esa-sceva/satcom-chunk-collection huggingface dataset:
## 1 Introduction
[21] focused on reducing the construction cost by decreasing the optimum content of bitumen with partial replacement of waste frying oil. Their study proved that with the inclusion of only 3-5% of frying oil, the bitumen content was reduced by 11%. They further concluded that the fry oil modification enhanced the self-healing properties of HMA at low temperatures. [PERSON] et al. [22] utilized the used and virgin maize oil for binder modification. Their results showed that with the increase of maize oil content the elasticity was increased while the stiffness was reduced. The mixing and compaction temperatures were decreased by 5-10 \({}^{\circ}\)C, proving an efficient modifier for warm mix asphalt (WMA). [PERSON] et al. [15] investigated the effect of bio-based and refined waste oil on low temperature properties of asphalt binder. They discovered that the glass transition temperature tended to decrease and the fracture energy of asphalt binder could be enhanced up to three folds by using 5% refined waste oil. [PERSON] et al. [23] performed X-Ray fluorescence spectroscopy on asphalt cement modified with waste engine oil. They observed a premature failure in pavement due to loss of strain tolerance and physical hardening of asphalt binder caused by waste oil residues after modification. Waste engine oil addition can soften and rejuvenate aged asphalt binders and results in an environmentally friendly mixture [24; 25]. In this context, the use of waste engine oil in partial replacement of binder in HMA, RAP or WMA can prove to be an acceptable and sustainable solution to managing this waste material. This study was carried out to evaluate the rheological properties of asphalt binder with 2.5% of a single multigrade fresh and waste (filtered and un-filtered)engine oil, with an aim to decrease the viscosity (rejuvenation) and stiffness (thermal cracking) at low temperatures. _Objective(s)_  
Taking into account the previous literature, the objectives of this research work are as follows  
1. To assess the properties imparted to asphalt cement with a specific viscosity grade engine oil (5W30) rather than a collective blend of different waste engine oils. 2. To study the effect of metal traces present in waste engine oil on rheological properties of modified asphalt cement. 3. To evaluate the effect of waste oil modification on low and high temperature properties of asphalt cement.
# Design of a Hand-Launched Solar-Powered Unmanned Aerial Vehicle (UAV) System for Plateau
## 4 UAV Flight Control  
### Lateral-Directional Nonlinear Dynamic Model  
The wings of a solar-powered UAV provide the main solar cell laying surface, so a complete wing without split by control surface is especially important for a small solar-powered UAV. In this paper, the MP Solar UAV was anileron-free and used rudder to control both yaw axis and roll axis. The rudder deflection generated yaw moment, and the sideslip angle generated by the rudder deflection also brought a large roll moment because the wing had a dihedral design [16]. The lateral-directional nonlinear dynamic model [17] of aileron-free UAV was established as Formula (19).  
\[\left\{\begin{array}{l}\dot{v}=pw-ru+g\cos\theta\sin\varphi+Y/m\\ \dot{\varphi}=p+q\sin\varphi\tan\theta+r\cos\varphi\tan\theta\\ \dot{\psi}=q\sin\varphi\sec\theta+r\cos\varphi\sec\theta\\ \dot{p}=\Gamma_{1}pq-\Gamma_{2}qr+\Gamma_{3}l+\Gamma_{4}n\\ \dot{r}=\Gamma_{5}pq-\Gamma_{1}qr+\Gamma_{4}l+\Gamma_{6}n\end{array}\right. \tag{19}\]  
where the specific expansion of symbols are shown in the Formula (20).  
\[\left\{\begin{array}{l}\Gamma=I_{x}I_{z}-I_{xz}^{2}\\ \Gamma_{1}=I_{xz}\Big{(}I_{x}-I_{y}+I_{z}\Big{)}/\Gamma\\ \Gamma_{2}=\Big{[}I_{z}\Big{(}I_{z}-I_{y}\Big{)}+I_{xz}^{2}\Big{]}/\Gamma\\ \Gamma_{3}=I_{z}/\Gamma\\ \Gamma_{4}=I_{xz}/\Gamma\\ \Gamma_{5}=I_{x}\Big{(}I_{x}-I_{y}\Big{)}+I_{xz}^{2}\\ \Gamma_{6}=I_{x}/\Gamma\\ Y=\frac{\partial\Omega S}{2V}\Big{(}C_{\eta}p+C_{\gamma}r\Big{)}+\overline{q}S \Big{(}C_{\eta}\beta+C_{\gamma\gamma},r\Big{)}\\ l=\frac{\partial^{2}S^{2}}{2V}\Big{(}C_{\eta}p+C_{\gamma}r\Big{)}+\overline{q}bS \Big{(}C_{\eta}\beta+C_{\delta\gamma},\delta_{r}\Big{)}\\ n=\frac{\partial^{2}S}{2V}\Big{(}C_{\eta}p+C_{\mu r}r\Big{)}+\overline{q}bS \Big{(}C_{\eta\beta}+C_{n\delta},\delta_{r}\Big{)}\end{array}\right. \tag{20}\]  
where \(I_{x}\), \(I_{y}\), \(I_{z}\), and \(I_{xz}\) are the moment of inertia and the product of inertia of the UAV, respectively. The \(u\),\(v\), and \(w\) are the velocity component of flight path under the body axes. The \(p\), \(q\), and \(r\) are the angular rate of the body axes. The \(\varphi\), \(\theta\), and \(\psi\) are angle of roll, pitch, and yaw, respectively. \(Y\), \(l\), \(n\) are lateral force, rolling moment, and yawing moment. The \(\overline{q}\) is dynamic pressure and \(\delta_{r}\) is the angle of rudder deflection.
## 2 Data and Methodology
Note that the radiosonde refractivity (N) can be calculated from the radiosonde temperature (T in K), pressure (P in hPa), and vapor pressure (e in hPa), using the following equation [39; 58]:  
\[\mathrm{N}=77.6\frac{\mathrm{P}}{\mathrm{T}}+3.73\times 10^{5}\frac{\mathrm{e}}{ \mathrm{T}^{2}} \tag{1}\]  
The matching method of [PERSON] et al. [4] is adopted in this study. Radiosonde measurements within 2 h and 300 km of COSMIC RO soundings are compared to those from the COSMIC satellites between 2014 and 2015. If no matching COSMIC profile is available, the radiosonde sounding is not used. If more than one matching COSMIC profile exists, then the COSMIC profile with lowest perigee point closest to the radiosonde station is used. Because the radiosonde data have a higher vertical resolution than COSMIC wetPrf profiles, we interpolate the radiosonde profiles to the vertical levels of the COSMIC wetPrf profiles. The biases and root mean square errors (RMSEs) between the COSMIC wetPrf profiles and the radiosonde measurements of each parameter (e.g., temperature, pressure, vapor pressure, and analyzed refractivity) are calculated. As this study is also to access the regional differences of the discrepancies between COSMIC and radiosonde measurements over China, it is better to calculate the biases and RMSEs between COSMIC and radiosonde profiles in vertical means from 0 to 40 km.
# Determination of the Waterway Parameters as a Component of Safety Management System
## 2 Related Works  
There has been significant progress within the last decades in the development of safety management and decision support systems [5; 6]. In the 1980s, deterministic methods of designing the parameters of sea waterways were still dominant [7]; in the 1990s and the first decade of the 21 st century, there was a development of probabilistic methods with the use of simulation tests [8]. The vessel technical error (UTE) was introduced by IMO in 2001 [9] and used in research [10]. The systematic approach to the waterway design has begun to be introduced nowadays [3] and was applied during the INSMS \"NEPTUN\" application development presented in this paper.  
In terms of marine traffic engineering (MTE), the sea waterway is a restricted area of water adapted and used for the ship traffic of various vessel types. MTE deals with the qualitative and quantitative analyses of this traffic in areas limited in terms of navigation safety. The MTE system is in a safe state if it allows the accident-free passage of the ship in accordance with her route plan while maintaining the required traffic parameters, i.e., the safety level of the MTE system is related to the probability of accident-free passage of the ship or to the accident risk (probability of a ship accident in the domains of time and space and its consequences). A Quantitative Risk Assessment (QRA), as a formal and systematic risk analysis approach to estimating the likelihood and consequences of hazardous events and expressing the results quantitatively as a risk, was introduced to MTE in the 1990s [11]. Nowadays, it has become the marine engineering standard introduced by DNV [1] and others [12; 13]. Its full introduction into the fairway operation on a daily basis has not been  
Figure 1: INSMS “NEPTUN” application flowchart.  
implemented yet [2]. The numerical basics of the final QRA in the application developed by the authors have been adopted from the Polish method [3] used for calculating the safe widths of fairways, which evolved from a number of empirical deterministic methods, like: PIANC [14], Spanish [15], Japanese [2], USACE [16], and Canadian [17], after the supplementation of probabilistic/statistical terms and the validation of used models by simulation studies in a full mission bridge simulator.  
It is worth mentioning the wider aspect of a waterway system's safety. The authors that presented the research focused on the waterway parameters, type of the vessel, and their size i.e., length, breadth, and draft. The propulsion system was not taken into account, but it is of great importance in the context of the manoeuvrability of the vessel--in particular, modifications affecting the vessel's behaviour in shallow waters [18; 19; 20]. The same aspect concerns the shape of the hull [21]. Moreover, taking into account the technological development, one cannot forget about the research on remote piloting while approaching the port via an intelligent fairway [22], as well as the current impact of the hydrometeorological conditions on the ship's behaviour on the fairway [23].
## 5 Experimental Analysis
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{4}{c}{**Average Value of the Function \(F\)**} & \multicolumn{4}{c}{**Number of the Best Solutions**} & \multicolumn{2}{c}{**CPU**} \\ \hline  & **Swap** & **Ins.** & **Swap All** & **Ins. All** & **Adj. Swap** & **Swap** & **Ins.** & **Swap All** & **Ins. All** & **Adj. Swap** & **Time [s]** \\ \hline FS, 1 st run & 76.19 & 76.13 & 76.17 & 76.02 & 75.91 & 0 & 0 & 0 & 0 & 0 & 0.05 \\ FS, 2 nd run & 76.18 & 76.11 & 76.18 & 76.01 & 75.98 & 0 & 0 & 0 & 0 & 0 & 0.05 \\ \hline RS, 1 st run & 77.38 & 77.33 & 77.38 & 77.32 & 77.17 & 328 & 319 & 324 & 302 & 275 & 0.80 \\ RS, 2 nd run & 77.38 & 77.32 & 77.37 & 77.30 & 77.16 & 329 & 306 & 322 & 299 & 270 & 0.81 \\ \hline SH, 1 st run & 77.25 & 77.16 & 77.21 & 77.08 & 76.99 & 55 & 48 & 51 & 46 & 39 & 4.46 \\ SH, 2 nd run & 77.23 & 77.15 & 77.22 & 77.07 & 77.01 & 50 & 49 & 53 & 44 & 40 & 4.45 \\ \hline RJ, 1 st run & 77.50 & 77.43 & 77.49 & 77.36 & 77.29 & 275 & 255 & 271 & 234 & 223 & 0.17 \\ RJ, 2 nd run & 77.48 & 77.44 & 77.46 & 77.37 & 77.29 & 266 & 255 & 263 & 243 & 218 & 0.17 \\ \hline TJ, 1 st run & 77.58 & 77.55 & 77.58 & 77.52 & 77.46 & 315 & 299 & 301 & 277 & 258 & 0.45 \\ TJ, 2 nd run & 77.57 & 77.55 & 77.58 & 77.49 & 77.48 & 309 & 293 & 305 & 273 & 259 & 0.45 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Results of the experiments—30 projects. mean value of \(F\), but often generates schedules with the highest value of \(F\). The least efficient and most costly in terms of calculation is the activity right-shift procedure. For projects from J30 set, the best solutions are generated using Swap or Swap all moves, while for J90, the most effective is Insert move. The worst results are achieved for the Adjacent swap move.
## 4 Conclusions  
The co-digestion of OFMSW together with DSS could create synergy effects such as achieving required DM contents necessary for the operation of wet digestion systems. In addition to its role as inoculum, the inherent CH\({}_{4}\) potential of the DSS would be better exploited. In Germany and worldwide, the mesophilic process temperatures are most commonly used. Therefore, lowered process temperatures could positively influence biogas plants worldwide through reduced operating costs. The results were achieved with OFMSW and DSS but could also be relevant for AD of energy crops together with manure. However, lowered process temperatures could be problematic for biogas plants using substrates that need hygienic treatment such as OFMSW. A separate sanitation unit could become necessary leading to investment and operating costs. According to the German Biowaste Ordinance, only the treatment of OFMSW in AD at thermophilic temperatures fulfills the hygienic requirements, which is why biogas plants operated at mesophilic conditions are already equipped with a separate sanitation unit. From a legal perspective, lowered process temperatures are mainly relevant for biogas plants with separate sanitation units (e.g., mesophilic biogas plants using OFMSW) and for biogas plants operating at mesophilic temperatures without using critical feedstock such as energy-crop-based biogas plants.  
Further experiments with thermophilic temperature levels, other AD substrates, and different AD systems should be carried out in order to validate the results of this study. In addition, detailed modeling and simulation of different biogas plants and their operation at lowered temperatures should be conducted, focusing on heat balance, energy output, and AD process parameters such as HRT, organic loading rate, or digester volumes.  
Conceptualization, G.S. and S.P.; methodology, G.S., J.P., H.O., and J.E.; validation, G.S., M.S., J.E., J.P., and J.M.; formal analysis, G.S.; investigation, G.S., M.S., and J.E.; writing--original draft preparation, G.S.; writing--review and editing, G.S. and J.M.; visualization, G.S. and J.M.; supervision, S.P., H.O., and J.M.; project administration, S.P.; funding acquisition, S.P. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the project ENsource, which was supported by the Ministry of Science, Research, and the Arts of the State of Baden-Wuerttemberg (Germany), and the European Regional Development Fund (ERDF 2014-2020). Support code: FEIH_ZAFH_562822, FEIH_ZAFH_1248932.  
Not applicable.  
The data presented in this study are available on request from the corresponding author.  
The authors would like to thank [PERSON] for language editing.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
# Cellular-V2X Communications for Platooning: Design and Evaluation
## 6 Performance Evaluation
### Results
#### 6.4.2 PM-to-PM Phase
In some repetitions, multiple PMs (belonging to either the same or different platoons) transmit at the same time, hence the number of allocated RBs in one TTI is large. This causes the PMs to report smaller values of wideband CQIs, which in turn imply even more allocated RBs. Thus, there is a positive feedback that rapidly brings the network in saturation. In other runs, transmissions from PMs are more separated in time and the utilization of per-TTI bandwidth stays smaller. In this case, the positive feedback described above is not triggered and the network does not saturate. Figure 8: Metrics evaluated with and without CQI reporting, simultaneous transmissions (\(L=10\)). **(a)** Average allocated RBs per TTI; **(b)** Ratio of successfully completed CAM cycles; **(c)** Average completion time of one CAM cycle. **Impact of frequency reuse**. Finally, we assess the benefit of reusing frequency resources among PM-to-PM transmissions. As anticipated in Section 4.2, a feature envisaged for V2V (and more generally D2D) communications is to allow two or more transmissions to share the same bandwidth if their mutual interference is low. To this aim, we use the allocation scheme proposed in [31], where we assume that the eNodeB is able to build a graph, whose vertices represent the communication links between PMs and an edge exists between vertices if the mutual interference when they use the same RBs is above a configurable threshold. In the following, we refer to the latter as _conflict threshold_. When allocating resources, the eNodeB avoids to grant the same RBs to PM-to-PM communications that are connected by an edge in the graph. Since the tuning of the conflict threshold affects the construction of the graph (hence, the scheduling), we compare the scheme with no reuse against two scenarios where the conflict threshold is set to \(-75\) and \(-90\) dBm, respectively. In these simulations, CQI reporting by the PMs to the eNodeB is enabled, which is shown to be efficient and effective, before reaching saturation of resources. The average allocated RBs per TTI are reported in Figure 9a. As expected, frequency reuse allows the eNodeB to save resources, which can be exploited to serve a larger number of VUEs. In fact, the eNodeB is now able to support also 28 platoons using 60% of the bandwidth on average. Note that the larger conflict threshold gives a reduction of the number of allocated RBs, which becomes more remarkable as the number of platoons increases, at the cost of slightly lower reliability, as shown in Figure 9b, which reports the ratio of successfully completed cycles for platoons composed of nine PMs. The benefits of frequency reuse are also evident in terms of the average completion time, which stays well below the considered CAM cycle period \(T\) (Figure 9c), even when considering a higher number of platoons. Figure 9: _Cont._
## 4 Experiments and Results
### Acoustic Data-Driven Subword Units
Finally, the DB index is obtained by calculating the average ratio of separation measure and the scatter measure for all \(N\) clusters. Table 2 shows the results of measuring the DB index by increasing the number of clusters from 40 to 160 (the lower the better). As a result, the best performance of the DB index is 2.65 when using 120 clusters (\(k=120\)). Next, we extracted the Gra-MFCC-Tree-120 units of Table 1(d), mimicking the method proposed in a previous study [11]. First, we trained the CD grapheme-based HMM/GMM systems to derive the phoneme-like units. Then, the phoneme-like units were derived through likelihood-based decision tree-based clustering by using a single HMM state and 39-dimensional Mel-frequency cepstral coefficient (MFCC) feature vectors (\(c_{0:12}\) + first derivative + second derivative) per frame. Here, the previous study differs from our method in that the previous study's statistical table for building the decision tree was generated with the acoustic features obtained from each frame. Our method generates the statistical table using segment-level fixed-length vectors unlike the previous method [11] that used frame-level feature vectors. We next build the Pho-MFCC-Tree-120 units in Table 1(e). We aim to build subword units suitable for spontaneous speech from phoneme units. On the other hand, the previous study aimed to build phoneme-like units from grapheme units. We can simply build a subword unit by using the CD \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**\#Clusters** & **40** & **80** & **120** & **160** \\ \hline DB index & 2.68 & 2.67 & **2.65** & 2.67 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of the DB index according to the number of clusters. phoneme units instead of the CD grapheme units used in the previous study [11]. The decision tree clustering method, used to build these new units, may be slightly different from the method used in the previous study [11]. Note that the proposed method automatically generates questions by top-down binary data clustering, which means that it is not necessary to supply hand-generated questions, unlike in previous studies [11]. Finally, we build the Pho-LTV-Tree-120 units of Table 1(f) by using the method proposed in Section 3. The proposed unit is obtained by using the fixed-length vector extraction method in a previous study [9] and the decision tree-based clustering method also used in a previous study [11]. As a result, we upgraded k-means clustering (applied to the unit extension method used in the previous study [9]) to decision tree-based clustering.
## 3 Results and Discussion
### Impact of Landscape Positions on Vegetation Phenology  
Vegetation phenology was compared in adjacent pastures with different landscape positions (Figure 6). The EVI values were similar in a wet year 2013 in both pastures. Pasture 15 (lowest toe and lowland) was burned in 2012 and P16 (upper riser and toe) was burned in 2011. The unburned P16 greened-up as early as the burned P15 in 2012 due to warm temperatures combined with well-distributed precipitation during spring. Alternatively, burning did not induce early green-up in P16 during 2011, despite application of a prescribed burn. In 2011, both pastures greened-up around the same time and P15 (unburned pasture) had higher EVI values throughout the entire growing season, most likely because of greater availability of soil water due to differences in landscape position and burning treatment. Pasture 15 is mostly lowland along a stream and P16 has an intermediate landscape position with upper riser to upper toe. Thus, P15 was likely the recipient of overland flow of any runoff that occurred, and lateral flow through the soil profile from areas with higher elevation.  
Figure 6: Seasonal dynamics of the enhanced vegetation index (EVI) for three selected years (dry years 2011 and 2012, and wet year 2013) in adjacent pastures located at different landscape positions. Pasture 15 (lowland along stream) was burned in 2012 and Pasture 16 (upper rise to toe) was burned in 2011.
# Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review
## 2 The Definition of Digital Twins
### Definition of Digital Twins--What Does Digital Twins Term Stand For?
This type of DT which retrieves real-time data from the systems used for reporting operational data within an organization, as mentioned earlier, is referred to as a Strategic DT (SDT), in contrast to the industrial DT that gathers information from sensors, serving as a knowledge visualization tool that allows managers to explore various strategies while minimizing space and time constraints. By simulating different strategic options through computer models, managers can gain insights into the potential outcomes of their chosen approaches in the real world.