esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Ship collision avoidance (CA) is the most fundamental and essential issue of maritime safety, regardless of whether the ship is a conventional ship or a future maritime autonomous surface ship (MASS). However, effective ship-to-ship communication has been recognized as a critical issue and one of the major challenges affecting the success of ship CA. This study intends to investigate the basic trust concerns in the cybersecurity components of the ship CA process and develop a blockchain-based solution for trustworthy communication. The novel idea behind applying blockchain to ship CA decision-making is that the various participating ships in a scenario of dynamically changing ship encounters form a decentralized network of opportunities, which makes blockchain an appealing tool to offer a solution for evaluating and maximizing trust in entity dynamics. The mechanism of entity participation in upholding a master chain for avoiding ship encounters is described in this work. The research begins by analyzing conventional ship CA decision scenarios under COLREGs in order to identify formal communication strategies that can make information more understandable. Based on this, it is demonstrated how beliefs of trust (BoT) between entities are encoded and combined on the chain to enable entities in the encounter scenario to form an initial opinion about another entity before becoming familiar with it. This first encounter occurs during ship CA. Second, this article examines how encounter ships have temporary rights in the process of making CA decisions. This generates blocks and attaches them to the chain at the consensus layer of blockchain technology. Finally, this study undertakes a case test of ship CA based on the aforementioned communication principles. In order to ensure safe and effective communication during brief, one-time ship encounters, the results offer a practical method for conveying CA reasoning in encounter scenarios. As a result, it can aid in the selection of better (more reliable) nodes to uphold the evidence-based understanding of the ship CA process and assess the reliability of unidentified members.  
maritime safety; ship collision avoidance; blockchain-based communication; decision-making logic +
Footnote †: journal: Applied Sciences  
Article An Approach of Consensus-Based Double-Layer Blockchain System for Multi-Ship Collision Risk Mitigation Considering COLREGs  
[PERSON], [PERSON], [PERSON], [PERSON], [PERSON], G. An Approach of Consensus-Based Double-Layer Blockchain System for Multi-Ship Collision Risk Mitigation
### Explicit Analysis for Contact Problems in Rolling  
Numerical methods used by FEM software to solve contact problems can influence the computational time and simulation accuracy. As suggested by the Abaqus manual, explicit dynamics solution techniques can be more computationally efficient and reliable than implicit methods for 3D rolling models with complex geometries, nonlinear material properties and discontinuous effects such as contact and friction [52]. However, [PERSON] et al. [54] found that for simple loading conditions with rigid bodies involved in contact simulation, implicit analysis solver requires less computational time than explicit analysis solver. The explicit method was found preferable for complex contact interactions, for example, between deformable bodies or where large deformation is involved. The explicit method demonstrates increased robustness/convergence and greater suitability for parallel calculations using multiple processors [54]. In contrast, [PERSON] et al. [55] suggested that the implicit method is more accurate and efficient, although less robust than the explicit method.  
To accelerate explicit analysis for quasi-static problems, material density can be artificially increased (i.e., using mass scaling method) [52]. However, with aggressive mass scaling, inertia starts to play a significant role in the solution and will affect the result [48]. To restrict the artificial inertia effect, it is recommended by [PERSON] et al. [56] and Abaqus Analysis User's Guide [48] that the ratio between kinetic and internal energies of the model should be maintained at no larger than 5%.  
Specifically for rolling, the problem can be treated as quasi-static and solved by the explicit method for FEM analysis. For instance, [PERSON] et al. [41] investigated RS in railway axles that experienced multi-run parallel deep rolling. [PERSON] et al. [42] created a model to optimise the deep rolling process for IN718 turbine blades and 42 CrMo4 crankshats, in which a mass scaling factor of 250 was used and a reduction in CPU time by two-thirds was achieved without impairing the accuracy. [PERSON] et al. [45] developed a rolling model to predict the RS in a rolled bearing race, and a mass scaling factor of 400 was adopted to reduce computational time.
# Improved Anticancer Activity of the Malloapelta B-Nanoliposomal Complex against Lung Carcinoma
## 1 Introduction  
Lung cancer is the leading cause of cancer-related death worldwide (18.4%), and is especially prevalent in male smokers [1]. The most common type of lung cancer is non-small cell lung cancer (NSCLC), accounting for 85% of cases of lung cancer [2]. Approximately 40% of lung cancers are adenocarcinomas, and most cases of lung cancer in smokers are of this type. Several therapeutic methods are available for treatment of lung adenocarcinoma, including surgery, radiofrequency ablation, radioactive therapy, chemotherapy, and immunotherapy, alone or in various combinations. However, these therapeutic options are not only expensive but also insufficiently effective. Therefore,there is an increasing need for new, safer, and more effective clinical treatments. Our previous study showed that 1-(5,7-dimethoxy-2,2 dimetyl-2H-cromen-8-yl)-but-2-en-1-on (malloapelta B), isolated from _Mallotus apelta_, is a potential active anticancer compound [3]. This compound, malloapelta B (malB), inhibits the activation of nuclear factor kappa B (NF-\(\kappa\)B) with an IC\({}_{50}\) value of 5.0 uM. This IC\({}_{50}\) value is much lower than that of parentonolide (PTN, 6.66 \(\pm\) 0.07 uM) [4; 5]. The compound was also shown to downregulate genes that contribute to inflammatory mechanisms, such as tumor necrosis factor (TNF)-\(\alpha\), interleukin (IL)-6, and II-1B [6]. Additionally, as reported, the enone side chain may play an important role in the activity of this molecule [4]. However, the potential effects of malB against lung carcinomas in vitro and in vivo have not been studied in detail. In addition, its high toxicity and low solubility represent barriers to the development of malB as an anticancer drug for use in chemotherapy. Nanoliposomes have recently emerged as ideal drug carriers with a number of beneficial characteristics, including minimal immune response, biocompatibility, biodegradability, reduction of drug toxicity, etc. [7]. Nanoliposomes can be used to encapsulate hydrophobic drugs as a means of improving their solubility in water. Due to these advantages, a number of nanoliposomal formulations incorporating different anticancer drugs are available commercially, including daunorubicin (DaunOxome), doxorubicin in PEG-liposomes (Doxil), vincristine (Marqibo), topotecan (INX-0076), nystatin (Nyotran), and paclitaxel (LEP-ET) [8]. Therefore, in the present study, malB was entrapped in nanoliposomes at different concentrations, and anticancer activities of these malB-nanoliposomal formulations against lung carcinomas were examined as well as their anti-malignant potential in Lewis lung carcinoma (LLC) tumor-bearing mice.
# Tracking of Moving Targets Through Asynchronous Measures
## 5 Conclusions  
The proposed 3D tracking algorithm, developed for updating the position for every single ranging measure, can offer significant advantages in critical scenarios and use cases such as a lack of LoS anchors, serial measures, and fast-moving targets. However, accurate range measurements are required in order to observe significant improvements over commonly used algorithms. In standard non-critical scenarios, the proposed algorithm performs similarly to the standard ones; thus, we think it might represent a simple and effective option to tackle the problem of 3D tracking in challenging use cases, especially in the field of UAV applications.  
It is worth highlighting that the proposed algorithm has been tested only through simulations, and the effects of some parameters have not been considered. Therefore, future work should include experimental tests to improve the validity and generality of our results, including the integration of estimates from other sensors such as GNSS and inertial navigation systems. Moreover, the algorithm is currently designed for the implementation with Two-Way Ranging systems, and would need to be updated in order to deal with Time Difference of Arrival (DToA) systems as well.  
Conceptualization, A.F.; methodology, A.F. and L.R.; software, A.F.; validation, A.F. and L.R.; writing, A.F. and L.R.; visualization, A.F. and L.R.; supervision, L.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding authors.  
The authors would like to thank Leonardo S.p.A. for funding [PERSON] PhD in Information Technology at Politecnico di Milano and also for the fruitful cooperation, which has inspired the topic covered in this article.  
The authors declare no conflicts of interest.  
Figure 6: Positioning root mean square error of the vertical (V) and horizontal (H) components with \(v=10\,\mathrm{m/s}\), \(\sigma_{p}=0.1\,\mathrm{m}\), \(r=1000\,\mathrm{m}\) and \(p=100\%\).
## 3 Fractional Factorials and Aliasing  
Statistically designed experimentation (i.e., design of experiments or DOE) is a formal 'deductive' methodology, where independent variables (factors) are manipulated at different settings (levels) in a controlled fashion to explore optimization problems for key response variables. [PERSON] [45] is the father of DOE and expanded on the classic analysis of variance (ANOVA) methodology. A 'full factorial' DOE has experimental runs with replicates at all possible levels for all of the factors. Even though full factorial designs are the most informative designs, such designs are expensive.  
[PERSON]. [PERSON] was influenced immensely by [PERSON]'s work and studied under [PERSON] at the University of London [46]. He developed a series of designs known as'response surface methods' (RSM) which allows researchers to use a fraction of the total experimental runs (fractional factorials). [PERSON]'s popular 'central composite' and 'Box-Behnken' RSM designs [1] minimize the number of experimental runs, while sustaining inference. A key consideration for RSM and any type of fractional factorial design is the aliasing structure of the design. Resolution III designs are designs where two-level interactions are aliased with main effects and other two-level interactions, and are typically avoided given that two-level interactions are typically significant. For example, a \(\frac{1}{2}\) fraction \(2^{k-1}\), \(k=4\) with a replicate has \(n=16\) experimental runs is a Resolution III design with aliases: A = BC, B = AC, C = AB, AB = CD, BC = AD, and AC = BD. Generally, analysts select the highest possible design resolution (e.g., resolutions \(\geq\) IV) when choosing a design to avoid confounding main effects. If the analyst conducts a fractional factorial design and does not have a detailed knowledge of the phenomenon under investigation, an aliasing structure is assumed. By developing RT models as a possible first step for the factors under investigation, unknown interactions and split-points may be discovered. This may accelerate innovation by choosing statistically significant interactions for a DOE that lead to lower costs of experimentation.
## 2 Materials and Methods
### Analysis Methods
#### 2.3.2 Ensemble Empirical Mode Decomposition  
Ensemble empirical mode decomposition (EEMD) was used to study the fluctuation and trend of carbon fluxes and meteorological factors [60; 61; 62; 63]. The main principle of this method is to decompose the original data into independent modes, including intrinsic mode functions (IMFs) with different characteristic scales and a trend component.  
\[X_{j}(t)=\sum\limits_{i=1}^{n}S_{ij}(t)+r_{j}(t) \tag{10}\]  
\(X_{j}(t)\) is the original data sequence, \(S_{ij}(t)\) is the component of different IMFs, and \(r_{j}\) is the trend term. The variation period of each IMF component is:  
\[P_{K}=\frac{L}{E_{K}} \tag{11}\]  
where \(L\) is the length of the IMF component and \(E_{k}\) is the number of extreme points of the \(k\)-th IMF component. The importance of the IMF components at various timescales can be estimated by the variance contribution rate:  
\[V_{i}=\sum\limits_{k=1}^{k}\left(S_{i}(t)\right)^{2}-\left(\sum\limits_{k=1}^ {k}S_{i}(t)\right)^{2} \tag{12}\]  
\[V=\frac{V_{i}}{\sum\limits_{i=1}^{i}V_{i}}\times 100\% \tag{13}\]  
where \(V_{i}\) is the variance of the ith component \(S_{i}(t)\), and \(V\) is the variance contribution rate of this component. The greater the \(V\) value is, the more powerful the ability of this component to reflect the original sequence, and the higher its importance.  
\begin{table}
\begin{tabular}{c c c} \hline \hline \(\beta\) & 1\(Z_{\text{mk}}\!\mid\) & **Meaning** \\ \hline \(>\)0 & \(>\)1.96 & Significant increase \\ \(>\)0 & \(\leq\)1.96 & Increase \\ \(<\)0 & \(>\)1.96 & Significant decrease \\ \(<\)0 & \(\leq\)1.96 & Decrease \\ \hline \hline \end{tabular}
\end{table}
Table 2: Classification of Carbon Flux Trend.
###### Abstract  
The three-dimensional (3D) reconstruction of Electromagnetic Tomography (EMT) is an important task for many applications, such as the non-destructive testing of inner defects in rail systems. Additionally, image reconstruction algorithms utilizing deep learning methods have been verified to be useful in recent years. Therefore, the interpretability of deep learning is a question that is relevant to its application in other areas. This paper proposes an innovative rotational convolution pattern, Conv-P, for convolutional neural network (CNN) image reconstruction in a 3D EMT system. This pattern is based on the projection relationships inherent in tomographic imaging, where each convolution is performed on adjacent projections along the excitation rotation direction. The advantage of this pattern is that it can generate the convolution process by utilizing the 3D structural information from real sensors. To verify the effectiveness of this convolution pattern, we constructed a 3D dual-layer 16-coil EMT model and tested its image reconstruction performance. The results demonstrate that, compared with two common convolution patterns, Conv-P achieves a 4.7% and 4.1% increase in the Image Correlation Coefficient (CC), a 19.8% and 13.1% reduction in the Relative Image Error (IE), a 0.67% and 1.59% increase in the Peak Signal-to-Noise Ratio (PSNR), and a 3.24% and 0.74% increase in the Structural Similarity Index Measure (SSIM).
## 3 Experimental Test Procedure
### Creation of a Numerical Model Used for Control Data  
Based on the measurement and geometry data for the beam, measured on the test site and extracted from the point cloud and LVDT measurement data, a numerical model of the beam was created. The used numerical model was modeled in commercially available software SCIA Engineer 19.2 based on a finite elements method (FEM) structural analysis, which is the standard in civil engineering [34]. The inputs for the model were the dimension and orientation of the wooden beam, mechanical properties of the timber material, and load. The material was timber class C14 (EN 338), with a modulus of elasticity of 7000 MPa and a shear modulus of 440 MPa. The load was applied to an area 200 \(\times\) 70 mm in the middle of the top surface. The ultimate load was 16.9 kN/m\({}^{2}\). The load was deduced by comparing the maximum displacement of the model and was obtained from LVDT measurement. This approach accurately defined the material model instead of the general normative timber model. While performing numerical analysis, anisotropic properties of timber were not taken into account since displacements are due to bending, and along-grain stresses were dominant. The outputs of the model are displacements of points on the beams and internal forces, which were not used within the scope of this paper. Based on the numerical model, z-axis displacement (change of height) were calculated for every point on the beam in each epoch, as shown for epoch 214 displacement in Figure 13. It should be noted that the test beams were not perfectly horizontal in space; also, the wooden supports were not perfectly horizontal and perpendicular to the beams. All the imperfections in the setup were accounted for and inputted in the model for calculations of displacements based on point cloud data. Coordinates of the numerical model were in the same coordinate system, which was defined by the instrument setup.  
Figure 12: Example matching points between epoch 210 and 214 for BEAM 1 (Source: Own compilation).
# Directional Paging for 5G Communications Based on Partitioned User ID
## 5 Conclusions  
In this article, we propose the Partitioned user ID based Directional Paging (PIDP) mechanism for mmWave-enabled directional 5G communications. The paging resource overheads are significantly higher for directional communications as beam sweeping becomes essential to cover the area of a cell. The proposed PIDP mechanism reduces the UE ID size included in the paging message, which is transmitted over multiple beams, to reduce the paging resource overheads. To ensure that the UE ID information is not compromised in PIDP, the configuration and distribution of UE over various paging occasions are also modified. PIDP manifests around 15% gain with a 20% shorter UE ID when compared to directional paging with the full UE ID included in the paging message transmitted over multiple beams.  
[PERSON] created the basic idea; [PERSON] mathematically analyzed the proposed technique; [PERSON] performed computer simulations; [PERSON] and [PERSON] wrote the paper.  
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT (Ministry of Science and ICT, Korea) ) (NRF-2018R1C1B6008126).  
The authors declare no conflict of interest. The founding sponsors had no role in the design of the study; in the collection, analyses or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.
# Review of Blockchain Tokens Creation and Valuation
## 3 Blockchain Tokens Development
### Creation
#### 3.3.1 ERC-20 Fungible Token  
ERC20 is the standard for creating FTs--digital assets that are equivalent and interchangeable with one another [58]. This standard specifies a common set of rules all ERC20 tokens must adhere to, ensuring consistency. Also, it offers an environment where they can be easily traded, managed, and implemented within a vast array of decentralized applications. Having multiple versions over the years, the latest version of ERC20, which can be directly imported into any smart contract and inherited by your code, is also efficient in terms of gas consumption and method calls.  
Algorithm 1 shows the creation of a basic, FT on the Ethereum blockchain by importing the ERC20 standard interface and inheriting it in the contract. The creator needs to specify the FT name and symbol and mint the entire initial supply of tokens in the wallet that deploys this contract. There are other methods for creating the token supply, such as allowing the owner to create tokens whenever they want or minting new tokens at each transfer, etc.  
```
1:pragma solidity '0.8.20;
2:import \"@openzeppelin/contracts/token/ERC20/ERC20.sol\";
3:
4:contract DemoTokenERC20 is ERC20 {
5:constructor (uint256 initialSupply) ERC20(\"Demo\", \"DMO\") {
6:__mint (Ms. Sender, initialSupply);
7:}
8:}
```  
**Algorithm 1**Smart Contract 1--DemoTokenERC20.  
Algorithm 2 shows the interface defined by the ERC20 standard to which all of the tokens must adhere and implement. The _totalSupply_ function will return the total number of tokens in existence, while the _transfer_ function moves several tokens from the caller to an account address and returns a _Boolean_ value indicating the operation's success. The function _transferFrom_ uses an allowance mechanism, where the wallet representing the 'from' parameter must allow the caller of the _transferFrom_ method to spend tokens on its behalf.  
```
1:pragma solidity '0.8.20;
2:Interface IERC20 {
3:function totalSupply () external view returns (uint256);
4:function transfer (address to, uint256 value) external view returns (uint256);
5:function transferFrom (address from, address to, uint256 value) external view returns (uint256);
6:function balanceOf (address account) external view returns (uint256);
7:function allowance (address owner, address spender) external view returns (uint256);
8:function approve (address spender, uint256 value) external returns (bool);
9:}
```  
**Algorithm 2**Smart Contract 2--IERC20.  
Finally, there are multiple variations of this interface, which further enhance its functionality and use cases, such as [100]: ERC20 Detailed, ERC20 Burnable, ERC20 Pausable, Lockable, etc. All of these are based on the basic ERC20 contract, and they add some functionality on top of it.
# Considering Uncertainties of Key Performance Indicators in Wind Turbine Operation
## 5 Results
### Data Completeness  
The importance of complete inputs for the calculation of KPIs is discussed in this section using the example of an air density measurement. Figure 6 shows the impact of the missing air density measurement and the quality of different approximations on the calculation of wind power density. If no air density measurement is available, it is common to use the standard atmosphere of 1.225 kg/m\({}^{3}\). If the considered site or nacelle is at a higher altitude, this assumption leads to systematic high results. A correction for altitude likely results in an underestimation since the average temperature is usually below the standard temperature of 15 \({}^{\circ}\)C. If the air density is also corrected for the average temperature, a yearly wind power density KPI is already close to the reference as lower and higher temperatures balance out. Good results and drastically reduced deviations are achieved when temperature measurements are available.  
If the small and systematic underestimation of the air density is ignored, the remaining deviations can be explained by weather-related pressure fluctuations. Thus, the uncertainty of an approximated air density can be derived from a known and site-specific distribution of the air pressure. As the sensitivity of the air density to changes of the humidity is low, the recommendation of the IEC standard 61400-12-1/2 [30; 31] to use a default humidity of 50% is reasonable.  
The presented results are validated against the North Sea WF data. The higher weather-related standard deviation of air pressure at the offshore location led to a higher standard deviation of the air density and thus of the wind power density. The discussed uncertainty propagates through the power curve to the production-based availability.  
Figure 5: Effect of decreasing data availability on the uncertainty of power curves. The uncertainty is represented by deviations in the calculation of a generic annual energy yield using a rayleigh wind speed distribution (6.45 m/s) as reference.  
Figure 6: Monthly sensitivity of the mean wind power density to missing information.