esa-sceva/satcom-chunk-collection huggingface dataset:
###### Abstract  
Mercury intrusion porosimetry (MIP) has been utilized for decades to obtain the pore size, pore volume and pore structure of variable porous media including inorganic rocks and organic rock (e.g., shales and coals). Diffusivity and permeability are the two crucial parameters that control gas transport in coals. The main purpose of this work is to derive the CH\({}_{4}\) effective gas diffusivity and permeability in different rank coals with vitrinite reflectance of 0.46-2.79% R\({}_{\rm o,m}\) by MIP. Furthermore, regular CH\({}_{4}\) diffusivity and permeability measurements are conducted to compare with the results of the derived CH\({}_{4}\) diffusivity and permeability with MIP data. In this work, CH\({}_{4}\) diffusivity and permeability of different rank coals are acquired with established equations, which are basically in accordance with the experimental values. However, the coal rank (maximum vitrinitere flectance, R\({}_{\rm o,m}\)) exhibits no significant relation to the effective diffusion coefficient (_De_) and gas diffusivity (\(D^{\prime}\)). The cementation factor (m values) varies from 2.03 to 2.46, which tends to exhibit a semi-consolidated structure for coals compared with other rocks (e.g., dolomite, limestone, sandstone and red brick). The results show that the cementation factor could be an important factor for gas flow in coals. The correlation of CH\({}_{4}\) diffusivity to porosity and permeability of 12 coal samples were explored, and it appears that CH\({}_{4}\) diffusivity exhibits an increasing trend with an increase of permeability, and two different exponential relationships respectively exist in diffusivity versus porosity and permeability versus porosity. Therefore, this study could be conducive to gas sequestration or gas production during enhanced coalbed methane (CBM) recovery.  
mercury porosimetry; CH\({}_{4}\) diffusivity; cementation factor; permeability +
Footnote †: journal: Applied Soft. 2018, 8, 860; doi:10.3390/app8060860
## 5 Conclusions  
In this paper, we propose a signal processing mechanism of optical interference cancellations over OCDMA networks. An intelligently structured receiver based on AWG with correlation decoding and balanced subtractions is implemented. The proposed scheme progressively reduces the receiver noises through recursively canceling interferences from other users. Therefore, the network is allowed to support high-speed transmissions under an acceptable noise floor. Analytical and simulation results show that the proposed receiver offers a significant improvement in data rates. At a BER of 5.07 \(\times\) 10\({}^{-9}\), the proposed RIC scheme provides up to twenty simultaneous users with a bit-rate of 5.2 Gb/s, achieving a total network capacity of 104 Gb/s.  
For future research work, employing other OCDMA codes with better correlation properties in RIC is an exciting topic. For M-sequence codes using in this paper, although RIC significantly reduces the PIIN variance, the residual noise power is considerable due to the large cross-correlation value (\(\lambda=N/4\)). Balanced incomplete block design (BIBD) code [30] is a promising solution to this bottleneck, as it has an ideal cross-correlation value (\(\lambda=1\)) and the cyclic-shift property perfectly matching the AWG characteristic. However, the receiver architecture, including the input/output port connections between AWGs, still requires further designations.  
[PERSON] contributed to the conceptualization, methodology, and writing of this paper. [PERSON] conducted the investigation and formal analysis. [PERSON] conceived the simulation setup and contributed to writing--review & editing.  
This research received no external funding.  
The authors declare no conflict of interest.
## 1 Introduction
In addition, it is implicitly assumed that for each pixel there is at least one sample available. If there is a pixel which is not included in any marred sample, this method cannot recover it. Another well-known method for gappy data reconstruction is the Gappy Proper Orthogonal Decomposition (POD) method [12; 13], which was proposed as an extension to POD considering the incomplete datasets. POD captures most of the phenomena in a large amount of a high-dimensional dataset while representing it in a low-dimensional space which causes a significant reduction in required computational power [14]. This technique has been used in various problems such as fluid dynamics [14], active control [15], and image reconstruction [16; 17], to name a few. The original POD uses the fully-sampled dataset in order to reconstruct the POD basis functions. Even though Gappy POD aims at reconstructing gappy datasets, it, in fact, relies on the presence of a set of completely-known standard POD basis vectors which we believe makes the whole method inapplicable when there is no such set available. Also, a POD-based method for denoising and spatial resolution enhancement of 4D Flow MRI datasets is proposed by [PERSON] et al. [18]. This method uses a set of POD basis vectors as the reconstruction basis where the set of POD basis vectors is derived from the results of a computational fluid dynamics (CFD) simulation. Even though this method was shown to outperform the competing state-of-the-art denoising methods, the fact that it is specifically developed for noisy 4D Flow MRI datasets makes it impractical for the datasets resulting from other types of dynamic systems. None of these methods take into consideration the dynamics of a given dataset. In the work presented here, an approach similar to csDMD was taken. With csDMD, the aim is to reconstruct the DMD mode shapes based on some given set of basis vectors, whereas, in our approach, called DMDct hereafter, given the DMD eigenvalues obtained from the sub-sampled dataset, the full dataset is reconstructed through an \(l_{1}\)-minimization scheme. Similar to csDMD, DMDct relies on the proper choice of the underlying basis functions. In this paper, we specifically focus on 2-D problems defined over a rectangular grid of equally-spaced nodes. By considering this specific geometry, we can take the one-dimensional discrete cosine transform (DCT) basis vectors and use them for building the two-dimensional basis vectors implicitly, hence requiring less memory.
# Inland Water Level Monitoring from Satellite Observations:
## 4 Discussion
Lastly, the terrestrial water level is a useful component of the river discharge essential climate variable (ECV), among the 55 variables that were carefully selected and defined by the Global Climate Observing System (GCOS) to help in understanding and tracking the changes and progress of various components within the Earth system. Therefore, the current study contributes also to the call by remote sensing and hydrological communities for inland water level monitoring in the framework of the ongoing development of the concept of essential climate variables (ECVs) [147; 148]. Additionally, future research should be conducted summarizing and disseminating the research findings concerning river discharge monitoring through satellite observations.
## 6 Simulation Results
### Computational Overhead  
The energy consumption in LWSNs is mainly due to data transmission. Thus, it is particularly important to reduce data redundancy and detect false data as early as possible. The energy consumption in this scheme mainly includes the computational overhead of encryption and decryption, the computational overhead of MACs and data communication overhead. The total number of computations in this scheme is shown in Figure 4, which is affected by the number of monitoring nodes and contains the computation of encryption, decryption and MACs. As shown in Figure 4, as the monitoring nodes increase, the total number of computations becomes larger. Since the DAA needs to encrypt and decrypt hop-by-hop, its number of computations is more than FESA.
# Visual Ranging Based on Object Detection Bounding Box Optimization
## 6 Conclusions  
The bounding box optimization method proposed in this study aims to improve ranging accuracy by eliminating the pixel gap between the bounding box and the object. This method can also be applied to other ranging methods (such as the imaging model method) to enhance ranging accuracy. In addition, in the preprocessing part of this method, we performed image enhancement using the CLAHE method to eliminate the influence of uneven illumination and blurred target boundaries on segmentation, which produced good  
Figure 11: Comparison of distance visualization before and after optimization for serial number 1: (**a**) distance visualization before optimization at point O\({}^{\prime}\); (**b**) distance visualization after optimization at point O\({}^{\prime}\); (**c**) distance visualization before optimization at point O\({}^{\prime\prime}\); and (**d**) distance visualization after optimization at point O\({}^{\prime\prime}\).  
segmentation results. Although this method produces good results, it increases the time cost and is not suitable for real-time tasks. In the future, a fuzzy segmentation algorithm, such as the fast generalized fuzzy c-means (FGFCM) algorithm, can be used for segmenting the original image to achieve higher efficiency and more accurate segmentation.  
The proposed similar triangle ranging method based on height difference is only suitable for fixed targets, because the method needs to adjust the height of the camera to achieve distance measurement. Thus, it cannot be applied in ranging for moving targets. In addition, the distance measurement experiments in this study were conducted within a range of 6 m. If one wishes to measure targets at a greater distance, it is possible to adjust the camera height and pitch angle to achieve longer distance measurements. However, ensuring that the target can be captured at both heights is a prerequisite for utilizing the ranging method described in this paper. Otherwise, if only one image containing the target is available, it is not possible to measure the distance to the target using the method described in this paper.  
Conceptualization, Z.S. and Z.L.; methodology, Z.S.; visualization, Z.S. and S.C.; investigation, M.G. and H.T.; experiment, Z.S.; writing--original draft preparation, Z.S.; validation, Z.L. and S.C.; project administration, Z.S., Z.L. and S.C.; funding acquisition, Z.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Key Research and Development Program of Jiangsu Province, grant number BE2022062.  
Not applicable.  
We would like to acknowledge the funding of Key Research and Development Program of Jiangsu Province and thank our team members for their help and encouragement.  
The authors declare no conflict of interest.
## 3 Results and Discussions
### Simulation Results of Brain Functional Sensing
The \(C\) values of gray matter and vessel were 200 \(\upmu\)m and 4 mM, respectively, and the \(Y\) values were both 70%. The simulation results are shown in Figure 10. Figure 10a shows the CW fluence extracted at plane \(y=0\)\(\upmu\)m. The structure parameters of the simulated tissue are also indicated. The blue curve in Figure 10b is the backscattered signal, and the fitting results of the gray matter and vessel are shown in the picture. The final fitting results and calculated \(C\), \(Y\), and \(S\) from the fitting results are listed in Table 6. We can see that the calculated \(C\) and \(Y\) are incorrect because the absorption of gray matter is too small in the near-infrared waveband. By contrast, the calculation results for blood vessels are much more accurate. In the simulations of this paper, we did not simulate the OCT signals of all wavelengths within the spectral bandwidth of the light source but thought that the extinction coefficient is homogeneous within a certain spectral width, which undoubtedly leads to certain errors. In the visible-light waveband, the maximum wavelength bandwidth set in this work was 15 nm, which has proven to be reasonable [36]. In addition, the impacts of the STFT process on functional sensing were not studied. We will optimize the MMC-OCT program to simulate the complete imaging process of the spectroscopic OCT in future researches. \begin{table}
\begin{tabular}{c c c c c} \hline \hline \(\lambda\) (nm) & \(\epsilon_{O}\) (mmol\({}^{-1}\)-mm\({}^{-1}\)) & \(\epsilon_{D}\) (mmol\({}^{-1}\)-mm\({}^{-1}\)) & \(S\)-Gray (mm\({}^{-1}\)) & \(S\)-Vessel (mm\({}^{-1}\)) \\ \hline
750 & 0.052 & 0.176 & 7.625 & 76.25 \\
800 & 0.083 & 0.102 & 7.3 & 73 \\
900 & 0.122 & 0.1 & 6.65 & 66.5 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Optical parameters of gray matter and blood vessel at selected wavelengths.
# Internet of Things and Blockchain Integration: Security, Privacy, Technical, and Design Challenges
## 3 RQ 1 and RQ 2--Current Challenges and Recommendations to Enhance BIoT Integration
### BC-Based Privacy
#### 3.2.1 Identity Privacy
Supplementary data are stored separately and are subject to technological and organizational safeguards to prevent personal data from being linked to an identified or identifiable natural person. [10]. In most cases, pseudonymization is accomplished by substituting user identities with pseudonyms, i.e., particular form identifiers that do not enable the re-identification of persons on their own. Because each wallet user is assigned a unique address that appears to be random (i.e., produced by cryptographic procedures and serving as a pseudonym), BC cryptocurrency platforms such as Ethereum and Bitcoin adopt pseudonymization procedures. Other approaches to improve anonymity include blind signatures, homomorphic commitments, ring signatures, composite signatures, mixing services, and zero-knowledge proof [26]. To commit data without exposing them to others, homomorphic commitments employ homomorphic encryption. Confidential transactions leverage homomorphic promises to mask transaction amounts. Before signing the message, the message owner blindfolds the content using a blinding factor, which is a type of digital signature. Because they allow a person to sign a communication without understanding what it contains, blind signatures are commonly employed in privacy-related applications. A ring signature is a digital signature used to sign a message's content by a group member. Identifying the actual signing member of a group is computationally impossible. The ring signature used in the Monero platform combines confidential transactions with ring signature and produces ring confidential transactions. A composite signature is made up of several separate signatures that are not in any particular order. Individual signatures might be difficult to compute from a composite signature. Composite signatures can be used to make Bitcoin-like currency more anonymous. Mixing services received from several clients can also be used for anonymization. It is impossible to track the activities of users using the mixing service [26].
## 3 Results and Discussion
### Proteolytic Degradation Analyzed by SDS-PAGE
1-(3, 3-dimethylbicyclo [2.2.1] hept-2-yl)-ethanation and ethyl hexanoate were the specific volatile compounds produced in _Shewanella purfaciens_ inoculated group, which might be the spoilage markers of this species. An increase of antioxidant BHT was also observed in _Shewanella purfaciens_ inoculated group. This compound was also found in spoiled salmon inoculated with Photobacterium phosphoreum [42]. [PERSON] et al. [24] found that sterile Sebastes melanops inoculated with _Pseudomonas fluorescens_ or _Shewanella purfaciens_ produced several sulfur-containing compounds (methyl mercaptan and dimethyl disulfide) and trimethylamine which were not detected in this study. This is likely due to the difference in the type of fish fillets and different experimental procedures. 1-octen-3-ol and (z)-2-penten-1-o increased significantly in _Pseudomonas mandelii_ inoculated group, and this was different from other bacteria inoculated groups. This result implied that the spoilage characteristics of _Pseudomonas mandelii_ might relate to unsaturated alcohols, which were considered to originate from oxidation of unsaturated fatty acids [43; 44]. Similarly, previous studies used 1-octen-3-ol and (z)-2-penten-1-o as the potential markers for spoilage of other aquatic products [45; 46]. Figure 4: _Cont._  
Figure 4: Total ion current diagram of volatile compounds and heat-map in sturgeon fillets inoculated with different bacteria stored aerobically on ice. Control (**A**); _Pseudomonas fluorescens_ (**B**); _Pseudomonas mandeli_ (**C**); _Shevanella putrefaciens_ (**D**); heatmap (**E**). The level 3 pathways annotations were described on the left and colored according to level 2 categories. Acids, alcohols, aldehydes, esters, hydrocarbons, ketones, and other families were colored in violet, red, pink, green, blue, pistachio green, and yellow respectively. The hierarchical clustering tree was on left based on samples.
## 3 System Architecture
### RoI Detection  
RoI algorithms are being increasingly used to detect objects because these algorithms provide high accuracy in problem-solving. Almost all RoI algorithms use two approaches: object-based and feature-based [26]. The feature-based approach collects all possible pixels based on the similarity of optical features. Then, these pixels are analyzed to make RoI algorithms. One disadvantage of a feature-based approach is that it is insufficient for identifying the entire target because all pixels do not have a robust feature that is displayed in optical pixels. In contrast, the object-based method can detect RoIs better than the pixel-to-pixel feature-based method because the object-based method uses information about the structures and shapes for detection. The object-based method includes many typical approaches, such as matched filter and template matching [27]. However, the object-based method has certain disadvantages, such as complex calculations and unreliable and low-quality images. In this research, because of using multi-LEDs to transmit data, we need some algorithms to detect and receive data automatically at light sources. RoI emerged as the brightest candidate for it. In this paper, we used the RoI methods to detect the LED objects in each image, which were captured by a camera. It reveals the position of transmitters. Then, the signal from the transmitters can be decoded by receivers.
## 2 Materials and Methods
### Single-Particle Reactor  
A laboratory-scale SPR (Figure 1a,b) with internal dimensions of 200 mm \(\times\) 130 mm \(\times\) 130 mm was employed to combust the biomass particles [14; 15; 16; 34]. The temperature of the electrically heated reactor was regulated by proportional-integral-derivative (PID) control using a thermocouple. Dry air carrier gas was supplied to the reactor from the bottom through a pre-heated stainless steel tube, a layer of steel-wood and a ceramic honeycomb structure to ensure a homogenous, laminar flow around the biomass particle. The biomass particles were placed in a sample holder made of platinum wires, which was hung in the centre of the SPR above the honeycomb carrier gas inlet using a stainless steel rod. The rod was connected to a micrometre translation stage used to adjust the distance between the particle and the laser beam, i.e., the height-above-particle (HAP). Platinum was used to avoid chemical reactions between the solid fuel (ash and melt) and sample holder material during conversion. A pneumatic system was employed to alternate the reactor positions between sample loading and sample conversion, the former being used to insert the particle into the SPR. Fuel ignition occurred within a few seconds after switching to the sample conversion position.  
The SPR had small openings in the front and back wall, with diameters of 5 and 10 mm, respectively, that served as optical access ports through which the laser beams were aligned. The access ports (not equipped with glass windows in this study) were purged with nitrogen (N\({}_{2}\)) using a flow rate of 0.2-0.3 L/min to avoid background signals from ambient H\({}_{2}\)O and to prevent combustion gases from exiting the SPR though the ports. The optical components for aligning the laser beams through the reactor and for detection of the transmission were installed on breadboards mounted on the outer walls of the SPR. The combustion experiments were performed at an SPR set temperature of 1123 K and using a carrier flow rate of 4 L/min. In all experiments, only the drying/devolatilization phase (flame, see Figure 1c) and the char conversion phase (glowing particle, see Figure 1d) were recorded. The time point corresponding to the end of devolatilization, which is equivalent to the start of the char conversion, was distinguished visually (flame extinguished) and via the results of the optical measurements (atomic K significantly decreased; H\({}_{2}\)O below detection limit). The end of the char combustion phase was also visually confirmed.
## 3 Applications
### Three-Dimensional Printing Applications in Cultural Heritage Field
The replica was used for research and educational purposes, and to study the original statue's condition, which was fragile and needed conservation. The National Museum of Emerging Science and Innovation in Japan used 3D printing technology to create a replica of a 12 th-century Buddha statue. This statue, which is considered a valuable cultural artifact, is one of the museum's most prized possessions. By using digital scanning techniques, the museum was able to accurately capture the intricate details and exact measurements of the original statue, including its textures, shapes, and patterns. The resulting 3D-printed replica offers visitors a unique opportunity to view the statue up close and appreciate its beauty and cultural significance. Moreover, the replica serves as a valuable tool for conservators and researchers, allowing them to study the original statue without risking damage. The museum's use of 3D printing technology demonstrates how this innovative technique can be used in the preservation and sharing of cultural heritage with wider audiences [102].