esa-sceva/satcom-chunk-collection huggingface dataset:
# Analysis and Optimization of Output Low-Pass Filter
## 1 Introduction
#### Design Criteria  
The main objective of a grid-connected inverter, GCI, is to deliver high-quality power with low THD to the grid while maintaining the necessary power factor. As illustrated in Figure 2, a CSI configuration with a low-pass line filter plays a critical role in this process. The properties of the low-pass filter can significantly affect the inverter's performance  
Figure 2: The current-source RB-IGBT-based single-phase grid-connected PV inverter shows waveforms for every operational phase. The output filter is configured as a parallel-damped CL type.  
regarding power factor and harmonic suppression. Consequently, careful consideration must be given to the design elements of the low-pass filter. The principal objective of constructing the low-pass filter is to guarantee that the GCI complies with required grid standards [10; 11] while reducing power losses caused by damping resistance:  
* From 20% to the rated output power, the power factor should be 0.8 leading and 0.95 lagging;
* It is essential to minimize high-frequency harmonics, ensuring that the output current maintains a THD of less than 5%.  
These standards provide comprehensive guidelines for the grid connection of energy systems using inverters. As mentioned above, Australian Standards [11] require that inverters produce a high-quality current waveform with a power factor ranging from 0.8 leading to 0.95 lagging when the inverter output is between 20% and 100% of its rated voltamperes. Grid-connected inverters are required to comply with specific THD standards as well [11]. The current should have less than 5% total harmonic distortion for harmonics up to and including the 50 th, as indicated in Table 1. Most inverters primarily control the output current and are not required to monitor voltage harmonic distortion, although grid voltage has strict harmonic limits as well.  
Additionally, losses due to iron and copper components can reduce the overall efficiency of the inverter when such a filter is employed. As a result, to keep the efficiency higher, a maximum damping resistor power loss, \(P_{d}\), of 5% of the rated power is arbitrarily selected. This should also be considered in the design of a GCI low-pass filter.
## 7 Discussion  
This study aimed to explore how the digital literacy of the elderly population affects the effectiveness of social platform promotional strategies. An empirical study was conducted to analyze the behavioral characteristics of AISs and PIRs at multiple stages of platform adoption. By referring to our empirical results and research on social platforms and innovation diffusion, we built an agent-based model to simulate the process of social platform adoption among the elderly. By changing the proportion of the target group of PIRs and the relevant parameters representing the promotional strategies of the platform, we analyzed the impact of the proportion of PIRs as well as the effect of each strategy under different proportions of PIRs on market penetration.  
The digital literacy of the target group directly affects platform adoption. The fewer PIRs with information seeking capabilities there are in the target group, the greater the market penetration of social platforms will be. The high proportion of PIRs is a significant obstacle that hinders platform adoption.  
The effect of some promotional strategies on market penetration is affected by the proportions of PIRs. Improving service quality is more effective for market penetration when the proportion of PIRs in the target group is lower. Strategies directly related to information diffusion, such as increasing the number of seeds and increasing the strength of mass media messages, have stronger effects on market penetration when the proportion of PIRs in the target group is higher. In addition, cultivating opinion leaders is most effective for market penetration with a moderate proportion of PIRs. Interestingly, regardless of the proportions of PIRs, the effect of increasing interacting times marginally decreases.
# Bounce: A High Performance Satellite-Based Blockchain System
## 5 Implementation
### Merkle Tree Construction and Multisigning  
As explained in Section 4, the construction of the Merkle Tree(s) begins well before the beginning of a given slot \(i\). The Sending Station sends the transaction set \(L\) to at least \(f+1\) Broadcast Ground Stations. (Recall that \(f\) is our assumption of the maximum number of Broadcast Ground Stations that will fail, either traitorously or by omission.) In our implementation, the Sending Station uses a small number (the fanout) of the destination Broadcast Ground Stations as relays which in turn uses small numbers of other destination Broadcast Ground Stations as relays until the desired number (\(f+1\)) of destination Broadcast Ground Stations have received the transactions. In our implementation, the fanout is 3.  
Because our goal is to process several million transactions per slot, the volume of data transferred could reach several hundred megabytes. Because gRPC's default message size limit of 4 MB is inadequate at this scale, we use a direct TCP socket connection to communicate millions of transactions. Each Broadcast Ground Station maintains a long-running TCP listener, while the Sending Station establishes a TCP stream to transmit transactions. To minimize serialization and deserialization overhead, we leverage rkyv, a zero-copy deserialization framework for Rust. When network speed is constrained, we use zstd compression.  
Upon receiving a request, a Broadcast Ground Station constructs the Merkle Tree, caches it, signs the root, and returns the signed root to the Sending Station. In parallel, the Broadcast Ground Station forwards the request and the transactions to other Broadcast Ground Stations, based on the overlay topology. We use Keccak-256 for hashing when building the Merkle Tree.  
The Sending Stations transmit only the transactions in the request and simultaneously construct the Merkle Tree while awaiting responses from Broadcast Ground Stations. When a response is received, the Sending Station verifies the signature, confirms root consistency, and caches it. After accumulating \(f+1\) valid responses, the Sending Station aggregates the signatures into a multisignature (described in Section 5.3, Algorithm 2) and stores the multisigned root in a queue, ready for transmission to the satellite.
# Performance Analysis of the Shore-to-Reef Atmospheric Continuous-Variable Quantum Key Distribution
## 5 Performance Analysis
As illustrated in the figures, we can find that with distance of ocean transmission unchanged, both the increase of total distance of transmission and the distance of shore-based will lead to the decrease of secret key rate. The reason for it is that the extinction coefficient is highly involved with the distance of transmission. The extinction effect is increasing with the soar of distance, which leads to the reduction of secret key rate. Similar to the case of fixed shore-based distance, the secret key rate decreases with the increase of relative humidity; however, the decline is not dramatic. The numerical simulation demonstrates that the sea salt particles radius and relative humidity are closely related to the performance of ocean atmospheric CVQKD. Therefore, the role of sea salt could not be neglected. A study on the influence of sea salt particles on CVQKD protocol also provides a vigorous basis for evaluating CVQKD protocol in complex atmospheric environment.
## 2 Related Work and Security Landscape in mHealth
### Comparative Positioning Table  
Although several prior studies have addressed specific aspects of security in mHealth environments, many of them limit their scope to isolated components such as mobile applications, cloud services, or wearable devices. Few works adopt an end-to-end, multi-layered auditing perspective that includes real-world evaluation of an operational platform. To highlight this contribution gap, Table 1 presents a comparative overview of representative studies, outlining their focus, methodological depth, and evaluation scope in contrast with the present PHGL-COVID audit. This structured comparison underscores the originality and comprehensiveness of our work, particularly in bridging the gap between simulated environments and real-world deployments.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Study (Ref)**} & \multirow{2}{*}{**Layers Covered**} & \multirow{2}{*}{**Deployment Type**} & \multirow{2}{*}{**Methodology**} & \multirow{2}{*}{**Limitations**} & **Added Value in This Study** \\ \hline \multirow{2}{*}{[1]} & Backend & \multirow{2}{*}{Simulated} & ABE-based & No real-world & Live container audit \\  & (encryption & focus) & & threat modelling & testing & with CVE chaining \\ \hline \multirow{2}{*}{[3]} & Mobile privacy & \multirow{2}{*}{Survey-based} & User-centric & No security & Mobile-level token \\  & behavior & & model & testing & abuse verification \\ \hline \multirow{2}{*}{[7]} & Mobile app & National-scale & Static/dynamic & No BLE or & Cross-platform token \\  & deception & RCT & analysis & assessment & leakage + BLE flow \\ \hline \multirow{2}{*}{[12]} & Federated + & \multirow{2}{*}{Theoretical} & \multirow{2}{*}{Risk taxonomy} & No empirical & Real-world risk \\  & blockchain & & & validation & propagation scenarios \\ \hline \multirow{2}{*}{[17]} & Top mHealth & \multirow{2}{*}{Static analysis} & Permission & No device-level & \multirow{2}{*}{End-to-end audit on} \\  & apps & & inspection & & & \\ \hline \multirow{2}{*}{This work} & Wearable, & \multirow{2}{*}{Live prototype} & Static/dynamic, & \multirow{2}{*}{-} & Full-chain exploit \\  & mobile, backend & & packet sniffing, & CVE scanning & mapping in mHealth \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparative Summary of Recent mHealth Security Studies versus the PHGL-COVID Multi-Layered Audit.  
As illustrated in Table 1, most existing works focus on individual layers of the mHealth ecosystems, such as wearable protocols, mobile app permissions, or backend servers, without examining the cross-layer dependencies that may amplify vulnerabilities. In contrast, this study offers a comprehensive audit that identifies not only isolated flaws but also their potential for propagation across architectural boundaries. This integrated perspective paves the way for the subsequent sections, where we detail the architecture, auditing methodology, and real-world findings from the PHGL-COVID deployment.
# Localization of Radio Sources Using High Altitude Platform Station (HAPS)
## 2 Materials and Methods
### Radio Propagation Model  
In this study, ray-tracing simulation was used to estimate radio-wave propagation, and therefore statistical models were not applied. When considering a radio-wave propagation model with a HAPS as the receiving station, various propagation losses must be taken into account. These include free-space path loss, gaseous absorption and rain attenuation, terrain-induced losses, vegetation losses, building penetration losses, clutter losses due to building obstructions, human body obstruction losses, and diffraction losses due to spherical Earth curvature. The free-space path loss was calculated using the Friis formula, as shown below.  
\[PL_{\text{fsp}}=10\log_{10}\left(\frac{4\pi d}{\lambda}\right)^{2}\left[\text {dB}\right] \tag{8}\]  
\(d\) and \(\lambda\) represent the distance between the transmitting and receiving antennas and the wavelength, respectively. The attenuation due to gaseous absorption and rainfall was not considered in this study, as the ITU-R recommendations [18; 19] indicate that their impact is negligible at 2 GHz. Since the simulation assumed an urban environment with dense buildings, terrain-induced diffraction and vegetation losses were also not considered. Building penetration loss was not considered because the radio sources targeted for localization were assumed to be located outdoors. The losses caused by building obstructions were attributed to reflection and diffraction. In this study, simulations were primarily performed considering only reflected waves. Additionally, another simulation was performed taking into account edge diffraction, where radio waves refract upon incidence on building edges (corners and boundaries). Human body obstruction loss was not considered to simplify the analysis. The effects of spherical Earth diffraction were also not considered, as the receiving point was not located near the Earth's surface.  
Based on the above considerations, the propagation losses accounted for in this simulation include free-space path loss, building reflection, and ground reflection for the purpose of localization. The attenuation due to ground and building reflections, denoted as \(L_{\text{ref}}\), was calculated using the Fresnel equations in the ray-tracing simulation. The relative permittivity and conductivity of the surface materials used in this analysis were referenced from ITU-R studies [18]. Both the ground and buildings were assumed to be made of concrete, with a relative permittivity of 5.31 and a conductivity of 0.0548 S/m. Considering these factors, the total propagation loss \(PL\) was computed as follows.  
\[PL=PL_{\text{fsp}}+PL_{\text{ref}}\left[\text{dB}\right] \tag{9}\]  
Figure 5: Cylindrical antenna with tilted element plate.
## 4 Conclusions  
The results obtained from this study indicated that oxidation development was lower in oven-cooked turmeric-added samples compared to thyme-added samples and all deep-fried samples at the end of the storage. Deep-frying resulted in higher oxidation development compared to oven cooking for all samples during the storage period of 30 and 60 days. Turmeric and thyme additives exhibited an antimicrobial effect, resulting in a significant reduction in TMAB counts compared to the control samples during the storage period. The addition of thyme and turmeric to the formulation of coated chicken liver samples, which were then subjected to either deep-frying or oven cooking, resulted in a substantial reduction in the carcinogenic IQ, MeIQx, and 4.8-DiMelQx compounds and total HCA content. For the total HCA content of the deep-fried and oven-cooked samples, the addition of thyme resulted in a decrease of 14.42% and 13.20%, and the addition of turmeric resulted in a decrease of 18.75% and 23.35%, respectively. The sensory properties of all the samples were evaluated with high scores by the panelists during storage (ranging from 6.10 to 8.60 on a 9-point scale) While the appearance and color scores of the deep-fried samples were significantly higher than those of the oven-cooked samples, formulation differences did not cause any significant differences in the texture, flavor, and overall acceptance scores of samples. However, the fact that the oxidation development is higher in deep-fried samples compared to oven-cooked samples is a limitation due to the shorter shelf life of deep-fried samples. In the light of the data obtained, it was concluded that turmeric-added gluten-free coated chicken liver cooked in the oven can be stored at \(-20\)\({}^{\circ}\)C for up to 60 days while maintaining its microbiological, oxidative, and sensorial quality in terms of texture, flavor, and overall acceptance, and can take its place in the food market as a pre-cooked frozen healthy offal product. Further studies could focus on designing new, healthier, ready-to-eat gluten-free pre-cooked offal products prepared with different spices and with a longer shelf-life. In order to maintain the healthy properties of these products, studies can be carried out on the application of alternative cooking methods.  
G.Y.T.: supervision, methodology, conceptualization, funding acquisition, investigation, project administration, writing--original draft, and writing--review and editing. B.C.:methodology, conceptualization, analysis, investigation, and writing--original draft. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Ege University Scientific Research Projects Coordination Unit, Izmir Turkive, under project No: 22986.  
Not applicable.  
Data Availability Statement: Data supporting the findings of this study are available upon request from the corresponding author due to that there is a patent application within the scope of this study. The patent application made to the Turkish Patent Institute has been approved but is still under evaluation.  
The authors declare no conflicts of interest.
## 3 Cluster-Disjoint Multipath Routing Protocol  
Many applications such as military, medical, and disaster cases require real-time and reliable packet transmission. Multipath routing is exploited to improve reliability; however, it tends to impair real-time transmission due to path construction and path recovery process. Therefore, in this section, we describe a cluster-disjoint multipath routing protocol for real-time and reliable packet transmission. The proposed scheme could be largely categorized as a cluster construction process in network initialization, and a mutlipath transmission process without path construction and path recovery.
# Investigation of Impact Behavior of STS304L Steel Plate Under Cryogenic Temperature
## 2 Experiment Details
### Drop-Weight Impact Test  
To analyze the temperature sensitivity of the mechanical behavior of STS304L under impact loading, a drop-weight impact test apparatus (Instron CEAST 9340, Instron, Pianezza, Italy) was used. The total impact weight was 32.546 kg, comprising the impactor weight (0.046 kg) and an additional weight (32.5 kg). The drop height was determined based on the required impact energy and total weight, with energy levels ranging from 50 J up to the point where cracks appeared. A schematic of the drop-weight impact test apparatus is illustrated in Figure 2a. The impact force signal was recorded at 500 Hz using a force sensor and data acquisition system. To ensure a single impact per test, an anti-rebound system was employed, preventing multiple strikes on the specimens.  
Because insufficient impactor hardness can alter the mechanical response, the impactor was fabricated from high-hardness SKD11 steel and reinforced with hard chrome plating to further enhance hardness and reduce friction.  
The impactor shape plays a crucial role in drop-weight impact tests. Previous studies have indicated that sharper impactors do not significantly contribute to energy absorption through strain-induced martensitic transformation, whereas rounded impactors enhance energy absorption owing to this transformation [19]. As this study focuses on the relationship between mechanical behavior and strain-induced martensitic transformation at different temperatures, a hemispherical impactor was selected, as depicted in Figure 2b.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**C** & **Si** & **Mn** & **P** & **S** & **Ni** & **Cr** & **Mo** \\ \hline
0.018 & 0.4 & 1.63 & 0.03 & 0.001 & 8.2 & 18.1 & 0.22 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Chemical composition (wt%) of STS304L.  
Figure 1: (**a**) Drop-weight impact test specimen and (**b**) initial microstructure of STS304L.  
All tests were performed in triplicate, and the average values were used for analysis to ensure reliability and reproducibility.
## 3 Proposed Work
### Watermark Embedding and Extraction
```
0: Watermarked image (\(C_{1}\)), m, s, Random key (\(R_{key}\)), \(\alpha\)
0: Extracted Watermark (\(EW\))
1: Apply 1-IWT to \(C_{1}\), to obtain \(LL^{1}\), \(LH^{1}\), \(HL^{1}\) and \(HH^{1}\) sub-bands
2: Apply SVD to \(LH^{1}\) and \(HL^{1}\) sub-bands to obtain \(U^{1}_{LH}\), \(S^{1}_{LH}\), \(V^{1}_{LH}\), \(U^{1}_{HL}\), \(S^{1}_{HL}\), \(V^{1}_{HL}\)
3: Divide \(S^{1}_{LH}\) and \(S^{1}_{HL}\) into \(4\times 4\) non-overlapping blocks. 4: Select low entropy blocks (\(B^{1}_{LH}\), \(B^{1}_{HL}\)). 5: Determine watermark extraction positions (\(P_{1}\) and \(P_{2}\)) using BBS Pseudo random series generated by using \(m\) and \(s\). 6: Extract watermark vector from \(S^{1}_{LH}\) and \(S^{1}_{HL}\) using the steps below: \(V^{11}_{add}\leftarrow(B^{1}_{LH}(P_{1},P_{2})-B_{LH}(P_{1},P_{2}))/\alpha\)\(V^{11}_{even}\leftarrow(B^{1}_{HL}(P_{1},P_{2})-B_{HL}(P_{1},P_{2}))/\alpha\)
7: Generate a pseudo random key (\(PR_{key}\)) using \(R_{key}\). 8: Re-shuffle the extracted watermark vectors i.e., odd (\(V^{11}_{odd}\)) and even (\(V^{11}_{even}\)) vectors using \(PR_{key}\). \(EV_{odd}\gets PR_{key}\cdot V^{11}_{odd}\)\(EV_{even}\gets PR_{key}\cdot V^{11}_{even}\)
9: Combine \(EV_{odd}\) and \(EV_{even}\) to get the extracted watermark. \(EW\gets EV_{odd}+EV_{even}\)
```  
**Algorithm 2** Watermark extraction. Figure 2: Determining the embedding position randomly in low entropy blocks.
## 3 Results and Discussion
### Experimental Details  
Parameter settings: We utilized RRG as the backbone network of RRMSA-Net, applying weights from the _Pytorch_ pre-trained VOC model. MSAS was used for multi-scale detection. Additionally, when the momentum was set to 0.9, the proposed RRMSA-Net was optimized using the Adam optimizer. The initial learning rate was set to 0.005, with a decay rate of 0.1 after 1000 iterations. All experiments were conducted on a server equipped with an Nvidia 3070 (Nvidia Corporation, Santa Clara, CA, USA), based on the _Pytorch_ framework. ResNet was adopted as the baseline. The introduction of any module may complicate the computation.