esa-sceva/satcom-chunk-collection huggingface dataset:
## 5 Conclusions and Future Directions  
Agricultural practices such as soil aeration can end up having a great impact on the microbial bioavailability of soil-applied herbicides such as metolachlor, and the findings of this study provided clear evidence for enhanced bioavailability and microbial biodegradation of metolachlor in the anaerobic soil systems. The respective Freundlich adsorption coefficients for anaerobic and aerobic soil conditions indicate that the adsorption of metolachlor in the soils was noticeably reduced under anaerobic conditions. Similarly, relatively low Freundlich desorption constants for metolachlor in the anaerobic soils, irrespective of their varying soil properties, suggest a greater release of adsorbed herbicide from the anaerobic soils. To the best of our knowledge, the current study is among the first attempts to evaluate the impacts of soil aeration on the binding and retention of metolachlor in soils from the upper midwestern United States that have been under corn-soybean crop rotations. Anaerobic soil incubations induced better degradation and mineralization of metolachlor in the range of soils evaluated, despite differences in the soil properties. Among the various soil types used in the experiment, Drummer soil with the highest organic matter content exhibited the highest rate of degradation and mineralization for metolachlor both under aerobic and anaerobic soil conditions. The non-sterilized soil microcosms showed substantial degradation and mineralization of metolachlor compared with the corresponding sterilized control microcosms despite the incubation conditions. These facts accentuate the major role of microbial activities in the degradation and metabolism of metolachlor within the soil profile, despite variances in the soil properties and aerobic conditions. These distinctive differences in the degradation and mineralization kinetics of metolachlor in aerobic and anaerobic soil environments suggest the need for a thorough investigation of microbial involvement in the fate of the herbicide when the soil undergoes changes in its redox status.  
Conceptualization, R.K. and G.S.; methodology, R.K.; investigation, R.K.; resources, G.S.; writing--original draft preparation, R.K.; writing--review and editing, G.S., R.T. and W.L.; supervision, G.S.; project administration, G.S.; funding acquisition, G.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data Availability Statement: The data presented in this study are available on request from the corresponding author.
# Research on Response Postures of Subway Train in Straight Line Collision
## 3 Straight-Line Collision Condition Setting
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Working Condition** & \
\begin{tabular}{c} **Impact** \\ **Velocity/(kmin)** \\ \end{tabular} & **Impact Angle/(\({}^{\circ}\))** & **Impact Position** & \multicolumn{3}{c}{**Response Postures**} \\ \cline{1-7}  & TR-V45-A0-Z & & & & **Carriage-1** & **Carriage-2** & **Carriage-3** \\ \hline  & TR-V45-A0-C1 & & & & Frontal collision & Carriage overturn & Carriage overturn & Carriage overturn \\  & TR-V45-A0-C1 & & & & Front-side collision C1 & & Lateral buckling & \\  & TR-V45-A0-C2 & & & & & & & \\  & TR-V45-A0-C3 & & & & & & & \\  & TR-V45-A0-C3 & & & & & & & \\  & TR-V45-A5 & & & & & & & \\  & TR-V45-A5 & & 5 & / & LLMF & Lateral buckling, Carriage overturn & \\ Collision with a & TR-V45-A5 & & 10 & / & LLMF & Lateral buckling, Carriage overturn & \\ rigid wall & TR-V45-A15 & & 15 & / & LLMF, Carriage & & \\  & TR-V45-A20 & & & & & & \\  & TR-V45-A30 & & 30 & / & LLMF, Carriage & & \\  & TR-V45-A45 & & 45 & / & LLMF, Carriage & & \\  & TR-V45-A6 & & & & & & \\  & TR-V45-A6 & & & & & & \\  & TR-V45-A7 & & & & & & \\ \hline  & TT-V25-A0-Z & & 0 & Frontal collision & / & / & / \\  & TT-V25-A5 & & 5 & / & / & / & / \\  & TT-V25-A10 & & 10 & / & / & / & \\  & TT-V25-A15 & 25 & 15 & / & / & & \\  & & & & & & & \\ Train-train collision & TT-V25-A30 & & 30 & / & / & D Deralment &
\begin{tabular}{c} D \\ **performary** \\ **deralment** \\ \end{tabular} \\ \cline{2-7}  & TT-V36-A0-Z & 36 & 0 & Frontal collision & & & & \\  & & & & & & \\ \hline TT-V45-A0-Z & 45 & 0 & Frontal collision & & & \\  & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Cont. For straight-line collision between two identical trains, the standard EN 15227: In 2020 Railway Applications-Crashworthiness requirements for railway vehicles (hereinafter referred to as EN 15227) [30], the collision condition set for C-II railway vehicles is as follows: A subway train with an initial speed of 25 km/h collides with another stationary subway train of the same type. The physical quantities used to evaluate crashworthiness include: impact force and wheel-rail relative vertical displacement. The energy absorption value of each part is extracted to evaluate the deformation or damage of the train. Therefore, this paper carried out the parameter analysis under seven working conditions of no angle impact at different speeds and oblique impact with angle at 25 km/h. For straight-line collision between train and obstacle, 30 working conditions were conducted with variables such as impact speed, impact angle and impact position to obtain a variety of response postures. The causes for the response postures were analyzed according to the data such as pitching and yawing, plastic deformation of the carriage, relative displacement of the wheel and rail, and the force between the wheel and rail.
# Information-Aware Secure Routing in Wireless Sensor Networks
## 7 Conclusions  
In this work, we investigated the secure routing problem for WSNs in the presence of malicious nodes. First, we established a network model for multi-hop communications between sensor nodes and the sink node in the presence of malicious nodes in WSNs. The model describes the behaviors of sensor nodes in WSNs. Second, a method for calculating trust between adjacent nodes was determined as the basis for the route selection. The attack probability of the node is used as the metric for the trust of the node, and it depends on the past behaviors of the node. The attack probability of a path is calculated on the basis of the attack probability of each node in the path and the serial-parallel system in reliability theory. Third, we developed a secure routing model based on information-aware sensor nodes in WSNs. The cost function is based on the node information (attack probability of the K-hop path, the status of each node in the path). The sensor node chooses a path with the least cost required to relay the packet to the sink node. Fourth, an improved version of the Dijkstra algorithm was designed to make it more suitable for our model. Finally, we conducted extensive simulations to verify the validity of our model and algorithm.  
In the proposed model, the nodes that are closer to the sink node are chosen as relay nodes to save energy and reduce transmission delay. However, the transmission delay of each path is not specifically quantified, and the upper limit of the delay is not set. In the future, we will consider transmission delay as a factor for path selection to make the secure routing model more realistic.  
Conceptualization, Q.S., L.Q. and L.S.; methodology, Q.S., L.Q. and B.X.; validation, Q.S., Y.D. and J.Z.; investigation, Q.S.; data curation, Q.S., Y.D. and J.Z.; writing--original draft preparation, Q.S.; writing--review and editing, L.S.; supervision, L.Q.; project administration, L.S.; funding acquisition, L.S. 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, grant number 61772478.  
The authors declare no conflict of interest.
## 3 Theoretical Background and Method
### The Algorithm Switching Orthogonalization Procedure (ASOP) Method
The mean and standard variance of Level 0 and Level 1 are listed in Table 1. As we can see, the calculated results of \(Q\) value accord with the visual observation of the eye diagram, and in this situation, we should select the in-phase signal as the initial reference vector.
## 5 Experimental Results
### Global Comparisons of All Tested Structures  
These group of experiments concerned comparisons and evaluations of different structures that executed the same work, i.e., the same set of tasks. For this purpose, another factor--\(SP\), the system productivity--was defined. It is expressed by:  
\[SP=\frac{N_{T}\cdot F_{sys}}{Min_{indistance}} \tag{5}\]  
where \(N_{T}\) is the number of processed tasks.  
Table 3 presents the results for eight different structures with the same productivity, \(SP=150\). Additionally, the power and resource savings are presented in separate diagrams, Figures 12 and 13, respectively. In the latter case, all structures contained the same amount of switching resources (F8 Muxes), which is why they are not presented in the diagram. In both diagrams, the basic STP \(\times\) 30 structure was used as a reference architecture. The results depicted in the first diagram (Figure 12) concern the basic system's processing of up to 30 tasks, showing that the best results were obtained from the simple architecture with a clock-gating mechanism. Quite good results were obtained for pipelined (mulitasking) solutions when properly configured, i.e., when multiple cores with appropriately chosen (reduced) frequencies were used.  
As to Figure 13, describing the resource savings, one can observe that the best results could be achieved for the low number of multitasking cores processing many tasks. However, in such cases, it is usually necessary to increase the frequency, and this entails increasing the power margin. This was due to the fact that, in the case of STP-type architectures, the number of cores had to be increased, while, for MTP structures, the frequency had to be increased in order to meet all hard deadlines. This is also shown in in Figure 14, which presents the absolute values of the average power consumed by a single task in different scenarios. Definitely, the best solution was this scenario: one task per a single core with clock gating (STP CG). However, because of the natural limitations of such a solution, in many cases, multitasking equivalents should be considered.  
Figure 12: The comparison of power savings per task relative to the architecture consisting of single-task cores (STP) for different structures with \(SP=150\).  
Figure 13: The comparison of resources savings relative to the architecture consisting of single-task cores (STP) for different structures with \(SP=150\).
# Complex-Valued Phase Transmittance RBF Neural Networks for Massive MIMO-OFDM Receivers
## 2 Background
### Quasi-Orthogonal Special Case  
In order to increase the spectral efficiency in orthogonal codes, [PERSON] [56] proposed quasi-orthogonal STBC (QOSTBC) of rate one, relaxing the requirement of orthogonality. However, when compared with orthogonal codes, the diversity gain is reduced by a factor of two. Besides, in contrast to orthogonally designed codes that process one symbol at a time at the decoder, quasi-orthogonal codes process pairs of transmitted symbols, which exponentially increases the computational complexity of decoding [11].  
[PERSON] [56] proposed a coding matrix of rate one for \(M_{T}=4\), given by  
\[\mathbf{QOSTBC_{4,4}}=\begin{bmatrix}s[1]&s[2]&s[3]&s[4]\\ -s[2]^{*}&s[1]^{*}&-s[4]^{*}&s[3]^{*}\\ -s[3]^{*}&-s[4]^{*}&s[1]^{*}&s[2]^{*}\\ s[4]&-s[3]&-s[2]&s[1]\end{bmatrix}. \tag{4}\]  
In the literature, related approaches with a maximum of \(M_{T}=6\) antennas were proposed for quasi-orthogonal codes [57; 58; 59]. In [58], the authors developed an architecture similar to [56]; however, this presents full-diversity at the cost of more processing and is limited to \(M_{T}=4\) antennas. In the same way, by increasing the decoding processing, [PERSON] and [PERSON] [59] proposed two quasi-orthogonal schemes with \(M_{T}=5\) and \(6\) antennas [11].  
Figure 3: MIMO-OFDM model system with channel estimation.
## 3 Proposed Model
### Proposed Mobile-Aware Cluster Head-Election Scored (MACHES) Algorithm  
Using the K-means clustering algorithm in the WSN protocol results in the member nodes in the cluster being as uniform as possible, but it takes longer to cluster than traditional hierarchical algorithms. In addition, CH election has the problem of continuous CH election on the same node, only considering the residual energy of the node or node that is mostly close to the cluster's center point. This results in shortening the lifetime span of the network, and when electing a cluster head while not considering the distance to the node and base station, the overall energy efficiency of the network can be reduced.  
The proposed MACHES algorithm aims to enhance conventional clustering approaches by introducing a sophisticated scoring mechanism that evaluates nodes based on their residual energy, their proximity to the cluster center (CC) and the BS, and their mobility stability. This method ensures that the elected CHs are not only energy rich but also optimally located to minimize overall transmission distances and energy costs.  
Initially, clusters are formed only during setup stage or when significant energy depletion occurs, reducing the need for frequent reconfigurations. For a CH election, each node is evaluated based on three key scoring factors: (i) the mobility score of each node (\(S_{M}\)), the BS score (\(S_{BS}\)), and CC score (\(S_{CC}\)). (ii) These scores assess a node's mobility stability, residual energy relative to its distance from the BS, and the CC, respectively. The mobility score is calculated based on both the node's displacement compared to its maximum possible displacement and a normalized direction change against the maximum direction change. The mobility score is designed to prioritize nodes that are relatively stable (low displacement and minimal direction change) as cluster heads, as high mobility can lead to instability in cluster formation. Nodes with the highest scores are shortlisted as CH candidates. (iii) The final selection considers the total integrated score to ensure that the elected cluster head minimizes energy consumption across the network, thereby (iv) optimizing the overall network performance.  
The protocol operates in two primary phases, (1) initialization and (2) cluster-head election, each designed to optimize the distribution and management of nodes within the network.
# In-Band OSNR Measurement Method for All-Optical Regenerators in Optical Domain
## 2 Principle of the Measurement Method for All-Regenerator
According to the above analysis, the in-band measurement method for the \(OSF\) parameter or the \(OSNR\) output from the all-optical regenerator are described as follows: (1) Firstly, measure the PTF curve of the regenerator and choose the operating point for regeneration. At the same time, the signal gain \(G_{0}\) is also known. (2) Secondly, fix the input average power perfectly matching with the operating point, and adjust the input \(OSNR_{\text{in}}\) by loading different power of ASE noise, in which the total gain \(G\) of the degraded signal can be measured by the optical power meter. (3) Finally, calculate the output \(OSNR\) and the \(OSF\) parameter of the optical regenerator from Equations (2) and (3), respectively. This in-band method is free of complex tests in the electrical domain and the limit of the out-band method in the optical domain.
# Performance Evaluation of Carbon Black Nano-Particle Reinforced Asphalt Mixture
###### Abstract  
Applications of nanotechnology in the pavement industry have increased rapidly during the last decade in order to enhance a pavement's sustainability and durability. Conventional asphalt binder generally does not provide sufficient resistance against rutting at high temperatures. Carbon black nano-particles (CBNPs, produced by perennial mountain trees' carbonization) were mixed into the performance grade (PG) 58 asphalt binder in this study. Conventional asphalt binder tests (penetration, ductility and softening point), frequency sweep, performance grading, and bitumen bond strength tests were conducted to study the enhancement in the properties of asphalt binder. Dynamic modulus and wheel tracking tests were also performed to investigate the effect of CBNPs on asphalt mixture properties. Experimental results demonstrated that preferred dosage of CBNPs in asphalt is 10% by weight of the bitumen. Results of scanning electron microscopy (SEM) and storage stability tests validated homogenous and stable dispersion of CBNPs in the asphalt binder. Asphalt mixtures became stiffer and resistant to rutting at high temperatures by addition of CBNPs in asphalt binder. Significant improvement in bitumen aggregate bond strength was also observed by incorporating CBNPs. It is concluded that CBNPs can be used to effectively enhance the high-temperature performance and consequently the sustainability of flexible pavements.  
carbon black nano-particles (CBNPs); asphalt binder; performance grading; scanning electron microscopy (SEM); dynamic modulus; rutting
## 3 Numerical Calculation Application and Experimental Setup
### Steady State CFD Model Setup
#### 3.2.3 Solution Setup  
Nine flow rates from \(Q_{0.6}\) to \(Q_{1.4}\) at an interval of \(0.1Q_{des}\) were investigated in this work. The fluid media in pump was set as 20 \({}^{\circ}\)C clean water, and its density and viscosity are 998.2 kg m\({}^{-3}\) and 1.003 \(\times\) 10\({}^{-3}\) Pa s, respectively. Second order upwind scheme was applied for discretion of the momentum equation and SIMPLE algorithm was used for the iterative computation. The convergence criterion was less than \(10^{-4}\) for the maximum residual values for the mass and momentums in three directions.  
The case with \(Q_{des}\) flow rate was chosen to run the grid independence test. Calculated results including head and efficiency under six different mesh densities were presented in Figure 6, whose calculation formulas were expressed as Equations (7) and (8).  
\[H=\frac{P_{0}-P_{i}}{\rho g}+\Delta \tag{7}\]  
where \(H\) is pump head, \(P_{i}\) and \(P_{o}\) are the total pressure of the inlet and outlet of the pump respectively, and \(\Delta\) represents the height difference between the center points of inlet and outlet faces.  
\[\eta=\frac{955\rho gQH}{nT} \tag{8}\]  
where \(Q\) is volume flow (m\({}^{3}\)/h), \(n\) is the shaft's rotational speed (rev\(\cdot\)min\({}^{-1}\)) and \(T\) denotes the torque on the main shaft (N m).  
Figure 6 shows that both head and efficiency of the pump began to keep stable when the number of girds exceeds \(3.70\times 10^{6}\). And the fluctuation ranges of head and efficiency can be controlled within 0.7% and 0.5%, respectively. Therefore, the grid with number of \(3.70\times 10^{6}\) was chosen for further computation. Numbers of element and node of each sub-domain were listed in Table 3, and the element quality, skewness factor, and orthogonal quality of the entire gird were 0.79, 0.35, and 0.86, respectively.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline
**Parameter** & \(\mathbf{\alpha_{1}}\) & \(\mathbf{\beta}\) & \(\mathbf{\beta^{\prime}}\) & \(\mathbf{\sigma_{k1}}\) & \(\mathbf{\sigma_{\omega 1}}\) & \(\mathbf{\alpha_{2}}\) & \(\mathbf{\beta_{2}}\) & \(\mathbf{\sigma_{k2}}\) & \(\mathbf{\sigma_{\omega 2}}\) \\ \hline Value & 0.556 & 0.075 & 0.09 & 0.85 & 0.5 & 0.44 & 0.828 & 1 & 0.856 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Parameter settings of the SST \(k\)-\(\omega\) turbulence model.
## 1 Introduction
### DL Application in Quality Control of AM
#### 1.3.1 DL Definition  
Artificial Neural Networks (ANN) are a type of Machine Learning (ML) technique that is modeled and inspired by the brain [66]. These networks mimic the learning process through a technique called back-propagation that optimizes weights in the network [67]. DL networks are an advanced version of ANN and rely on a feedforward network to approximate some function \(f^{*}\)[68]. DL networks get their name from having a chain of functions which are algorithmically deeper than the standard ANN with a connected final layer called the output layer [68]. In essence, DL networks are very large versions of ANN.  
DL has become popular in part due to advancements in computational power and the addition of advanced activation functions [69; 70; 71]. One such activation function is called Rectified Linear Unit or ReLU. The ReLU function is mathematically represented as:  
\[a_{i,j,k}=max(z_{i,j,k},0) \tag{1}\]  
where, \(z_{i,j,k}\) is the input of the activation function located at \((i,j)\). A particular type of DL that has successfully been employed for classification experiments is Convolutional Neural Networks (CNN). CNNs are used for a variety of applications including time-series (1D grid) and imagery (2D grid) [68]. In this investigation, we treat the data as a time-series and utilize it for a 1D CNN algorithm. Other activation functions include the hyperbolic tangent (tanh) and sigmoid functions, the sigmoid is used in the CNN modelduring this investigation for the dense layer. The tanh and sigmoid functions are defined in Equations (2) and (3) (respectively) as [72]:  
\[tanh(x)=\frac{sinh(x)}{cosh(x)}\rightarrow\frac{e^{x}-e^{-x}}{e^{x}+e^{-x}} \tag{2}\]  
\[g(x)=\frac{1}{1+e^{-x}} \tag{3}\]  
One advantage to the tanh function is that its range outputs between \(-1\) and \(1\) for real values of the input \(x\)[72]. The main advantage of the tanh function compared to the sigmoid function is that the hyperbolic has a steeper derivative however, neither of these functions work well with deeper networks for convolution [73]. The sigmoid function is commonly used in the last or 'fully connected' layer in classification problems because it outputs 0 or 1.
# The Emerging Energy Internet: Architecture, Benefits, Challenges, and Future Prospects
## 6 Future Prospects for Energy Internet  
Various future prospects of EI are detailed henceforth.  
1. The heart of EI is ER. In order to have an interoperable and standardized communication framework for ER, the following challenges are to be addressed: * A standardized information model that addresses the interoperability needs of the power system devices must be developed for ER. Recently, in the literature [70], the authors developed an IEC 61850 standard-based ER model. Building on this work, more analysis on the performance of communication-based ER can be carried out. * A performance evaluation of the developed information model of ER for different communication technologies, such as LAN, WiFi, and WiMax.  
2 Power optimization with the help of ER can be explored. This can be achieved by optimizing the energy and information flow path in order to achieve the desired optimal results.
3 Energy management solution in microgrids can be achieved with effective coordination among ERs. For this purpose, the IEDs of all of the power devices need to be equipped with standard firmware that accommodates suitable EMS data functions.
4 As the core concept of EI integrates the Internet with the energy transactions, a robust security mechanism is extensively required.