esa-sceva/satcom-chunk-collection huggingface dataset:
# A Review of Biochar Properties and Their Utilization in Crop Agriculture and Livestock Production
## 4 Biochar as a Manure/Sludge Additive
Researchers report that the BC addition improves composting process performance and contributes to the mitigation of gaseous emissions overall, retaining precious nutrients in the composted material. However, given the amazing properties of BC, many areas where BC could be utilized remain undiscovered. In the paper of [PERSON] et al. [48], it is merely suggested (in one sentence), that BC could reduce odor emissions from composting processes, and only one paper on the matter has been found. Thus, a complex investigation of BC influence on gaseous emissions is needed, including research on NH3, H2S, and VOCs emissions to evaluate BC amendment deodorizing potential, not only from composting mixtures but, for example, animal manure during livestock production. \begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** &
\begin{tabular}{c} **Feedstock** \\ **Material** \\ \end{tabular} & **Biochar Dose** & **Effect** \\ \hline [PERSON] et al. [39] & Wood shavings & 12\% (by volume) of dairy cattle slurry & - 77\% NH3 emission reduction - 63\% N2O emission reduction - 84\% CO2 emission reduction \\ \hline [PERSON] et al. [40] & Pinewood & 1.14 to 4.56 kg\(\cdot\)m\({}^{-2}\) of swine manure & - Up to 23\% NH3 emission reduction - Up to 30\% H2S emission reduction - Up to 26\% indole emission reduction - Up to 24\% CH4 emission increase \\ \hline [PERSON] et al. [41] & Pine chips & 5\% and 20\% by mass of poultry litter & - 58\% NH3 emission reduction - 71\% H2S emission reduction \\ \hline [PERSON] et al. [42] & Wood & 5\% by mass of sewage sludge-woodchips mixture & - 50\% NH3 emission reduction during the first week of composting - Enhancement of organic matter decomposition \\ \hline [PERSON] et al. [43] & Willow woodchips & 5\% and 10\% by mass of poultry manure-wheat straw mixture & - Up to 44\% NH3 emission reduction \\ \hline [PERSON] et al. [44] & Commercially manufactured & 1\% by mass of poultry manure-tomato stalk mixture & - Improvements in physicochemical properties of the composting mixture - Promotion of microbial activity in the compost \\ \hline [PERSON] et al. [45] & Wood & 5\% and 10\% by mass of poultry manure-wheat straw mixture & - Shortening of thermophilic phase - Increase in temperature of composting mixture - Up to 7.4\% increase in CO2 emission \\ \hline [PERSON] et al. [46] & Green waste Poultry litter & 10\% by dry mass of poultry manure-wheat straw mixture & - Up to 75\% N2O emission reduction - Up to 40\% of total N retained in the composting mixture \\ \hline [PERSON] et al. [24] & Brewer’s spent grain & 1\% to 50\% by mass of byproducts of the beer brewing process & - BC can increase biogas production by up to 32\%. \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of selected data on biochar application to waste for reduction of gaseous emissions.
## 4 Discussion  
Class II malocclusions represent a prevalent orthodontic problem generally associated with mandibular retrusion rather than maxillary protrusion [1]. Over the years, the literature has shown that functional appliances could be used to treat this malocclusion orthopedically, not only by determining skeletal and dentonalveolar effects but also causing a modification of the upper airway dimensions, highlighting a possible relationship between the upper airway, skeletal structures, soft tissues, and the muscular component [18]. The present study evaluated the changes in skeletal, dentonalveolar, and sagittal dimensions of the oropharyngeal airways induced by treatment with a fixed functional appliance (MARA) in patients with Class II malocclusion. For ethical reasons, we used a control group belonging to the AAOF Legacy collections that, while it might show some bias [19], proves to be a suitable representation of what occurs to growing subjects with untreated Class II malocclusion. During the active phase of treatment (T1-T2), the results of the present study showed no favorable effects on upper airway dimensions in the treated group compared to the control group. In the literature, there is only one study performed by CBCT evaluating volumetric changes in the upper airway in patients with Class II malocclusions treated with MARA followed by a fixed appliance and compared with an untreated group [12]. In disagreement with what was observed in our study, [PERSON] et al. showed that treatment with MARA determines a significant increase in the upper airway (\(p\) = 0.005 in reference to air volume) and a repositioning of the hyoid bone in treated patients compared to the control group (A-P distance 4.3 mm vs. 1.5 mm, \(p\) = 0.000). The different conclusions reported by this study could be interpreted by considering that the observation period represents an important
# A Seabed Real-Time Sensing System for In-Situ Long-Term Multi-Parameter Observation Applications
## System Design of SRSS/ILMO
### Seabed Observation Controller Design  
The seabed observation controller adopts dual microprocessor architecture with an ARM processor and FPGA supporting SOPC (system on a programmable chip) technology. Considering the different working processes, such as placement process, seabed penetration process, seabed observation process, seabed pull up process and recovery process, sensors are assigned to ARM and FPGA by category. ARM connects with the underwater acoustic communication module, PA200, TCM XB, the pressure sensor, and the penetration system needed in the placement and recovery process, seabed penetration and pull up process. At the same time, ARM is responsible for system scheduling, data storage, and low power management. In order to ensure data security, the system uses a dual media card to store data. Seabed in-situ long-term observation sensors are connected to FPGA, which is responsible for observation data collection, current and voltage management, and detection of each sensor. The system uses a star network topology structure to connect various observation sensors. The block diagram of the seabed observation controller is shown in Figure 5.  
Figure 4: Seabed engineering geology observation of SRSS/ILMO.
# Urban Traffic State Sensing and Analysis Based on ETC Data: A Survey
## 5 ETC-Based Urban Traffic Management: Applications and Practices
### System Integration and Technology Development Trends
Future ETC systems will achieve deeper system integration and functional expansion driven by emerging technologies such as 5G communication, artificial intelligence, and the Internet of Things, opening new pathways for the modernized development of urban traffic management.
# Compression of Vehicle Trajectories with a Variational Autoencoder
###### Abstract  
The perception and prediction of the surrounding vehicles' trajectories play a significant role in designing safe and optimal control strategies for connected and automated vehicles. The compression of trajectory data and the drivers' strategic behavior's classification is essential to communicate in vehicular ad-hoc networks (VANETs). This paper presents a Variational Autoencoder (VAE) solution to solve the compression problem, and as an added benefit, it also provides classification information. The input is the time series of vehicle positions along actual real-world trajectories obtained from a dataset containing highway measurements, which also serves as the target. During training, the autoencoder learns to compress and decompress this data and produces a small, few element context vector that can represent vehicle behavior in a probabilistic manner. The experiments show how the size of this context vector affects the performance of the method. The method is compared to other approaches, namely, Bidirectional LSTM Autoencoder and Sparse Convolutional Autoencoder. According to the results, the Sparse Autoencoder fails to converge to the target for the specific tasks. The Bidirectional LSTM Autoencoder could provide the same performance as the VAE, though only with double context vector length, proving that the compression capability of the VAE is better. The Support Vector Machine method is used to prove that the context vector can be used for maneuver classification for lane changing behavior. The utilization of this method, considering neighboring vehicles, can be extended for maneuver prediction using a wider, more complex network structure.  
intelligent transportation systems; autoencoders, maneuver classification; data compression Article Compression of Vehicle Trajectories with a Variational Autoencoder
## 3 Results and Discussion
### Thermal Conductivity Measurement Results
As a result, further thermal conductivity measurements were conducted at different mean temperatures (0, 10, 24, and 30 \({}^{\circ}\)C with 20 \({}^{\circ}\)C temperature differences, see Figure 5.). We have concluded that thermal conductivities increased as a function of mean temperature. The lowest thermal conductivity was attributed to the orange sample, followed by the green, yellow, and pink materials, in ascending order. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Insulation Material** &
\begin{tabular}{c} **Thickness at 20\%** \\ **Compression [cm]** \\ \end{tabular} & **Thickness at 2 kPa [cm]** \\ \hline Pink & 3.30 & 0.44 \\ Yellow & 3.65 & 0.74 \\ Green & 3.66 & 0.91 \\ Orange & 2.25 & 0.82 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Thicknesses during the thermal conductivity measurements. Figure 4: Thermal conductivity measurement results. With the [PERSON] equipment, we were able to measure the specific heat capacity (C\({}_{\text{p}}\)) values of the samples at 10 \({}^{\circ}\)C, and the results are shown in Table 5. It was found that the highest value was attained for the yellow sample, followed by the orange, green, and pink in descending order. Higher specific heat capacity means a higher potential for storing heat, which is a very important thermal property of insulation materials. Similar investigation results have been presented elsewhere [16; 43].
## 2 System Model  
Consider a LEO satellite IoT scenario, as shown in Figure 1, which consists of multiple IoT terminals, a cluster of low-orbit satellites and a gateway station. When the service occurs, the terminal encapsulates the generated data into packets and transmits them to LEO satellites. The LEO satellite nodes are responsible for forwarding the information to the gateway station. The downlink transmission is in a transparent forwarding way, so we assume that there is no loss in the downlink. After receiving the forwarding signals, the ground gateway station will process and demodulate the signals to obtain the service information generated by the terminals. We assume a Rice channel between terminal and satellite, with the channel coefficients denoted by \(h_{i}\), the second-order Reed-Muller (RM) sequence used to encode the preamble of packet. For packets without collision, the RM sequence carries the user ID information, so the gateway station can quickly detect the active user and perform channel estimation on the packet preamble to obtain the channel state information (CSI). For the collided packets, due to the nested structure of the subsequences of RM sequences, the corresponding CSI of the sequence can be obtained by the least squares (LS) channel estimation algorithm after the successful detection of the sequence according to the iterative RM sequence detection algorithm proposed in the literature [24]. At the same time, because the RM sequence has a larger sequence space when the same preamble length and a low detection complexity, the second-order RM sequence can also reduce the occurrence of packet collision phenomenon of the IoT. In terms of access protocols, the system uses the SC-ACRDA scheme proposed in this paper, where SC-ACRDA uses a multi-satellite selective collaborative beamforming algorithm to complement the elimination of collision scheme in the ACRDA protocol, as detailed in Section 4.  
Figure 1: An IoT scenario models.
# Evaluation of Snowboarding Helmets in Mitigation of the Biomechanical Responses of Head Surrogate
## 1 Introduction
The most prevalent anti-rotational technology is the multidirectional impact protection system (MIPS). This system features a thin slip liner that helps minimize rotational forces on the head by enabling movement between the helmet and the head upon impact. In addition to MIPS, WaveCel technology has been developed, which employs a collapsible cellular structure designed to provide rotational suspension. Using bicycle helmets, the efficacy of the aforementioned anti-rotational technology has been investigated. However, findings in the literature regarding their effectiveness in mitigating head accelerations and brain strains are confounding [6; 20; 22; 23; 38]. A few investigations suggest that anti-rotational technologies reduce rotational head kinematics considerably [20; 22], while a few other investigations suggest that the mitigation offered by anti-rotational technologies is either marginal or insignificant [6; 38]. Thus, understanding the role of anti-rotational technologiesin mitigating rotational head kinematics and brain response is far from complete. Further, the effectiveness of the aforementioned anti-rotational technology in mitigating brain responses in snowboarding has not been investigated. The goal of the manuscript was to evaluate the efficacy of snowboarding helmets (conventional and anti-rotational) in mitigating head kinematics and kinetic responses. Towards this end, we have evaluated the performance of various snowboarding helmets under blunt impact. We also evaluated the performance of newly developed (developed in house), low-cost silica-based anti-rotational pads by integrating them with a conventional snowboarding helmet. We measured head kinematics and brain simulant pressures in a head surrogate. Experimentally measured head kinematics was used as an input to the computational human head model to obtain the brain responses. This work is novel in several aspects: (a) We holistically evaluate the performance of different types of snowboarding helmets (conventional and anti-rotational) against blunt impact. Using experiments, we measured the head kinematics (i.e., angular velocity, angular acceleration, linear acceleration) and brain simulant pressures in the head surrogate equipped with the aforementioned snowboarding helmets. Further, using concurrent simulation, we computed brain responses (i.e., brain simulant pressure, equivalent von Mises stress, and MPS) in the computational head model. We believe that we are the first to evaluate the performance of snowboarding helmets in terms of brain responses. (b) We evaluated the performance of newly developed, low-cost silica-based anti-rotational pads by integrating them with a conventional snowboarding helmet. These aspects have never been investigated in the past.
# Towards a Low-Cost Precision Viticulture System Using Internet of Things Devices
## 6 Experimental Results  
In order to evaluate the performance of the system, several experiments were conducted in a vineyard. The experiments took place in August 2019 and in October 2019, in order to have different performance of the solar panels at the nodes. In total, 10 wireless monitoring nodes were used along with 4 relay nodes.  
\begin{table}
\begin{tabular}{l l} \hline \hline Battery & 1500 mAh LiPo \\ \hline Camera & HD camera 720p, 30 fps video output \\ \hline Flight Time & 18 min \\ \hline Interfaces & Wi-Fi 802.11b/g \\ \hline \hline \end{tabular}
\end{table}
Table 6: AR Drone 2.0 Specification.  
Figure 11: Experimental results of the drone (**a**) flying time and (**b**) current consumption when flying 1 km, under different configurations.  
Each wireless monitoring node had 4 soil moisture and 4 soil temperature sensors. The distance between the relay nodes was approximately 1 km. All the components of the system are shown in Figure 12.
## 2 Related Work
Therefore, directional antennas are utilized to reduce spatial self-interference because they have the advantages of assigning shapes to the antenna and improving signal gain. Therefore, we equipped the UAVs with directional antennas. Many studies have also been conducted on the use of directional antennas. In [23], the maximum coverage of the UAVs with adjustable antenna beam width was analyzed. In [24], the directional transmission communication was proposed to improve the transmission quality. [PERSON] et al. analyzed the coverage performance of UAVs equipped with directional antennas [25]. The beam multiplexing technique of directional antennas was intensively studied in the future development of 6G [26]. They both analyzed the effect of directional antennas on network performance under the PPP model. However, the rejection relationship of network nodes in the real environment was not considered. To summarize, we followed the \(\beta\)-. The GPP model deploys the UAV in the air and equips the UAV with directional antenna. The research focus of this paper was to derive the connection probability, ergodic ability, and coverage probability of the multi-hop relay system based on a UAV network under \(\beta\)-GPP, as well as the fitting of accurate data. Since the \(\beta\)-GPP series constitutes an intermediate category between PPP (random independent) and GPP (relative regular), we can visually simulate many real drone networks by adjusting the variation of \(\beta\).
# Quantum Key Distribution in the Presence of the Intercept-Resend with Faked States Attack
## 4 Detecting the \(\mathit{IRFS}\) Attack
### The Non-Structured _Nack State Protocol_  
The argument of Point 2 implies that [PERSON] uses only a single station, but this is not a practical restriction. [PERSON] could use two stations, one close to [PERSON] to detect and one close to [PERSON] to generate fake pulses. If the quantum channel uses optical fibers (the most common practical channel for ground-based \(QKD\)), all [PERSON] would need is a radio link between her two stations to \"catch up\" with the quantum link. Even if we assume a low source rate of 1 MHz, the time delay between pulses is only one microsecond, which can be compensated using a 600-m link (traveling in free space takes two microseconds; travel in fiber takes three microseconds). Any practical \(QKD\) system will operate over distances greater than 600 m, making it entirely feasible for [PERSON] to detect both pulses of a pair before sending her fake state to [PERSON] using a second station.  
However, there is no reason why each pair has to be sent in a consecutive manner. We call this protocol the non-structured _nack state_. If [PERSON] were to send a burst of the first states of each pair, followed by a burst of the second states of each pair, she would create a separation between the pairs equal to the length of the bursts without reducing the pulse rate. Consider a 100-km fiber optic link; [PERSON] could send the first states of each pair for 500 microseconds, followed by the second state of each pair for the next 500 microseconds, with [PERSON] re-choosing the same basis for both 500-microsecond bursts. Because the 500-microsecond delay is at least the full travel time in the quantum channel, [PERSON] would always be forced to fake the first state of each pair before receiving the second. If there is no issue with this approach, the authors can use it to justify Point 2, which in turn justifies Point 1.
## 5 Conclusions  
Monitoring vegetation dynamics and their influencing mechanism is crucial for informing urban sustainability. However, how different vegetation indices vary in their changes and responses to climate change and land use change remains unclear. Based on the trend detection of vegetation greenness and productivity, this study examined their inconsistency and explored its potential reasons in three agglomerations. The results showed that both vegetation greenness and productivity exhibited an overall upward trend in the three agglomerations during the study period. However, a notable inconsistency was observed, indicating that increases in greenness do not necessarily translate into corresponding increases in productivity. This inconsistency was attributed to the combined effects of land use change and climate change, which operated differently in various regions. Furthermore, this study found that the influence of climatic factors and land use change differed among agglomerations because of variations in natural backgrounds. This study offers a fresh perspective on regional vegetation change research, which is valuable for policymakers and land managers seeking to promote sustainable urban development.  
Conceptualization, methodology, and funding acquisition, Y.H.; software, formal analysis, writing, and editing, Y.H. and F.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (42201102) and Research Project of Shanghai Municipal Bureau of Ecology and Environment (No. 9, HuHuanKe [2023]).  
Not applicable.  
The data supporting this study are available from the following resources in the public domain. The LAI dataset was obtained from MOD15A2H ([[https://lpdaac.usgs.gov/products/mod15a2](https://lpdaac.usgs.gov/products/mod15a2) hv006/]([https://lpdaac.usgs.gov/products/mod15a2](https://lpdaac.usgs.gov/products/mod15a2) hv006/), accessed on 23 May 2024). The GPP dataset was obtained from MOD17A2H ([[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 23 May 2024). Land use/cover data were obtained from the International Geosphere Biosphere Program (IGBP) classification scheme of MCD12 QI ([[https://modis.gsfc.nasa.gov/data/dataprod/mod12.php](https://modis.gsfc.nasa.gov/data/dataprod/mod12.php)]([https://modis.gsfc.nasa.gov/data/dataprod/mod12.php](https://modis.gsfc.nasa.gov/data/dataprod/mod12.php)), accessed on 23 May 2024). Climatic data, including temperature, rainfall, and solar radiation, were obtained from the Resource and Environment Science and Data Center ([[http://www.resdc.cn](http://www.resdc.cn)]([http://www.resdc.cn](http://www.resdc.cn)), accessed on 24 May 2024). The administrative boundary was obtained from the Geographical Information Monitoring Cloud Platform ([[http://www.dsac.cn/](http://www.dsac.cn/)]([http://www.dsac.cn/](http://www.dsac.cn/)), accessed on 18 May 2024).  
The authors declare no conflicts of interest.