esa-sceva/satcom-chunk-collection huggingface dataset:
# Designing a C-ITS Communication Infrastructure for Traffic Signal Priority of Public Transport
## 3 Methodology and Results
### Communication Range
#### 3.1.5 Comparison and Results  
All intersections along the U5 track were examined using the radio propagation planning tool and, in critical cases, they were also examined by radio measurements. An evaluation of the signal strengths took place, including an evaluation of the communication ranges. Further radio measurements for verification were carried out at nodes where, according to the radio propagation planning tool, registrations points were not located or where they were only very close to the communication area. Additional validation of the radio propagation planning tool was carried out at other intersections. Thus, there were data sets for calibration as well as data sets for tool validation.  
In the concluding discussion, the entire state of radio propagation on the U5 was considered. The estimation by the radio propagation planning tool is shown on the left  
Figure 3: Communication ranges: scenario in the planning tool and comparison of real measurements.  
(prediction) in Figure 4. The tool calculated the complete environment of each RSU and, by contrast, measured each section for both graphs with identical color coding, providing a visual comparison of the two areas. In addition, it should be noted that the network of measured RSUs contained fewer transmitters/receivers than previously considered since only borderline cases should be secured in the reporting points. Nevertheless, the consistently high availability of radio coverage can be observed along the U5 corridor as yellow to orange hexagons. The coloring was based on the maximum determined level of the hexagonal zone, so in the case of two RSUs, the stronger RSU was taken into account. It is possible that the better-received RSU is not the one with the smallest distance. For this reason, the individual results for each RSU location were previously tabulated. Figure 4 shows the radio coverage of the route in this section, resulting from the radio propagation planning tool on the one hand and the on-site radio measurements on the other.  
Result 3:  
In summary, the traffic light locations were initially used to determine the RSU locations. In a further step, the registration points were located, and an overall picture of the radio coverage was created. No registration points outside of radio coverage were identified, nor were any that could only be served via RSU-hopping. Nevertheless, hopping is a possible method and thus a helpful redundancy at cell boundaries of C-ITS G5 coverage. The C-ITS service TSP can thus be implemented with the current response times of the traffic lights without having to make any adjustments to the controllers in the first step.
## Literature Review
### Artificial Neural Network Model  
Recently, forecasting the water surface elevation using the artificial neural network models was attempted to solve the problems in a physical or a numerical model. For instant, [PERSON] et al. [16] performed a short-term forecasting of the water surface elevation using the ANN model for the water surface elevation station in the Gamcheon Basin. [PERSON] et al. [17] constructed an ANN-based forecasting model in the river and reviewed the applicability of the model. [PERSON] et al. [18] verified the accuracy of the forecasting model by constructing an ANN model for the Mankam River in Indonesia and used tributary water surface elevation and tidal level to construct a real-time forecasting system. However, the ANN model did not consider the past data in learning the data. Thus, the recent research trend about forecasting water surface elevation using artificial neural network changed from ANN, recurrent neural network (RNN) models to long short-term memory (LSTM). [PERSON] and [PERSON] [19] confirmed that the RNN model derived effective real-time forecasting results by applying the RNN model to forecast the short-term discharge and reservoir level in Gondo aquifer, Burkina Faso. [PERSON] [20] used the Multi-Layer Neural Network (MNN) to forecast the tidal level in the Chao Phraya River estuary, Thailand, and generated a relationship curve between water surface elevation and discharge in the tidal stream by using the tidal level. [PERSON] et al. [21] forecasted the water surface elevation in Hangang River and compared the forecasting accuracy of each model by applying ANN, RNN and a nonlinear autoregressive network with the exogenous (NARX) model. Thus, they confirmed that the NARX neural network model was most suitable for forecasting water surface elevation by analyzing the error of the forecasting result. [PERSON] et al. [22] confirmed that the LSTM is superior to the previous feed-forward neural network (FFNN) model in predicting water surface elevation over a long-term period. [PERSON] and [PERSON] [23] used the RNN, RNN-BPTT, and LSTM to perform water surface elevation forecasting of the Trinity River in Texas, USA, and showed that the LSTM had a good performance for forecasting the water surface elevation. [PERSON] et al. [24] used the LSTM to forecast the upstream water surface elevation in the Geumgang river basin, Korea. The accurate forecasting was performed for the entire water surface elevation. However, the forecasting result was underestimated at a high water surface elevation. [PERSON] et al. [25] forecasted the water surface elevation of the Jamsu bridge in Hangang River, Korea, using the LSTM and confirmed that the forecasting accuracy of the model decreased as the forecasting leading time was longer. Through the sound results from the research mentioned above, the LSTM was chosen in this study. Furthermore, the hybrid activation function was proposed to resolve the underestimation at a high water surface elevation and improve the accuracy of forecasting in longer leading times.
## 4 Theoretical Analysis
### Search Failure Probability
#### 4.2.4 Functional Bloom Filter
Therefore, from Label (29)  
\[P(I)=\frac{1}{3}(P_{c,i})^{k}+\frac{2}{3}(P_{c,n})^{k}. \tag{34}\]  
\(\bullet\) False Positive Probability  
A false positive that results in a search failure can occur for input \(y\
otin S\) only. In other words, \(P(F_{P}|S)=0\), which means that inputs included in set \(S\) do not cause false positives. Therefore, the probability of false positives in a functional Bloom filter, \(P(F_{P})\), can be formulated as  
\[P(F_{P})=P(S^{c})P(F_{P}|S^{c}). \tag{35}\]  
We need to consider \(P(F_{P}|S^{c})\). Let \(P_{p,n}\) represent the positive probability for input \(y\) which is not in set \(S\) (\(y\
otin S\)). Consider a specific cell that is hashed by \(y\). If the specific cell was hashed by any element in \(S_{q}\) and it was not hashed by any other element in \(S-S_{q}\) in programming, then the specific cell has value \(q\) for \(1\leq q\leq Q\). The probability that the specific cell is not hashed by \(n-n^{\prime}\) elements in \(S-S_{q}\) with \(k\) hash functions is \((1-\frac{1}{m})^{k(n-n^{\prime})}\). \[P_{p,n}=\Big{(}1-(1-\frac{1}{m})^{k(n-n^{\prime})}\Big{)}(1-\frac{1}{m})^{k(n- n^{\prime})} \tag{36}\]  
The false positive event occurs when all of the cells other than conflict cells among \(k\) cells hashed by \(y\) have the same value. Note that there can be \(Q\) cases with equal probability for \(q=1,\ldots,Q\). \[P(F_{P}|S^{c})=Q\sum_{j=1}^{k}\binom{k}{j}(P_{p,n})^{j}\cdot(P_{c,n})^{k-j} \tag{37}\]  
For \(3n\) inputs, as \(P(S^{c})=\frac{2n}{3n}=\frac{2}{3}\), \(P(F_{P})\) is as follows. \[P(I)=P(S)P(I|S)+P(S^{c})P(I|S^{c}). \tag{29}\]0From Labels (28), (29), and (35), the search failure probability of a functional Bloom filter, \(P(F_{b})\), can be formulated as follows. \[P(I)=P(S)P(I|S)+P(S^{c})P(I|S^{c}). \tag{29}\]1 \[P(I)=P(S)P(I|S)+P(S^{c})P(I|S^{c}). \tag{29}\]2 \[P(I)=P(S)P(I|S)+P(S^{c})P(I|S^{c}). \tag{29}\]3 (40) \[P(I)=P(S)P(I|S)+P(S^{c})P(I|S^{c}). \tag{29}\]4  
We have an interesting question here of whether false positive or indeterminable is more harmful to raise search failure. While some of the indeterminables are caused by positive inputs, which are the elements included in the programming set, every false positive is caused by negative inputs, which are not included in the programming set. It has been recently shown that the indeterminables caused by positive inputs can be identified and resolved in the programming procedure by constructing an additional functional Bloom filter [46]. Therefore, false positives are more harmful to raise the search failures.
# Facile Fabrication of a Low-Cost
## 3 Results and Discussion
### Effect of Solution \(pH\)  
In order to investigate the effect of solution acidity on the adsorption performance of Alg-PAM, -100 mg of Alg-PAM adsorbent was added to 40 mL pH = 1, 2, 3, 4, 5, or 6 of Pb\({}^{2+}\) (0.1 mM) solution. After stirring for 24 hours and filtration, the concentration of Pb\({}^{2+}\) in the filtrate was measured by ICP-OES. The experimental results are shown in Figure 4. When the pH value of the solution is 1, Alg-PAM can only remove 17.7% of Pb\({}^{2+}\) in wastewater, which may be ascribed to the fact that the carboxyl and amino groups on Alg-PAM are protonated in the strongly acidic environment, thereby reducing the functional groups bound to Pb\({}^{2+}\)[23]. When the pH value of the solution is within the range of 3 to 6, Alg-PAM can remove more than 99.0% of Pb\({}^{2+}\) in wastewater. When the pH value of the solution exceeds 6, according to the solubility product rule, the Pb\({}^{2+}\) in the solution begins to form a Pb(OH)\({}_{2}\) precipitate. Therefore, the optimum pH value of the adsorbed solution ranges between 3  
Figure 3: (**A**) Digital photograph of Alg–PAM; (**B**) Scanning electron microscope (SEM) Image of Alg–PAM; and (**C**) partial enlargement of (**B**).  
Figure 2: X-ray photoelectron spectrometer (XPS) spectra of sodium alginate-polyacrylamideamide (Alg–PAM) (**a**) before and (**b**) after Pb\({}^{2+}\) adsorption.  
and 6. Within this range, neither the amino group nor the carboxyl group is protonated, and the Pb\({}^{2+}\) in the solution does not form a Pb(OH)\({}_{2}\) precipitate.
# Engine Fault Detection by Sound Analysis and Machine Learning
## 4 Results and Discussion
### Results for DWT-Based Features  
The performance of the vehicle fault diagnosis model using DWT-based features is evaluated and summarized in Table 6. Various configurations of DWT parameters, including the decomposition level and widely used wavelets such as db4, db8, db20, sym3, and sym8, were tested to identify the optimal settings [24; 40]. The table also presents the best hyperparameters found through Grid Search for the ELM classifier, such as the activation function and number of neurons, alongside the resulting precision, recall, F1-score, and accuracy metrics.  
Figure 5: Confusion matrix for 20 MFCC coefficients and window length of 0.02 s using MFCC-based features.  
From the table, it is clear that different combinations of DWT parameters and ELM hyperparameters result in varying levels of performance. The highest accuracy was achieved using a decomposition level of 3 and a _sym8_ wavelet with a _sine_ activation function, yielding a precision of 84.17%, recall of 83.60%, F1-score of 83.72%, and accuracy of 83.93%. This suggests that the choice of wavelet and decomposition level significantly influences the classification performance.  
The confusion matrix in Figure 6 provides further insights into the classification performance for the best configuration (decomposition level of 3 and sym8 wavelet). The model achieves high accuracy for electrical faults (93.5%) and front-end faults (91.7%), indicating strong performance in these categories. However, the model shows lower accuracy for spark plug faults (65.0%), suggesting that distinguishing spark plug faults from other fault types remains a challenge. Additionally, healthy cases are identified with an accuracy of 74.0%, indicating some misclassification into fault categories, which highlights an area for further improvement.  
Overall, the results of the experiments using DWT-based features demonstrate the effectiveness of the proposed method for fault diagnosis in vehicles. While the method shows strong performance in certain fault categories, it achieved lower performance overall compared to MFCC-based features. These findings provide insights into the optimal combination of DWT parameters and ELM hyperparameters and highlight areas for further optimization to enhance the performance of the method in future studies.  
\begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multicolumn{2}{c}{**DWT Parameters**} & \multicolumn{4}{c}{**Best ELM**} & \multicolumn{4}{c}{**Performance Results**} \\ \multicolumn{2}{c}{**Hyperparameters**} & \multicolumn{4}{c}{**Performance Results**} \\ \hline \multirow{2}{*}{**Level**} & \multirow{2}{*}{**Wavelet**} & **Activation** & **Number of** & \multirow{2}{*}{**Precision**} & \multirow{2}{*}{**Recall**} & **Macro** & **Weighted** & \multirow{2}{*}{**Accuracy**} \\  & & **Function** & & **Neurons** & & & & **F1-Score** & **F1-Score** & \\ \hline  
\hline \hline \end{tabular}
\end{table}
Table 6: Performance results for DWT-based features. The bold indicates the highest score.
## 1 Introduction  
In recent years, there has been an increase in patients needing aesthetic orthodontic treatment such as clear aligner therapy. The influence of traditional orthodontic appliances, such as brackets, on patients' aesthetic perceptions and quality of life has been widely studied. For example, [PERSON] and colleagues examined the orthodontic treatment need, types of brackets, and oral health-related quality of life, highlighting the importance of considering these factors in treatment planning [1].  
In addition to the aesthetic impact of orthodontic appliances, patients increasingly seek optimal aesthetic results by focusing on, for example, the incisor position and arch symmetry; therefore, the current orthodontic research focuses on improving the performance of clear aligners during orthodontic treatment, which is also associated with the use of mini-screws to address complex treatments in order to combine the aesthetic need during treatment and the need for an optimal aesthetic result [2, 3].  
In addition to the cosmetic aspect, the literature has also focused on the effects of aligner treatment on tooth structures by comparing it to conventional treatment with special attention paid to root resorption; some studies have shown minimal or insignificant differences in root resorption between the two treatment groups, while others have suggestedthat patients treated with clear aligners may have slightly lower levels of root resorption than those treated with fixed brackets [4; 5; 6; 7].  
The literature has also addressed the advantages of aligner removability. In fact, although the ability to remove the aligner is an advantage because it makes it less invasive for patients by allowing better oral hygiene than traditional fixed braces [8], it can also be a disadvantage because it requires patient cooperation [9].  
The performance of aligner therapy is related to aligner and attachment characteristics [10].  
To improve the performance of aligners in managing tooth movement, the use of attachments was introduced [11].  
Attachments are composite buttons that are transferred to the tooth surface using an adhesive technique through a template. They serve as a force transfer device from the aligner to the tooth, enhance retention, and improve specific tooth movements [11; 12].  
Attachments can have different designs, with various shapes and sizes, chosen according to the planned tooth movement. These supports are virtually placed and subsequently bonded on the tooth surfaces using specific placement templates [13; 14; 15].  
The clinical reproduction of the attachment shape is influenced by various clinical variables, such as the transfer template material [10; 16], the attachment construction material [17], and the type of polymerization [18].  
This study's aim is to propose a new technique for attachment reproduction. It involves the creation of attachments with 3D printing technology and the subsequent bonding of pre-made attachments with assisted clear templates. Moreover, this study aims to compare traditional attachment fabrication and the originally proposed technique in terms of the reproduction accuracy.
# The Role of Fungi in Food Production and Processing
## 2 Understanding the Research Prospects
### Mycotoxins and Food Safety
#### 2.5.2. Aflatoxin
Among all the known mycotoxin biosynthesis routes, the aflatoxin gene cluster is notable for having the greatest number of cytochromes P-450 [107].
## 2 Materials and Methods
### Tailored High-Harmonic Generation  
Besides being a well-established source for XUV spectroscopy and pump-probe experiments high-harmonic generation offers additional tunability and flexibility via tailoring the harmonics. One inherent feature of HHG is its strong dependence on the driving laser parameters (e.g., the cutoff law) and focusing geometry (phase matching), which make it sensitive for spatial and spectral pulse-shaping [26]. HHG in a hollow-core fiber has additional phase-matching conditions compared to a free-focus geometry [27], which offers enhancement or suppression of single harmonics (Figure 5).  
Figure 4: After spectral broadening laser pulses are sent through a prism compressor with a computer-controlled deformable mirror for pulse-shaping. These pulses are focused into an argon-filled capillary for high-harmonic generation. The XUV pulses are separated from the fundamental laser by aluminum foils and are sent either to an XUV spectrometer or to a metal surface that reflects the beam onto a Channeltron.  
In our experiments, we have used shaped XUV pulses from a hollow-core fiber to characterize the reflectivity of the surfaces with a tunable, broadband source with photon energies between 30 eV and 55 eV. Further details about the pulse-shaping device, computer-controlled optimizations, and the HHG in capillaries can be found in [23; 26; 28] (and references therein). For our experiments, we generated XUV spectra with different spectral widths and amplitude distributions for testing our measurement setup and data processing.
## 2 Materials and Methods
### In Vitro Antimicrobial Potential of Nanoparticles  
6.1 Determination of Antimicrobial Activity of ZnO Nanoparticles Loaded with _Lavandula pubescens_ Shoot Methanol Extract (50 and 100 mg) Using Agar Well Diffusion Technique  
The antimicrobial activities of the LPM, ZnO, and LP-ZnO NPs (50 and 100 mg extracts) were evaluated by the agar well diffusion method. After overnight incubation in nutrient broth, the bacterial suspension turbidity was adjusted to coincide with the 0.5 McFarland standards, followed by the inoculation of the bacteria on a Mueller-Hinton agar (MHA) plate using streaking techniques. To induce sporulation in the fungal strains, a 10-day culture in SDA at 28 \({}^{\circ}\)C was used. After submerging in a 5 mL aliquot of sterile 0.85% NaCl (_w/v_), the fungal colonies on the surface were mildly scraped with a sterile loop and transferred to a sterile tube. The fungal inoculum turbidity was standardized as before to obtain a fungal population of 10\({}^{6}\) CFU (colony-forming units). One milliliter of the fungal suspension previously inoculated was added to SDA and then swabed onto the surface of the media. Wells of a 6 mm diameter on the agar plates of bacterial and fungal cultures were made using a sterile cork-borer. Then, 7.5 mg of the tested LP-ZnO NPs were added to 1 mL of DMSO/deionized water, followed by sonication. The treating solution (7.5 mg/mL, _w/v_) was applied to the plate wells that had already been inoculated with the studied bacteria/fungi cultures. Augmentin and voriconazole (500 mg/mL) were used as controls (for bacteria and fungi, respectively). After that, the culture plates were left at 4 \({}^{\circ}\)C for one hour for the proper diffusion of the nanoparticles [32]. The plates were then incubated for 24 h at 37 \({}^{\circ}\)C for the bacteria, and for 7 days at 28 \({}^{\circ}\)C for the fungi. The antimicrobial activity was assessed following the incubation period by measuring the zone of inhibition. Every experiment was carried out twice.
## 3 Result Discussion
### Aerodynamic Comparison
The separation slowed down the pressure recovery and induced a pressure difference between the opposite sides, which contributed to the drag force of the device. Figure 8: Condition 3 surface and space streamline. Figure 10: Condition 5 surface and space streamline. Figure 9: Condition 4 surface and space streamline. As shown in Figure 6, the area of the high-pressure zone on the windward side of configuration 1 was large under operating conditions. It was mainly distributed in the lower half of the two observation windows and the windward side of the two ears. About 1/3 of the total drag was caused by the two ears. Reducing the windward area of the two ears is appropriate when ignoring other design constraints. For example, increasing the sweep angles of the two sides of the ears can reduce the drag during forward driving. Figure 6 shows three dominant eddies downward from the leeward side of configuration 1 under operating conditions. They formed a large recirculation zone near the leeward side of the ear and the leeward area at the upper part of the inlet and behind the inlet. Therefore, the resistance under condition 1 was large. When driving in the reverse direction (condition 2), a similar pressure distribution existed as when driving in the forward direction. The area of the high-pressure zone at the two ears was smaller than that in condition 1. The relative position of the separation point was behind, and the backflow zone at the leeward side was also smaller. Therefore, the total drag was considerably reduced by about 50% compared with the reduction in the total drag in the forward direction. The configuration 2 situation was similar to that of configuration 1, and the resistance under the two conditions was equivalent to that of configuration 1. The third configuration was clean and had no strong blocking effect when the ear drove forward. The resistance magnitude of forward and reverse driving was the same, and reverse driving was slightly slower than forward. The ear of configurations 1 and 2 was subjected to a large negative lift when driving in the forward direction (in modes 1 and 3, respectively). This was because the air separation occurred above the two ears, and the pressure was high, whereas the flow near the ears induced a lower pressure. The pressure difference produced about 0.27 (condition 1) and 0.22 (condition 3) downward resultant force coefficients on a single ear and a remarkable rolling moment. Thus, one must pay considerable attention to the strength of the connection between the ears and the body during the design stage.