esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Conclusions  
The acoustic method using an acoustic Doppler current profiler (ADCP) can be applied for observing the distribution and migration pattern of zooplankton based on the MVBS variation as well as a vertical velocity profile. From the time series data, a relatively high MVBS that was indicated as the SSL was found near the seabed at \(11.5\) to \(16\) m. Combined moored and mobile ADCP provided insight into determining the spatial and temporal variation of zooplankton with their behavior. The DVM pattern was shown based on the echogram and vertical velocity profiles, which resulted in zooplankton moving to shallower depth during the night and moving to the deeper depth at daylight. The difference of theoretical TS (\(\Delta\text{TS}\)) from the DWBA model were then compared to the MVBS difference (\(\Delta\text{MVBS}\)) to identify the source of the strong scattering in the SSL, which showed that the dominant zooplankton species was not the main scatterers. The strong signal in the SSL was instead caused by the school of various zooplankton species. This study provides implications for understanding behavior or zooplankton using echo intensity analysis and vertical velocity profiles of an ADCP.  
**Author Contributions:** Conceptualization, A.D. and T.M.; Formal analysis, A.D. and T.M.; Funding acquisition, H.M.M.; Investigation, A.D.; Methodology, A.D., H.M.M., T.P., S.S. and T.M.; Software, A.D. and T.M.; Supervision, H.M.M.; Validation, T.M.; Visualization, A.D.; Writing--original draft, A.D.; Writing--review & editing, H.M.M., T.P., S.S. and T.M.  
**Funding:** The authors would like to acknowledge the Directorate General of Higher Education (DIKTI) for financially supporting this research through PMDSU Research Grant Scheme (No. 129/SP2H/PTNBH/DRPM/2018), also Directorate of Human Resource Qualifications, Directorate General of Resources for Science and Technology and Higher Education (DG-RSTHE), Ministry of Research, Technology and Higher Education of Republic of Indonesia for financially supporting this publication through Enhanced International Publication (EIP) Program (No. 1406.3/D3/PG/2018).  
**Acknowledgments:** This work is also supported by Marine Geological Institute, Ministry of Energy and Mineral Resources, Bandung, Republic of Indonesia. We sincerely thank the editors and reviewers for their constructive and valuable comments of our paper.  
**Conflicts of Interest:** The authors declare that there are no conflicts of interest.
# Particle and Particle Agglomerate Size Monitoring by Scanning Probe Microscope
## 3 Size-Monitoring Method with the Use of the SPM
For example, an image can contain lines significantly different from neighbouring lines due to the probe-surface interaction or 1/f noises [36]. There can also be brightness oscillations due to the final speed of the regulating system, surface contamination, vibroacoustic disturbances, and imperfect scanning system. Such disturbances influence the object shape and the position of key points. More complex, transformation invariant descriptors such as SIFT [37], SURF [38] can also be ineffective in the conditions of disturbances and distortions characteristic of the SPM. The analysis shows that specialized methods should be used for image matching instead of conventional ones. For example, it is logical if the centres of key points coincide with the particle centres and the information on the particle size is included in the key \begin{table}
\begin{tabular}{c c c c} \hline \hline
**SPM Model** & **Company** & **Range, mm** & **Minimal Step (Resolution), \(\upmu\)m** \\ \hline C3M Next II [23] & NT MDT & \(5\times 5\) & 0.3 \\ \hline AFM5500M [33] & Hitachi & \(100\times 100\) & 2 \\ \hline Dimension Icon [34] & Brucker & \(180\times 150\) & 2 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Characteristics of probe microscopes. point descriptor. It is also advisable to use the values of the platform sensors for determining the mutual orientation (displacement, angle of rotation) of the images (for example, in the topoStitch program [39], prior information on the image values can be used for image stitching). Considering the difficulties in solving the problem of particle agglomerate size monitoring by conventional methods, we propose a new integrated approach based on the use of:  
* The surface curvature detectors for correct image segmentation and particle detection;
* The detection results for overlapping images coordinate matching and sample displacement computation;
* The complexity of displacement sensors and the determined images overlap value for refinement of results.
## 6 Evaluation
### Performance Study  
This section discusses the performance results of the data monetization cloud architecture we explained in Section 5.3. The Substrate network is tested with a different configuration of 5, 10, 15, 20 and 25 validator nodes that participate in the variations of (1) AuRa and GRANDPA and (2) BABE and GRANDPA. We organize the test as follows:  
* A client that submits the transaction to the load balancer offloads the transaction to a node chosen based on the round-robin algorithm. The client is based on Javascript, which uses the library of Polkadot.js for the following purposes: 1. Establishing WebSocket communication to the Substrate node and retrieving the meta details of the network like pallet information, account details like a nonce, public key identifier and other miscellaneous details like chain information, fork information, block details and transaction details. 2. Transaction (extrinsic) construction with the signature using the private key of an account, encoding and decoding transaction payload, submission of the transaction and retrieving its status in the network as finalized or processing.
* For the test, the client submits the transaction of CreateAsset, which creates an asset NFT ERC 721 token in the network. Each transaction has a unique processing complexity based on its purpose logic, affecting its finalization rate or throughput in the network. The test transaction comprises the following complexity: 1. Calculation of Hash for generating a unique asset Id. Counted as one operation.  
Storage operation of asset details in asset storage, storing asset count, asset index, and ownership details in separate runtime storage structure either as a storage map, storage double map, or storage value. They are counted as 10 operations.
3. Read operation from storage to retrieve the existing details before any update. They are counted as five operations.
* Transactions (extrinsic) are submitted by the multithreaded client of 1000 threads signed by 2000 pre-generated accounts.
* Then, the transaction is submitted asynchronously at an input rate of 1000 transactions per second with 50,000 total transactions repeated in three iterations to avoid any bias in the result. The block size comprising extrinsic transactions is limited to five megabytes which is optimal as small size can induce message overload and bigger size can delay by a processing bottleneck.
* The submitted signed transactions are checked for finalization, and based on block number, the time difference is calculated for estimating the finalized throughput of the network.  
In the next section, we discuss the different test formats across the two consensus algorithm choice variations for the block proposer: AuRa (Authority Round) or BABE (Blind Assignment for Blockchain Extension) and block finalization based on chain level agreement: GRANDPA (GHOST-based Recursive Ancestor-Deriving Prefix Agreement).
## 2 Related Work
### Vehicle Trajectory Completion  
The completion of missing trajectories can be generalized as a trajectory prediction problem. In the early studies, trajectory prediction did not consider the interaction between individuals and only used historical data as the basis to predict the future trajectory [46; 47]. In recent studies, advanced deep learning methods used networks such as RNNs and graph attention and considered the interactions between individuals in the model, combinedwith individual historical trajectory data, to predict future trajectories [48; 49]. [PERSON] et al. proposed a vehicle trajectory prediction model based on graph attention [50]. The graph attention network simulates the interaction between vehicles and improves the authenticity and accuracy of the predicted trajectory. Experiments show that the model based on graph attention can effectively simulate the interaction between vehicles, and the model has a better effect on the task of vehicle trajectory prediction. In addition, geofencing has been shown to be a reliable method for trajectory prediction of vehicles (ground or aerial). Using the new kinematic model, combined with the geo-fence algorithm, the trajectory of vehicles in the area can be predicted [51; 52; 53]. There are also studies based on traffic flow and individual complete trajectories to complete the overall traffic flow trajectories. [PERSON] proposed a macro-micro integration framework for completing and reconstructing vehicle trajectories on the highway in a multi-source data environment [54]. The framework completes the vehicle trajectories using fixed-position sensor data to collect the position and speed of vehicles at a certain location and a small amount of probe vehicle (PV) data that generates continuous trajectories. Considering the feasibility of practical applications, we hope to improve the accuracy of the vehicle trajectory prediction model based on graph attention in our framework.
## 5 Conclusions  
We evaluated the spatiotemporal consistency among NASS winter wheat statistics (planted area, harvested area, grain production), CDL-derived planted area, and GPP\({}_{\text{VPM}}\) for 2008-2018 at national and county scales. High spatiotemporal consistencies of planted area from the CDL and NASS datasets were found. There were large disagreements between the CDL planted area and NASS harvested area in many counties, especially in the SGP. The correlation between annual total GPP\({}_{\text{VPM}}\) and grain production varied with individual counties, depending upon the differences between CDL planted area and NASS harvested area. It was found that the cumulative GPP\({}_{\text{VPM}}\) at an 8-day interval and HI\({}_{\text{GPP}}\) were able to accurately predict winter wheat grain production at the county scale from early May to late June. HI\({}_{\text{GPP}}\), calculated as the ratio of grain production over GPP, varied over a small range over different counties and years, when excluding those counties with large differences of CDL planted and NASS harvested areas, with a median value of 0.27. The results from this study highlight the importance of differentiating planted area and harvested area in crop mapping. Our results also demonstrate the potential of using GPP\({}_{\text{VPM}}\) products in estimating and monitoring grain production of winter wheat in the CONUS.  
Conceptualization, X.X. and X.W.; Methodology, X.W. and X.X.; data analysis. X.W. and X.X.; interpretation and discussion, X.W., X.X., J.S., Z.Y., Y.Q. and J.W.; writing, X.W. and X.X. led the early drafts, and all authors contributed to editing and revision of various versions of the manuscript; project administration, X.X., and funding acquisition, XX. All authors have read and agreed to the published version of the manuscript.  
This research was supported in part by research grants from the USDA National Institute of Food and Agriculture (NIFA, 2016-68002-24967), the US National Science Foundation EPSCoR program (IIA-1946093, IIA-1920946), and the NASA Geostationary Carbon Cycle Observatory (GeoCarb) Mission (GeoCarb Contract # 80 LARC17C0001).  
Not applicable.  
The gross primary production (GPP) data for the CONUS from the VPM model, driven by MODIS imagery, CDL cropland area data, and NCEP re-analysis climate data, are available upon request to the corresponding author.  
We thank three anonymous reviewers for their time and effort in reading the manuscript and providing their comments and suggestions, which help us to improve the manuscript.  
The authors declare no conflict 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.
# Light-Controlled Microbots in Biomedical Application: A Review
## 2 Prospective Applications
### Light For Cell Penetration  
Primarily transfection of genes, drugs, and proteins into cells is carried out primarily by chemical transfection, electroporation, sonoporation, hydrodynamic, magnetofection, and gene guns. These techniques are employed on clusters of cells and cannot be used when a single cell comes into consideration. Manipulation of a single cell requires high precision and can be achieved using an optical tweezer (OT) integrated with a spatial light modulator (SLM). [PERSON] et al. were the first to use a cavitation bubble formed by the breakdown of nanoparticles after being exposed to a pulsatile laser [114]. The laser-induced breakdown of the nanoparticle led to the formation of plasma and emission of shockwaves, subsequently vaporizing the nanoparticle and the surrounding liquid and forming a cavitation bubble. The bubble expansion from further ablation of the nanoparticle leads to local permeabilization of the cell membrane. Plasmids encoded with Mito-DsRed were transfected into human embryonic kidney (HEK) cells by laser-induced breakdown of 500 nm polystyrene nanoparticles. [PERSON] et al. successfully transfected plasmid-coated nanoparticles into the human breast cancer cell line, MCF-7 [115]. In this instance, they utilized a near-infrared (NIR) femtosecond laser pulse to perforate the cellular membrane. They successfully created a 3 \(\mu\)m hole in the cell membrane by subjecting the cells to a 75 mW laser for 100 ms. The transfected cell exhibited a green fluorescent protein under the fluorescence microscope, confirming the insertion of the plasmid-coated nanoparticles into the cell.
# Comprehensive Survey on VLC in E-Healthcare: Channel Coding Schemes and Modulation Techniques
## 4 Channel Coding Schemes for Error Correction in VLC in E-Healthcare Scenarios
### Reed-Solomon and LDPC Codes in VLC  
RS codes are block error correction codes that are particularly effective in correcting burst errors that occur in sequences, due to noise or interference. RS codes have been applied to VLC systems to maintain robust communication in environments prone to sudden signal degradation, such as indoor spaces where lighting conditions can fluctuate. RS codes perform well in scenarios with high SNR requirements, as they correct multiple errors within a block. However, the high computational complexity of RS decoding can limit their application in real-time, low-latency scenarios, such as e-health systems, where patient monitoring data must be transmitted and received quickly.  
LDPC codes, on the other hand, offer a more efficient alternative, with lower decoding complexity, while maintaining strong error correction capability. LDPC codes utilize a sparse parity-check matrix, enabling iterative decoding algorithms that rapidly converge to correct errors. In VLC systems, LDPC codes have been found to strike a balance between performance and complexity, making them suitable for applications that require high data rates and reliability. For example, in water-to-air VLC systems (W2A-VLC), the combination of RS and LDPC codes has been shown to significantly reduce the BER and frame error rate (FER), demonstrating improved communication reliability over noisy channels, even with varying transmitter-receiver distances [69].  
Moreover, recent advances in VLC systems have introduced coding schemes designed specifically to address flicker mitigation and dimming support, which conventional forward error correction (FEC) codes may not handle effectively. One such approach combines polar codes (PCs) with a Knuth balance code and enhanced prefix coding, to achieve flicker-free transmission while improving efficiency [70]. This scheme reduces computational complexity by eliminating lookup tables and generating minimal redundancy, which increases energy efficiency. The proposed coding structure offers significant improvements in transmission efficiency, particularly for dimming values of 75% (or 25%) and 87.5% (or 12.5%), compared to standard polar codes or polar codes with run-length limited (RLL) encoding. Furthermore, the scheme exhibits superior BER performance compared to traditional approaches, making it ideal for real-time VLC applications where flicker-free, energy-efficient communication is critical [71]. This integration of polar codes with optimized flicker and dimming support represents a significant step forward in the development of practical VLC systems, especially for healthcare settings where reliable real-time data transmission is essential.
## 5 Analysis of Simulation Experiments
### Analysis of Hyper-Parameters  
Figure 12(a),b depict the effect of the variance of the hyper-parameters \(\beta\) and \(\gamma\) upon the profitability of the system under RL(EK-CBM). It is depicted that both hyper-parameters affect the decision-making conducted by the agents of RL(EK-CBM). More specifically, in Figure 12(a), the \(\beta\) improves the performance of mechanism, when the former is equivalent to 0.005. This improvement is evident in simulation scenarios (e.g., scenario 20), wherein the system finds itself under frequent stochastic events, including increased order arrivals and recurrent system failures. In that case, it is likely that the agents initiated recurrent production and maintenance operations to address the current demand and deterioration within the system. This approach results in increasing the revenues in the system. Contrariwise, Figure 12(b) indicates that the small value of \(\gamma\) reduce the profitability of the system after scenario 20, where remanufacturing and refurbishing activities are not frequently authorized. Given the frequency of order arrivals and failures, the system did not produce enough products for customers. Instead, it is likely that it contained a large quantity of faulty products, which were scarcely remanufactured. As such, a substantial number of pending orders remained unfulfilled, resulting in increasing lost sales for the system.  
Figure 11: Analysis of revenues with comparison of **(a)** average production rate vs average failure rate, and **(b)** average remanufacturing rate vs average refurbishing rate.  
Figure 12: The comparison of average manufacturing rate against **(a)** remanufacturing and **(b)** refurbishing rates in terms of system revenues.
# Electro-Optic Properties of High-Efficiency Organic Electronics with the Addition of An Interlayer
## 4 Conclusions  
This study investigated the electro-optic properties of an OLED device with the addition of an interlayer. The difference according to the interlayer addition was clear. At the initial 3 V, Device (A) showed at least 200% efficiency at 0.12 (Cd/m\({}^{2}\)) luminance compared to Device (B) at 0.5 (Cd/m\({}^{2}\)). At the maximum emission of 11 V, the level of luminance was markedly higher for (A) at 1630.16 (Cd/m\({}^{2}\)) than (B) at 97.63 (Cd/m\({}^{2}\)) at the same voltage. In addition, the SAMs effectively reduced the hole injection barrier between organic films in each constituting layer of the OLED, which led to a higher current density of 1722 (mA/cm\({}^{2}\)) for (A) compared to the 84.955 (mA/cm\({}^{2}\)) for (B). As such, the device with the interlayer via SAM filming could reduce the work function between the basic ITO (4.8 eV) and light-emitting layer Alq3 (5.8 eV) to exert a carrier ladder effect and allow efficient hole carrier transport, which was shown to cause a low driving voltage and higher power efficiency and current density at the same voltage. In summary, the findings of this study suggest that an increase in OLED efficiency could lead to an increase in the performance of photobiomedical devices.  
Conceptualization, S.-G.P.; methodology S.-G.P. and S.-S.Y.; validation, S.-G.P.; formal analysis, A.B.; investigation, S.-G.L.; resources, A.B.; data curation, S.-G.L.; writing--original draft preparation, S.-G.L.; writing--review and editing, S.-G.P. and S.-S.Y.; visualization, S.-G.L.; supervision, S.-G.P.; project administration, S.-G.P. All authors have read and agreed to the published version of the manuscript.  
This research is funded by the Financial Program for Customized Research Capabilities in 2022.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
Figure 6: The curves of Power efficiency and Voltage characteristics with linear–linear scale.  
Figure 7: The curves of current efficiency and current density characteristics with linear–linear scale.
## 3 Results
### Single Module Motion Response Analysis of Offshore Airports
#### 3.2.2 Vertical Displacement  
For offshore oversized floating bodies, the amount of vertical deformation and vertical rigid body displacement are often on the same order of magnitude, which may lead to huge deformation of the structure and thus affect the safety performance of the offshore airport, so the amount of vertical displacement is an important reference indicator for the design of oversized floating bodies. Figure 14 shows the distribution curves of the vertical displacement amplitude of the single floating body with time under different incident rule waves; they are the amplitude of vertical displacement caused by elastic deformation, the amplitude of vertical rigid body displacement and the total vertical displacement amplitude after considering the influence of the first two, respectively. Figure 15 shows the amplitude of vertical displacement under the action of irregular waves incident in different wave directions.  
It is easy to see that as the wave angle increases, the amplitude of the vertical displacement of the floating body gradually increases. For regular waves, the loading will be initially displaced by the impact of wind and waves, and then will reach a relatively stable vibration range under the dragging effect of the mooring, with small undulations, which basically has no impact on the safety performance of the airport. On the contrary, with the changing curve of vertical displacement amplitude under irregular waves, the displacement amplitude caused by elastic deformation is small. The rigid body vertical displacement plays a dominant role, and when the wave incidence angle increases, the rigid body displacement peak peak increases, which is more obvious in extreme weather  
Figure 14: Magnitude of vertical displacement under waves with different incidence rules. (**a**) Elastic deformation; (**b**) Total displacement; (**c**) Rigid displacement.  
Figure 13: Von [PERSON] stress variation clouds under different wave directions. (**a**) t = 40 s; (**b**) t = 70 s; (**c**) t = 140 s.  
conditions, and will seriously affect the normal work of the offshore airport. It is worth noting that the total vertical displacement amplitude of the floating body cannot be considered as a simple superposition of the vertical displacement amplitude of the rigid body and the elastic deformation amplitude.