esa-sceva/satcom-chunk-collection huggingface dataset:
## 4 Discussion
Nevertheless, the color change score was not influenced by the surface treatment in the lithium disilicate material. Hence, it is indicated that the material in the polishing paste underwent interaction with the aging conditions and resulted in more differences in the color of zirconia samples. The findings of this review revealed that lithium disilicate samples demonstrated significantly greater translucency as compared to monolithic zirconia samples, which is in agreement with the outcomes of several other studies [61; 62; 63]. Although the transparency of monolithic zirconia was increased as compared to traditional zirconia owing to themodifications performed while the production stage, it is still not comparable with even traditional lithium disilicate at the same material thickness. The methodology-associated limitations of the included studies are important to recognize. First, most of the studies used zirconia from a single manufacturer. An amalgamation of varying shades and types of monolithic zirconia from multiple manufacturers is recommended since materials from different manufacturers may behave differently. Hence, it is recommended to use zirconia from multiple manufacturers in future experiments. Second, some studies performed aging for a limited time to simulate the clinical life of the prosthesis. Additionally, the aging process was performed only in water vapor and at standard temperatures. Further research should be performed over an extended period in the presence of different conditions, such as colored drinks, cigarettes, saliva, and different enzymes for a better reflection of clinical conditions. Third, 5 out of the 12 included studies did not assess the effect of translucency on the color of zirconia. It is recommended to incorporate translucency into the analysis and to investigate the color variations between different ceramic materials. Fourth, the in vitro studies permit standardization via the provision of a more precise estimate of the impact of material reduction alone on color stability in the absence of other potentially confounding variables, clinical studies are recommended for better reflection of the clinical setting of occlusal adjustments and restoration success based on the perception of patients. Moreover, most of the studies used zirconia with a similar yttria content. Zirconia with different yttria contents should be used in future investigations. Additionally, a few studies used one type of toothpaste with limited toothpushing strokes. Since toothpaste with a higher amount of radioactive dentin abrasion will result in more intense wear of the characterized stains, it is recommended to perform a greater number of toothbrush strokes in future studies to assess the impacts of longer periods of simulated toothpushing on the optical features of monolithic zirconia. Finally, enhancements in shade manufacturing and the optical characteristics of zirconia material are recommended to minimize the consequences of restoration failure and to ensure the long-lasting satisfaction of patients.
## 5 Conclusions  
The conclusion of this study can be summarized in the following key points:  
* This study demonstrates that utilizing a node-independent model for collision analysis of reinforced concrete barriers effectively eliminates the need for node sharing, reducing the time and complexity involved in the modeling process.
* The strength performance comparison between steel reinforcement and concrete revealed differences based on the presence of the bridge deck. Higher stress occurs over a larger area when the bridge deck is included, which is crucial for considering economic efficiency in the design process.
* The assessment of passenger impact severity using THIV and PHD indicators showed that the deformable model with the bridge deck provides more favorable results in terms of passenger safety. This suggests that including the bridge deck in the design may be more advantageous, particularly from an economic standpoint.
* In terms of vehicle stability post-collision, all three models produced similar results. This indicates that an approach assuming the barrier as a rigid body without considering the bridge deck and treating the barrier foundation as a fixed point may be practical. It suggests the potential to efficiently verify vehicle stability without complex modeling analyses.
* These findings provide important guidelines for the design and evaluation of reinforced concrete barriers. Future research should include additional experiments and analyses under various conditions to further validate these results.  
**Funding:** This research was funded by the Basic Science Research Program through the National Research Foundation of Korea, NRF-2020R1 IIA3061349.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.  
**Conflicts of Interest:** Author [PERSON] was employed by the company Korea National Railway. The remaining authors declare that the research was conducted in the absence of commercial or financial relationships that could be construed as a potential conflict of interest.
## 4 Advanced Strategies for eNO\({}_{3}\)R Toward Ammonia and Nitrogen
### Copper-Based Electrocatalyst for the eNO\({}_{3}\)R: A Case Study for Ammonia Production
#### 4.1.6 Copper-Based Transition Metal Oxide Composite  
Transition metal oxide composite electrodes, particularly those incorporating Cu, have shown promising electrocatalytic activity in nitrate reduction. For example, combining copper oxide (CuO) with cobalt oxide (Co\({}_{3}\)O\({}_{4}\)) on titanium (Ti) electrodes results in a dramatic increase in nitrate reduction efficiency, reaching nearly 100%. The unoccupied \(\pi\) * orbital and the unclosed d-orbital shells of CuO facilitate nitrate adsorption and its subsequent reduction to nitrites, accelerating the overall nitrate reduction process [174]. [PERSON] et al. [175] proposed a Ti/Cu\({}_{5}\)ZnO\({}_{x}\) composite electrode that offers more active sites for the degradation of intermediate nitrogen compounds, especially in alkaline solutions compared to Ti/CuO\({}_{x}\). The addition of zinc enhances the reduction in nitrite to nitrogen gas (N\({}_{2}\)), achieving reduction efficiencies comparable to those of precious metal catalysts like palladium [175]. The process of creating composite electrodes, including those involving copper, is complex and has a low success rate. This complexity limits their large-scale preparation and practical application.
# Multicell Interference Management in Device to Device Underlay Cellular Networks
###### Abstract  
In this paper, the problem of interference mitigation in a multicell Device to Device (D2D) underlay cellular network is addressed. In this type of network architectures, cellular users and D2D users share common Resource Blocks (RBs). Though such paradigms allow potential increase in the number of supported users, the latter comes at the cost of interference increase that in turn calls for the design of efficient interference mitigation methodologies. To treat this problem efficiently, we propose a two step approach, where the first step concerns the efficient RB allocation to the users and the second one the transmission power allocation. Specifically, the RB allocation problem is formulated as a bilateral symmetric interaction game. This assures the existence of a Nash Equilibrium (NE) point of the game, while a distributed algorithm, which converges to it, is devised. The power allocation problem is formulated as a linear programming problem per RB, and the equivalency between this problem and the total power minimization problem is shown. Finally, the operational effectiveness of the proposed approach is evaluated via numerical simulations, while its superiority against state of the art approaches existing in the recent literature is shown in terms of increased number of supported users, interference reduction and power minimization.  
Keywords:interference management; resource allocation; power control; multicell device to device underlay networks; game theory; linear programming +
Footnote †: journal:  
_Future Internet_
## 5 Open Issues and Challenges  
### System Throughput  
System throughput, which is the most important factor to evaluate system performance, is related to data rate and packet delivery ratio. The higher the system throughput is, the more reliable communication will be in any scenario. Mobile and high-density WBASNs adversely affect bandwidth utilization. Because one application of WBASNs is healthcare service in which each sensor conveys vital signals from a human body to the service center, signal loss may result in a dangerous situation for patients. Therefore, the first requirement of any mitigation scheme is to maximize system throughput.
# MEC Server Sleep Strategy for Energy Efficient Operation of an MEC System
## 5 Performance Evaluation  
In this section, we verify the proposed method via simulation studies. We compare the performance of our method with that of a conventional method using the LSTM model as a task arrival rate predictor.
# A Cross-Layer Optimized Opportunistic Routing Scheme for Loss-and-Delay Sensitive WSNs
## 6 Performance Analysis and Comparison
### Performance Comparison of COOR(R) and COOR(P) Strategy  
Based on the above experimental results, both the COOR(R) strategy and COOR(P) strategy achieve great improvements to the base approach. Meanwhile, it can be observed that the former method provides a more reliable communication while the latter one focuses more on achieving low latency. Therefore, in practical applications, the COOR(R) strategy is more favorable in loss  
Figure 21: **(a)** Energy consumption of node under \(r=\)60, \(N=2\); **(b)** Energy consumption of node under \(r=70\), \(N=3\); **(c)** Energy consumption of node under \(r=80\), \(N=4\); **(d)** Energy consumption of node under \(r=90\), \(N=4\).  
Figure 22: The effect of different initial transmission powers on energy consumption.  
sensitive networks, especially when the reliability is the primary requirement and a certain delay can be tolerated. On the other hand, when the hypothetical scenario is delay sensitive or there is a strong need for real-time data, the COOR(P) strategy is more sensible.  
For a more intuitive presentation of the different focus of the two approaches, some typical and practical examples are given in the Table 3.
## 2 Materials and Methods
### Satellite Data and Image Processing
#### 2.4.3 Random Forest (RF) Algorithm for Carrot Yield Prediction  
A geodatabase of processed S2 images, time-series VIs, and LCC layers were developed. The recorded GPS co-ordinates generated a shape file of 90 sampling plots. Temporal changes in the spectral reflectance of carrot plants across the growing season were assessed and categorized as per the carrot growth stage. SNAP and ArcMap 10.8.1 were used to pre-process the data and build the models. Season-wise mean values of selected S2 bands, VIs, and LCC of each sampled location were extracted. Carrot crop monitoring and productivity zones of the three tested fields were assessed. As described in [PERSON] and [PERSON] [30], based on the phenology information (15, 30, 45, 60, 75, 90, 105, and 120 DAP), datasets were assessed. Due to cloud and haze coverage, and lack of availability of S2 images, the study ensured that at least one S2 image for each phenology stage. Subsequently, the interpolation was performed using the RF algorithm for spatial variation in crop development and yield was assessed at the field scale for productivity zones using a machine-learning-based regression tool of SNAP software (Figure 2). In recent years, various ML models have been developed to classify satellite images using large volumes of datasets. Random forest (RF), a popular ML approach, uses many subclasses to classify data subsets that are randomly picked from the input data [55].  
An RF algorithm is a supervised ML algorithm that is widely used for classification and regression problems in image analysis. The decision trees in the RF algorithm are the subclass classifiers. The RF procedure was performed in four steps, namely, (i) data preparation; (ii) model training with the use of Random Forest Classifier in SNAP software construction; training of carrot fields including variation in yield; (iii) averaging and voting of data by the decision tree; and (iv) selection of voting results and final prediction based on the bagging, meaning that the results so based on majority voting and model validation. The class with the most votes among the trees is introduced as the prediction output, and voting takes place among all of the trees' predictions [56].  
In this study, ML algorithms are driven to capture nonlinear relationships between the inputs (i.e., VIs, LCCs, etc.), and outputs (biophysical properties) through training datasets. The predictors used for the RF algorithm were ranked. These rankings were developed based on Pearson's correlation coefficients, which were initially estimated to verify the association between carrot yield (Y\({}_{\text{A}}\)) and Sentinel-2 bands (2, 3, 4, and 8A), vegetation indices (VIs), and SPAD values (i.e., LCCs). During the RF algorithm evaluation, five different categories of models were established based on the following: (a) S2 bands, (b) VIs, (c) a combination of S2 bands + VIs, (d) a combination of S2 bands + SPAD readings, and (e) a combination of S2 bands + VIs + SPAD values with correlation coefficient > 0.70).
## 4 Experimental Results of Active Localization in a Reverberant Environment  
This section presents the experimental results to verify the proposed method.  
In Section 2.4, we confirmed the feasibility of the proposed approach in an anechoic chamber, that is, the concept of detecting the position of a person or an object through a reflected sound. The results of an anechoic chamber indicated that there was no error in Equation (3). However, in an actual space in which reverberation exists, an error occurs in Equation (3). Therefore, the conditions under which the active localization method can operate in the reverberation space are identified in Section 3.  
We used Equations (22) and (23) to predict whether the active localization method would function in a classroom, and we describe the experimental results using the proposed method to estimate the position of a PVC pipe and a person.
## 1 Introduction
The dual-line approximation method, a robust algorithm specifically designed to counteract signal jitter near the zero-crossing, which conventional methods fail to handle effectively under high sampling frequencies. 2. The synchronous sampling method, which, for the first time to our knowledge, combines the differential measurement principle with a time-domain reconstruction technique to actively cancel runout-induced errors in torsional vibration signals, avoiding the feature loss associated with filtering. This integrated approach offers a practical, high-fidelity, and non-invasive solution, which is particularly valuable for large-bore, low-to-medium-speed diesel engines used in marine propulsion and power generation, where torsional vibrations are a major concern.
# FBG-Based Monitoring of Geohazards: Current Status and Trends
## 4 Current Status of Applying FBG Systems for Geohazard Monitoring
### Slope Stability and Landslide Monitoring
#### 4.1.3 Forecasting and Early Warning of Landslides  
Landslide warning is of great significance in mountainous regions where people live directly located below slopes. Time-estimation and location-determination of an impending collapse are two fundamental parts of a landslide prediction program. As pointed out by [PERSON] et al. for a road situated below a potential landslide, a sensing system should be able to predict the landslide at least 1 to 2 h in advance of the occurrence [7]. They reported an FOS system for displacement monitoring and collapse prediction in several landslide sites in Japan. In these studies, the FBG technology was combined with BOTDR and Macro Distortion Monitor (MDM). The results show that the FBG sensors detected the abnormal strain variations 2 h before the slope collapsed.  
In China, [PERSON] et al. investigated the feasibility of predicting landslides based on the monitoring data of FBG-instrumented rods [71]. Soft and hard rods were buried in the slope mass and an artificial landslide was triggered by manual excavation. The test results indicate that, to make the measurements sensitive, it is important to optimize the installation locations of the sensors.  
The setting of appropriate warning and alarm threshold values is another open issue for landslides warning. The development of accurate FBG systems makes it possbile to sense minute deformations.  
Figure 8: Monitoring results of slope movements (adapted from [15]).  
However, it is still a challenge to establish a forecasting model and to determine alarm trigger conditions based on the FBG monitoring results. In this aspect, a pilot study was conducted by [PERSON] et al. [72]. Through physical and numerical modeling, they investigated the feasibility of slope stability evaluation for locally loaded slopes based on strain measurements. It is found that the strain distribution characteristics captured by FBG sensors are closely related to the propagation of plastic zones and the formation of critical slip surfaces. Taking into consideration the convenience of field instrumentation and monitoring sensitivity, the maximum strains at multiple elevations can be used as characteristic parameters for setting landslide warning threshold values.
## 1 Introduction
A wide variety of machine learning models are now in use in natural hazard research, including: artificial neural network (ANN) [39; 40], adaptive neuro-fuzzy inference system (ANFIS) [41; 42; 43; 44], support vector machine (SVM) [15; 45; 46], K-nearest neighbor (KNN) [47], logistic model tree (LMT) [48; 49], alternating decision tree (ADTree) [50; 51; 52; 53], random subspace (RS) [54], credal decision tree (CDT) [14], quantile regression (QR) [55], radial basis function (RBF) [56], stochastic gradient descent (SGD) [57]. classification and regression tree (CART) [58], 4J8 decision tree [59], reduced error pruning tree (REPTree) [61; 63], randomforest (RF) [64], naive bayes tree (NBT) [11; 15], bayesian logistic regression (BLR) [65], Fisher's linear discriminant function (FLDA) [66], bayes net (BN) [67], grey wolf optimizer (GWO) [68; 69], naive bayes (NB) [70]; naive Bayes tree (NBTree) [71; 72; 73], evidential belief function (EBF) [74], and kernel logistic regression (KLR) [75]. All machine learning algorithms must be tested and validated in landslide-prone areas to select those with the highest performance and prediction accuracy. Therefore, the main aim of this study is to compare the efficiency of BLR, SVM, and ADTree algorithms to landslide susceptibility along a road section using in Kurdistan province, Iran. BLR is an algorithm that is a combination of a base-based theory algorithm and a logistic regression function. However, the ADTree is a decision tree algorithm. Its performance on landslide modeling and susceptibility modeling has been earlier confirmed and suggested [51; 53; 76; 77; 78; 79]. Therefore, in this study, we aim to compare the performance of a functional-based algorithm, SVM, a bayes-based theory algorithm, BLR, with a decision tree-based algorithm, ADTree, for shallow landslide susceptibility modeling in the study area. SVM, in particular, can handle complex and non-linear datasets [35], and thus, is a robust benchmark model that has been successfully used in landslide susceptibility mapping. This study is a pioneering step in the application of advanced predictive machine learning algorithms in landslide susceptibility research in the study area Another objective is to check the ability of the BLR and ADTree algorithm as the benchmark models, such as the SVM in landslide susceptibility mapping.
## 2 Experiment I: Directivity-Controlled Auditory Distance in Auralized Rooms
### Influence of Beampattern Design  
Figure 4 shows a detailed analysis of the auditory distance for the beampatterns \(A_{1\ldots 7}\), \(B_{1\ldots 7}\), and \(C_{1\ldots 7}\) according to Table 1 and Figure 1, based on the responses to the sets \(1\ldots 3\), \(4\ldots 6\), and \(7\ldots 9\) of Table 3, using all signals \(S_{1\ldots 3}\) and the room \(R_{1}\). The direct comparability of all curves in Figure 4 is feasible as all designs were determined to include reference patterns corresponding to a 3 rd-order beam facing to (\(A_{1}=B_{1}=C_{1}\)) and off (\(A_{7}=B_{7}=C_{7}\)) the listening position, respectively. This allowed to linearly re-map the responses gathered in the sets \(1\ldots 9\) to fill out the entire interval \([0;1]\) for each listener. Figure 4 shows the medians and the corresponding 95% confidence intervals.  
Both designs \(A\) and \(B\) yield monotonic curves. A pairwise analysis of variance (ANOVA) of the data pooled over all signals reveals the beampattern to be significant factor (\(p\ll 0.01\)) for \(A_{1\ldots 5}\). For the design \(B\), all directivities are (weakly) significant (\(B_{1\ldots 7}\), \(p<0.08\)).  
A comparison of the curve obtained for \(A_{2,4,6}\) to the results of [PERSON] [8], reveals a similar linear mapping to auditory distance.  
By contrast, the curve obtained for \(C_{1\ldots 7}\) is not monotonic in the proposed sequence. If we compare strength and angle of direct sound and specular reflections arriving at the listener for directivities \(C_{4}\) and \(C_{7}\), cf. Figure 5, we see more energy coming from lateral directions for \(C_{4}\). The more diffuse sound field explains the significantly greater auditory distance (\(p\leq 0.04\)) for \(C_{2\ldots 6}\) compared to \(C_{7}\).  
Figure 4: Medians and corresponding 95% confidence intervals for all beampattern designs \(A\), \(B\), and \(C\), pooled over all signals and normalized individually on directivities indicated by 1 and 7.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Set No.** & **Design** & **Index** & **Signal** & **Room** & **Reverb. Level** \\ \hline
1 & \(A\) & \(1\ldots 7\) & \(S_{1}\) & \(R_{1}\) & 0 \\
2 & \(A\) & \(1\ldots 7\) & \(S_{2}\) & \(R_{1}\) & 0 \\
3 & \(A\) & \(1\ldots 7\) & \(S_{3}\) & \(R_{1}\)  
For conditions with more energy coming from lateral directions, e.g., \(C_{3\ldots 6}\), major intersubjective differences are found affecting the size of respective 95% confidence intervals. Therefore we conclude that these conditions lead to an ambiguous distance percept.
## 1 Introduction
Some protocols give the highest priority to the reliability of the network, whereas, some give top priority to the network lifetime, that is, energy efficiency. The next sections of the paper survey few prominent routing protocols of UWSN and analyze those based on the mentioned factors and metrics. Section 2 describes the applications of UWSN, the communication mediums, network architecture, localization and reliability of the UWSN. Some of the important routing protocols of UWSN and their architectures, working procedures, advantages and drawbacks are presented in Section 3. Section 4 summarizes the evaluation process and depicts the evaluation of the considered schemes in tabular formats. The manuscript is concluded in Section 5.