esa-sceva/satcom-chunk-collection huggingface dataset:
# Navigation Safety on Shipping Routes during Construction
## 2 Literature Review  
### Analysis of Selected Navigational Channels  
In navigational channels and adjacent areas, various obstacles may take place and impact navigation safety. These obstacles may be constant or temporary; they influence the parameters of passages for ships and the need to assure additional precautionary measures for navigation in such places.  
Different natural obstacles take place in fjords and archipelagos, such as the Norwegian fjords, the Stockholm archipelago, and other similar places. These obstacles appear constantly and are related to natural conditions on the routes. Their occurrences influence the decrease in passage width. Therefore, ship navigations along these areas are performed considering the limitations dependent on natural conditions.  
Mentioned natural and constant navigational obstacles could be reduced with investments in infrastructure development. However, it should be noted that in some cases, the improvements are rather expensive and time consuming (e.g., may include excavations, dredging works, etc.). Sometimes, it is even impossible to provide changes in infrastructure due to environmental restrictions or other regulations.  
Temporary obstacles in navigational channels may deal with construction work or other activities performed on shipping routes that limit for some time the possibility of passing it according to previous regulations. The port gates renovation in Klaipeda port may be taken as an example of temporary navigational obstacles occurrence (Figure 1). During construction work conducted within the approach and inside the navigational channel, a decrease in the channel's width in some places was observed. Navigational obstacles changed with the progress of construction work, which was challenging for ship master planning sailing trajectories.  
In navigational channels or adjacent areas, construction work may be carried out using different equipment that also influences the temporary changes in the ship's passage parameters (Figure 2).  
It should be highlighted that construction work carried out within or close to navigational channels is usually short term. However, different restrictions are applied for ships passing through these places. These restrictions include speed limitations, possible maximum parameters of the ships, the need to use pilots and tug assistance, etc. Therefore, it is very important to find the best solutions to assure navigation safety in such areas that may be conducted, i.e., via the in-advance calculation of the ship's trajectory and the ship's sailing band in narrow passages in the case of acting hydro-metrological and hydrological conditions.  
Figure 1: Klaipeda port gates renovation process [10].
# Effects of Temperature on Growth and Isoprene Metabolism Pathway in _Eucomnia ulmoides_ [PERSON]
## 5 Conclusions  
In this study, we confirmed that temperature conditions significantly influence rubber synthesis in _E. ulmoides_. Specifically, treatment at 25 \({}^{\circ}\)C was found to be conducive to the growth of _E. ulmoides_ seedlings and rubber synthesis. Based on transcriptome and RT-qPCR results, our findings have led to the hypothesis that treatment at 35 \({}^{\circ}\)C upregulated the expression of _CLH_ in the chlorophyll degradation pathway, leading to a reduction in the chlorophyll content and weakening of photosynthesis. Additionally, in the isoprene pathway, upregulation of _GGPS_ and TPS genes, coupled with the downregulation of _FPS1_ and _GPS_, contributed to the diversion of IPP precursors toward the synthesis of terpen, such as monoterrenes, diterpenes, and sesquiterpenes. This also led to the increased synthesis of GGPP while reducing the amount of FPP, the initiator of rubber synthesis in _E. ulmoides_, resulting in a decline in rubber content at high temperatures. Therefore, to achieve a high yield of _E. ulmoides_ rubber, it is advisable to avoid HT conditions during cultivation. These results provide essential foundational data for understanding the regulatory mechanism of environmental factors in the biosynthesis of _E. ulmoides_ rubber.  
[PERSON] performed the experiment, analyzed the data, and wrote the initial draft of the paper. [PERSON] conceived and oversaw the project, supervising the experimental design, data analysis, and paper revision. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This work was supported by the Guizhou Academy of Agricultural Sciences Talent Special Project, grant number((2022)02 and (2023)02), the project of the Talent Office of Guizhou Province(grant number RCJD2018-14), and the Guizhou Province High-level Innovative Talents Cultivation Project, grant number((2016) 4003).  
**Data Availability Statement:** The _Eucommia ulmoides_ transcriptome database has been successfully uploaded to the NCBI database. All the data from this study can be find in the manuscript.  
**Conflicts of Interest:** The authors declare no conflict of interest.
# Video Streaming Adaptive QoS Routing with Resource Reservation (VQoSRR) Model for SDN Networks
## 3 The Proposed VQoSRR Framework
### The VQoSRR Reservation Method
#### 3.3.1. Reservation Policy Control Strategy  
The proposed policy mechanism calculates a weighted rate for each expected flow, then a portion of the total link rate is assigned based on this weight. The study considered employing the QoS thresholds and application service category (strict or soft constraints) as parameters to estimate the weight. The proposed policy defines QoS thresholds as ranges at the policy manager, then different applications' flows are grouped to one of these ranges by the administrator. Consequently, let \(FG_{x}\) be the aggregated flow group under a specific threshold range (\(\mathcal{TR}p_{j}\)), where \(1\leq j\leq n\), and \(p\) indicate the precedence of the \(\mathcal{TR}\) according to its \(FG\) quality requirements, whether they are high or low, so that the highest requirements take the first precedence, followed by the next highest, and so on.  
Moreover, assume \(FG_{x}\) belongs to one of three service categories: strict or hard QoS constraints, soft or tolerated QoS constraints, and the best effort category without any guarantees. So, let \(\mathcal{S}\in\{k,l,m\}\), \(k>l>m\), where \(\mathcal{S}\) is a parameter denoted to the service category. Additionally, assume that each threshold range and flow group take a degree of importance:  
* \(\mathcal{Y}\) importance factor of \(\mathcal{TR}\) of \(FG_{x}\).
* \(\mathcal{Z}\) importance factor of \(FG_{x}\).  
Figure 3: The main components of resource reservation approach.  
Based on the above assumptions, the objective is to calculate a weighted bandwidth rate (\(wr\)) for \(FG_{x}\) from the total link rate \(\mathcal{R}\) in according to the importance of their QoS constraints. Firstly, if the threshold range precedence is smaller than other threshold ranges, then the important factor of it (\(\mathcal{Y}\)) will be higher, which is formulated as follows:  
\[\left\{\begin{array}{c}if\ \text{min}\ \big{[}\mathcal{TR}p_{j}\ ^{FG_{1}}, \ \mathcal{TR}p_{j}\
_applied sciences_  
_Article_  
**Experimental Investigation and Validation on Suppressing the Unsteady Aerodynamic Force and Flow Structure of Single Box**  
**Girder by Trailing Edge Jets**  
**[PERSON] 1,2\({}^{\copyright}\) and [PERSON] 1,2,*(\({}^{\copyright}\))**  
1 Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology, Harbin Institute of Technology, Harbin 150090, China; [EMAIL_ADDRESS]  
2 Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin 150090, China  
*Correspondence: cvl_s00 hit.edu.cn  
**Abstract:** In the present investigation, a wind tunnel experiment was performed to evaluate the effectiveness of the trailing edge jets control scheme to mitigate the unsteady aerodynamic force and flow structure of a single box girder (SBG) model. The flow control scheme uses four isolated circular holes for forming the jet flow to modify the periodic vortex shedding behind the SBG model and then alleviate the fluctuation of the aerodynamic force acting on the test model. The Reynolds number is calculated as \(2.08\times 10^{4}\) based on the incoming velocity and the height of the test model. A digital pressure measurement system was utilized to obtain and record the surface pressure that was distributed around the SBG model. The surface pressure results show that the fluctuating amplitude of the aerodynamic forces was attenuated in the controlled case at a specific range of the non-dimensional jet momentum coefficient. The Strouhal number of the controlled case also deviates from that of the original SBG model. Except for the pressure measurement experiment, a high-resolution digital particle image velocimetry system was applied to investigate the detailed flow structure behind the SBG model to uncover the unsteady vortex motion process from the SBG model with and without the trailing edge jets flow control. As the jet flow blows into the wake, the alternating vortex shedding mode is switched into a symmetrical shedding mode and the width of the wake flow is narrowed. The proper orthogonal decomposition was used to identify the energy of the different modes and obtain its corresponding flow structures. Moreover, the linear stability analysis of the flow field behind the SBG model shows that the scheme of trailing edge jets can dramatically suppress the area of unsteady flow.  
**Keywords:** unsteady aerodynamic force; single box girder; Strouhal number; linear stability analysis
## 2 Materials and Methods
### Machine Learning Models
#### 2.2.1 Artificial Neural Networks  
Artificial neural networks (ANNs) aim to simulate and perform functional features similar to the biological neural network of the human brain. This provides the capability of learning relationships from examples, making them ideal for situations where there is no reliable relationship between input and output data [22]. ANN studies and applications differ and vary almost in every field of our lives and scientific fields such as economics [23] and neuroscience [24].  
Even though several neural network types exist in the literature, the backpropagation (BP) neural network is the most widely and commonly considered ANN because of its efficiency and simplicity. Essentially, ANN consists of an input layer, at least one hidden layer, and an output layer where the number of neurons (nodes) in the input and output layer depends on the problem domain [25]. The determination of hidden layer numbers and the neuron numbers of the corresponding layers is a challenging task, and still, trial and error is the most effective way to determine the neuron numbers. The neurons are interconnected through the layers, and the summation function (net function) is used to obtain the general knowledge for each neuron and input. The activation function, commonly a sigmoid one, provides the outputs of most informative neurons depending on the information level, and generally, the gradient-descent algorithm is applied for error minimization during the convergence. The weights are adjusted accordingly and propagated back iteratively to achieve minimum error and to provide efficient convergence.  
The equation of obtaining the output in ANN was described as shown in Equation (1) [26]:  
\[\hat{y}_{i}=f_{j}\left(\sum_{h-1}^{m}w_{jh}\times f_{h}\left(\sum_{i=1}^{n}w_{ hi}x_{i}+w_{hb}\right)+w_{jb}\right) \tag{1}\]  
where \(i\) represents the input layer, \(h\) represents the hidden layer, and \(j\) represents the output layer. Weights and bias are denoted as \(W\) and \(b\), respectively. \(X\) indicates the input value, and \(n\) and \(m\) stand for the number of input and output neurons, respectively.
# Blind Recognition of Frame Synchronization Based on Deep Learning
## 3 Test and Analysis
For example, ResNet-50 has approximately 25.6 million parameters and a computational complexity of about 4.1 billion floating point operations (FLOPs), whereas the complexity of the algorithm in reference [12] is approximately \(O(n)\), where \(n\) is the actual frame length. Given that blind recognition is always used in a non-cooperative communication scenario with higher BER and limited prior information, it is more reasonable to sacrifice computational complexity to achieve better recognition performance. The main purpose of this paper is to demonstrate that using neural networks for frame synchronization recognition can achieve good performance. Further we can focus on the complexity and recognition performance of the algorithm to obtain neural networks with low complexity and excellent performance. Figure 7: Comparison of joint recognition performance of frame length and frame synchronization code between BRFS-DL, references [12] ([PERSON], 2021), [13] ([PERSON], 2023) and [25] ([PERSON], 2020).
## 4 Simulation and Results Analysis  
Iridium, as a typical polar (\(\pi\)) constellation, is the first satellite constellation to implement global mobile communication by onboard processing technology, and it is often used in the communication performance simulation of low-orbit satellites. So, it is selected for simulation analysis. The parameters are summarized in Table 1[28]. The initial number of wavelength resources for the constellation is 16, the processing delay is 10 ms, and the threshold of transmission delay of request is 300 ms [29]. The simulation duration is 1200 s. The snapshot cycle is set to 1 min, and every time slot is 1 s [30]. The arrival of each request follows Poisson distribution, and the waiting time follows exponential distribution [31]. The destination user of the connection request is randomly selected from other users. The performance evaluation of the algorithm uses the blocking probability and wavelength utilization for comparison and analysis.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameters** & **Iridium** \\ \hline Configuration & \(\pi\) \\ Inclination, \(\theta\) & 86 \\ Number of satellites, \(N\) & 66 \\ Number of tracks, \(P\) & 6 \\ Number of satellites per orbit, \(S\) & 11 \\ Phase factor, \(F\) & 4 \\ Track height, \(H\) (km) & 780 \\ Orbital period (s) & 6027 \\ Inter satellite links & 2 intra/ 2 inter \\ ISLs connectivity & Non-permanent \\ \hline \hline \end{tabular}
\end{table}
Table 1: Iridium constellation parameters.
# Investigation of Debonding Effect in Internal Replacement Pipe System Under Lateral Loading
## 3 Surface Preparation and Its Impact on Debonding
### Continuous IRP System with Different Levels of Adhesive Strength  
This section presents an analysis of the deflection performance, debonding mode of the adhesive layer, fatigue life, and catastrophic failure of the continuous steel IRP system under deflection loading ranging from a fatigue load of 21.4 kN (4.8 kip) to a maximum of 71.2 kN (16 kip). The numerical findings indicate that the system remains intact, with no observed debonding or failure in both the adhesive and IRP layers across a range of shear strengths from 5 MPa (0.7 ksi) to 40 MPa (5.8 ksi), even when loaded up to a maximum of 71.2 kN (16 kip). Therefore, the continuous system exhibits better strength and significantly smaller deflection compared with the discontinuous ones due to the higher level of overall stiffness [16].
## 1 Introduction  
In principle, the simplest approach for making monolithic column involves the direct co-polymerization of functional monomers with crosslinkers in order to yield monolithic stationary phases with the desired functionalities. Although this direct approach may look at a first glance simple and can be readily achieved, the choice of porogens, polymerization temperature and other conditions still involve many trial and error to reach an optimum monolith. Therefore, time consuming and labor-intensive re-optimization of the polymerization conditions from one monolith to another is required to get a monolith with satisfactory chromatographic performances. In addition, polar and nonpolar functional monomers are not always directly and/or easily available and some monomers are incompatible with certain co-polymerization processes. As an alternative route of monolithic column preparation, post polymerization functionalization (PPF) of precursor monoliths allows the introduction of various polar and nonpolar ligands onto the monolithic surfaces starting from one generic and optimized template monolith. In that sense, PPF is an essential technique used to modify the monolithic surface chemistry for use in a variety of studies. Furthermore, the major advantage of using PPF is that a variety of columns with different retentive properties can be obtained from one generic optimized monolith matrix. So far, various PPF procedures have been described and demonstrated in the literature to yield separation performances in different separation methods, such as capillary electrochromatography (CEC), HPLC, capillary LC and nano-LC. Thus, it is the aim of this review article to summarize the various strategies in PPF of monoliths and demonstratesthat the PPF is an efficient process for fast development in stationary phases. In this review article, the different template monoliths which have been applied in PPF, will be divided into precursor monoliths with epoxy, succinimide, hydroxy, chloro and carboxy functionalities as well as those based on photografting, hypercrosslinking, incorporated nanoparticles and miscellaneous processes. The various PPF strategies performed on the different precursor monoliths have allowed the efficient separations of different analytes using a few original monoliths as the starting columns, which helped to save time and consumable.
# Groundwater Prediction Using Machine-Learning Tools
## 5 Performance Results and Discussion
### Performance Comparisons
Improvements in MAE and RMSE were less than 6.5%, and still fell short of the performance obtained with GMMs without parameter optimization. Figure 10 gives residual plots and \(R^{2}\) values for the best XGB+GMM (**a + i, j + t + s**) model and the best SVR model (**a + i, j + t**), superimposed on the untrained model residuals. Visually, XGB+GMM and SVR are giving predictions closer to the 45\({}^{\circ}\) line than the untrained regressor, while the \(R^{2}\) values  
Figure 8: Performance improvement of SVR versus the untrained previous month regressor. Figure 9: Example of an image prediction made with the model (XGB+GMM). are more than doubled. Figure 11 presents Regression Error Characteristics (REC) curves for the same three models. For XGB+GMM, 85% of pixel predictions have a deviation of 5 or less.
# A Survey on Intelligent-Reflecting-Surface-Assisted UAV Communications
###### Abstract  
Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that need to be addressed to realize IRS-assisted UAV communications systems.  
intelligent reflecting surface (IRS); unmanned aerial vehicle (UAV); spectral efficiency; energy efficiency; optimization +
Footnote †: journal: _Energies_  
0
Footnote 0: Copyright** © 2022 by the authors. Liconse MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([[https://creativecommons.org/licenses/by/](https://creativecommons.org/licenses/by/)]([https://creativecommons.org/licenses/by/](https://creativecommons.org/licenses/by/)) 4.0/).
## 4 Techniques Used in Academia to Improve Performance Metrics
### Mechanisms to Improve Reliability  
Reliability is an integral part of any industrial monitoring and control system as any slight degradation in communication can potentially result in complete system malfunction. The industrial environment may suffer from noise, internal interferences, multipath propagation, external interferences, collision, and physical obstruction. In order to ensure reliable wireless communication, various techniques are introduced to mitigate communication problems such as interference and weak signals. We discuss the mechanisms presented in academia for addressing the reliability requirement in an industrial automation environment, such as diversity, error control schemes, multipath routing, and network coding.
###### Abstract  
This report analyzes the different standard methods of quantity measurement, which, when applied in the processes of receiving and transferring fuel quantities, lead to discrepancies and accounting losses. Three main factors contribute to these discrepancies: unavoidable errors of measuring devices (calibration uncertainty ranging from 0.1 to 0.5% at best), systematic errors due to non-applied corrections during transactions, and systematic errors due to different regulations, which result in inconsistent conversion rules applied throughout the entire purchase-production-sales chain. Modeling of air buoyancy effects showed that neglecting buoyancy correction can lead to measurable and economically significant discrepancies, especially in large-scale operations. The mass of light petroleum products can be underestimated by up to 0.15%, potentially resulting in approximately $3 million in annual financial losses for a medium-sized refinery processing 10,000 tonnes per day. These findings underscore the necessity of applying buoyancy corrections for conventional weighing, especially for liquid petroleum products (LPP) measured in open systems. Conversely, for LPG weighed in closed, pressurized containers, a constant correction factor (0.99985) applies, but its economic impact is negligible. Therefore, the study recommends omitting this LPG correction unless contractually required, to streamline processes and reduce complexity. Achieving result comparability throughout the entire petroleum supply chain requires implementing uniform quantity calculation provisions using calibrated instruments and standardized methods under different conditions. This necessitates that all measurement results are traceable to reference conditions (mass in vacuum, volume at +15 \({}^{\circ}\)C). The proposed algorithms for oil mass and volume measurement and recalculation highlight the need for unified international regulations and a robust system.  
buoyancy; commercial transactions; liquefied petroleum products; mass in air; measurement losses; temperature correction factor; volumetric and geometric measurement method +
Footnote †: journal: Applied sciences