esa-sceva/satcom-chunk-collection huggingface dataset:
# Exploring the Impact of Multitemporal DEM Data on the Susceptibility Mapping of Landslides
## 3 Methodology
### Ratio of Number of Landslides to Area (RNA)  
RNA denotes the ratio of the number of historical landslide events to the area of the susceptibility levels at which historical landslide events are located. The RNA of the level \(i\) is obtained with the following equation:  
\[RNA_{i}=n_{i}/A_{i} \tag{3}\]  
where \(RNA_{i}\) is the number of landslides per area at a particular level \(i\); \(n_{i}\) is the number of historical landslide events at level \(i\); and \(A_{i}\) is the area of level \(i\) in the assessment.
## 1 Introduction
Therefore, traditional optimization approaches (e.g., exhaustive search) are infeasible for real-time optimization. The large number of IRS elements in an IRS-aided D2D framework require real-time optimization schemes with low complexity. Fortunately, reinforcement learning (RL), a subset of machine learning (ML), is very effective for controlling relevant policies and supporting intelligent decisions under uncertain and dynamic environments [11]. Q-learning, deep Q-learning, actor-critic framework, and other RL approaches have been enormously adopted for resource management in wireless networks [12; 13; 14; 15]. Therefore, we propose an RL-based scheme to solve the optimization problem of the IRS-assisted D2D underlay cellular network.
## 3 RPM Path Planning Method Based on Probabilistic Roadmap and Heuristic Rule
### NLP Problem Solving and Initial Value Generation
#### 3.2.2 Path Pruning Heuristic Rule with Reverse Search  
In Section 3.2.1 we obtained a passable path using the PRM, but the computed passable path usually has more redundant points and more turning points. In fact, the quality of this path is still not high enough, and directly using it as the initial solution to the NLP problem may increase the computational effort or even affect the generation of optimal or sub-optimal paths. To optimize this problem, this paper proposes path pruning heuristic rules with a reverse search to reduce the number of redundant points in the path to improve the quality of the planned path, as shown in Figure 4.
# Oscillation Suppression Method of Digital Proportional Valve Based on Fuzzy Intelligent PID Control
## 2 Mathematical Model of Proportional Valve with HSVB as Pilot Section  
### Structure and Working Principle  
Figure 1 shows the structure and working principle of the DPV with HSVB as the pilot valve.  
The valve mainly includes a controller, a pilot valve bridge composed of four HSV, which include two normally closed valves (NC\({}_{1}\) and NC\({}_{4}\)) and two normally open valves (NO\({}_{2}\) and NO\({}_{3}\)), and a main valve. The controller outputs four PWM signals with different duty cycles that adjust the on/off time and frequency of four HSVs and control the flow and pressure in the left and right chambers, and then, control the movement of the main spool. The spool displacement sensor is used to detect and feedback the displacement of the main spool in real time to form a closed-loop control, so as to accurately control the flow rate through the main valve.  
Figure 1: Schematic and working principle of the DPV.
# Multi-Attribute Collaborative Optimization for Multimodal Transportation Based on User Preferences
###### Abstract  
Given the differing interests and demands of various participants in multimodal transportation, this paper proposes a multi-attribute decision-making method driven by user preferences. Firstly, a four-dimensional optimization model is established with the objectives of minimizing transportation costs, transportation time, carbon emissions, and transportation risks. Furthermore, considering the practical aspects of transportation, differentiated time window constraints are designed based on the continuous time windows of highway transportation, railway train schedules, and the arrival and departure time characteristics of waterway vessels. In terms of solution methods, an improved Genetic Algorithm (GA) and Aptenodytes Forsteri Optimization (AFO) hybrid algorithm (GA-AFO) is proposed, which introduces GA to generate a high-quality initial population to accelerate convergence. By replacing the traditional gradient estimation strategy with a random mutation strategy based on probability distribution, the local search mechanism of AFO is enhanced. Furthermore, in response to the aforementioned multi-objective problem, a multi-attribute decision-making method is devised to reconcile the subjective preferences of decision makers with objective weights, thereby yielding more scientifically valid decision outcomes. Numerical experiments have shown that the designed hybrid algorithm can quickly find solutions and demonstrates good robustness. The proposed multi-attribute decision-making method is able to generate decision schemes tailored to the preferences of different decision makers, thus providing a scientific basis for the formulation of personalized transportation schemes.  
Keywords:transportation planning; multimodal transportation; user preferences; GA; AFO Article
## 2 Materials and Methods
### Experiment Specifications
#### 2.3.2 Simulation Parameters  
We took data from the first four days for training our SFC Deployment agent and used the last day's trace for evaluation purposes. Given a fixed simulation time-step interval of 15 seconds and a fixed number of \(N^{e}=80\) time-steps per episode, we trained our agent for 576 episodes, which correspond to 2 runs of the 4-day training trace. At any moment, the vCDN conditions are composed by the VNF instantiation states, the caching VNF memory states, the container resource provision, utilization, etc. In the test phase of every algorithm, we should fix the initial network conditions to reduce evaluation bias. However, setting the initial network conditions like those encountered at the end of its training cycle might also bias the evaluation of any DRL agent. We want to evaluate every agent's capacity to recover the steady state from general environment conditions. Such an evaluation needs initial conditions to be different with respect to the steady-state achieved during training. In every experiment we did, we set the initial vCDN conditions as those registered at the end of the fourth day when considering a greedy SFC deployment policy.  
We fix the QoS, Hosting costs, and DT-cost weight parameters in (16) to 0.6, 0.3, and 0.1, respectively.  
In the context of this research, we did not have access to any information related to the data-transmission delays. Thus, for our experimentation, we have randomly generated fixed data-transmission delays considering the following realistic assumptions. We assume that the delay between a content provider and a hosting node is generally bigger concerning the delay between any two hosting nodes. We also assumed that the delay between two hosting nodes is usually bigger than between hosting and client-cluster nodes. Consequently, in our experiment, delays between CP nodes and hosting nodes were generated uniformly in the interval 120-700 [ms], delays between hosting nodes, from the interval 20-250 [ms], the delays between hosting nodes and client clusters were randomly sampled from the interval 8-80 [ms]. Also, the unitary data-transportation costs were randomly generated for resembling a multi-cloud deployment scenario. For links between CP nodes and hosting nodes, we assume that unitary DT costs range between 0.088 and 0.1 USD per GB ([[https://cloud.google.com/cdn/pricing](https://cloud.google.com/cdn/pricing)]([https://cloud.google.com/cdn/pricing](https://cloud.google.com/cdn/pricing)) (accessed on 26 October 2021)). For links between hosting nodes, the unit DT costs were randomly generated between 0.08 and 0.004 USD per GB, while DT Cost between hosting nodes and client cluster nodes is assumed null.  
The rest of the simulation parameters are given in Appendix A.3.
## 2 Definition and Methods of Analysis
### TRP Testing Methods  
In practical tests, the discrete sampling method is usually used to approximate the continuous integral to the discrete summation. It is assumed that the measurement points are selected on a rectilinear grid with a constant sampling step. As shown in Figure 2, the discrete summation in the full spherical grid method can be expressed as  
\[\text{TRP}_{\text{grid}}\approx\frac{\Delta\theta\Delta\phi}{4\pi}\sum_{m,n} \text{EIRP}(\theta,\phi)\text{sin}\,\theta \tag{5}\]  
where \(\Delta\theta\) and \(\Delta\phi\) are the sampling steps for the elevation and azimuth angle, respectively. For each emission frequency, the EIRP (as a sum of two orthogonal polarizations) is measured at each spatial sampling step on the selected grid.  
The TRP testing of spurious emissions can be carried out using a simpler approach, that is, the two-cut method or the three-cut method. As shown in Figure 3, the two-cut method requires the DUT to be aligned with a chosen xy-plane (blue) and xz-plane (red) of the antenna measurement coordinate system. For an orthogonal-cut grid,  
\[\text{TRP}_{\text{two-cut}}=\frac{1}{2}\Big{(}\overline{\text{EIRP}(\theta, \phi)}_{1}+\overline{\text{EIRP}(\theta,\phi)}_{2}\Big{)} \tag{6}\]  
where \(\text{EIRP}(\theta,\phi)_{n}\) for \(n=1,2\) is the EIRP (as a sum of two orthogonal polarizations) in each cut, i.e., the xy-plane and xz-plane. The bar denotes the average angular value calculated for each cut. When calculating orthogonal cuts, the intersections are calculated multiple times, and duplicate values can be removed from the sample before averaging.  
Figure 1: Spherical coordinates and DUT dimensions.  
Figure 2: Schematic diagram of a full spherical grid with fixed steps. Suppose that the sampling radius is 1 m.  
The beam peak should be required to align the orthogonal cuts that are beamformed, as identified in the exploratory scan for harmonics and spurious emission frequencies. If the TRP limit is exceeded, a third orthogonal cut in the yz-plane (yellow) can be added by using the \(\Delta\theta\) angular step. Therefore, the average values are separately calculated in all three cuts, and then the average value of these three average values is taken.  
\[\mathrm{TRP}_{\mathrm{three-cut}}=\frac{1}{3}\Big{(}\overline{\mathrm{EIRP}( \theta,\phi)_{1}}+\overline{\mathrm{EIRP}(\theta,\phi)_{2}}+\overline{ \mathrm{EIRP}(\theta,\phi)_{3}}\Big{)} \tag{7}\]
# Research Progress and Future Prospects of Key Technologies for Dryland Transplanters
## 2 Classification of Transplanters
### Semi-Automatic Transplanter
#### 2.2.3 Guide-Tube Semi-Automatic Transplanter  
During operation of the guide-tube transplanter, operators manually remove plug seedlings from trays and place them into the feed hopper of the seedling feeder. As the feed nozzle rotates to the inlet of the guide tube, it opens, allowing seedlings to enter the tube by gravity. Guided by the tube, seedlings fall into the planting furrow, where a soil covering wheel then covers and compacts the soil to complete transplantation.  
[PERSON] et al. [68] designed a semi-automatic vegetable transplanter where operators manually place seedlings into a distributor. As the distributor moves seedlings above the seedling guide tube, they are dropped into the tube, then fall into the furrow opened by the furrow opener under gravity and tube guidance. The soil is covered and compacted to complete planting. [PERSON] et al. [69] developed a semi-automatic sugarcane seedling transplanter based on sugarcane agronomy (Figure 7a), consisting of a seedling guide mechanism, blocking mechanism, pushing mechanism, and other components, resulting in a low transplanting success rate. [PERSON] et al. [70] studied a guide-tube tobacco transplanter (Figure 7b) for tobacco transplantation. The operation featured a plant spacing of 500-650 mm, transplanting depth of 80-120 mm, and irrigation volume of 300-500 mL, improving tobacco transplanting quality and enabling large-scale mechanical transplanting.  
Figure 6: Chain-clip semi-automatic transplanter. (**a**) 2 ZL-2 Chain-clamp sweet potato transplanter [37]. (**b**) Semi-automatic chain-clip pineapple seedling transplanter [66].  
Figure 7: Guide-tube semi-automatic transplanter. (**a**) Semi-automatic transplanting machine for sugarcane seedlings [69]. (**b**) Guide-tube-type tobacco transplanter [70].
###### Abstract  
An Actinide Lanthanide Separation Process (ALSEP) for the separation of trivalent actinides (An(III)) from simulated raffinate solution was successfully demonstrated using a 32-stage 1 cm annular centrifugal contactor setup. TheALSEP solvent was composed of a mixture of 2-ethylhexylphosphonic acid mono-2-ethylhexyl1 ester (HEH[EHP]) and _N,N',N'_-tetra-(2-ethylhexyl1)-diglycolamide (T2 EHDGA) in _n_-dodecane. Flowsheet calculations and evaluation of the results were done using the Argonne's Model for Universal Solvent Extraction (AMUSE) code using single-stage distribution data. The co-extraction of Zr(IV) and Pd(II) was prevented using CDTA (_trans_-1,2-diaminocyclohexane-_N,N,N'_-tetraacetic acid) as a masking agent in the feed. For the scrubbing of co-extracted Mo; citrate-buffered acetohydroxamic acid was used. The separation of An(III) from the trivalent lanthanides (Ln(III)) was achieved using citrate-buffered diethylene-triamine-_N,N,N'_,N\"_-_\"_-pentaacetic acid (DTPA), and Ln(III) were efficiently back extracted using _N,N,N'_,N'_-tetraethyl-diglycolamide (TEDGA). A clean An(III) product was obtained with a recovery of 95% americium and curium. The Ln(III) were efficiently stripped; but the Ln(III) product contained 5% of the co-stripped An(III). The carryover of Am and Cm into the Ln(III) product is attributed to too few actinide stripping stages, which was constrained by the number of centrifugal contacts available. Improved separation would be achieved by increasing the number of An strip stages. The heavier lanthanides (Pr, Nd, Sm, Eu, and Gd) and yttrium were mainly routed to the Ln product, whereas the lighter lanthanides (La and Ce) were mostly routed to the raffinate.  
actinide separation; ALSEP; HEH[EHP]; PC88A; T2 EHDGA; TEDGA; AMUSE
# Herbicide Bioassay Using a Multi-Well Plate and Plant Spectral Image Analysis
###### Abstract  
A spectral image analysis has the potential to replace traditional approaches for assessing plant responses to different types of stresses, including herbicides, through non-destructive and high-throughput screening (HTS). Therefore, this study was conducted to develop a rapid bioassay method using a multi-well plate and spectral image analysis for the diagnosis of herbicide activity and modes of action. Crabgrass (_Digitaria cliaris_), as a model weed, was cultivated in multi-well plates and subsequently treated with six herbicides (paraquat, tiafenacil, penosulam, isoxaflutole, glufosinate, and glyphosate) with different modes of action when the crabgrass reached the 1-leaf stage, using only a quarter of the recommended dose. To detect the plant's response to herbicides, plant spectral images were acquired after herbicide treatment using RGB, infrared (IR) thermal, and chlorophyll fluorescence (CF) sensors and analyzed for diagnosing herbicide efficacy and modes of action. A principal component analysis (PCA), using all spectral data, successfully distinguished herbicides and clustered depending on their modes of action. The performed experiments showed that the multi-well plate assay combined with a spectral image analysis can be successfully applied for herbicide bioassays. In addition, the use of spectral image sensors, especially CF images, would facilitate HTS by enabling the rapid observation of herbicide responses at as early as 3 h after herbicide treatment.  
202424919103390/s2403091039  
Moreover, a significant amount of labor and time is necessary to cultivate enough plants to validate the responses. Furthermore, conducting evaluations in the field with a portable device results in delays and inevitable errors in the plant diagnostic procedure. Therefore, it is crucial to create novel bioassay approaches that can provide a compact and simple approach to assess and diagnose plant responses.  
In herbicide discovery and development, a herbicide bioassay is essential for not only detecting and quantifying herbicide efficacy but also diagnosing the herbicide mode of action. A multi-well plate is a widely used tool in cell culture for carrying out large-scale biological investigations [14]. Several studies have exhibited the application of multi-well plates for cultivating plants and assessing their responses to herbicides. Little plants or plant parts, such as leaves, were placed into multi-well plates, and a spectral image analysis was applied to diagnose and evaluate the responses of plants under stress conditions, including herbicides [15; 16; 17]. These studies demonstrate a good synergy between the two methods; however, combining the use of a spectral image analysis has not been previously investigated.  
Therefore, this study was conducted to develop a multi-well plate assay method for herbicide screening. To detect plant responses to herbicides, plant spectral images were acquired after herbicide treatment using RGB, IR thermal, and CF sensors and analyzed for diagnosing herbicide efficacy and mode of action.
## 3 Significance of Ancillary Services in Deregulated Systems  
Ancillary services are those functions performed to support the basic services of generation capacity, energy supply, and power delivery in deregulated power systems [34]. Ancillary services play an important role in sustaining power flow, reducing differences between demand and supply, and facilitating power systems' operation during uncertainties (frequency deviation, voltage variations, imbalances between supply and demand, etc.) [35]. Ancillary services may include black start regulation, synchronized operation, contingency reserves, and flexibility reserves [36]. In deregulated power systems, ancillary services investment becomes essential because, without these services, the power system remains uncertain, unstable, and unreliable [37]. Variable load demands, power quality, and uncertainty of fuel price and penetration of renewable energy require ancillary servicesin power networks [38; 39]. Different types of ancillary services for problems associated with power systems are shown in Table 1.  
One of the most economical and efficient solutions of deregulated power system problems is the injection of FACTS controllers [40]. Transient instability, dynamic instability, oscillations, frequency imbalance, or voltage fluctuations can be eliminated by adding ancillary services in power networks [41].
# TransECA-Net: A Transformer-Based Model for Encrypted Traffic Classification
## 3 Methodology
### Transformer
However, the Transformer, which does not rely on the state of the previous time step, can process the entire input sequence simultaneously. Regarding feature extraction, while LSTMs can extract temporal features, they may require additional mechanisms (such as attention) to highlight important features. By contrast, the Transformer's self-attention mechanism inherently identifies and emphasizes key features within the sequence. This is especially crucial in encrypted traffic classification, where the features are not always immediately apparent. As for model complexity, while the Transformer is more complex than the LSTM--due to its multiple layers of self-attention and feed-forward networks--it is more efficient in processing complex data. (See Table 1 for details). Finally, in the TransECA-Net model, the operation of the fully connected layers proceeds as follows: The output of the Transformer is flattened again, and three linear layers (fully connected layers) are used to make decisions for the classification task. This process includes dropout layers to reduce overfitting and ReLU activations to introduce non-linearity. The final output layer is responsible for predicting the class labels, with its dimensionality matching the number of target categories.
## 3 Results and Discussion
### Hole Taper  
Hole taper in degrees for all the drilled holes is shown in Figure 9. It can be seen that the taper decreases with increase in pulse length for both materials. No significant difference in hole taper between the two sheets can be recognized; in four cases, the holes drilled in the PBF sheet have higher tapering, and in three cases, the holes drilled in cold-rolled steel sheet have higher tapering. At its highest, the difference is 0.7 percentage units, but mostly it is much less than that.  
More interesting than the amount of taper is the shape of the tapering. Hole tapering in laser drilling has been reported many times, but it is almost always shaped like letter Y, i.e., the taper is not constant throughout. Instead, there is significant tapering close to the entry hole, after which the width of the hole stays mostly constant [32; 37]. Drilling experiments in this study resulted in almost perfectly conical holes, due to the technique that was employed. Based on these results, it is difficult to say what exactly causes the taper angle to increase so rapidly with the decrease in pulse length. It can be concluded that holes with well-defined edges, but with high tapering, can be achieved with drilling by engraving without special optics to tilt the laser beam.
## 4 Discussion
### Modulation of Rsm sRNAs Expression in Response to Nutrient-Poor Conditions  
The stimuli that activate the Gac-Rsm system are still unknown [57]. In this study, we demonstrated that _rsm_ genes are highly up-regulated under nutrient-poor conditions. Even if Rsm sRNAs are principally synthesized in the stationary phase, our results indicate that their expression is not only related to cellular density, but also and essentially to the physiological and metabolic state of cells. According to carbon source nature and availability, certain metabolites may accumulate within cells and induce specific responses. In _P. protegens_ CHA0, pools of 2-oxoglutarate, succinate, and fumarate were shown to be positively correlated with the expression level of _rsm_ genes [58]. Moreover, the expression of Rsm sRNAs is attenuated in the double mutant _relA spoT_, for which ppGpp synthesis has been completely abolished [34]. Our data show an activation of (p)ppGpp synthesis in response to nutrient starvation, correlating well with an increase of the four Rsm sRNAs in _P. brassicacearum_ NFM421.  
Another signaling molecule, the cyclic-di-GMP second messenger, which modulates the transition from the planktonic to the biofilm state [59], was shown to be positively regulated by GacS-GacA system in _P. aeruginosa_[35,37]. More recently, [PERSON] et al. [36] showed that the QS system and polyketide antibiotic 2,4-DAPG production are regulated by c-di-GMP through RsmA and RsmE proteins in _P. fluorescens_ 2P24. Our work also suggests a connection between the Gac-Rsm cascade and the c-di-GMP signaling pathway in phytochemical _Pseudomonas_.  
Surprisingly, under circumstances that are not advantageous for _P. brassicacearum_ proliferation, such as when nutrients are depleted, bacteria favor the activation of _rsm_ expression and enhance their stability and increase (p)ppGpp and c-di-GMP intracellular levels. Consequently, production of certain secondary metabolites and biofilm formation might be enhanced, suggesting their importance in the adaptive response to environmental constraints.  
Based on the present results and those of previous studies [34,36], we propose a model according to which ppGpp as well as c-di-GMP are directly or indirectly positively regulated by GacS/GacA system under nutrient limitations conditions (Figure 7).