esa-sceva/satcom-chunk-collection huggingface dataset:
# On the Design and Implementation of a Blockchain-Based Data Management System for ETO Manufacturing
## 2 Background and Related Works
### Blockchain in Engineering and Manufacturing  
Blockchain is an electronic distributed ledger with the features of decentralization, data immutability, consensus mechanism, and many more [12; 13; 14; 15; 16]. Blockchain technology, as a new model of data sharing, provides a means for parties to build mutual trust without the need for a trusted third party. This mechanism records data changes in a block as a transaction and uploads them to the chain. Since all participants jointly maintain the ledger, any party's changes to the data can only be recognized through consensus; otherwise, the transaction will be rejected. Most importantly, when smart contracts are integrated into the blockchain, the application scenarios of blockchain technology become more and more extensive. Smart contracts are a computer protocol linking multiple parties to complete a dedicated contract. Smart contracts are supported by major blockchain development platforms, such as Ethereum and Hyperledger [17; 18].  
To date, many studies have shown that the application of blockchain in production scenarios has many advantages, and its distributed storage structure greatly ensures the security of data, which are extremely difficult to tamper with [19; 20; 21; 22; 23; 24; 25]. The storage structure ensures the data are immutable and facilitates the traceability of the data. Thus, it helps to achieve transparent tracking of the production process. [PERSON] [26] undertook a detailed review of the application of blockchain technology in engineering and manufacturing in terms of achieving three outcomes: protecting data validity [27; 28; 29; 30; 31; 32], enhancing communication within an organization [33; 34; 35; 36; 37; 38], and improving manufacturing production efficiency [39; 40; 41; 42; 43]. [PERSON] et al. [44] discussed in detail the use of an Ethereum-baseddistributed ledger technology to improve information trustworthiness and access control in cloud-based manufacturing. To solve the data sharing problem of the production supply chain in the Industrial Internet of Things (IIoT), [PERSON] et al. [45] proposed a new blockchain-based supply chain structure, which integrates attribute encryption to make data access more fine-grained. At the same time, it further improves the reliability and traceability of IIoT data. [PERSON] et al. [46] proposed a hybrid blockchain mechanism to provide security for multinational IIoT data with offices in multiple countries. A blockchain-based resource-sharing collaboration framework was designed by [PERSON] et al. [47], which can support ecosystems with established collaborations and hierarchies. While blockchain technology has provided many benefits for smart manufacturing, there are still many problems in applying it to ETO-type manufacturing, especially in ensuring the validity of production chain data when the production process route is uncertain.
# Research on Optimization of Target Positioning Error Based on Unmanned Aerial Vehicle Platform
## 2 Definition of a Coordinate System
### Airframe Coordinate System \((O_{h}-X_{h}Y_{h}Z_{h})\)  
The airframe coordinate system shares an origin with the geographic coordinate type. The \(X\)-axis points directly in front of the carrier aircraft, the \(Y\)-axis points in the direction of the right wing of the UAV, and the \(Z\)-axis is parallel to the vertical axis of the UAV, pointing downward, as shown in Figure 3. When there is no attitude change in the UAV, these coordinates coincide with the spatial, right-angled coordinate system. At a certain point, the coordinates are represented as \((X_{h},Y_{h},Z_{h})\).
# Combining InSAR and GNSS to Track Magma Transport at Bastic Volcano
## 6 Discussion
### Combining InSAR and GNSS for Complementary Spatial and Temporal Information
#### 6.2.2. Advantages of the Subgraph Method for Temporal Inversions  
The Subgraph method is a new method developed to determine the pressurized part of a mesh from GNSS time series. In comparison with the Projected Disk method, which requires four parameters, only three parameters are needed, two for the geometry and one for the overpressure. As for the Projected Disk method, an a priori on the source geometry is needed, which is determined from the inversion of InSAR data covering the eruption. Results are very close to those obtained with the Projected Disk in terms of misfit and volume changes (Figure 11). However, comparing results with an intermediate Sentinel-1 interferogram, we find that the Subgraph method explains this data better than the Projected Disk method (Table 4). It also leads to a more realistic evolution of pressure, area and average opening. In terms of source geometry, the eruptive fissure never opens with the Projected Disk method (Figure 12). However, with the Subgraph method we are able to follow the propagation of magma upward to the surface. These results indicate that the Subgraph method, by avoiding the projection of a planar circle on a curved surface, is a more reliable method than the Projected Disk method.
## 3 Conditions for Complete Optical Absorption by Critical Coupling  
Examining the critical coupling behavior can be useful for obtaining perfect absorption at a desired frequency. Perfect absorption occurs when the overall reflectance of the structure is zero, which can be derived from the Equation (1) as  
\[r_{12} =r_{\text{eff}}(r_{12}r_{21}-t_{12}t_{21})\exp(i2k_{0}\widetilde{n}_{ \text{ITO}}t_{\text{d}}) \tag{2}\]  
To find the conditions satisfying the Equation (2), we define the function \(D(t_{\text{d}},\lambda)\) as follows:  
\[D(t_{\text{d}},\lambda)=(r_{\text{eff}}/r_{12})(r_{12}r_{21}-t_{12}t_{21})\exp( i2k_{0}\widetilde{n}_{\text{ITO}}t_{\text{d}}). \tag{3}\]  
In Equation (3), the critical coupling condition is satisfied for \(t_{\text{d}}\) and \(\lambda\) that forces the magnitude and phase of \(D(t_{\text{d}},\lambda)\) to be 1 and the integer multiples of \(2\pi\), respectively. Figure 7a,b show the magnitude and phase plots of \(D(t_{\text{d}},\lambda)\). In Figure 7a, the white-colored and red-colored dashed lines indicate where the magnitude and phase of \(D(t_{\text{d}},\lambda)\) are 1 and \(2\pi m(m\) being an integer), respectively. The points where two dashed lines cross correspond to the unity absorption. These points are distributed near 590 nm, at which the magnitude of the reflection coefficient between the ITO and grating (\(r_{\text{eff}}\)) is minimized. For comparison, the magnitude and phase of \(D_{0}(t_{\text{d}},\lambda)\) for a flat Al reflector (\(w=0\)) are presented in Figure 7c,d, respectively. Here, \(D_{0}(t_{\text{d}},\lambda)\) can be achieved by replacing \(r_{\text{eff}}\) as \(r_{0}=(\widetilde{n}_{\text{ITO}}-\widetilde{n}_{\text{AI}})/(\widetilde{n}_ {\text{ITO}}+\widetilde{n}_{\text{AI}})\) in Equation (3), where \(\widetilde{n}_{\text{AI}}\) represents the complex refractive index of Al. As can be seen from the plots, perfect absorption is unattainable in our calculation range without the subwavelength grating reflector since the unity magnitude condition on \(D_{0}(t_{\text{d}},\lambda)\) cannot be fulfilled. By exploiting this tendency, we can determine the structural parameters of visible light absorbers with desired absorption profiles.  
Figure 6: **(a)** The spectral absorption map with respect to the incident angle up to 80\({}^{\circ}\). The structural parameters are the same as those used in Figure 5 (\(p=160\) nm, \(w=40\) nm, \(t_{\text{g}}=30\) nm, and \(t_{\text{d}}=270\) nm). Absorption modes generated at oblique incidence are marked with the dashed red-colored oval. **(b)** Absorption profiles for three incident angles of \(\theta=20\), \(40\), and \(60^{\circ}\). Absorption peak shifts of new modes with increasing incidence angle are indicated by green-colored arrows.
## 2 Materials and Methods
### Calibration of Standard Curves  
Odor-active compounds identified by SDE-GC-O were quantitated by constructing standard curves. The mixed standard solutions were prepared through dissolving standard compounds in dichloromethane. Six levels of concentration were prepared for the calibration, and standards were analyzed in triplicate. In order to make the quantitative results more accurate, 16 aldehydes and 18 non-aldehydes were divided into two groups. Ten mg of each standard compound and 0.1 g of the internal standard solution (1,2-dichlorobenzene, 10 ug/g) were introduced to 5 g dichloromethane. The standard stock solution was then diluted with dichloromethane for six levels (1:10, 1:20, 1:30, 1:40, 1:50, and 1:60) for the calibration. The calibration equation for each compound was carried out by plotting the response ratio of standard compounds and 1,2-dichlorobenzene against their concentration ratio.  
These solutions were analyzed using HP-Wax column by GC-MS as described in Section 2.8, except that mass spectrometry was conducted in the single ion monitoring (SIM) mode. By the calibration equation, the concentration of each odor-active compound was calculated. The final results were the average of three replicates. The limits of detection (LOD) were estimated as the concentration of a standard whose signal-to-noise ratio was 3. The limits of quantitation (LOQ) were estimated as the concentration of a standard whose signal-to-noise ratio was 10.
## 2 Materials and Methods  
### Materials  
Commercial standardized biochars were purchased from UK Biochar Research Centre. Chosen samples were produced from five different biomasses feedstock (_Miscanthus_, wheat straw, oil seed rape, rice husk, and mixed softwoods) using a pilot-scale rotary kiln pyrolysis unit [14] setting the highest treatment temperature (HTT) to 550 \({}^{\circ}\)C. Pyrolysis parameters and yields are summarized in Table 1 according to the producer data (further info on the feedstock can be found following the link in reference [15]).  
Two components BFA diglycidyl resin were purchased from CORES (Cores epoxy resin, LPL). The curing agent was a mix of primary amines and DMP-30 promoting a two steps polymerization process (see with Figure 1).  
In the first step of polymerization, epoxy groups reacted with amines at room temperature producing a low polymerization degree material with aromatic or aliphatic inter chains junction. Afterwards, a thermal curing was carried out to complete the polymerization. During both steps, DMP-30 acted as catalyst and co-curing agent promoting a more uniform polymerization process. Use of small chains amines (1,3-phenylenedmethanamine and N\({}^{1}\),N\({}^{3}\)-dimethylpropane-1,3-diamine) together with the presence of residual hydroxylic functionalities made this material of interest for plenty of applications, such as casting or lamination [16].  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Feedstock**} & \multirow{2}{*}{**ID**} & \multicolumn{2}{c}{**Heating Rate**} & \multicolumn{2}{c}{**Residence Time (min)**} & \multirow{2}{*}{**Biochar Yield**} \\  & & \multicolumn{2}{c}{**(\({}^{\circ}\)C/min)**} & & \\ \cline{3-5}  & & & **Kiln Residence Time** & & **HTT Residence Time** & **(wt.\%)** \\ \hline _Miscanthus_ straw & MSP & 65 & 12 & 4 & 22.8 \\ \hline Wheat straw & WSP & 80 & 15 & 5 & 24.1 \\ \hline Rice husk & RH & 98 & 15 & 8 & 37.2 \\ \hline Mixed softwoods & SWP & 78 & 12 & 4 & 21.8 \\ \hline Oil seed rape & OSR & 78 & 12 & 5 & 28.9 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Main pyrolytic process parameters adopted by UK Biochar Research Centre for the production of standardized biochar samples.
# Physical and Respiratory Rehabilitation in Spinal Muscular Atrophy: A Critical Narrative Review
## 3 Results
### Motor Rehabilitation
#### 3.1.2 Aerobic Training  
[PERSON] et al., in their non-randomised controlled trial, studied the effect of training aerobic programs lasting twelve weeks in an in-home setting [52]. Participants trained at home using a cycle ergometer and performing aerobic sessions lasting 30 min at 65-70% of VO2 max, estimating VO2 max through correlation with heart rate. Thus, maintaining the heart rate to an oxygen uptake of 60-75% of VO2 max. All subjects monitored and recorded their heart rate during cycling using a Polar Pulse Watch. The patients were instructed to perform 3-5 min of warm-up before each training session, gradually increasing the workload until they reached the heart rate target. The number of sessions progressively augmented from two to four times a week, aiming to reach 42 sessions in 12 weeks. The training improved VO2 max in patients with SMA III by 27 \(\pm\) 3% (\(p\) < 0.001), but no significant changes in muscle strength, 6 MWT, 6 SST, TUG, and 5 STST in any patient.  
[PERSON] et al. conducted an RCT to examine the effects of a mixed program involving both strengthening and aerobic home-based training sessions in 14 participants with type III SMA [56]. The participants engaged in aerobic training using a cycle ergometer for 30 min,five times a week, and performed strengthening sessions three times a week, each with a similar duration. This intervention was administered for 19 months in the experimental group and 12 months in the control group. No significant changes in the experimental group after 6 months of exercise in the 6 MWT walking distance were reported. Instead, an improvement in VO2 max was observed in all participants after six months of exercise, with the greatest gains among those who adhered closely to the program. Compliance was defined as completing at least 90% of the recommended weekly exercise and not missing more than two consecutive weeks within three months. Across all participants (n = 10), percent-predicted VO2 max increased by 4.9% (\(p\) = 0.036), while the most compliant individuals (n = 5) experienced an even greater improvement of 6.6% (\(p\) = 0.012).
# Retrieval of High Spatial Resolution Aerosol Optical Depth from HJ-1 A/B CCD Data
## 2 Data and Methods  
### HJ-1 A/B CCD Data  
The Chinese HJ-1 Satellite Constellation for Environmental and Disaster Monitoring includes three satellites, i.e., HJ-1 A, HJ-1 B, and HJ-1 C. These satellites are used to forecast and monitor environmental conditions and disasters in China. The revisiting period of a single satellite is 4 days. The revisiting period can reach 2-4 days after the networking of HJ-1 A and HJ-1 B data (it is noted that HJ-1 C is a radar satellite that cannot be used for optical monitoring of land surfaces). The HJ-1 A and HJ-1 B satellites are equipped with two multispectral CCD sensors with blue, green, red, and near-infrared bands (Table 1). The data can be downloaded from the Land Observation Satellite Data Service Platform of the China Centre for Resources Satellite Data and Application ([[http://218.247.138.119:777/DSSPlatform/index.html](http://218.247.138.119:777/DSSPlatform/index.html)]([http://218.247.138.119:777/DSSPlatform/index.html](http://218.247.138.119:777/DSSPlatform/index.html))).
# CNN-BiLSTM-DNN-Based Modulation Recognition Algorithm at Low SNR
## 4 Experiment and Conclusion Analysis
### Analysis of Experimental Results
#### 4.2.3 Ablation Experiment  
To confirm the algorithm's efficacy, we carried out ablation experiments in which we experimented with models with attention mechanisms and models without attention mechanisms and compared the experimental results. All experiments used the conditions described in Section 4.1. Table 5 records the highest recognition accuracies and average accuracies of the study.  
Figure 6: Confusion matrix of different models at 0 dB in the RadioML2016.10b dataset.  
Figure 7: Confusion matrix of different models at 0 dB in the RadioML2016.10a dataset.  
The modulation recognition experiments of the proposed network model on the RML2016.10b and RML2016.10a datasets demonstrate that, from \(-20\) dB to \(18\) dB, the average recognition accuracy of the model with an attention mechanism is 0.51% and 1.75% higher, respectively, than that of the model without an attention mechanism. The highest accurate recognition rate is increased by 0.26% and 1.86%, respectively, which shows that the model with an attention mechanism can identify the modulation mode better than the model without an attention mechanism.
# Traffic Noise Reduction Strategy in a Large City and an Analysis of Its Effect
## 3 Results and Discussion
### Noise Quality Levels with Noise Barriers  
In order to further analyze the noise reduction effect of the noise barriers, Figure 9 compares the areas covered by traffic noise with different levels of quality between the cases with and without noise barriers. The definitions of the noise quality levels are given in Table 2 in Appendix A. It is noteworthy that, by applying noise barriers, the areas with a good noise quality level during the daytime and nighttime increased by about 4.68% and 5.65%, respectively. The areas with a quite good noise quality level increased by about 1.57% and 1.35%, respectively. The areas with slightly polluted noise quality level increased by about 1.72% and 0.7%, respectively. Correspondingly, the areas with moderate and heavy noise pollution were remarkably reduced by using noise barriers. Hence, it can be concluded that the overall noise quality level of Panyu District could be greatly improved by installing noise barriers along the traffic arteries in critical areas.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Noise Indicator** & \(\mathbf{SPL}_{min}\) & \(\mathbf{SPL}_{max}\) & \(\mathbf{\Delta SPL}_{min}\) & \(\mathbf{\Delta SPL}_{max}\) \\ \hline \(L_{day}\) & 39.8 & 80.1 & 0.1 & 5.2 \\ \(L_{night}\) & 39.2 & 72.0 & 0.2 & 6.1 \\ \(L_{dn}\) & 42.3 & 83.5 & 0.3 & 5.6 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Minimum (_min_) and maximum (_max_) noise levels of Panyu District in Guangzhou City with the existence of noise barriers. \(\Delta\)SPL = SPL\({}_{200}-\)SPL\({}_{w}\), where _wo_ and \(w\) stand for without and with noise barriers, respectively. All units are in dBA.  
\begin{table}
\begin{tabular}{l c c c c c c c c} \hline \hline
**Functional Area** & \(\mathbf{L}_{day1}\) & \(\mathbf{L}_{night1}\) & \(\mathbf{L}_{day2}\) & \(\mathbf{L}_{night2}\) & \(\mathbf{\Delta L}_{day1}\) & \(\mathbf{\Delta L}_{night1}\) & \(\mathbf{\Delta L}_{day2}\) & \(\mathbf{\Delta L}_{night2}\) \\ \hline Forest area & 39.8 & 39.2 & 61.3 & 61.1 & 3.0 & 2.9 & 1.9 & 2.0 \\ Residential area & 42.8 & 42.6 & 65.4 & 63.6 & 0.6 & 0.5 & 5.1 & 5.5 \\ Cultural education area & 49.0 & 48.5 & 63.9 & 63.5 & 0.4 & 0.5 & 4.9 & 5.0 \\ Administrative area & 52.4 & 51.9 & 60.5 & 60.1 & 0.6 & 0.7 & 2.7 & 2.5 \\ Medical service area & 48.1 & 47.6 & 60.3 & 60.0 & 0.6 & 0.7 & 3.1 & 2.5 \\ Trade area & 52.1 & 51.5 & 64.2 & 63.4 & 1.5 & 1.5 & 2.8 & 2.9 \\ Industrial area & 53.1 & 53.3 & 65.2 & 65.1 & 1.8 & 0.3 & 5.8 & 5.5 \\ Warehousing area & 53.6 & 52.3 & 67.9 & 67.3 & 0.7 & 2.2 & 0.5 & 0.5 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Minimum and maximum noise levels of different functional areas in Panyu District of Guangzhou City with the existence of noise barriers. The numbers 1 and 2 stand for minimum and maximum, respectively. All units are in dBA.
# Robotic Systems and Navigation Techniques in Orthopedics: A Historical Review
## 3 Computer-Aided Navigation Systems (CANSs)
### Typical Systems  
#### 3.2.1 Stryker Navigation System  
Stryker Navigation system II Cart (Stryker NAV3i website (accessed on 28 June 2023): [[https://www.stryker.com/us/en/navigation/products/nav3i.html](https://www.stryker.com/us/en/navigation/products/nav3i.html)]([https://www.stryker.com/us/en/navigation/products/nav3i.html](https://www.stryker.com/us/en/navigation/products/nav3i.html))) (Stryker, Kalamazoo, MI, USA) is an optical-based navigation system with an optical localizer accuracy of about 0.07 mm [71]. The navigation system can reconstruct the 3D bone model by using the original CT data. Dynamic reference trackers are placed on the patient's bone for later registration with considerations of avoiding nerve injuries and interrupting navigation pointer operations [71]. A study on validating the registration accuracy of a Stryker navigation system (Stryker II cart Navigation system) for elbow arthroscopic debridement showed that the registration accuracy can be within 1 mm [71].
## 3 Classification Framework for Analysis
### AI and Machine Learning in Remote Patient Monitoring
In the field of molecular diagnosis, particularly in relation to the diagnosis of infectious diseases, neoplastic diseases, cancer biomarkers, genetic mutations, and genotyping, as well as facilitating food safety control and environmental monitoring, nucleic acid testing is associated with high levels of specificity and sensitivity. Nucleic acid testing has a number of important advantages over other techniques, such as immune detection and microbial culture, including high levels of sensitivity and accuracy and a short operational time window. As a result, nucleic acid testing can quickly diagnose specific conditions and subsequently enable early therapeutic intervention. The COVID-19 outbreak that began in early 2020 is still spreading on a worldwide scale. This virus continues to have catastrophic effects and a wide potential for spread. The COVID-19 epidemic was diagnosed and controlled with the help of nucleic acid testing. The spread of this epidemic is puttingevery nation's medical diagnostic capacity to the test; as a result, there is currently an unprecedented need for the use of nucleic acid testing technology. Nucleic acid testing was in extremely high demand during the outbreak; however, it was not adequately satisfied. In fact, the technique of \"mix-testing\" has been widely used to expedite diagnosis. In this method, various samples are combined into one sample before testing, and, after irregularities are found, individual samples are analyzed [150]. Point-of-care testing has twice been suggested by the Chinese premier as a means of advancing nucleic acid testing. It was obvious that point-of-care diagnostics for nucleic acid analysis could cover this particular gap. Due to the exorbitant expense of this technology and the fact that nucleic acid testing equipment in China was previously primarily imported, China appeared to be particularly unresponsive to serious diseases. In China and other developing nations, the study and creation of low-cost, highly sensitive, quick, and portable nucleic acid testing equipment is now becoming more and more crucial. Many businesses have previously succeeded in creating point-of-care testing tools that could be used to find particular viruses with related kits. The polymerase chain reaction amplification systems GeneXpert, Filmarray, Cobas Liat, and others that were previously offered on foreign stock exchanges were quick and automatic but also expensive and could not be widely used in China. Due to the lack of point-of-care nucleic acid testing devices in China, which was a major factor in the epidemic, the current pandemic has encouraged the development and marketing of domestic point-of-care nucleic acid testing devices such as EasyNAT, Galaxy Nano, boxarray, GenPlex, iPonatic, and AutoSAT [150].