esa-sceva/satcom-chunk-collection huggingface dataset:
## 3 Construction
### Security
#### 3.2.2. Dishonest User Game (Non-Replicability of Ciphertext)  
The dishonest user game of this scheme is defined as follows: A user attempts to confuse the auditor by forging the authority's signature and republishing a ciphertext. The game is played by a challenger and an adversary.  
\(-Setup\): Challenger \(\mathcal{B}\) starts the \(Setup(1^{q},U)\) algorithm and sends the public parameters \(PK\) and \(sk_{Do}\) to the attacker \(\mathcal{A}\).  
\(Ciphertext\)\(Generation\): Challenger \(\mathcal{B}\) generates the ciphertext \(CT_{A,T}\) through the \(Encrypt\) algorithm and sends it to \(\mathcal{A}\); \(\mathcal{A}\) generates a new ciphertext \(CT^{{}^{\prime}}_{A,T^{{}^{\prime}}}\) according to the initial ciphertext \(CT_{A,T}\).  
\(Output\): If \(Decrypt(Sk_{Du},CT_{A,T})=Decrypt(Sk_{Du},CT^{{}^{\prime}}_{A,T^{{}^{\prime}}})\) and \(C^{{}^{\prime}}_{0}=M\cdot e(g^{\alpha\beta},g^{st^{{}^{\prime}}})\) then we say that the attacker successfully copies the ciphertext.  
The adversary's advantage in the dishonest user game is defined as  
\[Adv=\mid Pr[\mathcal{A}\;success]\mid\]  
**Definition 8**.: _If the probability of a polynomial-time adversary winning the game described above is negligible, then we consider the ciphertext of our scheme to be secure and irreproducible._  
In order to satisfy the requirement of data confirmation, the conventional CP-ABE scheme is insufficient. To ensure auditing capabilities in our CP-ABE scheme, we have developed a method that involves incorporating the data owner's unique identifier (such as an address or ID number) into the ciphertext using Paillier encryption. The process of our scheme is illustrated in Figure 3.  
Figure 3. Process.
# Improved Application of Hyperspectral Analysis to Rock Art Panels from El Castillo Cave (Spain)
## 2 Materials and Methods
### Pigment Analysis
#### 2.5.4 Spectral Analysis  
The sampling was carried out using Analytical Spectral Devices' full resolution spectrometer. This spectrometer can obtain data 350-2500 nm, but it is important to note that the hyperspectral imaging system takes advantage only of data between 400 and 1000 nm. The spectral signatures used to train the system were obtained from existing panels in the cave to train the subsequent process of the mapping methods [4]. Areas without calcitic concretion and biodeterioration were sampled in different areas with ochre pigment, black pigment, and rocky support.
# Genetic Engineering Approaches for the Microbial Production of Vanillin
###### Abstract  
Vanilla flavour is widely used in various industries and is the most broadly used flavouring agent in the food industry. The demand for this flavour is, therefore, extremely high, yet vanilla bean extracts can only meet about 1% of the overall demand. Vanillin, the main constituent of vanilla flavour, can easily be obtained through chemical synthesis. Nonetheless, consumer demands for natural products and environmentally friendly industrial processes drive the development of biotechnological approaches for its production. Some microorganisms can naturally produce vanillin when fed with various substrates, including eugenol, isoeigenenol, and ferulic acid. The characterisation of the genes and enzymes involved in these bioconversion pathways, as well as progress in the understanding of vanillin biosynthesis in _Vanilla_ orchids, allowed the development of genetic engineering and synthetic biology approaches to increase vanillin production in naturally vanillin-producing microorganisms, or to implement novel vanillin biosynthetic pathways in microbial chassis. This review summarises and discusses these genetic engineering and synthetic biology approaches for the microbial production of vanillin.  
vanillin; bioconversion; metabolic engineering; pathway design; synthetic biology; microbial production; accessible raw material +
Footnote †: journal: biomolecules
# Performance Analysis of the Korean Positioning System Using Observation Simulation
###### Abstract
The QZSS has a plan to provide a highly precise positioning service for users in Japan with a high elevation angle to improve the signal reception, and its service area will also cover the East Asia and Oceania region [15]. In the process of preparing for the development of a new GNSS system, its performance can be predicted through various simulations. [PERSON] et al. [16] presented simulation results for the performance of GPS augmentation using QZSS in specific areas. [PERSON] et al. [17] investigated the availability of a low Earth orbit (LEO) constellation transmitting navigation signals for a positioning service. From the simulation results, they showed that the LEO constellation can contribute to improving the performance of GNSS precise point positioning (PPP). Multi-constellation positioning with an increased number of navigation satellites can significantly improve the accuracy and precision of positioning. [PERSON] et al. [18] investigated that the LEO constellation can significantly enhance the performance of current multi-GNSS real-time PPP using simulated data. Their results also demonstrated that the LEO-enhanced GNSS can be beneficial for precise positioning. The accuracy of GNSS PPP depends on the quality of GNSS orbits and clock products. Some studies investigated improving the orbit quality of new GNSS satellites, such as Galileo and BDS [19; 20]. Recently, the Korean government has proposed to build a new RNSS system [9], which is called the Korean Positioning System (KPS). It is planned for full operational capability in 2039. The initial KPS constellations are composed of seven satellites, which include three GEO and four IGSO satellites. KPS will provide independent navigation services in its service area. However, it can be compatible with GPS as a regional augmentation system. This is also why the GPS constellation will be included in this study. In this study, we briefly introduce the KPS system with its configuration. As there are no KPS observations at ground stations, we simulate all observations. For its performance evaluation, we employ 24 GPS as designed initially and 7 KPS satellites planned for the PNT services in the Asia-Oceania region. Preliminary results related to the KPS performance are analyzed with simulated observations, which include the number of visible satellites for availability, precise orbit determination (POD), signal-in-space ranging errors (SISRE), standard point positioning (SPP), and kinematic PPP (KPPP). This study also includes an analysis of the expected accuracies that is carried out when using this system with GPS.
# Diamonds for Life: Developments in Sensors for Biomolecules
## 2 Chemical Vapour Deposited Diamond Thin Films
### Plasma Treatment of Diamond Thin Films  
The surface of a diamond thin film typically bears hydrogen atoms (H-diamond). It is possible, nevertheless, to produce diamond films with other terminal groups, influencing, in this way, properties such as electron affinity, surface conductivity and wettability and ultimately changing its ability to adsorb and attach molecules, cells, and bacteria [15]. Oxygen and nitrogen are two of the most common terminal groups of diamond surfaces. This termination can be achieved by exposing the diamond to selected gas atmospheres under conditions that allow them to react with the diamond surface.  
The replacement of H atoms with O ones can be achieved by exposure to a plasma of oxygen [16], or to atomic oxygen generated from a radiofrequency (RF) plasma [17], or by thermal oxidation in oxygen atmosphere [18; 19]. Unlike the original H-diamond, the surface of diamond, being rich in oxygen, is hydrophilic, and has a positive electron affinity (PEA). Its electrochemical properties (that is, electron transfer kinetics and potential window) are different from those of the surface of H-diamond.  
While the existence of oxygen terminal atoms guarantees a hydrophilic surface, the presence of nitrogen ones brings the additional advantage of allowing the covalent binding of biomolecules such as DNA and peptides [20; 21]. In a similar fashion to the oxidation process, the inclusion of nitrogen atoms onto the diamond surface can be achieved with an RF plasma treatment in an atmosphere of He/NH\({}_{3}\)[22] or in N\({}_{2}\)[23]. The latter process can generate multiple bonding configurations, such as C\(\equiv\)N, C=N, and C-NH\({}_{2}\).  
Figure 2: Electron microscopy image of: (_left_) polycrystalline boron-doped-diamond film; (_right_) the same film after a secondary deposition with non-doped diamond, generating nano-sized crystalline grains (magnification was increased to better show the very small grains). Reprinted with permission from [PERSON] et al. [13]. Copyright 2004 Elsevier BV.
# Research Progress and Applications of 2D Antimonene
## 2 Theoretical Research and Experimental Methods
### Epitaxial Growth
#### 2.4.1 Preparation of Multilayer Antimonene
In 2018, [PERSON] et al. [10] grew a layered monocrystal antimonene film with a thickness of 17 nm and a size of 16.2 nm on the surface of MoS\({}_{2}\)/sapphire. Two layers of MoS\({}_{2}\) were generated on the sapphire surface, and then the substrate was moved to the growth chamber, where the growth temperature was 200 \({}^{\circ}\)C for 60 s, and continuous antimonene films were synthesized, as shown in Figure 8. AFM and HRTEM were used to observe the appearance of antimony films. The adhesion of antimony at 200 \({}^{\circ}\)C is higher than that at room temperature. The monocrystal-oriented (012) antimony films were detected by XRD (X-ray diffraction). At the same time, multilayer antimony as contact metal for other 2D materials was studied. By using standard lithography, metal deposition and chemical etching, gold-antimony electrodes with different degrees of separation were prepared from antimony on MoS\({}_{2}\)/Sapphire samples. TLM (transmission line) method was used to determine that the specific contact resistance of Au/antimony electrode was significantly reduced. Better performance can be obtained by using antimony as a contact metal for 2D devices. In 2019, [PERSON] et al. [51] prepared antimonene with a thickness of 4-9 nm and a size of 1-3 \(\upmu\)m on graphene/gel substrate. The antimony molecule used was Sb\({}_{4}\), and the weak interaction between antimonene and graphene was proved. LEED (low-energy electron diffraction) pattern was used to show that the growing layer had the crystal structure of \(\beta\)-antimonene, and the lattice constant was 4.28 \(\pm\) 0.02 A. AFM observed 2D islands and their appearance on the surface and analyzed the effect of deposition rate. LEEM studied the growth dynamics of antimonene, and the image showed that as the islands approached each other, the island binding decreased and the lateral growth rate decreased. It is shown that there is a large Sb\({}_{4}\) diffusion length (LD) on graphene, which promotes competition between growing islands. In addition to the preparation of \(\beta\)-phase antimonene, \(\alpha\)-phase antimonene has also been experimentally prepared. [PERSON] et al. [52] grew 2 ML \(\alpha\)-phase antimonene on an \(\alpha\)-Bi topological insulator. Under the condition of ultra-high pressure, 2 ML Bi and Sb were sequentially deposited on molybdenum disulfide substrate to prepare antimonene. The substrate temperature was 295 K. The prepared antimonene was measured by STM and its period was calculated to be 7.3 nm \(\pm\) 0.6 nm. The nontrivial topological structure of \(\alpha\)-phase antimonene, belonging to the quantum spin Hall class, was studied. Figure 8: Growth of antimonene on MoS\({}_{2}\)/sapphire. Reprinted with permission from Ref. [10]. Copyright 2018, American Chemical Society.
## 5 Discussion  
Two separate response variables representing glacier changes were quantified using Landsat imagery. First, spatial location of glacier terminus was traced over time as a  
Figure 11: (**Left**) Generalized Additive Model for Gorner Terminus 2000 to 2021 (pixel resolution is 30 meters). (**Right**) Generalized Additive Model for Gorner Area 2000 to 2021. Measured (circles) and trend (yellow).  
proxy to glacier change. Second, glacier area was measured over time to quantify glacier variations. Response variables modeled using multiple regression and GAM. GAM could better model the nonlinear glacier variations. Global CO\({}_{2}\) level, temperature (both local and global), and precipitation were identified as significant factors to model glacier variations. The results of this study agree with the previous research emphasizing the importance of local climate factors [17; 18]. These finding are in line with what is currently known about the physics of glacier motion. The interaction between the climate factors could impact the glacier changes and potentially may help to better understand the complex dynamics of global climate subtleties.  
As a proxy, spatiotemporal variation of glacier's terminal point, offers valuable insights about glacier change. However, terminus variations do not provide sensible quantification of changes in the glacier's size. Hence, quantification of glacier surface area by the proposed approach in this paper, provides essential insights about glacier's size by measuring its surface area, in comparison with the previous works measuring terminus variations such as [19; 20; 21; 22; 23; 24; 25; 26].  
Moreover, due to the non-linear trends in the glacier variations, GAM could substantially improve the modeling of glacier's variation using climate factors. The relation between glacier change and climate factors cannot be deciphered by linear models such as multiple regression. Hence, by the additional flexibility of a nonparametric approach, GAM could discover the nonlinear trends in the glacier variations that could not be inferred using linear models in the previous works [7; 8; 9].  
Although the proposed semi-automated image segmentation pipeline is a promising approach, it still requires user's input to customize it for different glaciers as distribution of pixel intensities changes in different scenes and over different spectral bands. This can prevent broad application to a large number of glaciers. Nevertheless, this study provides some proof of concept and valuable insights about complexity of this challenging problem. The segmentation can possibly be improved by the inclusion of processed bands using fusion of multiple Landsat spectral bands. Moreover, the computational cost of the entire process demands for an efficient data cleaning process in the preprocessing phase. Considering the scale and coverage of Landsat imagery along with the large number of glaciers around the globe, the clean-up process is not a trivial task.
# Predictive Power Management for Wind Powered Wireless Sensor Node
## 5 Experimental Results
### MPTT Testing  
The experimental tests are conducted in accordance with the wind condition of the deployment ground illustrated in Figure 5 where the average wind speed is given as 4.5 m/s, and we record the variation of WTG's output power under different wind speed when its subsequent load value changes,  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline C\({}_{\text{in}}\) & 220 uF \\ NMOS1/2 & Si1563 EDH \\ \(L1\) & 220 uH \\ Supercapacitor & 2 F,5.5 V \\ \(D1/2\) & IN5819 \\ \(L2\) & 15 uH \\ C\({}_{\text{out}}\) & 47 uF \\ PWM generator & LTC6906 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Catalog of hardware components.  
Figure 4: Hardware prototype of the Wind-powered sensor node.  
as shown below in Figure 6. Apparently, when \(R_{Optimal}\) = 400 \(\Omega\) WTG generates the maximal electrical power. Therefore, if algorithm DC-TPC works out the parameters \(W_{Bost}\) and \(W_{Buck\text{-}Bost}\), thus the optimal working point could be achieved.  
Figure 7 shows the variation of EH-WSN's overall power loss \(P_{D\_system}\) with supercapacitor voltage \(V_{SC}\) and load current \(I_{O2}\) according to Equation (15). [Note: for the convenience of analysis and comparison, the prediction mechanism in this step is prohibited, the TPC module sets to be a given quantity, and the values of \(C_{1}\),..., \(C_{8}\), are (15, 0.25, 0.004, 0.09, 11, 0.12, 0.004, 0.075)]. As can be seen here, the power dissipation is minimized when \(V_{SC}\) changes near \(V_{DD}\) = 2.4 V.  
Figure 5: Wind speed measurement record (2018.06, Nanjing, Jiangsu, China).  
Figure 6: The variation of Wind Turbine Generator (WTG) output power under different wind speed V.S. Its subsequent workload.  
Next, there are three exams to be conducted, which is to differentiate the performance of the MPTT scheme in powering the load. The followed electrical load is at first powered with an EH system but without the MPTT scheme, then with EH system carried on MPTT (\(I_{O2}\) = 20 mA), and finally with EH system running MPTT (\(I_{O2}\) 120 mA). The duration for each period is 180 s, and the supercapacitor voltage variation under these conditions is compared in Figure 8.  
From the above figure we can find that the supercapacitor voltage \(V_{SC}\) keeps decreasing during the period when algorithm DC-TPC is not running. On the contrary, \(V_{SC}\) could keep nearly balance in the mode with MPTT but \(I_{O2}\) = 120 mA, this demonstrates that the harvested wind energy could make the node self-sustainable in a continuous input situation. Finally, within the MPTT (\(I_{O2}\) = 20 mA) mode our system yields the most superior performance, which shows a powerful survivability to make \(V_{SC}\) rise from 2.17 to 2.37 V. Therefore, the MPTT mechanism is obviously applicable for the conditions of harvesting conventional wind energy.
## 2 Urban Pipeline Gas Leak Sensor Placement Method
### Risk Level Clustering Analysis near Inspection Wells  
Hierarchical clustering is a method of cluster analysis that constructs a tree-like structure to illustrate the clustering process of data points. There are two main approaches to hierarchical clustering: bottom-up (agglomerative) and top-down (divisive).  
A suitable distance metric is selected to calculate the distance between two data points. Commonly used distance metrics include Euclidean distance, Manhattan distance, etc. In this case, Euclidean distance is chosen:  
\[d(x_{i},x_{j})=\sqrt{\sum_{k=1}^{n}{(x_{ik}-x_{jk})^{2}}} \tag{1}\]  
where \(x_{ij}\) and \(x_{j}\) are data points, and \(n\) is the number of dimensions.  
Then, initialize each data point as an individual cluster:  
\[C_{i}=\{x_{i}\},\ i=1,2,\ldots,N \tag{2}\]  
where \(N\) is the total number of data points.  
Calculate the distance between all clusters and merge the two clusters with the smallest distance. The average linkage method is commonly used:  
\[d(C_{i},C_{j})=\frac{1}{|C_{i}|,|C_{i}|}\sum_{x\in C_{i}}\sum_{y\in C_{j}}d(x,y) \tag{3}\]  
where \(|C_{i}|\) and \(|C_{j}|\) represent the number of data points in clusters \(C_{i}\) and \(C_{j}\), respectively.  
The data preprocessing step ensures data integrity by handling potential missing values or errors. Next, hierarchical clustering was chosen as the clustering method, which gradually merges nodes into larger groups by calculating the similarity between them. In this process, Hamming distance is used as the distance metric, suitable for handling the binary nature of the data. The linkage criterion used is average linkage to ensure uniformity within the clusters.  
During the clustering execution phase, hierarchical clustering is applied, and the merging process between nodes is visualized using a dendrogram. After determining the appropriate number of clusters, a cut point is selected on the dendrogram, dividing the nodes into four groups. Each group represents a set of nodes with a similar number of critical facilities and safety hazards.  
The final classification allows for the identification of nodes with different risk levels, providing a scientific basis for optimizing sensor placement. This classification method, based on actual facilities and safety characteristics, improves the targeting and efficiency of the monitoring system, ensuring the rational allocation and use of resources in the gas pipeline network, thereby enhancing the overall safety monitoring capability of the system.
# Audio-Visual Action Recognition Using Transformer Fusion Network
## 4 Experimental Results
### Results
\begin{table}
\begin{tabular}{c c c c} \hline
**Case** & **Swin-T** & **Swin-S** & **Swin-B** & **Swin-L** \\ \hline (1) & **87.50\%** & **88.25\%** & **89.34\%** & **89.28\%** \\ (2) & 82.24\% & 84.43\% & 85.38\% & 86.00\% \\ (3) & 86.48\% & 87.80\% & 88.59\% & 89.05\% \\ (4) & 85.25\% & 86.20\% & 88.18\% & 87.36\% \\ \hline \end{tabular}
\end{table} 
Table 2: The ablation study for Swin transformer on the Kinetics-sound dataset: (1) all elements, including a single frame (spatial), \(T\) frames (temporal), and audio; (2) single frame and \(T\) frames without audio; (3) single frame and its corresponding audio; and (4) \(T\) frames and its corresponding audio. The bold numbers represent the best results for each Swin type. \begin{table}
\begin{tabular}{l c} \hline
**Case** & **Accuracy** \\ \hline EF-NN [15] & 80.06\% \\ LF-NN [15] & 61.00\% \\ EF-SVM [15] & 66.10\% \\ LF-SVM [15] & 82.50\% \\ Proposed methods (Swin-B, case (1)) & **93.00\%** \\ \hline \end{tabular}
\end{table} 
Table 3: Comparison of multi-modal results on UCF-sound dataset. EF denotes early fusion, and LF denotes late fusion. NN denotes neural network. The bold numbers represent the best results. As shown in Table 4, our proposed method (1) with Swin-B achieves the highest accuracy of 89.34% on the Kinetics-sound dataset. This performance surpasses those of all other listed methods, including the Multi-level Attention Fusion Network (MAFnet) [35], AVSlowFast models [17], and even the MBT [24]. Notably, our method's accuracy is approximately 4% higher than the nearest competing methods, marking a significant improvement.
# High-Speed GaN-Based Superluminescent Diode for 4.57 Gbps Visible Light Communication
## 3 Results
### Device Characterizations  
Figure 3 presents the optical power vs. current and voltage vs. current curves of the fabricated SLD tested at room temperature. The device has a turn-on voltage of \(\sim\)3.1 V, which is similar to a typical GaN-based LED. With increasing injection current exceeding 80 mA, a super-linear L-I curve is observed, suggesting that the device entered the amplified spontaneous emission regime, which is typical for an SLD. The optical power increases to \(\sim\)4.46 mW under the injection current of 290 mA.  
In Figure 4a, we plot the emission spectra of the SLD under different injection currents. A blue shift of the emission peak is observed with increasing injection current. The emission peak changes from \(\sim\)447 nm at 40 mA to \(\sim\)441 nm at 200 mA. This is mainly attributable to the band filling effect [11]. Figure 4b shows the change in the emission peak position and the full-width at half maximum (FWHM) against the injection current. A fast decrease in peak FWHM, from \(\sim\)19 nm at 40 mA to \(\sim\)10 nm at 80 mA, can be observed, suggesting the onset of the superluminescence effect. This matches the L-I characteristics shown in Figure 3 well. The SLD has a relatively broad spectrum, with FWHM of \(\sim\)12 nm at a high injection current of 300 mA.