esa-sceva/satcom-chunk-collection huggingface dataset:
# Detection of Cavities from Dental Panoramic X-ray Images Using Nested U-Net Models
## 3 Results and Analysis
### Qualitative Validation  
Additionally, as displayed in Figure 10, we display a sample of the segmentation results using different nested U-Net models. It is notable that U-Net3+ [23] outperformed compared with other methods discussed in the literature [21,22]. This is because U-Net3+ improves its detection capabilities of objects and borders of interest by allowing the network to gather data at various resolutions.  
Figure 8: The performance results of U-Net 3+ in the training and validation sets. The dataset split to 80/10/10 for training and validation, respectively: (**a**) Loss function. (**b**) Intersection over the Union. (**c**) Dice coefficient. (**d**) Accuracy.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dataset** & **IoU** & **Dice** & **Accuracy** \\ \hline Training & 0.77 & 0.89 & 0.98 \\ \hline Validating & 0.77 & 0.90 & 0.98 \\ \hline Testing & 0.67 & 0.60 & 0.95 \\ \hline \hline \end{tabular}
\end{table}
Table 5: The best performance results of U-Net 3+ with a 60–40% validation size: 0.1 and augmentation for the training and validation and a 80–10–10% split for testing.  
As discussed earlier in Section 1, X-rays have many problems in the quality of acquisition, which caused difficulties in data training, especially the dental panoramic image. The panoramic radiograph contains shadows that are reflections of various structures and organs, such as the lips. It also contains dark spots such as spots in the roots. Those shadows and spots confused the training process and affected the model's performance. Additionally, the quality of panoramic X-rays is essential for accurately detecting cavities or any lesions. Some panoramic X-rays are poor quality, making it difficult to detect abnormal lesions. Figure 11 presents some examples of shadows and dark areas on panoramic X-rays.  
Figure 10: Samples of panoramic X-ray images from the IvisionLab dataset were used for the qualitative validation and comparison of the various U-Net shape models: (**a**) Original image. (**b**) Ground truth. (**c**) U-Net. (**d**) U-Net++. (**e**) U-Net3+.  
Figure 9: The best performance results of U-Net 3+ in the training and validation sets. The dataset was split to 60%/40% (training/validation) with validation size = 0.1: (**a**) Loss function. (**b**) Intersection over the Union. (**c**) Dice coefficient. (**d**) Accuracy.  
Usually, the dentist is familiar with these areas and can determine if this is a lesion or a fake spot. In contract, the deep learning models may fail to identify these issues.
# Piezoelectric Transformers: An Historical Review
## 1 Historical Introduction
### Late 1950s to Late 1960s: Clevite Corporation--Introduction of PZT to PT Technology  
Most of the work of the General Electric team on piezoelectric transformers during the 1950s-1960s was based on Barium Titanate, the only commercially available ferroelectric material at the time. This situation changed when, in 1954, [PERSON] recognized the importance of the morphotropic phase boundary in the Lead Zirconate Lead Titanate (PZT) family of ceramics [21; 22; 23]. Over the decade of the 1960s, [PERSON] was the head of the research center of the piezoelectric division at the then Clevite Corporation, Bedford, OH, USA, which later became known as Vernitron Corporation, and today is known as Morgan Ceramics. [PERSON]'s studies were followed by more detailed studies by [PERSON] (not a relative of [PERSON]), [PERSON], [PERSON] (all at Clevite Corporation) and others, which led to the evolution of the entire family of PZT piezoceramics. Over the decade of the 1960s, the group led by [PERSON], at Clevite Corporation, were unquestionably world leaders in this subject area [24; 25; 26].  
Briefly after the publication of Rosen work, [PERSON] and [PERSON], on behalf of the Clevite Companies, filled for the patent \"Piezoelectric Ceramic Resonator\" for use in voltage transformation [27]. Strictly speaking, this patent was addressed to the field of ceramic resonators, but the configurations presented in this patent have also been used for piezoelectric transformers. The topology presented by [PERSON] and [PERSON] consisted of a disc or plate polarized only in the thickness direction and with two separated electrodes representing the input from the output as illustrated in Figure 5.  
This topology has been extensively evaluated by many other researchers, not only for piezoelectric transformers but more extensively for ceramic filters and resonators. Perhaps the most appealing characteristic of this topology is the single polarization required for the full ceramic, so the electrodes shape can be obtained by partially etching the full electroded ceramic. In 1965, [PERSON] presented the equivalent circuit development for the radial modes of the unipoled disc-type configuration [28].  
Figure 5: Unipoled piezoelectric transformers by [PERSON] and [PERSON] [27].  
In 1972, [PERSON] patented one of the first specific applications for piezoelectric transformers as starter and ballast for gaseous discharge lamps [29]. In this patent, [PERSON] suggested a variety of configurations for piezoelectric transformers as shown in Figure 6. Among the different configurations, of special relevancy is the rectangular configuration having two sections with thickness polarization (Figure 6a). The configurations of Figure 6b,c correspond to the same topologies illustrated above in Figure 5 as introduced in the 1960 patent by [PERSON] and [PERSON].
## 3 Results and Discussion
### Modelled Wind Speeds During 2017  
Table 1 shows the mean, STD, RMSE and R for the measured and modelled wind speed for 2017. The average wind speed from measurements was 7.69 m/s, which is quite well represented by the WRF model, although D01 has a slightly higher value and D02-D04 slightly lower. The measured wind speed standard deviation is 4.62, while the modelled wind speeds are in the 3.4-4.2-range.  
Comparing measured wind speed with WRF results, the results from WRF clearly show a lower RMSE and higher R as we increase the horizontal resolution of the model from 27 km to 3 km in D01 to D03, respectively. The innermost mesoscale simulation for D04 with a 1 km resolution has a slightly higher RMSE than D03, as well as a similar R. This result corresponds well with earlier results for this measurement site [27], where a 3 km resolution showed better agreement between the measurement and model than 1 km.  
The normalised histograms for the measured and modelled wind speeds are shown in Figure 7. For wind speeds below the 90 th percentile, the model values show a tendency towards higher wind speeds. This can clearly be seen as the probability density is shifted to higher wind speed in the model results. For wind speeds above the 90 th percentile, on the other hand, the measured wind speeds have a tendency towards higher probability.  
\begin{table}
\begin{tabular}{l l l l l} \hline
**Time Series** & **Mean** & **STD** & **RMSE** & **R** \\ \hline Meas, 2017 & 7.69 & 4.62 & & \\ WRF D01 & 7.89 & 4.07 & 4.22 & 0.54 \\ WRF D02 & 7.41 & 3.79 & 3.92 & 0.58 \\ WRF D03 & 7.17 & 3.55 & 3.40 & 0.69 \\ WRF D04 & 7.23 & 3.53 & 3.74 & 0.68 \\ \hline \end{tabular}
\end{table}
Table 1: Mean, STD, RMSE and R for measured and modelled wind speeds for the year 2017.  
Figure 6: Wind speed (**left**) and direction (**right**) of 10 longest high-wind events at Fakken wind park. Red dashed line: 90 th percentage wind speed. Legend: Starting time of event.
## 3 Limitations  
To identify the genes and treatments linked to psoriasis, a literature search utilizing PubMed, Google Scholar, MEDLINE, and Web of Science was conducted with a keyword search for genetic susceptibility to psoriasis, genetics, psoriasis, psoriasis treatments, bi-ologies, and treatments linked to psoriasis. A total of 180 articles were screened by two independent reviewers. The articles that specifically discussed genes and treatment targeting gene products implicated in psoriasis were selected, for a total of thirty-seven articles. All other articles were excluded. Additionally, we screened the reference sections of all included studies. The results included narrative reviews, systematic reviews, editorial letters, and meta-analyses. In this literature review, we identify genes associated with the inflammatory mediators present in psoriasis and classify existing treatment options as (1) treatments that directly target a gene product and (2) treatments that target factors secondarily related to a gene product.  
This review has limitations that should be acknowledged. First, the lack of standardized approaches for studying the genetic variants associated with psoriasis complicates the comparison of findings across different studies. Furthermore, the functional implications of the identified genetic variants and their precise mechanisms of action remain unclear, as collecting prospective data would be challenging. Finally, while this review discusses potential gene targets for therapy, it is important to recognize that translating genetic findings into effective treatments can often be complex. These limitations underscore the need for more robust and standardized methodologies in genetic studies of psoriasis.
# Effect of Buildings on the Radiation Characteristics of MF Broadcast Antennas
## 3 Results  
The results presented herein focus on the radiation patterns of the monopole and the array in the presence of buildings; all the diagrams include the radiation pattern of the corresponding antenna in free space, for the sake of comparison. It was found that the radiation pattern, among other antenna characteristics, such as the gain and the voltage standing wave ratio (VSWR), were particularly influenced by antenna blockages, not only at the HF band [2], but also at much higher frequencies [3; 4; 5].  
Figure 3: (**a**) Horizontal and (**b**) vertical cross-section of the configuration depicted in Figure 2.  
The radiation patterns plotted herein are actually a graphical representation of the magnitude of the far electric-field intensity of the antenna in polar coordinates. The magnitude of the far electric-field intensity in the presence of buildings resulted from the sum of the far-field in free space (i.e., Equation (5) for the monopole or (7) for the array) and the scattered field given by Equation (4). It should be noted that the corresponding radiation patterns in free space were plotted by using (only) Equation (5) or Equation (7) for the monopole and the array, respectively.
## 5 Radiometric Calibration Processing Results
### Response Energy and Calibration Constant Calculation  
In this study, the inner leg length of CR used is 1000 mm, and its theoretical RCS is calculated as [14]:  
\[\sigma_{refi}=10 lg\left(\frac{4\pi a^{4}}{3\lambda^{2}}\right) \tag{18}\]  
where \(\sigma_{refi}\) is the peak RCS of the trihedral CR in dB square meters (dBsm), \(a\) corresponds to the edge length of the corner reflector, \(\lambda\) represents the wavelength of the C-SAR/01, which is 0.055517 m. Thus, the theoretical RCS of the corner reflector can be calculated as 31.332 dBsm. The impulse response energy of each point target was calculated using the peak method and the sliding window-based integral method, respectively. Thereafter, the calibration constants of each point target were calculated according to Equation (6), obtaining the results shown in Tables 6 and 7. As shown in Table 6, for the UFS mode image, the average of response energy obtained by the sliding window-based integral method is 66.507 dB, and the mean value of the calibration constant is 32.092 dB, whereas the mean of response energy obtained by the peak method is 62.985 dB, and the mean value of the calibration constant is 28.57 dB. The standard deviation of the calibration constants calculated by the integral and peak methods are 0.233 and 0.342 dB, respectively. Figure 11a shows the distribution of the calibration constants for UFS data calculated by the peak and the sliding window-based integral method. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**CR Number**} & \multirow{2}{*}{
\begin{tabular}{c} **Theoretical RCS** \\ _(/dBsm)_ \\ \end{tabular} } & \multicolumn{2}{c}{**Integral Method**} & \multicolumn{2}{c}{**Peak Method**} \\ \cline{3-6}  & & \multicolumn{1}{c}{**Response**} & **Calibration** & **Response** & **Calibration** \\  & & **Energy (/dB)** & **Constant (/dB)** & **Energy (/dB)** & **Constant (/dB)** \\ \hline CR-1 & 31.332 & 65.988 & 31.565 & 62.56 & 28.138 \\ CR-2 & 31.332 & 66.655 & 32.246 & 63.603 & 29.193 \\ CR-3 & 31.332 & 66.588 & 32.185 & 62.552 & 28.15 \\ CR-4 & 31.332 & 66.555 & 32.142 & 62.844 & 28.43 \\ CR-5 & 31.332 & 66.606 & 32.195 & 63.08 & 28.669 \\ CR-6 & 31.332 & 66.419 & 31.8997 & 63.165 & 28.744 \\ CR-7 & 31.332 & 66.736 & 32.314 & 63.091 & 28.669 \\ Mean response energy/dB & & & 66.507 & & 62.985 \\ Mean calibration constants/dB & & & 32.092 & & 28.57 \\ Standard deviation of calibration & & & 0.234 & & 0.342 \\ constants/dB & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Response energy and calibration constant results of each point target for UFS mode data on 12 May. \begin{table}
\begin{tabular}{c c c} \hline \hline
**CR Number** & **UFS Data** & **FSI Data** \\ \hline CR-1 & 36.903 & 32.598 \\ \hline CR-2 & 38.181 & 33.866 \\ \hline CR-3 & 38.262 & 32.262 \\ \hline CR-4 & 37.398 & 34.88 \\ \hline CR-5 & 38.572 & 32.769 \\ \hline CR-6 & 37.678 & 32.109 \\ \hline CR-7 & 39.905 & 34.125 \\ \hline Mean & 38.128 & 33.230 Figure 11: Results of calibration constants based on automatic angle reflectors for (**a**) UFS mode data and (**b**) FSI mode data.
# Design Procedure for Motion Profiles with Sinusoidal Jerk for Vibration Reduction
## 4 Numerical Results
### Kinematic Comparative Study
By applying the algorithm from Section 3.3, the motion durations (\(T_{f}\)) corresponding to different conditions are computed. Specifically, if C1 is selected, then \(T_{f}\) = 1.3250 s; if C2 is selected, then \(T_{f}\) = 1.2922 s; and if C3 is selected, then \(T_{f}\) = 1.3048 s. Therefore, to minimize the motion duration, condition C2 is finally selected for parameter tuning to achieve the time-frequency-optimal sinusoidal jerk profile. The optimal solution is \(T_{1}\) = 0.1047 s, \(T_{2}\) = 0.1453 s, \(T_{3}\) = 0.5828 s, and \(J_{\max}\) = 0.1047 s, such that \(T_{1}\) + \(T_{2}\) is equal to two vibration periods (i.e., \(t_{2}\) = 2\(T_{d}\)). The total duration of the optimal profile (1.2922 s) is only 0.05 s longer than the original one (1.2422 s). For Case 2 shown in Figure 8, the maximum allowable velocity is not reached in the minimum-time profile because of the relatively short moving distance, and, accordingly, the constant velocity segment vanishes. In this case, the optimization procedure modifies \(T_{3}\) to satisfy condition C3, resulting in an optimal profile with seven segments. Similarly, in Case 3 depicted in Figure 9, the maximum allowable acceleration is not attained for the minimum profile due to the velocity limit, and thus the constant acceleration segment is absent. The application of the proposed optimization procedure on the time parameters leads to the optimal profile that satisfies condition C2. Finally, the minimum-time profile is composed of only sinusoidal jerk segments in the last case, as none of the kinematic bounds are attainable due to the limitation on the moving distance. With condition C3 selected, the original motion profile becomes a five-segment profile after tuning \(T_{3}\), as illustrated in Figure 10.  
The trapezoidal velocity and S-curve motion profiles generated with the same constraints are also shown in Figures 7-10 for comparison. The trapezoidal velocity profile exhibits infinite jerk due to acceleration discontinuities, while the S-curve profile effectively limits jerk but still experiences jerk discontinuities at segment switching times. Compared to the trapezoidal velocity and S-curve profiles, the sinusoidal jerk profile features better smoothness, ensuring continuous velocity, acceleration, and jerk. An associated trade-off with this smoothness improvement is a slight increase in the motion duration. However,  
Figure 10: Motion profiles resulting from different techniques in Case 4: (**a**) displacement; (**b**) velocity; (**c**) acceleration; (**d**) jerk. this increase in the motion duration is adequately compensated for by the shortened settling time, which will be clarified in the next subsection.
## 2 Methodology
### Slurry density
Colloidal rate  
The colloidal rate refers to the proportion of colloidal material in the slurry, reflecting the extent to which clay particles hydrate and disperse in water. It is an important indicator of the physical stability of the slurry. A higher colloidal rate means the slurry is less likely to segregate, resulting in a more uniform mixture and better physical stability. In this experiment, the colloidal rate was measured by pouring the mixed slurry into a graduated cylinder and allowing it to stand for one day [37]. The colloidal rate was determined by the percentage of the volume of the settled slurry at the bottom relative to the total volume of the original mixture. The relationship between the CMC solution content, the bentonite content, and the colloidal rate of the slurry is shown in Figure 4. It was found that as the content of the CMC solution and bentonite increased, the colloidal rate also increased. The colloidal rate increased approximately linearly with CMC solution content, whereas, with increasing bentonite content, the rate of increase slowed down. This is likely because the CMC solution, being a high-viscosity colloid, acts as an effective thickening agent, enhancing the slurry's viscosity and keeping the solid particles suspended, thereby consistently increasing the colloidal rate. Figure 3: Influence curves of slurry: (**a**) specific gravity; (**b**) viscosity. According to he \"Regulation for Vertical Drilling Construction and Acceptance\" (GB 51227-2017) [38], the general parameters for drilling slurry should meet the following requirements: a density of 1.15 g/cm\({}^{3}\) to 1.30 g/cm\({}^{3}\); a viscosity of 18 s to 30 s; a colloidal rate > 98%. Based on the experimental results above and in accordance with the standard, the selected slurry formulation and its characteristic parameters are shown in Table 6, where the bentonite content is 19.7% and the CMC solution content is 4.2%.
## 3 Results
### Position Accuracies in Y-Direction  
The judgments of position accuracy in Y-direction (vertical position) were assessed against the reference positions. The ANOVA result showed that the difference the VR displays caused to the vertical position estimation was not significant (F [1, 15] = 0.29, \(p<0.60\)), and the vertical position accuracies for HMDs and SWDs were, 0.90 and 0.91 respectively.  
The analysis of variance showed that the effect of both target distances (F [2, 30] = 5.42, \(p=0.01\)) and exocentric distance (F [1, 15] = 5.42, \(p<0.01\)) were significant, whereas the effect of size (F [1, 15] = 1.13, \(p=0.34\)) was not significant. The post-hoc analysis indicated that the exocentric distance accuracy ((Figure 6a) was significantly higher at 65 cm than at the 150 cm from the participant, where the exocentric distance accuracies were 0.92 (SD = 0.04), 0.92 (SD = 0.04), and 0.88 (SD = 0.05) for the target distances 65, 100, and 150 cm from the participant, respectively. Besides, the vertical position judgment accuracy was worsened as exocentric distance increase (Figure 6b). All the two-way interactions, three-way interactions, and the four-way interaction did not show a significant difference on the exocentric distance judgment accuracy.
## 3 Test and Analytical Methods
### X-Ray Diffraction Analysis (XRD)  
To ensure sample representativeness, uniform unadulterated specimens were oven-dried to remove moisture and prevent interference with XRD analysis. Solid aggregates were manually ground using a mortar and pestle and sieved to achieve homogeneity [26]. For amorphous content quantification, 20 wt% ZnO was added as an internal standard to the powdered samples. Mineral phase identification and compositional analysis were performed using MDI Jade 9.0 software. XRD experiments were conducted on a Cu K\(\alpha\) diffractometer (D8 Advance, Bruker, Germany) at 40 mA and 40 kV. Scans covered a 20 range of 5-80\({}^{\circ}\)with a step size of 0.02\({}^{\circ}\)[27].
## 4 Results
### Effect of Nozzle Configuration Under Different Ambient Pressures and Constant Inlet Pressure  
Figure 7 shows the influence of nozzle configuration on the rock erosion characteristics of the SC-CO\({}_{2}\) jet under four ambient pressures and constant inlet pressure. In this group of experiments, the inlet pressure was set constant as 40 MPa, and the fluid temperature was 330 K. The dimensionless standoff distance was increased from 1 to 10. The ambient pressure was sequentially increased from 2 to 26 MPa with the increment of 8 MPa.  
Figure 6: Effect of nozzle configuration on rock erosion volume of the supercritical carbon dioxide (SC-CO\({}_{2}\)) jet under different inlet pressures.  
As is depicted in Figure 7, on the whole the increasing ambient pressure reduces the maximum erosion volume of all the jets. This indicates a weakened intensity of rock erosion ability of the jets, which is attributed to the dramatic reduction of the pressure drop across the nozzles with the increasing ambient pressure, for less pressure energy could be transferred to the kinetic energy of the jets. Moreover, under the constant inlet pressure, the nozzle configuration has varying effects on the rock erosion ability of the SC-CO\({}_{2}\) jet at different ambient pressures. More specifically, compared with the convergent nozzle, the maximum increments of rock erosion volume caused by the Laval-1 nozzle are about 23.8%, 21.8%, and 13.1%, corresponding to ambient pressures of 2, 10, and 18 MPa, respectively; while those caused by the Laval-2 nozzle are about 53.4%, 49.2%, and 37.7%, respectively. For the ambient pressure of 26 MPa, curves of the Laval nozzles are always below that of the convergent nozzle, which indicates the weaker erosion action of these two nozzles compared with that of the convergent nozzle. In addition, it is obvious from Figure 9 that the jets of all the three nozzles have shorter optimal standoff distances at ambient pressure of 2 MPa than that at relatively high ambient pressure.