esa-sceva/satcom-chunk-collection huggingface dataset:
# Temporal Changes in Land Use, Vegetation, and Productivity in Southwest China
## 2 Data and Methods
### Data  
The normalized difference vegetation index (NDVI) data came from the study derived from the MOD13A2 data product, with a spatial resolution of 1 km and a temporal resolution of 16d ([[https://ladsweb.modaps.eosdis.nasa.gov/](https://ladsweb.modaps.eosdis.nasa.gov/)]([https://ladsweb.modaps.eosdis.nasa.gov/](https://ladsweb.modaps.eosdis.nasa.gov/)) (accessed on 6 August 2021)). These data were preprocessed on the Google Earth engine platform ([[https://earthengine.google.com](https://earthengine.google.com)]([https://earthengine.google.com](https://earthengine.google.com)) (accessed on 6 August 2021)), and the NDVI data from May to September 2000-2019 were downloaded. The gross primary productivity (GPP) datasets were obtained from the MOD17A2 HV6 data product with a spatial resolution of 500 m and a temporal resolution of 8d ([[https://lpdaac.usgs.gov/products/mod17a2](https://lpdaac.usgs.gov/products/mod17a2) hv006/]([https://lpdaac.usgs.gov/products/mod17a2](https://lpdaac.usgs.gov/products/mod17a2) hv006/) (accessed on 28 August 2021)), and we downloaded the contemporaneous datasets from the Google Earth engine platform ([[https://earthengine.google.com](https://earthengine.google.com)]([https://earthengine.google.com](https://earthengine.google.com)) (accessed on 28 August 2021)). The LULC data came from the first Landsat-derived annual China Land Cover Dataset  
Figure 1: Study area location in China and land cover types in 2019.  
(CLCD) from 1990 to 2019, with a spatial resolution of 30 m and an overall accuracy rate of 79.31%, better than MCD12Q1, ESACCI_LC, FROM_GLC, and GlobaLand30. The LULC types in these data were divided into nine categories: cropland, forest, shrub, grassland, water, snow/ice, barren, impervious, and wetland. The CLCD dataset introduced in this article is freely available at [[http://doi.org/10.5281/zenodo.4417810](http://doi.org/10.5281/zenodo.4417810)]([http://doi.org/10.5281/zenodo.4417810](http://doi.org/10.5281/zenodo.4417810)) (accessed on 10 August 2021) [49].
# A Novel Love Wave Mode Sensor Waveguide Layer with Microphononic Crystals
###### Abstract  
Surface acoustic wave (SAW) sensors have been applied in various areas with many advantages, such as their small size, high sensitivity and wireless and passive form. Love wave mode sensors, an important kind of SAW sensor, are mostly used in biology and chemistry monitoring, as they can be used in a liquid environment. Common Love wave mode sensors consist of a delay line with waveguide and sensitive layers. To extend the application of Love wave mode sensors, this article reports a novel Love wave mode sensor consisting of a waveguide layer with microphononic crystals (PnCs). To analyze the properties of the new structure, the band structure was calculated, and transmission was obtained by introducing delay line structures and quasi-three-dimensional models. Furthermore, devices with a traditional structure and novel structure were fabricated. The results show that, by introducing the designed microstructure of phononic crystals in the waveguide layer, the attenuation was barely increased, and the frequency was shifted by a small amount. In the liquid environmental experiments, the novel structure with micro PnCs shows even better character than the traditional one. Moreover, the introduced microstructure can be extended to microreaction tanks for microcontrol. Therefore, this novel Love wave mode sensor is a promising application for combining acoustic sensors and microfluidics.  
surface acoustic wave; sensor; love wave mode; delay line; phononic crystals +
Footnote †: journal: Applied Sciences  
1
# Modeling Population Dynamics and Assessing Ecological Impacts of Lampreys via Sex Ratio Regulation
## 1 Introduction  
### Background  
Sea lampreys, resembling eels and feeding on blood, are widely distributed globally, as depicted in Figure 1. This species possesses a distinct mechanism for determining sex, governed by the larvae's growth speed [1]. The growth rate of marine lampreys during the larval stage varies by the availability of food, which influences the sex ratio in adulthood. Adaptive sex ratio variation in nature is influenced by multiple factors and exerts significant effects at various biological scales, ranging from population-level dynamics to broader ecosystem processes. Consequently, examining how lampreys' gender proportions correlate with their habitat's resource availability is crucial for maintaining ecosystem stability over time.  
We aim to create a comprehensive model to explore the interaction between the adaptive differences in the sex ratio of sea lampreys and ecological systems. The objective of this approach is to enhance the overall comprehension of sea lampreys' biological characteristics and their ecological functions. Such a model not only helps to elucidate the underlying mechanisms of sea lamprey population dynamics but also offers valuable scientific insights for ecological conservation and management.
# A Review of SATis5: Perspectives on Commercial and Defense 5G SATCOM Integration
## 4 Overview of Recent and Existing Commercial SATis5 Testbeds and Projects
### eMBB EU-Commissioned SatT5G Project
The testbed provides a CDN that efficiently utilizes the integrated 5G over parallel satellite and terrestrial delivery paths providing enhanced end-to-end (E2E) quality of experience (QoE) for multiple users consuming 4K-layered video. The testbed incorporates mABR adaptation, link selection, and enhanced video streams into a video-segment scheduling network function (VSNF) that is located at the MEC server. The testbed provides a network infrastructure in rural areas where the capacity of terrestrial backhaul is limited. Additionally, the satellite backhaul link offloads the terrestrial backhaul traffic. Figure 9 describes a SaT5G testbed framework for Use Case 2[14]. A 5G hybrid backhauling using a multilinking testbed was built to demonstrate Use Case 3. The testbed focuses on the demonstration of the Multipath version of the Quick UDP Internet Connections (QUIC) protocol (MPQUIC). The software was customized to support hybrid satellite and terrestrial backhauling networks. The 5 GIC/QUIC along with MPQUIC were set up in the testbed and test results were obtained and compared with TCP data obtained from the emulated satellite link. Figure 10 depicts a SaT5G testbed  
Figure 8: SaT5G Architecture for Use Case 1: Multicast/caching MEC testbed. Figure 9: SaT5G Architecture for Use Case 2: Multiclient video streaming with multilinking testbed [14]. framework for Use Case 3. Table 5 provides a summary of key SaT5G testbed results related to the above three use cases.
# Plastic Properties of Prestressed High-Strength Steel Reinforced Concrete Continuous Beams
###### Abstract  
In this paper, the plastic properties of prestressed high-strength steel reinforced concrete (PHSSRC) beams are studied, by performing static load tests on eight built-in Q460 and Q690 prestressed high-strength steel reinforced concrete continuous beams and one built-in Q355 prestressed steel reinforced concrete (PSRC) continuous beam. The design parameters of the specimens were the steel strength grade, the steel ratio, the comprehensive reinforcement ratio, and the stirrup ratio. The failure mode, load-deflection curve, internal force redistribution ability, curvature ductility, plastic hinge performance, and moment modification coefficient of continuous beams under the influence of various parameters were analyzed to measure the plastic performance of the continuous beams. These results show that after the plastic hinge is formed in the middle support and mid-span of the prestressed high-strength steel reinforced concrete continuous beam, the test beam eventually becomes a rotating mechanism and is destroyed with increasing load. The built-in high-strength steel can significantly improve the bearing capacity of the specimen, and the maximum increase in the bearing capacity is 37.3%. The specimen still has a high bearing capacity after reaching the ultimate bearing capacity. With a decrease in the steel ratio, the degree of internal force redistribution is deepened, the curvature ductility is improved, and the plastic performance is enhanced. Increasing the comprehensive reinforcement ratio and the stirrup ratio can improve the plastic performance of the specimen. The calculation formula of the equivalent plastic hinge zone length is proposed. The calculation formula of the moment modification coefficient, with the relative plastic rotation angle and relative compression zone height as independent variables, is established. When the relative plastic rotation angle is not greater than 0.829 \(\times\) 10\({}^{-5}\), the moment modification coefficient increases with increasing plastic rotation angle and is not greater than 0.37. In the range of 0.3\(\sim\)0.4, the moment modification coefficient decreases with increasing height of the relative compression zone.  
high-strength steel; prestressed steel reinforced concrete; continuous composite beams; plastic properties; moment modulation +
Footnote †: journal: Applied Sciences
## 4 Results and Discussion
### Robustness Evaluation  
#### 4.2.1 Geometric Attacks  
Translation, rotation, and scaling are examples of common geometric attacks. Watermark information is extracted from each sub-block of different data after various types and degrees of geometric attacks are performed on the experimental data. Table 2 lists the watermark images with the highest recognition degree extracted from different experimental data as well as different attack modes. It is evident that a watermark image with easily discernible copyright content can be extracted under all three geometric attack modes. Under both rotation and translation attacks, the extracted watermark images have NC values of 1, while under scaling attacks, the lowest NC value is 0.9821, and the highest is 1. Because of this, the proposed watermarking scheme can withstand attacks that use geometry. Because the CDTN architecture is both unique and invariant under rotation and translation attacks, the extracted spatial information remains unchanged after the DFT is calculated and remains consistent over time. In contrast, the experimental data produce a large change under the scaling attack, which has some effect on the feature points extraction. However, the CDTN possesses the characteristics of scaling invariance and overall invariance of local changes; the phase of DFT possesses scaling invariance; and, under the double insurance, the watermarking scheme also has strong robustness against the scaling attack.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Attack Mode** & **Scale** & \(W^{\prime}\)**/(a)** & \(W^{\prime}\)**/(b)** & \(W^{\prime}\)**/(c)** \\ \hline \multirow{6}{*}{Rotation} & \multirow{2}{*}{\(30^{\circ}\)} & \multirow{2}{*}{\(\begin{array}{c}\text{NC}=1\text{, BER}=0\%\end{array}\)} & \multirow{2}{*}{\(\begin{array}{c}\text{NC}=1\text{, BER}=0\%\end{array}\)} & \multirow{2}{*}{\(\begin{array}{c}\text{NC}=1\text{, BER}=0\%\end{array}\)} \\ \cline{3-3}  & & & & \\ \cline{3-3}  & & &
# Research on an Index System for the Earthquake Disaster Resistance Capability of Highway Tunnels
## 2 Analysis of Seismic Damage Scenes in Highway Tunnels
### Analysis of the Influencing Factors of Earthquake Disasters in Portal Sections of Highway Tunnels
#### 3.3.3 Pavement Cracking  
Pavement cracking refers to the excessive cracks produced by pavement under the action of an earthquake, which affects normal use. Under the influence of seismic forces, asphalt or plain concrete pavement materials cannot resist the load generated by an earthquake alone. In addition, the pavement is a consumption structure, which will cause pavement cracking when the loss is too large and the maintenance is insufficient. During the Wenchuan Earthquake, there were many pavement cracks in the tunnel body section of the Shaohuoping Tunnel and Baiyunding Tunnel, and the pavement cracks were clear and had a certain direction. There are also small distributions in Longxi Tunnel, Longdongzi Tunnel and Jiujiaya Tunnel; the pavement of Ma'anshi Tunnel is cracked horizontally, and there are many inclined cracks in the lining near the pavement.  
In the case of investigation, due to the defects of the operation management company in pavement maintenance, the technical condition of the pavement structure is poor. During operation, the pavement shrinks due to vehicle load and pavement temperature and cracks under the action of seismic force. Therefore, the main causes of pavement cracking can be divided into operation management factors.
# High-Precision Combined Tidal Forecasting Model
## 3 Combined Tidal Forecasting Model Based on Harmonic Analysis and ARIMA-SVR
### Model Checking
#### 3.2.2 Analysis of Prediction Results of Astronomical Tide Level  
The astronomical tidal level calculation used 11 main tidal constituents, namely, \(M_{2}S\), \(S_{2}\), \(N_{2}\),\(K_{2}\),\(K_{1}\), \(O_{1}\), \(P_{1}\), \(Q_{1}\), \(M_{4}\), \(MS_{4}\), and \(M_{6}\). Figure 6 compares the astronomical tidal level predicted by the harmonic analysis method with the original (not de-noised) measured tidal level. Figure 7 is an error distribution chart of the tidal levels predicted by the harmonic analysis method alone, and Figure 8 plots the linear regression between the observations and predicted results of the harmonic analysis method. As indicated by the deviation of the best-fit line (red line in Figure 8) from the \(Y=X\) line, the observed and predicted values were highly discrepant. The simple harmonic analysis introduced obvious errors at some points. The \(E_{\mathrm{RMS}}\) of the harmonic analysis method was determined as 0.180571 m. This large error is attributed to the oversimplified analysis method: the simple harmonic method only considers the influence of the tide-generating force and ignores the non-astronomical components of the changing water levels.  
Figure 5: Sequence of the noise signal.  
Figure 6: Comparison of tidal levels predicted by the harmonic analysis method alone and the observed data.
###### Abstract  
The salt concentration of the pore solution can alter the micro-pore and particle structure of soil, thereby affecting its engineering properties. To investigate the compression characteristics of marine soil under different salt concentrations, one-dimensional compression and SEM scanning tests were conducted on marine reconstituted clay from the Yellow Sea with varying NaCl concentrations (0-5%). The effects of NaCl concentration on the compression characteristics and microstructure of marine sedimentary clay were analyzed. The results indicate that: (1) Compressibility increases up to a NaCl concentration of 2.5%, after which it declines. At 2.5% NaCl threshold concentration, the coefficient of compression, compressibility index, and consolidation coefficient reach their peak values, and the response becomes more pronounced with increasing compression pressure. During the secondary compression stage, as pore water is expelled, the impact of NaCl concentration on compressibility diminishes, while the rebound characteristics remain unaffected by NaCl concentration; (2) SEM analysis reveals that at a NaCl threshold concentration of 2.5%, the pore fractal dimension, particle fractal dimension, pore anisotropy, and particle anisotropy reach their maximum values, with the most complex shape and pores and particles aligning in the same direction. When the concentration is less than 2.5%, the soil exhibits narrow pores and rounded particles upon compression. When the concentration exceeds 2.5%, the microstructure changes in the opposite direction, confirming the particle rearrangement mechanism driven by surface contact under moderate salinity. At the threshold concentration of 2.5%, a balance between electrostatic forces and attractive forces enables stable surface-to-surface contacts, maximizing compressibility. The findings of this study provide valuable references for the foundation design of marine geotechnical engineering in specific sea areas, thereby enhancing the safety and reliability of related projects.  
marine soil; pore water salt solution; one-dimensional compression characteristics; microstructure characteristics; particle arrangement +
Footnote †: journal: Applied sciences  
Article
## Instrument Description
### RF Receivers  
The custom designed RF receivers (see Figure 2) are monitored and managed by the instrument controller. Each receiver has two input connectors: one for the antenna signal and one for the calibration signal. The receiver provides the power for the active antenna element pre-amp through a bias tee. A single-pole, double-through switch selects between the antenna and the calibration port. The signal passes through a two-way splitter, one output branch goes to the test connector of the receiver, and the other one is fed into a four-way filter bank to select one of the four frequency bands (L1 = 1575.42 MHz,  
Figure 1: Block diagram of the Software PARIS Interferometric Receiver (SPIR) hardware.  
L2 = 1227.60 MHz, L5 = 1176.45 MHz, LRAD = 1413 MHz). The filtered signal is amplified by two amplifier stages, one of which is digitally adjustable within a range of 31.5 dB. The signal is then down-converted to IF (\(\approx\)19 MHz) using in-phase and quadrature branches, and these components are then low-pass filtered (35 MHz) and further amplified. A DC-offset compensation circuit sets the DC component of the signal (see Section 2.2.1). The total power of the signal is measured by the Power Measurement System (PMS) (see Section 2.2.2). Finally, a fast comparator quantizes the in-phase and quadrature components with one single bit each. Sampling at 80 MHz is effectively achieved at the input of the FPGA using D-type flip-flops.
# Research on Blockchain-Based E-Bidding System
## 2 Preliminaries
### Consortium Blockchain  
Most of the traditional blockchain applications, such as Bitcoin, Ethereum, etc., are based on completely open and transparent permissionless blockchain. The public blockchain is a highly decentralized distributed ledger, which is convenient for any node to read data, send transactions, and freely enter and exit the blockchain network, and the transactions can be effectively confirmed. However, it has high latency, low efficiency, and lacks corresponding supervision mechanisms, which brings potential privacy threats. Therefore, it is not suitable for such activities as bidding.  
The private blockchain is a non-public \"chain\" in which write permissions of each node are subject to internal control, while read permissions are selectively opened to the outside as required. Applicable to the internal data management and audit of specific organizations, only internal authorized users can access the blockchain data. Public tenders require the participation of multiple institutions, so private chains are not qualified for this scenario.  
Consortium blockchain, also known as \"permissioned chain\", is a semi-closed blockchain, which refers to a blockchain that is jointly managed by multiple industry institutions. Only members of the consortium can read, write and send all or part of the data [17]. It fundamentally closes the channels for unauthorized nodes to access data, realizes complete authority control and security guarantee, and significantly reduces the risk of blockchain privacy leakage [18]. Moreover, the transaction operation performance of the consortium blockchain is high, the transaction is cost-free, and the smart contract can be upgraded and extended easily. Since the E-bidding system needs to strictly control the anonymity of participants and the encryption of transaction information according to the requirements [19], the consortium blockchain technology is more suitable for the system.
## 3 Results and Discussion  
### Spectroscopic Studies of Ligand (L1) Cu (II) Complex  
#### 3.1.1 Nuclear Magnetic Resonance Spectroscopy  
1H NMR spectrum (Figure 1a) of the synthesized organic ligand, L1, was observed in deuterated chloroform solvent and showed two singlet peaks at 8.4 ppm and 8.6 ppm, assigned to H-N-C=O cyclic ring. The singlet peak at 5.23 ppm is assigned to the C-H of dichloromethane which was used during the purification of L1. Additionally, the peaks of the aromatic protons of the ligand (L1) were observed in the range 6.67-8.42 ppm, while the doublet peaks appeared at 7.62-8.32 ppm corresponding to various benzene C-H protons. Moreover, the origin of the chemical shift at 8.5 ppm might be associated with the aromatic C-H in position 3 of the indole nucleus. The synthesized organic ligand, L1, exhibits delocalization of electrons through -NH and C=O groups to form tautomeric structures, as shown in Scheme 2. The signal in the range of 0.95-1.2 ppm has been observed for the methyl group of the coordinated diethyldi thiocarbamate ligand (L2). The proton NMR spectra (Figure 1b) of mixed-ligand Cu (II) complex was observed in the deuterated dimethyl sulfoxide solvent with TMS as internal reference. The -CH\({}_{2}\) protons of the diethylditiocarbamate moiety is assigned at the 3.7 ppm (quadruplet) of the Cu (II) complex [26]. The O=C-NH proton has been assigned the strong signal at 3.36 ppm while attachment of third benzopyrrole moiety was observed due to the presence of a singlet peak at 4.34 ppm, hence a decrease in the chemical shift in the metal complex as compared to the organic ligand. The chemical shift values of other aromatic protons were observed in the region of  
Figure 2: Electron delocalization behavior via keto-enol equilibrium in the synthesized organic ligand (L1).  
7.32-8.23 ppm for the metal complex alongside the peak at 8.72 and 11.65 ppm corresponding to the -NH proton of the cyclic benzopyrrole moiety [27].
## 3 Mathematical Modeling of CCPP
### CCPP Modeling
#### 3.1.2 HRSG Modelling  
The HRSG in Figure 3 is a triple-pressure reheat waste-heat boiler. The mathematical model of the HRSG includes several modules, such as the heat exchange calculation of the water wall, evaporating heating surface, and superheater. Each module's energy exchange was calculated using the following equation:  
\[Q_{r}=\alpha A(\frac{T_{in}+T_{out}}{2}-T_{p}), \tag{7}\]  
\[T_{out}=T_{in}-\frac{Q_{r}}{c_{Y}g_{Y}} \tag{8}\]  
\[S_{G}=\frac{1}{T_{2}S+1}Q_{r} \tag{9}\]  
\[S_{G}-S_{F}=C_{B}\frac{dP_{d}}{dt} \tag{10}\]  
\[P_{d}-P_{T}=K_{sh}S_{F}^{2} \tag{11}\]  
where \(Q_{r}\) is heat exchange; \(\alpha\) is convection heat transfer coefficient; \(A\) is effective heat exchange area; \(T_{in}\) is gas turbine exhaust temperature; \(T_{out}\) is exhaust temperature of HRSG; \(T_{P}\) is saturation temperature at saturation pressure of the steam; \(c_{Y}\) is the specific heat capacity of the flue gas; \(g_{Y}\) is the flow rate of flue gas; \(S_{G}\) is the total effective heat absorption of the HRSG-heated surface; \(T_{2}\) is the time constant of the heat transfer process of HRSG; \(P_{d}\) is the boiler drum pressure; \(S_{F}\) is the flow rate of superheated steam; \(C_{B}\) is the heat-storage coefficient of the boiler drum; \(P_{T}\) is main steam pressure; \(K_{sh}\) is the resistance coefficient of superheater pipeline.