esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Experimental Setup and PIV Measurement  
We looked at a double-feedback fluidic oscillator that had a rectangular throat cross-section (\(10\times 20\) mm\({}^{2}\)), hydraulic diameter (D\({}_{\text{h}}\)) of 13.3 mm, and a ratio of the width of the jet throat to the depth equal to AR\({}_{\text{j}}\) = 0.5. The exit cross-section was \(40\times 20\) mm\({}^{2}\), and the diverging angle of the nozzle was \(90^{\circ}\). The confinement of the external region was investigated, which was obtained by inserting two plates at the bottom and the top of the external domain of the fluidic oscillator, resulting in a channel  
Figure 2: (a) Fully confined external domain, and (b) fluidic oscillator with double-feedback channel.  
with the same height as the fluidic oscillator's exit. Then, it did not take a step in the z-direction, as shown in Figure 3a.  
2D-2C TR-PIV was widely used to measure the flow velocity field in a plane and was applied to study the flow structures of the fluidic oscillator. A water tank that was made with acrylic, which had the same refractive index as water, was seeded with silver-coated hollow glass spheres with an average diameter of 11.7 \(\upmu\)m and a density of 1.1 g/cm\({}^{3}\). Since there was no significant discrepancy between the densities of these particles and the water, these particles could readily follow the water without any destruction of the flow.  
The experimental setup and PIV system consists of a continuous laser (532-nm wavelength and 5 W), a cylindrical lens with a focal length of 1000 mm, and a spherical lens with a focal length of 25 mm were used to attain a laser sheet less than 1 mm thickness to minimize the three-dimensional effects on the PIV measurement, and a high-speed camera with a resolution of 1024 by 1024 pixels (Photron FastCam SA1.1), and a lens with an f-number of 2.8 (Nikon, micro lens 65 mm), as shown in Figures 3 and 4. In addition, post-processing of PIV images was conducted by software developed by our group, to extract the velocity fields from sequence images. A cross-correlation scheme was performed to obtain the instantaneous and ensemble-averaged velocity vector and a final interrogation window of \(16\times 16\) pixels with 50% overlap was applied to satisfy the [PERSON] criterion. The uncertainty in the velocity vector, based on the size of the interrogation window, sampling rate, and particle density (6-8 seeding particles in each interrogation window), was estimated to be 2% [38]. The flow rate of the jet was controlled by a flowmeter. Based on the hydraulic diameter and mean velocity (Uj = Q/A\({}_{\text{Hroat}}\)), the Reynolds number spanned the range of 2680-10,730.  
Figure 4: Experimental setup for (**a**) fully confined and (**b**) free external domain.  
Figure 3: Diagram and size of (**a**) fully confined and (**b**) free geometry.
## 3 Methodology
### Quality Assessment
#### 3.3.2 Comparison between HJ Composites and MODIS Products  
The quality assessments for 8-day and 16-day HJ composites are relatively difficult because of the lack of similar spatio-temporal resolution composite products. In this paper, the 8-day 500-m MODIS MOD09A1 and 16-day 500-m MOD13A1 products were used for comparison. Due to the difference between TOA reflectance and surface reflectance, the comparison between the 8-day HJ composites and MOD09A1 was performed simply by visual evaluation. Considering that the change of radiation related to the atmosphere condition can be partially eliminated in NDVI because of the ratio processing [45], scatter plot was drawn for the comparative samples between the 16-day HJ composites TOA NDVI and MODIS NDVI product to evaluate the radiometric consistency.  
The comparison between the 16-day 30 m HJ-1A/B NDVI and 500 m MOD13A1 was implemented as follows. Firstly, the 30 m HJ-1A/B TOA NDVI were spatially aggregated to 500 m resolution by averaging all the pixel values that contribute to the output pixel. Then, the MOD13A1 provided in the Sinusoidal projection were re-projected into Albers Equal Area projection using the MODIS reprojection tool (MRT). The aggregated 500 m HJ-1A/B NDVI and MOD13A1 were then used to collect comparable samples over homogeneous regions using an algorithm proposed by [PERSON] _et al._[46].
## 4 Experiments and Analysis of Results
### Security
#### 4.4.2 Extraction Correctness
This suggests that the algorithm can effectively detect potential malicious activities in the transmission environment using identifying information, thus verifying the authenticity of the data. Due to the threshold nature of the described algorithm, the successful extraction of secret data requires multiple users to simultaneously provide the decryption keys needed. However, managing multiple users can introduce significant complexity, potentially leading to conflicts such as resource contention from concurrent decryption attempts. To address this challenge, we conducted experiments with existing distributed locks, and through comparison, found that Redisson distributed lock can effectively handle concurrent access among multiple users while minimizing related complexities [32]. Table 8 presents the experimental results, showcasing that Redisson distributed lock offers benefits such as fast response times, simplicity of operation, and support for fine-grained lock control, making it better-suited for serving multiple users in the RDH-EI algorithm. The implementation of Redisson distributed lock involves locking the system during secret data extraction operations. We employed the (3, 4)-threshold algorithm in this paper to embed random data into large images, followed by simultaneously having two groups of users apply for  
Figure 10: Comparison experiment of information extraction versus pre-embedding information. (**a**) Comparison experiment I of secret data. (**b**) Comparison experiment II of secret data. (**c**) Comparison experiment I of identifying information. (**d**) Comparison experiment II of identifying information. (**e**) Comparison experiment III of identifying information. (**f**) Comparison experiment IV of identifying information. system occupation and locking. We designated the thread that first occupies the system as Thread A and the unsuccessful one as Thread B. We set time points to observe the behavior of Thread B, and the results are shown in Table 9.  
When Thread A successfully occupies the system and locks it, the system sets the leaseTime to 30 s and activates a watchDog that renews the lock every 10 s to maintain a timeout of 30 s. Meanwhile, Thread B fails to lock and subscribes to listen for release notifications of the lock. When the system lock is released, a broadcast message is sent out. As Thread A occupies the system for 10 and 20 s, the watchDog extends the lock duration to 30 s, while Thread B continues to listen. Around the 50 s mark, when Thread A completes its operation and releases the lock, Thread B receives the broadcast, attempts to acquire the lock, succeeds, and starts its operation, with the watchDog also kicking in. Experimental results demonstrate that Redisson distributed lock effectively resolves coordination issues among multiple users.
# In Vitro Gene Expression Responses of Bovine Rumen Epithelial Cells to Different pH Stresses
## 1 Introduction  
Both metabolizable energy and dry matter intake (DMI) must be adjusted to maximize milk production [1]. Therefore, the diet of high-yielding cows is supplemented with grain or particulate matter [2]. The ruminal environment may drastically shift in response to the abrupt addition or increase of starch during feeding [3]; the composition and metabolism of the ruminal microbiota changes, which causes a buildup of volatile fatty acids (VFAs) and a sharp decline in rumen pH [4; 5]. Therefore, rumen acidosis is common in dairy cows. Depending on the extent of the clinical manifestations of rumen acidosis, the end result may be subacute ruminal acidosis (SARA) or acute ruminal acidosis (ARA). When ruminal acidosis occurs, the rumen is continuously exposed to pH < 5.0. Subacute ruminal acidosis has no clinical manifestations and is defined as rumen pH dropping from 5.5 to 5.0 and remaining in that range for 111 to 180 min over a 24 h period [6]. According to research in the dairy industry, approximately 20% of high-producing dairy cows have SARA, which has raised significant concerns for the industry [7]. In dairy cows, SARA has been proven to impact feed intake, milk production, rumen microflora, and rumen digestion, and can lead to diarrhea, rumen mucosal injury, laminitis, rumenitis, and other conditions. The ARA condition develops more rapidly and more seriously [8; 9; 10].  
Previous studies have shown that grain-induced SARA raises the levels of acute-phase proteins in peripheral blood, including haptoglobin and serum amyloid A, which signify a systemic inflammatory response [11]. A high-grain diet disrupts the function of the rumen epithelium, including cell necrosis and disruption of tight junctions [12]. This promotes the migration of microorganisms and immunogenic substances into the portal circulation [13], causing further systemic inflammation. Lipopolysaccharide (LPS) and lowered pH may operate synergistically to alter epithelial barrier function and ultimately breach the epithelial barrier, according to a study that employed isolated rumen and colon tissues from steers [14]. After fracture of the epithelium, LPS and endotoxin are free to translocate through the damaged ruminal wall [15; 16]. The mRNA expression levels of IL-18, IL-2, IL-6, and IL-8 increased during the interaction of LPS with BRECs, suggesting that these may be mainly responsible for the triggered ruminal inflammation [17]. Nevertheless, systematic research on the mechanism of pH reduction on BRECs is rare.  
Therefore, the objective of our study was to simulate rumen acidosis with butyric acid in vitro and investigate the mechanism of its effects by transcriptomics and metabolomics. This study expands our knowledge regarding the molecular mechanism of BREC inflammation under low-pH conditions and identifies molecular pathways that are significantly regulated in acidotic BRECs, which could be used to attenuate the detrimental impact of ruminal acidosis and provide a theoretical basis for feeding high-yield dairy cows with high concentrate.
## 1 Introduction
[PERSON] et al. [29] aimed to optimize an EEG-based CNN classifier for online E-health programs, which needs high precision and inexpensive time cost to manage the brain dynamics simulations. They employed the BO algorithm on time series data in a fashioned manner. They sliced up the hyperparameters into groups. Each group was optimized under the same conditions in the same space but separately. Then, the selection of the most optimized values is conducted through a matrix based on Markov Chain. The employment of the BO contributed significantly on building a robust CNN model and successfully handling EEG data. [PERSON] et al. [30] used two different techniques for MI-EEG classification on the BCI competition IV dataset 2a [9] and eight other pieces of EEG data [30]. On both methods, feature extraction was executed by a Filter Bank Common Spatial Pattern (FBCSP). After frequency band selection, the matrix containing salient features is fed into previously optimized conventional CNN to perform binary classifications of all classes. The same processed data are fed into four more evolutive CNNs classifiers. As a result, the accuracy improved. As can be noticed, individual models were used in the majority of EEG signal classification investigations. In our study, we focused on merging the optimum results of three robust CNNs trained separately. Besides that, none of the aforementioned studies used BO in conjunction with Ensemble Learning (EL) approaches. Consequently, they failed to meet near-perfect performance, which is unacceptable in the clinical context. This paper builds upon EL, DL, and BO to accomplish three major goals:  
* Design an efficient classification system by merging the top three best CNNs generated by the help of BO addressed for BCI-based rehabilitation uses. * Obtain competitive findings using BCI IV-2a competition data by reaching high levels of Precision, Recall, F1-score, Accuracy, and Kappa. * Highlight the significant contribution of BO and checkpoint call back techniques on boosting the performance of CNN on MI data. The paper is structured as follows: Section 2 discusses the proposed BO-based Average Ensemble approach for the classification of four EEG tasks, including the left hand, right hand, tongue, and feet. Section 3 illustrates the experimental results and a comparison of state-of-the-art strategies. Lastly, Section 4 concludes the paper.
# User Acceptance of Information Feed Advertising: A Hybrid Method Based on SEM and QCA
## 1 Introduction
To describe the impact of information feed advertising on users' acceptance intention, this paper proposes six influencing factors from the perspective of the characteristics of information feed advertising and the social network characteristics in the mobile Internet environment. Compared with existing studies, this paper considers the advertising effect, the factors of information feed advertising itself, and the social network characteristics in the mobile Internet environment, comprehensively describing the impact of information feed advertising on user acceptance. 2. To quantitatively describe the influence of various factors on users' acceptance of information feed advertising and analyze the impact of a combination of different factors on users' willingness to accept information feed advertising, we propose a two-stage hybrid research method based on SEM and QCA. In the first stage, SEM is used to analyze the influence of a single variable on user acceptance of information feed advertising. Then, in the second stage, the QCA method analyzes the effect of different variable combinations on user acceptance of information feed advertising. Compared with the existing work, our hybrid research method can analyze the influence of a single factor and further explore the impact of different combinations of various factors, which can better meet the practical application needs of information feed advertising. 3. Based on the actual network questionnaire data, we verify the hybrid research method. The SEM analysis shows that consistency, informativeness, sociality, and advertising reward have a significant positive impact on the user acceptance of information feed advertising, while perceived advertising clustering has a significant negative effect on user acceptance of information feed advertising. In addition, accuracy has no significant impact on user acceptance of information feed advertising. The QCA analysis reveals that seven different configurations of six variables can significantly enhance the user acceptance of information feed advertising. Thus, enterprises can improve user acceptance of information feed advertising, and the industry can choose the appropriate combination of factors according to its resource allocation conditions to maximize the user's willingness to accept information feed advertising. The rest of the paper is structured as follows. In Section 2, we briefly describe the related work of this study. Section 3 gives the research design. Section 4 presents data analysis and empirical results. Finally, in Section 5, we conclude the entire paper and discuss future work.
# An In-Depth Review on Blockchain Simulators for IoT Environments
## 4 A Systematic Review of Blockchain Simulators in IoT
### Comparative Analysis
#### 4.3.4 Ethereum + Ganache  
Ethereum is a decentralized, open-source blockchain with smart contract functionality. Ganache is a test blockchain simulator meant to simulate the Ethereum network and aid in the development of an application meant to be implemented on the Ethereum network. This is done by creating a user-friendly test network that can circumvent the need to set up an Ethereum client such as Geth or openEthereum [49].  
The Ethereum network is a well-established blockchain network that allows people to actively develop new and innovative applications and products that directly tie to Ethereum and use its native cryptocurrency, ether. This allows people to use a blockchain  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No. of Certificates** & **Gas Limit (Units)** & **Gas Cost** & **Gas Price (CGWED)** \\ \hline
1 & 22,645 & 147,633 & 100 \\
10 & 218,730 & 1,389,224 & 1000 \\
20 & 419,660 & 2,752,440 & 2000 \\
30 & 619,290 & 4,128,660 & 3000 \\
40 & 825,720 & 5,504,880 & 4000 \\
50 & 1,032,150 & 6,881,100 & 5000 \\
100 & 2,064,300 & 13,762,200 & 10,000 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Smart contract cost analysis generated using Blocksim. Reprinted/adapted with permission from Ref. [44]. 2021 IEEE.  
network that already has nodes and circumvent the need to set up self-hosted nodes for testing. However, some shortcomings include long transaction times and high gas prices.  
Ganache, being a development tool used by the Ethereum network, provides an easy testing ground for people trying to develop applications meant to be used on the Ethereum network. This limits Ganache to simulate blockchains that are based on Ethereum, meaning it might be difficult to simulate blockchains with different parameters [49].  
In terms of IoT environments that have used the Ethereum network or Ganache simulators to simulate blockchain, we see them being implemented in IoT devices, IoT communication, and IoT logistics. For the simulation of blockchain in IoT communications, Ethereum was the sole simulator. While in the simulations of blockchain within IoT devices and logistics, Ganache was used alongside Ethereum.  
In the secure IoT communication simulation, Ethereum was used purely to simulate blockchain security. This meant that Ethereum was used in hashing and encoding [50]. In smart devices, Ethereum was used as the base network for storing data via smart contracts and generating hashes [35]. All of this was simulated on Ganache since it is much more user-friendly than directly applying the simulation to the Ethereum network. Finally, in IoT logistics, Ganache was used to simulate a local blockchain while truffle was used to generate smart contracts. In this environment, the network simulated by Ganache was used to test data integrity stored on the blockchain, data tracking, and clearance check [30], with clearance checking referring to the process that ensures items being tracked fit the quality requirements.
# Underwater SLAM Meets Deep Learning: Challenges, Multi-Sensor Integration, and Future Directions
## 6 Practical Challenges in Underwater SLAM  
Underwater SLAM is a critical technology for enabling autonomous navigation and exploration in subaquatic environments. Unlike terrestrial and aerial SLAM--where communication infrastructure, computational resources, and power supply are relatively stable--the unique and often harsh conditions of underwater settings introduce a range of practical challenges that must be addressed to ensure reliable and efficient SLAM performance. These challenges span multiple domains, including communication, computational  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Reference** & **Challenge** & **Approach** & **Results** & **Limitations** \\ \hline Font et al. (2017) [72] & AUV navigation accuracy & EKF with USBL, IMUs, DVLs, and GNSS & Enhanced robustness & Requires precise calibration \\ \hline Rahman et al. (2018) [73] & Underwater mapping & Visual-inertial SLAM with acoustic data & Improved 3D reconstruction & Limited sensor coverage \\ \hline Thoms et al. (2021) [78] & Infrastructure inspection & LiDAR and sonar fusion & High-quality 3D maps & Complex sensor integration \\ \hline Hu et al. (2022) [79] & Localization drift & Visual-inertial-pressure fusion & Reduced drift & Relies on pressure data \\ \hline Cardaillac et al. (2023) [80] & Acoustic-optical matching & Camera and sonar fusion & Improved scale recovery & Requires calibration \\ \hline Qiu et al. (2024) [81] & Illumination issues & Acousto-optic feature association & Improved trajectory accuracy & Depends on beam positions \\ \hline Jang et al. (2021) [82] & Sensor mismatches & Opti-acoustic SLAM with style-transfer & Improved feature matching & Needs better natural object handling \\ \hline Xu et al. (2021) [83] & Poor visibility & Visual-acoustic bundle adjustment & Enhanced robustness & Needs high-quality data \\ \hline S. Ma et al. (2024) [75] & Scale estimation &
\begin{tabular}{c} Monocular-inertial-pressure fusion \\ \end{tabular} & Improved scale and pose accuracy & Requires stable pressure measurements \\ \hline Y. Huang et al. (2024) [76] & Stability under variable conditions & Multi-sensor fusion with refined data association & Improved stability & Complex calibration \\ \hline \hline \end{tabular}
\end{table}
Table 6: Summary of selected sensor fusion research in underwater SLAM.  
resource management, and energy efficiency, each significantly impacting the feasibility and effectiveness of underwater SLAM systems. This section delves into these key challenges, exploring their implications, surveying current solutions, and highlighting ongoing limitations.
## 5 Conclusions  
In summary, our research shows that blockchains can be a useful tool for managing product data in the context of a digital passport in a safe and transparent way. This is key for making products more eco-friendly and for meeting environmental regulations. The findings can serve as a basis for further studies and for applying this technology in various sectors.  
The application of DPPs in sectors such as automotive, electronics, construction, fashion, food, and pharmaceuticals enhances traceability, compliance, and sustainability by providing detailed, transparent, and tamper-proof information throughout a product's lifecycle. This promotes responsible production and consumption practices, reduces environmental impact, and supports regulatory adherence across these industries.  
Despite the numerous benefits of DPP technology, there are several challenges and limitations to consider. One major challenge is the integration of DPP systems with existing legacy systems and processes, which can be complex and resource-intensive. Another limitation is the scalability of the blockchain network. As the number of nodes increases, the system may face performance issues such as increased network latency and consensus overhead. Additionally, the initial setup and ongoing maintenance of a blockchain-based DPP system require significant investment in terms of time, money, and technical expertise.  
The widespread adoption of DPPs requires strong collaboration among stakeholders, including manufacturers, suppliers, regulators, and consumers. Achieving this level of cooperation and aligning interests across diverse groups can be difficult. Despite these challenges, the potential benefits of DPPs in promoting sustainability and enhancing product lifecycle management make addressing these limitations worthwhile.  
Conceptualization, M.H.; formal analysis, V.M.; investigation, V.M.; methodology, M.H.; software, R.M.; validation, R.M.; writing--original draft, M.H. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
**Institutional Review Board Statement:** Not applicable.  
Informed Consent Statement: Not applicable.  
**Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
**Conflicts of Interest:** The authors declare no conflicts of interest.