esa-sceva/satcom-chunk-collection huggingface dataset:
# Vulnerabilities and Limitations of MQTT Protocol Used between IoT Devices
## 4 Research
### Performance Assessment  
In order to compare the performance of the HMAC algorithm based on different cryptographic hash functions, timers have been placed before and after the execution of each function to calculate an approximate execution time. Additionally, in order to smooth out the irregularities in time  
Figure 1: Hash-based Message Authentication Code model.  
measurements caused by hardware interrupts, each pair of timers recorded a large number of iterations for each function; therefore, the values described in the graphs represent 1000 iterations of each function. The time measurement script was written in Python 3 and has made it possible to take advantage of the most accurate timer functions available within Python. Furthermore, the script makes use of libraries, such as 'hashlib' and 'pycrypto', which have implemented AES and HMAC algorithms, as well different cryptographic hash functions.  
The following timings were generated on the resource-constrained device, the Omega2+-Upon execution, it will run the HMAC generation speed test for a number of cryptographic hash functions currently used in different cryptosystems. As shown in the table below, some hash functions are faster than others at generating a digest on a 32-bit CPU. Additionally, it can be noticed that the encryption phase of AES in Cipher Block Chaining mode is considerably slower than operation of producing a Hash-based Message Authentication Code digest (Figure 2).  
As shown by the bar chart, an ideal algorithm for the Onion Omega2+ should be chosen from SHA3-224, SHA3-256, or Blake2. According to References [10,11], the Blake2 hashing algorithm is considerably faster at generating a digest, even when compared to SHA, SHA2, or SHA3, and it is more suitable for resource-constrained devices. Additionally, Blake2s was optimized to work on a 32-bit CPU and produces and output hash of 32 bytes (256 bits). The increase in performance on the Onion Omega, when comparing Blake2s to SHA3-224 or SHA3-256 digest generation is on average 20%. The reason why the comparison is made between Blake2s and SHA3-224 and SHA3-256 is because these algorithms, from the SHA3 category, are faster on a 32-bit CPU.
# Multi-Adjacent Camera-Based Dangerous Driving Trajectory Recognition for Ultra-Long Highways
## 6 Conclusions  
This paper proposes an effective framework for vehicle trajectory recognition on ultra-long highways, and designs a network architecture based on DeepSORT and YOLOv5s for efficient multi-vehicle target tracking to quickly obtain trajectories within the visible area. We also propose an attribute recognition module to effectively implement vehicle re-identification, correctly splice together the trajectories of the same vehicle on different road segments, and ultimately restore the complete trajectory of the vehicle. In addition, to solve the problem of a certain range of blind spots between the fields of view of adjacent cameras in ultra-long-distance road scenarios, a bidirectional LSTM structure is introduced in our framework to predict the trajectory of the blind spots. This study realizes the splicing and reconstruction of vehicle motion trajectories in the entire area, which is conducive to the effective identification of abnormal trajectories. Judging from the Cumulative Matching Characteristic (CMC) curve, the proposed model has high advantages and even improves by more than 15.38% compared with other state-of-the-art methods. Experimental results demonstrate the effectiveness of this method in accurately identifying various vehicle behaviors, including lane changing, parking, and even other dangerous driving behaviors.  
**Funding:** This work was supported by the Scientific Research Project of Shaanxi Provincial Department of Transportation (No. 21-42X) and Innovation Capability Support Program of Shaanxi (Program No. 2022 TD-16).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Dataset available on request from the authors. The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** Authors [PERSON] and [PERSON] were employed by the company CCCC First Highway Consultants Co., Ltd., Xian, China. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
## 3 Numerical Examples
### Characterization of Longitudinal Thermoelastic Guided Wave
#### 3.2.2 Displacement Distribution and Temperature Variation Distribution of Longitudinal Modes  
Figure 5 shows the displacement distribution curves of the first three longitudinal modes at k = 2 and the temperature change curves. From the figure, it can be seen that the magnitude of the displacement change in the mass point in the elastic mode is much  
Figure 4: Dispersion curves of longitudinal modes in hollow cylinders of silicon nitride: (**a**) spectrogram of hollow cylinder; (**b**) phase velocity profile.  
larger than that in the thermal mode. Meanwhile, there is no circumferential component in the displacement of the mass in the longitudinal mode. For the L (0,1) mode, the radial component \(u_{r}\) of the displacement is dominant in the wall thickness range, and the axial component \(u_{z}\) has a weak influence. Moreover, the trend of change shows that the radial displacement varies relatively little over the entire range of wall thicknesses, whereas the axial displacement component shows a large amplitude variation. The magnitude of temperature variation is also larger for this mode. For the L (0,2) mode, the axial component of the mass displacement, \(u_{z}\), varies in a smaller magnitude, and the radial displacement of the mass, \(u_{r}\), varies in a larger range. For the thermal mode represented by mode 3, the magnitude of the displacement changes at the plasma point decreases sharply at this point compared to the previous two modes. The mass displacement of this mode is similar to that of the L (0,2) mode. The axial displacement component \(u_{z}\) changes by a smaller magnitude, and the radial displacement component \(u_{r}\) changes by a larger magnitude.  
Figure 5: Displacement versus temperature variation: (**a**) coupling temperature L (0,1); (**b**) temperature change; (**c**) coupling temperature L (0,2); (**d**) temperature change; (**e**) thermal mode; (**f**) temperature change.  
The above analysis shows that the amplitude of the mass displacement of the thermal mode is much smaller than that of the first two modes. However, the amplitude of temperature change in these three modes is similar, and the boundary condition of isotherm is satisfied on both the inner and outer surfaces.
# A New Methodology for Estimating Surface Albedo in Heterogeneous Areas from Satellite Imagery
## 4 Methods  
Taking into account the aforementioned methodologies for surface albedo calculation, this work has analysed four original methodologies for the computation of surface albedo with the aim of evaluating which model makes a better representation of the reality of most land covers. The difference between the four methodologies is the way the atmospheric corrections are performed: V01 and V02 correct by-product of albedo (Section 4.1) and V03 and V04 correct the Landsat 8 bands (Section 4.2) (Figure 2).  
Following this evaluation, a new approach based on three combined methodologies have been tested based on the NDVI of the land cover (Section 4.4). All these methodologies are represented in Figure 2.  
\begin{table}
\begin{tabular}{c c c c c c} \hline
**Code** & **Name** & **Latitude** & **Longitude** & **Elevation** & **Installation Date** \\ \hline BND & Bondville, Illinois & 40.05192\({}^{\circ}\) N & 88.37309\({}^{\circ}\) W & 230 m & April 1994 \\ FPK & Fort Peck, Montana & 48.30783\({}^{\circ}\) N & 105.10170\({}^{\circ}\) W & 634 m & November 1994 \\ PSU & Penn. State & 40.72012\({}^{\circ}\) N & 77.93085\({}^{\circ}\) W & 376 m & June 1998 \\ SXF & Sioux Falls, South Dakota & 43.73403\({}^{\circ}\) N & 96.62328\({}^{\circ}\) W & 473 m & June 2003 \\ \hline \end{tabular}
\end{table}
Table 2: Information from the SURFRAD stations selected in this work: code, city, latitude, longitude, elevation, and installation date.  
Figure 1: Location of SURFRAD stations used in this study and the area covered by the ABOVE mission.
# Minimizing Travel Time and Latency in Multi-Capacity Ride-Sharing Problems
## 3 The Transportation Algorithm and Its Analysis
### Discussion  
Clearly, the TA is a polynomial-time algorithm, and it is easy to implement; moreover, it can be generalized to handle a variety of situations. We now list three situations and briefly comment on the corresponding worst-case behavior:  
* **Ride-sharing with car-dependent speeds or _related_ ride-sharing.** In this situation, the cars have speed \(p_{1},p_{2},\ldots,p_{n}\). The travel time of serving requests in \(R_{k}\) is denoted by \(\text{cost}(k,R_{k})/p_{k}\), and the total travel time of an allocation \(M\) is denoted by \(\sum_{(k,R_{k})\in M}\text{cost}(k,R_{k})/p_{k}\). Analogously, the total latency of an allocation \(M\) is denoted by \(\sum_{(k,R_{k})\in M}\text{wait}(k,R_{k})/p_{k}\). Without going into the details, we point out that the TA can be modified by appropriately redefining \(v_{1}(k,r)\) and \(v_{2}(k,r)\) in terms of the cost above; we claim that the corresponding worst-case ratios of TA as shown in Table 1 remain unchanged;
* **Car redundancy:**\(c\cdot n>m\). In this situation, our problem is to find an allocation that serves all requests with the minimum total cost (total travel time or total latency). Clearly, some cars may serve less than \(c\) requests, or even do not serve a request. To apply TA for this situation, we need to add a number of requests to fill the shortage of requests, without affecting the total travel time or latency. We created an instance of our problem by adding a number of dummy requests \(R_{d}\) with \(|R_{d}|=c\cdot n-m\), where the travel time between a request in \(R_{d}\) and a car in \(D\) is zero, i.e., \(v_{1}(\gamma_{i}(k),r)=0\) and \(v_{2}(\gamma_{i}(k),r)=0\) for all \(i\in[c],k\in D,r\in R_{d}\). Since the cost of assigning dummy requests is zero in any feasible solution, removing dummy requests of a solution for the newly created instance with \(c\cdot n=|R|\) will give us a solution to the original instance;
* **Car deficiency:**\(c\cdot n<m\). In this situation, our problem is to find an allocation that serves the maximum number of requests (\(c\cdot n\) requests) with the minimum total cost (total travel time or total latency). It follows that some requests will not be served. To apply the TA for this situation, we created an instance of our problem by adding a number of dummy cars \(D_{d}\) with \(|D_{d}|=m-n\cdot c\), where the travel time between a car in \(D_{d}\) and a request in \(R\) is \(H\) (\(H\) is a sufficiently large number), i.e., \(v_{1}(k,r)=H\) and \(v_{2}(k,r)=H\) for all \(k\in D_{d}\), \(r\in R\). Removing dummy cars (and their corresponding requests) gives us a solution to the original instance. Since we found an assignment with the minimum total weight and we removed the set of requests assigned to the dummy cars, we claim that the TA selected \(c\cdot n\) requests with the minimum total weight. In fact, the proofs in Section 3.1 imply that the TA\((v_{1})\) is a \((2c-1)\)-approximation algorithm for CS\({}_{sum}\) and the TA\((v_{2})\) is a \(c\)-approximation algorithm for CS\({}_{lat}\).
# Herbal Support for the Nervous System: The Impact of Adaptogens in Humans and Dogs
## 2 Ginseng (_Panax ginseng_ [PERSON])
### Studies Related to Therapeutic Effects on Humans  
[PERSON] et al. [67] analyzed the effect of a water extract of _P. ginseng_ reducing oxidative stress associated with aging. The main biologically active substances in the aqueous extract were saponins, including ginseng; for the study, 200 mg of aqueous extract per kilogram of body weight was administered for 4 weeks. The authors compared lipid peroxidation levels and antioxidant concentrations in both young and old rats. Older rats exhibited a significant increase in oxidative damage markers (e.g., lipid peroxidation) and organ damage markers such as aspartate aminotransferase, alanine aminotransferase, urea, and creatinine. This was accompanied by a notable decline in enzymatic antioxidants (superoxide dismutase, catalase, glutathione peroxidase, glutathione reductase and glutathione-S-transferase) as well as non-enzymatic antioxidants, including reduced glutathione, vitamin E, and vitamin C. In aged rats whose diet was supplemented with aqueous ginseng extract, oxidative damage was significantly reduced, likely due to an improvement in antioxidant balance through both enzymatic and non-enzymatic protective mechanisms.  
Biological aging leads to increased susceptibility to several functional disorders, making elderly individuals more prone to various diseases compared to younger individuals. Alzheimer's disease (AD) is an age-related neurodegenerative disorder characterized by cognitive deficits and the formation of amyloid plaques due to the accumulation of amyloid-\(\beta\) peptides. A non-saponin fraction rich in polysaccharides (NFP) from ginseng significantly alleviated amyloid-\(\beta\) accumulation, neuroinflammation, neuronal loss, and mitochondrial dysfunction in the hypothalamus of an AD mouse model, administered for 8 weeks at a dose of 150 mg/kg. Furthermore, NFP treatment alleviated mitochondrial deficits in HT22 cells treated with amyloid-\(\beta\). Additionally, NFP treatment significantly enhanced adult hippocampal neurogenesis (AHN) and neural stem cell neurogenesis in both healthy and AD-affected brains. Moreover, NFP administration markedly improved and restored cognitive function in both healthy and Alzheimer's disease-affected mice. Collectively, NFP treatment induced changes in proteins involved in central nervous system organization/maintenance in the aging brain and mitigated AD pathology. Therefore, the non-saponin fraction rich in polysaccharides from ginseng may be a potential therapeutic candidate for aging and AD treatment [69].  
The optimal dose of ginseng for an adult described in the literature is 50 to 100 mg of extract standardized to 20% ginseng or 500 to 2000 mg of dried root [70; 71; 72].
# Optimization of Effective Throughput in NOMA-Based Cognitive UAV Short-Packet Communication
## 5 Conclusions  
In this paper, we derive an effective throughput for secondary users and optimize the power allocation, information bits, and sensing time to maximize the effective throughput for the secondary users under the constraints of the transmission power and effective decoding error probability. Specifically, we prove that the effective throughput is a concave function with respect to the sensing time and information bits, respectively, and then the bisection method is employed to obtain the optimal value. For the power allocation, we first reduce the feasible power range of \(u_{1}\). Then, the one-dimensional linear search method is used to obtain the optimal value. Therefore, the complexity of the proposed algorithm is considerably reduced compared to the exhaustive method. In the simulations, it can be seen that the NOMA scheme can achieve higher optimal values compared to the OMA scheme. In Figure 7, we can see that the proposed algorithm has a similar performance to that of the exhaustive method. In addition, when there are significant differences between the two channels, the NOMA is more appealing.  
Figure 6: False-alarm probability versus sensing time for different \(\gamma_{p}\) and \(P_{d}\).  
Figure 7: Performance comparison for different algorithms and schemes.  
**Author Contributions:** Conceptualization, S.Z., H.H. ([PERSON]) and Y.H.; Methodology, S.Z., H.H. ([PERSON]) and H.H.H. ([PERSON]); Software, H.H. ([PERSON]); Validation, S.Z.; Writing--original draft, S.Z.; Writing--review & editing, H.H. ([PERSON]), Y.H., G.C., T.H. and H.H. ([PERSON]); Visualization, S.Z. and Q.A.; Supervision, H.H. ([PERSON]), Y.H., G.C., T.H. and Q.A.; Project administration, H.H. ([PERSON]); Funding acquisition, H.H. ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work is supported by grants from the National Natural Science Foundation of China (No. 61901509) and the Natural Science Foundation of Shanxi Province of China (No. 2021 JQ-366).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Steam Gasification of Lignite in a Bench-Scale Fluidized-Bed Gasifier Using Olivine as Bed Material
## 2 Materials and Methods
### Experimental Test Rig
The data acquisition frequency was 100 Hz, which is much higher than the values typically observed in gas-fluidized beds under study (less than 10 Hz). The duration of each acquisition was 2-3 min, to ensure their repeatability and significance [24]. Stored signals were processed by means of a MATLAB(r) script, which calculated their standard deviations, as well as the power spectral density function (PSDF), by fast Fourier transform [25]. Standard deviations are directly related to the size of bubbles erupting at the upper bed surface (the higher the standard deviation, the bigger the bubbles), while PSDF allows dominant frequencies of pressure fluctuations to be identified, related to the number of erupting bubbles [18]. The lignite gasification tests were carried out using olivine as bed material, with a constant feeding rate of lignite and steam. For each test, a new batch of calcined olivine was inserted as bed material in the reactor, in order to compare tests with equivalent initial conditions avoiding the accumulation of ash in the bed material, which could have beneficial effects, such as the enhancement of tar conversion [26; 27]. The operating temperature was changed in the tests between 750 and 850 \({}^{\circ}\)C and air injections were added in three of the six tests. Tests #1, #2, and #3 were carried out at operating temperatures of approximately 750, 800, and 850 \({}^{\circ}\)C, respectively. Tests #4, #5, and #6 had the same input conditions adopted in the first three tests, but with an additional air stream of 8 NI/min injected in the freeboard of the reactor. The operating conditions used are summarized in Table 1. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Test** & **\#1** & **\#2** & **\#3** & **\#4** & **\#5** & **\#6** \\ \hline Feedstock (g/min) & & & & 12.75 & & \\ Operating Temperature (\({}^{\circ}\)C) & 750 & 800 & 850 & 750 & 800 & 850 \\ Air Injections (NI/min) & - & - & - & 8 & 8 & 8 \\ Steam flow (g/min) & & & & 8.25 & & \\ N\({}_{2}\) flow (NI/min) & 8.83 & 17.20 & 7.39 & 7.32 & 7.44 & 7.44 \\ Steam/Fuel (g/g) & & & & 0.65 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Operating conditions of the test campaign. Figure 1: Scheme of the bench-scale gasification test rig. 1—water pump; 2—steam generator; 3—air and N\({}_{2}\) gas tanks; 4—air and N\({}_{2}\) mass flow controllers; 5—bubbling fluidized-bed gasifier; 6—electric furnace; 7—ceramic filter candle (OD of 60 mm, length of 440 mm); 8—screw conveyor for feeding fuel; 9—heat exchangers for steam condensation; 10—tar sampling unit; 11—vacuum pumps; 12—syngas mass flow controllers; 13—gas analyzers.
## 2 Materials and Methods
### Experimental Data and Remote Sensing Imagery
#### 2.2.3 Remote Sensing Data  
Due to the cloudy and rainy weather in the study area, it is easy to result in a long-term sequence of single optical remote sensing data being missing. Therefore, this experiment uses data from multi-source satellites for analysis. Multi-source satellite images include Landsat@ OLI and Sentinel-2 data. The Landsat 8 satellite is the latest generation of terrestrial remote sensing satellites. Its sensors have been significantly improved in terms of imaging mode, the band setting, signal-to-noise ratio, etc. In contrast, Sentinel-2 has a higher spatial resolution (10 m) and shorter revisit period (5 days), which can supplement missing data in time. Collected satellite data from 2014 to 2018 (29 scenes) consider the different seasons, including 11 scenes during the dry season (November to April of next year), and 18 scenes during the flood period (May to October of each year) (Table 2).  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Season** & **Type of Data** & **Image Date** & **Track Number** \\ \hline \multirow{6}{*}{Dry season} & & 14 Novmeber 2014 & 21 December 2016 & \\  & & 1 January 2015 & 8 December 2017 & \\  & Landsat@ OLI & 17 January 2015 & 24 December 2017 & Path: 124 \\  & & 3 November 2016 & 6 January 2017 & Row: 45 \\  & & 5 December 2016 & 22 January 2017 & \\  & Sentinel-2 & & 19 December 2018 & 49 QDE \\ \hline \hline \end{tabular}
\end{table}
Table 2: Summary of the satellite remote sensing data used in this study, which includes a ground-synchronized remote sensing image on 16 October 2015.  
The processing of remote sensing data is mainly based on ENVI and ArcGIS platforms, including radiation correction, FLAASH atmospheric correction, band fusion and other operations. Its purpose is to eliminate errors caused by atmospheric scattering, absorption and reflection.
## 2 Explanation of the Working Process and Perturbation Theory of the Seeder  
### Composition and Working Principle of Seeder Structure  
The structural composition of the pneumatic perturbation type small cabbage fine seeder is shown in Figure 1, which is mainly assembled by the seed box shell, seed guide tube, drive shaft, seed discharge disk, air chamber cavity, and other components. When the pneumatic seeder works, cabbage seeds first enter the seed-filling cavity at the bottom of the seed box from the seed inlet and pile up. Driven by the drive shaft, the linear serrated disk starts to rotate. Its upper serrated structure will break the inertia of the seeds piled up in the seed-filling chamber during the rotation process and separate a small number of cabbage seeds from the seed population for the smooth progress of the seed-filling process. At this time, the negative pressure provided by the fan will generate a pressure gradient difference on both sides of the linear serrated disk hole, so that the cabbage seeds will rely on the negative pressure to be adsorbed on top of the linear serrated disk hole and follow the rotation of the seed discharge disk. When the cabbage seeds rotate to the sowing area,the negative pressure disappears, and the cabbage seeds at the disk hole are blown down to the seed guide tube under the action of its gravity and the positive pressure-blowing force of the fan to complete a sowing operation.
# Navigation in GEO, HEO, and Lunar Trajectory Using Multi-GNSS Sidelobe Signals
## 2 Observation Simulation Strategy
### Space Vehicle's Orbital Parameters  
Three classic types of space missions were considered, including GEO, HEO, and lunar trajectory. Detail parameters are listed in Tables 3-5. Note that the entire lunar mission included three Earth parking orbits and two lunar orbits; however, the lunar trajectory  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**System** & **GPS** & \multicolumn{2}{c}{**BDS**} & \multicolumn{2}{c}{**GLONASS**} & **Galileo** \\ \hline Orbital type & MEO & GEO & IGSO & MEO & MEO \\ Number of & 31 & 3 & 3 & 24 & 24 & 24 \\ satellites & & & & & \\ Constellation & & & & & \\ configuration & & & & & \\ Inclination & 55\({}^{\circ}\) & 0 & 55\({}^{\circ}\) & 64.8\({}^{\circ}\) & 56\({}^{\circ}\) \\ Altitudes [km] & 20,200 & 35,786 & 35,786 & 21,528 & 19,100 & 23,221.7 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Parameters of GNSS Constellations.  
Figure 1: GNSS constellations.  
parameters we listed here only cover epochs that the spacecraft transfers from the Earth to the moon.