esa-sceva/satcom-chunk-collection huggingface dataset:
## 2 Materials and Methods
### Design and Method  
The study evaluated the preparations of 37 dental students performing Class I amalgam cavity preparation on the mandibular left first molar as part of a complete dentition oriented in a dental mannequin head (Columbia, Dentalez, Malvern, PA, USA model AH-1-BP).  
All participants performed three Class I amalgam cavity preparations on multicolored 3D-printed teeth, after undergoing a half-hour didactic lecture regarding the concept of doing so using the unique, 3D-printed, multicolored oriented teeth. Twelve participants were also randomly selected to perform the same task on two conventional plastic teeth. All preparations were performed using a micromotor handpiece (NSK, Tokyo, Japan) and straight fissure bur (330 bur, Strauss, Palm coast, FL, USA) according to the accepted preparation parameters. Participants were seated during the procedure and made use of a unit light source to simulate the actual clinical environment.  
All cavity preparations were evaluated blind by two independent examiners using an explorer hand instrument without magnification; they were provided a checklist with specific criteria to result in standardized data for analysis (Appendix A). Both instructors are instructors in the operative course at the phantom laboratory. Examiners 1 and 2 have 7 and 3 years of experience as clinical instructors, respectively, although both were 10 years post-graduation.  
Each preparation was initially evaluated using the prescribed checklist by each examiner; this procedure was performed a second time after 3 months under identical conditions. Examiners were blinded as to participant identity at all times.  
Performance evaluation was regimented using analytical evaluation methods (checklist and criteria). The criteria examined were: outlines of cavity preparation, proportion of cavity walls, cavity depth, line angles of the cavity, directionality of the gingival floor and axial walls, injury to adjacent tooth, and finish (Appendix A). Grades were on a continuous scale of 0-100, where the passing grade was 60. Measured success of tasks was judged by depth of cavity (0.2 mm inside the dentine-enamel junction, or 1.5 mm as measured from the depth of the central groove), a marginal configuration of 90\({}^{\circ}\), maintaining as much unprepared tooth structure as possible (preserving cusps and the marginal ridge), having pulpal and gingival walls perpendicular to occlusal planes, and maintaining round internal preparation angles.
## 5 Conclusions  
To summarize, the wide image output by the CMOS camera with a scanning mirror is simulated in this paper. The degradation law of high-resolution large-width imaging, interfered with by satellite random vibrations, is analyzed. The simulation result shows that the camera exposure time is extended when the payload attitude angle is increasing during dynamic imaging. Further, the degree of image distortion on the camera focal plane becomes larger at locations far away from the satellite nadir. The error of velocity, caused by random vibration, increases the shift amount of an image on the camera focal plane, which directly reduces the image quality. Therefore, the field of view (FOV) should be reasonably set, and the damping mechanism should be installed to obtain a high resolution large-width image.  
Conceptualization, L.J.; methodology, L.J.; software, L.J.; validation, [PERSON] ([PERSON]); formal analysis: [PERSON] and [PERSON]. ([PERSON]); investigation, [PERSON] ([PERSON]); resources, [PERSON]; data curation, [PERSON] ([PERSON]); writing--original draft preparation, [PERSON] ([PERSON]); writing--review and editing, [PERSON], [PERSON] ([PERSON]) and [PERSON]; visualization, [PERSON] ([PERSON]). All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (NSFC), grant number 62101071 and 62171430. This research was funded by the Natural Science Foundation of Jilin Province, grant number 20210101099 JC and 20210101186 JC.  
Not applicable.  
The authors would like to thank National Natural Science Foundation of China.  
The authors declare no conflict of interest.
## Appendix A System Dynamic Modeling and Motion Jacobian  
In the global inertial coordinates system \(XOY\), the geometric position relation of each part of the space robot system with respect to the origin can be expressed as the following:  
\[\left\{\begin{array}{l}\vspace  
Then the Lagrange function can be expressed as:  
\[L=T-V=T, \tag{10}\]  
Combined with the second Lagrange modeling method and Equation (10), the dynamics equation of a rigid space robot system with carrier position uncontrolled and attitude controlled can be derived as:  
\[\mathbf{D}(\mathbf{q})\ddot{\mathbf{q}}+\mathbf{H}\big{(}\mathbf{q},\dot{\mathbf{q}}\big{)}\dot{\mathbf{q}}= \tau+\tau_{d}, \tag{11}\]  
The kinetic equation satisfies the following:  
**Property A1.**\(\mathbf{D}(\mathbf{q})\), \(\mathbf{H}\big{(}\mathbf{q},\dot{\mathbf{q}}\big{)}\) are uniformly ultimate boundedness.  
\[D_{\text{m}}\leq\mathbf{D}(\mathbf{q})\leq D_{\text{M}},H_{\text{m}}\leq\mathbf{H}\big{(} \mathbf{q},\dot{\mathbf{q}}\big{)}\leq H_{\text{M}},\]  
where \(D_{\text{m}},D_{\text{M}},H_{\text{m}}\), \(H_{\text{M}}\) are positive constant.  
**Property A2.**\(\dot{\mathbf{D}}(\mathbf{q})-2\mathbf{H}\big{(}\mathbf{q},\dot{\mathbf{q}}\big{)}\) satisfies the skew symmetry.  
\[z^{\text{T}}\Big{(}\dot{\mathbf{D}}(\mathbf{q})-2\mathbf{H}\big{(}\mathbf{q},\dot{\mathbf{q}} \big{)}\Big{)}\mathbf{z}=0,\forall\mathbf{z}\in\Re^{4\times 1}.\]  
**Assumption A1.**_The external disturbances and their derivatives are bounded._  
\[\|\tau_{d}\|\leq\Psi,\|\dot{\tau}_{d}\|\leq\Psi,\]  
_where \(\Psi\) and \(\Psi\) are positive constant._  
Considering the mission design requirements, the motion Jacobian relation of the point 't' on the end replaceable instrument relative to the origin \(O^{\prime}\) in \(X^{\prime}O^{\prime}Y^{\prime}\) needs to be studied. When the vector \({r_{t}}^{\prime}\) is projected within the coordinate system \(X^{\prime}O^{\prime}Y^{\prime}\), we have:  
\[\left\{\begin{array}{l}{x_{t}}^{\prime}=L_{1}\cos(q_{1})+L_{2}\cos(q_{1}+q_ {2})+L_{3t}\cos(q_{1}+q_{2}+q_{3})\\ {y_{t}}^{\prime}=L_{1}\sin(q_{1})+L_{2}\sin(q_{1}+q_{2})+L_{3t}\sin(q_{1}+q_{2 }+q_{3})\end{array}\right., \tag{12}\]  
where \(L_{3t}=L_{3}+L_{t}\) indicates the length of space robot arm \(B_{3}\) when being attached with end replaceable instrument \(B_{t}\).  
In coordinate system \(X^{\prime}O^{\prime}Y^{\prime}\), the attitude of the end replaceable instrument is in line with \(B_{3}\), then we have:  
\[\left\{\begin{array}{l}q_{t}=q_{1}+q_{2}+q_{3}\\ \dot{q}_{t}=\dot{q}_{1}+\dot{q}_{2}+\dot{q}_{3}\end{array}\right., \tag{13}\]  
The Jacobian relation of the relative motion of the end point of the end replaceable instrument is obtained by taking the time derivative of Equation (12), then we have:  
\[\dot{\mathbf{X}}_{t}=\mathbf{J}_{t}\dot{q}_{t}. \tag{14}\]
# Potential Synergistic Inhibition of _Enterococcus faecalis_ by Essential Oils and Antibiotics
## 2 Materials and Methods  
### Essential Oils and Antibiotics  
Cinnamon (Cinnamom Zeylanicum; bark) and clove (Eugenia Caryophyllus) essential oils (EOs) were purchased from Now Pure Essential Oils (Bloomingdale, IL, USA). According to the GCNS data by the manufacturer, the main chemical component of the cinnamon and clove EOs was trans-cinnamaldehyde and eugenol, respectively. The EOs were diluted with DMSO (20% \(v/v\)) to make a stock concentration of 10% for the cinnamon (CN) and 50% for the clove (CL) EOs. For the experiments, the CN oil was further diluted with DMSO and tested at 10%, 5%, 2.5%, and 1.25%, and the CL oil was diluted and tested at 50% and 25% concentrations. These EO concentrations were chosen as they produced a zone of inhibition that was below the CLSI Intermediate Breakpoint for _Enterococcus_ spp. and when combined with an antibiotic would produce a zone of inhibition at or near the level of Intermediate Breakpoint [47].  
Two classes of antibiotics, a penicillin class (ampicillin) and aminoglycoside class (kanamycin, streptomycin, gentamicin), were tested in this study. The stock concentrations of the antibiotics were: Kanamycin 50 mg/mL, Streptomycin 50 mg/mL, Gentamicin30 mg/mL, and Ampicillin 100 mg/mL (Fisher Scientific, Waltham, MA, USA). For the experiments, the antibiotics were diluted with distilled water and tested at 10% (kanamycin 5 mg/mL, streptomycin 5 mg/mL, gentamicin 3 mg/mL, ampicillin 10 mg/mL) and at 5% (kanamycin 2.5 mg/mL, streptomycin 2.5 mg/mL, gentamicin 1.5 mg/mL, ampicillin 5 mg/mL) concentrations. These antibiotic concentrations were chosen as they produced a zone of inhibition that was below the CLSI Intermediate Breakpoint for _Enterococcus_ spp., and when combined with an EO would produce a zone of inhibition at or near the level of Intermediate Breakpoint.
## 5 Numerical Simulation of Core Discing Mechanism Considering Drilling Pressure
In numerical simulation tests 3, 4, and 5, the maximum tensile stresses of the complete core section at the core root are 31.13 MPa, 38.57 MPa and 50.64 MPa, respectively. The stresses at some points reach tensile strength, but the stress nephogram shows that the tensile failure zone is tiny, and no closed tensile failure zone is formed along the ring direction. The maximum tensile stresses of the discing core section at the core root are 50.40 MPa, 58.54 MPa, and 68.59 MPa, respectively, and tensile strength is reached. Moreover, the area where the stresses are greater than 20 MPa forms a closed ring on the core surface, indicating that tensile failure occurs along the ring direction. The numerical simulation and coring drilling tests can explain the core discing mechanism under low confining pressure well: Tensile failure is caused by the stress concentration of the bit at the core root. When the rotation speed is constant, the drilling rate is too fast and the rock in contact with the bit has not been broken in time, then the bit moves forward for a distance. In order to ensure the constant rotation speed and drilling rate, the bit torque and drilling pressure will increase to input more energy for rock breaking. The greater the drilling pressure and torque, the more significant the stress concentration effect at the  
Figure 15: Core surface normal stress distribution. (**a**) Simulation test 1; (**b**) Simulation test 2; (**c**) Simulation test 3; (**d**) Simulation test 4; (**e**) Simulation test 5; (**f**) Simulation test 6.  
bottom of the borehole, and a ring-shaped tensile stress zone is formed at the root of the core. With the continuous increase of drilling pressure and torque, the tensile stress on the core also increases. When the bit output energy exceeds a certain amount, the tensile stress of the core exceeds the rock tensile strength and the core breaks. With the occurrence of tensile failure, the energy inside the rock is dissipated to the outside, and the drilling pressure and torque are reduced. When the drilling depth reaches a certain level, the rock cuttings accumulate again, resulting in the increase of drilling pressure and torque, and the tensile failure of the core again. Two tensile failures form a core disc. Drilling pressure and torque increase and decrease repeatedly to form multiple core discs.
## 3 Results and Discussion
### MMRTG Emissivity Analysis
#### 3.3.1 Convective Heat Transfer  
\[\dot{Q_{ac}}=h_{amb}A_{b}(T_{b}-T_{a})\sim 1250.7\,\mathrm{W} \tag{4}\]  
\[h_{amb}=0.32 Re^{0.675}P^{0.4}(\frac{k}{l_{e}})\sim 3.47\,(\mathrm{W}/\mathrm{m}^{ 2}\mathrm{K}) \tag{5}\]  
where  
* \(\dot{Q_{ac}}\): convective heat transfer rate (W);
* \(h_{amb}\): convective heat transfer; coefficient of the ambient air (W/m\({}^{2}\)-K).
* \(A_{b}\): surface area of the body (m\({}^{2}\));\(T_{b}\): temperature of the body (K);
* \(T_{a}\): ambient temperature (K);
* \(h_{amb}\): convective heat transfer coefficient of the ambient air (W/m\({}^{2}\)-K);
* \(Re\): Reynolds number (dimensionless), a measure of the flow regime;
* \(Pr\): Prandtl number (dimensionless), a measure of the relative thickness of the thermal and velocity boundary layers;
* \(k\): thermal conductivity of the fluid (W/m\(\cdot\)K);
* \(l_{e}\): characteristic length (m).  
To calculate the Prandtl number, we can initially simplify by assuming that the Martian atmosphere consists solely of CO\({}_{2}\). However, based on actual atmospheric data, the specific heat capacity \(c_{p}\) will be set to \(7.4\times 10^{2}\) J/kg\(\cdot\)K. For the thermal conductivity \(k\), we will use a simplified value of 0.0163 W/m\(\cdot\)K.
## 3 Results
### 3.3. Seepage Behaviour of SLA Samples  
#### 3.3.1. Pore Size and Printing Resolution  
The porosity of rocks is typically low, with only certain types of rocks, such as sandstone [69], limestone [70], dolomite [71] and porous volcanic rocks [72] exhibiting porosity greater than 10%. Microscopic examination of Zigong sandstone reveals a relatively uniform pore size distribution, with pore diameters generally less than 180 um, most of which are less than 50 um. The actual printing accuracy may be lower due to deformations prior to solidification and mechanical disturbances such as motion inertia and printing head jitter.  
Figure 6: Comparison of the stress–strain curves and the corresponding cracking processes between the double-flawed moulded gypsum (left) and PP (right) specimens: (**a**) 45\({}^{\circ}\)–45\({}^{\circ}\), (**b**) 45\({}^{\circ}\)–75\({}^{\circ}\), and (**c**) 45\({}^{\circ}\)–105\({}^{\circ}\).  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Flaw Geometry**} & \multicolumn{2}{c}{**Moulded Gypsum**} & \multicolumn{2}{c}{**3 DP Gypsum**} \\ \cline{2-5}  & **UCS (MPa)** & **Failure Strain** & **UCS (MPa)** & **Failure Strain** \\ \hline
45\({}^{\circ}\)–45\({}^{\circ}\) & 28.1 & 0.68\% & 5.6 & 1.24\% \\
45\({}^{\circ}\)–75\({}^{\circ}\) & 25.9 & 0.71\% & 4.9 & 1.17\% \\
45\({}^{\circ}\)–105\({}^{\circ}\) & 27.1 & 0.75\% & 6.1 & 1.43\% \\ \hline \hline \end{tabular}
\end{table}
Table 3: Average mechanical properties of the moulded gypsum and the 3 DP specimens with double pre-existing flaws.  
Practical experience suggests that when the printed pore diameter is greater than 0.3 mm, it closely resembles the original model, while printed pore volumes become smaller than the model size when the pore diameter ranges from 0.1 mm to 0.3 mm. A pore size less than 0.1 mm results in significantly reduced or even complete filling of the printed pore. Consequently, the effective print pore size of current 3 DP technologies is approximately 0.3 mm. In addition, considering the chemical reaction with water, the PP sample is unsuitable for the research on permeability. Therefore, the present study uses the SLA method to replicate the pores with sizes larger than 0.1 mm to study the permeability behaviour.
## 4 Case Study
### Recognition Result
#### 4.2.2 Cold Wave Weather Recognition Under GAN Sample Generation  
After using GANs to generate 5000 cold wave samples and mixing these generated samples with the original training data, the total number of samples in the training set was expanded to 22,520. At the same time, the test set remains composed of original data, with 3504 samples. In this experiment, different classification models were used to train the augmented training set, and their classification performance was evaluated on the test set. The results are presented in Table 5. Through the generation and expansion of cold wave samples, the number of cold wave samples in the training set was significantly increased. Experimental results demonstrate that this method improves the recall rates of all six classification models to varying degrees. Among these models, the recall rate of the SVM model showed a notable improvement, rising to 0.7153, indicating that the recognition ability of the SVM model for real cold wave data has been substantially enhanced under this data augmentation approach.  
Using data generation techniques to augment cold wave samples not only enhances the classification model's ability to learn cold wave features but also significantly improves its recognition of cold wave events. This method effectively mitigates the classification bias caused by sample imbalance and reduces the poor recognition performance for some data categories due to insufficient samples. Overall, the data augmentation strategy, assisted by GANs, provides a practical solution for improving the performance of classification models in the context of small sample sizes and imbalanced data.
## 3 Results and Discussion
### Summary and Further Discussion  
In the present study, the alkali-activated slag system revealed a better Cl-binding capacity than the alkali-activated fly ash system after 7 days, although they had similar capacities at 7 days. In the alkali-activated slag system, Cl-hydrotalcite remarkably formed after 7 days compared to Cl-hydrocalumite, which has a similar structure with [PERSON]'s salt. Therefore, the chemical Cl-binding mechanism in the alkali-activated slag is considerably different from the hydrated portland cement system, of which the chemical Cl-binding mostly depends on [PERSON]'s salt.  
In the alkali-activated fly ash system, the Cl-bearing zeolites did not extensively form after 7 days as much as Cl-hydrotalcite in the alkali-activated slag system; however, zeolite X and Y were substantially synthesized after 7 days. Given that, in earlier studies [12; 13; 31], when no Cl was present, dominant crystalline zeolite phases in the alkali-activated fly ash system were mostly sodalite and chabazite rather than faiujasite, it is possible that the extensive formation of zeolite X and Y might suppress the formation Cl-bearing zeolites in this study, although a further study is required to understand the interactions between zeolite X/Y and Cl-bearing zeolites in the system.  
Regarding the pore structures, the alkali-activated slag system revealed both pore-size refinement and porosity reduction after 7 days, while the alkali-activated fly ash system had only pore-size refinement. Therefore, considering Cl-binding and pore structure, the alkali-activated slag system would have a better durability performance in seawater environments than the alkali-activated fly ash system.
## 4 Discussion
### CUI Rate Model with Corrosion Phases  
For further analysis, the combined input data for the CUI rate model was divided into several corrosion phases, as shown in Figure 8. Specifically, phase 0 shows a nearly straight line and is linear with a near-zero value. In this phase, the coating and insulation system was in a steady-state and act as a protection system successfully. However, at about 3 years of time elapsed, the protection system might have some trauma, such as the initial degradation of coating materials, slight damage to the insulation, or any other possibility that happens during operation or maintenance. This means that, as time elapsed, local substance reaction can occur unimpeded by the external transmission.  
Figure 7: Comparison of CUI rate model developed based on single type input (Field only and Experiment only) with combined data input (Combined Field and Experiment).  
Then, in phase 1 and phase 2, the model can be described in approximation, as an exponential linear relationship between the formation of corrosion and time. If the corrosion has been initiated earlier at the end of phase 0, both of these phases were controlled by the concentration of oxygen in the electrolyte substance. The corrosion rate was administrated by the rate of oxygen content in the chemical reaction, together with the corrosion product layer to the external surface.  
However, the linear function in phase 2 will have a higher slope compared to phase 1, as the rate of oxygen diffusion to the corroding surface was increased by time. After the corrosion yields took place on the external surface of the piping material (at the end of phase 2), oxygen flux will decay. During this period, the transition from phase 2 to phase 3, the function will be non-linear.  
During phase 3, the CUI rate is governed by the metabolic rate of a corrosion agent in the electrolyte. In general, the presence of other chemical substances in the electrolyte, which interact with the metal surface and corrosion, will promote an equilibrium steady-state for the corrosion rate. Thus, during phase 3, the CUI rate was linear as time elapsed.  
At the end of equilibrium steady-state in phase 3, the long term CUI rate data for phase 4 returned exponentially upward as in phase 1 and 2, but with a much greater slope. During this time, it is very dangerous to leave the pipe in service as the CUI rate might suddenly increase higher than expected. Thus, it is suggested that when piping enters phase 4, inspection is compulsory and proper maintenance, either repair or change is required.  
In summary, for this CUI rate model, phase 0 and phase 1 have a longer formation time of up to 3 years and 19 years, respectively. The formation of corrosion takes a longer time to initiate due to the initial protection by the coating and insulation system as the nature of CUI itself. Once this initial effect wears off, the effect of coating and insulation system as per the trend in phases 2 to 4 are likely to follow the pitting corrosion model, as discussed by [PERSON] [27].
# Gap Analysis of Ambient Electromagnetic Noise Measurements Stored in the ITU Data Banks
###### Abstract  
For any radio frequency (RF) sensor (receiver) to function optimally, the ambient noise field strength, converted to electrical power by the transducer (antenna), must be lower than the in-ternal noise of that sensor. Therefore, knowledge of the expected ambient noise level is essential for the design of sensors for earth observation, atmospheric research, radio astronomy or navigation. The International Telecommunication Union (ITU) provides a model that predicts ambient man-made noise levels, differentiated by frequency, origin and environment. This is entirely empirical model is based on data from the 1960's and 1970's. In recent years, 90,205 noise measurements have been collected to update the model. The analysis of that data set presented here is essential as it shows a pitfall to avoid: despite to size of the data set it is space over the parameter space, and unacceptable biases occur when a purely empirical model is based on them. The paper proposes another approach: to create a mathematical model based on physics that can be fine-tuned and validated using these collected measurements, without producing the biases. A revolutionary side effect of such a model would be the linking of two currently isolated domains, that of spectrum management and electromagnetic compatibility.  
ambient; electromagnetic noise; radio noise; man-made noise; EMC; measurement; ITU; Study Group 3; Recommendation ITU-R P.372; Recommendation ITU-R SM.1753
# Optimizing Sustainable Energy Transitions in Small Isolated Grids Using Multi-Criteria Approaches
## 2 The Electric System of El Hierro
### The Generation System
#### 2.2.1 The Diesel Generation Plant  
Electric power on the island of El Hierro has traditionally been supplied by fossil fuel-based generators, specifically small-scale diesel units. These units are located at the \"Llanos Blancos Thermal Power Plant\" in the municipality of Valverde [46]. There are 10 units with net power outputs ranging from 670 to 1900 kW and gross power outputs between 780 and 2000 kW, totaling a gross power of 14.91 MW and an effective electrical power of 13.04 MW. Over the last years, its net capacity factor (CF) has stayed at about 40%. Yearly electrical energy generation from fossil fuel units has been reduced from approximately 40 GWh prior to the commissioning of the Gorona plant to between 20 and 25 GWh thereafter (Figure 4) [24].