid methyl ester; guaiacylacetone, propiovanillone) suggest an oxidative action resulting from the decomposition process of compost [54]. This may come from either oxidation or oxidation followed by cleavage of the C3 alkyl chain from G units at the C\(\alpha\) and C\(\beta\) position. An indicative of this oxidative attack could be the observed decrease in the (aldehyde/ketone + acid) (Al/K + Ac) ratio. In this case, the Al/K+Ac ratio decreases, except for a rise during T3. An increase in the (Ph-C1 + Ph-C2/Ph-C3) ratio, along with an increase in Ph-C2 compounds and a decrease in Ph-C3 compounds, may indicate the ability of decomposition process in compost not only to oxidize lignin but also to breakdown the C3 side alkyl chain linkages. There is a final increase in this ratio, followed by a constant increase in Ph-C2 compounds, which may indicate this decomposition process in compost.
## 4 Discussion  
As an important physiological indicator of plants, variations in chlorophyll SPAD, leaf temperature, green-peak and red-valley reflectance, and Fv/Fm are closely related to changes in stomatal aperture, leaf water content, photosynthetic activity, and enzyme activity [49; 53]. As plants are exposed to SO2, photosynthesis is inhibited and chlorophyll is converted to demagnetized chlorophyll [54]. The limitation of photosynthesis can be divided into stomatal and non-stomatal factors [55; 56], with the stomatal factor showing a decrease in Gs (stomatal conductance) and insufficient CO2 supply and the non-stomatal factor, demonstrating a reduction in the activity of key enzymes for photosynthesis. If Pn decreases along with Gs and Ci, stomatal factors are likely responsible, and if Pn decreases as Ci increases, the main limiting factors for photosynthesis seem to be non-stomatal factors. The chlorophyll content, leaf temperature, green-peak reflectance, and Fv/Fm at 10 days were significantly lower than those at 40 days, regardless of the sampling date or SO2 concentration. The SO2 resistance for the 10-day leaves was consistently lower than for the 40-day leaves.  
Juveniles of most plants are more sensitive to environmental changes and extremes, even in resilient species. This is because they require a more suitable environment to re-establish a fully independent SPAC system from a dormant state that is isolated from the soil and atmosphere. Some plants are salt-tolerant to the point of being salt-loving, and moderate salinity is beneficial to their growth [18]. However, the seed germination of these plants is sensitive to salt, and rainfall and other salinity-eluting environments are more conducive to seed germination. The fragile tissue structure and low lignification of seedlings of some tree species makes them vulnerable to adverse effects, such as extreme low temperatures and summer droughts.  
The stomatal opening of red-leaved _P. cersifera_ was the largest and the least vulnerable to SO2 damage. [PERSON] [57] also found that the stomata of the lightly damaged parts of leaves were more open during the examination of the damage caused by SO2 on plants. This study also concluded that red leaves of _P. cersifera_ were slightly damaged, followed by _S. oblate_ with green leaves, while _U. pumila_ with yellow leaves were the most damaged. Significant differences in the stomatal aperture values were also observed. Red-leaved tree species with large stomatal aperture values have a stable metabolic balance of water and energy, excellent growth conditions, resistance to adversity, and ability to resist atmospheric pollution.
## 1 Introduction
[PERSON] [19] adopted a balanced Jeffcott rotor model of a hydropower generator and studied the dynamic consequences of UMP due to shape deviations on the rotor and stator. [PERSON] [20] investigated the nonlinear dynamic behaviors influenced by UMP and analyzed the stiffness characteristics of the rotor system of the PMSM based on a Jeffcott rotor model. [PERSON] [21] analyzed the dynamic characteristics of a rotor-bearing system considering the rub-impact on the hydraulic generating set under the UMP, and the analysis focused on the effects of the excitation current, eccentricity, and stiffness of shaft. Almost all the papers mentioned above used a symmetrical Jeffcott rotor as a simplified model to analyze the dynamic characteristics of a PMSM. In many practical applications, the rotor is not always in the middle of the shaft, which means that the gyroscopic effect needs to be taken into consideration. Some researchers have studied the influence of the gyroscopic effect on the rotor system, and the results have showed that the influence cannot be ignored [22; 23]. The models adopted in their research were based on the assumption that the supports were rigid. In a PMSM, the supports of the shaft are always elastic due to the influence of the bearings, and it is necessary to take these elastic supports into consideration. The purpose of this paper is to investigate the nonlinear dynamic characteristics of the rotor-bearing system in a PMSM. In this paper, we consider the influence of UMP and the gyroscopic effect. In Section 2, the radial air-gap flux density of an eccentric rotor is analyzed based on the early research [24; 25; 26; 27]. In Section 3, the dynamic model of the rotor bearing system is presented under the influence of UMP and bearing forces. In Section 4, the nonlinear dynamic characteristics of the system are investigated and the fourth-order Runge-Kutta method is employed to calculate the nonlinear responses. In addition, the effects of the static eccentricity, rotor offset and radial clearance are analyzed in detail. Finally, the conclusions of this study are presented in Section 5.
# A Laser Irradiation Method for Controlling _Pieris rapae_ Larvae
## 2 Materials and Methods
### Test of the Effect of Laser Irradiation on Pieris rapae Larvae
#### 2.3.3 Experiment 2: Combinations of Different Working Parameters Tests  
Based on the results of the single working parameter tests, the ranges of the four parameters were selected and used to perform tests of various combinations of different working parameters. The four parameters tested in this experiment exerted nonlinear effects on the antifeedant percentage and mortality rate of _P. rapae_ larvae. Therefore, a Box-Behnken design (BBD) was used to perform surface analysis tests with four factors and three levels, as shown in Table 2. The experimental design was created with Design-Expert 10.0.4 (Stat-Ease Inc., Minneapolis, MN, USA), and 29 sets of tests were generated. Therefore, a total of 1800 4 th-instr larvae ((29 + 1(CK)) groups \(\times\) 20 larvae \(\times\) 3 replicates = 1800 larvae) were thus used.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Experiment Number 1**} & \multirow{2}{*}{**Laser Power/W**} & **Irradiation Area \({}^{2}\)/mm\({}^{2}\)** & **Laser Opening Time/s** & **Irradiation Position 3** \\ \hline
1 & 1 & 0.01 & 2 & Middle \\
2 & 2.5 & 0.01 & 2 & Middle \\
3 & 5 & 0.01 & 2 & Middle \\
4 & 7.5 & 0.01 & 2 & Middle \\
5 & 10 & 0.01 & 2 & Middle \\
6 & 5 & 0.01 & 2 & Middle \\
7 & 5 & 0.79 & 2 & Middle \\
8 & 5 & 3.14 & 2 & Middle \\
9 & 5 & 7.07 & 2 & Middle \\
10 & 5 & 0.01 & 0.5 & Middle \\
11 & 5 & 0.01 & 1 & Middle \\
12 & 5 & 0.01 & 2 & Middle \\
13 & 5 & 0.01 & 3 & Middle \\
14 & 5 & 0.01 & 2 & Head \\
15 & 5 & 0.01 & 2 & Mesothorax \\
16 & 5 & 0.01 & 2 & Middle \\
17 & 5 & 0.01 & 2 & End \\ Control group (CK) & – & – & – & – \\ \hline \hline \end{tabular}
\end{table}
Table 1: List of working parameters used in 18 groups of single factor laser irradiation experiment.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Factors**} & \multicolumn{3}{c}{**Factor Levels 1**} \\ \cline{2-4}  & \(-\)**1** & **0** & **1** \\ \hline Laser power/W & 1.5 & 4.5 & 7.5 \\ Irradiation area/mm\({}^{2}\) & 0.79 & 3.93 & 7.07 \\ Laser opening time/s & 0.5 & 1.5 & 2.5 \\ Irradiation position 2  & Head & Mesothorax & Middle of abdomen \\ \hline \hline \end{tabular}
\end{table}
Table 2: Combined experiment table based on the experimental results of a single working parameter designed by the Response Surface Methodology (RSM).  
After the tests, optimization analysis on response surface was carried out by BBD experimental design method. It identified the optimal parameter combinations by the multiple quadratic regression equation fitting each independent variables and dependent variables.