esa-sceva/satcom-chunk-collection huggingface dataset:
# Energy Harvesting over Rician Fading Channel:
## Appendix B Proof of Theorem 2  
Again, without loss of generality, we can only consider the case \(i=1\) (the SER at node 1). Obviously, the CDF of the SNR at node \(S_{1}\), denoted by \(F_{\gamma_{1}}(x)\), is the outage probability at \(S_{1}\) when the threshold SNR is equal to \(x\). Thus, it can be written as  
\[F_{\gamma_{1}}(x)=\Pr\left(\frac{X_{1}X_{2}}{X_{1}X_{2}a+X_{1}^{2}a+X_{1}b+c}< x\right)=\begin{cases}\Pr\left(X_{2}<\frac{xX_{1}^{2}a+xX_{1}b+xc}{X_{1}-xX_{1}a} \right),&\text{if }x\leqslant\frac{1}{a},\\ 1,&\text{if }x>\frac{1}{a}.\end{cases} \tag{12}\]  
Then, we can substitute Equation (11) into Equation (11) to get  
\[SER_{1}=\frac{\omega\sqrt{\theta}}{2\sqrt{\pi}}\int_{0}^{\infty}\frac{e^{- \theta x}}{\sqrt{x}}F_{\gamma_{1}}(x)dx=\frac{\omega\sqrt{\theta}}{2\sqrt{\pi}} \int_{0}^{1/a}\!\!\frac{e^{-\theta x}}{\sqrt{x}}F_{\gamma_{1}}(x)dx+\frac{ \omega\sqrt{\theta}}{2\sqrt{\pi}}\int_{1/a}^{\infty}\frac{e^{-\theta x}}{\sqrt {x}}dx. \tag{13}\]  
By using the results from the previous version, the CDF \(F_{\gamma_{1}}(x)\) for \(x\leq 1/a\) is given by  
\[F_{\gamma_{1}}(x)=1-2\zeta_{1}e^{-2K}e^{-b\zeta_{2}\tilde{\gamma} _{ln}}\sum_{l=0}^{\infty}\sum_{k=0}^{\infty}\sum_{m=0}^{l}\sum_{n=0}^{m}\sum_{p=0 }^{n}\frac{K^{l+k}\xi_{1}^{rk}\xi_{1}^{rk}(\xi_{2}\tilde{\gamma}_{th})^{\frac{3 m-2n+p+k+1}{2}}a^{m-n}b^{p}c^{\frac{n-p+k+1}{2}}}{l!p!(n-p)!(m-n)!(k!)^{2}(\zeta_{1}+a \xi_{2}\tilde{\gamma}_{th})^{\frac{-2n+p+k+1}{2}}} \tag{14}\] \[\times K_{m-2n+p+k+1}\left(2\sqrt{(\zeta_{1}+a\xi_{2}\tilde{\gamma} _{th})\xi_{2}\tilde{\gamma}_{th}c}\right).\]  
Let us denote \(\Xi(x)\triangleq 1-F_{\gamma_{1}}(x)\). Then, Equation (13) can be rewritten as \[SER_{1} =\frac{\omega\sqrt{\theta}}{2\sqrt{\pi}}\int\limits_{0}^{1/a}\frac{e^ {-\theta x}}{\sqrt{x}}\left\{1-\Xi(x)\right\}dx+\frac{\omega\sqrt{\theta}}{2\sqrt {\pi}}\int\limits_{1/a_{1}}^{\infty}\frac{e^{-\theta x}}{\sqrt{x}}dx=\frac{ \omega\sqrt{\theta}}{2\sqrt{\pi}}\int\limits_{0}^{\infty}\frac{e^{-\theta x}} {\sqrt{x}}dx-\frac{\omega\sqrt{\theta}}{2\sqrt{\pi}}\int\limits_{0}^{1/a}\frac {e^{-\theta x}}{\sqrt{x}}\Xi(x)dx \tag{18}\] \[=\frac{\omega}{2}-\frac{\omega\sqrt{\theta}}{2\sqrt{\pi}}\int \limits_{0}^{1/a}\frac{e^{-\theta x}}{\sqrt{x}}\Xi(x)dx.\]  
Then, Equation (19) can be obtained by substituting \(\Xi(x)\triangleq 1-F_{\gamma_{1}}(x)\) and Equation (17) into Equation (18).
# Defect Tailoring in HfO2/Si Films upon Post-Deposition Annealing and Ultraviolet Irradiation
## 5 Conclusions  
In the present work, HfO\({}_{2}\) films prepared by room-temperature dip coating were treated at different conditions after deposition onto p-Si. Films were characterized by XRD, Raman, AFM, UV-Vis, and fluorescence spectroscopy. The films were monoclinic after thermal treatment at 350 \({}^{\circ}\)C and became amorphous and more compact upon UV treatment. A band diagram that considered both optical and fluorescence spectroscopy was proposed, including normalized fluorescence as a measure of the Density of States. The results indicate that UV treatment generates several defect states within the mobility gap, which may decrease the performance of HfO\({}_{2}\) films in microelectronics but may also allow their use in optoelectronic, photocatalytic, and electrocatalytic applications.  
Conceptualization, F.L.-H. and F.C.-B.; methodology, S.S.-R. and F.I.G.-M.; validation, R.M.W.-G., A.L.H.-M. and F.L.-H.; formal analysis, F.C.-B.; investigation, S.S.-R. and F.I.G.-M.; resources, A.L.H.-M.; data curation, R.M.W.-G. and A.L.H.-M.; writing--original draft preparation, S.S.-R., F.I.G.-M., R.M.W.-G., F.L.-H. and F.C.-B. writing--review and editing, F.I.G.-M. and F.C.-B.; visualization, F.I.G.-M. and F.C.-B.; supervision, R.M.W.-G., A.L.H.-M. and F.L.-H.; project administration, F.L.-H.; funding acquisition, F.L.-H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by CONAHCYT, grant numbers 2019-40798 and 2022-321595. GIXRD analyses was carried out at the National Laboratory of Nano and Biomaterials (LANNBIO), CINVESTAV-IPN, which is financed by the FOMIX-Yucatan grant numbers 2008-108160, CONACYT LAB-2009-01-123913, 292692, 294643, 188345 and 204822.  
Not applicable.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.  
**Acknowledgments:** We thank [PERSON] for the access to LANNBIO, to [PERSON] for obtaining the diffractograms, and to [PERSON], [PERSON] and [PERSON] for instrument maintenance. The access to four-point tests was enabled by [PERSON].  
**Conflicts of Interest:** The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
# A Novel Cross-Layering Power Control Mechanism for AODV +
## 5 Performance Evaluation  
We test the operation of our power control mechanism in the network simulator NS-3 [17]. Two scenarios will be analyzed: linear topology and a MANET with RandomWaypoint.
## 4 Experimental Results and Discussion
### Quantitative Metrics Comparison
#### 4.7.1 Comparative Analysis  
From the analysis of Tables 8 and 9, the following specific comments are listed:  
YOLOv586 + C2f: A slight improvement in [EMAIL_ADDRESS]:0.95 but reductions in [EMAIL_ADDRESS], the F1-Score, Recall, and Precision. Increased accuracy suggests better generalization, but an insufficient overall improvement.  
YOLOv586 + Bot-Transformer: Improved Recall and F1-Score indicating better true positive recovery, but slight decreases in [EMAIL_ADDRESS] and Precision suggest false positives. Reduced accuracy indicates a need for optimization.  
YOLOv586 + GeLu: enhanced [EMAIL_ADDRESS]:0.95 and Recall but decreased Precision, improving sensitivity to variations but potentially increasing false positives.  
YOLOv586 + C2f + Bot-Transformer: improved F1-Score and Precision but decreased Accuracy highlights the need to balance precision and recall.  
YOLOv586 + C2f + GeLu: significantly improved Recall but decreased Precision; increased Accuracy suggests better generalization.  
YOLOv586 + Bot-Transformer + GeLu: enhanced Recall and F1-Score but decreased Precision indicating a need for further optimization.  
YOLOv586 + Bot-Transformer + GeLu + C2f: improvements in all metrics, especially Precision and Accuracy, which suggest a robust performance but still room for enhancing Recall.  
YOLOv586 + Hyperparameters: a significant improvement across all metrics, particularly [EMAIL_ADDRESS]:0.95 and Recall with a slight reduction in Precision indicating room for better balance.  
YOLOv586 Improved Hairiness: the final model shows significant improvements in all metrics compared to the standard YOLOv586 validating the effectiveness of module combinations and optimizations.
# Seismic Response Mitigation of Base-Isolated Buildings
## 5 Numerical Study
### Seismic Effectiveness of Hybrid System  
Probability distribution functions of the BI buildings with and without TMD schemes are presented in this section. Assuming a lognormal model, the probability distribution of bearing displacement, top floor acceleration, and normalized base shear are estimated form the calculated response. Cumulative distribution function (CDF) of response quantities of BI buildings with and without TMD schemes are presented in Figures 7 and 8. Figure 7 shows that the use of TMDs in BI buildings is more effective in mitigation of displacement response than acceleration response and base shear demand. In addition, MTMDs and d-MTMDs are only marginally better than STMDs. Overall, TMDs are found to be effective in decreasing the seismic response (bearing displacement and top floor acceleration) of 5-story BI building. It is noticed that the trend of reduction in displacement and acceleration of the 10-storey building is almost the same (see Figure 8) as that of the 5-story building, but the TMD devices are less effective.  
Figure 6: Reduction in average of peak top floor acceleration of BI and BI equipped by TMD schemes under DBE earthquake ground motions.  
Figure 7: Cumulative probability distribution functions of maximum bearing displacement, peak top floor acceleration, and normalized shear force for 5-story building.
# Numerical Study on the Yaw Control for Two Wind Turbines under Different Spacings
## 4 Results
### Instantaneous Power Analysis of Two Turbines
When the yaw angle is 0\({}^{\circ}\), the standard deviation of the output power fluctuation of WT2 for the cases of 5D, 6D, 7D and 8D is 3.64%, 4.39%, 5.88% and 8.93%, respectively, due to the wake expansion. When the yaw angle of WT1 becomes larger, in the dual role of the asymmetric distribution and spread of wake, the standard deviation of the output power of WT2 no longer increases monotonously. From the above analysis, it can be concluded that the influence of yaw angle on power fluctuation is more significant than that of turbine spacing.
## Materials and Methods
### Experimental Procedure  
From previous studies, some industrial toxic substances, e.g., Zn\({}^{2+}\), Cu\({}^{2+}\), Ni\({}^{2+}\), Pb\({}^{2+}\), aromatic hydrocarbons, and antibiotics, were dominant in municipal WWTPs in Jiangsu Province [51; 52; 53; 54]. Accordingly, Zn\({}^{2+}\), Ni\({}^{2+}\), and phenol were selected as the target toxins representing those substances in this study. In the laboratory OUR monitoring system, the stock solution was prepared by dissolving  
Figure 2: Online early-warning system. (**a**) Schematic program of the online early-warning system. (**b**) The mobile platform for the online early-warning system. (**c**) Inside look of the mobile platform for the online early-warning system. Up-layer, programmable logic controller (PLC); down-layer, reaction system.  
1.041 g of ZnCl\({}_{2}\), 1.104 g of NiCl\({}_{2}\), and 0.500 g of phenol in 1.0 L of deionized water. They were then serially diluted in wastewater with the activated sludge and the final concentration ranged from 0 to 60 mg/L (details see Table S1). According to the real operation parameters in most WWTPs in Jiangsu Province (MLSS = 4000-5000 mg/L), MLSS content of the activated sludge was set from 1000 to 5000 mg/L to evaluate the impacts of MLSS on the ROUR. As MLSS had buffering capacities for the inhibitory effects of toxic substances (see Section 3.2), the optimal MLSS content was 2000 mg/L for the measurement of the ROUR and it was set for the following tests to assess the influence of pH and HRT. The pH was adjusted by H\({}_{2}\)SO\({}_{4}\) (1.0M) to 2, 4, 5, and 6 in acidic treatments, whereas under alkaline conditions, NaOH (1.0M) was used to adjust the pH value to 8, 9, 10, and 12. The optimal HRT was 20 min and set to 1-60 min to evaluate the impacts of HRT on the ROUR. For all the experiments, the operation temperature was 20 \({}^{\circ}\)C.  
In the online early-warning system, the MLSS content was 500 mg/L and the HRT was fixed as 10 min. The target toxins included Zn\({}^{2+}\), Cu\({}^{2+}\), Ni\({}^{2+}\), Cr(VI), and Cd\({}^{2+}\), prepared by dissolving 1.041 g of ZnCl\({}_{2}\), 1.054 g of CuCl\({}_{2}\), 1.104 g of NiCl\({}_{2}\), 1.951 g of KCrO\({}_{4}\), and 0.816 g of CdCl\({}_{2}\) in deionized water as stock solution. From metal speciation predicted by MINTEQ program [55], all the PTEs were in cation form, except for Cr (90% in form of HCrO\({}_{4}\)\({}^{-}\) and 10% in form of CrO\({}_{4}\)\({}^{2-}\)). Accordingly, the final concentration was 0-10 mg/L for Zn\({}^{2+}\), Cu\({}^{2+}\) and Ni\({}^{2+}\), 0-15 mg/L for Cd\({}^{2+}\) and 0-40 mg/L for Cr(VI), respectively (details see Table S2).
## 3 Results
### Grindability of Molding Sands  
As depicted in Figure 5, the incorporation of perlite ore into molding sands has a slight or positive impact on their grindability, particularly for systems with QS1 sand. In the case of QS3 sand, the largest increase in grindability (up to 0.95%) is observed when the perlite ore with the largest grain size (PO1) is introduced, compared to 0.21% for the molding sand without additives. A similar trend is noted for the molding sand based on QS2 sand. It is noteworthy that the introduction of perlite ore additives with finer fractions to the QS2-sand-based molding sand results in an increase in grindability resistance (2.27%). For instance, there is a 1.40% increase for the QS2-PO4 molding sand (addition of Hungarian perlite ore), compared to 1.71% for the molding sand without additives. A similar relationship is observed for the QS1-PO4 system, where the grindability decreases by over 15%, from 3.08% to 2.52%. The reduction in the grindability of the molding sands using Hungarian perlite (PO4) may result from the greater \"packing\" (higher compaction level) of the molding sand. During the mixing of the ingredients, all fractions are coated with a layer of liquid binder and hardener. When the grains of the sand matrix and the mineral additive are densely packed, cohesive bonding bridges may form, where a larger surface area of the binder is joined. After hardening, this connection exhibits higher strength and also improves the grindability resistance of the molding sand. However, at present, this is a hypothesis that requires additional research.  
The research has demonstrated that the introduction of inorganic binders into molding sands has little or a positive impact on the technological properties, such as the permeability and grindability. An unfavorable effect of the loosening additive on the grindability of the molding sand is observed only when the PO1 perlite ore is introduced into the molding sands based on QS2 and QS3 sand. The specific surface area of the molding mixture increases, and not all grains are coated with the binder. Larger grains come into contact with each other and bond through binder bridges. The finer fraction is not as tightly bound to the coarser grains, which may promote its susceptibility to detachment. Moreover, it has a significantly positive effect in reducing the final strength, thereby enhancing the knock-out properties. The most favorable outcomes are observed for systems incorporating Hungarian perlite ore (PO4), characterized by the lowest uniformity in terms of grain size, the smallest average grain size, and the main fraction collected on 0.40/0.32/0.20 mm sieves. Typically, dusty fractions tend to diminish the properties of molding sands. However, the presented results indicate that the presence of very fine grains in perlite ore does not constitute a technological disadvantage; on the contrary, it may improve the properties of molding sands.
# Stitching-Based Resolution Enhancement in Wavefront Phase Measurement of Silicon Wafer Surfaces
## 2 Materials and Methods
### Optics  
The optical part (Figure 4) consists of a 1-inch lens with a focal length of 100 mm for the collimator. Next, the collimated light undergoes transmission through a 4f system with a magnification factor of 2, achieving a field of view with a diameter of 40 mm. The relay setup for this process involves the utilization of two achromatic lenses. The first lens is an achromatic lens with a focal length of 100 mm and a diameter of 1 inch. The second lens is an achromatic lens with a focal length of 200 mm and a diameter of 3 inches. Subsequently, the light is reflected on the silicon wafer and collected on the aforementioned conjugate planes by an _ASI6200 MM Pro_ camera, which has a resolution of 6388 \(\times\) 6388 pixels with a pixel size of 3.8 \(\upmu\)m. With these characteristics, the theoretical lateral resolution is 7.56 \(\upmu\)m. The light source used here is a 400 nm LED. The selection of a 400 nm LED as the light source was based on two important criteria, namely, the diffraction limit and the Fresnel distance.  
The diffraction limit refers to the fundamental limitation on the ability of an optical system (such as a lens or aperture) to accurately reproduce or resolve fine details of an object or a wavefront. It is determined by the wavelength of light and the numerical aperture of the optical system. When the dimensions of the details or features in an object are smaller than the diffraction limit, they cannot be resolved separately and appear blurred or smeared together. The expression used to calculate the diffraction limit for small angles is provided by  
\[\theta\approx 1.22\frac{\lambda}{d}, \tag{1}\]  
where \(\lambda\) is the wavelength, \(d\) is the aperture diameter, and \(\theta\) is the minimum angle for two objects to be distinguishable in radians.  
On the other hand, the Fresnel distance plays a crucial role in determining the distance at which the diffraction effects become significant. As mentioned earlier, it marks the point where the wavefront starts to exhibit notable changes due to diffraction. By considering the Fresnel distance, the system ensures that the propagation of light and the resulting diffraction effects are appropriately accounted for. In addition, according to [34], the Fresnel length determines the resolution of the intensity fluctuations. Its significance is that any wave front perturbations of scale smaller than the Fresnel length are blurred and invisible to the detector. The expression is provided by  
\[\sqrt{\lambda z}=\Delta x, \tag{2}\]  
where \(\lambda\) is the wavelength, \(z\) is the distance between the conjugated planes, and \(\Delta x\) the size of the pixels.  
Figure 4: Simplified optical design of the 4f system.
# Fault-Tolerant Topology of Agricultural Wireless Sensor Networks Based on a Double Price Function
###### Abstract  
Wireless sensor networks (WSN) enable the acquisition of multisource environmental data and crop states in precision agriculture. However, the complex agricultural environment causes the WSN topology to change frequently and link connection probability is difficult to predict. In order to improve the utilization of network resources and balance the network energy consumption, this paper studies an agricultural fault-tolerant topology construction method based on the potential game and cut vertex detection. Considering the connectivity redundancy, node lifetime, and residual energy, a fault-tolerant topology algorithm for agricultural WSN based on a double price function is designed. The network is clustered according to the node location and residual energy to form a single-hop effective cluster. Based on the network cluster, the price function is constructed in order to reduce energy consumption and balance network energy efficiency. The initial transmit power set supporting inter-cluster communication is obtained by potential game theory. While preserving the game characteristics of topology, the redundant links are eliminated and the transmit power is adjusted by a cut vertex detection algorithm to realize the construction of a 2-connected cluster head network. Simulation results show that the network topology constructed by the studied algorithm can balance the energy consumption and prolong the network lifetime effectively.  
agricultural WSN; potential game; double price function; cut vertex; fault-tolerant topology definition  
Existing topology control protocols improve network performance to a certain extent. However, in the field of agriculture, densely distributed crops and complex climate aggravate the multipath effect of wireless signals, resulting in unstable link-connected probability [9]. Existing algorithms focus on overall network optimization and seldom consider the impact on data transmission of other nodes when some nodes fail. In order to ensure delivery probability and prolong the network lifetime, it is necessary to reduce energy consumption while maintaining network connectivity redundancy.  
Aiming at the problem of frequent topology changes in agricultural WSN, a fault-tolerant topology protocol based on double price potential game and cut vertex elimination is studied in this paper. The agricultural monitoring network is clustered according to the residual energy, transmission distance, and node density. The topology between clusters is initialized through the double price potential game to coordinate the transmit power of selfish nodes, realize the dual optimization between the whole network and individual nodes, reduce the node load, and balance the overall energy consumption of the network. Combined with the cut vertex detection algorithm, this paper eliminates the redundant links in the initial network topology, and constructs a 2-connected fault-tolerant topology between clusters by adjusting the transmission power.
## 4 Simulation Results and Discussion
### Comparison with APF Algorithm  
To verify the superiority of the algorithm, we first compare the APF-IRRT* with APF algorithm alone. We first construct a grid map as 50 m \(\times\) 50 m, and set (1, 1) and (49, 49) as start point and target point, respectively. Three obstacles, which are represented by black squares, are set at (15, 20), (32, 16) and (36, 40), respectively. The parameters of APF are set as: attractive coefficient \(APF\_a=20\), the maximum attractive force \(APF\_amax=1\), repulsive coefficient \(APF\_r=15\), and repulsion distance \(APF\_po=20m\). The maximum number of iterations is set to 1000, and the step size is set to 0.4.  
Figure 5 shows the simulation results of APF algorithm and proposed algorithm. From 20 independent experiments, we obtained the average path lengths of the APF algorithm as 82.34 m and search time as 10.27 s, and the APF-IRRT* algorithm obtained an average of 70.76 m and 2.36 s. Obviously, compared to the APF algorithm, the APF-IRRT* algorithm has significant advantages in terms of path length and search time.
# Cooperative Reception of Multiple Satellite Downlinks
## 2 System Description and Design  
In communications, a system which involves a single radio link from the transmitter to the receiver is referred to as single-input single-output system (SISO). Conventional SISO satellite-to-ground communications are not efficient and reliable in providing guaranteed QoS coverage due to several reasons, one of which the inability to establish long time communication [33]. Limited time communication can be established only when a satellite passes over a ground station and hence no real time network status data can be collected for necessary dynamic changes [33]. When it comes to the QoS evaluation of digital receivers, some measures can be used to indicate the system performance and one of them is the rate of detected errors at the receiver, the measure which is known as the bit error rate (BER) [34; 35]. BER is simply the number of the falsely detected bits to the total number of the transmitted bits during the observation time. Seeking as low BER as possible is the main objective of every digital communication link designer. However, different factors and challenges face the designing procedure as it involves a comprehensive study about the transmission channel, the surrounding environment, and receiver resources in addition to a compatible selection of a modulation scheme. Good consideration of these factors would consequently lead to a reliable radio communication link with low BER [36].  
In this article, the process of receiving copies of the transmitted signal by diversity sites was simulated in MATLAB using binary frequency shift keying (BFSK)--one of the basic modulations used by radio-amateur satellites, and the signal quality was degraded using the additive white Gaussian noise (AWGN), a simple and powerful model in satellite communications. For comparison, BER calculation of both SISO (no diversity) and SIMO systems (with different algorithms of diversity combining) were realized.  
To well execute the objective of this paper, we initially carried out the design of the conventional single communication link system and performed the BER calculation in the first part of this section. Then, we conducted multi-site cooperative system modeling and simulation in the following part of the section.