esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
### Nitrogen Effects on Egg Parasitoids  
Hymenoptera parasitoids cause significant mortality to planthopper eggs [65; 66; 67]. Using field cages in Indonesia that excluded different components of arthropod natural enemy communities, [PERSON] et al. (2002) [65] estimated that egg parasitoids reduced BPH populations by approximately 50%, with predatory bugs and spiders further reducing populations to below 1% of their potential. Furthermore, a number of studies have indicated that egg parasitoids respond to egg densities at plant and batch scales [66; 68; 69]. In the present study, egg parasitism by _Oligosita_ spp. was also density dependent at the plant scale (Table 2). Adult _Oligosita_ spp. and _Gonatocerus_ spp. occurred in higher numbers at low-nitrogen plots, where phloem-feeding herbivores were also more abundant (Figure 1D). However, the parasitism of eggs in sentinel plants was generally higher in high-nitrogen plots (i.e., _Oligosita_ spp. with WBPH--Figure 3; _Oligosita_ spp. with BPH--Figure 4; _Anagrus_ spp. with BPH--Figure 4). Discrepancies between the results of sweep-net sampling and sentinel plants are probably due to the diversity of _Oligosita_, _Anagrus_ and _Gonatocerus_ species in the rice ecosystem. For example, _Gonatocerus_ spp. were relatively common in sweep nets in the wet season, but egg parasitism by _Gonatocerus_ was low (i.e., \(<\)1%) each season, suggesting that most of the _Gonatocerus_ spp. captured in sweep nets were parasitoids of arthropod eggs other than BPH, WBPH or GLH.  
[PERSON] et al. (1981) [70] identified several egg parasitoids of planthopper and leafhopper eggs in Luzon that included _Mymar tapobanicum_ ([PERSON]) and _Polynema_ sp. (Mymaridae), and _Stephanodes_ sp. (Trichogrammatidae) that we did not detect among parasitized eggs. Furthermore, [PERSON] et al. (2018) [71] have shown that the diversity of _Anagrus_ and _Gonatocerus_ species that parasitize BPH and GLH (and presumably WBPH) in the Philippines is underestimated because of the occurrence of several cryptic species. Because the results from sentinel plants are directly related to parasitoid function, our results indicate that egg parasitism by _Oligosita_ spp. in particular is higher under high-nitrogen conditions (Figures 2-4) and therefore likely stabilizes nitrogen-induced increases in planthopper populations. Although the number of WBPH eggs in sentinel plants was not statistically significantly affected by nitrogen content (Table S1), slightly higher numbers in the high-nitrogen plants, together with apparent density dependent parasitism [66; 68; 69], may have contributed to the higher rates of parasitism estimated for high-nitrogen plots; however, the association was not apparent in all experiments (Table 2), thereby suggesting that semiochemical lures also contributed to the effect in all cases. Because _Oligosita_ spp. were the most abundant parasitoids and are responsible for higher parasitism rates compared to other parasitoids (i.e., _Anagrus_ spp.) in Philippine rice fields, and based on evidence for the involvement of semiochemical lures, then our results support the Optimal Defense Hypothesis.
## 2 System Model and Problem Formulation  
We consider a WPCN system with WET on downlink and WIT on uplink, as discussed in [5]. The network consists of a base station (BS) with a hybrid access point (H-AP) for information and energy to serve the WPCN and \(K\) single-antenna users, denoted by \(U_{k},k=1,2,3,\ldots,K\) as seen in Figure 2. We consider the TDD protocol for transmission, in which channel properties are the same on uplink and downlink. The system has frame-based transmission, as shown in Figure 3, where the total frame length is T seconds, which is equal to A channel coherence time in which channel properties remain constant.  
Each frame is divided into two phases, as shown in Figure 3: downlink energy transfer and uplink information transfer. In the downlink phase, the H-AP transmits the energy signal to all users in  
Figure 3: The frame-based WPCN scheme: The total frame is divided into two phases. In the downlink phase, the H-AP transmits an energy signal to all users. The second phase, the uplink phase, shows the allocation of time for each user to send an information signal to the H-AP.  
Figure 2: A wireless powered communication network (WPCN): A base station with a hybrid access point (H-AP) for energy and information transmission, and K single-antenna users.  
seconds, where \(\tau_{o},(0<\tau_{o}<1)\) is normalized to the frame length for generalization. Each \(U_{k}\) harvests energy from the energy signals sent by the H-AP in the downlink phase. In the uplink phase, each \(U_{k}\) utilizes that harvested energy to send the information signal to the H-AP. In Figure 3, \(\tau_{1},\tau_{2},\tau_{3},\ldots,\tau_{k}\) are the allocated time slots for every user to transmit information during the uplink phase.
## 1 Introduction
Accordingly, the aim of this study is to evaluate the feasibility of Sentinel-1 InSAR for monitoring ground motion in high mountain terrain, based on a case study of the Lake Sarez area in Tajikistan. A similar assessment with respect to the effect of geometric distortions has previously been undertaken over the Zhouqu area in China, based on ALOS and ENVISAT SAR data acquired with opposing viewing geometries [8]. However, the objective of the current study is to assess the constraints on the efficacy of Senetinel-1 InSAR posed by both geometric distortions and decorrelation due to land cover, and to explore ways in which these could be mitigated through the choice of both viewing geometry and InSAR processing technique. Lake Sarez is a famous 'quake lake' threatened by a number of landslide hazards on several of the steep slopes that surround it. This site was selected as it has been widely studied in the past, and the application of new or improved remote sensing techniques would undoubtedly help supplement the knowledge of the risks around the lake and in the wider area [12].
# Chromaticity Recognition Technology of Colored Noise and Operational Modal Analysis
## 5 Discussion  
Traditional OMA has made great progress in recent decades and has many applications in various industries. However, traditional OMA analysis is often based on the assumption of white noise excitation, which restricts the development of OMA. In many cases, stimuli in the environment cannot be considered as white noise. For example, in the aerospace field, the excitation of aircraft by air often cannot be regarded as white noise. In the field of civil engineering, bridges are affected by various factors such as wind and vehicle movement, and external excitation is also colored noise.  
This article first gave a brief introduction to the frequency domain fitting algorithm for modal parameters under colored noise excitation. It then introduced the system response function under colored noise, proposes the CRF, proposing a technique to approximate the chromaticity of this chromaticity function, namely CRT. By inputting the chromaticity value into the frequency domain fitting algorithm, higher accuracy modal parameters can be obtained. Through the research in this article, the scope of color noise research can be extended to noise with incomplete shape determination, improving its applicability and the accuracy of OMA testing, and reducing the cost of modal recognition. Finally, a cantilever beam was selected as the specimen for numerical simulation and experimental verification, and the results showed that the CRT algorithm proposed in this paper has a certain feasibility.  
It should be pointed out that the method proposed in this article is applicable to non-uniform situations where the environmental excitation is stationary. A stationary environment refers to a stochastic process whose statistical characteristics do not change over time. The mean and variance of stationary noise remain constant over time, and the covariance between any two periods depends only on the distance or lag between those two periods, rather than on the actual time at which this covariance was calculated. Non uniform environmental excitation refers to the power spectral density of noise not being a straight line.  
Conceptualization, X.L.; methodology, X.L.; software, X.L.; validation, X.L.; formal analysis, H.C.; investigation, H.C.; resources, H.C., X.H.; data curation, X.L.; writing--original draft preparation, X.L.; writing--review and editing, H.C., X.H.; visualization, X.L.; supervision, X.L. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**White** & **Pink** & **Blue** & **Purple** & **Brown** \\ \hline
3.1449 & 5.9210 & 5.7971 & 17.1014 & 19.4203 \\
2.4259 & \(-12.9612\) & \(-10.2426\) & \(-17.8167\) & \(-23.4771\) \\
10.9372 & 14.0631 & \(-15.7399\) & \(-30.9417\) & \(-67.2646\) \\
7.6190 & 0.3316 & \(-50.4762\) & \(-59.0476\) & \(-51.4286\) \\ \hline \hline \end{tabular}
\end{table}
Table 14: Sensitivity of FSDD to identifying damping error (%) under different chromatic noise excitations.
# Ozone Generation by Surface Dielectric Barrier Discharge
## 3 Results and Discussion
### Ozone Concentration Indoors
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \multirow{2}{*}{**Active Power [W]** (Applied Voltage [kV])} & \multicolumn{3}{c}{**During SDBD Operation**} & \multicolumn{3}{c}{**After SDBD Is Turned Off**} \\  & \multicolumn{3}{c}{**(Equation (l))**} & \multicolumn{3}{c}{**(Equation (2))**} \\ \cline{2-7}  & \(\mathbf{C_{e}\) (ppm)} & \(\mathbf{\tau\) (h)} & \(\mathbf{\chi^{2}\) *} & \(\mathbf{C_{e^{\prime}}\) [ppm]} & \(\mathbf{\tau^{\prime}\) (h)} & \(\mathbf{\chi^{2}\) *} & \(\mathbf{T_{1/2}\) (min)} \\ \hline
0.94 (12.8) & 0.059 & 0.572 & \(1.97\times 10^{-5}\) & 0.063 & 0.237 & 0.89 \(\times\) 10\({}^{-5}\) & 10.4 \\
1.35 (14.4) & 0.081 & 0.452 & \(0.38\times 10^{-5}\) & 0.076 & 0.325 & 0.54 \(\times\) 10\({}^{-5}\) & 11 \\
1.81 (16) & 0.111 & 0.571 & \(1.57\times 10^{-5}\) & 0.104 & 0.304 & 0.72 \(\times\) 10\({}^{-5}\In closing, this study can be used as a guide in selecting the maximum power of the SDBD discharge that will allow safe work in an enclosed space (taking into account its volume). Various standards define the safe concentration of ozone differently. Usually, this value ranges from 0.05 ppm to 0.1 ppm [72]. It can be seen from Figure 9 that in order not to exceed the upper limit of the safe ozone concentration in the room, the SDBD generator must operate with an active power not exceeding a value of approximately 1.7 W. Although, as was shown above, the ozone production yield depends mainly on the active power of the SDBD discharge, the correct choice of the electrode geometry can help to reduce the ozone concentration in a specific application. For example, if the SDBD generator is to act as an EHD flow actuator, the optimal choice is to use the serrated electrode, which generates much higher EHD flows than the smooth-edge and thin-wire electrodes for the same active power [40,73]. On the other hand, if the SDBD generator is to be used as an ionizer, the use of a thin-wire electrode should be considered, since its construction inhibits the formation of the plasma streamers and allows higher values of applied voltage.
## 3 Results
### Damage Scenario Classification
It shows that even the slight deviations in \(F_{A}\), \(F_{D}\) and \(F_{E}\), as discussed in the previous section, are mostly sufficient to recognize the considered screed damages. Overall, the four used classifiers achieved similar accuracies in all matrix entries. Only the damaged screed scenario reveals a more significant trend with a comparatively poorly-performing SVM, while ANN shows the best results. Figure 14: Measurements at a 6 cm CT and 6 cm PS floor construction for the scenarios: (**a**) dry, (**b**) damaged insulation, and (**c**) damaged screed. The bottom (**d–f**) shows the respective A-scan vector plots for each B-scan (top). Figure 13: Water ingress (dark dyeing) in the 2 cm GW insulation. The picture shows the bottom of the used insulation plate (40 cm \(\times\) 40 cm \(\times\) 2 cm) in quadrant IV. Looking at the achieved scores of each extracted feature can give a better insight into the data's structure and their decisive components. Table 3 points out \(F_{B}\) as the best-performing feature, followed by \(F_{C}\) and \(F_{A}\). The reasons for these scores become clearer by considering the selected scatter plots in Figure 15 with standardized values. Combining the best-performing, RW2-related features \(F_{B}\) and \(F_{C}\) shows a good separation of the damaged insulation scenario with a broad distribution of possible values. However, due to the discussed appearance of smooth reflection patterns, the damaged screed is mostly indistinguishable from the dry scenario. In this case, features regarding DW and RW1 are obviously more decisive, which can be seen by a better separation in the middle and left scatter plot. However, the separation is not that clear as for the damaged insulation with \(F_{B}\) and \(F_{C}\), which explains the comparatively lower scores. The blue outliers belong to the 7 cm CT screed shown in Figure 9, where the extra reflector caused an unusually strong deviation in \(F_{D}\).
## 4 Discussion  
### Propagation Results  
#### 4.1.1 Free Space Propagation  
In the snapshot \(n=7000\) of the 5 GHz experiment, shown in Figure 4, it can be observed how the source was stopped and the propagation continued until the time iteration \(n=8500\), where it can be noticed how the CPML efficiently absorbed the waves, and there was no electromagnetic field remaining visible in the domain. No spurious propagations can be seen within the domain coming from the region of the absorbing boundaries. The efficient absorption can be corroborated by observing the electric field viewers' behaviour \(E_{z}\) depicted in Figure 6. It is observed that once the source emits the last wavefront and passes through the viewers, the electric field abruptly drops to zero, and no spurious propagation is recorded within the domain, even though the simulation continued for a long time. Additionally, to validate the absorption performance, the electromagnetic energy flow in the domain increases until the 5 GHz source is turned off, as can be observed in Figure 5. After such a moment, the electromagnetic energy flux remains constant and then begins to decrease as it is absorbed by the CPML boundary, reaching the zero value, with no spurious energy appearing in the domain in the additional time.  
Therefore, the effectiveness of the absorbing boundary technique implemented in this work, with the optimised parameters reported at the beginning of Section 3, is demonstrated.  
Analogous results can be found for the case of a 25 GHz scenario in free space. The great similarity of the boundary condition performance with the 5 GHz experiment is remarkable since there are no remnant or spurious waves coming from the absorbing boundaries. This can be observed in the behaviour of the propagation snapshots (see Figure 10).  
The \(E_{z}\) electric field viewers for the 25 GHz case in free space show a completely analogous behaviour to the 5 GHz case (see Figure 12). In the same way, the energy flux behaviour is similar, as can be observed in Figure 11.  
Thus, the successful application of the CPML absorbing boundary conditions is efficient in the frequency range of 5G herein studied. It is necessary to note that although the initial values of the parameters in Table 1[53] provided good results with 5 GHz propagation, their performance was not good enough with 25 GHz source propagation, so the CPML parameter optimisation performed in this work was fundamental in order to have a unique and coherent set of CPML parameters for the frequency range herein explored.
## 2 Theory and Implementation
### Working Principle Based on \(\Delta\)-\(\Sigma\) Modulation  
Figure 3 shows the measurement results as two curves, one is the sensing voltage of thermal radiation measured by the sensor and the other is the output signal of delta-sigma modulation. When the operating state of the light source altering, the output of the modulated signal will change to the corresponding state. In this process, the microprocessor based on the delta-sigma algorithm plays an important role. It monitors the change of the electrical signal from the light source through the preset scan time (denoted as \(t_{s}\)) and identifies the current working state of the light source. After \(N\) times of sampling which is comprise of heating duty (denoted as \(m\)) and cooling duty (denoted as \(N\)-\(m\)) of light source, we can obtain the total sampling time (denoted as \(N\times t_{s}\)) and total heating time (denoted as \(m\times t_{s}\)). In our study, the signal reading is quantized as Ratio (Ratio = \(\frac{m\times t_{s}}{N\times t_{s}}=\frac{m}{N}\)). Finally, we can obtain the relationship between correct gas concentration and Ratio by mathematical derivation [6].
# Advanced Strategies for Mitigating Particulate Matter Generations in Poultry Houses
## 3 Factors Affecting Dust Generations
### Effect of Bedding Materials on PM Levels  
Cage-free housing commonly uses bedding materials on the floor for producing hens with litter floor to perform natural behaviors of dust bathing and foraging [51; 52; 53; 54; 55; 56; 57; 58]. In Europe, litter floor distribution should include bedding material covering at least 33% (one-third) and 100% of total space in laying hens and broiler houses, respectively [51]. This litter floor is the main source of PM emissions in CF houses. Particulate matter production from bedding material can be influenced by the type of bedding materials, moisture content, depth of bedding material, replacing or cleaning frequency [52]. Bedding materials can be organic (wood shaving or chips, straw, paper, rice hulls, maize silage, plant husk, or grass) or inorganic (stone, sand, and clay) in origin and must be nontoxic, highly absorbent, and comfortable for animals [36; 53]. The management of bedding materials has been studied to control PM concentrations or emissions in animal houses [54; 55], as summarized in Table 3. Different types of bedding materials, including peat, clay pellets, chopped straw, wood shaving, chopped paper, or gravel, peat, and clay pellets, were compared. Peat and clay pellets have shown higher efficiencies in PM reduction ranging from 19 to 64% [56].
# Evaluation of Radio Access Protocols for V2X in 6G Scenario-Based Models
## 3 Performance Metrics of V2X Technologies
### Transmission Latency (L)
#### 3.2.3 L for LTE-V2X Protocol (L\({}^{\rm LTE}\))  
For LTE, L\({}^{\rm LTE}\) refers to the number of sub-frames needed to transmit \(P_{b}\) (in bytes) multiplied by the duration of a sub-frame (\(t_{sub-fr}^{LTE}\)= 1 ms) [21]. The division by 10 refers to the conversion from the number of frames to the number of sub-frames. L\({}^{\rm LTE}\) is calculated by the following expression:  
\[L^{LTE}=\left\lceil\frac{n_{RB}^{LTE}}{\left(n_{RB-fr}^{LTE}\right)/10}\ \ \right\rceil t_{sub-fr}^{LTE} \tag{7}\]  
where \(n_{RB}^{LTE}\) is the number of resource blocks needed to transmit \(P_{b}\) bytes (see [32], Table 7.1.7.2.1-1), \(n_{RB-fr}^{LTE}\) stands for the number of resource blocks per frame ([36], Table 2), and \(t_{sub-fr}^{LTE}\) refers to the sub-frame duration.
# MZAP--Mobile Application for Basketball Match Tracking and Digitalization of Endgame Reports
## 5 MZAP Android Application--Match Report Preview and Digital Signing
### Security Mechanisms for PDF Match Endgame Reports
#### 5.2.1 Password Protection of a PDF File  
Password generation is handled exclusively on the MZAP server, with each PDF being assigned two unique passwords. Prior to PDF generation, the match UUID is transmitted to the server. Both owner and user passwords are then generated using a cryptographically secure pseudo-random number generator (CSPRNG) [33], resulting in a 10-character string drawn from a custom ASCII character set. The passwords must include at least one uppercase letter, one digit, and one special character.  
Subsequently, the generated passwords are hashed using the Argon2 algorithm [34], producing a 95-byte (127-character Base64) hash. A random 10-character salt (generated using the same method as the passwords) is used in the hashing process. The resulting password hashes are stored in the MZAP server's database along with the associated UUID.  
Figure 21: Match report preview in English (**left**) and in Serbian (**right**).  
The passwords for digital signing are transmitted alongside the password for encrypting the PDF file. Upon receiving the specified data, the generated PDF file is locked using a hashed owner's password (as shown in Figure 22), encrypted with AES-256 encryption algorithm [32] using a hashed user's password and then digitally signed.
# Research on Phase Stabilization Algorithm of Femtosecond Timing System
## 6 Conclusions  
This paper investigated the design, implementation, and validation processes of a femtosecond timing system, aimed at providing precise time control and phase synchronization solutions for large particle accelerator facilities. By conducting an in-depth analysis of the current state of research and technological challenges in the field, alongside the latest advancements both domestically and internationally, this study constructed a prototype femtosecond timing system based on continuous wave lasers. The design process introduced a collaborative working algorithm for two phase control devices and incorporated a PID control algorithm to optimize adjustment accuracy. Additionally, an FPGA was utilized as the core interface converter, with modular design implemented through Verilog code, facilitating communication with critical devices and ultimately achieving precise phase compensation of the high-frequency reference signal.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Phase Offset** & **Phase Correction Module Not Enable** & **Enable Phase Correction Module** \\ \hline Average value & 1374.104 fs & 15.782 fs \\ RMS & 1537.92 fs & 19.925 fs \\ Maximum offset & 2484.75 fs & 74.85 fs \\ \hline \hline \end{tabular}
\end{table}
Table 1: Results of experiments.  
Figure 11: Signal phase offset situation.  
**Author Contributions**: Conceptualization, J.Z. and M.L.; methodology, J.Z. and M.L.; software, J.Z.; validation, J.Z.; resources, M.L.; writing--original draft preparation, J.Z.; writing--review and editing, J.Z. and M.L. All authors have read and agreed to the published version of the manuscript.  
**Funding**: This research received no external funding.  
**Institutional Review Board Statement**: Not applicable.  
**Informed Consent Statement**: Not applicable.  
**Data Availability Statement**: The data that support the findings of this study are available from the corresponding author upon reasonable request. The data are not publicly available due to privacy concerns.  
**Conflicts of Interest**: The authors declare no conflicts of interest.